نشریه مدیریت جامع حوزه های آبخیز
سال سوم شماره 3 (پیاپی 9، پاییز 1402)

Extended abstractIntroductionSoil serves as the foundation for all human productive activities, and the rise and fall of numerous great and ancient civilizations can be attributed to the fertility and preservation of soil. Some civilizations have experienced downfall due to inadequate productivity and failure to sustain natural resources. Erosion can be classified into two main categories: geological erosion, which can lead to soil formation and accelerated erosion, which causes soil degradation. The study of erosion is of great significance. For instance, Asia currently faces a concerning erosion condition, while Africa is experiencing a highly dangerous level of erosion. Erosion is a globally destructive phenomenon, particularly water erosion, which directly and indirectly impacts human life by depleting fertile agricultural soils. In order to determine appropriate protective measures, it is crucial to assess the level of erosion in a given area. Thus, evaluating the severity of erosion becomes an essential task. This study aims to examine the erosion and sedimentation status in the Golan watershed of Ilam province, as well as determining the current state of soil erosion and sediment yield.Methodology The study focuses on Golan watershed in Mehran city, Ilam Province, which spans an area of 78.87 km2. To conduct this research, the following methodology was employed. First, a topographical map on a scale of 1:50000 and aerial photos of the area were obtained. The topographic map was used to delineate the boundaries of the study area, while the aerial photos aid in understanding the natural features and assist in dividing the area into hydrological units. Next, Relevant information and statistics from previous studies related to the study area were collected. This data provide valuable insights and contribute to the analysis. Then, Base maps were prepared within a ArcGIS environment. These base maps include geological maps, soil types, vegetation cover, slope, direction, elevation classes, and other pertinent factors. To enhance accuracy, the base maps were verified in the field, and the necessary parameters for estimating erosion and sedimentation were scored through field surveys. After that, the MPSIAC model was utilized to estimate erosion and sedimentation. By inputting the collected data and factors derived from the base maps into the model, erosion and sedimentation rates were estimated. The model will help assess the vulnerability of the study area to erosion. Finally, Based on the estimations from the MPSIAC model, an erosion map was prepared. This map depicts the areas prone to erosion within the study area, providing valuable information for land management and erosion control strategies. By following this methodology, the research aims to evaluate erosion and sedimentation rates in the study area and generate an erosion map that can assist in effective land management and erosion prevention measures.Results In the Golan region, various types of erosion were observed, indicating the influence of different factors with varying intensities. These erosion factors can be categorized into two groups: natural factors and human-induced factors. The rocks in the study area were classified into five erosive groups. The geological factor score for the entire area was determined to be 6.15 based on the sensitivity map of rocks in the sub-areas. The soil factor score was calculated to be 3.71. Furthermore, the climate factor score was 17.8, the runoff factor score was 13.01, the topography factor score was 10.44, the land cover factor score was 9.62, the land use factor score was 15.67, the soil surface erosion factor score was 1.81, and the water erosion factor score was 15.41.Discussion and ConclusionIn terms of erosion and sedimentation, the study area fell into the high erosion class, with a sediment yield of 541.26 m3/km2/year. Field surveys identified 12 types of erosion in the watershed. By understanding the erosion factors, measures can be taken to control erosion. Based on the obtained zoning map, it is recommended to implement control and protective operations in erosive areas, while avoiding any activities or projects that may lead to accelerated erosion, such as road construction. Natural erosion occurs in nature and does not necessarily result in soil loss. However, human interventions in natural resources exacerbate erosion intensity, leading to accelerated erosion. Therefore, it is crucial to assess the intensity and types of erosion in different areas and implement appropriate planning and management measures. One proposed program to control soil erosion in the region is the implementation of land uses based on their capabilities, along with soil protection programs for agricultural lands. Additionally, techniques aimed at increasing the stability of soil grains should be considered to reduce erosion. In conclusion, understanding the factors contributing to erosion and implementing appropriate management strategies are vital to erosion control and soil conservation in the study area.

