Showing 2456 results for Type of Study: Research
Atefeh Raisi Nafchi, Jahangir Abedi Koupai, Mehdi Gheysari, Hamid Reza Eshghiazeh,
Volume 29, Issue 3 (10-2025)
Abstract
Rice is one of the most important crops and the primary food source for more than half of the world's population. The present study was conducted to compare the direct-seeded rice (DSR) of three rice varieties (Jozdan, Firuzan, and Sazandegi) using surface (DI) and subsurface (SDI) drip irrigation systems. The experiment was performed as a split–split plot arranged in a randomized complete block design with three replications in two years (2019 and 2020) in the research farm of Isfahan University of Technology in Najaf-Abad. According to the results of the variance analysis, the most suitable cultivar for DSR in the region (among the tested cultivars) is Sazandegi with a grain yield of 3400 kg/h-1. The results of this experiment showed that the amount of water consumed in DI was 20% less than in SDI. Also, DSR reduced water consumption by 40% compared to transplanted rice (TPR) in the region. However, the grain yield also decreased by about 45%.
Mohiaddin Goosheh, Abolfazl Azadi,
Volume 29, Issue 3 (10-2025)
Abstract
Soil organic carbon provides conditions for better plant growth by increasing soil quality by improving physical, chemical, and biological properties of the soil. Therefore, an experiment was conducted in a randomized complete block design (RCBD) with three replications at the Shavour Agricultural Research Station in Khuzestan Province to investigate the effect of different sources of organic matter on some soil properties and wheat yield. The main plots included cow manure, poultry manure, wheat straw, bagasse, and sugarcane filter cake, and the subplots included three fertilizer levels of 2.5, 5, and 10 tons per hectare. Also, one plot was considered as a control (without organic fertilizer) in each replication. The results showed that the best sources of organic fertilizer available in the province that have had a favorable result in increasing wheat yield and improving soil physical properties are filter cake, cow manure, and sugarcane bagasse fertilizers (with a yield of 4772, 4467, and 4452 kg/ha, respectively). Wheat straw also has the least effect on yield (4019 kg/ha) and plays a major role only in improving soil physical and chemical properties. It is worth noting that since no significant difference was observed between the fertilizer consumption amounts in the overall results, the consumption of 2.5 tons per hectare of each fertilizer source is more economical and is recommended. It also seems that the combined application of filter cake with sugarcane bagasse or cow or chicken manure with wheat straw and stubble, in a total amount of 2.5 tons per hectare, has a more favorable result in increasing wheat yield and improving soil physical properties.
Mehdi Feyzolahpour, Manizheh Ahmadi,
Volume 29, Issue 3 (10-2025)
Abstract
Drought is a hazard that can have widespread impacts on biodiversity, wildlife habitats, and ecosystem stability. The present study investigated the drought situation in the Bonab rural district. To assess the drought situation during the period 2013 to 2024, the Normalized Difference Vegetation Index (NDVI), Water Index (NDWI), Moisture Index (NDMI), Soil Adjusted Vegetation Index (MSAVI), and Land Surface Temperature (LST) were used. The results showed that the maximum value of the NDWI index reached from 0.16 in 2013 to 0.14 in 2024, which indicates an intensification of drought. However, the maximum value of the NDVI increased from 0.53 in 2013 to 0.58 in 2024, and the value for the MSAVI index for the years 2013 and 2024 was 0.69 and 0.73, respectively. All indices except the NDWI index had a negative correlation with the LST index, and the MSAVI index had the highest negative correlation with a Pearson coefficient of -0.39 in 2013. The results are also consistent with the results obtained from the SVM model. It is also observed that the area of barren lands has decreased from 887 square kilometers in 2013 to 851 square kilometers in 2024.
Javad Karami, Majid Habibi Nokhandan, Majid Azadi, Akbar Rashidi Ebrahim Hesari,
Volume 29, Issue 3 (10-2025)
Abstract
The present study investigates shoreline changes along the southern Caspian Sea coast in Mazandaran Province over 24 years (2000-2023) using Landsat 8 and Sentinel-2 satellite imagery. The images were obtained from the USGS and Google Earth Engine platforms, and after geometric and radiometric corrections were processed using near-infrared and shortwave Infrared bands to accurately detect the boundary between land and water. Shorelines were visually extracted from the imagery and digitized for each time interval. Spatial variations in the shoreline were analyzed using the Digital Shoreline Analysis System (DSAS) within the ArcGIS environment, applying statistical methods including Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), End Point Rate (EPR), and Linear Regression Rate (LRR). The results indicate a significant shoreline retreat in many areas of the study region, alongside a continuous decline in the Caspian Sea water level during the last decade. The integration of remote sensing analyses with atmospheric and hydrological data (temperature, precipitation, and river discharge) improved the accuracy of the results and suggests that the southern coastlines—particularly in Mazandaran—may experience more severe retreat by 2050, if current trends continue. These findings underscore the need for intelligent water resource management and the adoption of climate-adaptive policies in the region.
