مجله تحقیقات منابع آب ایران
سال چهاردهم شماره 5 (پیاپی 47، زمستان 1397)

Considering the limitation of water resources and their value in agriculture, the use of any strategy for consumption and optimal use of existing water is essential. One of these solutions is Deficit irrigation. The purpose of this study was to evaluate the effect of different percentages of reduction of water consumption in different growing stages as deficit irrigation scenarios on the Optimization of Water Use and dominant cropping pattern (Wheat, Barley, Sugar beet, Forage Corn, Maize corn and Alfalfa) in Qazvin plain irrigation network. In order to maximize farm income, the PMP method, along with the method of Maximum Entropy (ME) based on the reaction functions of the products yield comparing to water in the space of other constraints was used. The required information for this research was obtained by using two-stage cluster sampling method through completing 144 questionnaires in farm years of 2015-2016. Results showed that by applying deficit irrigation at best condition (first scenario), despite the 5.2% saving in water consumption, it is possible to increase farm income by 0.4%. On the other hand, depending on the severity of the crisis and the amount of the water scarcity, decision to determine the deficit irrigation strategy and the region's cultivation pattern would be different so that if more water conservation is desired, the results of the second and third scenarios are the best option for the optimal use of land resources and the minimum water consumption.

The proper prediction of reservoirs water level variation is considered as one of the important issues for management, designing, operation of dams and water supply. In this study, based on five soft models such as support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), radial basis function neural network (RBFNN), generalized regression neural network (GRNN) and the combined use of their results as input to one of these five models, a new structure called supervised intelligent committee machine (SICM) was proposed to predict the monthly reservoir water level of Karaj Amirkabir dam. The data used in this paper are water level, precipitation, evaporation, inflow and outflow of the dam. The evaluation of these models was done by nine error indexes and also the best model between them was selected using vikor decision maker method. After performing the necessary evaluations among the used soft models, the ANN known as the best model with nash–sutcliffe efficiency (NS) and mean square error (MSE) equal to 0.89 and 23.37 square meters, respectively. The results of the proposed approach are shown that the supervised (hybrid) neural network (SICM-ANN) has been able to provide high performance in predicting the monthly reservoir water level in Karaj dam with increasing the NS coefficient to 0.94 and decreasing the MSE index to 12.85 square meters (more than 45 percent decrease). Accordingly, hybrid use of soft models can be effectively applied to significantly reduce the predicted error of water level rather than single models.

In the management of water resources systems, there are various inherent uncertainties which are exacerbated as planning horizon gets longer. Among them, the uncertainties related to climate change and their consequences cause serious challenges, which are also attributed as deep uncertainties, too. Therefore, it is crucial to consider them in developing any plan for adaptation strategies. This issue constructs the main objective of current research work, which applies the concept of “robustness” to evaluate adaptation strategies and respected decisions. For this purpose, the paper uses Robust Decision Making (RDM) technique, which is linked to Soil and Water assessment Tool (SWAT) model for the required water and agricultural simulations. The case study of this research work is Zarrineh Rud River basin with high cultivated lands. It is also the main feeding river of northwest Iran’s Lake Urmia. At this stage, the paper focused on evaluation of the current management of the basin to adapt climate change. For this, different indicators including: inflows to the lake, change in groundwater storage, evapo-transpiration and crop yield were applied. The results showed that the current management is not robust and fails in most of the projected climate scenarios. These fails are worsened as rainfall decreases and temperature increases more than 0.75 Celsius. This suggests necessity of evolving strategies, which can be properly evaluated through the developed modeling framework.

Iran's electricity industry are looking for better ways and more efficient in generation, transmission and distribution of electrical power in recent years. The industry rules have changed to become more competitive. With uncertainty in market price, water inflow, the beneficiary's behavior, access to information and risk increasing, the profit maximization has been more difficult in electricity market for hydroelectric energy producers. In this situation, pursue a decision-making for optimum operating of power plants is one of the main producers concerns. For this purpose, time series data on average monthly during 2005–2015 was used and profit is forecasted for twenty-four months. For this study, energy data from Karun river hydropower plant karun1 was used. Firstly, Gómes-Maravall model was used to predict of electricity price and river inflow. Then, using an ARIMA model was estimated for operating and maintenance cost in the hydropower plant. In this research to study of hydropower plant profitability was used the system dynamics approach and multiple scenarios like: climate change and penalty costs scenarios.

