دانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822Evaluation of Drought in Gandaki River Basin of NepalEvaluation of Drought in Gandaki River Basin of Nepal126305410.22077/jdcr.2023.6865.1046FAآیوش بتارایموسسه جنگلداری، پردیس هتاودا، دانشگاه تریبووان، ماکوانپور، نپال.ساچین تیمیل سیناموسسه جنگلداری، پردیس پوخارا، پوخارا، دانشگاه تریبووان، پوخارا، نپال.سنتوش آیردانشکده مدیریت منابع طبیعی (CNRM)، دانشگاه کشاورزی و جنگلداری، کاتاری، نپال.گایاتری پودلموسسه جنگلداری، پردیس هتاودا، دانشگاه تریبووان، مکوانپور، نپال.منوکا مهارجانموسسه جنگلداری، پردیس هتودا و دانشکده جنگلداری و مدیریت منابع طبیعی، موسسه جنگلداری، دانشگاه تریبهوان، کاتماندو، نپال.Journal Article20231013Drought is often considered a silent disaster, leading to food and water shortages, displacement, and even conflict. Although evidence of ongoing climate change has been observed, limited research is carried out on drought conditions in Gandaki River Basin of Nepal. This study analyzed four indices i.e., Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Land Surface Temperature (LST) and Normalized Difference Drought Index (NDDI) for January and November between 1991 and 2021 by using Geographic Information System (GIS) and remote sensed data. NDVI showed that dense vegetation decreased by 93.26% and built-up area increased by 96.88% in January compared between 1991 and 2021. Compared between 1991 and 2021, NDWI showed that the high water stressed area increased by 49.5% in January. NDDI showed increased in abnormally drought area in January (164.03%) compared between 1991 and 2021.Both climate change and human activities significantly contributes increasing trend of drought over the 30-year period in Gandaki River Basin. The study suggests exploring the potential of modern tools such as GIS and Remote Sensing for prediction of drought and monitoring its impact on ecosystems and human. This will be beneficial for policy makers for developing the strategy for combating drought and climate change.Drought is often considered a silent disaster, leading to food and water shortages, displacement, and even conflict. Although evidence of ongoing climate change has been observed, limited research is carried out on drought conditions in Gandaki River Basin of Nepal. This study analyzed four indices i.e., Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Land Surface Temperature (LST) and Normalized Difference Drought Index (NDDI) for January and November between 1991 and 2021 by using Geographic Information System (GIS) and remote sensed data. NDVI showed that dense vegetation decreased by 93.26% and built-up area increased by 96.88% in January compared between 1991 and 2021. Compared between 1991 and 2021, NDWI showed that the high water stressed area increased by 49.5% in January. NDDI showed increased in abnormally drought area in January (164.03%) compared between 1991 and 2021.Both climate change and human activities significantly contributes increasing trend of drought over the 30-year period in Gandaki River Basin. The study suggests exploring the potential of modern tools such as GIS and Remote Sensing for prediction of drought and monitoring its impact on ecosystems and human. This will be beneficial for policy makers for developing the strategy for combating drought and climate change.https://jdcr.birjand.ac.ir/article_3054_c93023011d5eeaa8335d8c8d980c3f74.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822A biophysical Approach to Assess the Risks Associated with Climate Change for Spatial Analysis of Agricultural Drought VulnerabilityA biophysical Approach to Assess the Risks Associated with Climate Change for Spatial Analysis of Agricultural Drought Vulnerability2756305110.22077/jdcr.2023.6479.1027FAمحمدرضا فرزانهگروه پژوهشی مهندسی محیط زیست و پایش آلودگی، مرکز تحقیقات محیط زیست و توسعه پایدار، سازمان حفاظت محیط زیست، تهران، ایران.معصومه فخریعضو کارشناس موسسه تحقیقات برنامهریزی کشاورزی، اقتصاد و توسعه روستایی (APERDRI)، وزارت کشاورزی، تهران، ایرانایمان فاضلی فارسانیگروه مهندسی خاک، دانشگاه شهرکرد، شهرکرد، ایران.مریم نجفی بیراگانیگروه مهندسی آب، دانشگاه اراک، اراک، ایران.محمد عبدالحسینیگروه مهندسی آب، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران.Journal Article20230613Global warming has led to changes in climate variability and different characteristic of consequence extreme events. Recently, the study of compound extremes, defined as the co-occurrence of multiple events with extreme impacts, has attracted much attention because of their detrimental impacts on society and ecosystems. In countries like Iran with arid and semi-arid climate patterns, the inter-annual climate variability causes severe influences on agriculture through compound dry and hot extremes. Such impacts are expected to increase due to climatic changes. Decreasing water availability as a consequence will impose a direct impact on agriculture and could endanger the socio-economic development and social sustainability in these regions. Assessment of the vulnerability to climate change and its resulted-in agricultural drought is fundamental for effective adaptation strategies in the future. This paper is presenting a spatial GIS-based assessment method for agricultural drought vulnerability in current and future climatic conditions in