نشریه پژوهش های آبخیزداری
پیاپی 135 (تابستان 1401)

Gully erosion is one of the most important types of water erosion, which has a great role in the destruction of land production capacity due to intra-regional and extra-regional effects. Preparing a spatial map of the possibility of gully erosion for better management of land use with the aim of reducing land degradation in areas prone to gully occurrence is very efficient. The distribution of this erosion in Iran and the extent of factors and processes affecting its creation have been a major obstacle in creating a comprehensive model for predicting its occurrence on a large scale. The purpose of this study is to prepare a map of the probability of gully erosion using the machine learning model of maximum entropy in Fars province. In this research, it has been tried to use variables related to terrestrial characteristics, especially soil. According to the results, the area under the ROC curve is above 90%, which shows that the model has been able to evaluate the gully erosion in the study area using the studied data. According to the results of the Jaknaev test, the variables of R horizon probability, soil depth, percentage of coarse grains, pH, and silt particles have the greatest impact on modeling moat erosion in the study area. The spatial distribution map of the occurrence of the gully is a map of land susceptibility to gully erosion. Based on the findings, the highest sensitivity to gully erosion is related to the south of Fars province. The map prepared in this research can be used as a basic map for land management, managers and engineers of urban planning, road construction, natural resources, and agriculture.

Investigation of floods as one of the most common natural destructive phenomena is very important. Due to the problem of deficiency and defect of hydraulic data in most hydrometric stations in the country, flood hydrograph simulation by hydrological and hydraulic models is helpful. There are several hydrological and hydraulic models to simulate flood hydrographs. The present study has investigated the performance of Advection-Diffusion relationships of 36 flood phenomena in 5 study reaches of Kashkan river and its tributary. Physical properties related to the studied periods and hydrometery data related to each flood phenomenon, including discharge and scale of the input and output station, were used to determine the Manning roughness coefficient and flood simulation. Evaluation of obtained hydrographs indicates the acceptable accuracy of the model in term of simulating values of flood trends and discharge. In order to evaluate the accuracy of the model results, different coefficients such as: Nash-Sutcliffe, RMSE, Volumetric Efficiency, Kling-Gupta and R correlation coefficient were calculated. A value above 0.5 for the Nash-Sutcliffe coefficient in 29 flood phenomena out of 36 studied phenomena, and an acceptable range of other coefficients for all studied flood phenomena, indicates the verifiable results of flood hydrograph simulation using simplified propagation methods at reach scale for studied watershed. Therefore, Advection-Diffusion relationships can be used in similar watersheds to the study area to simulate floods.

Groundwater samples were prepared from 20 wells in the Gareh Bygone aquifer during the 2018 to 2020 years seasonally. Chemical characteristics of these samples including EC, pH, TDS, TH, SAR, SO4-2, Cl-, Na+, K+, Mg+2, Ca2+ and HCO3- were analyzed. The average of water salinity was 4.7dS/m, the acidity was 7.5, the average SAR value is about 6.7 and in some wells, this factor is about 10.6. Analysis of variance shows that all chemical characteristics except HCO3- have a significant difference. The principal component analysis identifies TDS, SO4-2, HCO3- and Na as the most effective variables in reflecting groundwater quality. Factor analysis also shows high TH, Na+, and HCO3-. Aquifer water resources are divided into three separate groups. The first group (with 97% similarity) receives the most impact from floodwater spreading and artificial recharge, and the other two groups (with 93 and 70% similarity) are located in the marginal areas or outside the floodwater spreading system. Despite poor management and uncontrolled discharge of the aquifer, at least in the central parts of the aquifer, which are more affected by artificial recharge by floodwater spreading, groundwater quality is more desirable.

This study was conducted with the aim of understanding the temporal and spatial variations of groundwater levels in the Meshgin Plain Aquifer, located in Ardabil Province, with the application of spatial statistics and temporal regression and using groundwater depth data on an annual scale from 2007 to 2016. In order to achieve the optimal method of zoning spatial changes in groundwater level, a comparison of different interpolation methods including Radial Basis Functions (RBFs), Inverse Distance Weighted (IDW), and Kriging (KRG) based on cross-validation was used. In addition, regression relationships between groundwater level and the study years were fitted to determine how the data series ascended or descended. A comparison of interpolation methods based on cross-validation showed that the root mean square error (RMSE) of RBF, IDW, and KRG methods were 21.98, 22.85, 22.57 in 2007; and 23.45, 27.88, 26.25 in 2016, respectively. Therefore, the RBF method with the lowest estimation error due to the power applied to scattered data and low sampling points in both years was selected as the optimal method for estimation of groundwater level in the aquifer. The weighted average of groundwater table loss was calculated as equal to nine meters. Furthermore, the iso-decline map of groundwater level was indicative of a decrease in groundwater level in the western half and its increase in the eastern half of the aquifer which is related to anthropogenic factors (withdrawal of groundwater in agricultural lands). In general, it can be stated that the accuracy and efficiency of interpolation methods depend on the region and data characteristics. In the case of Meshgin Plain Aquifer, the discharge factor has been more effective than the recharge factor in annual fluctuations of groundwater level. Accordingly, it is necessary to establish a balance between the pattern of cultivation and irrigation and the pattern of spatio-temporal variations of groundwater level in managerial plans for Meshgin Plain Aquifer.

