نشریه هیدروژیومورفولوژی
پیاپی 29 (زمستان 1400)

The common method of supplying water for agricultural purposes is flood irrigation used in semi-dry areas from past times. Flood utilization has long been one of the common water supply methods among farmers in dry areas of the world due to inaccessibility to sustainable surface or underground water resources. In North America, Indians have used simple flood irrigation methods for centuries (Hudson, 1975). The studied area is located at 110km from the center of the province, north of Uremia Lake and the drainage basin surrounding Tasoj city at 45°18' to 45°33' eastern longitude 38°20' to 38°24' northern latitude. The area includes ten sub-basins overlooking the city of Tasuj and the villages of Angashtjan and Amstajan, and its area is 9616.79 ha. The average height of the area is 1700m with an average rain of 271mm in 20 years and an average annual temperature of 13.4°C. The region is climatically affected by polar air from the north, polar sea from the northwest, tropical climate from the south. The region's climate is cold semi-arid, and the rainfall regime is in the Mediterranean. The main feature of this regime is intense rainfall, spring rainfalls, and intense snowing in winters, along with several months of drought in summer and late spring. The land use of this region includes farming gardens 938ha, irrigated aquaculture 2050ha, and dry farming 420ha. The cultivation pattern of farms and gardens mostly includes apple, walnut, Elaeagnus Angustifolia, almond, cherries and alfalfa, wheat, barley, and chickpeas that are the farming lands with aridity problems. Angoshtjan and Amstejan ponds and watersheds have two U.R.F upper Miocene geologic formations and the equivalent formations of Qom with marl, limestone, and sandstone deposits that produce high sedimentary floods (Habibzadeh, 2018). One of the main objectives of flood distribution projects is the improvement of the status of natural resources in flooding plains on the alluvial fans of the outflow of the problematic watershed, the storage of precipitation, supply of underground sources, supply of required water for crop and farming, quantitative and qualitative changes of vegetation, changes in plant composition and increase of plants for feeding and increase of soil fertility. Lashanizand et al. (2010) studied the changes in surface water quality of Kashkan basin due to periods of water scarcity and watery and for this purpose, 12 parameters of water quality and discharge statistics of eight hydrometric stations in 30 years and concluded qualitative changes from The ascending and descending trends follow the periods of watery and aridity. The purpose of this study, while presenting a qualitative analytical method of floods, is to use floods in agricultural water supply in the agricultural plains north of Lake Urmia.

The research project investigating the effects of incoming flood quality on flood spreading performance was carried out by the author to create model areas for flood exploitation for agriculture, promotion, and development of flood distribution systems in arid and semi-arid regions. Samplers were installed along the flood paths of the Angoshtjan and Amstejan sub-basins at the entrance of the plain and in three locations of impoundment system, above and below these systems with gages. After the installation of samplers, the flood sampling was done to this end, sampling was performed three times in 2011, two times in 2012 and one time in 2014; the number of samples to be taken was determined based on the flood discharge and the height of samplers and sent to the laboratory for analysis. The results related to the differentiation of the sampling location have been classified using Model and Wilcox diagram (Habibzadeh, 2017).

The main limitation in agriculture, especially in arid and semi-arid regions, is the supply of water needs. In such areas, water is the basis for planning for agricultural development. Every year, much water flows out of reach in the form of runoff or floods and causes much damage to agricultural lands, residential lands, and roads (Mesbah and Negahdar, 2015). According to the purpose of the research, it was necessary to prepare information about the amount of rainfall and floods in the region. For this purpose, the amount of flood extraction was calculated and collected based on 20-year statistics of rainfall and floods in the region. The average monthly rainfall and flood storage are shown in Table 1. Flood samples were sent to the laboratory for qualitative analysis during six floods over three years. Laboratory analyzes including salinity, acidity, anions, and flood cations were performed. The lowest salinity, or EC, is related to the flood of the Amstajan river with 345 μm /cm, and the highest is related to the flood of the Angoshtjan river with 799μm / cm.

In this project, to access the 2.5 million m3 outflow flood of Amstejan and Angoshtjan villages, the qualitative analyses of flood samples have been done based on Wilcox, Piper, and Stiff hydro-chemical diagrams. The mean electric conductivity in Amstejan sub-basin floods is 350mho/cm, and for Angoshtjan, the sub-basin is 600 mho/cm. The floods have relatively alkali acidity or neutral. The highest values, 8.06 and 8.04, are related to the inflow flood of the reservoir of flood collection. The quality of floods in terms of irrigation water classification of Wilcox method, where salinity and sodium rate are the most important criteria, is mostly in the C2S1 area. In terms of classification of irrigation water, C2, water with medium salinity that can be used for plants with medium tolerance to salinity, S1 is low sodium water which is good for irrigation of all types of soils and is not risky; therefore, they are good waters for agricultural purposes.