Extended AbstractIntroductionHydrological modeling is an essential tool in water resources management, and its accuracy and reliability are critical to successful design, planning, and decision-making processes. Calibration and validation are two essential processes used to evaluate the performance of hydrological models. The warm-up period is a crucial component of hydrological modeling that allows the model to reach an equilibrium state by representing the initial system conditions accurately.This study aimed to investigate the impact of the length of the warm-up period on the performance of four different hydrological models, namely AWBM, Sacramento, SimHyd, and TANK, in the Kashkan watershed. The study used different optimization methods in the RRL software package during the calibration and validation periods. The proposed warm-up periods of 5%, 7%, and 10% of the initial data length were used without considering drought and wet conditions.The findings of this study provide valuable insights into the impact of the warm-up period on hydrological modeling performance. The study showed that the length of the warm-up period does have a significant impact on model performance, with the best results obtained when the warm-up period was set to 5% or 7% of the initial data length. These findings have important implications for the design and implementation of hydrological models, as they highlight the importance of carefully selecting the warm-up period length to ensure accurate and reliable modeling results. Overall, this study adds to the body of knowledge on hydrological modeling and provides useful guidance for future research and practical applications.Materials and methodsThe Kashkan River watershed, with an area of over 9,000 hectares, was selected as the study area for this research. The Kashkan River is an important sub-watershed of the Karkheh River watershed, and daily rainfall, potential evapotranspiration, and potential evapotranspiration for the Kashkan watershed were used in this study, with a statistical period of 29 years (1988-2018). Since the rainfall-runoff process was investigated for the entire watershed, the Thiessen polygon method was used to obtain the weighted average of rainfall and evapotranspiration for the entire study area. Additionally, the Hargreaves-Samani (H-S) method was used to obtain potential evapotranspiration data.The data used in this study were divided into two parts, training and testing, based on trial and error and a review of sources. The training data accounted for 70% of the total data, while the remaining 30% was used for testing. The AWBM, Sacramento, SimHyd, and TANK models in the RRL software package were investigated, along with seven optimization methods using the Nash-Sutcliffe objective function.The findings of this study provide insights into the application of different hydrological models and optimization methods in the Kashkan River watershed. The study highlights the importance of accurately representing initial system conditions during modeling and the impact of the length of the warm-up period on model performance. These findings have important implications for water resource management, particularly in the design and implementation of hydrological models for the Kashkan River watershed and other similar regions.Results and DiscussionThis study examined the influence of different durations for the warm-up period on the calibration and validation of RRL software package models. Seven optimization methods and the Nash-Sutcliffe criterion were utilized in the analysis. Specifically, the warm-up phase of the software, which constitutes the initial segment of the statistical period, was investigated during the calibration and validation processes. Durations of 5%, 7%, and 10% were selected from the onset of the statistical period. The study involved conducting over 4000 iterations for all the examined models and optimizers.Given the characteristics of the optimizers, up to 5 iterations were performed for each optimizer in each model. The resulting average NSE value (Nash-Sutcliffe Efficiency) was analyzed and examined.The findings indicate that, on average, configuring the warm-up period to account for 5% and 7% of the complete dataset in the calibration and validation processes enhances the efficiency of the model compared to the recommended period suggested by the software. However, it is important to note that the outcomes may vary depending on the specific problem and prevailing conditions. Therefore, these results should be interpreted cautiously and in conjunction with other factors. Overall, this study offers a practical guideline for selecting an appropriate warm-up duration in the calibration and validation of RRL software package models.

