raoof mostafazadeh

Water security is strongly influenced by many factors including increasing urban population, economic development, changes in living standards, increasing water pollution, over-exploitation of groundwater resources, and climate change. The aim of the study is to evaluate the impact of hydrological index on water security index (WSI) in Qarasu sub-basins.

In this study, hydrological index (H), per capita water, and water discharge were used to estimate the water security index. In other words, the water security index uses normalization to assess the sustainability of the watershed.

The results of the water discharge index assessment in the Qarasu watershed showed that the highest water discharge among the 27 sub-basins studied was related to sub-basin 1 at the Namin hydrometric station with a value of 560,196,073 cubic meters and sub-basin 23 at the Nanekaran hydrometric station with a value of 305,170,988 cubic meters. The results of the per capita water assessment in the Qarasu sub-basins showed that the highest per capita water for each person was allocated to sub-basin 20 at the Nooran station with a value of 957.9733,133 liters and in the next rank, sub-basin 18 at the Baroq station with a per capita water value of 914.9249,868 liters among the sub-basins studied. Therefore, it is concluded that the higher the hydrological index in the sub-basins studied, the more suitable the basin sustainability index will be. Finally, it is suggested that executive and management measures be implemented in some sub-basins that do not have a suitable hydrological index, as the Water Security Index (WSI) is very low in them, in order to witness the development of sub-indices in all the studied basins so that the Water Security Index takes an upward trend.

As the population continues to grow, the significance of boosting food production becomes increasingly evident. Consequently, it is imperative to find solutions to address water limitations and enhance food production in regions facing water scarcity. In this context, it is proposed to implement strategies that involve expanding cultivated areas and optimizing the utilization of available water resources, particularly in scenarios where irrigation is restricted. Successful water engineering projects necessitate precise estimation of plants' water requirements across various regions. The goal is to maximize the efficiency of water usage per unit volume to ensure optimal agricultural output. This study aims to explore fluctuations in the water requirements and hydromodule of crops within different cultivation patterns in selected regions of northwest Iran, in response to climatic variables.

The objective of this study is to evaluate the variations in plant water needs in cultivation patterns across different regions in northwest Iran, taking into account climatic parameters. Initially, meteorological data from stations in Tabriz, Kalibar, Parsabad, Germi, and Bukan were collected from the national meteorological organization.Cultivation pattern of agricultural plants in the investigated stations was extracted from the Jihad Agricultural Organization of the respective province. Considering the vastness of the studied areas and the impossibility of detailed soil investigation, the soil of the areas was considered medium. According to Ministry of Energy researches, the irrigation efficiency for all the studied areas averagely was considered to 60%.Subsequently, utilizing CROPWAT 8.0 software based on the FAO56 equation, factors such as evapotranspiration of grass (used as a reference plant), solar radiation, and effective rainfall were determined for the selected stations. The hydromodule, representing water requirements, was then calculated monthly for the desired cultivation patterns in the respective areas. Finally, employing the Weibull transformation coefficient, the irrigation hydromodule with various return periods was derived for the study region.

The results indicated that the average potential evapotranspiration of grass, serving as the reference plant, was calculated as 4.12, 3.03, 2.86, 3.32, and 3.86 mm per day for the Tabriz, Kalibar, Parsabad, Germi, and Bukan stations, respectively. Furthermore, the average irrigation hydromodule for these stations was determined as 0.73, 0.35, 0.6, 0.7, and 0.62 liters per second per hectare, respectively. Utilizing the linear variation function, the average irrigation hydromodule for return periods of 2, 5, 10, 25, 50, 100, and 200 years for the aforementioned stations were obtained as 0.813, 0.552, 0.707, and 0.721 liters per second per hectare, respectively. Similarly, using the exponential function, the corresponding values were extracted as 0.818, 0.632, 0.719, 1, and 0.73 liters per second per hectare, respectively. Specifically, for the Tabriz, Kalibar, Parsabad, Germi, and Bukan stations, the irrigation hydromodule values with a return period of 2 years, employing the linear function, were calculated as 0.742, 0.439, 0.622, 0.821, and 0.67 liters per second per hectare, and with the exponential function, they were determined as 0.74, 0.444, 0.618, 0.829, and 0.672 liters per second per hectare, respectively. Additionally, for these stations, with a return period of 200 years, using the linear function, the calculated irrigation hydromodule values were 0.851, 0.613, 0.754, 1.015, and 0.748 liters per second per hectare, while employing the exponential function, they were determined as 0.862, 0.749, 0.777, 1.1, and 0.762 liters per second per hectare, respectively.

The irrigation hydromodule values in the Tabriz station increased by 0.851 liters per second per hectare, which is equivalent to a 10.88 percent increase compared to the average. Similarly, in the Kalibar, Parsabad, Germi, and Bukan stations, the increases were 0.613, 0.754, 1.01, and 0.748 liters per second per hectare, respectively, representing increments of 8.44, 13.17, 38, 19.7, and 7.78 percent compared to the average. Utilizing the exponential changes function, when the return period was adjusted from 2 years to 200 years and the probability of occurrence was reduced, the irrigation hydromodule increased by 0.862 liters per second per hectare in the Tabriz station, which corresponds to a 12.23 percent increase relative to the average. Similarly, in the Kalibar, Parsabad, Germi, and Bukan stations, the increases were 0.749, 0.777, 1.1, and 0.762 liters per second per hectare, respectively, representing rises of 30.5, 15.82, 09, 27.04, and 9.04 percent compared to the average. Given the water scarcity in various regions of the country, it is recommended to use the minimum values of functions (linear or exponential) to estimate the irrigation hydromodule for different return periods. With respect to linear function changes, and considering that the irrigation hydromodule does not decrease significantly (around 20% on average) with an increase in the return period (up to 200 years), it is advisable to design and implement storage facilities, transfer systems, and water distribution networks in the studied plains with a low probability of occurrence (high return period). This approach minimizes the increase in costs and reduces risks during water transfer and distribution operations.

Flood events are the most complex natural hazards that endanger human and animal lives, social and economic settings, and environmental resources more than any other natural disaster. This phenomenon is caused by the water flow exceeding the river's channel capacity. The expansion of flood zone along river banks in recent years due to climate change and inappropriate use of natural resources is associated with irreparable socio-economic and environmental damages. Simulation of potential flood zones is crucial for management purposes of flood prone areas. Hydraulic models are proved to be useful in simulating flood zones, identifying hotspot areas, and thus, estimating potential damages. The Arazkuseh River is situated downstream of three watersheds, namely Minodasht, Narmab and Nodeh Khandooz. It is prone to flooding during periods of heavy rainfall in the watersheds. The aims of this research are to assess the performance of the HEC-RAS 2-D hydraulic model in simulating the flood zone for the event of March 17, 2019, and to estimate the direct-tangible damages incurred in a 9-km river reach from the Arazkuseh River due to floods in different return periods.

