University of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120250309Estimation of Suspended Sediment in Coastal Areas of the Caspian Sea Using Machine Learning TechniquesEstimation of Suspended Sediment in Coastal Areas of the Caspian Sea Using Machine Learning Techniques118336510.22077/jdcr.2025.8983.1121FAEbrahimNohaniDepartment of Civil Engineering, Materials and Energy Research Center, Dez.C., Islamic Azad University, Dezful, Iran.0000-0002-2692-6253HamidrezaBabaaliAssociate Professor, Department of Civil Engineering, Islamic Azad University, Khorramabad branch, Khorramabad, Iran0000-0001-9410-879XRezaDehghaniPhD in Water Sciences and Engineering, Department of Soil Conservation and Watershed Management, Lorestan Province Agriculture and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Khorramab0009-0008-3309-2286Journal Article20250219Modeling suspended sediment is a crucial subject for decision-makers at the watershed level. Accurate and reliable modeling of suspended sediment load is essential for planning, managing, and designing water resource structures and river systems. In this research, a new hybrid intelligent approach based on the Support Vector Regression (SVR) model has been developed for estimating river sediment. For this purpose, two optimization algorithms, namely Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO), were employed to model the amount of suspended river sediment. For modeling, statistical data from the Babolroud River hydrometric station, located in Mazandaran province, were used as a case study. Data from 19 input parameter combinations were used in the years 1382 to 1402 (solar calendar years) which is 2003-2023 Gregorian calendar. To evaluate the performance of the models, the evaluation criteria of correlation coefficient, root mean square error, mean absolute error, and Nash-Sutcliffe efficiency coefficient were used. The results showed that combined scenarios in the investigated models improve the performance of the model. The results obtained from the evaluation criteria also showed that the Wavelet-SVR model has a correlation coefficient of 0.962, a root mean square error of 0.344 ton/day, a mean absolute error of 0.158 ton/day, and a Nash-Sutcliffe efficiency coefficient of 0.970 in the validation phase. Overall, the results showed that the use of intelligent models based on the SVR approach can be an effective approach in river engineering stability.Modeling suspended sediment is a crucial subject for decision-makers at the watershed level. Accurate and reliable modeling of suspended sediment load is essential for planning, managing, and designing water resource structures and river systems. In this research, a new hybrid intelligent approach based on the Support Vector Regression (SVR) model has been developed for estimating river sediment. For this purpose, two optimization algorithms, namely Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO), were employed to model the amount of suspended river sediment. For modeling, statistical data from the Babolroud River hydrometric station, located in Mazandaran province, were used as a case study. Data from 19 input parameter combinations were used in the years 1382 to 1402 (solar calendar years) which is 2003-2023 Gregorian calendar. To evaluate the performance of the models, the evaluation criteria of correlation coefficient, root mean square error, mean absolute error, and Nash-Sutcliffe efficiency coefficient were used. The results showed that combined scenarios in the investigated models improve the performance of the model. The results obtained from the evaluation criteria also showed that the Wavelet-SVR model has a correlation coefficient of 0.962, a root mean square error of 0.344 ton/day, a mean absolute error of 0.158 ton/day, and a Nash-Sutcliffe efficiency coefficient of 0.970 in the validation phase. Overall, the results showed that the use of intelligent models based on the SVR approach can be an effective approach in river engineering stability.https://jdcr.birjand.ac.ir/article_3365_b445e314138101eecc58503e98aa2b2d.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Development of the Optimal Exploitation Model of the Water Resources of Handijan Plain with Multi-Objective Bargaining MethodDevelopment of the Optimal Exploitation Model of the Water Resources of Handijan Plain with Multi-Objective Bargaining Method1940363910.22077/jdcr.2025.9141.1131FAFeizollahMotezazadehDepartment of Water Sciences, Shoushtar Branch, Islamic
Azad University, Shoushtar, Iran0009-0007-1129-0268MohammadhosseinPourmohammadiDepartment of Water Sciences, Shoushtar Branch, Islamic
Azad University, Shoushtar, IranSaebKhoshnavazDepartment of Water Sciences, Shoushtar Branch, Islamic
Azad University, Shoushtar, Iran0000-0003-1141-5714EbrahimNohaniDepartment of Civil Engineering, Materials and Energy Research Center, Dez.C., Islamic Azad University, Dezful, Iran.HosseinEslamiDepartment of Water Sciences, Shoushtar Branch, Islamic
Azad University, Shoushtar, IranJournal Article20250320Abstract<br /><br />Water resources management in agriculture is one of the main components of sustainable economic development and food security. In terms of growing season, crop plants are divided into two groups: spring and winter plants. Winter plants are generally called dryland crops. Dryland crops use winter rainfall to meet water needs. At the beginning of the growing season, several irrigation stages are recommended to provide soil moisture, and at the end of the growing season, supplementary irrigation is planned to fill the seeds. The production of dryland crops is less than the potential, but water productivity is higher. In this study, the issue of agricultural water transfer in the Handijan plain of Khuzestan province was first addressed in order to evaluate water resources for dryland cultivation, and then the optimal amounts of water required for dryland cultivation of four crops, wheat, barley, rapeseed, and lentils, were calculated. The results showed that the water crisis situation in the studied plain will be increasingly serious and the need for dryland cultivation and supplementary irrigation is recommended. In addition, in water deficit conditions, it is essential to reduce autumn irrigation and meet the plant's water needs during the stages of maximum plant coverage. Maximum plant coverage for the studied plants is from late March to mid-May. After this stage, the plant canopy gradually wears out and the final crop is harvested.