Protection and management of water quality of rivers, as one of the valuable natural resources, is of high importance, especially where the sacristy of water resources matter too. In the present study, in addition to identifying contamination resources, it was surveyed different sceneries of controlling the major pollutants of the Zarrineh River in order to meet the water quality standards for aquatic life. To achieve the research objectives water quality sampling, monitoring of the contamination resources and plant coverage, along the river were conducted during the three seasons in 2016. A river water quality and hydraulic model was implemented, calibrated and confirmed by using the data in QUAL2KW. Evaluation of the hydraulic behavior and river water quality indicate that during the dry seasons, both reaction and advection affect the variations in water quality parameters, whereas during the wet periods, advection dominants. Subsequently, analysis of the river water quality pollutants reveals that the distributed sources like pile of trashes and animal wastes at the river bank have the largest share in contamination (Nutrients) of the Zarrineh River and among the point source pollution and agricultural pollutants, the largest share in contamination during summer and fall seasons belongs to the point source and during the spring season belongs to agricultural pollutants. In the present condition, evaluation of water quality management sceneries during the fall season, shows that restricting Sugar Factory Sewage BOD5 to 210(mg/l) gives rise to keeping standard amount of BOD for the aquatic life.

Joint occurrence of coastal and inland urban flooding is considered as a major problem in coastal developed cities. An appropriate perception of flood hazard is imperative to face new challenges in flood management in these areas. To address this issue, flood frequency and intensity are determined based on historical storm data of the case study utilizing statistical analysis. Five copula functions have been fitted to hydrological data to find joint return periods of coastal and inland flooding and the best one has been detected based on the Kolmogorov–Smirnov and the root-mean-square error test. Afterward, flood delineation map is used as an effective tool in the improvement of decision making process in urban development plans. For this end, a geographic information systems based software named WMS has been utilized to delineate flood inundation and depth in Bronx brought of New York city in United States. Best management practices as flood management/mitigation strategies are categorized in five classes, namely resist, delay, store, discharge, and retreat. After that, a performance index has been derived based on five factors of degree of hazard mitigation, aesthetic, capital cost, maintenance and operation cost, and adaptability utilizing Multi Criteria Decision Making methods. Finally, one of the strategies is selected as a viable strategy to reduce flood hazards.

Modeling conceptual rainfall-runoff procedure involves large number of parameters and climate data. Uncertainty in these input parameters are very likely which lead to output errors as well as impractical prediction of long-term impact of management policies. In this study Soil and Water Assessment Tool (SWAT) is implemented to simulate rainfall-runoff process in Chelgerd sub-basin. To develop appropriate model with acceptable and reliable performance, Ensemble Kalman filter (EnKF) as data assimilation technique is used to assimilate the variables of model which are known as sources of error product; these sources include model parameters and input data. The paper in concluded that EnKF as a data assimilation technique is capable of reducing the computational error inherited in the simulation model. Results of proposed model is evaluated by Nash-Sutcliff (NS) factor with value of 0.86 which have better performance than modeling without EnKF technique. Also developed model performance is improved with NS value of 0.82 for validation period.

Given the complexity of urban environments, flood risk has increased in urban areas in recent years. In order to estab-lish a correct urban management, the control and optimal use of surface water should be carefully understood from the complex rainfall-runoff process in urban environments. The problems of urban basins are the lack of precise input pa-rameters, the lack of knowledge of the runoff production process, the lack of a flow measurement system at the outlet of sub-basins to calibrate and uncertain input parameters, and the results of mathematical and numerical models such as SWMM. This research investigates and analyzes the uncertainty of the GLUE method at levels in District 2 of the Metropolitan Municipality of Tabriz, with SWMM urban flood model. In order to quantify the uncertainty, the initial range of input parameters including CN, impervious, N pervious and N-impervious was determined. Using the GLUE algorithm, initial sampling operations were performed using parametric space by lattice square sampling. According to the results of simulations and the magnitudes of observational events, 20% of the total outputs and the series of gener-ated parameters were separated as acceptable simulations. According to the results of the evaluation of the distribution diagrams, Imperv% and N Imperv input parameters were identified as sensitive and effective parameters on model simulation and the range of parameters was obtained.