The HEC-RAS software has the ability to calculate water level in rivers while considering hydraulic structures. To estimate the velocity vectors, the two-dimensional diffusion wave was used, which takes into account more stable numerical solutions and reduces the calculation time. A Digital Elevation Model (DEM) map with a resolution of one-meter was used to create input terrain data for this model. The flood event hydrograph on March 17, 2019 with a peak discharge of 355 cubic meters was recorded at the Arazkuseh hydrometric station located at the joint outlet of the upstream watersheds. Manning's roughness coefficient values estimated based on field observations in the channel and flood plain were also calibrated with the index F during the evaluation of the model's performance. In order to evaluate the performance of the HEC-RAS 2-D model, the outputs of the model for the flood event on March 17, 2019 were compared with the flood zones identified by the Sentinel-2 satellite images at two different days (23 March and 2 April, 2019). The Pilgrim's computational method was used to identify temporal distribution model of the design rainfalls for the Arazkuseh watershed in different return periods. Additionally, the CoKriging geostatistical method was used to estimate the spatial pattern of the design rainfalls. Thus, the hydrographs simulated by the HEC-HMS hydrological model for the design rainfalls were considered as inputs to the HEC-RAS software. Following identifying the elements exposed to flooding, direct and tangible damages caused by the simulated floods to different land uses were estimated through collecting information from different sources accompanied by field observations.

The F index values (79% and 71% for 23 March, 2019, and 2 April, 2019, respectively) indicate that the HEC-RAS 2-D model has an acceptable performance in simulating the flood zone areas in the Arazkuseh River. However, the area of the simulated flood zone shows an overestimation compared to the flood zone observed by the Sentinel-2 images. The overestimation of the flood zone areas by the HEC-RAS 2-D model can be related to the accuracy of the DEM map and the Manning's roughness coefficient estimation. Analysis of the flood zone for the 100-year return period, as a base flood, reveals that crops, trees, dirt roads, residential areas, and asphalt roads are most likely to experience inundation, respectively. Even in 10-year return period, crop lands are likely to place in the flood zone due to gentle slope and the proximity to the river bank. The highest amount of direct-tangible costs for the 100-year flood, is associated to crop lands, residential areas, trees, dirt road, and asphalt road with values of 20889, 8650, 7503, 2250, and 1750 million Iranian Rial, respectively.

The use of DEM data with appropriate spatial resolution is very important in creating terrain data and simulating flood zones in two-dimensional models. Damages to agricultural products and costs attributed to the removal of sediments and cleaning up in crop lands will be significant due to the spreading out of the flood water in this land use. The high damage incurred to the residential areas is because of costly repairs required after flooding and also the price of houses' contents. The total area of land uses which are exposed to 100-year flooding is about 23 hectares and the total damage imposed is approximately, 41042 million Iranian Rial. Therefore, due to the expansion of the residential areas along the river, it is necessary to reduce the hazard of flooding, to enhance adaptive capacity and coping capacity, and to decrease the level of exposure. In crop lands, managers and practitioners should reduce the amount of damages to this land-use by appropriate actions such as flood insurance promotion and introducing resistant varieties to inundation in the study area.

Population growth and climate change are worsening pressure on water supplies, altering rainfall-runoff patterns, and posing significant challenges for water management. Climate change profoundly affects society, particularly water reserves, through temperature shifts, precipitation changes, and disruptions of river flows, ultimately impacting water scarcity and ecosystems. The objective of this study is to project the possible effects of climate change on water yield in a cold-climate watershed located in Ardabil province. The GR4J conceptual model is used to simulate the hydrologic watershed response to changes in climatic factors. The HadCM3 model was used to examine meteorological parameters under the A1B climate scenario through implementing LARS-WG. The GR4J has been calibrated using a trial-and-error method to maximize the NS coefficient. The results were evaluated using NS and RE. The results showed a significant variation in water yield values across different periods. The biggest yearly water yield is in 2030, dropping to 49.79 million cubic meters in 2050, representing a 13.6 million cubic meters decrease. Based on the results, the highest positive change occurred in February, where the percentage increased from 93% in 2030 to 138% in 2060, representing a 45% increase. Additionally, the biggest negative change is projected in October, when the percentage decreased from 27% in 2030 to -11% in 2060, representing a decrease of -38%. The results suggest that flooding and extreme flow events will increase, while low flow events will decrease significantly under climate change conditions, and the simulated flow values also show more fluctuations in the projected periods.

Therefore, the purpose of the current research was to investigate the health of Koozeh Topraghi watershed using the Vigor, Organization and Resilience (VOR) model during the years 2000, 2010 and 2021. Ecosystem resilience is considered as the potential of an ecosystem to respond to external disturbances by restoring its original structure and function. Each type of land has a different ability to recover, depending on its nature.To calculate resilience, a coefficient was determined for all types of land uses according to the type of service for each user. The results showed that in Koozeh Topraghi watershed, the Vigor index has the mean and standard deviation of 0.88±0.05 in the first year, 0.81±0.08 in the second year, and 0.17±0 in the third year. Were 0.68. The Organization index had the mean and standard deviation of 0.57±0.08 in the first year, 0.70±0.08 in the second year, and 0.68±0.07 in the third year. Also, the resilience index had the mean and standard deviation of 0.28±0.22 in the first year, 0.30±0.25 in the second year, and 0.29±0.25 in the third year. Also, the watershed health index (WHI) in 2000 was equal to the numerical value of 0.49 and in 2010 it had an increasing trend and reached 0.85, but in 2021 it decreased to 0.47. It can be concluded that the health of the watershed has decreased slightly in the studied period. Various reasons, inappropriate land use especially pasture production for agriculture, and changes in climatic and hydrological components, have caused inappropriate health conditions in the Koozeh Topraghi watershed.

In the current study, the risk of landslides in the Zamkan Watershed, located in Kermanshah Province, was evaluated. Two machine learning models, Support Vector Machine (SVM), and Logistic Regression, were used to prepare a landslide susceptibility map. Toward this, 13 informational layers including elevation, slope, aspect, Melton ruggedness number, terrain convexity, stream length, valley depth, topographic wetness index, precipitation, geological formations, distance from rivers, distance from roads, and vegetation cover were utilized as independent variables. Approximately 70% of the watershed's landslide pixels were used for model training, and 30% for model validation. Model validation was performed using ROC curves. The results indicated the higher performance and accuracy of the radial basis function (RBF) kernel of the SVM model for generating landslide hazard maps in the study area. The area under the curve (AUC) for the RBF kernel was approximately 0.951 for model training and 0.944 for model testing. The results suggest that slope with a coefficient of 0.28, precipitation with a coefficient of 0.27, lithology with a coefficient of 0.26, and elevation with a coefficient of 0.22 are the main controlling factors for landslides occurrence in the Zamkan Watershed. Both the SVM model and logistic regression confirmed the deterministic effects of selected factors on landslides. About 35% of the study area as classified as highly susceptible to landslides, primarily in the eastern half of the watershed. Factors such as high elevation, steep slopes, heavy precipitation, and the Kazhdomi Formation's composition were identified as key contributors to this susceptibility.