Isfahan province, Iran by constructing agricultural drought vulnerability maps. This assessment was conducted by evaluation of changes in the severity, duration, and frequency of compound dry and hot extremes. The results expressed the spatio-temporal variability of the empirical probability of drought occurrence, and indicated the relation between the vulnerability of agricultural drought and the characteristics of drought occurrence. The results of vulnerability assessment can be used to prioritize the counties for implementation of long-term drought management plans and effective countermeasures, as well as to contribute to sustainable agricultural development.Global warming has led to changes in climate variability and different characteristic of consequence extreme events. Recently, the study of compound extremes, defined as the co-occurrence of multiple events with extreme impacts, has attracted much attention because of their detrimental impacts on society and ecosystems. In countries like Iran with arid and semi-arid climate patterns, the inter-annual climate variability causes severe influences on agriculture through compound dry and hot extremes. Such impacts are expected to increase due to climatic changes. Decreasing water availability as a consequence will impose a direct impact on agriculture and could endanger the socio-economic development and social sustainability in these regions. Assessment of the vulnerability to climate change and its resulted-in agricultural drought is fundamental for effective adaptation strategies in the future. This paper is presenting a spatial GIS-based assessment method for agricultural drought vulnerability in current and future climatic conditions in Isfahan province, Iran by constructing agricultural drought vulnerability maps. This assessment was conducted by evaluation of changes in the severity, duration, and frequency of compound dry and hot extremes. The results expressed the spatio-temporal variability of the empirical probability of drought occurrence, and indicated the relation between the vulnerability of agricultural drought and the characteristics of drought occurrence. The results of vulnerability assessment can be used to prioritize the counties for implementation of long-term drought management plans and effective countermeasures, as well as to contribute to sustainable agricultural development.https://jdcr.birjand.ac.ir/article_3051_fca77df0c1fe164e359fa709a63de00c.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822Assessment of the Water, Food, and Energy Efficiency Indicators with a Nexus Approach and Sustainable Agricultural ManagementAssessment of the Water, Food, and Energy Efficiency Indicators with a Nexus Approach and Sustainable Agricultural Management5776305210.22077/jdcr.2023.6585.1031FAسیدعلی معاشریدانش آموخته دکتری آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران، تهران و کارشناس شرکت آب منطقهای یزد، یزد، ایران.سامان جوادیدانشیار، گروه مهندسی آب، پردیس ابوریحان، دانشگاه تهران، تهران، ایران.محمود مشعلدانشیار، گروه مهندسی آب، پردیس ابوریحان، دانشگاه تهران، تهران، ایران.بهزاد آزادگاندانشیار، گروه مهندسی آب، پردیس ابوریحان، دانشگاه تهران، تهران، ایران.حمید کاردان مقدماستادیار، موسسه تحقیقات آب، وزارت نیرو، تهران، ایران.Journal Article20230716Sustainable management of water, food, and energy resources and increasing efficiency is one of the key challenges in the field of sustainable management and development. Given climate change, global population growth, and growing demands, sustainable utilization of these resources is essential to ensure the possibility of human survival and sustainable growth. Achieving sustainable development goals requires a comprehensive and interactive approach, and resource management with an integrative perspective is a necessary component of sustainable development, where all stakeholders participate in the decision-making process and implementation of actions.<br />This study aims to enhance the efficiency of water, food, and energy in the Plusgan watershed and develop a validated tool for evaluating agricultural management strategies in relation to the nexus of water, food, and energy security. The study was conducted in two stages. In the first stage, management scenarios were identified to increase efficiency, and in the second stage, the nexus-oriented management scenarios were evaluated and prioritized.<br />In the second part of this research, among the 30 introduced sub-scenarios for improving efficiency, the sub-scenarios that involved a 20%, 10%, and 30% increase in the area of forage maize cultivation showed positive effects on water, food, and energy efficiency indicators. After prioritizing the influential sub-scenarios using the TOPSIS multi-criteria decision-making model, the sub-scenario with a 30% increase in the area of forage maize cultivation had the greatest positive impact on water, food, and energy efficiency. It was identified as the key scenario for evaluating efficiency in sustainable agricultural management.Sustainable management of water, food, and energy resources and increasing efficiency is one of the key challenges in the field of sustainable management and development. Given climate change, global population growth, and growing demands, sustainable utilization of these resources is essential to ensure the possibility of human survival and sustainable growth. Achieving sustainable development goals requires a comprehensive and interactive approach, and resource management with an integrative perspective is a necessary component of sustainable development, where all stakeholders participate in the decision-making process and implementation of actions.