In this paper, using variance based methods, the sensitivity analysis of the two well recognized water quality indices, namely NSFWQI and IRWQISC, is presented in a comparative approach. The research was conducted by employing monthly sampling at thirteen stations on Pasikhan River during 2015. Sensitivity analysis of the two models’ parametres could lead to recognize the most important ones for their better measurement and also to evaluatie the correctness of the parametrs’ weights used in the Iranianian model. In the seasonal analysis, BOD was determined as the most sensitive parameter for both indices. In spatial analysis, NSFWQI classified the river water quality as “Good” and “Bad” in upstream and downstream Pasikhan River, respectively. Using Factor prioritization approach, it was found that DO was the most effective parameter in NSFWQI, for which applying the approach minimized the uncertainty of the model output. In IRWQISC, Do at U/S stations and BOD at D/S stations were the most influencing parameters on the model output variance, which emphasized the importance of the frequency and precision of sampling of these two factors against the other nine employed factors . Another important achievement of the present research was revealing the inconsistency of the weights used in IRWQISC, with respect to the parameters’ sensitivity and their influence on the model output in Pasikhan River.

The various semi-distributed and distributed hydrological models have a very high potential for comprehensive water catchment simulation, but these models still need to be developed in order to get closer to the actual conditions of the catchment areas. To simulate the karstic basins using conventional hydrologic models, changes in model codes are required. The SWAT model, due to openness and freedom, has made it possible to implement and configure various conditions in the catchment area. In this research, a new model called SWAT-ML has been developed in which karst regions have different hydrological characteristics. The studied area is a karstic basin of Maharlu Lake and statistical simulation period from 1980 to 2013 for calibration and validation of surface runoff, base flow, agricultural production and actual evapotranspiration. The model was calibrated with an average of determination factor and Nash Sutcliff of 0.65, and it was found that the SWAT model has a great potential for estimating the yields of agricultural products. The developed model showed that in karstic watershed simulation, performance is better than SWAT model, and the calculated balance values by SWAT and SWAT-ML model, has a significant difference compared to hydro climatology budget.

The provision of appropriate legal instruments for precise oversight of exchanges process and resolution of possible problems is one of the requirements for establishment of efficient water market. The dominant approach of Iran’s water legal system is the incentive of water market formation. However, there are some legal documents such as Matters 27 and 28 of the Fair Water Distribution Law that limit the water exchange process. Although the guidelines for the implementation of these matters have been amended by the Ministry of Energy but there are still the ambiguities in the water market conditions. In this paper, along with the identification the incentive and restrictive laws of the water market, some of the legal challenges of water exchange are presented through the analysis of laws related to the Iran’s water legal system. Then, by examining the status of exchanges within the Borkhar pilot plain, the challenges and considerations for the success of this market are identified. Based on field-level visits in the study area inter-sectional exchanges are of interest, generally. So that, the agriculture-related industries and building industries have a willingness to purchase water from agricultural wells, potentially and actually. The results show that the establishment of an efficient water market needs the consideration of issues such as issuance of a separate document and independent of the land for withdrawals, modification and adjustment of exploitation licenses, equipping wells to smart meters and establishments of groundwater users’ formations by strengthening incentive laws and amending barrier laws.

Rising water demands and over-extraction of groundwater have caused critical problems in more than 50% of the aquifers in Iran. Simulating complex condition of such aquifers and selecting an appropriate management approach are required to compensate drawdown. Therefore, this study aimed to provide a management approach for the Ravansar-Sanjabi aquifer in Kermanshah using the MODFLOW model, an aquifer under a severe stress during last decades. After calibrating and evaluating the model, as well as providing a spatial distribution map for the actual drawdown during the period of 2007-2015, the aquifer is divided into four drawdown zones, including 0 to 5, 5 to 10, 10 to 20, and 20 to 45 meters, and then several options of combining scenarios were applied to compensate the drawdown in each of zones. The first scenario includes the condition of the last eight years of sources and sinks and recharge of the aquifer, which resulted in a7.2 m decline during the next eight years. In the second and third scenarios, with the effects of drought and wet conditions, the results showed that groundwater level would decline by 8.4 and 5.2 m, respectively. The results of the first three scenarios showed that the effect of climate fluctuations is not the main factor affecting the groundwater level decline. The results of the fourth scenario, with different combinations of 10% to 70% reduction in pumping rates, showed that the combination of 10% in zone1 and 20% in the other zones provides the best results in improving aquifer conditions.