Determining the extent of riverbank erosion and displaying it as a map in a GIS environment is effective in the optimal management of water and soil resources. The aim of the current research is to delineate the riverbank erosion zone from aerial photographs, perform regression modeling, and identify factors influencing the development of riverbank erosion using various spatial data including physiographic, hydrological, geological, and environmental data in different sections of the Balikhlouchai River in Ardabil Province. Initially, influential parameters in riverbank erosion in the region, including topographic, soil and land factors, hydrology, and land use changes, were calculated. Accordingly, the variables under study were obtained for four time periods: 1955 using aerial photographs, 1980 using TM satellite images, and years 2010 and 2013 using Google Earth images, and the effective extent of riverbank erosion was compared. Subsequently, multivariate regression analysis was performed using independent variables (including topographic, hydrological, soil erodibility, and land factors) and the effective extent of riverbank erosion as the dependent variable, using SPSS software, and suitable models were developed to estimate the amount of different riverbank erosion. Based on the results of regression analysis, environmental parameters such as slope of the river reaches, peak discharge, area under irrigated agriculture, concentration time, pasture coverage, and residential areas played a more significant role in exacerbating riverbank erosion.

Rainfall and discharge components are important parameters among climatic and hydrological parameters that identifying their behavior for water resources management is of particular importance. The aim of this study was to analyze the changes in river flow indicators in quantifying Basal Flow Index (BFI) and Flow Duration Curve (FDC) in the Sabalan mountain rivers. Therefore, first, the daily flow discharge in river gauge stations were divided into two periods pre and post the change based on changes in flow indicators or climatic components. Then, general statistics, BFI and FDC were calculated using River Analysis Package (RAP) software. The results showed that the maximum statistical values of river flow in Lay, Nir and Pol-e-Soltani stations have significantly decreased. BFI in most stations had an increasing trend, which can be related to the possible continuation of snowmelt in the foothills of Sabalan. In Ahl-e-Iman, Lay, Nir, Pol-e-Soltani and Viladaraq stations in the periods pre- and post-change, flow discharge in 50% of the days of the year was equal to or more than 0.081 and 0.108, 0.1 and 0.125, 1.3 and 0.884, 0.71 and 0.372, 0.07 and 0.055 cms were estimated. In general, the change in river flow indicators has been affected by the occurrence of significant changes in rainfall and temperature components

 Statement of the Problem: 

Landslides are among the most important geomorphological hazards in mountainous areas. Large-scale landslides often have significant social and economic impacts, making them one of the costliest natural disasters worldwide, causing considerable damage to individuals and infrastructure each year. Nowadays, due to climate change and human activities, the frequency, intensity, and impact of landslides have increased, posing significant threats to life and property. In recent years, with rapid socio-economic development, the spatial extent of human activities has also gradually expanded. The occurrence of heavy rainfall has increased the frequency of landslides in mountainous areas and the resulting economic losses have gradually increased, turning landslides into barriers to human environment development. Given the complex physics and diverse nature of triggering mechanisms (such as rainfall and earthquakes), dynamic landslide monitoring is vital for risk assessment and management. While small landslides constitute the majority of landslide events annually, large landslides are usually responsible for a significant portion of casualties and damages. In most parts of the world, identifying their locations and effects still faces many challenges due to the diversity of landslide types and morphologies, as well as the difficulty in collecting and updating survey forms. Therefore, the development of tools and techniques for identifying and monitoring these widespread gravitational processes is of great importance. Spatial assessment and preparation of hazard maps are fundamental strategies in landslide risk management. In the present study, spatial assessment and zoning of landslide risk in the Zemkan watershed in Kermanshah have been addressed. This watershed drains parts of the western slopes of the Zagros Mountainous area and has a high potential for landslides.

In order to assess the spatial risk of landslides in the watershed, studies of 13 factors affecting landslide occurrence were conducted, including elevation, slope, aspect, the Melton ruggedness number, surface convexity, length of slope, valley depth, TWI, precipitation, geological formations, distance from streams, distance from roads, and vegetation cover. In line with the research objectives, the necessary data were obtained from 1:25,000 and 1:50,000 topographic maps; 1:100,000 and 1:250,000 geological maps; Aster satellite images with a resolution of 27 meters; Sentinel satellite images (with a resolution of 10 meters) and Google Earth (GeoEye with an approximate resolution of 1 meter); climate data; field studies; and library resources. ArcGIS, ENVI, and SAGA GIS software were used for the preparation and preparation of thematic layers and the execution of research models. A catastrophe theory-based approach was employed for zoning and spatial prediction of landslide occurrence risk in the Zemkan watershed area. Functions of catastrophe theory were used in GIS environment to combine and overlay these factors. The model employed was used to address uncertainties associated with decision-making and data classification. In this model, the weight of criteria is determined by the internal mechanism of the system, which has a mathematical nature.

The results of the research demonstrate the satisfactory performance of catastrophe theory functions in zoning the risk of landslides. The model accuracy, calculated using field mapping of landslide zones and receiver operating characteristic (ROC) curves, was approximately 90%. Catastrophe theory-based modeling showed that slope factors with a coefficient of 1.3, precipitation with a coefficient of 1.2, elevation with a coefficient of 1.1, and geological formations with a coefficient of 1 are the most important variables affecting landslide occurrence in the Zemkan watershed. Over 32.4% of the study area fell into high and very high susceptibility classes. Several conditions have led to significant portions of the central and southern parts of the Zemkan watershed having a high landslide potential. In this regard, factors such as high elevation and slope, significant precipitation, the presence of landslide-sensitive geological formations such as marl, clayey limestone, and shale (Kazhomi formation), westward orientation perpendicular to westward winds, long slopes, high drainage density, and human interventions are noteworthy.

In the present study, a model based on catastrophe theory was utilized to mitigate uncertainties associated with decision-making and data classification. In this model, the weights of criteria are determined by the internal mechanism of the system, which has a mathematical nature. The results of the model are repeatable and generalizable, thereby reducing decision-making uncertainties and enabling the integration of multiple quantitative and qualitative data. The research findings indicate the effectiveness of catastrophe theory functions based on GIS in spatial assessment and zoning of landslide risk in the study area. The alignment of landslide field mapping with landslide risk zoning maps and receiver operating characteristic (ROC) curves indicates a model accuracy of approximately 90%. The model results show that slope, precipitation, elevation, and geology are the most important factors influencing landslide occurrence in the Zemkan watershed. A significant portion of the study area falls into high and very high susceptibility classes of landslides, indicating a considerable potential for landslides in the Zemkan watershed and the need for planning to mitigate the risks associated with landslide occurrence.