<br /><br />Keywords: Irrigation optimization, rainfed cultivation, bargaining, HendijanAbstract<br /><br />Water resources management in agriculture is one of the main components of sustainable economic development and food security. In terms of growing season, crop plants are divided into two groups: spring and winter plants. Winter plants are generally called dryland crops. Dryland crops use winter rainfall to meet water needs. At the beginning of the growing season, several irrigation stages are recommended to provide soil moisture, and at the end of the growing season, supplementary irrigation is planned to fill the seeds. The production of dryland crops is less than the potential, but water productivity is higher. In this study, the issue of agricultural water transfer in the Handijan plain of Khuzestan province was first addressed in order to evaluate water resources for dryland cultivation, and then the optimal amounts of water required for dryland cultivation of four crops, wheat, barley, rapeseed, and lentils, were calculated. The results showed that the water crisis situation in the studied plain will be increasingly serious and the need for dryland cultivation and supplementary irrigation is recommended. In addition, in water deficit conditions, it is essential to reduce autumn irrigation and meet the plant's water needs during the stages of maximum plant coverage. Maximum plant coverage for the studied plants is from late March to mid-May. After this stage, the plant canopy gradually wears out and the final crop is harvested.<br /><br />Keywords: Irrigation optimization, rainfed cultivation, bargaining, Hendijanhttps://jdcr.birjand.ac.ir/article_3639_ba304f3809ed31d0ad97b5a2b5df2a39.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522The Impact of Organic and Inorganic Amendments (Nano and Non-Nano) on Improving Physical and Hydraulic Properties of Saline SoilsThe Impact of Organic and Inorganic Amendments (Nano and Non-Nano) on Improving Physical and Hydraulic Properties of Saline Soils4160370010.22077/jdcr.2025.9403.1144FAFatemehHajebiPhD Student of Department of Natural Resources Engineering, Faculty of Natural Resources and Agriculture, University of Hormozgan, Bandar Abbas, Iran.NavazollahMoradiAssistant professor, Department of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, BandarAbbas, Iran.0000-0002-6588-9440OmmolbaninBazrafshan3. Professor, Department of Natural Resources Engineering, Faculty of Natural Resources and Agriculture, University of Hormozgan, Bandar Abbas, Iran.0000-0003-2524-3992AdnanSadeghi LariAssociate. Professor, Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, Bandar Abbas, IranJournal Article20250517Nanotechnology offers a promising approach for improving the physical and hydraulic properties of saline soils. To evaluate this potential, a study was conducted to assess the effects of both organic and inorganic amendments, applied at nano and conventional scales, on saline loamy soil. Soil samples were collected from a depth of 5 to 30 cm, and various treatments were applied, including pomegranate peel biochar and nanobiochar, nanobentonite, zeolite, microsilica, and nanosilica. These treatments were tested using soil columns (35 × 10 cm) under a completely randomized design with three replications. The results indicated that all applied amendments improved soil structural and moisture characteristics. Specifically, they increased the mean weight diameter of soil aggregates, enhanced the water stability index of aggregates, and optimized key moisture parameters such as field capacity, permanent wilting point, and available water content. Among all treatments, nanosilica showed the highest improvement in aggregate stability, increasing it by 35% compared to the control. This treatment also resulted in the lowest bulk density (1.5 g/cm³). The lowest permanent wilting point was observed in the conventional silica treatment, which was significantly different from other treatments at the 5% level. Except for conventional biochar, all other nano and non-nano amendments significantly increased field capacity at the 5% significance level. Similarly, the available water content was significantly improved by these amendments, excluding the conventional biochar treatment. Overall, the findings confirm the effectiveness of soil amendments, particularly nanosilica, in enhancing soil structure, aggregate stability, and hydraulic properties of saline loamy soils.Nanotechnology offers a promising approach for improving the physical and hydraulic properties of saline soils. To evaluate this potential, a study was conducted to assess the effects of both organic and inorganic amendments, applied at nano and conventional scales, on saline loamy soil. Soil samples were collected from a depth of 5 to 30 cm, and various treatments were applied, including pomegranate peel biochar and nanobiochar, nanobentonite, zeolite, microsilica, and nanosilica. These treatments were tested using soil columns (35 × 10 cm) under a completely randomized design with three replications. The results indicated that all applied amendments improved soil structural and moisture characteristics. Specifically, they increased the mean weight diameter of soil aggregates, enhanced the water stability index of aggregates, and optimized key moisture parameters such as field capacity, permanent wilting point, and available water content. Among all treatments, nanosilica showed the highest improvement in aggregate stability, increasing it by 35% compared to the control. This treatment also resulted in the lowest bulk density (1.5 g/cm³). The lowest permanent wilting point was observed in the conventional silica treatment, which was significantly different from other treatments at the 5% level. Except for conventional biochar, all other nano and non-nano amendments significantly increased field capacity at the 5% significance level. Similarly, the available water content was significantly improved by these amendments, excluding the conventional biochar treatment. Overall, the findings confirm the effectiveness of soil amendments, particularly nanosilica, in enhancing soil structure, aggregate stability, and hydraulic properties of saline loamy soils.https://jdcr.birjand.ac.ir/article_3700_f92586a25bb3145facd64ab20fd554ff.