University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Investigating the Application of Artificial Intelligence Approaches for Studying the Impacts of Large-Scale Climate Drivers on Precipitation in Balochistan, Pakistan Investigating the Application of Artificial Intelligence Approaches for Studying the Impacts of Large-Scale Climate Drivers on Precipitation in Balochistan, Pakistan 1 20 26454 10.22108/gep.2022.132899.1497 FA Sapna Mohammad Tajbar PhD Candidate, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran Ali Mohammad Khorshiddoust Professor, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran 0000-0003-3020-7603 Saeed Jahanbakgsh Asl Professor, Department of Climatology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran Journal Article 2022 02 28 Abstract The Balochistan province of Pakistan is mostly affected by severe drought events due to little amount of precipitation. “Several Large Scale Climate Drivers (LSCDs) are known for their effects on precipitation worldwide but studies in the region are missing; a wide variety of LSCDs and lagged associative information”.The current study aimed to identify the significant LSCDs in the Balochistan province of Pakistan and improve the prediction skill of monthly precipitation by employing the Principal Component Analysis, Artificial Neural Network (ANN), Bayesian Regularization Neural Network (BRNN), and Multiple Regression (MR) Analysis using the 12 months lagged LSCDs such as Nino-1+2, Nino-3, Nino-3.4, Nino-4, QBO at 30 and 50hpa (QBOI and QBOII), Sea Surface Temperature (SST), 2m air temperature (T2M), 500hpa and 850hpa geopotential heights (H500 and H850), 500hpa zonal velocity (U500), 500hpa and 850hpa meridional velocity (V500 and V850), Latent and Sensible Heat Fluxes Over Land (LHFOL and SHFOL), and Surface Specific Humidity (SSH). To collect the data, Global Land Data Assimilation System, Tropical Rainfall Measuring Mission, MERRA-2, NOAA, Freie University Berlin, and HadISST datasets were used. The results of the study showed that significant LSCDs with a 99% confidence level were SSH, SST, LHFOL, SHFOL, T2M, U500, Nino-3.4, and Nino-4. During the test period, compared with MR models of 0.15 to 0.49 and principal components of -0.16 to 0.43, the ANN and BRNN models had better predictive skills with correlation coefficients of 0.40 to 0.74 and 0.34 to 0.70, respectively. It can be concluded that the ANN and BRNN models enable us to predict monthly precipitation in the Balochistan region with lagged LSCDs. Extended Abstract Introduction Pakistan is one of the most vulnerable countries due to climate change. According to the Global Climate Risk Index (GCRI) report, with the passage of time, its vulnerability is increasing. The main threats consist of a rise in temperature, irregular patterns of rainfall, a rise in the sea level, and extreme events such as droughts, floods, and heatwaves. Precipitation plays an important role in the economy of Pakistan as an agricultural country that has experienced variations, particularly in a recent couple of decades when a sharp jump in global atmospheric temperatures was noticed. The southern part of Pakistan which comprises the Sindh and Balochistan provinces has an arid climate and is mostly affected by severe drought events due to less amount of rainfall throughout the year as compared to other parts of the country. This study’s main focus is Balochistan province which has a long history of severe droughts and is an important province in terms of agriculture. Less than 250mm is the annual average rainfall received by the region. It is predicted that throughout the 21st century if adaptation measures are not taken, there will be a continuous increase in droughts and scarcity of water which will adversely affect the lives of people and the economy. Globally, precipitation and droughts are strongly linked with the large-scale climate drivers through atmospheric associations but there are no detailed studies in Balochistan province that consider a wide variety of large-scale climate drivers and their lagged association with precipitation. The main objective of the present study is to identify the significant large-scale climate drivers in the Balochistan province of Pakistan and improve the prediction skill of monthly precipitation by applying the principal component analysis, artificial neural network, Bayesian regularization neural network, and multiple regression analysis considering the lagged association of climate drivers. Methodology In the present study, first, large-scale climate drivers from NOAA HadISST, MERRA-2, and Freie University Berlin in NetCDF files were processed using the ArcGIS model builder along with the precipitation data from GLDAS and TRMM. The data were first normalized in the range of 0 and 1 using the min-max normalization formula. For showing the 12 months’ lagged association between the large-scale climate drivers and precipitation, a cross-correlation method was employed and the heatmaps were created in Origin 2021b software to show significant lagged correlations. Principal component analysis was applied and the variances and Eigenvalues for each of the components were calculated. Multi-layer feed-forward neural network with a back propagation algorithm was used for the prediction of monthly precipitation with the first two PCs in most cases, three and one in some cases as the predictors. Bayesian Regularization Neural Network (BRNN) was applied which is a version of Artificial Neural Networks (ANN) and is a more powerful method as compared to conventional ANN. MATLAB R2015a environment was used for this purpose. Then, Multiple Regression Analysis (MRA) was carried out and was used as a benchmark for comparing ANN and BRNN models using significantly lagged climate indices in one case and in another case the selected PCs. To validate the performance of all developed models, the TRMM dataset was used. Finally, time series graphs and Radar charts were prepared for comparison. Discussions The findings of cross-correlations between monthly precipitation and large-scale climate drivers in Balochistan province showed the most dominant climate drivers as surface specific humidity, sea surface temperature, latent and sensible heat fluxes over land, 500hpa zonal velocity, 2m air temperature, Nino-3.4 and Nino-4, and the highest correlations were noticed for surface specific humidity, sea surface temperature, latent and sensible heat fluxes over land, 500hpa zonal velocity, 2m air temperature. It is noteworthy that in each district, the lagged correlation of maximum climate indices with precipitation was distinct at distinct lags. The multiple regression best models were selected on the basis of no violation of the limits of statistical significance and lower errors. The MLR model’s performance was low in the region where some of the districts had low correlations. The results from ANN and BRNN models showed that the BRNN models were on a lower side than the ANN models with higher values of correlation coefficient showing their capability of finding the pattern and trend of the GLDAS precipitation. The results of the evaluation of the generalization capability of all models on the TRMM dataset showed that both ANN and BRNN models relatively performed well as correlation and error values were closer to each other. Conclusions The results of this study showed that, first, significant LSCDs with 99% confidence level were surface specific humidity (SSH), sea surface temperature (SST), latent and sensible heat fluxes over land (LHFOL and SHFOL), 2m air temperature (T2M), 500hpa zonal velocity (U500), Nino-3.4, and Nino-4. Second, to predict the monthly precipitation using lagged LSCDs and principal components, MR models were developed. MR models’ performance was low. The highest Pearson correlation in MR models during the training set was observed for Musakhel district as 0.65 and during the test as 0.49 for Musakhel and Zhob. In MR-PC models, the highest correlation was recorded for Awaran (0.50) during the training and for Quetta (0.43) during the test. Third, ANN and BRNN models were developed using the selected PC components and gave higher correlations as compared to regression models indicating their capability of finding the pattern and trend of the observations. They generally manifested lower errors and are more reliable for the purpose of prediction in the region. Maximum correlations during training were 0.77 and 0.73 in both ANN and BRNN models, respectively, for the Lasbela district. In the test case, they were 0.74 and 0.70 for Awaran. Their generalization ability was tested on the TRMM dataset. In conclusion, this study divulged the possibility of monthly precipitation prediction using ANN and BRNN and lagged LSCDs for the study region. It is explicit that the response of precipitation to climatic factors is delayed. Comparing the results of the ANN, BRNN, and MLR, it can be concluded that the artificial intelligence approaches such as ANN and BRNN are reliable nonlinear statistical options that can generate similar and in some cases better forecasts and could be useful for the agriculture and water management in the Balochistan region as it is a very important part of Pakistan in terms of agriculture. In the future, this research will be extended by developing the prediction models by including more LSCDs and can be improved by the approaches of genetic algorithm for the best input selection and the use of observed station-based precipitation data sets. Keywords: Artificial Neural Network, Bayesian Regularization Neural Network, LSCD, Multiple Regression Analysis, Precipitation, Sea Surface Temperature, Balochistan Province-Pakistan. References - Aamir, E., & Hassan, I. (2020). The impact of climate indices on precipitation variability in Baluchistan, Pakistan. Tellus A: Dynamic Meteorology and Oceanography, 72(1), 1-46. - Adamowski, J., & Sun, K. (2010). Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. Journal of Hydrology, 390(1-2), 85–91. - Ahmed, K., Shahid, S., Haroon, S. B., & Xiao-Jun, W. (2015). Multilayer perceptron neural network for downscaling rainfall in arid region: A case study of Baluchistan, Pakistan. Journal of Earth System Sciences, 124(6), 1325–1341. - Ailikun, B., & Yasunari, T. (2001). ENSO and Asian summer monsoon: Persistence and transitivity in the seasonal march. Journal of the Meteorological Society of Japan, 79(1), 145–159. - Awan, J. A., & Maqbool, O. (2010). Application of artificial neural networks for monsoon rainfall prediction. 2010 6th International Conference on Emerging Technologies (ICET), 27-32. - Beale, M. H., Hagan, M. T., & Demuth, H. B. (2011). Neural network toolbox TM7: User’s guide. (n.p). - Begum, B., Tajbar, S., Khan, B., & Rafiq, L. (2021). Identification of relationships between climate indices and precipitation fluctuation in Peshawar City-Pakistan. Journal of Research in Environmental Earth Sciences, 10, 264–278. - Canchala, T., Alfonso-Morales, W., Ceron, W. L., Carvajal-Escobar, Y., & Caicedo-Bravo, E. (2020). Teleconnections between monthly rainfall variability and large-scale climate indices in southwestern Columbia. Water, 12(7), 1863. - Chand, A., & Nand, R. (2009). Rainfall prediction using artificial neural network in the south pacific region. 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Melbourne, VIC, Australia, 1-7. - Choubin, B., Khalighi-Sigaroodi, S., Malekian, A., & Kisi, O. (2014). Multiple linear regression, multi-layer perceptron network and adaptive neuro-fuzzy inference system for forecasting precipitation based on large-scale climate signals. Hydrological Sciences Journal, 61(6), 1001-1009. - Davey, M. K., Brookshaw, A., & Ineson, S. (2014). The probability of the impact of ENSO on precipitation and near-surface temperature. Journal of Climate Risk Management, 1, 5–24. - De Silva, T. M., & Hornberger, G. M. (2019). Identifying El Niño-Southern Oscillation influences on rainfall with classification models: Implications for water resource management of Sri Lanka. Journal of Hydrology and Earth System Sciences, 23(4), 1905-1929. - Doranalu Chandrashekar, V., Shetty, A., & Patel, G. C. M. (2019). Estimation of monsoon seasonal precipitation teleconnection with El Niño-Southern Oscillation sea surface temperature indices over the Western Ghats of Karnataka, Asia-Pacific. Journal of Atmospheric Sciences, 1-15. Retrieved from: https://doi.org/10.1007/s13143-019-00133-w. - Field, A. (2009). Discovering statistics using SPSS. Third Edition. London: Sage Publication Ltd. - Ghasemiyeh, H., Bazrafshan, O., & Bakhshayesh Manesh, K. (2017). Artificial neural network for monthly rainfall forecasting using teleconnection patterns (case study: Central Plateau Basin of Iran). Journal of Earth Space Physics, 43(2), 405-418. - Global, C. (2020). China-Pakistan economic corridor: CPEC, CPIC. Retrieved from: https://www.cpicglobal.com/pakistan-overview/cpec/. - Hossain, I., Rasel, H. M., Imteaz, M. A., & Pourakbar, S. (2015). Effects of climate indices on extreme rainfall in Queensland, Australia. Proceeding of 21st International Congress on Modelling and Simulation, MODSIM. - Iqbal, M. F., & Athar, H. (2018). Variability, trends, and teleconnections of observed precipitation over Pakistan. Journal of Theoretical and Applied Climatology, 134(1), 613–632. - Jamro, S., Channa, F. N., Dars, G. H., Ansari, K., & Krakauer, N. Y. (2020). Exploring the evolution of drought characteristics in Balochistan, Pakistan. Journal of Applied Sciences, 10(3), 913. - Khan, N., Sachindra, D. A., Shahid, S., Ahmed, K., Shiru, M. S., & Nawaz, N. (2020). Prediction of droughts over Pakistan using machine learning algorithms. Journal of Advances in Water Resources, 139, 103562. - LDAS. (2021). GLDAS: Project Goals. Retrieved from: https://ldas.gsfc.nasa.gov/gldas. - Lee, J. H., & Julien, P. Y. (2016). Teleconnections of the ENSO and South Korean precipitation patterns. Journal of Hydrology, 534, 237–250. - Lin, F. J. (2008). Solving multicollinearity in the process of fitting regression model using the nested estimate procedure. Journal of Quality & Quantity, 42(3), 417–426. - Li, X., & Ting, M. (2015). Recent and future changes in the Asian monsoon-ENSO relationship: Natural or forced?. Journal of Geophysical Reserach Letters, 42(9), 3502-3512. - Maier, H. R., & Dandy, G. C. (2000). Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications. Journal of Environmental Modelling & Software, 15(1), 101–124. - Mekanik, F., Imteaz, M. A., Gato-Trinidad, S., & Elmahdi, A. (2013). Multiple regression and Artificial neural network for long-term rainfall forecasting using large scale climate modes. Journal of Hydrology, 503, 11–21. - Menke, W., & Menke, J. (2009). Environmental data analysis with MATLAB. First Edition. UK: Elsevier. - Naz, F., Dars, G. H., Ansari, K., Jamro, S., & Krakauer, N. Y. (2020). Drought trends in Balochistan. Water, 12(2), 470. - Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ, R., ... & van Ypserle, J. P. (2014). Climate change 2014: Synthesis report. In Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Core Writing Team, R. K. Pachauri and L. A. Meyer]. IPCC, Geneva, Switzerland, 151 pp. - Rasul, G., Afzal, M., Zahid, M., & Bukhari, S. A. A. (2012). Climate Change in Pakistan Focused on Sindh Province. Technical Report PMD 25/2012 55, Pakistan Meteorological Department, Islamabad, Pakistan. Retrieved from: https://doi.org/10.13140/2.1.2170.6560. - Shukla, R. P., Tripathi, K. C., Pandey, A. C., & Das, I. M. L. (2011). Prediction of Indian summer monsoon rainfall using Niño indices: A neural network approach. Journal of Atmospheric Research, 102(1-2), 99–109. - Taweesin, K., & Seeboonruang, U. (2019). The relationship between the climatic indices and the rainfall fluctuation in the lower central plain of Thailand. International Journal of Innovative Computing, Information and Control, 15(1), 107–127. - Ye, L., Jabbar, S. F., Zahra, M. M. A., & Tan, M. L. (2021). Bayesian regularized neural network model development for predicting daily rainfall from sea level pressure data: Investigation on solving complex hydrology problem. Complexity, (Special Issue). Retrieved from: https://doi.org/10.1155/2021/6631564. - Zuecco, F., Facco, P., Hoeser, S. R., Fogli, M. R., Cicciotti, M., Bezzo, P., & Barolo, M. (2020). Troubleshooting an industrial batch process for the manufacturing of specialty chemicals using data analytics. Journal of Computor Aided Chemical Engineering, 48, 1129-1134. Abstract The Balochistan province of Pakistan is mostly affected by severe drought events due to little amount of precipitation. “Several Large Scale Climate Drivers (LSCDs) are known for their effects on precipitation worldwide but studies in the region are missing; a wide variety of LSCDs and lagged associative information”.The current study aimed to identify the significant LSCDs in the Balochistan province of Pakistan and improve the prediction skill of monthly precipitation by employing the Principal Component Analysis, Artificial Neural Network (ANN), Bayesian Regularization Neural Network (BRNN), and Multiple Regression (MR) Analysis using the 12 months lagged LSCDs such as Nino-1+2, Nino-3, Nino-3.4, Nino-4, QBO at 30 and 50hpa (QBOI and QBOII), Sea Surface Temperature (SST), 2m air temperature (T2M), 500hpa and 850hpa geopotential heights (H500 and H850), 500hpa zonal velocity (U500), 500hpa and 850hpa meridional velocity (V500 and V850), Latent and Sensible Heat Fluxes Over Land (LHFOL and SHFOL), and Surface Specific Humidity (SSH). To collect the data, Global Land Data Assimilation System, Tropical Rainfall Measuring Mission, MERRA-2, NOAA, Freie University Berlin, and HadISST datasets were used. The results of the study showed that significant LSCDs with a 99% confidence level were SSH, SST, LHFOL, SHFOL, T2M, U500, Nino-3.4, and Nino-4. During the test period, compared with MR models of 0.15 to 0.49 and principal components of -0.16 to 0.43, the ANN and BRNN models had better predictive skills with correlation coefficients of 0.40 to 0.74 and 0.34 to 0.70, respectively. It can be concluded that the ANN and BRNN models enable us to predict monthly precipitation in the Balochistan region with lagged LSCDs. Extended Abstract Introduction Pakistan is one of the most vulnerable countries due to climate change. According to the Global Climate Risk Index (GCRI) report, with the passage of time, its vulnerability is increasing. The main threats consist of a rise in temperature, irregular patterns of rainfall, a rise in the sea level, and extreme events such as droughts, floods, and heatwaves. Precipitation plays an important role in the economy of Pakistan as an agricultural country that has experienced variations, particularly in a recent couple of decades when a sharp jump in global atmospheric temperatures was noticed. The southern part of Pakistan which comprises the Sindh and Balochistan provinces has an arid climate and is mostly affected by severe drought events due to less amount of rainfall throughout the year as compared to other parts of the country. This study’s main focus is Balochistan province