<br />This study aims to enhance the efficiency of water, food, and energy in the Plusgan watershed and develop a validated tool for evaluating agricultural management strategies in relation to the nexus of water, food, and energy security. The study was conducted in two stages. In the first stage, management scenarios were identified to increase efficiency, and in the second stage, the nexus-oriented management scenarios were evaluated and prioritized.<br />In the second part of this research, among the 30 introduced sub-scenarios for improving efficiency, the sub-scenarios that involved a 20%, 10%, and 30% increase in the area of forage maize cultivation showed positive effects on water, food, and energy efficiency indicators. After prioritizing the influential sub-scenarios using the TOPSIS multi-criteria decision-making model, the sub-scenario with a 30% increase in the area of forage maize cultivation had the greatest positive impact on water, food, and energy efficiency. It was identified as the key scenario for evaluating efficiency in sustainable agricultural management.https://jdcr.birjand.ac.ir/article_3052_48ab940d8be31eabad14ec4082b803e9.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822Monitoring Changes in Rice Cultivation Area using Multi-Temporal Satellite images (Case Study: Beiranshahr Region, Iran)Monitoring Changes in Rice Cultivation Area using Multi-Temporal Satellite images (Case Study: Beiranshahr Region, Iran)7792305310.22077/jdcr.2023.6743.1040FAصمد عبدیموسسه تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرم آباد، ایران.محسن احمدیمرکز تحقیقات کشاورزی و منابع طبیعی لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرمآباد، ایران.ربیع رستومدانشگاه هریوت وات، پردیس دبی، پارک دانش دبی، دبی، امارات متحده عربی.آناهید سلمان پورموسسه تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرم آباد، ایران.Journal Article20230903The cultivation of crops with high water demand in arid and semi-arid regions can seriously threaten water resources. In the Beiranshahr region, western Iran, based on various factors, including high profit and short growing seasons, the desire of farmers to cultivate rice has increased in recent years. This research was conducted to investigate the expansion of rice cultivation area from 2013 to 2021 in this region. For this purpose, using Landsat 8 and Sentinel 1 satellite images, the changes in the area under rice cultivation in this area were determined. Using the groundwater data from Lorestan Regional Water, a change in the water table level was determined. The results showed that the area under rice cultivation has increased from 2,564 hectares in 2013 to 4,771 hectares in 2021. Investigating the underground water level showed that the depth of the water in some parts of the region has reached 10 meters, while in the past, the depth of the underground water in this region was less than 2 meters. These results show that increasing the planting of rice in this region can endanger the water resources of the region, and in the long term, the region will face serious challenges. Therefore, it is recommended to limit rice cultivation in the region and cultivate crops with less water demand instead. The development of pressurized irrigation systems in the region can help save water consumption.The cultivation of crops with high water demand in arid and semi-arid regions can seriously threaten water resources. In the Beiranshahr region, western Iran, based on various factors, including high profit and short growing seasons, the desire of farmers to cultivate rice has increased in recent years. This research was conducted to investigate the expansion of rice cultivation area from 2013 to 2021 in this region. For this purpose, using Landsat 8 and Sentinel 1 satellite images, the changes in the area under rice cultivation in this area were determined. Using the groundwater data from Lorestan Regional Water, a change in the water table level was determined. The results showed that the area under rice cultivation has increased from 2,564 hectares in 2013 to 4,771 hectares in 2021. Investigating the underground water level showed that the depth of the water in some parts of the region has reached 10 meters, while in the past, the depth of the underground water in this region was less than 2 meters. These results show that increasing the planting of rice in this region can endanger the water resources of the region, and in the long term, the region will face serious challenges. Therefore, it is recommended to limit rice cultivation in the region and cultivate crops with less water demand instead. The development of pressurized irrigation systems in the region can help save water consumption.https://jdcr.birjand.ac.ir/article_3053_4dae66e38aacfc660da5122d49b553b5.