مجله اکو هیدرولوژی
سال چهارم شماره 2 (تابستان 1396)

Water resources has been experienced serious tensions in recent years due to climate change. Purpose of this study is investigation of dynamical and statistical downscaling in order to downscaling extreme precipitation in catchment of Gorganrood river over 13 and 14 may 1992 that Leading to record the extreme discharge in this region. Two model namely SDSM and Regcm4 for his purpose were used. The results showed SDSM has very low ability to simulate extreme precipitation so that the mean absolute error (MAE) was about 20 mm in the years 1983-2012 with very low coefficients of determination of 0.18 to 0.002 whereas Regcm4 model has recorded a very high coefficient of determination and mean absolute error of the model was about 67 mm. Although this model could not well simulate of Lazoreh station precipitation, because the model taking into account the overall dynamic patterns to simulate. Weather maps analysis indicates that Low pressure patterns dominant in the western half and parts of South and Central Iran in this two-days. Direction South and West Stream was observed from Adan sea and the Persian Gulf as well as the Black Sea and the Mediterranean Sea. Geopotential Maps show low-height patterns be in level 500 Geopotential high and n level 850 Geopotential high in this region.

In the recent years, the dependence structure among hydrological variables is taken into consideration and it led to employ the multivariate analysis as a suitable alternative for univariate methods. In this study, the copula functions were employed for multivariate frequency analysis of low flows of Dez River basin at Tange Panj-Bakhtiari (TPB) and Tange Panj-Sezar (TPS) hydrometric stations. At the first, at first 7-d series of low flow was extracted from measured daily flows at the studied stations in the period of 1956-2012. In the next stage, 11 different distribution functions were fitted onto the low flow data which logistic distribution had the best fit on the TPB station and the GEV distribution had the best fit on the low flow data of TPS station. After specifying the best fitted marginal distributions, the copula parameter should be estimated. In this study, two methods of inference function for margins (IFM) and particle swarm optimization (PSO) were used to estimate copula parameter. The results showed that the PSO method had outperform than IFM in estimating the copula parameter. Among the Ali - Mikhail – Haq, Clayton, Frank, Galambos and Gumbel-Hougaard copulas, the Frank copula function had lowest error and highest accuracy in constructing the joint distribution of paired 7-d low flows data and was used for calculating the joint return periods in two states of “OR” and “AND”.

Estimation of discharge using regional analysis is an effective method for water resources management in ungauged basins. In the present study, for the purpose of estimating annual discharge in the ungauged sub-basins of Hablehroud Basin, linear regression and three independent variables including area, precipitation and slope were used. The basin under study was divided into five major and 44 minor sub-basins and using the data from five active hydrometric stations in the basin, regression equations for estimating annual discharge and specific discharge (the ratio of discharge to basin area) were extracted. The extracted equations were assessed in both major and minor sub-basins. The results showed that discharge estimation using the three variables of area, precipitation and slope in the five major sub-basins has an average error of 1.3%. However, the average error in the 44 minor sub-basins was totally unacceptable. The results also showed that the average error of specific discharge estimation in the five major sub-basins is 2.6%. Despite the increase of error in the major sub-basins, the average error of specific discharge estimation in the 44 minor sub-basins was reduced to 5.33%. The results of the present study indicate that when the basin under study is divided into small sub-basins, specific discharge can be considered as an appropriate variable in regional analysis of runoff.

Leaf area index is one of the most important variables characterizing energy flux, atmosphere- land surface exchange and vegetation structure. In this research, Leaf area index time series of wheat, alfalfa, apple and potato have been investigated using the modeling with basis on Box-Jenkins method and with the result of mathematical relationships between leaf area index and NDVI were compared. The trend of MODIS time series in the period of 2012 to 2015 with seasonal length 46 using seasonal Man –Kendall test was negative. The simulation of time series using ARIMA (p,0,q)×(P,1,Q)46indicated the error decreasing and correlation and NASH coefficient for example the correlation coefficient of wheat, alfalfa, apple and potato was 0.9, 0.94,0.93 and 0.89 respectively. The criteria comparison demonstrated the better performance of SARIMA model especially for alfalfa and apple time series with high values of leaf area index. Stochastic modeling has minimum error relative to the mathematical relationships. According to the high performance of SARIMA model, the preparing of leaf area index time series with high precise has more importance.