The drop in water level in the aquifers of Kermanshah province has been so severe that it has reached about 10 meters in some places. The purpose of this study is to evaluate GRACE satellite data to estimate the groundwater storage of Ravansar aquifer in Kermanshah province. Therefore, in this study, while examining the water level of Ravansar aquifer observation wells and also the spatial zoning of these changes, the current situation of the region was evaluated using Kriging method in GIS software. Then, in order to evaluate the GRACE satellite data, the JPL, GFS, CSR, and CRI algorithms were coded in Google Earth Engine cloud computing environment, and then the monthly and annual changes of liquid water Equivalent (LWE) were calculated. Also, the amount of Soil Moisture (SM) was estimated from the GLDAS hydrological model and by subtracting the amount of soil moisture from the estimated values of GRACE , the amount of changes in groundwater storage compared to its observational values was obtained. This study showed that not only can GRACE data be used to estimate the rate of changes in groundwater storage in aquifers, but also the data are of acceptable accuracy. Comparison of the results of different algorithms showed that the JP algorithm with a correlation coefficient of 0.73 has the highest correlation with observational data. According to the JPL , the values of changes in groundwater storage estimated from GRACE compared to the observed values show a decrease in groundwater storage of -1.8 cm.

Today, the preparation of land use maps using remote sensing data is one of the most important methods for producing land use maps and land use assessment together. Lack of proper infrastructure, non-observance of land development capability in selecting land uses and its unprincipled management leads to the phenomenon of soil erosion. The purpose of this study is to prepare land use maps using object-oriented method and to prepare soil zoning maps of Zarrineh Rud catchment for 2000 and 2018 Landsat satellite using WLC method. The results showed the detection of changes from object-oriented classification The highest rate of change in rainfed and irrigated agricultural land uses has been faced with the largest increase in area in the region. The trend of changes in barren land uses, rich and medium rangeland, has been decreasing over time, so that the area has decreased by 14.04, 10.66 and 5.73 percent, respectively. Man-made use has been increasing almost uniformly over time, which has grown by 2.47% over 18 years. The results obtained from the erosion zoning maps produced in 2000 and 2018 showed that there are two very high-risk and high-risk classes, each covering 15.29 and 27.51 percent of the area. These classes are mostly located in rainfed, irrigated, barren and medium range agricultural uses.

Today, hybrid models of artificial intelligence are considered as a suitable method for simulating hydrological phenomena, including quantitative estimation of river flow. For this purpose, there are various approaches in hydrology to estimate the flow rate of rivers, of which artificial intelligence models are the most important. Therefore, in this study, the performance of support vector-wavelet regression, backup vector-gray wolf regression and bat-support vector regression models to simulate the flow of Kashkan river located in Lorestan province during the statistical period of 2010-2011 in the daily time scale were analyzed. The criteria of correlation coefficient, root mean square error and mean absolute value of error and bias were selected for evaluation and performance of the models. The results showed that the hybrid models have acceptable results in simulating the river discharge. Comparison of models also showed that the support-wavelet vector regression model in the validation stage showed values ​​of R2 = 0.960, RMSE = 0.045, MAE = 0.024, NS = 0.968 and BIAS = 0.001 in predicting daily river flow. . Overall, the results showed that the use of hybrid support-wavelet regression model can be useful in predicting daily discharge.

In the Drastic model, the vulnerability index was obtained from 57 to 165, which is in the descriptive division into classes without risk to high risk of pollution, which if we consider three classes without risk of pollution to low pollution, we can say 44% of the total area of the plain is located on these three classes. Also, three classes of low to high, occupy 46% of the plain area. In fuzzy modeling, after scaling and overlapping seven input layers, we prepared the final map, which according to the index of this modeling, 47% of the total area of the plain has high vulnerability, that the result obtained is very similar to the result of DRASTIC method, but by comparing the two methods, it becomes clear that the fuzzy model is more accurate than the drastic method. In both maps, the northwestern to southwestern parts where the city of Tabriz is located, have the highest potential for pollution and the southwestern parts, which include the Sahand Mountains, have the lowest potential for pollution. Finally, using GQI index and according to drinking standard WHO and using ten parameters: hydraulic conductivity, chlorine, calcium, bicarbonate, magnesium, potassium, total soluble solids, sodium, sulfate and total hardness which are taken from wells in the plain, In high-risk areas, due to the high percentage of total soluble solids, total hardness and high hydraulic conductivity, water quality has also decreased and descriptively, the water quality of Tabriz plain is in the acceptable to appropriate range.

Sedimentation is one of the most important issues in the watershed. Due to the problems caused by sediment, it is necessary to investigate the relationship between hydrogeomorphic variables affecting sediment production and suspended sediment load in the watershed. The purpose of this study is to model the relationship between suspended sediment loads with hydrogeomorphic variables of the basin and to extract geomorphic features and their relationship with sedimentation in the watershed. By simple random method, two cows and conifers, which include 8 specific sub-basins and are equipped with hydrometric stations, were selected. Statistical multivariate regression method was used to analyze the relationship between geomorphic variables with sedimentation of each sub-basin. The results of the study of the relationship between geomorphic characteristics and sedimentation of sub-basins showed that the amount of sediment produced was positively correlated with slope index, roundness, drainage texture, rainfall, unevenness and basin area and was significant at the level of 0.001. In order to influence the variables on the sedimentation rate of the sub-basins, the principal component analysis and cluster analysis methods were used. The results showed that the three factors of roundness coefficient, slope coefficient and drainage texture coefficient of the basin explain 44.62, 25.22 and 16.74% of the variance of all research variables, respectively. In total, the three final extracted factors were able to explain 87% of the variance of all research variables.