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822Measuring Discharge in a Shallow River in an Arid Area solely using an Unmanned Aerial VehicleMeasuring Discharge in a Shallow River in an Arid Area solely using an Unmanned Aerial Vehicle93104305510.22077/jdcr.2024.7376.1061FAفرهاد اکبرپورمهندس حفاظت از رودخانه، شرکت آب منطقهای تهران، تهران، ایران.محمدعادل خراسانی نژاددانشجوی دکتری، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران.شروین شهریاریدانش آموخته دکتری، موسسه مهندسی هیدرولیک و مدیریت منابع آب، دانشگاه صنعتی گراتس، اتریش.مصطفی رحمان شاهیپژوهشگر پسادکتری، دانشگاه پلیتکنیک هنگ کنگ، هنگ کنگ.Journal Article20240302Unmanned Aerial Vehicles (UAVs) have recently been applied for river flow measurement. In this paper UAV images were first used to acquire surface velocity fields of a small river in an arid area in Iran based on the principles of Large Scale Particle Image Velocimetry (LSPIV). Subsequently, Large Eddy PIV method was applied on the instantaneous velocity data to obtain turbulent kinetic energy dissipation rates along a selected cross section of the experimented river. In addition, a UAV image was captured and processed to gain the bed material grain size distribution and consequently the Manning roughness coefficient. The resulted gradation curve matched the graph given by sieve analysis with an accuracy of nearly 7.8 percent. Moreover, an equation combining the acquired surface velocity, dissipation rates and Manning coefficient was used to estimate the river bathymetry. Although, the evaluated bathymetry does not fit the surveyed cross section very well, the average predicted depth matches the measured mean depth with a high precision. Finally, the river flow rate calculated using the information solely resulted from UAV images fitted the measured discharge with an accuracy of 5 percent proving the described framework to be a very effective method for primary river flow evaluation especially when supplementary depth measurement is not feasible.Unmanned Aerial Vehicles (UAVs) have recently been applied for river flow measurement. In this paper UAV images were first used to acquire surface velocity fields of a small river in an arid area in Iran based on the principles of Large Scale Particle Image Velocimetry (LSPIV). Subsequently, Large Eddy PIV method was applied on the instantaneous velocity data to obtain turbulent kinetic energy dissipation rates along a selected cross section of the experimented river. In addition, a UAV image was captured and processed to gain the bed material grain size distribution and consequently the Manning roughness coefficient. The resulted gradation curve matched the graph given by sieve analysis with an accuracy of nearly 7.8 percent. Moreover, an equation combining the acquired surface velocity, dissipation rates and Manning coefficient was used to estimate the river bathymetry. Although, the evaluated bathymetry does not fit the surveyed cross section very well, the average predicted depth matches the measured mean depth with a high precision. Finally, the river flow rate calculated using the information solely resulted from UAV images fitted the measured discharge with an accuracy of 5 percent proving the described framework to be a very effective method for primary river flow evaluation especially when supplementary depth measurement is not feasible.https://jdcr.birjand.ac.ir/article_3055_e714220f7247f04d3d1d1bc1250730ab.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS)Spatial analysis of flood risk in Tabas watershed using satellite images and geographic information system (GIS)105118305610.22077/jdcr.2024.7489.1066FAالهام یوسفیاستادیار، گروه محیط زیست، دانشکده منابع طبیعی و محیط زیست، دانشگاه بیرجند، ایران.مهدی کفاشکارشناسی ارشد برنامهریزی کاربری اراضی، دانشکده محیط زیست، دانشگاه بیرجند.بیرجند، ایران.محسن شریعتیکارشناسی ارشد برنامهریزی محیط زیست، دانشگاه تهران، تهران، ایران.Journal Article20240405Among the natural phenomena, flood can be the biggest cause of damage, which always endangers the lives and properties of people. One of the management measures which can play a significant role in reducing the damages is flood risk zoning. In this research, flood risk zoning has been done in the Tabas watershed. In general, the steps and this research were done in four steps the effective criteria in creating the risk of flooding were identified, and the relevant layers were prepared. In the next step, rasterization and standardization were done using fuzzy membership functions, then weighting of parameters was done using the ahp, and finally overlapping of the layers was done using fuzzy operators. The criteria of distance from river, slope, land use, rainfall, soil, dem and ndvi were respectively assigned the highest weight. Also, all fuzzy superposition operators have been used for flood risk zoning.