Extended AbstractIntroductionAccelerated soil erosion and severe sediment production disrupt the natural balance in watersheds and have off-site impacts on river channels and downstream reservoirs. There are different estimates of soil erosion and sediment yield in Iran. However, what the researchers agree on is that it is more than tolerable erosion. Rangelands cover more than half of Iran, and poorly covered lands play a large role in flood and sediment production. Therefore, the study of hydrology and soil erosion is necessary for sustainable use of pastures. The prerequisite for these studies is long-term monitoring of sediment, runoff, vegetation, soil, etc. A careful review of previous studies on rangeland hydrology shows that most studies have focused on the effect of grazing management at the plot scale or have used simulation approaches and experimental models, as well as in a short period of time. Therefore, it is very necessary to conduct scientific research using long-term monitoring data in experimental watersheds. In this regard, the present study was proposed with the aim of evaluating the sediment yield of small watersheds in pastures with grazing exclusion vs. overgrazing. The results of this research can provide useful information to researchers, promoters, planners, and ranchers.Materials and methodsSanganeh Soil Conservation Research Station (SSCRS) with an area of 30 ha was established about 25 years ago in Kalat County (Razavi Khorasan Province, Iran). In addition to measuring erosion in plots and monitoring vegetation, by building several ponds at the outlets of six small watersheds (SWs), their runoff and sediment yields have also been recorded since 2006. The present study was conducted with the aim of evaluating the erosion and sediment production of these SWs (1200 to 17000 m2). For this purpose, the runoff and sediment of 69 events were collected at the outlets of six SWs. Also, the time series of NDVIs were calculated for SSCRS, adjacent rural and nomadic (outside the village) rangelands on a seasonal scale. To determine the time series of NDVIs, all satellite images of the study area were downloaded and after pre-processing and corrections, the images were processed. Then, the soil erosion amounts of SWs were estimated in terms of the sediment delivery ratio of the study area (Noor, 2020) based on the average sediment yields (according to their long period of 15 years). In the next step, the amounts of soil erosion obtained were compared to the amounts of tolerable soil erosion for arid climate rangelands proposed by Skouti Oskouei and Arabkhedri (2018). Finally, the soil erosion of two similar watersheds, one in the overgrazing area (E6) and the other in the grazing exclusion area (E4), were compared.Results and DiscussionThe results showed that NDVI is influenced by livestock grazing intensity. The highest value of this index was observed in the grazing exclusion area (E1 to E5 SWs), then in the Sanganeh village rangeland (E6 SW), and the lowest value was observed in the nomadic rangelands. In terms of time scale, the biggest difference in NDVIs between overgrazing and grazing exclusion areas was observed in spring. The results of the investigation of sediment production indicated an inverse and non-linear relationship between the specific sediment yield and the area of SWs. This study showed that the amount of soil erosions in E2, E3 and E6 SWs are more than tolerable erosions which suggests the need for more conservation measures. Finally, the comparison of two similar SWs (E4 vs. E6) indicate a significant reduction in annual sediment yield (582%) due to grazing exclusion in the area. Also, the results showed that the sediment productions of E6 SW in the spring and autumn seasons are significantly higher than E4 at 1% and 5% levels, respectively. Furthermore, it is remarkably (but non significant) higher than than the E4 SW in the winter season.ConclusionGrazing exclusion in SSCRS rangeland led to a significant reduction in erosion and sediment production compared to overgrazing condition outside the station. However, in some SWs, the erosion amounts were still more than the tolerable values, which indicates the difficulty of restoration of destroyed rangelands on steep slopes with sensitive formations in arid climate. Implementation of management measures including scientific grazing (especially in spring) is necessary to reducing damage caused by floods and sediments.

Extended AbstractIntroductionMapping and assessment of surface water dynamics is essential for continuous monitoring of water resources as it has significant implications in engineering and scientific research for floodplain delineation, wetlands, disaster management, biodiversity, climate change, and water resource management (Huang et al., 2018; Jawak et al., 2015). Traditional surface water monitoring methods mainly rely on field surveys or on established measuring stations. Although the accuracy of the data obtained by this method is high, it is time-consuming and has low efficiency. In addition, many aquifers are very difficult to access because they are located in remote and rugged places, and only data from limited points in incomplete time series are obtained due to the limitations of economic and land factors (Ogilvie et al., 2018). With the expansion and development of remote sensing science and geographic information system, better ways have been provided to monitor water bodies in a long period such that the use of multispectral satellite images and different spectral indices for monitoring water bodies and floods is a fast and economical method in terms of time and cost. The high number of existing sensors and their differences in estimating the spectral and spatial characteristics of spectral indices have led to a good representation of the potential and limitations of satellite data. Therefore, in this research, to investigate the flood of 2019 in the southwest of Iran, the Modified Normalized Difference Water Index (MNDWI) and the Normalized Diference Vegetation Index (NDVI) obtained from the Landsat 8 satellite images were used.Materials and MethodsThe study area is a part of the southwest of Iran, which includes the southern part of Ilam province and the northern, northwestern, western and southwestern parts of Khuzestan province. In this study, to investigate the flood of 2018-2019, Landsat 8 sensor images were used for three months of January, February and March in 2019. This section used QGis3.28, GIS10.8, Excel software and remote sensing data including satellite images related to Landsat 8 sensor. These multispectral data were obtained from the United States Geology website (earthexplorer.usgs.gov) and were prepared for preprocessing and necessary processing. To prepare a map of the flood area and vegetation, radiometric and atmospheric corrections were performed on the received images (Eskandari Damaneh et al., 2016). After applying the necessary pre-processing, the MNDWI and NDVI were used to prepare the map of changes in water bodies and vegetation for the years 2018 and 2019, respectively (Rugel et al., 2017; Abutaleb et al., 2015; Arekhi et al., 2019).ResultsAccording to the results, the highest values of MNDWI in 2018 corresponded to those on March 12, which includes the northern and central parts. In 2019, the highest value of this index was on the date of March 19, which included the southern to southwestern parts of the study area. Examining the changes in MNDWI classes showed that in 2019, on February 2nd, 19th and March 7th, classes ranging from 0.11 to 0.15 occupied the highest level of the studied range, which is more than 68.75 percent of the area. This range and its trend were increasing. On the other hand, on the mentioned dates, classes ranging from 0.15 to 0.2 covered an area of more than 24.32% of the region, and these classes were decreasing. Accordingly, in 2019, on March 8th and May 14th, the largest percentage of the area under study was still in classes ranging from 0.11 to 0.15, and the total of these areas was more than 76.13% of the region, which was decreasing. On these dates, classes ranging from 0.15 to 0.2 included more than 20.03 percent of the study area, and these classes had gone through an increasing trend.Examining the changes of NDVI classes showed that in 2019, on February 2nd, 19th and March 7th, the largest percentage of the study area was taken by classes ranging from 0.2 to 0.3, which totaled 71.81%, and was increasing. Also, on these dates, classes ranging from 0.3 to 0.5 included more than 11.46% of the study area and these classes were decreasing. Also, in 2019, on March 8th and May 14th, the largest percentage of the study area was still taken by classes ranging from 0.2 to 0.3, and the total of these areas was more than 82.54%, which was decreasing. Meanwhile, on these dates classes ranging from 0.3 to 0.5 included more than 11.64% of the study area, and these classes had been increasing.Discussion and conclusionThe trend of spatial and temporal changes of the MNDWI index in this period shows that in February and March of 2019, the highest value of this index was in the northern and central parts of the studied region. While the highest value of this index was in March and May of 2019, it has been seen in the southern and southwestern parts of Khuzestan province. While this precipitation is in the season when the vegetation in this area is in good condition, the classes above 0.3 NDVI vegetation index in March 2018 and March 2019 are more than 42 and 38% of the area, respectively. Because the southern parts of Khuzestan province have lower altitudes than the northern and northwestern regions, it is plain and flat. This has caused it to serve as the foothills of the upper elevations of Khuzestan and Lorestan provinces, which in turn causes the influx of upstream waters into this region. Even if the vegetation cover is suitable in the season, it has caused a large and unexpected influx of water in these areas, which itself causes flooding of the residential regions, facilities and agricultural lands. In general, it can be concluded that by using the MNDWI and NDVI indices obtained from the Landsat satellite images, it is possible to monitor the water bodies and waterlogged areas resulting from natural hazards such as floods, as well as the vegetation of different regions with high accuracy. The findings of this study can be used in studies and decision making with sufficient confidence.