With the outbreak of the coronavirus and the disruption of the normal state of human life and death, the most social, economic, political, and especially educational activities changed to virtual communications.

The present study was planned with the aim of assessing the effectiveness rate of adopting Learning Management System (LMS) among students. A questionnaire method was used to obtain the perception and opinion of students of different courses and levels. The efficiency of LMS in seven different components was evaluated. The t-student test was employed to evaluate statistical results.

The results of statistical analysis has been interpretated based on the mean and standard deviation of each studied components. Except for exercises and assignments, other components were less than the average limit. The value of the univariate t-statistic was determined to be less than 1.65 (standard t-value) for all components except exercises and homework. Also, considering that the p-value level for all components (< 0.001), it is concluded that there was a significant difference in the answers of all research questions.

The results can be used to resolve the challenges of E-learning. Due to the prolongation of the outbreak of Covid-19 and the intensification of its consequences such as increasing demand for E-learning, the need for continued economic activities, and employing new tools and more effective use of IT will be necessary.

 Erosion is a critical geomorphological process with significant environmental implications, including land degradation, fertility loss, and negative effects on aquatic ecosystems. It is recognized as an environmental hazard due to the substantial damages it can cause.

 This research uses geomorphometric indicators and a fuzzy approach to zoning the soil erosion potential in the Khiavchai area of Meshginshahr. Various variables were used, including slope, aspect, surface curvature, range length, Melton's roughness coefficient, stream power index, drainage density, topographic wetness index, distance from the river, vegetation, precipitation, and geological formations. The information layers were combined based on their impact on erosion using different fuzzifier functions. The fuzzy gamma operator in a GIS platform was utilized to combine and overlay the indicators. 

 The results revealed that approximately 8.4% of the study area exhibited high erosion potential. In comparison, around 18.7% had a high erosion potential, primarily located in the middle parts of the watershed. The high erodibility in these areas can be attributed to erodible geological formations, steep slopes, and high drainage density. Other contributing factors include predominantly southern and western slope aspects, longer slopes, and poor vegetation. 

 The indicators used in assessing erosion-prone areas provide insights into the geomorphological and hydrological conditions of the study watershed. The prepared erosion map can serve as a foundation for prioritizing soil conservation management measures and reducing the impact of erosion. 

Innovation:

 This research employs a combination of geomorphometric indicators and a fuzzy approach to assess soil erosion potential accurately. The practical application lies in utilizing the study's findings to prioritize areas for effectively implementing erosion mitigation and soil conservation measures in land management.

The increasing human needs and changes in climate patterns have led to the construction of water storage structures to meet the water demand in many regions worldwide, including Iran. Consequently, the hydrological regimes of rivers in various parts of Iran, due to human activities such as dam construction, have undergone alterations in recent decades. Understanding the effects of dams on river hydrological regimes is essential for river flow management and the preservation of river ecosystems. In this regard, the present study assesses the changes in the health of the Urmia's Shahrchai River flow during three periods: pre-dam construction, dam construction, and dam operation, from 1951 to 2017, through calculating different flow health related indices. The results indicate that the deviation of all hydrological health sub-indices in the post-dam construction period is higher than the pre-dam construction period. Moreover, the deviation of flow regime sub-indicators was predominantly low to moderate until 1998 and varied from low to very high after 1998. Additionally, the highest deviation of studied flow health-related indices occurred during the reference and dam operation periods for flood occurrence and minimum monthly flow, respectively, while during the dam construction period, it pertained to minimum monthly flow. Furthermore, the findings suggest that the hydrologic health of Shahrchai River flow decreased by approximately 16% and 45% during the dam construction/operation periods, respectively, compared to the reference period. The results of this study can be utilized in the understanding of flow alteration and the sustainable regulation of the Shahrchai River flow regime.

Human activities have significantly contributed to environmental destruction, necessitating the assessment of land use changes to better understand and manage land resources. Land use plays a crucial role in balancing hydrology, economy, and the environment. By evaluating the intensity and trends of land use, we gain insight into the processes within the ecosystem. This study focuses on analyzing land use/cover changes in the Ramian watershed, Golestan province. Satellite images from Landsat were utilized to create land use maps in 1991, 2006, and 2021 using the Support Vector Machine (SVM) algorithm and ENVI software. The accuracy of these maps was assessed using the kappa coefficient and overall accuracy. The results indicate acceptable accuracy, with kappa coefficients of 0.74, 0.79, and 0.87, and overall accuracies of 81%, 86%, and 91% for the respective study years. Noteworthy changes occurred in dry farming, forest, irrigated agriculture, orchard, pasture, and residential areas, with percentages of 19.92%, -4.50%, 42.28%, 571.5%, -8.87%, and 107.3% respectively over the 30-year study period. These findings underscore the impact of human activities on land use degradation in the Ramian watershed landscape and can provide valuable insights for designing practical models to land management.

The decrease in global biodiversity caused by human activities and the continuous expansion of man-made land use has deepened the need better to understand the relationship between biodiversity and human disturbance. By knowing and examining the process of disturbance changes over time, it is possible to identify the factors that cause it and make appropriate decisions to reduce disturbances. Meanwhile, the application of landscape ecology in various fields of urban planning shows the ability to analyze and quantitatively express the results of human-environment interaction. Gaining comprehensive knowledge of the behavior of this type of change is necessary to achieve systematic management and efforts to ensure the sustainability of ecosystems. In addition, identifying the main processes and structural factors in creating key changes in the landscape provides a proper understanding of the behavior and changeability of the landscape. Ecological disturbances can be caused naturally (fires, floods, avalanches, hurricanes, or volcanoes) or by human activities (road construction, pollution, land use, or mining) and can even completely change a habitat. One of the needs of planning for effective and sustainable management and protection is a better understanding and awareness of the process of spatial changes of this type of disturbance. The timely identification and monitoring of ecosystem responses to disturbance stimuli is an important step in ensuring the sustainable use of natural resources and integrated watershed management. Based on this, the current research aims to identify disturbance drivers, develop multifunctional disturbance indicators, and analyze their spatial patterns in the Samian Watershed located in Ardabil Province.