Efforts to achieve suitable estimation of parametric or the structural uncertainty of mathematical or conceptual frameworks have been led to develop various probabilistic, possibilistic, and innovative methods. In this paper, uncertain parametric behavior in a monthly water balance model has been studied using the structure of the UNEEC-P method. In the approach proposed by this paper and for the first time, instead of using a variety of regression methods to estimate the upper and lower uncertain bounds, the original conceptual model has been used. The applied conceptual model is a three-parameter monthly water balance model, and the case study of the paper is a small basin with an area of 82 square kilometers in southern France. Also, in order to evaluate the performance of the proposed method, Generalized Regression Neural Network (GRNN) has been used to evaluate the results of the conceptual models. The estimation of parametric uncertainty has been used to simulate the results of GLUE method in a Confidence Level (CL) equal to 90%. In order to measure the accuracy and validity of the new mechanism proposed in this study, in addition to the usual evaluation indicators of similarity and dissimilarity, the AIC index is also used, and different statistical indicators such as Mean Square Error (MSE), Normal Mean Square Error (NMSE), Nash-Sutcliff (NS), Correlation Coefficient (CC), and AIC demonstrate the better performance of proposed method comparing to the GRNN.

In the past decade, machine learning for empirical rainfall–runoff modeling is considered to be a promising approach as a useful complement to hydrologic models, particularly in basins where data to support process-based models are limited. In this paper, we used black-box models (i.e. neuro-fuzzy and support vector machine) and gray-box models (i.e. TOPMODEL and HBV) for simulating the transformation of daily rainfall-runoff process in the Nodeh khormaloo watershed located in Gorganrood River Basin and compare their performance in terms of predictive accuracy. For the black-box models, the three input vectors including discharge, temperature and rainfall are selected in nine different scenarios based on the sequential time series data. Our result show that the neuro-fuzzy model which consists of three antecedent values of flow and one antecedent values of temperature outperforms other models when the root mean square error and coefficient of determination are used as quality indicators. In general, the black- box models outperformed the HBV and TOPMODEL simulations for the calibration and validation data sets. A detailed comparison of the overall performance indicated that the neuro-fuzzy and SVM models predicted runoff in warm months were consistently lower than that in the cold months.

The Assessment of groundwater vulnerability to pollution for groundwater protects, which is affected by high fertilizer use, is a proper tool. Groundwater of Urmia Plain due to various factories and agricultural activities, have potential for contamination. In this study, the modified version of the DRASTIC model and the original DRASTIC model, which is a global model, has investigated the inherent vulnerability potential of Urmia groundwater contamination. The correction of this model based on the revising of the ratings and weights of various factors was carried out using simple statistical methods and in the GIS environment, taking into account the correlation with the concentration of groundwater nitrate. The results showed that aquifer environment (A) did not significant correlation with nitrate concentration and was eliminated from the initial equation. The highest and lowest significant correlation was found between soil factors (s) and depth to groundwater (D), respectively, and weighed 5 and 2.7, respectively. The correction of ratings and weights led to improved zoning map, with the correlation of the DRASTIC index with nitrate concentration versus the original DRASTIC, increased by 11%. Based on the modified index of the Urmia Plain, 4.3, 30.8 and 64.9 percent were low, very low and without risk of pollution, respectively.