which has a long history of severe droughts and is an important province in terms of agriculture. Less than 250mm is the annual average rainfall received by the region. It is predicted that throughout the 21st century if adaptation measures are not taken, there will be a continuous increase in droughts and scarcity of water which will adversely affect the lives of people and the economy. Globally, precipitation and droughts are strongly linked with the large-scale climate drivers through atmospheric associations but there are no detailed studies in Balochistan province that consider a wide variety of large-scale climate drivers and their lagged association with precipitation. The main objective of the present study is to identify the significant large-scale climate drivers in the Balochistan province of Pakistan and improve the prediction skill of monthly precipitation by applying the principal component analysis, artificial neural network, Bayesian regularization neural network, and multiple regression analysis considering the lagged association of climate drivers. Methodology In the present study, first, large-scale climate drivers from NOAA HadISST, MERRA-2, and Freie University Berlin in NetCDF files were processed using the ArcGIS model builder along with the precipitation data from GLDAS and TRMM. The data were first normalized in the range of 0 and 1 using the min-max normalization formula. For showing the 12 months’ lagged association between the large-scale climate drivers and precipitation, a cross-correlation method was employed and the heatmaps were created in Origin 2021b software to show significant lagged correlations. Principal component analysis was applied and the variances and Eigenvalues for each of the components were calculated. Multi-layer feed-forward neural network with a back propagation algorithm was used for the prediction of monthly precipitation with the first two PCs in most cases, three and one in some cases as the predictors. Bayesian Regularization Neural Network (BRNN) was applied which is a version of Artificial Neural Networks (ANN) and is a more powerful method as compared to conventional ANN. MATLAB R2015a environment was used for this purpose. Then, Multiple Regression Analysis (MRA) was carried out and was used as a benchmark for comparing ANN and BRNN models using significantly lagged climate indices in one case and in another case the selected PCs. To validate the performance of all developed models, the TRMM dataset was used. Finally, time series graphs and Radar charts were prepared for comparison. Discussions The findings of cross-correlations between monthly precipitation and large-scale climate drivers in Balochistan province showed the most dominant climate drivers as surface specific humidity, sea surface temperature, latent and sensible heat fluxes over land, 500hpa zonal velocity, 2m air temperature, Nino-3.4 and Nino-4, and the highest correlations were noticed for surface specific humidity, sea surface temperature, latent and sensible heat fluxes over land, 500hpa zonal velocity, 2m air temperature. It is noteworthy that in each district, the lagged correlation of maximum climate indices with precipitation was distinct at distinct lags. The multiple regression best models were selected on the basis of no violation of the limits of statistical significance and lower errors. The MLR model’s performance was low in the region where some of the districts had low correlations. The results from ANN and BRNN models showed that the BRNN models were on a lower side than the ANN models with higher values of correlation coefficient showing their capability of finding the pattern and trend of the GLDAS precipitation. The results of the evaluation of the generalization capability of all models on the TRMM dataset showed that both ANN and BRNN models relatively performed well as correlation and error values were closer to each other. Conclusions The results of this study showed that, first, significant LSCDs with 99% confidence level were surface specific humidity (SSH), sea surface temperature (SST), latent and sensible heat fluxes over land (LHFOL and SHFOL), 2m air temperature (T2M), 500hpa zonal velocity (U500), Nino-3.4, and Nino-4. Second, to predict the monthly precipitation using lagged LSCDs and principal components, MR models were developed. MR models’ performance was low. The highest Pearson correlation in MR models during the training set was observed for Musakhel district as 0.65 and during the test as 0.49 for Musakhel and Zhob. In MR-PC models, the highest correlation was recorded for Awaran (0.50) during the training and for Quetta (0.43) during the test. Third, ANN and BRNN models were developed using the selected PC components and gave higher correlations as compared to regression models indicating their capability of finding the pattern and trend of the observations. They generally manifested lower errors and are more reliable for the purpose of prediction in the region. Maximum correlations during training were 0.77 and 0.73 in both ANN and BRNN models, respectively, for the Lasbela district. In the test case, they were 0.74 and 0.70 for Awaran. Their generalization ability was tested on the TRMM dataset. In conclusion, this study divulged the possibility of monthly precipitation prediction using ANN and BRNN and lagged LSCDs for the study region. It is explicit that the response of precipitation to climatic factors is delayed. Comparing the results of the ANN, BRNN, and MLR, it can be concluded that the artificial intelligence approaches such as ANN and BRNN are reliable nonlinear statistical options that can generate similar and in some cases better forecasts and could be useful for the agriculture and water management in the Balochistan region as it is a very important part of Pakistan in terms of agriculture. In the future, this research will be extended by developing the prediction models by including more LSCDs and can be improved by the approaches of genetic algorithm for the best input selection and the use of observed station-based precipitation data sets. Keywords: Artificial Neural Network, Bayesian Regularization Neural Network, LSCD, Multiple Regression Analysis, Precipitation, Sea Surface Temperature, Balochistan Province-Pakistan. References - Aamir, E., & Hassan, I. (2020). The impact of climate indices on precipitation variability in Baluchistan, Pakistan. Tellus A: Dynamic Meteorology and Oceanography, 72(1), 1-46. - Adamowski, J., & Sun, K. (2010). Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. Journal of Hydrology, 390(1-2), 85–91. - Ahmed, K., Shahid, S., Haroon, S. B., & Xiao-Jun, W. (2015). Multilayer perceptron neural network for downscaling rainfall in arid region: A case study of Baluchistan, Pakistan. Journal of Earth System Sciences, 124(6), 1325–1341. - Ailikun, B., & Yasunari, T. (2001). ENSO and Asian summer monsoon: Persistence and transitivity in the seasonal march. Journal of the Meteorological Society of Japan, 79(1), 145–159. - Awan, J. A., & Maqbool, O. (2010). Application of artificial neural networks for monsoon rainfall prediction. 2010 6th International Conference on Emerging Technologies (ICET), 27-32. - Beale, M. H., Hagan, M. T., & Demuth, H. B. (2011). Neural network toolbox TM7: User’s guide. (n.p). - Begum, B., Tajbar, S., Khan, B., & Rafiq, L. (2021). Identification of relationships between climate indices and precipitation fluctuation in Peshawar City-Pakistan. Journal of Research in Environmental Earth Sciences, 10, 264–278. - Canchala, T., Alfonso-Morales, W., Ceron, W. L., Carvajal-Escobar, Y., & Caicedo-Bravo, E. (2020). Teleconnections between monthly rainfall variability and large-scale climate indices in southwestern Columbia. Water, 12(7), 1863. - Chand, A., & Nand, R. (2009). Rainfall prediction using artificial neural network in the south pacific region. 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Melbourne, VIC, Australia, 1-7. - Choubin, B., Khalighi-Sigaroodi, S., Malekian, A., & Kisi, O. (2014). Multiple linear regression, multi-layer perceptron network and adaptive neuro-fuzzy inference system for forecasting precipitation based on large-scale climate signals. Hydrological Sciences Journal, 61(6), 1001-1009. - Davey, M. K., Brookshaw, A., & Ineson, S. (2014). The probability of the impact of ENSO on precipitation and near-surface temperature. Journal of Climate Risk Management, 1, 5–24. - De Silva, T. M., & Hornberger, G. M. (2019). Identifying El Niño-Southern Oscillation influences on rainfall with classification models: Implications for water resource management of Sri Lanka. Journal of Hydrology and Earth System Sciences, 23(4), 1905-1929. - Doranalu Chandrashekar, V., Shetty, A., & Patel, G. C. M. (2019). Estimation of monsoon seasonal precipitation teleconnection with El Niño-Southern Oscillation sea surface temperature indices over the Western Ghats of Karnataka, Asia-Pacific. Journal of Atmospheric Sciences, 1-15. Retrieved from: https://doi.org/10.1007/s13143-019-00133-w. - Field, A. (2009). Discovering statistics using SPSS. Third Edition. London: Sage Publication Ltd. - Ghasemiyeh, H., Bazrafshan, O., & Bakhshayesh Manesh, K. (2017). Artificial neural network for monthly rainfall forecasting using teleconnection patterns (case study: Central Plateau Basin of Iran). Journal of Earth Space Physics, 43(2), 405-418. - Global, C. (2020). China-Pakistan economic corridor: CPEC, CPIC. Retrieved from: https://www.cpicglobal.com/pakistan-overview/cpec/. - Hossain, I., Rasel, H. M., Imteaz, M. A., & Pourakbar, S. (2015). Effects of climate indices on extreme rainfall in Queensland, Australia. Proceeding of 21st International Congress on Modelling and Simulation, MODSIM. - Iqbal, M. F., & Athar, H. (2018). Variability, trends, and teleconnections of observed precipitation over Pakistan. Journal of Theoretical and Applied Climatology, 134(1), 613–632. - Jamro, S., Channa, F. N., Dars, G. H., Ansari, K., & Krakauer, N. Y. (2020). Exploring the evolution of drought characteristics in Balochistan, Pakistan. Journal of Applied Sciences, 10(3), 913. - Khan, N., Sachindra, D. A., Shahid, S., Ahmed, K., Shiru, M. S., & Nawaz, N. (2020). Prediction of droughts over Pakistan using machine learning algorithms. Journal of Advances in Water Resources, 139, 103562. - LDAS. (2021). GLDAS: Project Goals. Retrieved from: https://ldas.gsfc.nasa.gov/gldas. - Lee, J. H., & Julien, P. Y. (2016). Teleconnections of the ENSO and South Korean precipitation patterns. Journal of Hydrology, 534, 237–250. - Lin, F. J. (2008). Solving multicollinearity in the process of fitting regression model using the nested estimate procedure. Journal of Quality & Quantity, 42(3), 417–426. - Li, X., & Ting, M. (2015). Recent and future changes in the Asian monsoon-ENSO relationship: Natural or forced?. Journal of Geophysical Reserach Letters, 42(9), 3502-3512. - Maier, H. R., & Dandy, G. C. (2000). Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications. Journal of Environmental Modelling & Software, 15(1), 101–124. - Mekanik, F., Imteaz, M. A., Gato-Trinidad, S., & Elmahdi, A. (2013). Multiple regression and Artificial neural network for long-term rainfall forecasting using large scale climate modes. Journal of Hydrology, 503, 11–21. - Menke, W., & Menke, J. (2009). Environmental data analysis with MATLAB. First Edition. UK: Elsevier. - Naz, F., Dars, G. H., Ansari, K., Jamro, S., & Krakauer, N. Y. (2020). Drought trends in Balochistan. Water, 12(2), 470. - Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ, R., ... & van Ypserle, J. P. (2014). Climate change 2014: Synthesis report. In Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Core Writing Team, R. K. Pachauri and L. A. Meyer]. IPCC, Geneva, Switzerland, 151 pp. - Rasul, G., Afzal, M., Zahid, M., & Bukhari, S. A. A. (2012). Climate Change in Pakistan Focused on Sindh Province. Technical Report PMD 25/2012 55, Pakistan Meteorological Department, Islamabad, Pakistan. Retrieved from: https://doi.org/10.13140/2.1.2170.6560. - Shukla, R. P., Tripathi, K. C., Pandey, A. C., & Das, I. M. L. (2011). Prediction of Indian summer monsoon rainfall using Niño indices: A neural network approach. Journal of Atmospheric Research, 102(1-2), 99–109. - Taweesin, K., & Seeboonruang, U. (2019). The relationship between the climatic indices and the rainfall fluctuation in the lower central plain of Thailand. International Journal of Innovative Computing, Information and Control, 15(1), 107–127. - Ye, L., Jabbar, S. F., Zahra, M. M. A., & Tan, M. L. (2021). Bayesian regularized neural network model development for predicting daily rainfall from sea level pressure data: Investigation on solving complex hydrology problem. Complexity, (Special Issue). Retrieved from: https://doi.org/10.1155/2021/6631564. - Zuecco, F., Facco, P., Hoeser, S. R., Fogli, M. R., Cicciotti, M., Bezzo, P., & Barolo, M. (2020). Troubleshooting an industrial batch process for the manufacturing of specialty chemicals using data analytics. Journal of Computor Aided Chemical Engineering, 48, 1129-1134.

https://gep.ui.ac.ir/article_26454_bb1488a8934b6f323c03536b91be4941.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Geochemistry, Mineralogy, and Environmental Interpretation of Vesicular Horizons in the Soils of the Segzi Region, Eastern Isfahan Geochemistry, Mineralogy, and Environmental Interpretation of Vesicular Horizons in the Soils of the Segzi Region, Eastern Isfahan 21 42 26579 10.22108/gep.2022.132727.1492 FA Omid Bayat MA, Department of Soil Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran Alireza Karimi Professor, Department of Soil Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran Journal Article 2022 02 19 Extended Abstract Introduction Vesicular horizons are common on the surface of landforms in arid regions and play an important role in the hydrological properties and pedogenic processes in these areas. Vesicular pores are a characteristic feature of vesicular horizons and include separate pores with spherical to elliptical shapes and dimensions of micrometers to millimeters in diameter (Dietze et al., 2012). The eastern region of Isfahan located in the eastern part of the Zayandehroud River basin is affected by environmental disasters due to severe environmental drought, destructive human activities, and desertification processes. Although vesicular horizons are frequent in the soils and landforms of the eastern region of Isfahan (Bayat et al., 2018), there is no information about the geochemical and mineralogical properties of these horizons. The aim of the present study was to investigate the physical, chemical, geochemical, and mineralogical properties of vesicular horizons at different elevation levels of three landforms in the eastern region of Isfahan. Materials and Methods The study area is located in the center of Iran, east of Isfahan and around Segzi Playa. According to the meteorological stations of the region, the mean annual precipitation and temperature are about 107 mm and roughly 15 ˚C, respectively. Groundwater in piedmonts and plateaus of the region is deep and there are no signs of groundwater activity in the studied soils and landforms. The studied landforms include a remnant paleosurface across the Zayandehroud River (RP), a pediment in Jey industrial city (JP), and an alluvial fan near the Zefreh (ZA). Seven samples of vesicular horizons were taken from vesicular horizons in RP (at altitudes of 1542 and 1552 m), ZA (altitudes of 1623, 1764, and 1901 m), and JP (at altitudes of 1542 and 1557 m) landforms. The samples were described according to Schoenberger (2012) and analyzed regarding standard methods (Soukup et al., 2008; Soil Survey Staff, 2014). Results and Discussion The thickness of the studied vesicular horizons varied in the range of 3-6 cm, and on the alluvial fan, the thickness of the horizon increases with increasing the elevation. The chemical properties of the studied samples indicated very low electrical conductivity and organic carbon content and were similar to vesicular horizons in the Mojave Desert of California (McFadden et al., 1998). The particle size distribution indicated the predominance of sand particles in all samples and all samples were characterized by a bimodal distribution of particle sizes suggesting the contribution of at least two mechanisms in the transfer of particles to the studied vesicular horizons (Karimi et al., 2017; Sweeney et al., 2013). Mineralogical analysis of the samples showed the predominance of quartz and calcite in all samples and varied concerning the presence of mica and fibrous minerals. It seems that quartz is inherited from the parent material while calcite and mica minerals originated from the parent material and were also added by the wind. Fibrous minerals were probably of autogenic origin. The geochemical properties of the samples were consistent with the mineralogical results and showed the abundance of SiO2 and CaO in all samples. Among the trace elements, the highest abundance is observed in the strontium, which is due to the association of this element with carbonates (Ding et al., 2019). A comparison of geochemical properties of vesicular horizons with associated rocks showed the enrichment of SO3 and CaO relative to corresponding parent material indicating the addition of soluble ions, carbonates, and especially gypsum to the surface of the studied landforms. The Zr/Al ratio showed an increasing trend with increasing the silt content which proved the aeolian source of the silt particles as previous studies have shown a very strong correlation between aeolian sediments and the element zirconium (e.g., Waroszewski et al., 2018). Conclusions Increasing the amount of silt and the ratio of fine-grained particles to sand with increasing the elevation indicated the role of aeolian processes in adding fine-grained particles to the surfaces of different landforms of eastern Isfahan. Mineralogical and geochemical evidence also confirms the effect of dust on the formation of these horizons, so that the addition of mica minerals along with silt particles has occurred at higher altitudes. The geochemical study of vesicular horizons and application of Zr/Al ratios show that the composition of past and current dust in eastern Isfahan was the origin of dust for different landforms of the region is the same. Finally, the existence of developed vesicular horizons in the surfaces of the landforms of the region demonstrates long-term processes of wind erosion and dust influx into the soils. These natural processes are probably intensified by anthropogenic activities in recent years. Keywords: Aeolian Processes, Dust Addition, Alluvial Fan, Bulk Mineralogy. References - Anderson, K., Wells, S., & Graham, R. (2002). Pedogenesis of vesicular horizons, Cima volcanic field, Mojave Desert, California. Soil Science Society of America Journal, 66(3), 878-887. - Bayat, O., Karimzadeh, H. R., Eghbal, M. K., Karimi, A., & Amundson, R. (2018). Calcic soils as indicators of profound Quaternary climate change in eastern Isfahan, Iran. Geoderma, 315, 220-230. - Blair, T. C., & McPherson, J. G. (2009). Processes