Ali Akbarian Khalilabad, Hojat Karami, Seyed Farhad Mousavi,
Volume 29, Issue 3 (10-2025)
Abstract
The reduction of soil permeability due to the sedimentation of suspended particles is a significant challenge to the efficient operation of artificial recharge systems. In this study, the effects of sediment concentration (0.5, 2, and 4 g/L), soil particle size, and vertical distribution on clogging processes were investigated using laboratory soil column experiments. The results showed a two-phase decrease in permeability: a rapid initial drop caused by the blockage of coarse pores during the first 10 minutes, followed by a second phase where the system reached a relative equilibrium. Higher sediment concentrations led to a faster decline and lower equilibrium values of permeability. Fine-grained soils, despite having lower initial permeability, demonstrated greater resistance to clogging, while coarse-grained soils experienced more severe reductions. Vertical analysis indicated that the most significant permeability loss occurred at a depth of 40-50 cm, while deeper layers showed increased permeability due to the limited penetration of suspended particles. These findings can inform the selection of appropriate materials, the design of subsurface layers in recharge basins, the prediction of system lifespan, and the regulation of sediment load in inflows to enhance the efficiency and sustainability of artificial recharge systems.
Masoumeh Golestani, Sayed Farhad Mousavi, Hojat Karami,
Volume 29, Issue 3 (10-2025)
Abstract
Groundwater is a vital resource for meeting drinking, agricultural, and industrial needs in arid and semi-arid regions of Iran. In this study, quantitative and qualitative changes in groundwater in the Garmsar Plain were modeled using GIS, MODFLOW, and MT3DMS software during the period 2011-2013. Spatial and climatic data were comprehensively processed and prepared in the GIS environment, and groundwater flow was simulated using the MODFLOW model, and water quality changes were analyzed using the MT3DMS model. After validation with field data from 2012 to 2013, the model showed acceptable accuracy with statistical indicators of mean absolute error (MAE) in the range of 0.4 to 0.5 meters and root mean square error (RMSE) between 0.5 and 0.6 meters. The modeling results showed that a 15% increase in water withdrawal led to a decrease in the water table of up to 8 meters, a constant withdrawal led to a decrease of 7 meters, and a 15% decrease in withdrawal led to a decrease of 5 meters in the water table. From a quality perspective, the decrease in withdrawal improved the quality of irrigation water but increased the concentration of some pollutants, which requires the development of effective management strategies to protect groundwater resources. The findings of this study illustrate the importance of sustainable exploitation and smart management of groundwater resources in the Garmsar Plain.
Mohammad Shayannejad, Elham Fazel Najafabadi, Fahimeh Hatamian Jazi,
Volume 29, Issue 3 (10-2025)
Abstract
Regarding the increasing need for water resources and the decline of surface water resources, awareness of these resources is a crucial need in planning, developing, and protecting them. This research was conducted to model the water quality index (the most widely used feature of determining water quality) using machine learning models (Random Forest and Support Vector Machine) in the Zayandehrood River. Regarding the large number of water quality indices, the NSFWQI index was used in this study. First, this index was calculated, and then, input data, including water quality characteristics of 8 stations over 31 years, and the river water quality index were used. In this research, 80% of the data was used in the training stage, and the remaining 20% was used in the evaluation stage. The optimal model was selected based on the evaluation criteria, including R2, CRM, and NRMSE. The results showed that the Support Vector Machine algorithm (0.931 < R² < 0.982, 1.321
Abolghasem Bagheri, Azam Yadegari, Koohsar Khaledi,
Volume 29, Issue 3 (10-2025)
Abstract
Wheat is a strategic crop, and boosting its production is vital. This study identifies key factors affecting wheat yield by estimating and selecting superior production functions. The research used panel data from crop years 1400-1385 in Isfahan province counties over 15 years, analyzed with EViews 10 software. Results showed water use had the greatest positive effect; a one percent water increase raised wheat yield by 0.41 percent on average. Cultivated area, fertilizer, seeds, and labor also had positive, significant effects. In contrast, air temperature had a negative effect, and agricultural machinery had no significant effect. Isfahan's arid climate and water's role in yield underscore the need for modern irrigation methods and better water use efficiency to improve production.