<br />Among these operators, the 0.9 gamma operator shows the best and most reasonable result, so this map was chosen as the final flood risk zoning. In the final map, the total area of high-risk areas is 15432.13 ha. According to the final map obtained, areas with very high flood risk are located in the eastern part of the studied area. Areas with low risk are mostly located in the plains, valleys and depressions with less slope. The method used in this study can be used in other studies such as zoning of earthquake risk potential, development zoning and spatial analysis of disease distribution.Among the natural phenomena, flood can be the biggest cause of damage, which always endangers the lives and properties of people. One of the management measures which can play a significant role in reducing the damages is flood risk zoning. In this research, flood risk zoning has been done in the Tabas watershed. In general, the steps and this research were done in four steps the effective criteria in creating the risk of flooding were identified, and the relevant layers were prepared. In the next step, rasterization and standardization were done using fuzzy membership functions, then weighting of parameters was done using the ahp, and finally overlapping of the layers was done using fuzzy operators. The criteria of distance from river, slope, land use, rainfall, soil, dem and ndvi were respectively assigned the highest weight. Also, all fuzzy superposition operators have been used for flood risk zoning.<br />Among these operators, the 0.9 gamma operator shows the best and most reasonable result, so this map was chosen as the final flood risk zoning. In the final map, the total area of high-risk areas is 15432.13 ha. According to the final map obtained, areas with very high flood risk are located in the eastern part of the studied area. Areas with low risk are mostly located in the plains, valleys and depressions with less slope. The method used in this study can be used in other studies such as zoning of earthquake risk potential, development zoning and spatial analysis of disease distribution.https://jdcr.birjand.ac.ir/article_3056_0f07615e69d820bdff1cb37fca87d2ed.pdfدانشگاه بیرجند-گروه پژوهشی خشکسالی وتغییراقلیممجله پژوهش های خشکسالی و تغییراقلیم3092-60762220240822The Use of Time Series and Artificial Neural Networks in Drought Simulation (Case Study: Bojnourd City)The Use of Time Series and Artificial Neural Networks in Drought Simulation (Case Study: Bojnourd City)119134308510.22077/jdcr.2024.8014.1074FAمحترم محمدیاریانگروه جغرافیای آموزشی، دانشگاه فرهنگیان، تهران، ایران.ابراهیم امیریگروه جغرافیای آموزشی، دانشگاه فرهنگیان، تهران، ایران.Journal Article20240808Drought is a climatic phenomenon and is actually considered a part of the climate of a region. Drought has a hidden nature and the duration of its occurrence is long, and its effects appear in a non-structural way and as a result, the damages caused by it in various sectors such as agriculture, social, economic, environmental, etc. gradually appear. In this research, artificial neural network was used as a powerful tool in simulating the drought of Bojnourd city. For this purpose, the statistical data of precipitation, relative humidity, and temperature from 1997 to 2014 are the basis of the upcoming research. SPI drought index was used as sample output. 70% of the data were considered as training data and 30% as testing data. The networks used are of backpropagation type and radial basis function with error backpropagation algorithm and Lunberg-Marquardt learning method. Box Jenkins method from MINITAB software and BPI to BP24 models from MATLAB software were used in the branch for drought simulation. The value of the correlation coefficient for the training phase (R) was 0.95 and for the test phase it was 0.81, which has the lowest error in the test phase.the results of the training phase were close to each other in most of the models. Among the selected models of the post-release network, the BP19 model was selected as the selected example. RMSE determination coefficient was estimated with a value of 0.16 for the training stage and MAE (mean absolute error) was estimated as 0.0071.Drought is a climatic phenomenon and is actually considered a part of the climate of a region. Drought has a hidden nature and the duration of its occurrence is long, and its effects appear in a non-structural way and as a result, the damages caused by it in various sectors such as agriculture, social, economic, environmental, etc. gradually appear. In this research, artificial neural network was used as a powerful tool in simulating the drought of Bojnourd city. For this purpose, the statistical data of precipitation, relative humidity, and temperature from 1997 to 2014 are the basis of the upcoming research. SPI drought index was used as sample output. 70% of the data were considered as training data and 30% as testing data. The networks used are of backpropagation type and radial basis function with error backpropagation algorithm and Lunberg-Marquardt learning method. Box Jenkins method from MINITAB software and BPI to BP24 models from MATLAB software were used in the branch for drought simulation. The value of the correlation coefficient for the training phase (R) was 0.95 and for the test phase it was 0.81, which has the lowest error in the test phase.the results of the training phase were close to each other in most of the models. Among the selected models of the post-release network, the BP19 model was selected as the selected example. RMSE determination coefficient was estimated with a value of 0.16 for the training stage and MAE (mean absolute error) was estimated as 0.0071.https://jdcr.birjand.ac.ir/article_3085_c0afabc177ab948e472bf66ee8943490.pdf