and forms of alluvial fans. In A.J. Parsons and A. D. Abrahams (Eds.) Geomorphology of Desert Environments (pp. 413-466). Springer, Berlin, Germany. - Brown, K. J., & Dunkerley, D. (1996). The influence of hillslope gradient, regolith texture, stone size and stone position on the presence of a vesicular layer and related aspects of hillslope hydrologic processes: A case study from the Australian arid zone. Catena, 26(1-2), 71-84. - Carolin, S. A., Walker, R. T., Day, C. C., Ersek, V., Sloan, R. A., Dee, M. W., Talebian, M., & Henderson, G. M. (2019). Precise timing of abrupt increase in dust activity in the Middle East coincident with 4.2 ka social change. Proceedings of the National Academy of Sciences, 116(1), 67-72. - Chen, B., Yang, X., Jiang, Q., Liang, P., Mackenzie, L. L., & Zhou, Y. (2022). Geochemistry of aeolian sand in the Taklamakan Desert and Horqin Sandy Land, northern China: Implications for weathering, recycling, and provenance. Catena, 208, 105769. - Dietze M., Bartel, S., Lindner, M., & Kleber, A. (2012). Formation mechanisms and control factor of vesicular soil structure. Catena, 99, 83-96. - Ding, M., Peng, S. M., Zhang, W., Zhao, Q., Mao, L., Yang, J., & Zhang, L. (2019). Distribution of trace elements in Holocene loess-paleosol sequence and environmental change in lower reaches of the yellow river. Journal of Earth and Environmental Science, 237(3), 032052. - Gee, G. W., & Bauder, J. W. (1986). Particle-size analysis, In A. Klute (Ed.), Methods of Soil Analysis Part 1, Physical and Mineralogical Methods (pp. 383-412). Second Edition. Soil Science Society of America, Book Series No. 5. SSSA and ASA, Madison, Wisconsin, USA. - Gerson, R., & Amit, R. (1987). Rates and modes of dust accretion and deposition in an arid region- the Negev, Israel. In L.E. Frostick and I. Reid (Eds.), Desert Sediments: Ancient and Modern (pp. 157-169). Blackwell Scientific Publications, Oxford, UK. - Gheysari, F., Ayoubi, S., & Abdi, M. R. (2016). Using Cesium-137 to estimate soil partivle redistribution by wind in an arid region of central Iran. Eurasian Journal of Soil Science, 5(4), 285-293. - Han, F. X., & Singer, A. (2007). Biogeochemistry of trace elements in arid environments. Springer. - Harris, W., & White, G. N. (2008). X-ray diffraction techniques for soil mineral identification, In A.L. Ulery and R. Drees (Eds.), Methods of Soil Analysis, Part 5- Mineralogical Methods (pp. 81-115). Soil Science Society of America, Madison, USA. - Jones, S., Arzani, N., & Allen, M. B. (2014). Tectonic and climatic controls on fan systems: The Kohrud mountain belt, central Iran. Journal of Sedimentary Geology, 302, 29-43. - Karimi, A., Khormali, F., & Wang, X. (2017). Discrimination of sand dunes and loess deposits using grain-size analysis in northeastern Iran. Arabian Journal of Geoscience, 10(12), 1-13. - Loeppert, R. H., & Suarez, D. L. (1996). Carbonate and gypsum. In D. L. Sparks (Ed.), Methods of Soil Analysis: Part 3, Chemical Methods. Second Edition. (pp. 961-1010). Soil Science Society of America, Inc. American Society of Agronomy, Inc. Madison, Wisconsin, USA. - May, J. H., Wells, S. G., Cohen, T. J., Marx, S. K., Nanson, G. C., & Baker, S. E. (2015). A soil chronosequence on Lake Mega-Frome beach ridges and its implications for late Quaternary pedogenesis and paleoenvironmental conditions in the drylands of southern Australia. Quaternary Research, 83(1), 150-165. - McFadden, L. D., McDonald, E. V., Wells, S. G., Anderson, K., Quade, J., & Forman, S. L. (1998). The vesicular layer and carbonate collars of desert soils and pavements: Formation, age, and relation to climate change. Journal of Geomorphology, 24(2-3), 101-145. - McFadden, L. D., Wells, S. G., & Jercinovich, M. J. (1987). Influences of eolian and pedogenic processes on the origin and evolution of desert pavements. Journal of Geology, 15(6), 504-508. - Mohammed, A., Hirmas, D., Nemes, A., & Giménez, D. (2020). Exogenous and endogenous controls on the development of soil structure. Geoderma, 357, 113945. - Neaman, A., & Singer, A. (2011). The effects of palygorskite on chemical and physico-chemical properties of soils. In E. Galan. & A. Singer (Eds.), Developments in Palygorskite-sepiolite Research (pp. 325-349). Developments in Clay Science, Vol. 3, Elsevier, the Netherlands. - Nelson, D. W., & Sommers, L. E. (1996). Total carbon, organic matter. In D. L. Sparks (Ed.), Methods of Soil Analysis: Part 3, Chemical Methods. Second Edition. (pp. 961-1010). Soil Science Society of America, Inc. American Society of Agronomy, Inc. Madison, Wisconsin, USA - Omran, E. E. (2016). A simple model for rapid gypsum determination in arid soils. Journal of Modelling Earth Systems and Environment, 2(4), 1-12. - Schaetzl, T. J., & Thompson, M. L. (2015). Soils Genesis and Geomorphology. Cambridge: Cambridge University Press. - Scheib, A. J., Birke, M., & Dinelli, E. (2013). Geochemical evidence of aeolian deposits in European soils. Boreas, 43(1), 175-192. - Schoeneberger, P. J., Wysocki, D. A., &Benham, E. C. (2012). Field book for describing and sampling soils. Version 3.0. Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE. - Soil Survey Staff. (2014) Kellogg soil survey laboratory methods manual. Soil Survey Investigations Report No. 42, Version 5.0. R. Burt and Soil Survey Staff (Ed.). U.S. Department of Agriculture, Natural Resources Conservation Service. - Soukup, D. A., Buck, B. J., & Harris, W. (2008). Preparing soils for mineralogical analyses. In A. L. Ulery & R. Drees (Eds.), Methods of soil analysis, part 5- mineralogical methods (pp. 13-31). Soil science society of America, Madison, USA. - Sweeney, M. R., McDonald, E. V., & Markley, C. E. (2013). Alluvial sediment or playas: What is the dominant source of sand and silt in desert soil vesicular a horizons, southwest USA. Journal of Geophysical Research, 118(1), 257-275. - Thomas, G. W. (1996). Soil pH and soil acidity, methods of soil analysis; Part 3 Chemical Methods. Soil Science Society of America Book Series. - Toomanian, N., & Salami, H. R. (2020). Structural evolution of the Zayandeh-rud river basin based on historical climate changes. In S. Mohajeri, L. Horlrman, A. A. Besalatpour & W. Raber (Eds.), Standing up to Climate Change, (pp. 199-224). Springer, Cham, Switzerland. - Turk, J., & Graham, R. C. (2011). Distribution and properties of vesicular horizons in the western United States. Soil Science Society of America Journal, 75, 1449-1461. - Waroszewski, J., Sprafke, T., Kabala, C., Musztyfaga, E., Labaz, B., & Wozniczka, P. (2018). Aeolian silt contribution to soils on mountain slopes (Mt. Sleza, southwest Poland). Journal of Quaternary Research, 89(3), 702-717. - Young, M. H., McDonald, E. V., Caldwell, T. G., Benner, S. G., & Meadows, D. (2004). Hydraulic properties of a desert chronosequence in the Mojave Desert, USA. Vadose Zone Journal, 3(3), 956-963. Extended Abstract Introduction Vesicular horizons are common on the surface of landforms in arid regions and play an important role in the hydrological properties and pedogenic processes in these areas. Vesicular pores are a characteristic feature of vesicular horizons and include separate pores with spherical to elliptical shapes and dimensions of micrometers to millimeters in diameter (Dietze et al., 2012). The eastern region of Isfahan located in the eastern part of the Zayandehroud River basin is affected by environmental disasters due to severe environmental drought, destructive human activities, and desertification processes. Although vesicular horizons are frequent in the soils and landforms of the eastern region of Isfahan (Bayat et al., 2018), there is no information about the geochemical and mineralogical properties of these horizons. The aim of the present study was to investigate the physical, chemical, geochemical, and mineralogical properties of vesicular horizons at different elevation levels of three landforms in the eastern region of Isfahan. Materials and Methods The study area is located in the center of Iran, east of Isfahan and around Segzi Playa. According to the meteorological stations of the region, the mean annual precipitation and temperature are about 107 mm and roughly 15 ˚C, respectively. Groundwater in piedmonts and plateaus of the region is deep and there are no signs of groundwater activity in the studied soils and landforms. The studied landforms include a remnant paleosurface across the Zayandehroud River (RP), a pediment in Jey industrial city (JP), and an alluvial fan near the Zefreh (ZA). Seven samples of vesicular horizons were taken from vesicular horizons in RP (at altitudes of 1542 and 1552 m), ZA (altitudes of 1623, 1764, and 1901 m), and JP (at altitudes of 1542 and 1557 m) landforms. The samples were described according to Schoenberger (2012) and analyzed regarding standard methods (Soukup et al., 2008; Soil Survey Staff, 2014). Results and Discussion The thickness of the studied vesicular horizons varied in the range of 3-6 cm, and on the alluvial fan, the thickness of the horizon increases with increasing the elevation. The chemical properties of the studied samples indicated very low electrical conductivity and organic carbon content and were similar to vesicular horizons in the Mojave Desert of California (McFadden et al., 1998). The particle size distribution indicated the predominance of sand particles in all samples and all samples were characterized by a bimodal distribution of particle sizes suggesting the contribution of at least two mechanisms in the transfer of particles to the studied vesicular horizons (Karimi et al., 2017; Sweeney et al., 2013). Mineralogical analysis of the samples showed the predominance of quartz and calcite in all samples and varied concerning the presence of mica and fibrous minerals. It seems that quartz is inherited from the parent material while calcite and mica minerals originated from the parent material and were also added by the wind. Fibrous minerals were probably of autogenic origin. The geochemical properties of the samples were consistent with the mineralogical results and showed the abundance of SiO2 and CaO in all samples. Among the trace elements, the highest abundance is observed in the strontium, which is due to the association of this element with carbonates (Ding et al., 2019). A comparison of geochemical properties of vesicular horizons with associated rocks showed the enrichment of SO3 and CaO relative to corresponding parent material indicating the addition of soluble ions, carbonates, and especially gypsum to the surface of the studied landforms. The Zr/Al ratio showed an increasing trend with increasing the silt content which proved the aeolian source of the silt particles as previous studies have shown a very strong correlation between aeolian sediments and the element zirconium (e.g., Waroszewski et al., 2018). Conclusions Increasing the amount of silt and the ratio of fine-grained particles to sand with increasing the elevation indicated the role of aeolian processes in adding fine-grained particles to the surfaces of different landforms of eastern Isfahan. Mineralogical and geochemical evidence also confirms the effect of dust on the formation of these horizons, so that the addition of mica minerals along with silt particles has occurred at higher altitudes. The geochemical study of vesicular horizons and application of Zr/Al ratios show that the composition of past and current dust in eastern Isfahan was the origin of dust for different landforms of the region is the same. Finally, the existence of developed vesicular horizons in the surfaces of the landforms of the region demonstrates long-term processes of wind erosion and dust influx into the soils. These natural processes are probably intensified by anthropogenic activities in recent years. Keywords: Aeolian Processes, Dust Addition, Alluvial Fan, Bulk Mineralogy. References - Anderson, K., Wells, S., & Graham, R. (2002). Pedogenesis of vesicular horizons, Cima volcanic field, Mojave Desert, California. Soil Science Society of America Journal, 66(3), 878-887. - Bayat, O., Karimzadeh, H. R., Eghbal, M. K., Karimi, A., & Amundson, R. (2018). Calcic soils as indicators of profound Quaternary climate change in eastern Isfahan, Iran. Geoderma, 315, 220-230. - Blair, T. C., & McPherson, J. G. (2009). Processes and forms of alluvial fans. In A.J. Parsons and A. D. Abrahams (Eds.) Geomorphology of Desert Environments (pp. 413-466). Springer, Berlin, Germany. - Brown, K. J., & Dunkerley, D. (1996). The influence of hillslope gradient, regolith texture, stone size and stone position on the presence of a vesicular layer and related aspects of hillslope hydrologic processes: A case study from the Australian arid zone. Catena, 26(1-2), 71-84. - Carolin, S. A., Walker, R. T., Day, C. C., Ersek, V., Sloan, R. A., Dee, M. W., Talebian, M., & Henderson, G. M. (2019). Precise timing of abrupt increase in dust activity in the Middle East coincident with 4.2 ka social change. Proceedings of the National Academy of Sciences, 116(1), 67-72. - Chen, B., Yang, X., Jiang, Q., Liang, P., Mackenzie, L. L., & Zhou, Y. (2022). Geochemistry of aeolian sand in the Taklamakan Desert and Horqin Sandy Land, northern China: Implications for weathering, recycling, and provenance. Catena, 208, 105769. - Dietze M., Bartel, S., Lindner, M., & Kleber, A. (2012). Formation mechanisms and control factor of vesicular soil structure. Catena, 99, 83-96. - Ding, M., Peng, S. M., Zhang, W., Zhao, Q., Mao, L., Yang, J., & Zhang, L. (2019). Distribution of trace elements in Holocene loess-paleosol sequence and environmental change in lower reaches of the yellow river. Journal of Earth and Environmental Science, 237(3), 032052. - Gee, G. W., & Bauder, J. W. (1986). Particle-size analysis, In A. Klute (Ed.), Methods of Soil Analysis Part 1, Physical and Mineralogical Methods (pp. 383-412). Second Edition. Soil Science Society of America, Book Series No. 5. SSSA and ASA, Madison, Wisconsin, USA. - Gerson, R., & Amit, R. (1987). Rates and modes of dust accretion and deposition in an arid region- the Negev, Israel. In L.E. Frostick and I. Reid (Eds.), Desert Sediments: Ancient and Modern (pp. 157-169). Blackwell Scientific Publications, Oxford, UK. - Gheysari, F., Ayoubi, S., & Abdi, M. R. (2016). Using Cesium-137 to estimate soil partivle redistribution by wind in an arid region of central Iran. Eurasian Journal of Soil Science, 5(4), 285-293. - Han, F. X., & Singer, A. (2007). Biogeochemistry of trace elements in arid environments. Springer. - Harris, W., & White, G. N. (2008). X-ray diffraction techniques for soil mineral identification, In A.L. Ulery and R. Drees (Eds.), Methods of Soil Analysis, Part 5- Mineralogical Methods (pp. 81-115). Soil Science Society of America, Madison, USA. - Jones, S., Arzani, N., & Allen, M. B. (2014). Tectonic and climatic controls on fan systems: The Kohrud mountain belt, central Iran. Journal of Sedimentary Geology, 302, 29-43. - Karimi, A., Khormali, F., & Wang, X. (2017). Discrimination of sand dunes and loess deposits using grain-size analysis in northeastern Iran. Arabian Journal of Geoscience, 10(12), 1-13. - Loeppert, R. H., & Suarez, D. L. (1996). Carbonate and gypsum. In D. L. Sparks (Ed.), Methods of Soil Analysis: Part 3, Chemical Methods. Second Edition. (pp. 961-1010). Soil Science Society of America, Inc. American Society of Agronomy, Inc. Madison, Wisconsin, USA. - May, J. H., Wells, S. G., Cohen, T. J., Marx, S. K., Nanson, G. C., & Baker, S. E. (2015). A soil chronosequence on Lake Mega-Frome beach ridges and its implications for late Quaternary pedogenesis and paleoenvironmental conditions in the drylands of southern Australia. Quaternary Research, 83(1), 150-165. - McFadden, L. D., McDonald, E. V., Wells, S. G., Anderson, K., Quade, J., & Forman, S. L. (1998). The vesicular layer and carbonate collars of desert soils and pavements: Formation, age, and relation to climate change. Journal of Geomorphology, 24(2-3), 101-145. - McFadden, L. D., Wells, S. G., & Jercinovich, M. J. (1987). Influences of eolian and pedogenic processes on the origin and evolution of desert pavements. Journal of Geology, 15(6), 504-508. - Mohammed, A., Hirmas, D., Nemes, A., & Giménez, D. (2020). Exogenous and endogenous controls on the development of soil structure. Geoderma, 357, 113945. - Neaman, A., & Singer, A. (2011). The effects of palygorskite on chemical and physico-chemical properties of soils. In E. Galan. & A. Singer (Eds.), Developments in Palygorskite-sepiolite Research (pp. 325-349). Developments in Clay Science, Vol. 3, Elsevier, the Netherlands. - Nelson, D. W., & Sommers, L. E. (1996). Total carbon, organic matter. In D. L. Sparks (Ed.), Methods of Soil Analysis: Part 3, Chemical Methods. Second Edition. (pp. 961-1010). Soil Science Society of America, Inc. American Society of Agronomy, Inc. Madison, Wisconsin, USA - Omran, E. E. (2016). A simple model for rapid gypsum determination in arid soils. Journal of Modelling Earth Systems and Environment, 2(4), 1-12. - Schaetzl, T. J., & Thompson, M. L. (2015). Soils Genesis and Geomorphology. Cambridge: Cambridge University Press. - Scheib, A. J., Birke, M., & Dinelli, E. (2013). Geochemical evidence of aeolian deposits in European soils. Boreas, 43(1), 175-192. - Schoeneberger, P. J., Wysocki, D. A., &Benham, E. C. (2012). Field book for describing and sampling soils. Version 3.0. Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE. - Soil Survey Staff. (2014) Kellogg soil survey laboratory methods manual. Soil Survey Investigations Report No. 42, Version 5.0. R. Burt and Soil Survey Staff (Ed.). U.S. Department of Agriculture, Natural Resources Conservation Service. - Soukup, D. A., Buck, B. J., & Harris, W. (2008). Preparing soils for mineralogical analyses. In A. L. Ulery & R. Drees (Eds.), Methods of soil analysis, part 5- mineralogical methods (pp. 13-31). Soil science society of America, Madison, USA. - Sweeney, M. R., McDonald, E. V., & Markley, C. E. (2013). Alluvial sediment or playas: What is the dominant source of sand and silt in desert soil vesicular a horizons, southwest USA. Journal of Geophysical Research, 118(1), 257-275. - Thomas, G. W. (1996). Soil pH and soil acidity, methods of soil analysis; Part 3 Chemical Methods. Soil Science Society of America Book Series. - Toomanian, N., & Salami, H. R. (2020). Structural evolution of the Zayandeh-rud river basin based on historical climate changes. In S. Mohajeri, L. Horlrman, A. A. Besalatpour & W. Raber (Eds.), Standing up to Climate Change, (pp. 199-224). Springer, Cham, Switzerland. - Turk, J., & Graham, R. C. (2011). Distribution and properties of vesicular horizons in the western United States. Soil Science Society of America Journal, 75, 1449-1461. - Waroszewski, J., Sprafke, T., Kabala, C., Musztyfaga, E., Labaz, B., & Wozniczka, P. (2018). Aeolian silt contribution to soils on mountain slopes (Mt. Sleza, southwest Poland). Journal of Quaternary Research, 89(3), 702-717. - Young, M. H., McDonald, E. V., Caldwell, T. G., Benner, S. G., & Meadows, D. (2004). Hydraulic properties of a desert chronosequence in the Mojave Desert, USA. Vadose Zone Journal, 3(3), 956-963.