Increasing water demands and insufficient water resources has became the main reasons of raising water conflicts among stakeholders in Sefidroud basin. Sustainable allocation of water resources with viewpoint of economic efficiency and social equity is necessary to reduce these conflicts. Hence, they was assessed in Sefidroud basin, Iran. Sustainability of water allocation as the model constraint guarantees the minimum environmental requirements in water resource planning. In this study, a multi-objective programming model was developed to supply the requirements of the environmental, industrial and agricultural sectors in Sefidroud basin. The objects of the model were the maximizing of the economic benefit efficiency for the development of improved water allocation strategies as well the maximizing of the water allocation equity (measured by using of the Gini coefficient). NSGA-II algorithm was used to solve the developed multi-objective programming model. The best solution among pareto front was selected according to equilibrium viewpoint because of considering economic efficiency and social equity among stakeholders simultaneously. Additionally, two scenarios were defined in term of the rate of water loss and available water to assess the developed multi-objective programming model. The results showed that river basin authorities should decrease the rate of water loss and increase the available water to improve water allocation efficiency and equity. Additionally, the decrease in available water had highest impact on water allocation equity, but it had least impact on economic benefit efficiency. Furthermore, it should be considered for implementing water-saving policies according to critical conditions of water resources.

A comprehensive model based on AHP and GIS is developed to locate areas susceptible to artificial groundwater nourishing through flood spreading. Khoy plain, which in recent years has increased its groundwater usage, selected as the case study. Sixteen criteria considered including slope, land-use, geomorphology, geology, distance from fault zones, roads, waterways, wells, springs and aqueducts, rate of rainfall, temperature, and evapotranspiration, electrical conductivity of available groundwater, and its hydraulic gradient, thickness of non-saturated alluvial section, ability of aquifer transfer, and surface permeability of soil. Above-mentioned attributes were classified into four groups, i.e. physical, climatic, hydrological and hydro-geological clusters. Gathered data were prepared in GIS environment, and based on pair wise comparisons, the preference of each cluster and its sub-criteria was determined. By combination of the layers using Weighted Sum method in ArcGIS, unacceptable zones ignored, and the remaining ones were classified into five categories. Finally six scenarios were proposed in very suitable zones. The proposed scenarios were then prioritized based on developed model and the 3rd scenario was selected. Results indicated that due to the similarity of the climatic and hydrological characteristics of selected sites in the non-wide areas, the final decision will have a small effect on these indicators.

In this study, Tashk-Bakhtegan, with high interaction among of its systems, was studied. Firstly, To simulate effects of climate change, precipitation and temperature variable were be extracted from the Atmosphere-Ocean General Circulation Model (CanESM2 and MPI-ESM-LR, GFDL-ESM2G) by the new scenario of greenhouse gases (RCP2.6). To minimize uncertainty because of the downscaling method, three methods of multisite downscaling (XDS, Sequential k-nearest neighbor imputation method (SKNN) and Statistical Downscaling Model–Decision Centric (SDSM–DC)) were used. Then, the integrated dynamic model for the catchment scale was prepared. The effects of the climate change scenario and its adaptation strategies were simulated in the basin in the future period. Finally, measures of water security indicators were identified based on social, economic and environmental dimensions during the base and future period. Moreover, the influences of appropriate strategies on the reduction of vulnerability have evaluated the basis of indicators changing. The results show that economic water productivity in agricultural sector should be increased by increasing irrigation efficiency and agricultural activity should be reduced concerning decrease the vulnerability of system in the future period, and it is necessary to increase industry activity to economic and social indemnity.

In present paper,Standard Precipitation Index SPI and SPEI indices were compared in order to assessment of drought conditions in the Esfarayen-Sabzevar region.As the aforementioned region does not have sufficient long-term data to assess the drought, reanalysis data of ERA-Interim were used to combine with the observed data.For this purpose,climatic data of precipitation and temperature were extracted for each station in the statistical period of 1979-2016 using the web interfaces,Python script,ECMWF WebAPI and ArcGIS software. After correcting the bias of the data based on observational data,combined data of precipitation and temperature were obtained for the aforementioned period that was basis for calculating the drought.Finally,drought assessment and estimating the correlation of SPI and SPEI of three stations of Sarcheshmeh,Ghasemabad,andJoghtay in the time scales of3,6,12,18,and24months were done.After generating data combination, the Root mean square error(RMSE)and Bias were decreased from0.39and6.69to0.32and0.24 respectively;therefore,these data can be used for drought assessment in areas with not available data.Results showed that in the short time scales,the frequency of dry and wet periods is high which decreases with increasing the time scale,but their continuity increases.In the stations,in most of the cases,coordination in the dry and wet periods was observed in both indices.Based on the provided results regarding the correlation between SPIand SPEI indices, there is a positive and significant correlation between above indices and the correlation is higher in the humid regions.As a result,the SPI index can be used in the regions without temperature data and with a precession similar to the SPEI index.