Materials and Methods  :

In the present study, according to the literature review of the watershed and research related to disturbance indicators, a total of 29 disturbance drivers were identified. Then, Spearman's test was used to identify and remove disturbance indicators with significant correlation (p-value<0.05). Finally, using the weighted sum of disturbance drivers, four multifunctional indices based on land use (DI-LU) (with criteria of agricultural area, range area, total agricultural and residential, dry farming area, irrigation area, urban area, urban 600 m buffer, urban-agricultural 600 m buffer, ndvi and road density), demographic (DI-DG) (with criteria of population density, rural household density, density of 10-year working people, density of people working in agriculture, density of people working in the industry, density of people working in services and residential density), sources of pollution (DI-CR) (with criteria of soil erosion, special sediment, LQ spatial coefficient in the agricultural, LQ spatial coefficient in the industry, river distance from residentional areas, density of mining operations, density of industrial centers, pol1utant density) and hydrology (DI-HR) with criteria (with criteria of slope, reservoirs and wetlands area, dam storage, dam density) and a total disturbance index (TDI) were developed.

In this research, the multi-functional indicators of disturbance in 27 Samian sub-watersheds were calculated and zoned based on identified disturbance drivers. The results of equal weighting showed that the variables used in the calculation of disturbance indices based on the first to fourth groups were assigned weights of 0.13, 0.50, 0.17, and 0.33, respectively. The results of zoning showed that the maximum value of disturbance index based on land use (DI-LU) related to sub-watershed 27 with a value of 0.77 in the high class, demographic (DI-DG) related to sub-watershed 27 with a value of 0.89 in the class very high, pollution sources (DI-CR) related to watershed 15 with a value of 0.61 were placed in the high category and hydrology (DI-HR) related to watershed 25 with a value of 0.82 were placed in the very high disturbance category. The average of the first to fourth multifunctional indices were 0.46±0.16, 0.40±0.16, 0.38±0.09, 0.52±0.15 and 0.44±0.08 respectively. The results of the total disturbance index showed that the mean and standard deviation of the total disturbance index (TDI) are equal to 0.44 and 0.08. This confusion index was categorized into three categories: low, medium, and high. Besides, a significant area of the entire Samian watershed was placed in the middle class (0.41-0.60).

In recent decades, natural ecosystems have experienced unprecedented negative disturbances due to global climate warming, extreme weather events, excessive human exploitation of resources, and damage to the environment. In the long run, this has led to a series of complex problems that will threaten the survival and sustainable development of society. Accordingly, the regional identification of disturbance drivers is very important to reducing the conflicts between socioeconomic development and environmental protection. In this context, according to the zoning results, most of the sub-watersheds were placed in the middle class based on the fourth group, which indicates the importance of considering factors such as slope, dam storage, and dam density. From the general point of view, the Samian watershed has a medium, low, low, and medium class, respectively, based on the disturbance indicators of the first to fourth groups. In general, the central and northern parts of the watershed have higher disturbances than other parts. The results of the spatial analysis also showed that the central parts of the Samian watershed are affected by more disturbance. The results of the present research are used in the diagnosis of the dynamics of disturbances to understand the interactions of a watershed system and develop the strategies required for sustainable management.

Soil erosion is one of the most important geomorphological processes on the earth's surface, which has accelerated due to human intervention. This process causes many damages such as loss of fertile soils, destruction of infrastructure and filling of dams. In the assessment of soil erosion, several factors should be used in a combined and integrated manner. In this regard, in basins without data or with limited data, a set of geomorphological indicators can be used in combination with other indicators and the erosion potential can be evaluated. In the current research, the erosion potential of Firouzabadchay catchment area located in Ardabil province has been evaluated. In this regard, 13 indicators, mainly geomorphological, were used. In order to combine and overlapped the layers, fuzzy logic was used in the context of the geographic information system (GIS). The results show the high potential of soil erosion in the surface of the Firozabad catchment area. Several factors are effective in the erodibility of the basin's soils, which in this context can be the wide outcrop of Quaternary alluvial formations, gypsum marls, lahar and volcanic ash, weak vegetation, predominance of steep slopes, high drainage density, existence of numerous streams, high values of roughness number and long slopes. In zones of the study basin where several factors affecting erosion have favorable conditions, the rate of erosion has intensified. In this regard, we can mention the central sub-basins of the study basin, which are among the critical areas of the basin due to the presence of alluvial and marl formations, weak vegetation, high slope, high drainage density and several other factors.

Introduction and Goal:

In hydrological and water resources studies, the understanding of water balance components and changes holds great significance. Climate changes and human activities affect runoff changes, water resources management and sustainable development of society. In this regard, the current research was conducted with the aim of determining and comparing water balance changes using Budyko curve in Nir watershed, Ardabil province.

The Budyko curve was calculated for the Nair watershed in monthly, seasonal and annual time scales. In this study, the data of the rain gauge and evapotranspiration station of the watershed were also used in a statistical period of 33-years to calculate the average precipitation and evapotranspiration potential in the watershed. In the Budyko curve, the non-linear relationship that is limited by the physical limits of atmospheric water demand (PET>ET) and supply (P>ET) and the aridity index in the Budyko curve show the long-term water balance.

The results showed that, the trend of flow changes is directly related to the trend of weather components in annual time scale. Meanwhile, contrary to expectation, only in some seasons does the flow change process follow the change in climatic components. In addation, the Budyko curve analysis indicated that the amount of water consumption in the studied watershed regularly deviated from its predicted dependence on energy and water balance. The maximum, average and minimum ET for the studied years were obtained as 876.55, 431.85 and 277.88, respectively. Also, the maximum, average and minimum ratio of PET/P was 0.07, 0.05 and 0.02 respectively. In most of the years studied, the observational data aligned with the water limit range on the Budyko curve, indicating that the observed water consumption (AET/P) matched the predicted water consumption (PET/P). According to the results, the changes in AET/P are less in the years (1981, 1983, 1989, 1994, and 2010). Based on the changes in the values of PET/P and AET/P in the Budyko curve, the watershed ability to regulate AET can be considerable.

Conclusions and Suggestions:

The results of this study indicated that with increased temperature and decreased precipitation, the annual actual evapotranspiration of the watershed increased, leading to a reduction in runoff. The results can be the basis for providing management solutions and adapting to the climate change in order to optimally use the available water resources. In general, it can be said that the amount of potential evaporation in the studied watershed is more than the amount of precipitation. The study's findings can provide a basis for managing water resources under the limitations of climate change and human abstractions.

This research aims to analyze the spatial water footprint of agricultural products in four categories of blue, green, gray, and white water in Khiavchai sub-watersheds. To this end, the meteorological data (monthly rainfall and temperature) were used as input data for the CROPWAT program. The Google Earth images were used to map the land use areas and estimate the area of agricultural and rangelands. It was found that apples, sour cherries, cherries, walnuts, and grapes are the dominant crops produced in the orchard area. The four types of virtual waters of agricultural products were analyzed in four land uses, i.e., orchards, rainfed agriculture, irrigated agriculture, and rangelands. The total water consumed by the apple product is more than other products in all sub-watersheds and the amount of virtual water of walnut is also high in most sub-watersheds. The total consumption of blue, green, white, and gray water in sour cherry, cherry, and grape was the same and was evaluated as less than the other two products. In addition, the average amount of blue water for rainfed agriculture was estimated as 2788.85 m3 t-1, among which lentils and chickpeas had the higher blue water among the rainfed crops. According to the results, sub-watersheds 7 and 14 located in western parts of the study area had the highest of virtual water. In sub-watershed 7, a large part of its area is used for rangeland and only a small part is related to rainfed agriculture, and all area of sub-watershed 14 is used for rangeland. Therefore, the appropriate cultivation pattern can be determined based on the amount of virtual water and its spatial changes.