The most important goal of watershed management is soil and water conservation, flood reduction, and vegetation enhancement. Analyzing and evaluating the performance of watershed management measures, like other development projects, seems necessary for their economic justification. In this study, in order to evaluate the effectiveness of watershed management measures in Manojan city, Kerman. Quantitative methods include double mass curve, flow continuity curve, and hydrological regime. Qualitative methods include face-to-face interviews and completing a questionnaire. Also, the economic evaluation of these projects was performed using two criteria of net present value (NPW or NPV) and profit to cost ratio (B/C). For this purpose, data related to rainfall and runoff in the years before and after the implementation of the place, and questionnaires were collected and analyzed using Excel and SPSS software. The results showed that the double mass curve shows the positive effect of watershed management on decreasing runoff rate and the current continuity curve shows the relaxation of the flow and the effect of these measures in reducing peak discharges. Qualitative results also indicate that 80.58% of people in the region believe that watershed management measures had positive effects and 19.42 no positive effects. According to NPW and B/C criteria, watershed management measures implemented in Manojan city have economic justification and have a positive economic impact. In general, the positive effectiveness of watershed management measures in soil and water protection in the study area has been confirmed qualitatively and quantitatively.

Given Iran's location in the dry belt of the world and the lack of a comprehensive and accurate assessment of water security in the country, the study of variability in this category as one of the important dimensions of national security to develop appropriate management models seems important and inevitable. The present study aims to investigate and evaluate the water security in the large watershed of Central Plateau due to its large size and high population in terms of eight important sub-indicators including per capita renewable water resources, the intensity of water use, water productivity, investment in water infrastructure, water quality, access to drinking water and water pollution management, green cover changes and changes in large water bodies were established and implemented over a 20-years with 5-year intervals (1996 to 2016). The calculated values ​​for water security are 0.356, 0.330, 0.363, 0.291, and 0.291 respectively for 1996, 2001, 2006, 2011, and 2016 and the average during the twenty years of research was 0.326 units. The results also show that per capita renewable water resources and index of water use have the greatest impact on water security based on the prioritization of factors affecting water security. It is necessary to establish sustainable management of water resources while taking into account political, social, and economic requirements and paying attention to the issue of water security by the executive and legislative bodies in order to promote national security to establish a proper balance in the use of water resources and water security and Consequently, national security will be improved.

Climate change in lakes and reservoirs is one of the most critical issues facing human society today. Rising temperatures, melting ice in the North Pole, and the disappearance of ice sheets in Antarctica are some of the effects of climate change on earth. The present study intends to evaluate the trend of climate parameter changes in Abadeh Tashk station in Tashk catchment area using the Mann-Kendall test and using canESM2 output, one of the paired climate change models 1CMIP5 based on RCP 2.6 scenarios. And RCP4.5 and RCP8.5 to evaluate temperature changes in the period 1990-2020-2100 temperature changes in Abadeh Tashk station. The results showed that the decreasing trend of precipitation is significant but the temperature and evaporation trends are not significant. Scenario results showed that the average maximum temperature in the three scenarios for the study period will increase. Given that the general trend of rising temperatures is on the rise, it can be said that the trend of climate change in the basin is serious.

Landslide, as one of the most important natural hazards, causes financial losses and destruction of natural resources, every year. Rabar area, located upstream of Halilrood watershed, is prone to landslides due to the presence of marl formations and hence, a high amount of sediment has entered the Safa reservoir in Rabar city. Therefore, the purpose of this study is to zone this environmental hazard using convolutional neural network (CNN), support vector machine (SVM) and evidential belief function (EBF) models in Rabor region. To achieve this purpose, the parameters of altitude, slope, and distance from the fault, geology, land use, soil type, Normalized Difference Vegetation Index, and distance from the river were used. Then, using the data of the Geological Survey of Iran and field observations using GPS, a landslide distribution map was prepared as a dependent variable. There were 70 landslides, 49 (70%) of which were used for simulating and 21 (30%) for model validation. The results obtained from the validation of the models using the ROC showed that the AUC values for CNN, SVM and EBF models were 0.987, 0.958 and 0.899, respectively. Overall, the results showed a satisfactory correlation between the landslide data available in the area and the landslide susceptibility maps and the deep learning model of  the convolutional neural network had a higher performance compared with the other two models. Finally, the landslide susceptibility map was classified into four classes: low, medium, high, and very high susceptibility. According to the results of all models; the central, southeastern, and southwestern parts of the study area have a high and very high landslide risk. Carrying out appropriate designs such as retaining walls, preventing water infiltration, appropriate drainage, planting vegetation suitable for the environment, and landslide-prone slopes and etc can be appropriate in preventing and controlling this hazard.