Climate change is a major environmental problem because melting processes of the glaciers and snow packs are sensitive to climate change. The aim of this study, is predicting future changes in climatic parameters, estimating changes in snow covered area and snowmelt runoff under scenarios of climate change in Armand basin. To investigate the effect of climate on precipitation and temperature in Armand basin, Three models (NorESM1-M, IPSL-CM5A-LR and CSIRO-MK3.6.0) was used under the scenarios RCP8.5, RCP4.5, RCP2.6 were run, Temperature and precipitation in the next four periods (2021-2030, 2031- 2040, 2041-2050 and 2051-2060) under all three scenarios were calculated. As well as the daily images MODIS (Mod10A1) was used to determine the snow covered area in the basin. The relationship between the snow covered area with the observed temperature and precipitation was studied and has been used to predict future snow cover. The results showed that all three scenarios RCP predict rising temperature and reduced precipitation and snow cover. Studying of snowmelt runoff in the observation period (November 2000-May 2006) showed that about 47.7 of the annual runoff in the basin is related to snowmelt. Most snowmelt runoff during the winter has been created. The contribution of total water produced by melting snow during the fall and spring 34.9 and 52.8 percent respectively that Along with snowmelt, it is expected runoff will be reduced by about 0.12 cubic meters per second per year.

One of the important operations that optimize use of soil and water in the arid and semi-arid lands is soil and water conservation structures especially precipitation storage structures. Implementation of precipitation conservation such as the development of pitting and contour furrow has been suggested in fields including: that vegetation had decreased to the extent that had no role in the prevention of surface runoff but there are appropriate and palatable plant species individuals, soil compaction due to high traffic livestock has caused to decrease water infiltration into the soil, has done for controlling runoff and floods from rainfall with the aim of water saving and increasing of vegetation cover. This study was carried out in Bolbol rangeland of Yazd province to average rain fall of 130 mm since 2004 in surface of two hectares. The amount of vegetation and density species were measured in four and control, 7 years (2012) after the creation of mechanical operations of pitting and furrowing. Measurements were carried out along 12 transects and 120 plots. The results showed that pitting, contour furrow and control treatment sites had significant different from percentage vegetation and density (p

The assessment of river health can be used as a tool for environmental flow estimation and quantifying the amount, timing and required water flow quality to permanence of river ecosystems. The aim of present study is to determine the spatial and temporal changes of rivers health with an emphasis on hydrologic indicators by using statistical tests in Ardabil province. For this purpose, the daily discharge data of 24 hydrometric stations with the period of 1367-1390 used for river health analysis. In addition, the non-parametric Mann-Kendall test and Sen's estimator method were implemented to determine the presence or absence of positive and negative trends at different statistical levels. Also, after dividing the existed study span into four periods, the Kruskal–Wallis test was applied for the investigation of temporal variations and the existence of differences between short-term periods. Results showed the significant decreasing trend of river health in studied stations (13 stations from 24 stations). Sula and Firuzabad stations had significant increasing trend and in other remained stations the significant trend hadnt identified. According to the results obtained from the maps of spatial variability of river health maximum changing river health indicators in the central and minimum changing of the index observed the northern and southern parts of the province. In determines how it can be said that the changes hydrologic flow health in recent times than in the past can be related to increasing of exploitation intensity from surface water resources and reducing the water yield due to climate change.

In this study, the effects of hydro-geomorphology factors on the water quality changes of Siminehrood River and the process of these changes were studied at the different spatial and temporal scales. Data related to physical, chemical and hydrological parameters during 2003-2013 were received from the regional water organization of West Azarbaijan province and its seasonal average was calculated for each station. The related maps were extracted using GIS software. Then, the process of changing water quality during different seasons was studied for each station and the relationship between variables and their significance level was achieved by Pearson correlation test and SPSS software. Finally, Schueller and Wilcox diagrams were traced during each station and each season using Chemistry software for assessing the type and chemical quality of river water for drinking water and agricultural purposes. The quality of Kavlan station water during spring with amounts TDS (174.9), EC (269.1) and the concentration of chloride and sulfate ions (0.7) as the most favorable and Miandoab station during summer with amounts TDS (359.3), EC (529.3) and the concentration of chloride and sulfate ions (3.7) were introduced as the most critical spatial and temporal periods, respectively. In all research stations, the decrease of river water quality as the increase of EC, TDS and the concentration of chloride and sulfate ions had a direct and meaningful correlation with the discharge variable. In Siminehrood basin, the physical characteristics of the basin and hydro-geomorphology factors play a role in the presence or lack of pollution sources and seasonal-spatial changes of water quality. According to Schueller classification, Siminehrood River water is in a good and quite tasteless category in terms of drinking water. Also, in Wilcox diagram, all the stations are related to the C2S1 class for each season and have a slightly salty quality suitable for agricultural purposes.