To mitigate land degradation and desertification as an environmntal issue, it is crucial to monitorland degradation intensities, identify influential factors, and implement necessary measures. Thisstudy utilized remote sensing data and logistic regression modeling to assess desertificationin Larestan County. Multiple indicators were considered in this study, encompassing climatefactors (such as rainfall, evapotranspiration, and aridity index), groundwater indicators (includingelectrical conductivity, chloride content, sodium absorption ratio, and groundwater level decline),soil indicators (such as EC, texture, and organic matter content), land use and land cover (LULC)type, and wind erosion. The logistic regression model was employed to identify the most influentialfactors contributing to desertification. The findings revealed different risk classes: a small low-riskclass in the eastern and southern regions covering 2.4% of the total area, a moderate-risk classin the foothill-plain areas covering 38.3% of the total area. The high-risk class of desertificationis mainly concentrated in the central part of the study area, adjacent to regions with moderaterisk. It is characterized by relatively large patches, particularly in the southwest of the interiorplains, covering approximately 1,980 hectares, which accounts for 7.9% of the total area. Theconcentration of high-risk desertification in specific areas highlights the urgent need for proactivemeasures to preserve the environmental balance and sustainability of the study area.

Runoff and the rainfall-runoff relationship are one of the most fundamental research topics in hydrology. Due to the increasing trend of flood occurrence and the resulting damages, it is necessary to determine the flood-producing priority areas and prioritize the sub-watersheds in terms of flood control projects and integrated management of watersheds. The primary contributing areas in runoff generation and the affecting factors should be identified in a flood management project. Understanding the flood occurrence potential of watersheds can be useful in formulating different flood management plans, allocating necessary funds, water resources management, watershed management, and erosion control programs. Watershed Modeling System (WMS) as an integrated flood modeling software can simulate flood hydrographs considering the required parameters. Among the common runoff estimation methods, the SCS curve number method is the most common in estimating flood volume and flood runoff height. Land use changes as an important factor in the alteration of watershed hydrologic response can accelerate soil erosion and biodiversity loss. Land use change affects the curve number and consequently, discharge and flood hydrographs, as assessed in the current study.

The Khiavchai Watershed, with an area of about 134 km2 has been chosen as the study area. The annual rainfall of the study area is 343.8 mm. Toward the hydrologic modeling in the study area, the slope map of the watershed has been derived from the DEM of the study area using the ArcMap software. The maximum daily rainfall of 11 rating gauge stations has been obtained and the raw data has been processed using a common statistical test to check the data quality and homogeneity of SPSS software. The maximum 24-h rainfall data were analyzed using Easy Fit software to select the best statistical distribution. The 3-parameter Pearson distribution (as the best probability distribution function), has been used to calculate the rainfall values in 2 to 100-year return periods. The maximum daily rainfall values were entered into the ArcGIS software and the spatial distribution mapping was done using the IDW method. The average maximum daily precipitation with different return periods was converted to 6-h precipitation. The SCS and WMO rainfall patterns were compared in the study area, and the WMO rainfall patterns were selected as the appropriate input for the model. The maximum annual instantaneous discharge values have been used in estimating the flood discharge in 2, 5, 10, 25, 50, and 100-year return periods using EasyFit software. The input model parameters (slope map, slope direction, curve number, and soil hydrological group) were prepared in ArcGIS and Arc-Hydro software.

The results showed that the maximum flood discharge increases intensely with an increase in the return period. The average CN value of the basin was obtained at 76, the initial loss coefficient was obtained at 0.202, and the STRTL value was obtained at 16.203. According to the increasing curve number values, the infiltration time and the time to reach the peak are reduced. Therefore, by increasing the curve number by 5, 15, and 25%, respectively, the time to reach the peak is 240, 180, and 135 min, and the base time of the hydrograph has decreased by 1035, 885, and 750 min. Meanwhile, the peak value of the simulated flood hydrograph has increased from 1.74 to 6.466, 27.491, and 109.694 m3 s-1. With an increase of 25% curve number, the peak discharge in the return period of 10, 25, 50, and 100 years has increased to 13, 9, 7.5, and 6.3, respectively. The results show that the effect of changes in curve number values on the flood discharge, in the low return period is much more than the high return period. So in the return period of 100 years with 25% changes in curve number, the peak flood discharge value is 6.38 times in the 2-year return period. The results indicate that the least change in the type of land use (in order to reduce permeability) causes a considerable increase in flood discharge in the region.

The effects of changes in CN values have been assessed in the current research in a modeling framework to estimate the flood hydrograph components. Comparison of the estimated flood hydrograph components against observation values has been evaluated using relative error and root mean square error. The values of these statistical indices were obtained with the least error related to the 3-parameter lognormal distribution of about 10.32% and 8.68 m3 s-1. By comparing the results of the maximum flood analysis and the WMS model, it can be concluded that the simulated data are consistent with the observed flood records in the Pole-Solatani river gauge station located at the outlet of the Khiavchai Watershed.

The purpose of this study was to evaluate the temporal variations of vegetation cover of Gharesou River riparian area in Ardabil province using landscape metrics over a period of 8 years which is important for morphology assessment and river ecosystem protection planning and management. The Google Earth imagery for the years 2011, 2016, 2019 due to their live view and high resolution were used to map the Gharesou River riparian area vegetation. Correlation analysis in R environment was used to evaluate the relationship between landscape metrics in the study time period. The results showed that there is an increase in the number of patches, which showed an increase in landscape fragmentation of the riparian area vegetation. Landscape connectivity index was 91.52% to 95.49% in this region during the study period, indicating the removing small patches of vegetation communities around the river. The number of patches in the present study showed an increasing trend, which was the highest amount at 2019 year. The results of changes in the width of the Gharesou River showed that the river width in 2019 was 27.43m and 3.97 m, respectively. Comparison of river width values ​​over the three study periods indicates an increasing trend in river widths, which may be due to the limitation of river width by human activities or the protection of river banks to protect agricultural lands against flooding effect. Also, the correlation of river width showed that the correlation between time period 2019 and 2016 was 0.63 and significant at 0.001 levels. The lowest correlation between the period 2019 and 2011 was 0.30 at 5% significant level. In conclusion, the results of changes in riparian area communities can be linked to the extension of agricultural land adjacent to the main river course.