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Adaptive Drought Monitoring with an Integrated Approach of Terrestrial Data and Remote Sensing TechnologyAdaptive Drought Monitoring with an Integrated Approach of Terrestrial Data and Remote Sensing Technology6180381310.22077/jdcr.2025.9699.1154FAMahboubeEbrahimiAssistant Professor, Department of Agriculture, Faculty of Technology and Engineering, Payame Noor University, Tehran,
Iran0000-0002-6135-3577HadiSiasarAssistant Professor, Department of Agriculture, Faculty of Technology and Engineering, Payame Noor University, Tehran,
Iran.Journal Article20250707The lack of coverage of meteorological stations and the spatial-temporal heterogeneity of data have made accurate assessment of drought in metropolitan cities such as Tehran uncertain. This study aims to provide an integrated framework for drought monitoring by integrating remote sensing indices VCI from MOD13A2, TCI from MOD11A2, PCI from satellite precipitation product, and SMCI from soil moisture along with meteorological-hydrological indices (SPI, SPEI, and PDSI) for Tehran and its suburbs during the period 2000 to 2022. Preprocessing and extraction of indices were performed in Google Earth Engine and then correlation between indices at monthly, seasonal, and annual scales was analyzed using Mann-Kendall and age-slope tests, trends, and Pearson coefficient. The results showed that precipitation-based indices (SPI and PCI) have the greatest ability to explain short-term changes and show a high correlation with the soil moisture status index SMCI; in contrast, VCI responds to moisture fluctuations with a time lag, and TCI has an inverse and significant relationship with drought severity at long-term scales (PDSI/SPEI). From a temporal perspective, summers, with a combination of rainfall deficiency and heat stress, recorded the highest vulnerability, and the years 2008, 2010, and 2016 were the most severe drought periods. Convergence of evidence shows that the proposed multi-attribute approach, while reducing uncertainty, provides a more accurate picture of urban drought dynamics and can be the basis for water demand management planning, early warning, and urban greening model modification.The lack of coverage of meteorological stations and the spatial-temporal heterogeneity of data have made accurate assessment of drought in metropolitan cities such as Tehran uncertain. This study aims to provide an integrated framework for drought monitoring by integrating remote sensing indices VCI from MOD13A2, TCI from MOD11A2, PCI from satellite precipitation product, and SMCI from soil moisture along with meteorological-hydrological indices (SPI, SPEI, and PDSI) for Tehran and its suburbs during the period 2000 to 2022. Preprocessing and extraction of indices were performed in Google Earth Engine and then correlation between indices at monthly, seasonal, and annual scales was analyzed using Mann-Kendall and age-slope tests, trends, and Pearson coefficient. The results showed that precipitation-based indices (SPI and PCI) have the greatest ability to explain short-term changes and show a high correlation with the soil moisture status index SMCI; in contrast, VCI responds to moisture fluctuations with a time lag, and TCI has an inverse and significant relationship with drought severity at long-term scales (PDSI/SPEI). From a temporal perspective, summers, with a combination of rainfall deficiency and heat stress, recorded the highest vulnerability, and the years 2008, 2010, and 2016 were the most severe drought periods. Convergence of evidence shows that the proposed multi-attribute approach, while reducing uncertainty, provides a more accurate picture of urban drought dynamics and can be the basis for water demand management planning, early warning, and urban greening model modification.https://jdcr.birjand.ac.ir/article_3813_0a49e3c3a03ebde64f85c0bacd8a08e2.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Assessing the Impact of Climate Change on Heat Stress on Strategic Agricultural Products in Qazvin ProvinceAssessing the Impact of Climate Change on Heat Stress on Strategic Agricultural Products in Qazvin Province81104370210.22077/jdcr.2025.9739.1157FAHadiRamezani EtedaliProfessor, Irrigation and Drainage, Department of Water Sciences and Engineering, Faculty of Agriculture and Natural
Resources, Imam Khomeini International University, Qazvin, Iran.0000-0002-4840-0201SakineKoohiDepartment of Water Engineering, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran.0000-0002-0118-795XJournal Article20250712Abstract: Climate change, particularly through heat stress, presents a significant threat to agricultural production in Qazvin Province, a vital agricultural hub in Iran. This study aims to analyze the temporal patterns of heat stress—encompassing frequency, intensity, and duration—affecting strategic crops such as wheat, maize, and barley, and to evaluate its impact on their yields under the SSP2-4.5 and SSP5-8.5 climate scenarios. To this end, historical data (1997–2014) from the Qazvin synoptic station and projections from five global climate models (CNRM-CM6-1, CanESM5, GFDL-ESM4, HadGEM3-GC31-LL, MIROC6) were employed, utilizing an optimized ensemble model approach. The findings indicate that, particularly under the SSP5-8.5 scenario, the frequency of heat stress will rise substantially, with maize identified as the most vulnerable