Virtual water trade is investigated in industrial, agricultural, social sectors for national and global scales. In this study, interbrain virtual water was evaluated in irrigation sector for the Sefidroud basin to use in the allocation of water resources. In this regard, through investigating eight cropping pattern (S1-S8) in the riverbank of Qezelozan River (provinces of East Azarbaijan, Zanjan) during the years 2001-2025 were evaluated SWAT model. Data of Meteorological, hydrological river and crop yield for the years 2014-2025, were produced using Minitab 17. 0 software through ARIMA time series model. The results showed that cultivating dry-irrigated wheat (S6) is more appropriate in the East Azarbayjan and Zanjan province because of average of virtual water of wheat and rice is 2. 73-3. 24 and 3. 28-4. 06 (m3/kg), respectively. Also, excess water exchange for S6 from East Azarbayjan and Zanjan provinces to Gilan province resulted in to reduce virtual water of rice Guilan province.

The necessity of using discharge data in hydrological designs and regional programming is an unavoidable matter. Unfortunately, malfunctioning of observation instruments, natural disasters and other problems sometimes result in incomplete or missing data. Having of data related to time series is necessary for every investigation about hydrometeorology. Thus missing data should be estimated in a proper way. There are different methods for generation of missing data which estimates the data with regard to particular parameters. In this study, we have used four methods including linear regression, multiple regression, Longbein method and Thomas-Fiering method for reconstruction of hydrometric data including monthly and annual discharge, sediment and water quality data. Results showed that among various methods, in 192 cases of reconstruction of monthly average discharge of 17 stations, Longbein and multiple regression methods in 33% and 27% of the cases have provided the best results, respectively. Two-variable regression in 8 of 17 stations had the best answer and it is suitable for estimating of annual average discharge. Also results indicated that we cannot use of relation between discharge-water quality and discharge-sediment to reconstruct data using above mentioned methods in the Sefidroud basin.

Accurate spatial estimation of precipitation plays a key role in many hydrological modelling, water resources planning and agricultural management studies. In order to estimate high-resolution precipitation in the current research, an estimation model based on PRISM framework considering Digital Elevation Model (DEM) and other spatial attributes is developed and applied to Sefidroud basin during the years 2000-2015. In the first step, the monthly results were compared with modified Inverse Distance Weighted (IDW) as a benchmark method. Considering both models’ degrees of freedom, the parameters are calibrated with Genetic Algorithm in annual time scale and the obtained parameters are utilized to estimate model monthly cross validation error. According to the monthly results, both models had roughly same statistical performance in estimating precipitation at the selected rain gauges. In spite of similar statistical performance of the models, the spatial distribution of precipitation provided by the PRISM based method is more consistent with topographic pattern and existing evidences. In the next step the proposed model’ s ability to estimate mean monthly precipitation is compared with ordinary kriging method and according to the results, in wet months the developed model and in dry months kriging method represents more optimal results. According to small amount of summer precipitation, PRISM based approach is considered to be a better tool for spatial interpolation of precipitation than kriging.

Increasing water demands and insufficient water resources has became the main reasons of raising water conflicts among stakeholders in Sefidroud basin, Iran. Sustainable allocation of water resources with viewpoint of economic efficiency and social equity is necessary to reduce these conflicts which is assessed in this study. Setting the 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 objectives of the model were to maximize the economic benefit efficiency for the development of improved water allocation strategies as well to maximize 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 due to considering economic efficiency and social equity among stakeholders simultaneously. Additionally, two scenarios were defined in terms of the rate of water loss and available water to assess the developed multiobjective 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.

Because of the significant impact of water on economic development, social stability and ecological balance, the allocation of water resources has become a worldwide issue. In this paper, a multi-objective planning model consist of two objective functions was developed for water allocation to maximize the productivity of economical benefit and the equity of water allocation in Sefidroud basin located in Iran. A Compromise Programming method was applied to trade off both the objective functions. The different weights of the objective functions and the definitions of TDS, DSA and DSB schemes were investigated in terms of equity, economical benefit productivity and equity establishment. The results showed that TDS is the best scheme for balancing the target functions. With the except of TDS, surface water allocation and economical benefit do not follow a particular pattern in other weights of target functions, so that decision makers are confused to choose the best weights of the objective functions. Shannon Entropy theory is a suitable solution for selecting the best weights of the objective functions. The results obtained by applying the Shannon Entropy theory showed that the best weights of the objective functions for the productivity of economical benefit and water allocation equity according to the decision maker’ s priority were 0. 35 and 0. 65, respectively. Generally, the results of this study showed that if decision maker’ s priorities were not clear, Shannon Entropy theory and Compromise Programming method could be used to determine the weights of each objective functions in order to make a balance among the objective functions.