Monitoring and assessment of surface water quality are a very expensive and time consuming process, thus finding cheap, simple and relatively excat methods which determine water quality class based on minimum parametrs would be very useful. Decision tree as one of the data mining techniques classify data sets based on a tree structure. In this study, the decision tree method was used to classify water quality in some hydrometry stations located at northern side of Sahand Mountain, including Bostanabad, PoleSenikh, Lighvan and Vanyar. The water quality classes was defined based on if-then rules. For every considered river, the discharge and 12 hydrochemical parameters, including Ca2, Mg2, Cl-, HCO3-, Na%, pH, SO42-, total anions, total cations, total dissolved solids (TDS), sodium adsorption ratio (SAR) and Electrical conductivity (EC) were collected and used for developing desicion tree model. The results showed that the desicion tree model could evaluate water quality class with high accuracy base on only four parameters: EC, pH, SAR and Na. As the error of developed models in testing phase for Bostanabad, Vanyar, PoleSenikh and Lighvan stations were 3.4, 8.1, 22.9 and 1.6%, respectively.

Water quality is considered as one the most important factors in development of the civilizations and sustainability of human activities. Water quality can be evaluated by comparing the each of the chemical properties in water samples with their reference values. The single parameter comparison method has limitation and a comprehensive evaluation of the water quality is not possible with this method. Thus, water quality indices has been developed during the last 3 decades. The aim of this study was to comprehensively evaluate the water quality in Ardabil aquifer with a newly proposed drinking water quality index (DWQIProposed). The DWQIProposed was also were compared with the conventional water quality indices including DWQIA and DWQIG. Water samples were collected from 60 wells in Ardabil aquifer during the September 2014 and analyzed for 21 different physical, chemical, and biological properties. DWQIProposed were computed in four steps including parameter selection, parameter categorization, development of sub-index with regression statistics, and aggregating the sub indices. Results indicated that, although there was a quantitative difference between the DWQIProposed and DWQIG, but their probability distribution functions reflect a similar pattern. DWQIProposed and DWQIA have similar values for samples with excellent water quality. ANOVA results indicated that the mean difference between three indices is significant (P

according to some researches, Iran is in greatest and worst drought in its 30 years. Kashan plain basin is one of the critical areas that has water loss and progressive destruction of agriculture due to the lack of management on the use of groundwater resources. one of the most important inventions of Iranians that has long been an effective factor in management of water resources from the past has been ghanat. in this reaserch has been tried to improve water resources management by study of sansan's qanat around Kashan. so due to the structural cognition of qanat , the depth of wells were determined according to the laws of free fall. it resulted in inefficiency of the method and the cause was scribed in detail. again the depth and hydraulic slope was determined by rope and the length measurement tool. therefor qanat's schema was drawn in three particle: the elementary, middle and end that was the first of its kind. the results of tilt-shift on the rise in water flow and losses from evaporation was studied that it is considering the possibility of increasing freshwater by five folds.