crop, experiencing nearly 100% heat stress frequency during its growing season by 2099. Furthermore, both the intensity and duration of heat stress are projected to increase, resulting in significant yield reductions: wheat from 4.20 to 3.00 ton/h, barley from 3.80 to 2.18 ton/h, and maize from 37.9 to 33.1 ton/h. These results highlight the urgent need for adaptation strategies in Qazvin Province, such as adjusting planting schedules and developing heat-resistant crop varieties. Additionally, meticulous planning for water resource management and infrastructure development is critical to bolster agricultural resilience, as neglecting these measures could jeopardize regional food security and economic stability.Abstract: Climate change, particularly through heat stress, presents a significant threat to agricultural production in Qazvin Province, a vital agricultural hub in Iran. This study aims to analyze the temporal patterns of heat stress—encompassing frequency, intensity, and duration—affecting strategic crops such as wheat, maize, and barley, and to evaluate its impact on their yields under the SSP2-4.5 and SSP5-8.5 climate scenarios. To this end, historical data (1997–2014) from the Qazvin synoptic station and projections from five global climate models (CNRM-CM6-1, CanESM5, GFDL-ESM4, HadGEM3-GC31-LL, MIROC6) were employed, utilizing an optimized ensemble model approach. The findings indicate that, particularly under the SSP5-8.5 scenario, the frequency of heat stress will rise substantially, with maize identified as the most vulnerable crop, experiencing nearly 100% heat stress frequency during its growing season by 2099. Furthermore, both the intensity and duration of heat stress are projected to increase, resulting in significant yield reductions: wheat from 4.20 to 3.00 ton/h, barley from 3.80 to 2.18 ton/h, and maize from 37.9 to 33.1 ton/h. These results highlight the urgent need for adaptation strategies in Qazvin Province, such as adjusting planting schedules and developing heat-resistant crop varieties. Additionally, meticulous planning for water resource management and infrastructure development is critical to bolster agricultural resilience, as neglecting these measures could jeopardize regional food security and economic stability.https://jdcr.birjand.ac.ir/article_3702_a928731e103dfc64c0027fa84709689e.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Temporal Analysis and Intensity of Meteorological Drought (Case Study: Qaen City in South Khorasan Province)Temporal Analysis and Intensity of Meteorological Drought (Case Study: Qaen City in South Khorasan Province)105130405010.22077/jdcr.2025.9807.1159FAAliRezvaniAssistant Professor,, Department of Engineering,, Bozorgmehr University of Qaenat,, Qaen,. Iran.0000-0001-9617-1469MahdiKhorashadizadehAssistant Professor, Department of Engineering, Bozorgmehr University of Qaenat, Qaen, IranMohsenRezaeeAssistant Professor, Department of Civil Engineering, Zabol University, Zabol, IranJournal Article20250730Meteorological drought, as the initial stage of the broader drought process, is a significant climatic hazard with far-reaching implications for environmental sustainability. This study aims to evaluate the trend of meteorological drought in Qaen City, located in South Khorasan Province, over a 37-year period (from the 1988 to 2024 water years). For this purpose, annual precipitation and temperature data, along with two indices—the Percent of Normal Index (PNPI) and the Standardized Precipitation Index (SPI)—were used to analyze drought conditions in the region. According to the results, the average annual precipitation of the region was 161.30 mm (with a coefficient of variation of 37%), indicating high fluctuations in yearly precipitation and the occurrence of years with unusually high or low precipitation. Analyzing the trend in annual precipitation using linear regression, the Mann–Kendall test, and Sen’s slope method revealed no significant trend in precipitation values. However, the annual average temperature showed a significant upward trend, increasing at a rate of 0.078(°C)⁄year. Based on the PNPI and SPI indices, approximately 41% and 16% of the years, respectively (especially after 1999), experienced drought conditions. Wet periods were more frequently observed during the years 1990–1999, as well as in 2019 and 2020. The comparison of two drought indices reveals general agreement during extreme conditions but differences in normal years, as SPI provides a more conservative description of conditions. The study’s overall findings indicate a rising temperature trend, unstable precipitation patterns, and frequent drought occurrences in the region, highlighting increasing climate variability.Meteorological drought, as the initial stage of the broader drought process, is a significant climatic hazard with far-reaching implications for environmental sustainability. This study aims to evaluate the trend of meteorological drought in Qaen City, located in South Khorasan Province, over a 37-year period (from the 1988 to 2024 water years). For this purpose, annual precipitation and temperature data, along with two indices—the Percent of Normal Index (PNPI) and the Standardized Precipitation Index (SPI)—were used to analyze drought conditions in the region. According to the results, the average annual precipitation of the region was 161.30 mm (with a coefficient of variation of 37%), indicating high fluctuations in yearly precipitation and the occurrence of years with unusually high or low precipitation. Analyzing the trend in annual precipitation using linear regression, the Mann–Kendall test, and Sen’s slope method revealed no significant trend in precipitation values. However, the annual average temperature showed a significant upward trend, increasing at a rate of 0.078(°C)⁄year. Based on the PNPI and SPI indices, approximately 41% and 16% of the years, respectively (especially after 1999), experienced drought conditions. Wet periods were more frequently observed during the years 1990–1999, as well as in 2019 and 2020. The comparison of two drought indices reveals general agreement during extreme conditions but differences in normal years, as SPI provides a more conservative description of conditions. The study’s overall findings indicate a rising temperature trend, unstable precipitation patterns, and frequent drought occurrences in the region, highlighting increasing climate variability.https://jdcr.birjand.ac.ir/article_4050_385822e359afa26d52b5b286226f2cea.