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University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Capacity-building of Travel Repetition with the Approach of Quality of Perception of the Origin-destination Programs of Tourist Trains (Case Study: Lorestan Tourist Train) Capacity-building of Travel Repetition with the Approach of Quality of Perception of the Origin-destination Programs of Tourist Trains (Case Study: Lorestan Tourist Train) 43 68 26540 10.22108/gep.2022.132759.1493 FA Mohammad Taghi Heidari Assistant Professor, Department of Geography and Urban Planning, Faculty of Humanities, University of Zanjan, Zanjan, Iran Dariush Jahani Assistant Professor, Department of Geography, Payam Noor University, Tehran, Iran Parvin Rahmati MA in Geography and Tourism Planning, Department of Geography and Urban Planning, Faculty of Humanities, Zanjan University, Zanjan, Iran Yagoob Haghi PhD Candidate in Geography and Urban Planning, Department of Geography and Urban Planning, Faculty of Geography, University of Tehran, Tehran, Iran Journal Article 2022 02 19 Abstract The role of the transportation industry in the development of tourism, as a basic and pivotal pillar, accounts for only 5.8% of GDP which is very small. The present study tries to examine the quality of tourist train programs (tourism stimulates economic cycles and better use of resources) on Haldman and Sherman’s (1994) theory of loyalty of tourists to the tourism host community. Tourism is not possible without extensive improvement and development of the network and the quality of transportation. In this regard, the sample community of this study was the passengers of the Lorestan tourist train who intended to visit the Lorestan tourist destination with this train. The obtained data were analyzed using Smart pls software and Wizard scenario. The results of the study show that the most effective components of the origin-destination programs of the tourist train are related to the components of paying attention to the expectations and wishes of the tourists, up-to-date tourism at the destination, and attractive travel destinations. Introduction Rail lines are one of the most important means of transportation in the tourism sector. The device that experts believe is the safest form of transportation. Railways, on the other hand, reduce travel time compared to road transport and in some cases reduce travel costs, and therefore can be considered an important part of tourism. Tourist trains in Iran are not very old and in fact, since 2017 and shortly after the arrival of the first foreign tourist trains in Iran, they have started moving on the Iranian railway. This interesting tourist idea has been implemented on the ‘Tehran-Savadkuh-Sari’ and ‘Tehran-Zavareh’ routes so far. The Lorestan recreational train also runs on the ‘Tehran-Lorestan-Khuzestan’ route. In addition, for some time now, the doors of Tehran Railway Station have been open to tourists to review the historical file of this station, which is also registered in the list of national monuments. Methodology The present research is of applied type using the descriptive-analytical method. The analysis unit of this research was the passengers of the Lorestan tourist train and the sample population was the number of tourists who traveled to Lorestan by this train. The sampling was done in a completely purposeful manner based on the probabilistic and snowball sampling methods. The number of sample members was 30 and a questionnaire was used for collecting the data. Analysis of the obtained data was performed using Smart pls software and Wizard scenario. Discussion The most effective components of the origin-destination programs of the tourist train are related to the components of local attractions by 94%, impact intensity (route coefficient) by 97%, satisfaction levels by 93%, impact intensity by 96%, behavioral image by 92%, impact intensity by 96%, and creativity by 92%. Also, the highest satisfaction calculated in the factor loads section was related to paying attention to the expectations and demands of tourists, up-to-date tourism at the destination, attractive travel destinations, and employing trained and experienced staff. Conclusion The more local attractions are paid attention to at the destination level and the investment platforms are made in them, the more they can attract tourists and increase the frequency of tourists. Tourists have also attached great importance to tourism brands and popular tourist destinations. Also, the exploitation and introduction of more and more historical places, customs, and local and original lifestyles have created a pleasant and enjoyable aspect for the tourists. In contrast, the components of the quality of the tourism process and cheap tourism services have been less important in repeating the travel by tourists than other components. It should be noted that the polite and respectful attitude of citizens toward tourists and the well-being of tourism at the destination have the most important coefficient. In the next step, we can mention trained people and appropriate parks, advice and referrals from others, positive attitudes to travel again, and providing information through the media. Keywords: Tourist Train, Service Quality, Tourist Loyalty, Travel Drivers. References - Adongo, A. C., Amenumey, E. K., Kumi-Kyereme, A., & Dube, E. (2021). Beyond fragmentary: A proposed measure for travel vaccination concerns. Journal of Tourism Management, 83, 104180. - Alegre, J., & Magdalena, C. (2010). Tourist expenditure and quality: Why repeat tourists can spend less than first-timers. Journal of Tourism Economics, 16(3), 517-533. - Bassols-Gardella, N., & Coromina, L. (2022). The perceived image of multi-asset tourist destinations: Investigating congruence across different content types. Journal of Service Business, 16(1), 57-75. - Castillo-Manzano, J. I., Castro-Nuño, M., López-Valpuesta, L., Pedregal-Tercero, D. J., & Garrido-Michó, J. M. (2018). High speed rail: Fast tracking tourism in the EU?. Annals of Tourism Research, 71, 64-66. - Daleela, M., & Siti Nor, K. A. (2020). First-time and repeat visitors to Langkawi Island, Malaysia. Procedia Economics and Finance, 35, 622-631. - Dayour, F., Ghana, W., Adongo, C. A., Amuquandoh, F. E., & Adam, I. (2020). Managing the COVID-19 crisis: Coping and post-recovery strategies for hospitality and tourism businesses in Ghana. Journal of Hospitality and Tourism Insights, 4(4), 373-392. - Delbecq, A. L., Van de Ven, A. H., & Gustafson, D. H. (1975). Group techniques for program planning: A guide to nominal group and Delphi processes. Glenview, Illinois: Scott, Foresman. - Deng, T., Gan, C., Du, H., Hu, Y., & Wang, D. (2021). Do high speed rail configurations matter to tourist arrivals? Empirical evidence from China’s prefecture-level cities. Journal of Research in Transportation Economics, 90, 100952. - Do Valle, P. O., Silva, J. A., Mendes, J., & Guerreiro, M. (2006). Tourist satisfaction and destination loyalty intention: A structural and categorical analysis. International Journal of Business Science and Applied Management, 1(1), 25-44. - Jensen, M. T., & Larsen, J. (2021). Rail tourism transitions: A sociological framework. Annals of Tourism Research, 87(C). - Jin, S., Yang, J., Wang, E., & Liu, J. (2020). The influence of high-speed rail on ice–snow tourism in northeastern China. Journal of Tourism Management, 78, 104070 - Kartsan, P. (2022). Transport communication and organization of transport services in the tourism sector. Transportation Research Procedia, 61, 180-184. - Łapkoa, A., & Panasiuk, A. (2019). Water tourism as a recipient of transport services on the example of Szczecin. Transportation Research Procedia, 39, 290–299. - Law, C. C., Zhang, Y., Gow, J., & Vu, X. B. (2022). Dynamic relationship between air transport, economic growth and inbound tourism in Cambodia, Laos, Myanmar and Vietnam. Journal of Air Transport Management, 98, 102161. - Maghrifani, D., Liu, F., & Sneddon, J. (2022). Understanding potential and repeat visitors’ travel intentions: The roles of travel motivations, destination image, and visitor image congruity. Journal of Travel Research, 61(5), 1121-1137. - Meleddu, M., Paci, R., & Pulina, M. (2015). Repeated behaviour and destination loyalty. Journal of Tourism Management, 50, 159-171. - Mohamad, M., Ghani, N. I., Abd Halim, M. S., & Loganathan, N. (2015). Effects of the Malaysian travel destination brand image on tourist satisfaction and destination loyalty. American-Eurasian Journal of Agricultural & Environmental Sciences (Tourism & Environment, Social and Management Sciences), 15, 61-72. - Nepal, S. K. (2020). Adventure travel and tourism after COVID-19 – business as usual or opportunity to reset?. Journal of Tourism Geographies, 22(3), 1-5. - Qiu, R. T., Park, J., Li, S., & Song, H. (2020). Social costs of tourism during the COVID-19 pandemic. Annals of Tourism Research, 84, 102994. - Romao, J., & Bi, Y. (2021). Determinants of collective transport mode choice and its impacts on trip satisfaction in urban tourism. Journal of Transport Geography, 94, 103094. - Sariego-López, I., Moreno-Melgarejo, A., & Garcia-Moreno, M. B. (2020). Repeat visitors in Cantabria (Spain): Exploring tourist behavior. Revista ESPACIOS, 41(17), 13. - Smith, S., Costello, C., & Muenchen, R. A. (2010). Influence of push and pull motivations on satisfaction and behavioral intentions within a culinary tourism event. Journal of Quality Assurance in Hospitality and Tourism, 11(1), 17-35. - Sorupia, E. (2005). Rethinking the role of transportation in tourism. Proceedings of the Eastern Asia Society for Transportation Studies, 5(11), 1767-1777. - Stahl, N. N., & Stahl, R. J. (1991). We can agree after all! Achieving consensus for a critical thinking component of a gifted program using the Delphi technique. Journal of Roeper Review, 14(2), 79-88. - Šulc, I., & Fuerst-Bjeliš, B. (2021). Changes of tourism trajectories in (post) covidian world: Croatian perspectives. Journal of Research in Globalization, 3, 100052. - Tan, W. K. (2017). Repeat visitation: A study from the perspective of leisure constraint, tourist experience, destination images, and experiential familiarity. Journal of Destination Marketing and Management, 6(3), 233-242. - Ye, Y., Su, C. H., Tsai, C. H., & Hung, J. L. (2020). Motivators of attendance at eco-friendlyevents. Journal of Convention and Event Tourism, 21(5), 417-437. - Yi, X., Fu, X., Jin, W., & Okumus, F. (2018). Constructing a model of exhibition attachment: Motivation, attachment, and loyalty. Journal of Tourism Management, 65, 224–236. Abstract The role of the transportation industry in the development of tourism, as a basic and pivotal pillar, accounts for only 5.8% of GDP which is very small. The present study tries to examine the quality of tourist train programs (tourism stimulates economic cycles and better use of resources) on Haldman and Sherman’s (1994) theory of loyalty of tourists to the tourism host community. Tourism is not possible without extensive improvement and development of the network and the quality of transportation. In this regard, the sample community of this study was the passengers of the Lorestan tourist train who intended to visit the Lorestan tourist destination with this train. The obtained data were analyzed using Smart pls software and Wizard scenario. The results of the study show that the most effective components of the origin-destination programs of the tourist train are related to the components of paying attention to the expectations and wishes of the tourists, up-to-date tourism at the destination, and attractive travel destinations. Introduction Rail lines are one of the most important means of transportation in the tourism sector. The device that experts believe is the safest form of transportation. Railways, on the other hand, reduce travel time compared to road transport and in some cases reduce travel costs, and therefore can be considered an important part of tourism. Tourist trains in Iran are not very old and in fact, since 2017 and shortly after the arrival of the first foreign tourist trains in Iran, they have started moving on the Iranian railway. This interesting tourist idea has been implemented on the ‘Tehran-Savadkuh-Sari’ and ‘Tehran-Zavareh’ routes so far. The Lorestan recreational train also runs on the ‘Tehran-Lorestan-Khuzestan’ route. In addition, for some time now, the doors of Tehran Railway Station have been open to tourists to review the historical file of this station, which is also registered in the list of national monuments. Methodology The present research is of applied type using the descriptive-analytical method. The analysis unit of this research was the passengers of the Lorestan tourist train and the sample population was the number of tourists who traveled to Lorestan by this train. The sampling was done in a completely purposeful manner based on the probabilistic and snowball sampling methods. The number of sample members was 30 and a questionnaire was used for collecting the data. Analysis of the obtained data was performed using Smart pls software and Wizard scenario. Discussion The most effective components of the origin-destination programs of the tourist train are related to the components of local attractions by 94%, impact intensity (route coefficient) by 97%, satisfaction levels by 93%, impact intensity by 96%, behavioral image by 92%, impact intensity by 96%, and creativity by 92%. Also, the highest satisfaction calculated in the factor loads section was related to paying attention to the expectations and demands of tourists, up-to-date tourism at the destination, attractive travel destinations, and employing trained and experienced staff. Conclusion The more local attractions are paid attention to at the destination level and the investment platforms are made in them, the more they can attract tourists and increase the frequency of tourists. Tourists have also attached great importance to tourism brands and popular tourist destinations. Also, the exploitation and introduction of more and more historical places, customs, and local and original lifestyles have created a pleasant and enjoyable aspect for the tourists. In contrast, the components of the quality of the tourism process and cheap tourism services have been less important in repeating the travel by tourists than other components. It should be noted that the polite and respectful attitude of citizens toward tourists and the well-being of tourism at the destination have the most important coefficient. In the next step, we can mention trained people and appropriate parks, advice and referrals from others, positive attitudes to travel again, and providing information through the media. Keywords: Tourist Train, Service Quality, Tourist Loyalty, Travel Drivers. References - Adongo, A. C., Amenumey, E. K., Kumi-Kyereme, A., & Dube, E. (2021). Beyond fragmentary: A proposed measure for travel vaccination concerns. Journal of Tourism Management, 83, 104180. - Alegre, J., & Magdalena, C. (2010). Tourist expenditure and quality: Why repeat tourists can spend less than first-timers. Journal of Tourism Economics, 16(3), 517-533. - Bassols-Gardella, N., & Coromina, L. (2022). The perceived image of multi-asset tourist destinations: Investigating congruence across different content types. Journal of Service Business, 16(1), 57-75. - Castillo-Manzano, J. I., Castro-Nuño, M., López-Valpuesta, L., Pedregal-Tercero, D. J., & Garrido-Michó, J. M. (2018). High speed rail: Fast tracking tourism in the EU?. Annals of Tourism Research, 71, 64-66. - Daleela, M., & Siti Nor, K. A. (2020). First-time and repeat visitors to Langkawi Island, Malaysia. Procedia Economics and Finance, 35, 622-631. - Dayour, F., Ghana, W., Adongo, C. A., Amuquandoh, F. E., & Adam, I. (2020). Managing the COVID-19 crisis: Coping and post-recovery strategies for hospitality and tourism businesses in Ghana. Journal of Hospitality and Tourism Insights, 4(4), 373-392. - Delbecq, A. L., Van de Ven, A. H., & Gustafson, D. H. (1975). Group techniques for program planning: A guide to nominal group and Delphi processes. Glenview, Illinois: Scott, Foresman. - Deng, T., Gan, C., Du, H., Hu, Y., & Wang, D. (2021). Do high speed rail configurations matter to tourist arrivals? Empirical evidence from China’s prefecture-level cities. Journal of Research in Transportation Economics, 90, 100952. - Do Valle, P. O., Silva, J. A., Mendes, J., & Guerreiro, M. (2006). Tourist satisfaction and destination loyalty intention: A structural and categorical analysis. International Journal of Business Science and Applied Management, 1(1), 25-44. - Jensen, M. T., & Larsen, J. (2021). Rail tourism transitions: A sociological framework. Annals of Tourism Research, 87(C). - Jin, S., Yang, J., Wang, E., & Liu, J. (2020). The influence of high-speed rail on ice–snow tourism in northeastern China. Journal of Tourism Management, 78, 104070 - Kartsan, P. (2022). Transport communication and organization of transport services in the tourism sector. Transportation Research Procedia, 61, 180-184. - Łapkoa, A., & Panasiuk, A. (2019). Water tourism as a recipient of transport services on the example of Szczecin. Transportation Research Procedia, 39, 290–299. - Law, C. C., Zhang, Y., Gow, J., & Vu, X. B. (2022). Dynamic relationship between air transport, economic growth and inbound tourism in Cambodia, Laos, Myanmar and Vietnam. Journal of Air Transport Management, 98, 102161. - Maghrifani, D., Liu, F., & Sneddon, J. (2022). Understanding potential and repeat visitors’ travel intentions: The roles of travel motivations, destination image, and visitor image congruity. Journal of Travel Research, 61(5), 1121-1137. - Meleddu, M., Paci, R., & Pulina, M. (2015). Repeated behaviour and destination loyalty. Journal of Tourism Management, 50, 159-171. - Mohamad, M., Ghani, N. I., Abd Halim, M. S., & Loganathan, N. (2015). Effects of the Malaysian travel destination brand image on tourist satisfaction and destination loyalty. American-Eurasian Journal of Agricultural & Environmental Sciences (Tourism & Environment, Social and Management Sciences), 15, 61-72. - Nepal, S. K. (2020). Adventure travel and tourism after COVID-19 – business as usual or opportunity to reset?. Journal of Tourism Geographies, 22(3), 1-5. - Qiu, R. T., Park, J., Li, S., & Song, H. (2020). Social costs of tourism during the COVID-19 pandemic. Annals of Tourism Research, 84, 102994. - Romao, J., & Bi, Y. (2021). Determinants of collective transport mode choice and its impacts on trip satisfaction in urban tourism. Journal of Transport Geography, 94, 103094. - Sariego-López, I., Moreno-Melgarejo, A., & Garcia-Moreno, M. B. (2020). Repeat visitors in Cantabria (Spain): Exploring tourist behavior. Revista ESPACIOS, 41(17), 13. - Smith, S., Costello, C., & Muenchen, R. A. (2010). Influence of push and pull motivations on satisfaction and behavioral intentions within a culinary tourism event. Journal of Quality Assurance in Hospitality and Tourism, 11(1), 17-35. - Sorupia, E. (2005). Rethinking the role of transportation in tourism. Proceedings of the Eastern Asia Society for Transportation Studies, 5(11), 1767-1777. - Stahl, N. N., & Stahl, R. J. (1991). We can agree after all! Achieving consensus for a critical thinking component of a gifted program using the Delphi technique. Journal of Roeper Review, 14(2), 79-88. - Šulc, I., & Fuerst-Bjeliš, B. (2021). Changes of tourism trajectories in (post) covidian world: Croatian perspectives. Journal of Research in Globalization, 3, 100052. - Tan, W. K. (2017). Repeat visitation: A study from the perspective of leisure constraint, tourist experience, destination images, and experiential familiarity. Journal of Destination Marketing and Management, 6(3), 233-242. - Ye, Y., Su, C. H., Tsai, C. H., & Hung, J. L. (2020). Motivators of attendance at eco-friendlyevents. Journal of Convention and Event Tourism, 21(5), 417-437. - Yi, X., Fu, X., Jin, W., & Okumus, F. (2018). Constructing a model of exhibition attachment: Motivation, attachment, and loyalty. Journal of Tourism Management, 65, 224–236.