Ali Reza Jafarnejadi, Abdolali Gilani, Fatemeh Meskini-Vishkaee, Maryam Hoseini Chaleshtori,
Volume 29, Issue 3 (10-2025)
Abstract
Rice, as one of the world's most strategic crops, plays a vital role in global food security. This study investigated the effects of different nutrition management approaches on yield and water productivity in dry direct-seeded rice cultivation (local Anbouri Red Dwarf cultivar) at Shavoor Research Station in Khuzestan Province. The experiment was conducted in a randomized complete block design with four treatments, including 1) Farmer's conventional practice, 2) Soil test-based fertilization, 3) Soil test-based fertilization + supplementary nutrition, and 4) 25% reduced chemical fertilizers + biofertilizers, with three replications. Results demonstrated that the supplementary nutrition (4270 kgha-1) and biofertilizer with 25% chemical fertilizer reduction (4356 kgha-1) treatments increased yield by 17% and 19.3 %, respectively, compared to conventional practice (3651 kgha-1). This improvement was primarily attributed to increased panicles per m² (10-14%) and enhanced nutrient uptake efficiency. The biofertilizer treatment also showed the highest water productivity (0.25 kg m-³) and the best benefit-cost ratio (23.25). Economic analysis confirmed that combining biofertilizers with 25% chemical fertilizer reduction significantly reduced costs while maintaining yield. These findings suggest that integrating soil testing with either biofertilizers or stage-specific nutrition represents an effective strategy for enhancing yield, improving water use efficiency, and reducing dependence on chemical inputs in dry-seeded rice cultivation. These methods can be recommended as sustainable models for farmers in arid regions like Khuzestan, which face salinity challenges and water resource limitations.
Mahin Tahvilian, Saeed Eslamian, Ali Reza Gohari, Mohammad Jamali,
Volume 29, Issue 3 (10-2025)
Abstract
Time of concentration (Tc) is one of the key parameters in hydrological studies, playing a critical role in flood control structure design, runoff simulation, and water resource management. This study evaluates the performance of seven empirical equations—Bransby-Williams, California, Giandotti, Kirpich, Pilgrim, Rational Hydrograph (SCS), and Carter—in estimating Tc across 35 sub-watersheds in Khuzestan Province, Iran. To assess the accuracy, six sub-watersheds with reliable rainfall-runoff data were selected, and observational Tc values were calculated. The estimated results from the empirical formulas were then compared with observed data using statistical indices such as RMSE, ME, and the Nash–Sutcliffe Efficiency (NSE). The findings revealed that the Kirpich equation provided the most accurate and reliable estimates, with RMSE = 2 hours, ME = 0.44 hours, and NSE = 0.91. Subsequently, all seven models were applied to estimate Tc for the remaining sub-watersheds. Finally, a concentration time zoning map was generated, which can serve as a practical tool for hydraulic design, flood risk analysis, and optimal water resource planning in Khuzestan Province.
Hossein Rezazadeh, Parisa Alamdari, Salar Rezapour, Mohammad Sadegh Askari,
Volume 29, Issue 3 (10-2025)
Abstract
Soil quality assessment plays a crucial role in sustainable land management, particularly in degraded areas such as saline and sodic soils. This study aimed to determine the spatial distribution of the Soil Quality Index (SQI) in saline and sodic soils around Lake Urmia using two geostatistical interpolation methods: Kriging and Inverse Distance Weighting (IDW). A total of 82 soil samples were collected from a depth of 0–30 cm, and 24 physical, chemical, and heavy metal properties were analyzed. The Soil Quality Index was calculated based on both linear and non-linear approaches. Principal Component Analysis (PCA) was used to identify a Minimum Data Set (MDS), including: calcium carbonate equivalent, EC, clay percentage, BD, silt percentage, organic carbon, Pb, and cadmium, which explained more than 78% of the total variance. The results indicated that the SQI showed moderate spatial variability across the study area, with a decreasing trend from west to east. Comparison of the interpolation methods revealed that Kriging performed better in the linear model, while IDW showed higher accuracy in the non-linear approach. The best-fitted theoretical model was spherical, with a range of influence varying between 6,130 and 20,610 meters. Overall, integrating the Soil Quality Index with geostatistical methods provides a powerful tool for understanding spatial variability and supporting effective planning in saline and sodic soils.