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Modeling and Optimization of Water Allocation Using a Hybrid LSTM–HHOA Approach Under Climate Change ConditionsModeling and Optimization of Water Allocation Using a Hybrid LSTM–HHOA Approach Under Climate Change Conditions131158369610.22077/jdcr.2025.9958.1165FAParisa-SadatAshoftehAssociate Professor, Department of Civil Engineering, University of Qom, Qom, Iran0000-0003-2561-0510LeilaShakaramiPh.D. Student, Department of Civil Engineering, University of Qom, Qom, IranJournal Article20250822The present study aimed to optimize water allocation from the Qarnaku Dam for the future period (2070–2099) and enhance the resilience of the water supply system. Among CMIP5 climate models, GFDL-ESM2G was selected as the most suitable option for temperature, and NorESM1-M was selected for precipitation. Subsequently, monthly runoff was simulated using Long Short-Term Memory (LSTM) networks, yielding satisfactory accuracy. Agricultural water demand was estimated using the Cropwat model, indicating a 20% increase in future net irrigation requirements. The performance of the Horse Herd Optimization Algorithm (HHOA) and Genetic Programming (GP) was evaluated using the Rastrigin and Rosenbrock benchmark functions, revealing superior results for HHOA. Further analysis showed that HHOA reduced water deficits by up to 22% and improved reservoir resilience from 67% to 79%. Additionally, the LSTM model achieved a Nash–Sutcliffe Efficiency (NSE) coefficient of 0.85, confirming its reliability in simulating monthly runoff. Overall, the integration of advanced metaheuristic techniques with intelligent runoff prediction models provides an effective framework for reservoir management under climate change conditions.The present study aimed to optimize water allocation from the Qarnaku Dam for the future period (2070–2099) and enhance the resilience of the water supply system. Among CMIP5 climate models, GFDL-ESM2G was selected as the most suitable option for temperature, and NorESM1-M was selected for precipitation. Subsequently, monthly runoff was simulated using Long Short-Term Memory (LSTM) networks, yielding satisfactory accuracy. Agricultural water demand was estimated using the Cropwat model, indicating a 20% increase in future net irrigation requirements. The performance of the Horse Herd Optimization Algorithm (HHOA) and Genetic Programming (GP) was evaluated using the Rastrigin and Rosenbrock benchmark functions, revealing superior results for HHOA. Further analysis showed that HHOA reduced water deficits by up to 22% and improved reservoir resilience from 67% to 79%. Additionally, the LSTM model achieved a Nash–Sutcliffe Efficiency (NSE) coefficient of 0.85, confirming its reliability in simulating monthly runoff. Overall, the integration of advanced metaheuristic techniques with intelligent runoff prediction models provides an effective framework for reservoir management under climate change conditions.https://jdcr.birjand.ac.ir/article_3696_95c9d994f8d75d4d60f8bb8f25902339.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Assessing the Impact of Climate-Induced Migration on the Expansion of InformalAssessing the Impact of Climate-Induced Migration on the Expansion of Informal159180376410.22077/jdcr.2025.9971.1167FASalehEbrahimipourPhD Student in Geography and Urban Planning, Department of Geography, Faculty of Management and Accounting, Islamic
Azad University, Mashhad, Iran.0009-0007-8400-1922KatayoonAlizadehAssociate Professor, Department of Geography and Urban Planning, Department of Geography, Faculty of Management and Accounting, Islamic Azad University, Mashhad, Iran.Journal Article20250825Objective: This study aimed to analyze the impact of climate-induced migration on the expansion of informal settlements (marginalization) in the metropolitan city of Mashhad, Iran.<br /><br />Methods: This mixed-methods (quantitative-qualitative) study was conducted with a statistical population of 384 migrants residing in informal settlements in Mashhad (selected via cluster sampling) and 20 semi-structured interviews with experts. Data were collected using a researcher-made questionnaire (Total Cronbach’s α = 0.84) and interviews, and were analyzed using path analysis, regression, and thematic analysis.<br /><br />Findings: Quantitative findings revealed that climatic pressures (β = 0.59) and spatial inequality (β = 0.44) had a direct and significant impact on marginalization. Furthermore, climate migration indirectly affected this phenomenon through reducing socio-economic resilience (β = -0.32). Qualitative findings identified five main themes: Migration as a Response to Livelihood Crisis, Reproduction of Inequality, Weak Resilience, Policy Vacuum, and An Uncertain Future.<br /><br />Conclusion: The results confirm that climate migration, in the absence of supportive policies, is not only an emergency response but also a factor in the reproduction of poverty and spatial inequality. Managing this phenomenon requires the development of integrated, justice-oriented policies and planning to enhance resilience in both sending and receiving areas.Objective: This study aimed to analyze the impact of climate-induced migration on the expansion of informal settlements (marginalization) in the metropolitan city of Mashhad, Iran.<br /><br />Methods: This mixed-methods (quantitative-qualitative) study was conducted with a statistical population of 384 migrants residing in informal settlements in Mashhad (selected via cluster sampling) and 20 semi-structured interviews with experts. Data were collected using a researcher-made questionnaire (Total Cronbach’s α = 0.84) and interviews, and were analyzed using path analysis, regression, and thematic analysis.