Accurate estimation of the re-aerationrate coefficient is very important for the purposes of dissolved oxygen and self-purification modeling in rivers. The main target of this paper is to evaluate 29 commonly used re-aerationrate coefficient prediction equations, in Sefidroud River, North of Iran, as a case study. In this paper, the river’s dissolved oxygen has been modeled involving Streeter- Phelps method. Then the predicted re-aerationrate coefficient results have been compared with four series of collected and measured data of the river. The studied reach of the river has a length of 110km, including 12 water quality sampling stations along that and it is extended from downstream of Sefidroud Dam to the south coast of Caspian Sea.According to the results, among all equations Parkhurst-Pomeroy equation has shown the most accurate prediction of the re-aerationrate coefficient values, with the statistical parameters of Standard Error (SE), Mean Multiplicative Error (MME), Sum of Square of Residuals (SSR) equal to 0.51, 1.05 and 2.35, respectively. Moreover, results indicate that the river has a high Biochemical Oxygen Demand (BOD) and also, a low Self-Purification capacity, during September, which is simultaneous with the seepage of nonpoint drained agricultural pollutions.

Sediment deposition in reservoirs is inevitable and the turbidity current is one of the most important factors that affects sediment distribution in reservoirs. Knowledge about the turbidity currents properties can help to manage and release these currents from dam reservoirs. The Sefidroud dam reservoir has many problems on water storage due to sediment deposition. In this study, the properties of these currents including head velocity, plunge point depth and its distance from the dam are simulated by TCM model, in different discharges and water elevations of the Sefidroud reservoir. The results show, depending on the discharge and water elevation, plunge point depth changes from 2.2 to 8.3 m, its distance is between 6-11 km from the dam structure and the head velocity variation is up to 0.48 m/sec.

The objective of this research is to investigate the accuracy of Qual2kw software in simulating the quality parameters of Sefidroud River at the bottom of the dam. For this purpose, sampling and conducting laboratory studies for 12 stations in the range of 110 km in two summer seasons (August) and autumn (November) in 1398 has been done. In this study, Qual2kw software to simulate the eight main parameters of water quality including water temperature, pH, electrical conductivity, total suspended solids, soluble oxygen, biochemical oxygen demand, total nitrogen and total phosphorus, for August and November 1398, respectively, measured and verified Is. The results showed that the highest and lowest accuracy of the model with average NRMSE values in two stages is equal to 3. 3 and 47. 5% for pH and total nitrogen parameters, respectively. The highest correlation values between the measured and simulated values for the parameters of total solids and electrical conductivity were 0. 97 and 0. 96, respectively, in the model calibration stage. The results of the present study indicate the appropriate capability of Qual2kw model to model water quality parameters of Sefidroud River. The results of the present article indicate the appropriate accuracy of the Qual2kw model in order to simulate water quality parameters in the Sefidrood River, which is in accordance with the results of Aryan, Nejad et al. (2015). It should be noted that the hydraulic properties of the flow affect the amount of dissolved oxygen in the Sefidrood River more than changes in the quality of other parameters.

Due to the important values of Sefidroud as the most important and valuable drinking water source, agriculture, and aquatic environment in Guilan province, the study of water quality of this river is necessary. This research has been done with the purpose of studying the quality and the potential for self-purification of this river in Roudbar and also its quality status for drinking water, hygiene and agriculture. For this purpose, the water quality changes during the months of February, 2013 to January, 2014 (12 months) has been measured in four different stations along the river. The total number of 48 samples has been taken monthly.After the analysis of the obtained data and the calculation of the water index, the best water quality index in the discharging station of Sefidroud Dam has been observed in February with the amount of 84 and the worst water quality index was 58 in Ganje Station in October. The mean of WQI in Sefidroud in studied area was 69.19, which was in the mid-range. Also, from the discharging station to the station near the Tarik Dam, a visible quality loss was observed due to entering a high amount of different types of sewage into the water. This actually makes this water inappropriate for drinking and agriculture. The river has lost its potential for self-purification in downstream stations and also has increased its pollution.

The Sefidroud River is the largest river in the north of Iran and has a special importance in the survival of Caspian anadromous fish. In this study, the biodiversity and abundance of fish were investigated in eight points of the Sefidroud River and one point on the sea coast from March 2022 to January 2023. There were identified a total of 40 species of fish from various ecological groups; riverine (26 species), migratory (6 species), and estuarine-marine (8 species). The highest and the lowest number of species were observed in the mid-region of the river and the marine area with 21 and 17 species, respectively. The spatial ecological niche was observed for some species such as three Gobiidae species Caspian goby (Neogobius caspius), Caucasian dwarf goby (Knipowitschia caucasica), and Iranian Goby (Ponticola iranicus) occupied the sea coast, the estuary, and the upstream area, respectively. Mugilidae species were also seen up to 10 km from the sea. The eggs and larvae of anadromous fish were observed in the highest station. Kutum (Rutilus frisii) and Danube bleak (Alburnus chalcoides) fry fish had the highest abundance among the identified species of with 222 and 92 number/200m2, respectively. Bream (Vimba persa), Leaping mullet (Chelon saliens), European bitterling (Rhodeus amarus), Sanias spined loach (Cobitis saniae), North Caucasian bleak (Alburnus hohenackeri) had moderate frequency between 27 to 59 number/200m2 and the abundant of other species was low between 0.014 to19 number/200m2. The lowest Shannon's diversity index was in the furthest distance from the Caspian with value 1.03, while the highest value, with significantly difference p<0.05, was observed in 5 km to the sea with value 1.6  Also, the highest and lowest values ​​of the index were observed in November 2022 and January 2023, respectively.