Flood susceptibility mapping is the first step in flood management programs. Flood prediction can help reducing its following damages. The main objective of this study is identification of prone areas to flooding using new ensemble Bayesian-AHP methods in the Neka-Sari watershed, Iran. Flood inventory map was prepared due to statistical analyses. A total of 240 (70 %) and 102 (30 %) out of 342 observed events were used as training and validation data set, respectively. Based on literature review, as well as extensive field studies, a total of 11 parameters in relation to flood occurrences were selected for flood mapping, including slope percent, elevation, distance to river, drainage density, NDVI, lithology, land use, topography wetness index (TWI), stream power index (SPI), rainfall, and curvature. The weights of each factor were determined by AHP method. Also, the relation between factor classes and flood events and the weight of each lasses were estimated using Bayesian theory. Finally, by integration of factors and their classes in ArcGIS, flood susceptibility map was obtained with five classes. In order to evaluate the obtained model, ROC curve was employed. Results showed that the ensemble model had a high accuracy (76.10 %) in flood susceptibility mapping. Also, slope percent, elevation, and land use have the highest effect on flood events with values of 0.260, 0.195, and 0.146, respectively. According to the results, 24.17 and 37.15 % of the study area are categorized in high and very high susceptibility classes, respectively. The presented combined model can be used for further studies on natural hazard mapping and disaster management.

Given that Qazvin Province located in the seventh drought place in the country and need to manage vast water resources. Water storage estimation methods have developed over the years and observation of changes in the gravitational field by satellite GRACE is one of these methods. This satellite produces a series of water storage changes data with spatial resolution of 1 ° on a regional scale. This study aimed to evaluate data from GRACE satellites in Qazvin province to find a comprehensive solution for quick and easy access to the water resources. To validate the GRACE satellite data, land surface model data (GLDAS) and wells data in the region were used. The results show that the GRACE satellites as a Gravity satellite just produce to estimate changes in Earth's water supply, give a good estimate of the changes in the ground water storage and groundwater level changes. Statistical analysis showed that RMSE =5.54, MAE = 4.16 and MBE = 1.5 the seasonal scale in millimetre between groundwater level data from the GRACE satellites and observation wells, and RMSE =2.92, MAE = 4.24 and MBE =0.184month scale in centimetre between the data changes in land water storage from GRACE satellite and GLDAS model. Also, the correlation between changes in water storage data from the GRACE satellite and GLDAS model and groundwater level changes from GRACE satellite and observational data is significant at the 99% probability level. The results showed that GRACE satellite shows terrestrial water storage changes better than GLDAS model.

Submarine Groundwater Discharge (SGD) is defined as any water subsurface flow from the land into the sea. Recognizing the area having this flow is very important for hydrologic and ecologic studies. For determination of Submarine Groundwater Discharge Probable Areas into the Persian Gulf on Coastlines of Bushehr Province, at first, required corrections (atmospheric, radiometric, and geometric) were made on the obtained thermal band 10 data of Landsat 8 during 2015 and 2016 across the study area using ENVI® 5.3 software. Then, by mapping sea surface temperature (SST) and standard temperature anomaly (STA) and thus determining the minimum shared area of thermal anomalies during 2015 and 2016 by GIS10.3.1 software, SGD probable areas into the Persian Gulf on Bushehr Province coastlines was recognized and mapped. The results show that there are SGD probable areas on Bandar Mogham to Kangan, Kangan to Mond River, Mond River to Shif Island, Bandargah to Ganaveh, and Bandar Rig to Hendijan coastlines with, respectively, 2823, 4165, 6159, 4725, and 4445 hectares. This area on coastlines of Bushehr Province is 22317 hectares discharging into the Persian Gulf that may suppose an Impressive flow. Therefore, surveying more details and quantifying is essential for estimating the precise rate.

The supply to manage and optimal use of water in agriculture is essential for management and conserve water resources. This study aimed to evaluate the effect of seasonal precipitation fluctuations on annual rainfed yield. Monthly precipitation data for 26 rainfall stations with Statistical period 1992 to 2014 of the east part of Urmia Lake basin were used. Clustering were done with Ward and K-means methods. The homogeneity of cluster were checked through H-Statistics method and homogeneous clusters were shown in GIS environment. The effect of seasonal precipitation were compared with annual rainfed yield. Results showed that the effect of precipitation in the spring, autumn and winter in the amount of rainfed yield is positive and precipitation in these seasons has a remarkable effect on increasing yield, In the three seasons precipitation cause increase of soil moisture storage that summer is consumer this storage But in the summer there is an inverse relationship between precipitation and annual rainfed yield. In order to identify areas combined with increased precipitation and rainfed yield Iso-line of precipitation seasons with the rainfed yield of study area was drawn. The results of this lines showed that in the spring, autumn and winter at the Daryan, Lighvan, Khormazard, Sahlan, harvy, Saidabad, ShirinKandy, Ghorigol, Tabriz and Moghanjigh increased amount of pricipitation is directly related to the amount of yield. These areas can be introduced more eligible rainfed Cultivation in East Lake Urmia and recognition the effects of precipitation on yield rainfed areas can be more practical and reliable.