<br /><br />Findings: Quantitative findings revealed that climatic pressures (β = 0.59) and spatial inequality (β = 0.44) had a direct and significant impact on marginalization. Furthermore, climate migration indirectly affected this phenomenon through reducing socio-economic resilience (β = -0.32). Qualitative findings identified five main themes: Migration as a Response to Livelihood Crisis, Reproduction of Inequality, Weak Resilience, Policy Vacuum, and An Uncertain Future.<br /><br />Conclusion: The results confirm that climate migration, in the absence of supportive policies, is not only an emergency response but also a factor in the reproduction of poverty and spatial inequality. Managing this phenomenon requires the development of integrated, justice-oriented policies and planning to enhance resilience in both sending and receiving areas.https://jdcr.birjand.ac.ir/article_3764_641d77dd5271fca28764612a028d9c8e.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Assessment of the Intensity and Duration of Meteorological Drought in South Khorasan Province in the Mid-Term Future HorizonAssessment of the Intensity and Duration of Meteorological Drought in South Khorasan Province in the Mid-Term Future Horizon181202372810.22077/jdcr.2025.10060.1169FAAmirKhayatPhD Student in Irrigation and Drainage, Department of Water Science and Engineering, University of Birjand, Iran.0009-0003-3450-8371MahdiAmirabadizadehAssociate Professor, Department of Water Science and Engineering, and Member of the Drought
and Climate Change Research Group, University of Birjand, Birjand, Iran.0000-0002-8626-4036ZahraAkhondiAgricultural Jihad Organization of South Khorasan Province0009-0003-1368-7809Journal Article20250909Drought is a recurring natural climatic phenomenon that typically occurs in all parts of the world. This study was conducted to investigate the intensity and duration of drought in the two counties of Ferdows and Tabas in South Khorasan Province. In this study, daily precipitation time series data for the selected stations were collected over a 25-year statistical period (1990–2014), and the Standardized Precipitation Index (SPI) was analyzed for the two studied stations using two GCM models, IPSL and MPI, from CMIP6. The SSP2-4.5 scenario was used to estimate SPI for the period 2030–2059, and the BCSD downscaling method was applied to predict meteorological data. The results indicate that the overall SPI trend for both models show significant fluctuations between positive and negative values, posing challenges for water resource management in the two counties. However, the IPSL model predicts drought with greater intensity, highlighting the need to develop water management plans based on various climate scenarios for the studied counties. According to the study’s findings, an increase in the average intensity and duration of drought in the future period compared to the baseline indicates an intensification of drought. Nevertheless, the number of normal periods in both the baseline and future periods was higher than other periods at the stations studied.Drought is a recurring natural climatic phenomenon that typically occurs in all parts of the world. This study was conducted to investigate the intensity and duration of drought in the two counties of Ferdows and Tabas in South Khorasan Province. In this study, daily precipitation time series data for the selected stations were collected over a 25-year statistical period (1990–2014), and the Standardized Precipitation Index (SPI) was analyzed for the two studied stations using two GCM models, IPSL and MPI, from CMIP6. The SSP2-4.5 scenario was used to estimate SPI for the period 2030–2059, and the BCSD downscaling method was applied to predict meteorological data. The results indicate that the overall SPI trend for both models show significant fluctuations between positive and negative values, posing challenges for water resource management in the two counties. However, the IPSL model predicts drought with greater intensity, highlighting the need to develop water management plans based on various climate scenarios for the studied counties. According to the study’s findings, an increase in the average intensity and duration of drought in the future period compared to the baseline indicates an intensification of drought. Nevertheless, the number of normal periods in both the baseline and future periods was higher than other periods at the stations studied.https://jdcr.birjand.ac.ir/article_3728_460b491b917d4185ed1f5be97229721a.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Effects of Foliar Application of Zinc Oxide Nanoparticles on Morphophysiological and Bochemical Responses of Catharanthus Roseus (L.) G. Don under Water Deficit StressEffects of Foliar Application of Zinc Oxide Nanoparticles on Morphophysiological and Bochemical Responses of Catharanthus Roseus (L.) G. Don under Water Deficit Stress203226381710.22077/jdcr.2025.10186.1176FAHaniyehHaq NariMs.C. Graduate in Ornamental Plants, Department of Horticultural Sciences, Faculty of Agriculture, Lorestan University, Lorestan, Iran0009-0006-2797-5846AbdolhosseinRezaei NejadProfessor of Ornamental Plant Physiology, Department of Horticultural Sciences, Faculty of Agriculture, Lorestan University, Lorestan, Iran0000-0002-5428-3697FarhadBeiranvandPh.D. in Horticultural Sciences – Physiology of Ornamental Plants. Department of Horticultural Sciences, Faculty of Agriculture, Lorestan University, Lorestan, IranNahidZomorrodiPh.D. in Horticultural Sciences – Physiology of Ornamental Plants. Department of Horticultural Sciences, Faculty of Agriculture, Lorestan University, Lorestan, IranJournal Article20251002The present study aimed to investigate the effects of foliar application of zinc oxide nanoparticles (ZnO-NPs) on the morphological and physio-biochemical traits of the ornamental–medicinal plant periwinkle [Catharanthus roseus (L.)] under water deficit stress. The experiment was conducted