The primary objective of this study is to develop a hydro-economic framework in Zayandehrud River Basin to optimize allocation of water released from Zayandehrud dam to downstream irrigation districts, to maximize economic benefits from agricultural activities. To achieve this goal, the existing agricultural activities in each irrigation district were simulated by applying the Positive Mathematical Programming (PMP) economic model. By coupling the developed water allocation planning model of the basin (MODSIM) with the economic model, the hydro-economic framework was then generated. Calibration and convergence of the models were performed by using the base-year (2014-2015) data. Obtained results of employing the hydro-economic framework in the management of water delivery revealed significant changes in water-allocation priorities between the irrigation districts. For instance, allocation priorities of Neko-Abad and Rudasht Irrigation Districts were first and fifth under the current conditions, respectively, which have significantly changed to fourth and second after employing the developed hydro-economic framework. As a case study, the potential of existing operating system in North Rudasht Irrigation District, as a representative of other irrigation districts in the basin, was investigated to make an infrastructure for optimum water allocation by using the hydro-economic framework. Results of modeling the existing operating system of North Rudasht Irrigation District showed a fair and inadequate performance, especially in the middle and lower sections, in optimum water allocation with an economic approach.

One of the most widely used method for estimation of erosion over the catchment and the sediment delivery from the catchment is revised universal soil loss equation (RUSLE). Several studies have been carried on the importance of topographic factor (LS) which includes slope steepness and slope length factors. Over the past decades, different methods have been developed for calculation of topographic factor and hence, choosing the best one is a confusing and challenging issue. Moreover, by increasing of geographic information system (GIS) application in hydrological modeling, mathematical calculations on grid-based datasets can easily be done in GIS environ. Due to depending on grid-based datasets, RUSLE model is influenced by several factors which among them, the effect of DEM resolution and the method of LS estimation are the most important ones. This research addresses the effects of all important factors on sediment delivery load at the outlet of the Barajin catchment by coupling RUSLE model and GIS environ. Also, in order to evaluate the efficiency of this model, mean annual sediment delivery load is calculated by analyzing discharge-sediment curve and observed data at Barajin hydrometric station between 1987 and 2015. Findings show that using different methods for estimation of LS factor without considering their limitations leads to a significant relative error (RE) in the calculation of sediment delivery load. Furthermore, McCool et al equation, due to a RE of lower than 10% in estimating the sediment delivery load, is the best method for calculation of LS factor.

Optimal allocation of water resources for supply and demand management with respect to climate change effects on water systems is essential. The purpose of this study is to simulate and optimize various components of اAharchay water system under climate change conditions and evaluate different climate and management scenarios.The effect of climate change on weather variables is investigated using the outputs of GCMs under A1B, A2 and B1 scenarios. Results for the period of 2011-2030 showed the decrease of rainfall and an increase of minimum and maximum temperatures for the study area. For estimation of the inflow to the reservoir during 2015-2025 years, the IHACRES model is used. Results for R2 and RMSE criteria were equaling to 0.65 and 1.21 for calibration and 0.56 and 1.4 for validation phases. Moreover, to estimate the water requirement under climate change impacts, evapotranspiration (ET) is calculated by CropWat model. For demand management in agricultural sector, optimization of soil and water allocation was carried out through linear and non-linear programming models (LP, NLP) considering plants’ growth stage and their sensitivity to water stress. Water balance in reservoir was simulated by WEAP under climate change scenarios to allocate water at demand nodes. Considering the climate and management scenarios, the best option was identified by AHP and its associated weights are then calculated. Resalts demonstrated the use of optimal cultivating levels, new irrigation method and reducing per capita drinking water was selected as the best management scenario with the highest values of temporal and spatial reliability.