https://gep.ui.ac.ir/article_26540_34ca672707314668051c55a0cfa29a36.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Investigating the Key Effective Factors in Reviving Inefficient Urban Spaces with the Approach of Quality Improvement (Case Study: Bisim Neighborhood of Zanjan) Investigating the Key Effective Factors in Reviving Inefficient Urban Spaces with the Approach of Quality Improvement (Case Study: Bisim Neighborhood of Zanjan) 69 86 26785 10.22108/gep.2022.130297.1455 FA Pari Alavi Ph.D. candidate, Department of Architecture, Zanjan branch, Islamic Azad University, Zanjan, Iran Hooman Sobouti Assistant professor, Department of Architecture, Zanjan branch, Islamic Azad University, Zanjan, Iran 0000-0001-9797-1249 Majid Shahbazi Assistant professor, Department of Architecture, Zanjan branch, Islamic Azad University, Zanjan, Iran Journal Article 2021 08 31 Introduction One of the problems faced by contemporary cities is the existence of inefficient urban structures, which often cause instability in various dimensions and make urban neighborhoods encounter serious challenges. Despite the existence of "theoretical foundations", unfortunately, the "comprehensive approach and attitude" in dealing with these spaces has not been able to provide a basic solution to organize the chaotic and disturbed faces of these urban neighborhoods. Perhaps, the lack of processing theoretical bases in addition to security has distorted their historical and architectural identities to a great extent. Considering the necessity of reviving these types of spaces, the current study aimed to improve the environmental qualities of such neighborhoods and find effective quality criteria in reviving inefficient spaces. Methodology In this applied research, which was prepared using a descriptive-analytical method, the five "physical", "social", "functional", "economic" and "management" factors were evaluated by surveying the residents of the studied neighborhood and performing a one-sample T-test. Then, they were prioritized by using the factor analysis test. The research statistical population included the residents of Bisim Neighborhood in Zanjan and the statistical sample consisted of the 20-year-old residents of this neighborhood. Discussion The results indicated the low level of environmental quality in Bisim Neighborhood and the residents' dissatisfaction with its poor condition. Thus, improvement of this situation required attention to the residents' preferences and their mental perceptions. The evaluations also showed that the "economic" factor with a weight of 0.621 was the first priority; the "functional" and "physical" factors with a weight of 0.592 were in the second place; and the "managerial" and "social" factors with the weights of 0.583 and 0.507 were in the next ranks, respectively. From the points of view of the residents of Bisim Neighborhood, the components of "housing price", "presence of spaces", "repair and maintenance of buildings", "spatial organization and permeability", and "access and spatial communication" respectively had the greatest impacts on improving the environmental quality of this neighborhood. Conclusion Since paying attention to the physical, social, economic, functional, and management dimensions are necessary and complementary to each other in order to improve the condition of inefficient tissues, in this research, the effective factors in improving the environmental quality in inefficient urban spaces were extracted from the theoretical bases and research literature. They were investigated after being implemented in the Bisim Neighborhood of Zanjan City. The results of the assessment of these factors indicated the residents' dissatisfaction with the poor condition of Bisim Neighborhood. The values obtained from the results of the one-sample T-test also showed the fact that this neighborhood was at a low level of environmental quality and improving this situation required paying attention to the residents' preferences and their mental perceptions. Keywords: environmental quality, wornout texture, inefficient spaces, residents' preferences, Bisim Neighborhood of Zanjan References - Azhar, J. (2019). Exploring the Potential of Urban Leftover Spaces, (Unpublished doctoral Philosophy). Victoria University, Wellington, Ph.D. - Filip, S. & Cocean, P. (2021), Urban industrial brownfields: constraints and Opportunities in Romania, Carpathian Journal of Earth and Environmental Sciences, Vol. 7, No. 4, p. 155 – 164 - Thomson, G. & Newman, P. (2018).Urban fabrics and urban metabolism–from sustainable to regenerative cities. Resources, Conservation and Recycling, 132, 218-229. - Basova1, S. Sopirova1, A. and Kristianova1, K. (2019). Potential of Recycling Urban Territories,IOP Conference Series: Materials Science and Engineering, 471, 9. Introduction One of the problems faced by contemporary cities is the existence of inefficient urban structures, which often cause instability in various dimensions and make urban neighborhoods encounter serious challenges. Despite the existence of "theoretical foundations", unfortunately, the "comprehensive approach and attitude" in dealing with these spaces has not been able to provide a basic solution to organize the chaotic and disturbed faces of these urban neighborhoods. Perhaps, the lack of processing theoretical bases in addition to security has distorted their historical and architectural identities to a great extent. Considering the necessity of reviving these types of spaces, the current study aimed to improve the environmental qualities of such neighborhoods and find effective quality criteria in reviving inefficient spaces. Methodology In this applied research, which was prepared using a descriptive-analytical method, the five "physical", "social", "functional", "economic" and "management" factors were evaluated by surveying the residents of the studied neighborhood and performing a one-sample T-test. Then, they were prioritized by using the factor analysis test. The research statistical population included the residents of Bisim Neighborhood in Zanjan and the statistical sample consisted of the 20-year-old residents of this neighborhood. Discussion The results indicated the low level of environmental quality in Bisim Neighborhood and the residents' dissatisfaction with its poor condition. Thus, improvement of this situation required attention to the residents' preferences and their mental perceptions. The evaluations also showed that the "economic" factor with a weight of 0.621 was the first priority; the "functional" and "physical" factors with a weight of 0.592 were in the second place; and the "managerial" and "social" factors with the weights of 0.583 and 0.507 were in the next ranks, respectively. From the points of view of the residents of Bisim Neighborhood, the components of "housing price", "presence of spaces", "repair and maintenance of buildings", "spatial organization and permeability", and "access and spatial communication" respectively had the greatest impacts on improving the environmental quality of this neighborhood. Conclusion Since paying attention to the physical, social, economic, functional, and management dimensions are necessary and complementary to each other in order to improve the condition of inefficient tissues, in this research, the effective factors in improving the environmental quality in inefficient urban spaces were extracted from the theoretical bases and research literature. They were investigated after being implemented in the Bisim Neighborhood of Zanjan City. The results of the assessment of these factors indicated the residents' dissatisfaction with the poor condition of Bisim Neighborhood. The values obtained from the results of the one-sample T-test also showed the fact that this neighborhood was at a low level of environmental quality and improving this situation required paying attention to the residents' preferences and their mental perceptions. Keywords: environmental quality, wornout texture, inefficient spaces, residents' preferences, Bisim Neighborhood of Zanjan References - Azhar, J. (2019). Exploring the Potential of Urban Leftover Spaces, (Unpublished doctoral Philosophy). Victoria University, Wellington, Ph.D. - Filip, S. & Cocean, P. (2021), Urban industrial brownfields: constraints and Opportunities in Romania, Carpathian Journal of Earth and Environmental Sciences, Vol. 7, No. 4, p. 155 – 164 - Thomson, G. & Newman, P. (2018).Urban fabrics and urban metabolism–from sustainable to regenerative cities. Resources, Conservation and Recycling, 132, 218-229. - Basova1, S. Sopirova1, A. and Kristianova1, K. (2019). Potential of Recycling Urban Territories,IOP Conference Series: Materials Science and Engineering, 471, 9.

https://gep.ui.ac.ir/article_26785_f47b10c67f2fabeccb8a62fc5480c553.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Potential Assessment of Areas Prone to Geotourism Development and Providing Optimal Patterns of Visiting Geosites in Kamyaran City Potential Assessment of Areas Prone to Geotourism Development and Providing Optimal Patterns of Visiting Geosites in Kamyaran City 87 102 26676 10.22108/gep.2022.131774.1475 FA Atrin Ebrahimi Ph.D. Candidate in Geomorphology, Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran Davood Mokhtari Professor of Geomorphology, Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran Shahram Roostaei Professor of Geomorphology, Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Irans Journal Article 2021 12 07 Introduction The term geosite is a new concept in tourism land and is very important in understanding the geological history and historical geological evolution of a region. Geosites are landforms that have gained special value over time due to human awareness, thus creating the necessary context for the development of tourism activities and special infrastructure in an area. Geosites may exist individually or in broader perspectives. They may be altered, damaged, or even destroyed by the effects of human activities. Different regions have different potentials in terms of geosite diversity and consequently the development of geotourism depends on geological, geomorphological, and hydro-climatic factors. One of the areas that has high potential in the development of the geotourism and tourism industry is the karst areas. Kamyaran city in Kurdistan province is one of the areas located in karst formations. Kamyaran city, despite having developed karst areas, types of landscapes, rivers, and springs, has a high potential for the development of the geotourism industry and geostourism. Despite the natural conditions in the region, it seems that more attention has been paid mainly to cultural issues. Due to the importance of the issue, in this study, the geotourism situation of Kamyaran city is studied and optimal geotourism models in this city have been presented. Materials and Methods In this research, in order to achieve the desired goals, library information, interviews, field visits, the digital model height of 30 meters, geological maps 1: 100000 and topographic maps 1: 50000 have been used. ArcGIS and SPSS software are the research tools. Also in this research, the Kubalikova model has been used to evaluate geosites and fuzzy logic and ANP models have been used to identify areas prone to geotourism development. This research has been done in three stages. In the first stage, using field visits, interviews, and library studies, the geosites of the region were identified and evaluated using the Kubalikova method. In the second stage, 9 parameters (the distance from the river, landscape, urban areas, communication lines, cultural sites, distance geosites, altitude, slope as well as vulnerability potential) and fusion logic integrated model and AHP were used to identify areas prone to geotourism development in Kamyaran city. In the third stage, based on the results obtained from the previous stages and the location of geosites, appropriate models for visiting geosites were presented. Discussion of Results and Conclusions The results of the evaluation of geosites based on the Kubalikova model indicate that among the geosites of the region, Palangan valley has the highest score with a total of 10.25 points, followed by Gavoshan dam, and Tangivar River with 10 and 75 points, respectively. The results also indicate that the geosites of the western regions of Kamyaran city had the highest score in terms of the Kubalikova method. In this study, after evaluating geosites, areas prone to geotourism development have been identified. Based on the results, the southern and western parts of Kamyaran city due to the distribution of potential geosites, the presence of permanent rivers, proximity to cultural sites, and proximity to communication lines had a great potential for geotourism development goals. According to the results, Palangan and Tangivar River geosites have the highest potential for geotourism development goals because they have a high score in terms of evaluation methods and are also in classes prone to geotourism development. Also, in this study, based on the location of geosites in the study area, 6 patterns were presented for visiting and planning for geotourism development goals. The results of evaluating the scores of geosites obtained in different models indicate that the total averages percentage of scores of the visited geosites were 26.25, 33.75, 30.75, 23.25, 13, and 71.75 in the second, third, fourth, fifth, and sixth patterns, respectively. Keywords: Geotourism, Kubalikova, Geotourism Routes, Kamyaran City. References - Carrión Mero, P., Herrera Franco, G., Briones, J., Caldevilla, P., Domínguez-Cuesta, M. J., & Berrezueta, E. (2018). Geotourism and local development based on geological and mining sites utilization, Zaruma-Portovelo, Ecuador. Geosciences, 8(6), 205. - Cheablam, O., Tansakul, P., Nantakat, B., & Pantaruk, S. (2021). Assessment of the geotourism resource potential of the Satun UNESCO global geopark, Thailand. Geoheritage, 13(4), 1-16. - Comanescu, L., Nedelea, A., & Dobre, R. (2012). The Evaluation of Geomorphosites from the Ponoare protected area. Journal of Geography, 11(1), 54-61. - Kubalíková, L., & Kirchner, K. (2016). Geosite and geomorphosite assessment as a tool for geoconservation and geotourism purposes: a case study from Vizovická vrchovina Highland (eastern part of the Czech Republic). Geoheritage, 8(1), 5-14. - Lugeri, F. R., Amadio, V., Bagnaia, R., Cardillo, A., & Lugeri, N. (2011). Landscapes and wine production areas: A geomorphological heritage. Geoheritage, 3(3), 221-232. - Migon, P., & Pijet-Migoń, E. (2017). Viewpoint geosites - values, conservation and management issues. Proceedings of the Geologists' Association, 128(4), 511-522. - Ovreiu, A. B., Comănescu, L., Bărsoianu, I. A., & Nedelea, A. (2019). Evaluating geomorphosites and the geomorphological hazards that impact them: Case study—Cozia massif (Southern Carpathians, Romania). Geoheritage, 11(3), 1067–1087. - Soladti, M., Coratza, P., Galve, J., & Tonelli P. (2012). Recognition and assessment of sinkholes as geosites: Lessons from the Island of Gozo (Malta). Quaestiones Geographicae, 31(1), 25- 35. - Strat, D. (2016). Wetlands – as significant features of the salt karst landscape in the Meledic Plateau, Vrancea Subcarpathians, Romania. Procedia Environmental Sciences, 32, 59-69 - Tirla, L., & Vijulie, I. (2013). Structural–tectonic controls and geomorphology of the karst corridors in alpine limestone ridges: Southern Carpathians, Romania. Geomorphology Journal, 197, 123–136. - Warowna, J., Zgłobicki, W., Gajek, G., Telecka, M., Kołodyńska, R., & Zieliński, P. (2014). Geomorphosite assessment in the proposed geopark vistula river gap (Poland). Quaestions Geographicae, 33(3), 173-181. Introduction The term geosite is a new concept in tourism land and is very important in understanding the geological history and historical geological evolution of a region. Geosites are landforms that have gained special value over time due to human awareness, thus creating the necessary context for the development of tourism activities and special infrastructure in an area. Geosites may exist individually or in broader perspectives. They may be altered, damaged, or even destroyed by the effects of human activities. Different regions have different potentials in terms of geosite diversity and consequently the development of geotourism depends on geological, geomorphological, and hydro-climatic factors. One of the areas that has high potential in the development of the geotourism and tourism industry is the karst areas. Kamyaran city in Kurdistan province is one of the areas located in karst formations. Kamyaran city, despite having developed karst areas, types of landscapes, rivers, and springs, has a high potential for the development of the geotourism industry and geostourism. Despite the natural conditions in the region, it seems that more attention has been paid mainly to cultural issues. Due to the importance of the issue, in this study, the geotourism situation of Kamyaran city is studied and optimal geotourism models in this city have been presented. Materials and Methods In this research, in order to achieve the desired goals, library information, interviews, field visits, the digital model height of 30 meters, geological maps 1: 100000 and topographic maps 1: 50000 have been used. ArcGIS and SPSS software are the research tools. Also in this research, the Kubalikova model has been used to evaluate geosites and fuzzy logic and ANP models have been used to identify areas prone to geotourism development. This research has been done in three stages. In the first stage, using field visits, interviews, and library studies, the geosites of the region were identified and evaluated using the Kubalikova method. In the second stage, 9 parameters (the distance from the river, landscape, urban areas, communication lines, cultural sites, distance geosites, altitude, slope as well as vulnerability potential) and fusion logic integrated model and AHP were used to identify areas prone to geotourism development in Kamyaran city. In the third stage, based on the results obtained from the previous stages and the location of geosites, appropriate models for visiting geosites were presented. Discussion of Results and Conclusions The results of the evaluation of geosites based on the Kubalikova model indicate that among the geosites of the region, Palangan valley has the highest score with a total of 10.25 points, followed by Gavoshan dam, and Tangivar River with 10 and 75 points, respectively. The results also indicate that the geosites of the western regions of Kamyaran city had the highest score in terms of the Kubalikova method. In this study, after evaluating geosites, areas prone to geotourism development have been identified. Based on the results, the southern and western parts of Kamyaran city due to the distribution of potential geosites, the presence of permanent rivers, proximity to cultural sites, and proximity to communication lines had a great potential for geotourism development goals. According to the results, Palangan and Tangivar River geosites have the highest potential for geotourism development goals because they have a high score in terms of evaluation methods and are also in classes prone to geotourism development. Also, in this study, based on the location of geosites in the study area, 6 patterns were presented for visiting and planning for geotourism development goals. The results of evaluating the scores of geosites obtained in different models indicate that the total averages percentage of scores of the visited geosites were 26.25, 33.75, 30.75, 23.25, 13, and 71.75 in the second, third, fourth, fifth, and sixth patterns, respectively. Keywords: Geotourism, Kubalikova, Geotourism Routes, Kamyaran City. References - Carrión Mero, P., Herrera Franco, G., Briones, J., Caldevilla, P., Domínguez-Cuesta, M. J., & Berrezueta, E. (2018). Geotourism and local development based on geological and mining sites utilization, Zaruma-Portovelo, Ecuador. Geosciences, 8(6), 205. - Cheablam, O., Tansakul, P., Nantakat, B., & Pantaruk, S. (2021). Assessment of the geotourism resource potential of the Satun UNESCO global geopark, Thailand. Geoheritage, 13(4), 1-16. - Comanescu, L., Nedelea, A., & Dobre, R. (2012). The Evaluation of Geomorphosites from the Ponoare protected area. Journal of Geography, 11(1), 54-61. - Kubalíková, L., & Kirchner, K. (2016). Geosite and geomorphosite assessment as a tool for geoconservation and geotourism purposes: a case study from Vizovická vrchovina Highland (eastern part of the Czech Republic). Geoheritage, 8(1), 5-14. - Lugeri, F. R., Amadio, V., Bagnaia, R., Cardillo, A., & Lugeri, N. (2011). Landscapes and wine production areas: A geomorphological heritage. Geoheritage, 3(3), 221-232. - Migon, P., & Pijet-Migoń, E. (2017). Viewpoint geosites - values, conservation and management issues. Proceedings of the Geologists' Association, 128(4), 511-522. - Ovreiu, A. B., Comănescu, L., Bărsoianu, I. A., & Nedelea, A. (2019). Evaluating geomorphosites and the geomorphological hazards that impact them: Case study—Cozia massif (Southern Carpathians, Romania). Geoheritage, 11(3), 1067–1087. - Soladti, M., Coratza, P., Galve, J., & Tonelli P. (2012). Recognition and assessment of sinkholes as geosites: Lessons from the Island of Gozo (Malta). Quaestiones Geographicae, 31(1), 25- 35. - Strat, D. (2016). Wetlands – as significant features of the salt karst landscape in the Meledic Plateau, Vrancea Subcarpathians, Romania. Procedia Environmental Sciences, 32, 59-69 - Tirla, L., & Vijulie, I. (2013). Structural–tectonic controls and geomorphology of the karst corridors in alpine limestone ridges: Southern Carpathians, Romania. Geomorphology Journal, 197, 123–136. - Warowna, J., Zgłobicki, W., Gajek, G., Telecka, M., Kołodyńska, R., & Zieliński, P. (2014). Geomorphosite assessment in the proposed geopark vistula river gap (Poland). Quaestions Geographicae, 33(3), 173-181.