The rainfall system of a major part of Iran is mediterranean, where the precipitation amount during the vegetation period is low. In addition, the occurrence of precipitation in the non-vegetation period or beginning of the vegetation period, which does not cover the surface of the earth well, is one of the important reasons for water erosion in Iran. Since vegetation has a special role in soil erosion control and runoff retention, any change in the vegetation structure and pattern, which expresses the landscape pattern and function, can have a significant effect on changing hydrological processes. Therefore, the assessment of soil and water loss and the quantification of its relationship with landscape metrics provide key information for the development of water and soil quality management strategies.

The current research was conducted to investigate the hydrological component changes with landscape metrics on 2 m2 plots using simulated rainfall at an intensity of 32 mm.h-1 in a part of rangelands of Ardabil County. At first, considering the type and percentage of vegetation as the main variable, eight groups of vegetation composition along with one group without vegetation (control) were considered with three replications. The composition (and percentage) of the vegetation from the first to the eighth groups, respectively, include low-height graminea predominance (45), the composition of dense bushes with graminea (43), bushes with low-height and medium-distribution (37), sparse bushes mostly with low and medium height (31), the composition of sparse bushes with graminea (56), dense bushes in upper parts (54), low-height bushes with very low distribution (15), and dense bushes with almost uniform distribution (56). After measuring the runoff and sediment at the plot outlets, different hydrological components were calculated. Then, plots with nine different vegetation combinations were imaged in three replicates before and after rainfall simulation. After transferring the images prepared from the plots to the Arc/Map10.8 environment, nine important landscape metrics were calculated.

Changes in the mean patch density (4.43-26.90), largest patch index (54.16-86.75), edge density (17.12-107.38), landscape shape index (1.50-4.47), mean shape area (4.16-37.46), mean Euclidean nearest neighbor distance (0.00-1.65), landscape division index (0.19-2.31), mean patch shape index (1.24-22.85), and the effective mesh size (15.80-43.96) indicate their different influence from different percentage and composition of vegetation cover. Spearman's correlation matrix analysis showed a nonsignificant relationship between the mean soil loss, runoff volume, runoff coefficient, and sediment concentration with landscape metrics (r<0.26 and p-value>0.10). The small scale of the studied plots, the lack of diversity in the vegetation composition, and the uniformity in terms of vegetation height can be cited as the reasons for the lack of correlation. In general, groups with vegetation values above 50% had a better condition in terms of LPI, AREA_MN, and MESH, which indicates more connectivity and less degradation. The increase in vegetation cover and spatial heterogeneity above the landscape surface can change the path of sediment transport, reduce sediment connectivity, and lead to a decrease in sedimentation.

The obtained results are applicable in explaining the appropriate reference to optimize water and soil protection measures on the watershed scale. However, It is suggested that similar and more comprehensive research be done in different scales of erosion plots and even in the landscape (slope) scale so that by considering a wide range of vegetation, topography, climatic conditions, as well as successive rains, it is possible to compare the results, optimum selection of study scale, and finally planning to manage and protect vegetation and water and soil resources.

Soil erosion in Iran is one of the most important problems of drainage basins that can be mentioned as main barriers to the sustainable development of agriculture, geoscience, and natural resources. Therefore, soil erosion control is one of the most urgent environmental issues which need to identify in erosion-prone areas in the watersheds. In many watersheds, the role of land use in soil erosion is greater than of other factors. Knowing the contribution of different types of land use to soil erosion leads to managing land use and reducing the severity of soil erosion, and even increasing the income of the watershed stakeholders. Evaluation and identification of soil erosion in coastal regions are one of the most important measures for comprehensive coastal management. Therefore, the current research was carried out with the aim of estimating soil erosion in different temporal and spatial scales with the G2 model, according to the land use/land covers of the Caspian Sea basin.

The northern region of Iran encompasses the Caspian Sea basin, which spans approximately 91,176 km2, equivalent to around 10% of the country’s total area. It is situated between latitudes 45°39'-35'N and longitudes 59°59'-44'E. With an average elevation of 1,195 m, the watershed exhibits significant variation, ranging from the highest point at Mount Damavand with an elevation of 5,699 m to the lowest point along the Caspian Sea coast at -28 m. The Caspian Sea basin is divided into seven primary basins and further subdivided into 108 sub-basins using the Strahler stream ordering method. In order to prepare soil erosion map in the study area, the input factors of G2 model were prepared in appropriate spatial and temporal scales using meteorological data, satellite images, application of GIS and RS. The G2 model combines five input erosion parameters in a multiplicative equation to produce month-time step maps and statistics of soil erosion. Ideally, a single layer suffices for S, T, and L factors, while a collection of 12 layers (one for each month) is required for the dynamic factors R and V. Also, the values of soil erosion were estimated for different types of land uses/covers in different time scales for the Caspian Sea basin.

The results showed that the average annual soil erosion for the study area is reported to be 11.24 t ha-1, the highest soil erosion rates observed in the West Azarbaijan, Mazandaran, North Khorasan, and East Azarbaijan provinces. On the other hand, the highest monthly soil erosion with the rates of 1.49, 1.48, 1.32, and 1.27 t ha-l were in November, October, April and May, and the lowest monthly soil erosion with the rates of 0.54 and 0.59 t ha-1 were in August and December, respectively. The highest amount of soil erosion occurred in autumn and spring compared to winter and summer. One of the reasons for the increase in soil erosion in the autumn season is the high intensity of rainstorms that occur in lands with little vegetation and in the spring season, may be due to the increase in rainfall and snow melting in this season and its effect on the increase of soil erodibility. Also, minimal soil erosion in summer and winter seasons can be caused by the decrease in the amount and intensity of rainfall or the absence of effective rainfall. In addition, it was found that with the increase of rainfall erosivity, soil erosion increased on a monthly time scale. The highest annual soil erosion with the rates of 16.87, 15.96, 11.51, and 11.22 t ha-1 were in rangeland, shrubland, barren lands and forest II, respectively. As a result, annual soil erosion values in the western, central, and eastern parts were estimated equal to 11.94, 13.47, and 10.53 t ha-1, respectively. Although the difference of soil erosion in monthly, seasonal and annual time scales in all different land use/land covers is significant at the 99% level, but it is not significant in a number of large land use/land covers in the Caspian Sea basin in the western-central, central-eastern and western-eastern parts.

According to the current research, 40.53% of the lands in the studied area have soil erosion of less than 1 t ha-1 yr-1, which are in the range of low erosion, because this amount of wastage is almost equal to the annual soil construction limit and is normal, and these areas do not need watershed operations and the risk of soil erosion is low. While about 18.73% of the land surface of the studied area, soil erosion exceeds 20 t ha-1 yr-1, and it is recommended that in these areas, in addition to biological operations, mechanical operations are also performed to reduce and control soil erosion. The results obtained from the present research provide managers and policymakers with information and appropriate decision-making bases for the management and sustainable use of soil and water resources.