Fractal geometry is used as a suitable tool for analysis of the sub-basin geomorphology and the river networks characteristics. It is also practical for very other complicated natural phenomena. Some of the most important indices of multi-fractals are generalized fractal dimensions, Singularity spectrum and the scaling coefficient. The main object of this article is the anlysis and evaluation of Walnut Gulch Watershed based on multi-fractal analysis of the river network images and geomorphology characteristics. To achieve this goal we inserted the required data in GIS template and Arc Map software. We also developed MATLAB codes for non-linear analysis. The selected analysis method here to define the fractal dimension of the river networks in the sub-basins is the Box Counting. During this process, first we obtain the fractal dimensions for each of the considered sub-basin with developed MATLAB codes and then the generalized fractal dimensions, Singularity spectrum and the scaling coefficient of the sub-basins are derived. In the last step, sub-basins geomorphologic characteristics such as: µ, SL, S, T, BS and Re are compared to the multi-fractal characteristics. The results showed that significant relationships between the geomorphologic characteristics of the sub-basins with multifractal features which may be extended to other watersheds if more studies are managed.

Total Precipitable Water Vapor is one of the important parameters in meteorology and hydrology. The aim of this study is the evaluation of remote sensing algorithms to estimate TPW over land using microwave and optical wavelengths in the western part of Iran. In this regard, the algorithm of TPW estimation in the microwave wavelength range by using Advanced Microwave Scanning Radiometer 2 (AMSR2) data on cloudy and clear sky days as well as the product of near infrared TPW of Moderate Resolution Imaging Spectroradiometer (MODIS) MOD05 in clear sky days were evaluated. MOD05 product does not work on cloudy days. The evaluation results based on radiosonde data on clear sky days showed that MOD05 product had higher precision than AMSR2 algorithm, so that the coefficient of determination (R2) derived from AMSR2 and MOD05 were 0.516 and 0.650, respectively. Moreover, the Root Mean Square Error (RMSE) of AMSR2 and MOD05 were acquired as 5.129 and 4.542 mm, respectively. On cloudy days R2 and RMSE of the obtained TPW from AMSR2 algorithm were 0.284 and 7.367 mm, respectively. Overall, on cloudy and clear sky days, the value of R2 and RMSE of estimated TPW from AMSR2 was 0.420 and 5.976 mm, respectively.

Nitrate contamination of groundwater has been concerned as one of the major environmental problems during last few decades. Recent studies have established that the nitrogen (N) and oxygen (O) isotopes of nitrate (NO3) can be used to trace nitrogen dynamics including identifying nitrate sources and nitrogen transformation processes. Stable isotope ratios (δ15N–NO3, δ18O–NO3 and δD-H2O) of groundwater samples were determined used to identify contamination sources and transformation processes occurring in Varamin aquifer, Southeast Tehran, Iran with intense human activities. The approach is based on the realization that NO3 originating from different sources would be exhibit differing isotopic compositions. In addition, δ18O–NO3 is more useful to identify nitrate from atmospheric sources and nitrogen transformation processes. In case study, nitrate concentration of groundwater were in the range of 0.4 to 79.59 mg/l with mean value of 25.14 mg/l. The nitrogen and oxygen isotopic compositions of nitrate in pore water extracts from groundwater samples indicate at least two potential sources of nitrate in Varamin Aquifer. These sources include animal and human waste as well as soil N that most common sources of nitrate contamination in groundwater are wastewater. Denitrification process occurred in the West and South West of Varamin aquifer, specially.

Nowadays, such interactions between humans and hydrologic cycle are occurring that has never previously been observed. Feedbacks and interactions between human and hydrological systems show that anthropogenic activities have led to a strong coupling between them and both positive and negative impacts of social developments can affect on hydrological system via management decisions. Although the fact that man and water are linked through a “system of mutual interaction” has been recognized for many years, there has not been quantitative understanding of feedbacks, two-way interactions and evolution and co-evolution concepts of coupling systems yet. These conditions have led to the emergence of a new science of "socio-hydrology" with the aim of understanding "the dynamics and co-evolution of coupled human-water systems", in 2012. Indeed, socio-hydrology is the study of coupled human-water systems based on co-evolution of social and hydrological systems, which analyzes how two-way feedbacks and interactions occur in these systems. Socio-hydrology, that is shaped by economic and policy frameworks, has led the boundaries of hydrology to accept human as an integrated part of the hydrological cycle and represents new advancement in hydrological science, which requires further rethinking.