Neda Haseli Nasrabadi, Reza Modarres, Saeed Soltani,
Volume 29, Issue 3 (10-2025)
Abstract
Floods are among the most frequent and destructive natural disasters worldwide, causing significant damage to human infrastructure and the environment each year. This study aims to assess the direct damages caused by flooding using the HEC-FIA model in the Semirom watershed. In the first step, flood inundation maps were generated using the HEC-RAS model based on digital elevation model (DEM) data, hydrological inputs, and Manning’s roughness coefficients under both steady and unsteady flow conditions. These maps were then converted into a format compatible with the HEC-FIA software and integrated with economic, land use, and population data to estimate flood damages. The economic database included updated information on agricultural, horticultural, residential, and industrial land uses, partly obtained through field surveys. The flood event of March 11, 2006, was selected as the base flood, and damage analyses were performed for various return periods. The results indicated that the agricultural sector suffered the most damage. In the base year flood, agricultural damages exceeded 821 billion IRR, while structural damages were estimated at approximately 3 billion IRR. In the 1000-year return period, agricultural damages rose to 1,427 billion IRR, and structural damages increased to 44 billion IRR. Analysis of shorter return periods showed a significant decrease in damages, with no structural damage observed in the 10-year return period or less, although agricultural areas remained vulnerable. The findings suggest that the HEC-FIA model has a high capability in estimating direct flood damages across spatial and temporal scales and can serve as an effective tool for flood risk management and planning.
Iman Saleh, Seyed Masoud Soleimanpour, Majid Khazaei, Omid Rahmati, Samad Shadfar,
Volume 29, Issue 4 (12-2025)
Abstract
Soil loss and extensive degradation caused by gully erosion have always caused serious damage. Because direct field measurement and monitoring of gully erosion are costly and time-consuming, it is very difficult to determine the amount of soil loss caused by gully erosion. The present research was conducted to calculate the volume of soil loss due to gully erosion using machine learning models in the Abgendi watershed of Kohgiluyeh and Boyar Ahmad province based on field studies. Machine learning models include random forest, support vector machine, artificial neural network, and adaptive neural fuzzy inference system. The location of 68 gullies in the area was recorded. Hence, initially, digital layers of factors affecting the expansion of gullies, including topography, pedology, lithology, and hydrology, were prepared as independent variables to model soil loss caused by gullies. Then, representative gullies were selected in the studied watershed, and the volume of soil loss due to gully erosion was directly measured in the field as a dependent variable. The measured gullies were randomly divided into two training and validation groups. The results of the models were evaluated using root mean square error (RMSE) and R2, and the models were compared. According to the results, gully erosion in the Abgendi watershed of Kohgiluyeh and Boyar Ahmad province is increasing every year. Also, the amount of erosion and soil loss will increase when the amount of rainfall and the frequency of intense rainfall (≥5mm) are high. Among the machine learning models used in the present research, the random forest (RF) model was selected as the best model to predict soil loss generated by gully erosion.
Mohammad Amin Abdollahi, Jahangir Abedi Koupai, Mohammad Mehdi Matinzadeh,
Volume 29, Issue 4 (12-2025)
Abstract
Urban floods and stormwater runoff are among the most significant environmental and social challenges in urban areas, caused by the accumulation of rainwater and the inadequacy of stormwater collection networks. The performance of the SewerGEMS software in analyzing rainfall events and evaluating the adequacy of the stormwater collection network in Shahrekord City under various conditions has been examined. Only two of the six observed rainfall events could be simulated. In the event of 06/11/1403 (Persian calendar), the observed peak discharge was approximately 1850 liters per second. In contrast, the simulated discharge for the two-sub-basin scenario was around 1750 liters per second, and for the eight-sub-basin scenario, about 1350 liters per second. The results of the two-sub-basin scenario are more reliable. In the event of 27/11/1403, the observed peak discharge was approximately 2000 liters per second, while the simulated discharge for the two-sub-basin scenario was around 1850 liters per second, and for the eight-sub-basin scenario, about 1400 liters per second. This demonstrates that the results for the two-sub-basin scenario are more accurate. The adequacy of the network was then evaluated for return periods of 2 years and 5 years. The results indicated that the stormwater collection network of Shahrekord is generally adequate; however, some areas, such as sections of the Bouali and 13 Aban canals, have deficiencies that lead to local flooding. Finally, recommendations such as identifying locations for artificial recharge basins and continuously monitoring and inspecting the canals, particularly before the rainy season, are proposed to improve the performance of the Shahrekord stormwater collection network and reduce flood-related risks.