as a factorial arrangement based on a completely randomized design) with four replications. The first factor was water deficit at three levels (80%, 50%, and 20% of available water content), while the second factor consisted of foliar application of ZnO-NPs at four concentrations (0, 50, 100, and 200 µM), applied as a pre-treatment at the four-leaf stage. The experiment continued until full flowering (two months), after which morpho-physiological parameters (plant height, stem length and diameter, leaf number, root volume and length, fresh and dry weights of stems, leaves, and roots, gas exchange parameters, relative water content (RWC), and electrolyte leakage (EL)) as well as biochemical traits (malondialdehyde (MDA) content, proline content, photosynthetic pigments concentration, and the activities of catalase, peroxidase, and ascorbate peroxidase) were measured. The results demonstrated that water deficit stress significantly reduced plant height, leaf area, RWC, photosynthetic pigments concentration, fresh and dry biomass, and gas exchange, while increasing EL, MDA content, proline accumulation, and antioxidant enzyme activities. In contrast, foliar application of ZnO-NPs enhanced antioxidant enzyme activity, RWC, photosynthetic pigments, and gas exchange, thereby improving plant tolerance to drought stress. Among the tested concentrations, 50 and 100 µM ZnO-NPs were the most effective in alleviating the adverse effects of water deficit and promoting plant growth under stress conditions.The present study aimed to investigate the effects of foliar application of zinc oxide nanoparticles (ZnO-NPs) on the morphological and physio-biochemical traits of the ornamental–medicinal plant periwinkle [Catharanthus roseus (L.)] under water deficit stress. The experiment was conducted as a factorial arrangement based on a completely randomized design) with four replications. The first factor was water deficit at three levels (80%, 50%, and 20% of available water content), while the second factor consisted of foliar application of ZnO-NPs at four concentrations (0, 50, 100, and 200 µM), applied as a pre-treatment at the four-leaf stage. The experiment continued until full flowering (two months), after which morpho-physiological parameters (plant height, stem length and diameter, leaf number, root volume and length, fresh and dry weights of stems, leaves, and roots, gas exchange parameters, relative water content (RWC), and electrolyte leakage (EL)) as well as biochemical traits (malondialdehyde (MDA) content, proline content, photosynthetic pigments concentration, and the activities of catalase, peroxidase, and ascorbate peroxidase) were measured. The results demonstrated that water deficit stress significantly reduced plant height, leaf area, RWC, photosynthetic pigments concentration, fresh and dry biomass, and gas exchange, while increasing EL, MDA content, proline accumulation, and antioxidant enzyme activities. In contrast, foliar application of ZnO-NPs enhanced antioxidant enzyme activity, RWC, photosynthetic pigments, and gas exchange, thereby improving plant tolerance to drought stress. Among the tested concentrations, 50 and 100 µM ZnO-NPs were the most effective in alleviating the adverse effects of water deficit and promoting plant growth under stress conditions.https://jdcr.birjand.ac.ir/article_3817_fa6c94460e902005a0b660266190c8ba.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Development and Projection of a Composite Drought Index Using Copula Functions under Future Emission Scenarios: Application of CMIP6 Climate Models in the Minab Esteghlal Dam WatershedDevelopment and Projection of a Composite Drought Index Using Copula Functions under Future Emission Scenarios: Application of CMIP6 Climate Models in the Minab Esteghlal Dam Watershed227250382710.22077/jdcr.2025.10226.1180FAHojjat AllahKeshavarzPh.D., Student, Department of Natural Resources Engineering and Statistics, Faculty of Agricultural and Natural Resources
Engineering, University of Hormozgan, Bandar Abbas, Iran.OmmolbaninBazrafshanProfessor, Department of Natural Resources Engineering and Statistics, Faculty of Agricultural and Natural Resources Engineering, University of Hormozgan, Bandar Abbas, Iran.0000-0003-2524-3992MarziehShekariAssistant Professor, Department of Mathematics and Statistics, Faculty of Science, University of Hormozgan, Bandar Abbas, Iran.0000-0001-7243-2185HosseinZamaniAssistant Professor, Department of Mathematics and Statistics, Faculty of Science, University of Hormozgan, Bandar Abbas, Iran.0000-0003-1126-6288Journal Article20251009Composite droughts, which simultaneously affect both meteorological systems and water resources, pose a serious threat to arid and semi-arid regions. This study aimed to model droughts under future climate change scenarios using copula functions. Historical data (1989–2020) and statistically downscaled outputs from the CanESM5 climate model under SSP126, SSP370, and SSP585 scenarios for the future period (2021–2040) were utilized. Watershed runoff was simulated using the IHACRES model. P-12 and R-12 were calculated, and a joint hydro-meteorological drought index (JDHMI) was developed using copula functions. Drought characteristics (frequency, intensity, duration, and magnitude) and trends were analyzed for both historical and future periods. Results indicated that the composite JDHMI exhibited less fluctuation compared to univariate indices, providing a more stable and comprehensive depiction of drought conditions. Under climate change scenarios, the drought pattern is projected to shift from fewer but longer and more severe droughts to more frequent, shorter-duration droughts, particularly under the SSP585 scenario. Although average duration and intensity decreased in some scenarios, the drought "magnitude" index—integrating intensity and duration—increased across all future scenarios, indicating an overall intensification of drought content. Furthermore, the frequency of "severe" droughts significantly increased under all scenarios. Trend analysis confirmed a