Hajilar chai basin located in the western part of varzegan and it may expose to potential of water resources contamination due to placement of Zarrin Dagh Astarkan gold extraction factory in this area. In order to monitor the water sources of the Hajilar chai basin, 12 water samples collected and analyzed in March 2021. The results showed that the concentration of Co, Pb and As are higher than permissible limit of WHO standard for drinking water in some places and probably the source of trace element related to geological formations and water rock interaction. The aim of this study is to evaluate the hydrchemical characteristics and source of contamination of water sources using graphical methods, multivariate statistical techniques such as factor analysis and hierarchical cluster analysis. The result of the graphical methods showed that the most of the water samples have bicarbonate calcium dominate type. The result of the factor analysis show that four factors were affecting the quality of water source. The first, third and fourth components result from affecting of formation on water resources and water rock interaction. The second component show evidences of the anthropogenic activities in the study area. Also, hierarchical cluster analysis classifies the data into three categories. The first cluster data have similar geochemical process and less trace element. In second cluster hydrochemcial equilibrium is not established, which is probably due to the impact of factory activities. In third cluster, the concentration of arsenic is high and probably is originated from geological formation.

Irregular abstraction of groundwater aquifers in the country has caused a sharp decline in the aquifer water level and the destruction of aquatic aquifers. In this study, in order to investigate the groundwater level of Marvdasht-Kharameh aquifer, located in Fars province, in relation to the uncontrolled abstraction of groundwater from the data of 81 piezometric wells in the period (2018-2018), the Modflow model was simulated. Also, the results of calculating the water balance of 7,500 wells in the basin indicate that the amount of 1100 million cubic meters of water from the aquifer constant storage has been reduced over a period of 10 years. According to the prepared interpolation maps, the highest rate of groundwater loss has occurred in Dorodzan, Ramjerd and Shool areas. Therefore, it is in line with the statistics of the Fars Regional Water Organization that there are wells with high discharge in these areas. According to the maps prepared from Marvdasht aquifer, due to the alluvial nature of the groundwater aquifer, the effect of water level drop can be observed from a short distance. On the other hand, in the intermediate maps, the coefficient of hydraulic conductivity parameter indicates that the rate of aquifer drop in the northwest, center and southeast of the basin has the highest value, which is appropriate with 11% relative error confirms modeling. Finally, by performing two scenarios of 10 and 30% reduction,

Estimation of flood hydrographs in the ungauged watersheds is a challenging issue in flood planning and management. Various models have been developed in this filed and it is necessary to evaluate the performance of models developed in different regions of the world with different climatic, hydrological and physiographic features in order to comment on their performance in different regions. The Gamma synthetic unit hydrograph model is a developed model for estimating flood hydrographs in the ungauged watersheds with limited studies in the world. In this study, the Gamma synthetic unit hydrograph model for estimating flood hydrograph characteristics in Qareh-Sou watershed located in Kermanshah province in Iran has been investigated. Criteria for percentage error in peak discharge, percentage error in volume, mean absolute error, mean bias error, coefficient of determination and Kling-Gupta were estimated to evaluate the accuracy of simulation results. Based on the results, the mean values of the criteria expressed are 6.28, 17.4, 0.89, 0.54, 0.74 and 0.75, respectively, indicating that the Gamma synthetic unit hydrograph model is quite accurate in estimating the characteristics of the flood hydrograph in this study. In addition, the visual comparison of computational and observational hydrographs illustrates the remarkable accuracy of the Gamma synthetic unit hydrograph model in estimating the shape of flood hydrographs in the studied events.

Flood is one of the natural phenomena that causes a lot of human and financial losses in the world every year and creates many problems for the economic and social development of countries. Therefore, in order to reduce the damage, control and guidance of this phenomenon, estimating flood discharge and identifying the factors affecting it is very important. In this study, in order to estimate the flood discharge of Kashkan catchment located in Lorestan province, new hybrid artificial intelligence models including artificial neural network - innovative gunner, artificial neural network - black widow spider and artificial neural network - chicken crowding during the period 1300-1400 were used. To evaluate the simulation performance, statistical indices of determination coefficient (R2), absolute mean error (MAE), Nash-Sutcliffe productivity coefficient (NSE), bias percentage (PBIAS) were used. The results showed that hybrid artificial intelligence models improve the performance of the single model. The results showed that the artificial neural network- innovative gunner model has more accuracy and less error than other models. Overall, the results showed that the use of hybrid artificial intelligence models is effective in estimating flood discharge and can be considered as a suitable and rapid solution in water resources management.