Meysam Bagherifar, Maryam Hafezparast,
Volume 29, Issue 4 (12-2025)
Abstract
The river flow prediction is a key aspect of hydrology that plays a significant role in water resources management, flood risk reduction, and agricultural planning. This study simulates the monthly flow of the Razavar River, located in western Iran, using an extreme learning machine (ELM) model enhanced by the Whale (WOA) Optimization Algorithm and Grasshopper Optimization Algorithm (GOA) metaheuristic optimization algorithms. The data used include river flow, precipitation, evaporation, and temperature, which were collected for 10 years with a monthly time step and normalized in the numerical range of zero to one. 80% of the data is used for training, and the remaining 20% for model evaluation. The performance of the models is measured with the statistical indices RMSE, NSE, and R². First, the basic ELM model is developed using the trial-and-error method to adjust the weights between the hidden and output layers. Then, the WOA and GOA algorithms are used to optimize the weights. The results show that the basic ELM model performs worse than the optimized models (Train: RMSE=0.1427, NSE=0.7795, R²=0.7911, Test: RMSE=0.1406, NSE=0.7811, R2=0.7916). While the WOA-ELM and GOA-ELM models provide similar results, the WOA-ELM model shows better performance in complex conditions (Train: RMSE=0.1215, NSE=0.7869, R2=0.7932, Test: RMSE=0.1165, NSE=0.7872, R2=0.7933). The results of this research show that meta-heuristic optimization algorithms play an important role in improving the performance of river flow prediction models due to their ability to search comprehensively and avoid getting stuck in local optima. The findings of this study emphasize the importance of applying these techniques in water resources management and sustainable planning and will pave the way for future research in this area.
Narjes Sanchooli, Hashem Khandan Barani,
Volume 29, Issue 4 (12-2025)
Abstract
The biological desalination system has lower energy consumption and environmental impacts, as well as simpler engineering technology and complexity compared to conventional desalination methods. This study aimed to investigate the effect of nutrients in the Chlorella vulgaris algae culture medium on the rate of algae growth, salinity reduction, TDS, and EC. For this purpose, an amount of algae was inoculated into culture media-containing treatments to achieve a density of 5 × 106 cells/ml. The results showed that the highest amount of dry biomass of algae was in the deep aquifer well water + BG-11 culture medium treatment, with a value of 0.76 ± 0.02 g. The highest amount of chlorophyll a and b was observed on days 4, 17, and 30 in the control treatment, which was significantly different from the other treatments (p < 0.05). The lowest value of light absorption of algae was observed in the control treatment on all days. At the end of the 30-day experimental period, the highest reduction in salinity, TDS, and EC was observed with 27.60, 26.83, and 41.60 percent reduction in the deep aquifer well water + culture medium treatment, respectively, which showed a significant difference (p < 0.05) with the deep aquifer well water treatment. The results showed that deep aquifer well water, due to its nutrient content, has a high potential for algae growth and, as a result, biological desalination and the absence of the use of commercial culture medium, which can reduce desalination costs.
Elaheh Ebrahimi, Mehdi Gheysari, Alireza Gohari,
Volume 29, Issue 4 (12-2025)
Abstract
Given the rising need for water consumption and the decrease in available water resources, improving water use efficiency appears essential. Using modern irrigation techniques and applying irrigation management based on current, accurate scientific principles will enhance irrigation efficiency. This study aimed to estimate evaporation and windfall losses using meteorological variables and measure these losses in the cities of Isfahan, Golpayegan, and Fereydounshahr under different weather conditions. Evaporation and windfall losses were examined at 3, 6, 9, 12, and 15 hours using two selected equations across three meteorological stations with seven years of weather data. Then, evaporation and windfall losses were estimated using two experimental methods (abbreviated as WD1 and WD2), a science-based method (named droplet size), and field measurements. Results showed that evaporation and windage losses calculated with the empirical equation WD1 were about 2% higher than the field measurement value, while WD2 was about 1.5% lower. The correction factors for WD1 were 0.54, 0.44, and 0.51 for Isfahan, Fereydounshahr, and Golpayegan, respectively, and for WD2, it was 1.62, 1.17, and 1.56, respectively. The differences in evaporation and windage losses at various times of day and months of the year were statistically significant at the 5% level.