In recent years, flood control projects have been more extended in the country. Given the cost of implementation, prioritizing the sub-basins is of most important and making decisions about flood and integrated watershed management being quite necessary.The first and most important step in the runoff flood management projects is prioritizing essential areas to carry out flood control projects. Decision-making methods provide effective tools for dealing with issues involving more than one goal. In this study, Parchin watershed basin was studied. Then, using multi-criteria decision-making methods (ELECTRE, Grey and TOPSIS) the sub-basins were prioritized.The results of Grey method were investigated by gray relational analysis for the score of 9 sub-basins. The sub-basin 7 with the highest score (0.719443) was prioritized in the first and sub-basin 1 with score of (0.466119) in second priority and sub-basin 4 with the least amount of score (.331493) was placed in the last priority.In TOPSIS method rating was done using calculated nearness to ideal solution options, sub-basins 7 with the highest nearness coefficient (0.843721) is in the first rank. The results from rating showed that all three methods were evaluated equally in first priority, in other priories methods gave different results. According to the above-mentioned results the three TOPSIS methods and gray analysis are more similar and more accurate than the electronic method.

An intense utilization of salt as lowering the freezing point of water in the mountainous areas of Iran country has been applied for long period. Therefore, this study aimed to determine the effect of road deicing salt on the vegetation composition, species richness and diversity indices in rangeland ecosystems of the area adjacent of Godar Kafanooieh road, Baft-Kerman, Iran in 2016. Sampling of vegetation was carried out after determining a homogeneous area of ​​ecological factors on the side of the road where runoff flowed into it. The establishment of 80 plots on a systematic sampling of vegetation along the four transects with length of 150 meters were taken.In this regard, the first ten plots on each transect were established every 5 meters and the distances between other plots were 10 meters. After calculating the diversity and richness indices based on presence or absence of species in the PAST and BIO-DAP softwares, the effect of distance from the salting road was performed by one-way ANOVA test and mean comparison was analyzed by Duncan's multiple range test. Results from 0 to 40 meters far from the road showed that plant species as Hertia intermedia, Ephorbia larica and Glycyrrhiza glabra have allocated high proportion of species composition. A significant increasing rate of Dominance and Burger indicators (86.7 and 97.7 percent in comparison to near road and 18.27 and 115 percent in comparison to furthest away distance from road (150 meters), respectively) and decreasing of Simpson, Shannon, Margarof, Menhing and Fisher indicators(45.2, 49.6, 38.5, 14.6 and 30.2 percent in comparison to near road and 53.4, 68.5, 77.6, 51.4 and 76.8 percent in comparison to the furthest away distance from road (150 meters), respectively) at the 40 meters far from the road indicated the dominance of few species with high population (mostly Salsola inconesense). Native rangeland species (Artemisia aucheri) along with other species such as Stipa barbata and Astragalus parrowianus were observed at 50 meters distance from the road and their contribution in vegetation composition were raised with increasing the distance. According to this research, salt deicing due to changing the ecologic condition for invader and halophyte species, will decrease richness and diversity species and lead to diminishing potential associated to increasing vulnerability of near rangeland ecosystems.

The water footprint consider as a indicator of freshwater resources appropriation which brings valuable insight about the environmental impact of a given product. The aim of this study is determining the best country’s province for the potato crop production in terms of fresh water consumption, for this object water footprint indicator was used. To achieve this goal, first data on harvested area, production and yield in major producing provinces were collected for the crop year 2014-15. Then to calculate the water footprint in each province, information such as crop water requirement and effective precipitation were collected separately for each province and finally water footprint components were determined. The results showed that green, blue and grey water footprint devoted most contribution in all provinces respectively. According to calculated total water footprint, Hamedan province is the best region for potato harvesting and Semnan province is the most difficult region for this purpose. Water footprint average for potato production was calculated 527 m3/ton in the country. According to water footprint indicator and provinces potato production, it was determined that in mentioned crop year, Hamedan province by using 338 MCM and North Khorasan by using 18 MCM of water, allocated the highest and the lowest amount of water to this agricultural production respectively.