Extended Abstract

Gully erosion is a severe form of soil erosion, but internal gully erosion processes are not well understood, especially at the scale of rainfall event. Nowadays, gully erosion is known as one of the most destructive types of erosion in agricultural lands and natural resources in the world such that it has a significant share of scientific research. Although soil erosion is a natural process, human activities in the past decades have greatly accelerated different types of erosion in nature. Gully erosion is the final and advanced stage of the erosion process, which, if not controlled, can cause huge damage to infrastructure as well as various agricultural parts, natural resources and environment, which either do not compensate for damage or if compensated, takes a long time in nature. In arid and semi-arid regions, due to certain conditions, the creation and development of gully erosion can make tremendous progress. Soil erosion in arid and semi-arid regions is one of the important consequences of climate change or is one of the consequences of environmental and ecological changes. Therefore, the purpose of this study is to rank the effective factors of morphometric erosion in creating gully erosion using statistical methods, as well as preparing gully erosion sensitivity map using maximum entropy model and its sensitivity in arid and semi-arid regions in arid and semi-arid provinces such as Kerman, which in turn provides valuable information on how to create and develop gully erosion in these areas.

In this study, 79 gullies were identified in Sarab Halil watershed in Kerman province. Then, 15 morphometric information layers were obtained along with gullies distribution map and PCA statistical Analysis was used to determine the most important factors affecting morphometric and finally, the map of gully erosion zoning was obtained using entropy maximum model for morphometric factors. In addition, MaxEnt model is a general model that allows users to evaluate the relationships between a dependent variable and several independent variables in different study contexts. The maximum entropy model based on the principle of entropy specifies the network of connections between dependent and independent variables and are obtained based on the role of each independent variable, its influencing weight, and its response curves. Entropy indicates the degree of uncertainty of the unbalanced distribution of the existing phenomena from the expected information content. Entropy method has been used in various fields such as mathematics, computer and economics in Iran and the world, but it has been used less commonly in geomorphology. In addition, Jackknife test was used to determine the importance of morphometric variables and the area under the curve criterion and acceptor performance specific curve were used to evaluate the accuracy of the model. The graph of the acceptor performance specific curve expresses the presence of the prediction against the accuracy of the absence of the forecast. If the amount of the area under the curve falls between 0.7 and 0.8, the model is considered good, and if the area under the curve ranges from 0.8 to 0.9, the model is considered very good, and if the amount of the area under the curve is more than 0.9, it is considered an excellent model. Meanwhile, the area index under the curve in receiver factor is equal to the probability of correctly distinguishing between the points of presence and absence by a model.