Sanaz Moghim, Amirabbas Samavaki,
Volume 29, Issue 4 (12-2025)
Abstract
The effect of climate change on agricultural productivity and efficiency is a major concern and challenge for the agricultural industry. Different hydrometeorological variables, such as extreme temperature, precipitation, and their variations, affect the growth and yield of agricultural products. Saffron is one of the most important agricultural products in Iran. Iran produces the largest amount of Saffron globally, and Hamadan Province is one of the major saffron-producing regions in Iran. This study uses different Artificial Intelligence methods not only for clustering and sensitivity analysis of the hydroclimatological variables but also for evaluating the impacts of climate change on Saffron yield in Hamadan Province. Results indicated that the Random Forest algorithm performs the best for sensitivity analysis among all algorithms. Extreme climate change indices, particularly those related to the monthly maximum and minimum temperatures, have the highest negative impact on saffron yield compared to other hydroclimatological indices. Furthermore, the minimum temperature has a more significant negative impact on saffron yield compared to the maximum temperature. Additionally, the counties of Malayer, Nahavand, and Asadabad, located in the south and west of Hamadan Province, exhibited the highest accuracy in sensitivity analysis. The findings suggest that monthly extreme temperatures can be used to assess the risk of saffron production, increase agricultural productivity, and improve decision-making for the cultivation of this product.
Mehdi Feyzolahpour, Behrouz Mohamady Yeganeh, Maryam Amri,
Volume 29, Issue 4 (12-2025)
Abstract
By utilizing land surface temperature (LST), valuable insights can be gained regarding the impact of land use on energy balance processes. Therefore, this study aimed to investigate the trend of LST changes due to land use changes in the Gorab rural district. Four land use types, including water bodies, bare land, Agricultural area, and forest, were determined from 2013 to 2024 for the maximum likelihood classification (MLC) and support vector machine (SVM) models. The surveys showed that the area of water in the dry period decreased from 0.9 km2 in 2013 to 0.4 km2 in 2024, a decrease of 0.5 km2. In contrast, the area of forest areas increased from 136.1 km2 in the dry period of 2013 to 147.2 km2 in 2024. The Kappa coefficient values for the SVM and MLC models during the wet season of 2021 were 53.94 and 68.7, respectively. Based on this, it was found that the MLC model has higher accuracy. To match spectral indices with LST values, NDVI, NDSI, and NDWI were calculated. Land use changes during the 2013-2024 period affected land surface temperatures, causing fluctuations from 11.5°C to 21.18°C in the wet season and from 13.81°C to 31.45°C in the dry season. The highest LST values were associated with barren land, while water bodies and vegetation cover had the lowest LST values. Among the spectral indices, the highest positive correlation was observed with NDWI, with a value of 0.64 in 2024. The highest negative correlation, -0.66, was observed with NDVI in the same year. Over the 11 years, the area of forest cover increased by 8.15%, while agricultural land decreased by 33.5%. The most significant change occurred in agricultural lands, which declined in area from 35.5 km² to 23.6 km².
Hamid Hosseinkhani, Elham Ghanbari Adivi, Rouhollah Fatahi Nafchi, Ali Raeisi,
Volume 29, Issue 4 (12-2025)
Abstract
Soil erosion and sediment transport are among the key challenges in the management of water and soil resources in Iran. In this study, the Modified PSIAC (MPSIAC) empirical model was applied to estimate sediment yield and evaluate the erosion status in the Plasjan watershed. The model is based on the assessment of nine influencing factors, including geological characteristics, soil properties, climatic conditions, runoff, land slope, vegetation cover, land use, surface erosion, and channel erosion. By assigning scores to each factor and integrating the spatial layers, the sediment yield intensity of each sub-watershed was quantified both qualitatively and quantitatively. The required base data were prepared and analyzed using the Geographic Information System (GIS). Subsequently, the final erosion index for each sub-watershed was calculated, and erosion hazard classes were determined according to the model’s standard tables. The total annual sediment production in the watershed was estimated at 803,301 tons, and the Sediment Delivery Ratio (SDR) was calculated as 14.48%, indicating considerable sediment deposition along the transport paths. The results showed that most sub-watersheds fall within the “moderate” erosion class, while insufficient vegetation cover, steep slopes, and land-use changes were identified as the main contributing factors to increased sediment yield. Based on these findings, identifying critical areas, implementing erosion control measures, and utilizing remote sensing and sediment monitoring technologies are strongly recommended. This study provides a scientific basis for improving watershed management and mitigating erosion-related risks in similar basins.