In this paper‏ ‏temporal and spatial trend of water quality‏ ‏in the Karun basin were examined ‎from upstream to downstream. To assess the trend of change, 16 stations with a statistical ‎period of 37 years (1353-1390) were selected. Station scattering was considered to cover the ‎whole basin. In order to analyze the trend, the MK test was performed and according to this ‎test, the discharge has decreased throughout the basin, except for the southeastern part of the ‎basin. Changes in z statistics for the quality parameters were higher at Ahwaz and Shushtar ‎stations located below the basin and at a significant level of 1%. After analysis of the ‎concentration of anions and cations along with the type and facies of water, it was ‎determined that Ahwaz, Gotvand and Shushtar stations have chlorine, Sodic facies and other ‎stations with Bicarbonate and Calcic type. The quality of drinking water in the stations has ‎decreased from the upstream to the outlet of the Karun basin and the worst quality is related ‎to stations in Ahwaz, Gotvand and Shushtar, which are within acceptable limits. In the ‎Investigation of agricultural water quality, also determined Ahwaz, Gotvand and Shushtar are ‎located in the C3S1 and other stations in the C2S1. The results show that the water quality of ‎the Karun basin has decreased from the upstream‏ ‏to downstream.‎

Groundwater is a vital source of water supply in Iran. Sustainable utilization of groundwater is an inevitable necessity. In many watersheds, overexploitation and neglecting the reasonable criteria for sustainable use of groundwater led to groundwater-dependent ecosystems destruction and many other inevitable losses. Due to the importance of this issue and because of the climate conditions similarity between Iran and California State, in this study the Sustainable Groundwater Management Act (SGMA) was analyzed. SGMA introduced six criteria for sustainable use of groundwater. To achieve the sustainable groundwater resources, all watersheds must develop their groundwater sustainable plan based on these six criteria. The primary results of the studies by California Department of Water Resources (DWR) have been shown that in most of the watersheds, the groundwater withdrawal exceeded the minimum threshold. Therefore, a long-term (25 year) program for achieving sustainable groundwater management goal must be developed. In Iran, it is also urgent to define a planned sustainability goal for all aquifers in the watersheds.

The need to simulate rainfall time series at different time scales for engineering purposes on the one hand and lack of recording such parameters in small scales because of administrative and economic problems, on the other hand, rainfall time series disaggregation to the desired scale is an essential topic in water resources engineering. In this study, for disaggregating the Tabriz and Sahand rain gauges time series, according to nonlinear characteristics of time scales, wavelet-artificial neural network (WANN) hybrid model is proposed. For this purpose, daily data of four rain gauges and monthly data of six rain gauges from Urmia Lake Basin for ten years were decomposed with wavelet transform and then using mutual information and correlation coefficient criteria, the subseries were ranked and dominant subseries were used as input of ANN model for disaggregating the monthly rainfall time series to the daily time series. Results obtained by the WANN disaggregation model were also compared with the results of ANN and conventional multiple linear regression models. The efficiency of the WANN model with regard to ANN and multiple linear regression models at validation stage for Tabriz rain gauge shows increase up to 8.5% and 33% and for Sahand rain gauge shows increase up to 13.7% and 26% respectively. It was concluded that hybrid WANN model can be considered as an accurate model to disaggregate the hydro-climatological time series.

In this study, the groundwater level of the Kabodarahang aquifer located in Iran, Hamadan Province is simulated using the MODFLOW, Extreme Learning Machine (ELM) and Wavelet-Extreme Learning Machine (WA-ELM) Models. Analysis of modeling results shows that numerical models simulate groundwater level with acceptable accuracy. For example, the correlation coefficient and scatter index values for the MODFLOW model are calculated 0.917 and 0.0004, respectively. Then, by different input combination and using the stepwise selection, 10 different models are introduced for the ELM and WA-ELM models as different lags. By evaluating all activation functions of the ELM model, the sigmoid activation function predicts groundwater level values with more accuracy. Also, Daubechies2 is chosen as the mother wavelet of the WA-ELM models. According to different numerical models results, the WA-ELM model is selected as the superior model in prediction of groundwater level. For the superior model, the correlation coefficient and Nash-Sutcliffe efficiency coefficient are calculated 0.959 and 0.915, respectively.