https://gep.ui.ac.ir/article_26676_da25c8adcc4d35d22410377b7ffedd69.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Analysis of the Relationship between Watching TV and Increasing Environmental Literacy Based on the Three Dimensions of Knowledge, Attitude, and Behavior (Case Study: Tehran Citizens) Analysis of the Relationship between Watching TV and Increasing Environmental Literacy Based on the Three Dimensions of Knowledge, Attitude, and Behavior (Case Study: Tehran Citizens) 103 118 26784 10.22108/gep.2022.133320.1515 FA Fatemeh Homayounie Moghadam Ph.D. student in Communication Sciences, Department of Communication Sciences, Faculty of Literature, Humanities and Social Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran Amir Masoud Amir Mazaheri Associate professor, Department of Sociology and Social Sciences, Faculty of Social Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran Akbar Nasrollahi Kasmani Assistant professor, Department of Media-Public Relation, Faculty of Communication Sciences and Media Studies, Central Tehran Branch, Islamic Azad University, Tehran, Iran Mohammad‌ Reza Rasouli Associate professor, Department of Media-Culture, Faculty of Communication Sciences and Media Studies, Central Tehran Branch, Islamic Azad University, Tehran, Iran Journal Article 2022 04 17 Abstract: Today, environmental issues are one of the serious problems of societies and human beings can be effective in protecting it with awareness. Television as an attractive medium can be effective in raising awareness. This study aimed to analyze the relationship between watching TV and increasing environmental literacy based on the 3 dimensions of knowledge, attitude, and behavior. This research was a survey in terms of nature and method. Its statistical population included the citizens of Tehran. The sample size was determined to consist of 384 people by using Cochran's formula, which was done by the two-stage cluster sampling. A researcher-made questionnaire was used to collect the data and SPSS22 software was applied to analyze them. The questionnaire validity was evaluated in a formal way and its reliability was determined at the knowledge, attitude, and behavior levels of 0.91, 0.84, and 0.78 by using "Cronbach's alpha coefficient", respectively. Pearson’s correlation test was used to analyze the data. The findings showed that 62% of the respondents were aware of television. The values of the correlation coefficient for the dimensions of knowledge, attitude, behavior, and environmental literacy were respectively 0.648, 0.679, 0.599, and 0.694, which confirmed the existence of a significant relationship between them. This meant that watching TV had a significant relationship with the acquisition of knowledge, attitude, and behavior. In general, watching TV explained strengthening of environmental literacy. To achieve a better result, it is expected that the national media make the necessary policies to strengthen environmental knowledge, attitude, and behavior. Introduction: Today, the public must be aware of the depth of the catastrophe because of their role in solving environmental problems. There is no doubt that the transition to global sustainability requires environmental literacy, which is a change in human knowledge, attitude, and behavior towards the environment. Environmental knowledge includes information about environmental problems and to improve the situation and perform the activities successfully. Environmental attitude is a relatively stable set of feelings, beliefs, and behavioral preparations of individuals and groups that are rooted in the value system of individuals. Also, environmental behavior is a set of individual reactions towards the environment in the society. As the Rio Summit, dubbed the 21st Century Environmental Sustainability Program, the importance of media in education is revealed. The mass media, especially television, can influence the audience's emotions by informing them about their environmental responsibilities via broadcasting, transmitting, and using environmental messages with the power of images. As mentioned in Paragraph A of Article 189 of the Law on the Fifth Development Plan, the correct information and environmental culture are emphasized by the state media, especially the Radio and Television. Accordingly, the purpose of this study was to investigate the relationship between watching television and increasing the environmental literacy of Tehran citizens. In this study, we sought to answer the question of whether there was a relationship between watching TV programs and increasing environmental literacy. The points that theoretically increase the importance of this research were measuring the environmental literacy of Tehran citizens through the demographic variables of age, sex, and education and the rate of watching programs with regard to television networks leading to their increased environmental literacy. The subject of environmental literacy should be one of the priorities to be considered by network managers, groups, and TV program producers as mentioned in the development documents. This issue can envisage the decision and policy makers’ tasks in the field of environment in the media horizon. In this regard, further communication must be made between the Environmental Protection Organization, experts and thinkers, government officials, and Radio and Television Organization to educate and inform TV audience and the general public as a large part of participants in environmental protection. A review of the results of other related studies indicated that all the 3 levels of knowledge, attitude, and behavior were researched in some studies and the relationship between media and environmental literacy was confirmed. Overall, the research findings showed that using the capacity of the media to attract public opinion to the issue of the environment and the content provided by the media were effective in increasing the audience’s environmental literacy. Methodology: In this research, a survey method was used. The main tool for data collection was a researcher-made questionnaire. Knowledge, attitude, and behavior were measured based on the demographic characteristics with 45 items in a 6-point Likert scale from not at all (1) to very high agreement (6). The questionnaire validity was determined by using a survey and obtaining suggestions from the media and environmental experts. To determine the questionnaire reliability, Cronbach's alpha coefficient was applied, the values of which were 0.91, 0.84, and 0.78 at the levels of knowledge, attitude, and behavior, respectively. The statistical population of this study included Tehran citizens aged ≥18 living in 22 regions. To estimate the sample size, Cochran's formula was selected with 95% error. Accordingly, the sample size was estimated to include 384 people and 400 questionnaires were presented to create a safe margin. They were reviewed and then coded using Spss software, version 22. Then, the research was conducted based on the need for the outputs related to the descriptive and inferential statistics in order to answer the questions and verify the hypotheses. The statistical analysis was done through descriptive statistics (mean) and inferential statistics (Pearson’s correlation test). Discussion: According to the descriptive statistics, 49 and 51% of the respondents were male and female, respectively. The scores of environmental literacy for the men and women were 0.39 and 2.28, respectively. In terms of age, the respondents were 35-39 years old and the score of environmental literacy in this group was 2.97. The data revealed that 12.7, 26.8, 4.5, and 16% of the respondents had undergraduate degrees and diplomas, postgraduate degrees, bachelor's degrees, and master's degrees, respectively. Their average scores of environmental literacy were 2.78, 2.60, 2.53, and 2.60, respectively. Regarding the use of information sources, 62% of the respondents were found to be aware of television, most of whom (82%) watched Channel 3. By referring to the total average, the general transfer of environmental knowledge, attitude, behavior, and literacy to the citizens through television showed the values of 2.41, 2.97, 2.78, and 2.66, respectively. In the hypothesis test, a significant relationship was found between watching TV and increasing environmental literacy in the dimensions of knowledge, attitude, behavior, and general environmental literacy through Pearson’s correlation coefficient. The coefficients in the dimensions of knowledge, attitude, behavior, and environmental literacy were 0.648, 0.679, 0.599, and 0.694 at the significance level of 0.000, which confirmed the existence of as a significant factor. In sum, all the 3 dimensions of the independent variables explained the relationship between watching television programs and environmental content and messages affecting on the citizens’ increase of environmental literacy. Conclusion: This article examined the relationship between watching TV and environmental literacy in terms of knowledge, attitude, and behavior by using a survey method. The statistical population included the citizens of Tehran. In general, the results were in line with the internal and external backgrounds of the previous studies and the theories examined. Due to the wide coverage of audience and use of informal institution of education, the transfer of knowledge through it seemed to be the easiest way because people tended to choose the easiest way to acquire environmental literacy. The audience or recipients of media messages as one of the communication elements could participate in environmental protection by gaining environmental literacy and play the role of aware activists. This had a greater impact beyond the responsibilities of organizations, such as environmental organizations and groups. For greater effectiveness, it is expected to formulate an appropriate strategy and policy to produce different types of television programs on the subject of environment and use the experts’ opinions in this field, while addressing problems, such as energy crisis, water crisis, and natural resource degradation. Transferring environmental knowledge, promoting nature-friendliness, creating a deep insight and understanding, and trying to strengthen environmental behavior for attracting environmental protection partnerships by teaching necessary techniques and skills can be the practical results of future research. Keywords: environmental literacy, television, citizens, environment References - Dobson, A. (2007). Environmental Citizenship: Towards Sustainable Development, Sust. Dev. Vol. 15, pp276–285 doi:10.1002/sd. 344 - Cumba Castro, E.A.(2020).Environmental education in the television media. Casestudy: Oromar TV, Alteridad,Vol. 15, No. 1,pp115-126. doi: 10.17163/alt.v15n1.2020.10 - Fote Roba,T.(2012) Media and environmental awareness: A geographical study in kembarozone, southern Ethiopia. Master of arts in the geography at the university of south Africa - Holbert, R.L., Kwak, N., Dhavan, V.S. (2003) Enviromental Concern, Patterns ofTelevision Viewing, and Pro-Envromental Behaviors: Integrating Model of Media Consumptionand Effects, Journal of Broadcasting & Electronic Media, 47,2, pg.177.doi: 10.1207/s15506878jobem4702_2 - Jharotia, A.K . (2018).Role of Media in Enhancement of Environmental Awareness, Conference: Power of Media: Shaping the Future. At:Tecnia Auditorium, New Delhi, pp. 1-11. - Kanozia, R.(2020). Promoting Environmental Literacy through Media: An Exploratory Studyof Punjab, India, Researchergate, pp1-22 Abstract: Today, environmental issues are one of the serious problems of societies and human beings can be effective in protecting it with awareness. Television as an attractive medium can be effective in raising awareness. This study aimed to analyze the relationship between watching TV and increasing environmental literacy based on the 3 dimensions of knowledge, attitude, and behavior. This research was a survey in terms of nature and method. Its statistical population included the citizens of Tehran. The sample size was determined to consist of 384 people by using Cochran's formula, which was done by the two-stage cluster sampling. A researcher-made questionnaire was used to collect the data and SPSS22 software was applied to analyze them. The questionnaire validity was evaluated in a formal way and its reliability was determined at the knowledge, attitude, and behavior levels of 0.91, 0.84, and 0.78 by using "Cronbach's alpha coefficient", respectively. Pearson’s correlation test was used to analyze the data. The findings showed that 62% of the respondents were aware of television. The values of the correlation coefficient for the dimensions of knowledge, attitude, behavior, and environmental literacy were respectively 0.648, 0.679, 0.599, and 0.694, which confirmed the existence of a significant relationship between them. This meant that watching TV had a significant relationship with the acquisition of knowledge, attitude, and behavior. In general, watching TV explained strengthening of environmental literacy. To achieve a better result, it is expected that the national media make the necessary policies to strengthen environmental knowledge, attitude, and behavior. Introduction: Today, the public must be aware of the depth of the catastrophe because of their role in solving environmental problems. There is no doubt that the transition to global sustainability requires environmental literacy, which is a change in human knowledge, attitude, and behavior towards the environment. Environmental knowledge includes information about environmental problems and to improve the situation and perform the activities successfully. Environmental attitude is a relatively stable set of feelings, beliefs, and behavioral preparations of individuals and groups that are rooted in the value system of individuals. Also, environmental behavior is a set of individual reactions towards the environment in the society. As the Rio Summit, dubbed the 21st Century Environmental Sustainability Program, the importance of media in education is revealed. The mass media, especially television, can influence the audience's emotions by informing them about their environmental responsibilities via broadcasting, transmitting, and using environmental messages with the power of images. As mentioned in Paragraph A of Article 189 of the Law on the Fifth Development Plan, the correct information and environmental culture are emphasized by the state media, especially the Radio and Television. Accordingly, the purpose of this study was to investigate the relationship between watching television and increasing the environmental literacy of Tehran citizens. In this study, we sought to answer the question of whether there was a relationship between watching TV programs and increasing environmental literacy. The points that theoretically increase the importance of this research were measuring the environmental literacy of Tehran citizens through the demographic variables of age, sex, and education and the rate of watching programs with regard to television networks leading to their increased environmental literacy. The subject of environmental literacy should be one of the priorities to be considered by network managers, groups, and TV program producers as mentioned in the development documents. This issue can envisage the decision and policy makers’ tasks in the field of environment in the media horizon. In this regard, further communication must be made between the Environmental Protection Organization, experts and thinkers, government officials, and Radio and Television Organization to educate and inform TV audience and the general public as a large part of participants in environmental protection. A review of the results of other related studies indicated that all the 3 levels of knowledge, attitude, and behavior were researched in some studies and the relationship between media and environmental literacy was confirmed. Overall, the research findings showed that using the capacity of the media to attract public opinion to the issue of the environment and the content provided by the media were effective in increasing the audience’s environmental literacy. Methodology: In this research, a survey method was used. The main tool for data collection was a researcher-made questionnaire. Knowledge, attitude, and behavior were measured based on the demographic characteristics with 45 items in a 6-point Likert scale from not at all (1) to very high agreement (6). The questionnaire validity was determined by using a survey and obtaining suggestions from the media and environmental experts. To determine the questionnaire reliability, Cronbach's alpha coefficient was applied, the values of which were 0.91, 0.84, and 0.78 at the levels of knowledge, attitude, and behavior, respectively. The statistical population of this study included Tehran citizens aged ≥18 living in 22 regions. To estimate the sample size, Cochran's formula was selected with 95% error. Accordingly, the sample size was estimated to include 384 people and 400 questionnaires were presented to create a safe margin. They were reviewed and then coded using Spss software, version 22. Then, the research was conducted based on the need for the outputs related to the descriptive and inferential statistics in order to answer the questions and verify the hypotheses. The statistical analysis was done through descriptive statistics (mean) and inferential statistics (Pearson’s correlation test). Discussion: According to the descriptive statistics, 49 and 51% of the respondents were male and female, respectively. The scores of environmental literacy for the men and women were 0.39 and 2.28, respectively. In terms of age, the respondents were 35-39 years old and the score of environmental literacy in this group was 2.97. The data revealed that 12.7, 26.8, 4.5, and 16% of the respondents had undergraduate degrees and diplomas, postgraduate degrees, bachelor's degrees, and master's degrees, respectively. Their average scores of environmental literacy were 2.78, 2.60, 2.53, and 2.60, respectively. Regarding the use of information sources, 62% of the respondents were found to be aware of television, most of whom (82%) watched Channel 3. By referring to the total average, the general transfer of environmental knowledge, attitude, behavior, and literacy to the citizens through television showed the values of 2.41, 2.97, 2.78, and 2.66, respectively. In the hypothesis test, a significant relationship was found between watching TV and increasing environmental literacy in the dimensions of knowledge, attitude, behavior, and general environmental literacy through Pearson’s correlation coefficient. The coefficients in the dimensions of knowledge, attitude, behavior, and environmental literacy were 0.648, 0.679, 0.599, and 0.694 at the significance level of 0.000, which confirmed the existence of as a significant factor. In sum, all the 3 dimensions of the independent variables explained the relationship between watching television programs and environmental content and messages affecting on the citizens’ increase of environmental literacy. Conclusion: This article examined the relationship between watching TV and environmental literacy in terms of knowledge, attitude, and behavior by using a survey method. The statistical population included the citizens of Tehran. In general, the results were in line with the internal and external backgrounds of the previous studies and the theories examined. Due to the wide coverage of audience and use of informal institution of education, the transfer of knowledge through it seemed to be the easiest way because people tended to choose the easiest way to acquire environmental literacy. The audience or recipients of media messages as one of the communication elements could participate in environmental protection by gaining environmental literacy and play the role of aware activists. This had a greater impact beyond the responsibilities of organizations, such as environmental organizations and groups. For greater effectiveness, it is expected to formulate an appropriate strategy and policy to produce different types of television programs on the subject of environment and use the experts’ opinions in this field, while addressing problems, such as energy crisis, water crisis, and natural resource degradation. Transferring environmental knowledge, promoting nature-friendliness, creating a deep insight and understanding, and trying to strengthen environmental behavior for attracting environmental protection partnerships by teaching necessary techniques and skills can be the practical results of future research. Keywords: environmental literacy, television, citizens, environment References - Dobson, A. (2007). Environmental Citizenship: Towards Sustainable Development, Sust. Dev. Vol. 15, pp276–285 doi:10.1002/sd. 344 - Cumba Castro, E.A.(2020).Environmental education in the television media. Casestudy: Oromar TV, Alteridad,Vol. 15, No. 1,pp115-126. doi: 10.17163/alt.v15n1.2020.10 - Fote Roba,T.(2012) Media and environmental awareness: A geographical study in kembarozone, southern Ethiopia. Master of arts in the geography at the university of south Africa - Holbert, R.L., Kwak, N., Dhavan, V.S. (2003) Enviromental Concern, Patterns ofTelevision Viewing, and Pro-Envromental Behaviors: Integrating Model of Media Consumptionand Effects, Journal of Broadcasting & Electronic Media, 47,2, pg.177.doi: 10.1207/s15506878jobem4702_2 - Jharotia, A.K . (2018).Role of Media in Enhancement of Environmental Awareness, Conference: Power of Media: Shaping the Future. At:Tecnia Auditorium, New Delhi, pp. 1-11. - Kanozia, R.(2020). Promoting Environmental Literacy through Media: An Exploratory Studyof Punjab, India, Researchergate, pp1-22