Gully erosion is one of the most important types of erosion in different climates of the planet, which causes widespread destruction and since it is very scattered in watershed areas, predicting its occurrence with low research costs is very important. The use of morphometric factors in this research, in addition to having low research and field costs, showed that the desired and acceptable results can be achieved without the use of other factors that have higher cost. Map of gully erosion prone areas obtained from entropy maximum model using morphometric factors in the study area showed that gully erosion in northeast, east and south is more likely to gully erosion between 0 and 31%, but in the east of the watershed and southeast, the gully erosion increases slightly and reaches the probability of 92%, but the percentage of the area is very low. However, towards the center, north, northwest, west and southwest of the study area, the probability of gully erosion increases and reaches 92% and sometimes in some parts up to 100%.

The results showed that in the occurrence of gully erosion, the morphometric factors of plan curvature, profile curvature, topographic wetness index, vertical distance to channel network, altitude, and length - slope factor, slope and earth's surface texture are effective in creating the gully erosion.

Extended AbstractIntroductionRepresentation of natural phenomena through hydrological models is very important for planning and management of water resources, because these models provide the possibility of investigating natural processes and evaluating modeling in different designs and are of great importance in management decisions. Hydrological models are a simplified representation of the real hydrological system, which help to study the functioning of the basin in response to various inputs and to understand the hydrological processes better. Considering the diversity of hydrological models, it is difficult to choose each model for each task, and there is a need for a comparative evaluation of models to determine the capability each model in the study area. Choosing a model from complex models that require many inputs and are difficult to work with or simple models that are easy to work with is considered important for water resource planners. Also, knowing the accuracy of the models in the simulation process is important and requires investigation. In this study, two hydrological models, MISDc and GR4J, were used to simulate the flow of Cham Anjir watershed. The results of the models show that both models have an acceptable ability to simulate the flow of the studied area, but the MISDc model has a higher ability to simulate the flow, and this model can simulate the peak discharges better than the GR4j model. The advantage of these models is that they are free and the data of these models are few and available. In this research, the efficiency of MISDc and GR4j models was evaluated. The basic data used includes observational data of temperature, precipitation, discharge, and evaporation and transpiration in the period 2008-2020 from 3 selected stations in the region and its surroundings. The required data of MISDc model are: daily data of precipitation, temperature and discharge, and the required data of GR4J include daily data of precipitation, evaporation and transpiration, and discharge. The data were given to the models after preparation in MATLAB software, and each model was executed separately. The model performance evaluation process is of fundamental importance during the model development and calibration process. Various indicators are presented and used to evaluate the models. The performance evaluation of two models was investigated through NS and R2 methods. In order to check the performance of the two models in the period of 2008-2020, data was prepared. In order to recalibrate the models, a 9-year period was determined and to check the validity of the models, a 4-year period was determined. After entering the data into the MATLAB software for the purpose of simulation, the parameters of the models were changed manually to obtain the most appropriate values ​​and the calibration stage was performed. Next, in the validation phase, the models optimal parameters were fixed, the new statistical period for the model was defined, and the model was implemented. Examining the performance of the two models during the calibration and validation stages shows the good performance of the two models in simulating the daily flow of Cham Anjir basin. The results of Nash coefficients evaluation and determination in the calibration stage for the MISDc model are 0.699 and 0.717, respectively, and for the GR4j model are 0.54 and 0.597 respectively. The results of the validation stage for the MISDc model are 0.794 and 0.851 respectively, and for the GR4j model are 0.70 and 0.715, respectively. These results show that the MISDc model performs better than the GR4j model. The MISDc model has been able to simulate the daily flow of the studied area well, especially in the peak discharges, and the GR4j model, due to its good simulation, has not been able to estimate the peak discharges as well as the previous model. In this research, to evaluate the performance of two MISDc and GR4j models in simulating the runoff of Cham Anjir basin, the data of precipitation, temperature, evaporation and transpiration, and discharge were used in the statistical period of 2008-2020. Then, the stage of data calibration, validation, and evaluation of the model's performance was carried out and examined. The results of the investigations show the good performance of the two models and the relative superiority of the MISDc model to the GR4j model. The results obtained in this research are close to the results of research conducted in different places, so according to the results obtained from the models, it can be said that the models can be used in the studies of water resources in the region, and it is also suggested that the models be used for estimation of runoff in similar areas.