Due to the proximity to natural resources and the environment around them, the villages are most affected by the environment and are of great importance. The improper rural development poses enormous environmental challenges such as degradation of rangelands and forests, overexploitation of soil and water resources and threats to wildlife. Of course, the distribution pattern and accessibility to service-based infrastructural indicators indicates the growth and development of rural areas and the attitude towards decentralized planning in the country. This research was carried out in 2022 with the aim of identifying and rank rank service-based infrastructure indicators based on services, in the northern villages of Ardabil province, using a variety of prioritization methodologies. The research method is descriptive-analytical and applied, according to the nature and purpose of the research. 15 indicators with appropriate level of validity and consensus of executive experts and academic experts were selected to measure the infrastructure in the region. According to the results, the highest rate related to the index of access to electricity is in the villages of Meshgin Shahr with a value of 86.71% and the lowest rate related to the index of access to agricultural machinery repair shop is in Garmi city with a value of 3.86. In general, the results showed that Dasht village in Meshginshahr city was at the first level compared to other villages (Ci=0.693) and Eastern Qashlaq village in Beileswar city was at the last level (Ci=0.497). Therefore, it is suggested that while locating rural areas at different levels, especially the level of access to existing facilities, the strengthening of village facilities and expansion of infrastructure and welfare services should be prioritized.

One of the important conditions for optimal use of land is obtaining information about landuse patterns and their changes over time. Landuse is usually defined based on human use of land, emphasizing the role of land in economic activities. Today, remote sensing technology is considered as the main element in landuse monitoring. The aim of the current research is to extract landuse maps for the years 2000 and 2021 in FirozabadKhalkhal region and to investigate the changes made in the studied time period in the region using the images of ETM and OLI sensors of Landsat. Also, checking the capability of basic pixel and object-oriented methods for landuse classification is another purpose of this study. In the current research, the object-oriented technique nearest neighbor algorithm and the vector machine method supporting the pixel-based algorithm have been used for landuse classification. Then, to verify the accuracy of these two methods, the overall accuracy and Kappa were extracted. The results of this evaluation show the high accuracy of the object-oriented method in extracting land use classes. Based on the results of the detection of landuse changes in the studied time period, the highest amount of changes occurred is related to the use of good pasture to poor pasture with a value of 51.72 square kilometers, followed by forest to good pasture with a value of 30.11 and the lowest changes It is related to the use of pasture and water with the amount of 0.03 square kilometers. The reasons for these changes are the increase in population, indiscriminate grazing of livestock, incorrect and illegal use of different lands. The use of more parameters such as scale, shape, compactness, color, texture, smoothness criterion and pattern for landuse classification in the object oriented technique can be considered as an innovation of the present study.

Statement of the Problem: Floods are a devastating natural disaster that can cause soil erosion, soil wastage, and damage to human infrastructure in flood-prone areas of watersheds. Therefore, it is crucial to predict and determine the amount of runoff production processes and its safe transfer to the outlet of the watershed. Various factors, including climatic and physiographic parameters, affect the conversion of precipitation into runoff. Climatic factors involve the intensity and duration of rainfall as well as the distribution of rainfall locations. Physiographic parameters include land use type, soil type, watershed area, basin shape, height, slope, direction, and type of drainage network. Therefore, several methods can be used to estimate the runoff generated by rainfall, and one of the commonly used methods in hydrology is the Soil Conservation Service (SCS) method. Furthermore, determining the spatial changes and correlation between the factors of runoff production and flooding can identify flood-prone areas. Therefore, this research utilized geographic information systems (GIS) to provide essential and fundamental information for obtaining direct runoff using the curve number (CN) method. The study aimed to estimate the height of excess rainfall runoff and analyze the spatial variations of runoff height and volume in the Sharganj watershed, Birjand. To achieve this goal, the SCS method was employed to estimate the amount of runoff generated by the maximum 24-hour rainfall in different return periods in the aforementioned watershed. Subsequently, the changes and spatial correlation of the values of the height and volume of the runoff were evaluated in the Sharganj watershed, Birjand.

This study estimated the amount of runoff produced from the maximum 24-hour rainfall in different return periods in the Sharganj watershed using the SCS method. To achieve this, the maximum 24-hour rainfall from surrounding stations was averaged using the IDW method. Next, the SCS method was utilized to estimate the runoff by combining land use maps and soil hydrological groups to prepare the curve number map. The basin runoff volume was then calculated for different return periods. Additionally, the spatial autocorrelation of the runoff height and volume in the 25-year return period was analyzed using the general Moran's index, and their clustering pattern was determined using Anselin Local Moran's Index.

The Sharganj watershed is primarily used for pastures and agricultural lands, with the former being located in hydrological group C. Despite this, rainfed and irrigated garden lands, mainly located in hydrological group B, have better permeability. Using ArcGIS software, land use maps and soil hydrological groups were combined to prepare a curve number map of the watershed. The results showed that the curve numbers of the sub-watersheds ranged from 68 to 79, with sub-watershed number 9 having the lowest curve number value (68) and sub-watersheds 22, 25, and 29 having the highest (79). The Global Moran's index values presented in Table 3 and Figure 10 showed that the spatial correlation of runoff height and volume had values of 0.1828 and -0.2694, respectively. The curve number decreased from west to east due to the presence of barberry gardens and irrigated agricultural lands. The spatial correlation map of runoff height values showed high-high (HL) clusters forming in the upstream parts of the basin, while low-low clusters (LL) were present in the downstream areas. These patterns were related to the amount of precipitation in the upstream part and the high slope of the upstream sub-watersheds. Meanwhile, the spatial correlation values of runoff volume indicated that the accumulation of runoff volume was higher in the sub-watersheds located downstream of the study area, with low formation of high-low (HL) clusters. This increase in flood volume occurred in the downstream sub-watersheds and adjacent to the outlet of the area. In general, the difference in the cluster pattern of runoff height and volume did not follow the same pattern, which depended on various factors affecting runoff production, such as the amount of precipitation in different parts and the difference in topography. It should be noted that the analysis was based on height and volume values in the 25-year return period, and the results can be expected to be similar for other return periods based on the curve number method.

The research findings suggest that the spatial changes in runoff height and volume components, which impact watershed response and flood producing procedures, are determined by various factors such as slope, land use, curve number, and soil hydrological group. Areas with high amounts of runoff are more susceptible to damages caused by floods and can be prioritized for management measures. Furthermore, the results indicate that the type of surface runoff control measures or flood volume control required will vary, providing valuable guidance for determining the appropriate damage reduction operations. Further studies analyzing the spatial correlation of height and runoff volume variables with other basin features and climatic factors could enhance the understanding of spatial changes. The formation of surface runoff is influenced by various factors related to rainfall and ground conditions, which could be considered in future research.