https://gep.ui.ac.ir/article_26784_7a52cf86d29b016436e9f5ecd014b941.pdf

University of Isfahan Geography and Environmental Planning 2008-5362 33 3 2022 09 23 Analysis the Effect of Perception of flood Risk on the Resilience of Local Communities to Disasters (Study Area: Villages of Binalood County) Analysis the Effect of Perception of flood Risk on the Resilience of Local Communities to Disasters (Study Area: Villages of Binalood County) 119 138 26802 10.22108/gep.2022.132102.1480 FA Tahereh Sadeghloo Assistant professor, Department of Geography, Ferdowsi University of Mashhad, Mashhad,Mashhad, Iran Khadijeh Bozarjemehri Associate professor, Department of Geography, Ferdowsi University of Mashhad,Mashhad, Iran Soodabeh Ahmadi Ph.D. student in Geography and Rural Planning, Ferdowsi University of Mashhad,Mashhad, Iran Journal Article 2022 01 09 Abstract: Perception of risks and awareness of their effects based on the rational nature of human biology and his desire for survival always reduce the likelihood of hazards and improve preparedness for possible effects. In this regard, the present study sought to investigate and analyze the effects of perception of flood risk on the resilience of local communities in the rural families of Binalood County. This study was a descriptive-analytical research in terms of method and an applied research in terms of purpose. The unit of analysis in this study included 190 rural households in the area, which was determined by using the Cochran's formula with an error of 0.07. The results of the statistical analysis indicated that the indicators of emotional and cognitive dimensions of perception with the average values of 3.5 and 3.1 had the highest impacts and functional dimension with an average value of 2.5 had the lowest impact at the sample level. Also, the results of evaluating the effects of risk perception on the resilience by using the regression test indicated that among the dimensions of risk perception, cognitive dimension had the greatest effect on the resilience of the studied villages. On the other hand, based on the results of the analysis of variance, there was a significant difference between the resilience levels of groups with different levels of risk perception in the local communities. Moreover, the groups with moderate level of perception had the highest resilience among the other groups. Rural women also had a greater understanding of flooding and its probability of occurrence. As a result, they were more resilient. On the other hand, comparison of the levels of perception and resilience between the insured and uninsured people showed that the insured people had more perception and resilience than the uninsured people. Introduction: Findings of the effects of risk perception on resilience can be used to identify systems of resilience and adopt policies tailored to the levels of perception and resilience in local communities. Resilience of rural communities has become one of the most important issues in recent decades in such a way that many studies have been written about natural hazards and resilience of local communities. In recent years, disaster management in the programs of natural hazard reduction has tried to create and strengthen the characteristics of resilient communities. The aim of this study was to investigate and analyze the effects of flood risk perception on the resilience of local communities in rural families in Binalood, Mashhad. The results of comparing the villagers’ average opinions based on one-sample t-test showed that the values of T-statistic in all the indicators except the performance index were higher than the average value (3). All dimensions of the independent variable of risk perception and the dependent variable of resilience of communities to risks indicated their significant effects on measuring and evaluating the variable purpose. The results showed that the villagers were at a moderate level in terms of perception and resilience. Therefore, paying attention to increasing understanding of the local community in terms of their ability and resistance to dangers, such as floods, was one of the most important factors for realizing their confrontation with dangers. Thus, an important source of information, cognition, and awareness can determine the outcome of a general behavior like resilience. This study also showed that there was a relationship between the perception of local communities and resilience to disasters by 0.616%, which indicated the importance of the relationship between these two variables and their coordinated changes. On the other hand, the difference in the structures of perception of risks between the two groups of men and women (women’s higher perception of the risks) indicated the importance of the women’s role in such events. Their greater understanding of risks could lead to increased resilience and consequently less vulnerability. The results of perception and resilience between the insured and uninsured people showed inequality of the structures of perception of risks and resilience among these people, indicating a higher perception and resilience among the insured people. Multivariate regression was used to measure the effects of the different dimensions of risk perception on resilience. The results obtained from the villagers showed that the perception of the studied local community with the resilience index of 0.715 had a positive relationship with its strong intensity in terms of the coefficient of impact of variables on resilience. The cognitive dimension with an impact factor of 0.696 had the highest positive effect on resilience. In fact, perception of risks by more people increases their readiness to face natural hazards, thus accelerating resilience and consequently helping them cope with the risks and more quickly recover after them. Methodology: This research was based on a descriptive-analytical method and the research type was applied and quantitative. Thus, the field survey data were used to explain the research objectives. The main tool for data collection was a researcher-made questionnaire based on the indicators and variables extracted from theoretical topics. The study was performed in the two dimensions of the independent variable of risk perception and dependent variable of local community resilience. The unit of analysis in this study included the rural households. Professors and experts in this field were employed to assess validities of the indicators and variables. Also, 12 rural points, which could be exposed to floods and riverbanks, were selected as the study area. The sample size was determined by using Cochran's formula with an error of 0.07%. Of the total number of 4780 households in the statistical population, 190 households were evaluated with at least 10 questionnaires by dividing the proportion of the remaining samples between the studied villages. Cronbach's alpha test was used to calculate the questionnaire reliability. The alpha coefficient of the questionnaire was 0.76, which indicated its reliability with acceptable internal consistency. In the next step, the quantitative data obtained from the descriptive and inferential tests were analyzed by using SPSS software. Kolmogorov-Smirnov test was utilized to evaluate normality of the data distribution. Then, the tests of mean comparison, Pearson correlation and regression, and analysis of variance were applied to measure the perception level of the local community to flood risk and its resilience, as well as the relationship and impacts of these two variables according to the type of data. Discussion: The results of the present study showed that being aware of the causes of these crises and recognizing their real effects were effective in resilience and preparedness for these disasters and could reduce the number of casualties and the people affected. Based on the results of the correlation test, the strong effects of the indicators of local community perception on its resilience to natural hazards, especially in the cognitive and emotional dimensions, confirmed this fact. Among the various dimensions, the most desirable dimension was the cognitive dimension, which involved the highest proportion of the subjects. The role of the emotional dimension in the indicators (probability of occurrence, fear of occurrence, feeling of fear, security of life, perception of security during sleep, and a sense of dominance and control) was found to be more desirable in resilience. The analysis of variance test also made a statistically significant difference between at least one of the groups and the others assuming that the people's resilience was partly a function of their understanding, awareness, and knowledge about risks. Based on the results, most of the subjects had a moderate level of risk perception. Conclusion: According to the results of the present study, it couls be said that it was not possible to completely control hazards, including floods, but the damage could be minimized by following proper management and strategies, such as raising awareness of the local community through training programs, which could increase its resilience though most accidents do not give people enough opportunity to even use the most essential facilities. For this reason, it is necessary to plan and prepare the exposed population to deal with such conditions. In fact, the areas with knowledge and perception are less exposed to risks and people will be more resilient to disasters. Therefore, knowledge and awareness as the important components of resilience and adaptation to risks are vital for the society. Various educational interventions at the individual and social levels are crucial to increase people’s levels of cognition and awareness, as well as their behaviors and responses to risks. People with a high and sufficient understanding of risks insure their assets in addition to showing better preparedness and response to disasters, which affect their resilience after the occurrence of risks. Another important point is that the functional dimension can be considered to be parallel with operationalization of the perception of risks and a kind of desire for prevention, which is the third step after perception. Keywords: risk perception, resilience, local communities, disaster management English References - Aboagye, D. Dari, Th. Koomson, J., (2013). Risk Perception and Disaster Management in the Savannah Region of Ghana. International Journal of Humanities and Social Science, Vol. 3, No.3, pp. 85-96. - Agrawal, N., Elliott, M., P Simonovic, S., (2020). Risk and Resilience: A Case of Perception versus Reality in Flood Management, Water,Vol. 12, No. 1254, pp. 1-18. - Antronico, L., De Pascale, F., Coscarelli, R., Gullà, G., (2020). Landslide risk perception, social vulnerability and community resilience: The case study of Maierato (Calabria, southern Italy), International Journal of Disaster Risk Reduction, DOI:10.1016/j.ijdrr.2020.101529,Vol. 46, No. 2, pp.1015-1029. - Birkholz, S. Muro, M. Jeffrey, P. Smith, H.M., (2014). Rethinking the relationship between flood risk perception and flood management, Science of The Total Environment, Vol. 478, pp. 12-20. - Birkholz, S. Muro, M. Jeffrey, P. Smith, H.M., (2014). Rethinking the relationship between flood risk perception and flood management, Science of The Total Environment, Vol. 478, pp. 12-20. - Bodoque, J.M.; Amérigo, M.; Díez-Herrero, A.; García, J.A.; Cortés, B.; Ballesteros-Cánovas, J.A.; Olcina, J., (2016). Improvement of resilience of urban areas by integrating social perception in flash-flood risk management. Journal of Hydrology. (2016). Vol. 541, part A, pp. 665–676. - Bradford, R. A., O'Sullivan, J. J., van der Craats, I. M., Krywkow, J., Rotko, P., Aaltonen, J., Bonaiuto, M., De Dominicis, S., Waylen, K., Schelfaut, K., (2012). Risk perception – issues for flood management in Europe, Nat. Hazards Earth Syst. Sci. Vol .12, No. 7, pp. 2299–2309. - De Pascale,F. Bernardo, M. Muto, F. Di Matteo, and D. Dattilo, V., (2016). Resilience and seismic risk perception at school: a geoethical experiment in Aiello Calabro, southern Italy. Natural Hazards, vol 86 (S2), pp.569–586. - Dhar Chowdhury, p., Haque, C.E., (2011). Risk perception And Knowledgeg Gap between Experts and the Public: Issues of Flood Hazards Management in Canada. Journal of Environmental Research and Development, Vol. 5, No. 4, pp.1017-1022. - Eiser, J.R. Bostrom, A., Burton, L., M.Johnston, D., McClure, J., Paton, D., van der Pligt, J., P.White, M., (2012). Risk interpretation and action: A conceptual framework for responses to natural hazards, International Journal of Disaster Risk Reduction, Vol. 1, PP. 5-16. - González-Riancho, P., Gerkensmeier, B., M.W. Ratter,B., Gonzalez-Rebattú-y González,M. (2015). Storm surge risk perception and resilience: A pilot study in the German North Sea coast,Ocean & Coastal Management, Vol. 112, pp. 44-60. - Holzmann, R., & Jorgensen, S., (2001). Social Risk Management: A New Conceptual Framework for Social Protection, International Tax and Public Finance, Vol. 8, No. 4, pp. 529-556. - Lechowska, E., (2018). What determines flood risk perception? A review of factors of flood risk perception and relations between its basic elements. Natural Hazards, Vol. 94, pp.1341–1366. - Madsen, W., O’Mullan, C., (2016). Perceptions of Community Resilience after Natural Disaster in a Rural Australian Town. Journal of Community Psychology, Vol. 44, No. 3, pp. 277-292. - Margarint, M. C., Niculit, Mi., Roder, G., and Tarolli, P., (2021). Risk perception of local stakeholders on natural hazards: Implications for theory and practice. Nat. Hazards Earth Syst. Sci., Vol. 21, No. 11, pp. 3251–3283. - Pelling, M., (2003). The vulnerability of cities, natural disasters and social resilience, earth scan publication, London, UK, ISBN 1-85383-830-6 (pbk.) ISBN 1-85383-829-2 (hardback), P. 3-203. - Ridzuan, A.A.; Oktari, R.S.; Zainol, N.A.M.; Abdullah, H.; Liaw, J.O.H.; Mohaiyadin, N.M.H.; Mardzuki, K. (2018). Community resilience elements and community risk perception at Banda Aceh province, Aceh, Indonesia, International Conference on Disaster Management (2018), 14 Nowember, Matec Web of Conferences, DOI: 10.1051/matecconf/201822901005, Vol (229). - Salvati, P., Bianchi, C., Fiorucci, F., Giostrella, P., Marchesini, I., and Guzzetti, F, (2014). Perception of flood and landslide risk in Italy: a preliminary analysis. Nat. Hazards Earth Syst. Sci., 14, 2014, www.nat-hazards-earth-syst-sci.net/14/2589/2014/doi:10.5194/nhess-14-2589-2014. pp. 2589–2603. - Shiromini Ranjan, E.; Abenayake, C.CH, (2014). A study on community’s perception on disaster resilience concept. Procedia Economic. Financ. Vol. 18, pp. 88–94. - Slovic, p., Weber, Elke U, (2002). Perception of Risk Posed by Extreme Events. Conference: Risk Management strategies in an Uncertain World, Palisades, New York, April 12-13, 2002, pp.1-21. - Sönmez, S. and Graefe, A.R., (1998).Determining Future Travel Behavior from Past Travel Experience and Perceptions of Risk and Safety. November 1998, Journal of Travel Research, Vol. 37, No.2, pp. 172-177. - Sundblad, E. L. Biel, A. Garling, T., (2007). Cognitive and affective risk judgements related to climate change. Journal of Environmental Psychology, Vol. 27, No.2, pp. 97–106. - Townend, I.H., French, J.R., Nicholls, R.J., Brown S., Carpenter, S., Haigh, I.D., Hill, C.T., Lazarus, E., Penning-Rowsell, E.C., Thompson, C.E.L., Tompkins, E.L, (2021). Operationalising coastal resilience to flood and erosion hazard: A demonstration for England.Science of the Total Environment, 783 (2021) 14688, pp. 1-16. https://doi.org/10.1016/j.scitotenv.2021.146880 - Ungar, M., (2019). Designing resilience research: Using multiple methods to investigate risk exposure, promotive and protective processes, and contextually relevant outcomes for children and youth. Child Abuse & Neglect, Vol. 96, 104098, pp. 1- 8. - Wachinger, G. Renn,O. Begg, Ch. and Kuhlicke, Ch., (2013). The Risk Perception Paradox Implications for Governance and Communication of Natural Hazards. Risk Analysis, Vol. 33, No.6, pp. 1049-65. - Wolff, K., Larsena, S., Øgaard, T., (2019). How to define and measure risk perceptions. Annals of Tourism Research, Vol. 79, pp. 1-9. Persian References - Azmi, A., Masoompour, J., Shahmoradi, A., (2015). Investigating the role of indigenous people in understanding natural hazards and preparing for them in Zalouab rural district of the central part of Ravansar city of Kermanshah province. Quarterly Journal of Knowledge Crisis Follow-up and Management, Vol. 6, No. 4, pp. 382-391. -Mousavi Herami, R., Mahboubi, A.A., Ghafouri, M., Khaneh Bad, M., (2003). Sedimentological studies and runoff rate downstream of Golestan dam, southwest of Mashhad. Journal of Science, University of Tehran, Vol. 29, No. 1, pp. 87-117. -Program and Budget, Vol 2 (2016): Website of Khorasan Razavi Governorate, Political, Security and Social Deputy of the Office of Social and Cultural Affairs.Social and Cultural Identity of Binalood city. https://ostandari.khorasan.ir/ -Rahmani, S., Yazdanpanah, M., Forouzani, M., Abdshahi, A., (2018). Investigating the beliefs and strategies of farmers' adaptation to water shortage conditions and the factors affecting them in Mamasani city.Journal of Water Research in Agriculture, Vol. 32, No. 2, pp. 321-340. -Rahnamaye Roodposhti, F., Nategh Golestan, A., Yaghoubnejad, A., (2015). Presenting a mental model of risk perception of investors of Tehran Stock Exchange. Investment Knowledge Quarterly, Vol. 4, No. 13, pp. 195-216. -Sadeghloo, T., Arab Teymouri, Y., Shakoori Fard, I., (2017). Assessing the level of knowledge and awareness of villagers about drought crisis management (Case study: Miyan Khaf rural villages of Khaf city). Geography and environmental hazards, Vol. 6, No. 2, pp. 73-100. -Savari, M., Khosravi Pour, B., (2018). Analysis of the effects of resilience on the vitality of rural households in drought conditions in Divandere city.Quarterly Journal of Spatial Planning (Geography), Vol. 8, No. 3, pp. 19-40. -Sharghi, A., Matouf, Sh., Asadi, S., (2017). Analysis of the Role of Risk Perception on Environmental Behavior during Earthquake in Ganjalikhan Complex and Kerman Bazaar. Islamic Iranian City Journal, Vol. 7, No. 28, pp. 77-85. -Yazdanpanah, M., Zubeidi, T., Zairi, H., (2018). Explaining the psychological structures affecting the understanding of the danger of promoters and agricultural extension experts of Khuzestan province in relation to climate change, geography and development, Vol. 16, No. 50, pp.199-212. -Zaheri, M., Majnuni Tutakhaneh, A., (2019). Investigating the role of perception of the risk of drying up of Lake Urmia in changing the behavioral patterns of the surrounding villagers. Regional Planning Quarterly, Vol. 9, No. 33, pp. 43-54. Figures and Tables - Fig. 1: Conceptual model of research: analysis of the level of perception of flood risk by the local community and its impact on disaster resilience (authors, 2021) - Fig. 2: Map of the political situation of the studied villages - Table 4: Assessment of the importance of the dimensions of perception and resilience to disasters for villagers (authors‚ 2021) -Table 5: Relationship between risk perception and resilience variable based on Pearson correlation coefficient (authors‚ 2021) - Table 6: Relationship between perception and resilience indicators (authors‚ 2021) - Table 7: Perception of risks between the two groups of respondents (male and female) by using the t-test of the two independent samples (authors‚ 2021) - Table 8: Comparison of the effects of perception between the two groups of men and women using the t-test of the two independent groups (authors‚ 2021) - Table 9: The means and standard deviation related to the comparison of perception and resilience between the insured and uninsured groups (authors‚ 2021) - Table 10: Comparison of the difference between the two insured and uninsured groups in terms of their perception and