significant and accelerating decline in the JDHMI index in the future. This framework can serve as a scientific basis for early warning systems, and sustainable water resource management in the face of climate change.Composite droughts, which simultaneously affect both meteorological systems and water resources, pose a serious threat to arid and semi-arid regions. This study aimed to model droughts under future climate change scenarios using copula functions. Historical data (1989–2020) and statistically downscaled outputs from the CanESM5 climate model under SSP126, SSP370, and SSP585 scenarios for the future period (2021–2040) were utilized. Watershed runoff was simulated using the IHACRES model. P-12 and R-12 were calculated, and a joint hydro-meteorological drought index (JDHMI) was developed using copula functions. Drought characteristics (frequency, intensity, duration, and magnitude) and trends were analyzed for both historical and future periods. Results indicated that the composite JDHMI exhibited less fluctuation compared to univariate indices, providing a more stable and comprehensive depiction of drought conditions. Under climate change scenarios, the drought pattern is projected to shift from fewer but longer and more severe droughts to more frequent, shorter-duration droughts, particularly under the SSP585 scenario. Although average duration and intensity decreased in some scenarios, the drought "magnitude" index—integrating intensity and duration—increased across all future scenarios, indicating an overall intensification of drought content. Furthermore, the frequency of "severe" droughts significantly increased under all scenarios. Trend analysis confirmed a significant and accelerating decline in the JDHMI index in the future. This framework can serve as a scientific basis for early warning systems, and sustainable water resource management in the face of climate change.https://jdcr.birjand.ac.ir/article_3827_b5b8c484824d8a06f4f3d570bc420313.pdfUniversity of Birjand-Research Group of Drought and Climate ChangeJournal of Drought and Climate change Research3092-60764120260522Investigating Appropriate Solutions for Climate Change Adaptation, Case Study of Baft City - KermanInvestigating Appropriate Solutions for Climate Change Adaptation, Case Study of Baft City - Kerman251268370110.22077/jdcr.2025.9734.1156FANasrollahHabibiPhD Student in Agricultural Economics, Department of Agricultural Production and Management, Faculty of Agriculture,Shahid Bahonar University of Kerman, Kerman.Iran.0009-0008-5054-167XElhamKhajpourAssistant Professor, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman,
Kerman, Iran.SedighehNabieianAssistant Professor, Department of Agricultural Economics, Faculty of Agriculture, Shahid Bahonar University of Kerman,
Kerman, Iran.0009-0008-5054-167XJournal Article20250714Climate change is currently a global phenomenon that has affected all aspects of the lives of organisms and their environment. Climate change, especially the recent droughts in the country, has visibly affected production in the agricultural sector. Adaptation to climate change is one of the most basic and important strategies for managing climate change in agriculture. This research was conducted to investigate the use of different plant varieties on the acceptance of adaptation to climate change in the agricultural sector in 2019. The present study is applied in terms of its purpose and descriptive-inferential in terms of its method. Research data were collected through a questionnaire whose validity and reliability have been evaluated (Cronbach's alpha is 9.76), using a random sampling method from 247 people. The method used in this research was the logit model, which was selected as the appropriate model after examination. The results indicate that factors such as variables, extension classes, use of different plant varieties, agricultural input subsidies, modern irrigation methods, and agricultural credits have a significant effect on the acceptance of climate change adaptation in the agricultural sector. Since water scarcity is one of the most important factors affecting the acceptance of climate change adaptation, and according to the results obtained, the use of different plant varieties will create a kind of confidence in farmers and ultimately lead to a reduction in farmers' risk aversion and will lead farmers to use different types of water-poor plants.Climate change is currently a global phenomenon that has affected all aspects of the lives of organisms and their environment. Climate change, especially the recent droughts in the country, has visibly affected production in the agricultural sector. Adaptation to climate change is one of the most basic and important strategies for managing climate change in agriculture. This research was conducted to investigate the use of different plant varieties on the acceptance of adaptation to climate change in the agricultural sector in 2019. The present study is applied in terms of its purpose and descriptive-inferential in terms of its method. Research data were collected through a questionnaire whose validity and reliability have been evaluated (Cronbach's alpha is 9.76), using a random sampling method from 247 people. The method used in this research was the logit model, which was selected as the appropriate model after examination. The results indicate that factors such as variables, extension classes, use of different plant varieties, agricultural input subsidies, modern irrigation methods, and agricultural credits have a significant effect on the acceptance of climate change adaptation in the agricultural sector. Since water scarcity is one of the most important factors affecting the acceptance of climate change adaptation, and according to the results obtained, the use of different plant varieties will create a kind of confidence in farmers and ultimately lead to a reduction in farmers' risk aversion and will lead farmers to use different types of water-poor plants.https://jdcr.birjand.ac.ir/article_3701_b181eaa49f5924e16c772dcb718fcd0f.pdf