مجله علوم و مهندسی آبخیزداری ایران
پیاپی 54 (پاییز 1400)

The mechanism of land subsidence and soil deformation is the dissipation of the excess pore water pressure and the compaction of the soil skeleton under the effect of natural or man-made factors. Land subsidence has occurred in more of 300 plains of Iran, and Semnan Plain is one of the most important areas that face to this phenomenon. The aim of current research was land subsidence susceptibility mapping using GLM and FDA models. At first acquiring information about the land subsidence occurred in the past was done. Locations of the land subsidence were specified using Landsat 8 satellite images and field surveys. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess accuracy of the models. The AUC for the GLM and FDA models was 0.657 and 0.618 respectively. Results of accuracy assessment show that accuracy of these models is located into the moderate class for land subsidence susceptibility mapping in the Semnan Plain. The research results can provide a basis for the protection of natural resources and environment and also promote the sustainable development of economy and society.

Climate change along with human interventions has changed natural hydrological cycle and consequently the need for more water resources, timely supply of water needs has faced serious challenges. Estimation of basal flow index has been one of the important issues in hydrology. In order to analyze the minimum flows in this study, 12 hydrometric stations with a statistical period of 30 years in northwestern Iran were selected due to the presence of Lake Urmia and then the annual minimum flow series were calculated with continuities of 3, 5, 7, 15 and 30 days. Based on the goodness-of-fit test of Kolmogorov-Smirnov, among the various distributions of the Wakeby distribution and based on Mann-Kendall test 66.67 Percent have a decreasing trend of minimum flow, based on Pettit 75 Percent of the studied stations have an increasing trend of minimum flow and according to Phenomenon test, 41.67 Percent of the stations have a minimum increasing trend of 95 Percent with different continuities. The results can be useful for having an accurate plan for the amount of water consumed and sustainable management of water resources in arid and semi-arid regions.

In the present study, the ARC SWAT model in ARC GIS software was used to model the Zolachai watershed in the city of Salmas (Chehric Alia). For sensitivity analysis, calibration, SPSS statistical software was used. In the model used from precipitation data, minimum temperature, maximum temperature and daily relative humidity of rain gauge and synoptic stations in the study area for 35 years (1984 to 2019), for five statistical periods of 7 years, for April, October and November used. To calibrate the ARC SWAT model in SPSS statistical software, indices of uncertainty, coefficient of determination, standard deviation, significance level and Fisher-in-law coefficient were used. The results of the uncertainty index for April, October and November were 0.8, 0.30 and 0.5 percent, respectively, and the watershed determination coefficient index for these three months was 0.0114, 0.5788 and 0.1551, respectively. Showed the percentage the standard deviation index was 0.97 percent for April, 07.07 percent for October and 1.09 percent for November. Significance level index for these three months showed 0.87 percent Fisher Sandkor coefficient as one of the important indicators of watershed validation for each quarter showed a number of 0.91 percent.

Soils are severely damaged by acid rain; acid rain also leads to excessive dissolving of minerals and valuable nutrients in the soil, which weakens vegetation. In this study, in order to determine the interaction effect between the slope aspect and precipitation intensity relative to acid rainfall in the Aghajari and Gachsaran formations, a part of Margha and Kuhe Gach watersheds of Izeh city with an area of 1609 and 1202 hectares were selected. A sampling of runoff and sediment was done in 16 points with three replicates in northern, southern, eastern, and western aspects of Aghajari and Gachsaran formations at different rainfall intensity of 1 and 1.25 mm/min and in distilled water, acidity 4 and 5 using Kamphorst rain simulator. The results showed that in both Gachsaran and Aghajari formations, rainfall intensity has the highest effect on runoff and sediment production in three concentrations of precipitation and also The interaction effect between precipitation intensity and slope aspect plays the least effect on in runoff and sediment production, and in Gachsaran and Aghajari formations, a runoff was much more sensitive to sediment production than the interaction effect between slope aspect and precipitation intensity.

Runoff create problems like erosion, flood and etc. Withe Assessment of the watershed we can identify the areas that have a potential for flood. And control operations taking only in those area. In this regard, identification areas with high potential for runoff for flood controls is great importance. Here, two major objectives have been considered: 1. evaluation Modclark model in simulation of runoff, 2. determine the potential distribution and sub-basin runoff in Ekbatan dam basin. For this purpose, first Modelark model inputs were extracted using the software ArcGIS then the model was run. The model was calibrated with two events and was validated with an event. The next step is to determine the potential for runoff of homogeneous units (combine the layer of slope, landaus, soil hydrology group and distance to basin output) for implementation of flood response, extracted 50-year return period then we achieved the impact of each unit in basin water output. The results showed this model have accuracy in estimating the flood volume and peak flow based on statistical profile relative error of floods, peak, time base and time to peak. Also, the potential for runoff in the downstream to the upstream areas of homogeneous units has been increased.

The aim of this study was to determine the areas sensitive to gully erosion and prioritize the factors affecting it in Kermanshah province, using the maximum entropy method (MaxEnt model). 9 factors affecting gully erosion potential in the area Including Elevation, Slope, Slope Direction, Lithology, Land Use, Topographic Moisture Index, Surface Curvature, Drainage Density and RSP was reviewed. Of the total gullies studied in the study, 70 percent were randomly classified as test data and 30 percent as validation data. To determine the most important parameters, the Jackknife diagram and the relative performance detection curve ROC were used to predict the model. The results showed that there is no alignment between the factors used. According to the Jackknife diagram, the lithological layers, slope, height and  drainage density were the most important factors influencing the susceptibility of gully erosion, respectively. ROC curve showed 91percent accuracy of the maximum entropy method in the training phase and 72 percent in the validation phase. According to the moat susceptibility zoning map, about 23.39 percent of the area has low sensitivity, 48.14 percent very low, 9.31percent high and 4.71percent very high and 14.46 percent has moderate sensitivity.