resilience to risks by using the t-test of the two independent groups (authors‚ 2021) - Table 11: Correlation value, adjusted coefficient of determination, and standard error of the effect of perception on resilience (authors‚ 2021) - Table 12: Multiple correlation coefficients of the effects of perception indicators on resilience (authors‚ 2021) - Table 13: Standard and non-standard regression coefficients for predicting the resilience of the local community (authors‚ 2021) - Table 16: The last stage of clustering the risk perception variable (authors‚ 2021) - Table 17: Comparison of mean resilience between the different groups (authors‚ 2021) - Table 18: Leven test (homogeneity of variances) (authors‚ 2021) - Table 19: Resilience at the different levels of risk perception (authors‚ 2021) - Table 20: Homogeneous groups in terms of risk perception (authors, 2021) Abstract: Perception of risks and awareness of their effects based on the rational nature of human biology and his desire for survival always reduce the likelihood of hazards and improve preparedness for possible effects. In this regard, the present study sought to investigate and analyze the effects of perception of flood risk on the resilience of local communities in the rural families of Binalood County. This study was a descriptive-analytical research in terms of method and an applied research in terms of purpose. The unit of analysis in this study included 190 rural households in the area, which was determined by using the Cochran's formula with an error of 0.07. The results of the statistical analysis indicated that the indicators of emotional and cognitive dimensions of perception with the average values of 3.5 and 3.1 had the highest impacts and functional dimension with an average value of 2.5 had the lowest impact at the sample level. Also, the results of evaluating the effects of risk perception on the resilience by using the regression test indicated that among the dimensions of risk perception, cognitive dimension had the greatest effect on the resilience of the studied villages. On the other hand, based on the results of the analysis of variance, there was a significant difference between the resilience levels of groups with different levels of risk perception in the local communities. Moreover, the groups with moderate level of perception had the highest resilience among the other groups. Rural women also had a greater understanding of flooding and its probability of occurrence. As a result, they were more resilient. On the other hand, comparison of the levels of perception and resilience between the insured and uninsured people showed that the insured people had more perception and resilience than the uninsured people. Introduction: Findings of the effects of risk perception on resilience can be used to identify systems of resilience and adopt policies tailored to the levels of perception and resilience in local communities. Resilience of rural communities has become one of the most important issues in recent decades in such a way that many studies have been written about natural hazards and resilience of local communities. In recent years, disaster management in the programs of natural hazard reduction has tried to create and strengthen the characteristics of resilient communities. The aim of this study was to investigate and analyze the effects of flood risk perception on the resilience of local communities in rural families in Binalood, Mashhad. The results of comparing the villagers’ average opinions based on one-sample t-test showed that the values of T-statistic in all the indicators except the performance index were higher than the average value (3). All dimensions of the independent variable of risk perception and the dependent variable of resilience of communities to risks indicated their significant effects on measuring and evaluating the variable purpose. The results showed that the villagers were at a moderate level in terms of perception and resilience. Therefore, paying attention to increasing understanding of the local community in terms of their ability and resistance to dangers, such as floods, was one of the most important factors for realizing their confrontation with dangers. Thus, an important source of information, cognition, and awareness can determine the outcome of a general behavior like resilience. This study also showed that there was a relationship between the perception of local communities and resilience to disasters by 0.616%, which indicated the importance of the relationship between these two variables and their coordinated changes. On the other hand, the difference in the structures of perception of risks between the two groups of men and women (women’s higher perception of the risks) indicated the importance of the women’s role in such events. Their greater understanding of risks could lead to increased resilience and consequently less vulnerability. The results of perception and resilience between the insured and uninsured people showed inequality of the structures of perception of risks and resilience among these people, indicating a higher perception and resilience among the insured people. Multivariate regression was used to measure the effects of the different dimensions of risk perception on resilience. The results obtained from the villagers showed that the perception of the studied local community with the resilience index of 0.715 had a positive relationship with its strong intensity in terms of the coefficient of impact of variables on resilience. The cognitive dimension with an impact factor of 0.696 had the highest positive effect on resilience. In fact, perception of risks by more people increases their readiness to face natural hazards, thus accelerating resilience and consequently helping them cope with the risks and more quickly recover after them. Methodology: This research was based on a descriptive-analytical method and the research type was applied and quantitative. Thus, the field survey data were used to explain the research objectives. The main tool for data collection was a researcher-made questionnaire based on the indicators and variables extracted from theoretical topics. The study was performed in the two dimensions of the independent variable of risk perception and dependent variable of local community resilience. The unit of analysis in this study included the rural households. Professors and experts in this field were employed to assess validities of the indicators and variables. Also, 12 rural points, which could be exposed to floods and riverbanks, were selected as the study area. The sample size was determined by using Cochran's formula with an error of 0.07%. Of the total number of 4780 households in the statistical population, 190 households were evaluated with at least 10 questionnaires by dividing the proportion of the remaining samples between the studied villages. Cronbach's alpha test was used to calculate the questionnaire reliability. The alpha coefficient of the questionnaire was 0.76, which indicated its reliability with acceptable internal consistency. In the next step, the quantitative data obtained from the descriptive and inferential tests were analyzed by using SPSS software. Kolmogorov-Smirnov test was utilized to evaluate normality of the data distribution. Then, the tests of mean comparison, Pearson correlation and regression, and analysis of variance were applied to measure the perception level of the local community to flood risk and its resilience, as well as the relationship and impacts of these two variables according to the type of data. Discussion: The results of the present study showed that being aware of the causes of these crises and recognizing their real effects were effective in resilience and preparedness for these disasters and could reduce the number of casualties and the people affected. Based on the results of the correlation test, the strong effects of the indicators of local community perception on its resilience to natural hazards, especially in the cognitive and emotional dimensions, confirmed this fact. Among the various dimensions, the most desirable dimension was the cognitive dimension, which involved the highest proportion of the subjects. The role of the emotional dimension in the indicators (probability of occurrence, fear of occurrence, feeling of fear, security of life, perception of security during sleep, and a sense of dominance and control) was found to be more desirable in resilience. The analysis of variance test also made a statistically significant difference between at least one of the groups and the others assuming that the people's resilience was partly a function of their understanding, awareness, and knowledge about risks. Based on the results, most of the subjects had a moderate level of risk perception. Conclusion: According to the results of the present study, it couls be said that it was not possible to completely control hazards, including floods, but the damage could be minimized by following proper management and strategies, such as raising awareness of the local community through training programs, which could increase its resilience though most accidents do not give people enough opportunity to even use the most essential facilities. For this reason, it is necessary to plan and prepare the exposed population to deal with such conditions. In fact, the areas with knowledge and perception are less exposed to risks and people will be more resilient to disasters. Therefore, knowledge and awareness as the important components of resilience and adaptation to risks are vital for the society. Various educational interventions at the individual and social levels are crucial to increase people’s levels of cognition and awareness, as well as their behaviors and responses to risks. People with a high and sufficient understanding of risks insure their assets in addition to showing better preparedness and response to disasters, which affect their resilience after the occurrence of risks. Another important point is that the functional dimension can be considered to be parallel with operationalization of the perception of risks and a kind of desire for prevention, which is the third step after perception. Keywords: risk perception, resilience, local communities, disaster management English References - Aboagye, D. Dari, Th. Koomson, J., (2013). Risk Perception and Disaster Management in the Savannah Region of Ghana. International Journal of Humanities and Social Science, Vol. 3, No.3, pp. 85-96. - Agrawal, N., Elliott, M., P Simonovic, S., (2020). Risk and Resilience: A Case of Perception versus Reality in Flood Management, Water,Vol. 12, No. 1254, pp. 1-18. - Antronico, L., De Pascale, F., Coscarelli, R., Gullà, G., (2020). Landslide risk perception, social vulnerability and community resilience: The case study of Maierato (Calabria, southern Italy), International Journal of Disaster Risk Reduction, DOI:10.1016/j.ijdrr.2020.101529,Vol. 46, No. 2, pp.1015-1029. - Birkholz, S. Muro, M. Jeffrey, P. Smith, H.M., (2014). Rethinking the relationship between flood risk perception and flood management, Science of The Total Environment, Vol. 478, pp. 12-20. - Birkholz, S. Muro, M. Jeffrey, P. Smith, H.M., (2014). Rethinking the relationship between flood risk perception and flood management, Science of The Total Environment, Vol. 478, pp. 12-20. - Bodoque, J.M.; Amérigo, M.; Díez-Herrero, A.; García, J.A.; Cortés, B.; Ballesteros-Cánovas, J.A.; Olcina, J., (2016). Improvement of resilience of urban areas by integrating social perception in flash-flood risk management. Journal of Hydrology. (2016). Vol. 541, part A, pp. 665–676. - Bradford, R. A., O'Sullivan, J. J., van der Craats, I. M., Krywkow, J., Rotko, P., Aaltonen, J., Bonaiuto, M., De Dominicis, S., Waylen, K., Schelfaut, K., (2012). Risk perception – issues for flood management in Europe, Nat. Hazards Earth Syst. Sci. Vol .12, No. 7, pp. 2299–2309. - De Pascale,F. Bernardo, M. Muto, F. Di Matteo, and D. Dattilo, V., (2016). Resilience and seismic risk perception at school: a geoethical experiment in Aiello Calabro, southern Italy. Natural Hazards, vol 86 (S2), pp.569–586. - Dhar Chowdhury, p., Haque, C.E., (2011). Risk perception And Knowledgeg Gap between Experts and the Public: Issues of Flood Hazards Management in Canada. Journal of Environmental Research and Development, Vol. 5, No. 4, pp.1017-1022. - Eiser, J.R. Bostrom, A., Burton, L., M.Johnston, D., McClure, J., Paton, D., van der Pligt, J., P.White, M., (2012). Risk interpretation and action: A conceptual framework for responses to natural hazards, International Journal of Disaster Risk Reduction, Vol. 1, PP. 5-16. - González-Riancho, P., Gerkensmeier, B., M.W. Ratter,B., Gonzalez-Rebattú-y González,M. (2015). Storm surge risk perception and resilience: A pilot study in the German North Sea coast,Ocean & Coastal Management, Vol. 112, pp. 44-60. - Holzmann, R., & Jorgensen, S., (2001). Social Risk Management: A New Conceptual Framework for Social Protection, International Tax and Public Finance, Vol. 8, No. 4, pp. 529-556. - Lechowska, E., (2018). What determines flood risk perception? A review of factors of flood risk perception and relations between its basic elements. Natural Hazards, Vol. 94, pp.1341–1366. - Madsen, W., O’Mullan, C., (2016). Perceptions of Community Resilience after Natural Disaster in a Rural Australian Town. Journal of Community Psychology, Vol. 44, No. 3, pp. 277-292. - Margarint, M. C., Niculit, Mi., Roder, G., and Tarolli, P., (2021). Risk perception of local stakeholders on natural hazards: Implications for theory and practice. Nat. Hazards Earth Syst. Sci., Vol. 21, No. 11, pp. 3251–3283. - Pelling, M., (2003). The vulnerability of cities, natural disasters and social resilience, earth scan publication, London, UK, ISBN 1-85383-830-6 (pbk.) ISBN 1-85383-829-2 (hardback), P. 3-203. - Ridzuan, A.A.; Oktari, R.S.; Zainol, N.A.M.; Abdullah, H.; Liaw, J.O.H.; Mohaiyadin, N.M.H.; Mardzuki, K. (2018). Community resilience elements and community risk perception at Banda Aceh province, Aceh, Indonesia, International Conference on Disaster Management (2018), 14 Nowember, Matec Web of Conferences, DOI: 10.1051/matecconf/201822901005, Vol (229). - Salvati, P., Bianchi, C., Fiorucci, F., Giostrella, P., Marchesini, I., and Guzzetti, F, (2014). Perception of flood and landslide risk in Italy: a preliminary analysis. Nat. Hazards Earth Syst. Sci., 14, 2014, www.nat-hazards-earth-syst-sci.net/14/2589/2014/doi:10.5194/nhess-14-2589-2014. pp. 2589–2603. - Shiromini Ranjan, E.; Abenayake, C.CH, (2014). A study on community’s perception on disaster resilience concept. Procedia Economic. Financ. Vol. 18, pp. 88–94. - Slovic, p., Weber, Elke U, (2002). Perception of Risk Posed by Extreme Events. Conference: Risk Management strategies in an Uncertain World, Palisades, New York, April 12-13, 2002, pp.1-21. - Sönmez, S. and Graefe, A.R., (1998).Determining Future Travel Behavior from Past Travel Experience and Perceptions of Risk and Safety. November 1998, Journal of Travel Research, Vol. 37, No.2, pp. 172-177. - Sundblad, E. L. Biel, A. Garling, T., (2007). Cognitive and affective risk judgements related to climate change. Journal of Environmental Psychology, Vol. 27, No.2, pp. 97–106. - Townend, I.H., French, J.R., Nicholls, R.J., Brown S., Carpenter, S., Haigh, I.D., Hill, C.T., Lazarus, E., Penning-Rowsell, E.C., Thompson, C.E.L., Tompkins, E.L, (2021). Operationalising coastal resilience to flood and erosion hazard: A demonstration for England.Science of the Total Environment, 783 (2021) 14688, pp. 1-16. https://doi.org/10.1016/j.scitotenv.2021.146880 - Ungar, M., (2019). Designing resilience research: Using multiple methods to investigate risk exposure, promotive and protective processes, and contextually relevant outcomes for children and youth. Child Abuse & Neglect, Vol. 96, 104098, pp. 1- 8. - Wachinger, G. Renn,O. Begg, Ch. and Kuhlicke, Ch., (2013). The Risk Perception Paradox Implications for Governance and Communication of Natural Hazards. Risk Analysis, Vol. 33, No.6, pp. 1049-65. - Wolff, K., Larsena, S., Øgaard, T., (2019). How to define and measure risk perceptions. Annals of Tourism Research, Vol. 79, pp. 1-9. Persian References - Azmi, A., Masoompour, J., Shahmoradi, A., (2015). Investigating the role of indigenous people in understanding natural hazards and preparing for them in Zalouab rural district of the central part of Ravansar city of Kermanshah province. Quarterly Journal of Knowledge Crisis Follow-up and Management, Vol. 6, No. 4, pp. 382-391. -Mousavi Herami, R., Mahboubi, A.A., Ghafouri, M., Khaneh Bad, M., (2003). Sedimentological studies and runoff rate downstream of Golestan dam, southwest of Mashhad. Journal of Science, University of Tehran, Vol. 29, No. 1, pp. 87-117. -Program and Budget, Vol 2 (2016): Website of Khorasan Razavi Governorate, Political, Security and Social Deputy of the Office of Social and Cultural Affairs.Social and Cultural Identity of Binalood city. https://ostandari.khorasan.ir/ -Rahmani, S., Yazdanpanah, M., Forouzani, M., Abdshahi, A., (2018). Investigating the beliefs and strategies of farmers' adaptation to water shortage conditions and the factors affecting them in Mamasani city.Journal of Water Research in Agriculture, Vol. 32, No. 2, pp. 321-340. -Rahnamaye Roodposhti, F., Nategh Golestan, A., Yaghoubnejad, A., (2015). Presenting a mental model of risk perception of investors of Tehran Stock Exchange. Investment Knowledge Quarterly, Vol. 4, No. 13, pp. 195-216. -Sadeghloo, T., Arab Teymouri, Y., Shakoori Fard, I., (2017). Assessing the level of knowledge and awareness of villagers about drought crisis management (Case study: Miyan Khaf rural villages of Khaf city). Geography and environmental hazards, Vol. 6, No. 2, pp. 73-100. -Savari, M., Khosravi Pour, B., (2018). Analysis of the effects of resilience on the vitality of rural households in drought conditions in Divandere city.Quarterly Journal of Spatial Planning (Geography), Vol. 8, No. 3, pp. 19-40. -Sharghi, A., Matouf, Sh., Asadi, S., (2017). Analysis of the Role of Risk Perception on Environmental Behavior during Earthquake in Ganjalikhan Complex and Kerman Bazaar. Islamic Iranian City Journal, Vol. 7, No. 28, pp. 77-85. -Yazdanpanah, M., Zubeidi, T., Zairi, H., (2018). Explaining the psychological structures affecting the understanding of the danger of promoters and agricultural extension experts of Khuzestan province in relation to climate change, geography and development, Vol. 16, No. 50, pp.199-212. -Zaheri, M., Majnuni Tutakhaneh, A., (2019). Investigating the role of perception of the risk of drying up of Lake Urmia in changing the behavioral patterns of the surrounding villagers. Regional Planning Quarterly, Vol. 9, No. 33, pp. 43-54. Figures and Tables - Fig. 1: Conceptual model of research: analysis of the level of perception of flood risk by the local community and its impact on disaster resilience (authors, 2021) - Fig. 2: Map of the political situation of the studied villages - Table 4: Assessment of the importance of the dimensions of perception and resilience to disasters for villagers (authors‚ 2021) -Table 5: Relationship between risk perception and resilience variable based on Pearson correlation coefficient (authors‚ 2021) - Table 6: Relationship between perception and resilience indicators (authors‚ 2021) - Table 7: Perception of risks between the two groups of respondents (male and female) by using the t-test of the two independent samples (authors‚ 2021) - Table 8: Comparison of the effects of perception between the two groups of men and women using the t-test of the two independent groups (authors‚ 2021) - Table 9: The means and standard deviation related to the comparison of perception and resilience between the insured and uninsured groups (authors‚ 2021) - Table 10: Comparison of the difference between the two insured and uninsured groups in terms of their perception and resilience to risks by using the t-test of the two independent groups (authors‚ 2021) - Table 11: Correlation value, adjusted coefficient of determination, and standard error of the effect of perception on resilience (authors‚ 2021) - Table 12: Multiple correlation coefficients of the effects of perception indicators on resilience (authors‚ 2021) - Table 13: Standard and non-standard regression coefficients for predicting the resilience of the local community (authors‚ 2021) - Table 16: The last stage of clustering the risk perception variable (authors‚ 2021) - Table 17: Comparison of mean resilience between the different groups (authors‚ 2021) - Table 18: Leven test (homogeneity of variances) (authors‚ 2021) - Table 19: Resilience at the different levels of risk perception (authors‚ 2021) - Table 20: Homogeneous groups in terms of risk perception (authors, 2021)

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