With the rise of people and the industry development, many pollutants had been enterance to environment. Besides, aquatic ecosystems are more vulnerable to chemicals with different combinations particularly heavy metals. In this study the pollution of sediment around the basin of Mighan wetland to lead, zinc, and copper heavy metals was assessed by acid digestion and Atomic Absorption Spectroscopy and Contamination Factor (CF) and Potential Ecological Risk Index (RI) were measured. According to the results, comparisons of metal concentration with sediment quality guidelines (SQGs) were done. Finally zoning metals using Kernel Density Estimation showed that the southern and western parts of the wetlands because of industrial zones, agricultural lands wastewater, and industrial area have a high concentration of pollutants. Meanwhile investigation of heavy metals represented a high concentration of copper metal relative to zinc and lead metals in the region. In the end, the requirement for contaminants controlling in the Mighan wetland is recommended.

Due to the reduced rainfall and overuse of underground water, check the water quality is one of the most important challenges discussed in various areas, such as Iran. Estimation of water quality using models such as neural network results in costs reduction and better management. The aim of the study is to assess ground water quality using adaptive fuzzy neural network (ANFIS) in the west of Fars province during 2003 to 2013 period. Three methods that consist of grid partitioning, sub-clustering and FCM with two models of Hybrid and back propagation was used to predict the quality of ground water for the study area. In this study, electrical conductivity (EC) and sodium adsorption ratio (SAR) were used to train the neural network. In addition, water quality class diagram Wilcox was used to train the network. In chemical pollution, according to Wilcox diagram, EC and SAR are the most important factors based on which waters can be classified in different classes such as very appropriate, suitable and unsuitable for agriculture. Results show that among the various models provided to predict groundwater quality, Hybrid models in FCM method has the greatest accuracy for the prediction of water quality in the study area with a maximum R (0.99) and minimum error.

At the present, erosion is one of the most important of environmental problems in the Iran watersheds. Therefore, determine the sediment and soil erodibility is very important for conservation and management of natural resources. The aim of this study is evaluate the spatial distribution of soil erodibility and relationship with some of the soil properties using geostatistical methods in the Khoor and Biabanak region. For this purpose, 33 soil samples were taken from depths of 0-50 cm along three transects from playa until mountain units to determining the components of sand, clay, silt, organic carbon and organic matter. Values of K factor and SEI were calculated by values of these parameters. Finally, to determine the spatial distribution, interpolation methods were tested and the most suitable method was chosen. The results showed that Radial Basis Function was the most suitable of interpolation method for the spatial distribution of the elements of sand, clay and K factor with RMSE 3.27, 3.22 and 0.0036, respectively. The simple Kriging method was suitable for carbon components and organic material with RMSE 0.34 and 0.59, respectively. For silt, Kriging Ordinary with RMSE 0.88, and for SEI index, Universal Kriging method with RMSE 0.0014 were suitable. According to the results of soil erodibility values, minimum and maximum amount of K factor with 0.025 and 0.07 t h MJ− 1 mm− 1, as well as minimum and maximum values of SEI with 0.03 and 0.07 are extensive in the East, and West and North West area, respectively.

Monitoring and prediction of droughts, especially accurate determination of its emersion time and duration, is very important in water resources management and planning drought mitigation strategies. In this study drought conditions in Northeast of Iran was evaluated by means of Joint Deficit Index (JDI). Monthly precipitation data from 6 synoptic stations including Torbat Heydariyeh, Sabzevar, Semnan, Shahroud, Gorgan and Mashhad during the period of 1971 to 2011 were used for calculating the JDI index. Results showed that in recent years the number of dry months across study area (especially at wet regions) increased, significantly. As in all of considered stations (except Semnan station) the percentage of dry months increased to over (more than) 50% during recent 10 years (2002-2011). Results showed that the JDI provides a comprehensive assessment of droughts and that it is capable of reflecting both emerging and prolonged droughts in an accurate manner and allows for a month-by-month drought assessment.

Ajabshir Plain is located in the eastern Azerbaijan province and in the north-west of Iran. This plain provides the water for drinking, agriculture, and industry in Ajabshir city. In this research, regarding the hydrology and hydrogeology conditions of the study area, the vulnerability of the aquifer against the pollutants was zoned using DRASTIC and SI models and geographical information system. In DRASTIC model 7 factors including depth to water, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity are used to generate the vulnerability map. The vulnerability assessment of aquifer is also affected by 5 factors including depth of groundwater, net recharge, lithology of the aquifer, topography and land use in the SI model. After preparing information layers and rating in ArcGIS software, the final map of aquifer vulnerability to pollution was prepared through integrating layers. Regarding the SI vulnerability map, about 2.24% of the study area is located in very low vulnerability area, 5.27% in low vulnerability area, 45.08% in moderate to low vulnerability area, 39.09% in moderate to high vulnerability area, and 8.3% in high vulnerability area. According to the DRASTIC model, 13.4% of the study area was allocated to very low vulnerability, 55.43% to low vulnerability, 28.69% to moderate to low vulnerability, and 3.08% to moderate to high vulnerability. The evaluation of two models by TDS element indicated that SI model (correlation coefficient= 0.76) is more accurate than DRASTIC model in terms of preparing vulnerability map for the study area. Moreover, both prepared vulnerability maps showed that conservation of groundwater resources of Ajabshir plain by managers and planners is necessary to control and prevent the aquifer from pollution and its stability for the future generation.

One of the key issues in the practical planning for water resources is the existence of uncertain factors. One of the approaches for decision making under such circumstances is interval programming. The aim of the study is to develop an interactive optimization model for water and crop area allocation. The developed model comprises four objectives that take into account socio-economic factors, the virtual water content of crops, and meeting environmental water requirements. For solving the model, four crop area scenarios (assumptions) were considered. Results showed that by raising the level of satisfaction threshold on the constraints, the amount of water allocated to each water user is declined. So that from the satisfaction level of 0.65 to the level of complete satisfaction, the model allocates only the minimum amount of water (40 MCM) to meet the environmental water needs. Based on considered scenarios for solving the model, the largest cultivation areas are allocated to wheat and maize for autumn and spring cultivations, respectively. Solving the model in the absence of upper bound for crop areas revealed that the greatest difference between optimal crop area and the highest cultivation area happened was belong to rice with 2777 and 5821.6 hectares in Dorudzan and Korbal districts, respectively. The main advantage of the developed model in the present study is the linear formulation as well as its ability to deal with uncertain parameters. Outcomes of the model provide information required for the assessment of risk and reliability of planning options for water allocation.

Instability of river bank leads to lots of problems in short and long terms. Gradual destruction of river bank makes consequently risk for structures and lands along the river coast. It can cause the field of sedimentation, reducing local angle of meanders and finally, making a new path for river. Numerical modeling of the effect of successive spur dike on flow and sediment patterns and providing protection for the bank of Minab River with using two-dimensional model CCHE2D, are conducted in this study. The parameters that were used for calibration, Including water depth and flow rate, which is measured in three river bend, At this stage, as well as to provide optimal networking of different models were used And Network 50*500 because it was closer to the results of field measurements was chosen. The results of this study show, Geometry of river flow and sediment regulated and guided the breakwater in the Thalweg river velocity and shear stress influences, So that a spur dike can lower velocity to 66 percent and deviation of maximum velocity lines from the banks and river bank zone, obviating 20 cm erosion and substituting 5 cm sediment on bank zone and finally it will establish and protect river banks.

Streamflow forecasting is necessary for water resources management and planning in rivers, lakes, reservoirs and protection of river banks during flood time. In this study, different soft computing models including artificial neural networks (ANN), the hybrid of wavelet-artificial neural networks (WANN), gene expression programming (GEP) and least square-support vector machines (LS-SVM) was utilized for river flow estimation of Khiav-Chay. Statistical measures and ANOVA test was used for evaluation of applied models. The results indicated that WANN model was the best one with the highest correlation coefficient (R=0.877) and lowest root mean squared error (RMSE=0.696) and Nash Sutcliff coefficient (NS=0.767) in validation phase. The results of ANOVA test was in agreement with statistical criteria values and WANN model with the lowest F statistic (F=0.11) and highest significant resultant (0.75) was selected as the best model. Furthermore, in estimation of maximum discharge, WANN with mean relative error equals to 30.19% has the minimum error of estimation compared to other models.