IRAN-WATER RESOURCES RESEARCH
Year:2018 | Volume:14 | Issue:3 |Papers Count:28

Flood has become a serious issue over the past decades, due to urban development and climate change and international interest in flood forecast has increased subsequently. On the other hand, due to the fact that the main cause of the flood is precipitation, its precise prediction in hydrological applications is important. This study evaluates the predicted rainfall data of the global numerical models of the TIGGE database and their improvement using bias correction for Karun Basin. Meteorological assessments were carried out in point and regional scale and the estimation of displacement error, volume and spatial pattern of precipitation of the models were performed using the CRA Object Oriented Method. At the next step, the predicted precipitation was improved using quantile mapping method. In assessing the initial data of the TIGGE database of global models, the ECMWF numerical model was dominated compared to other models in the point and region evaluation with respect to the indices compared, while CMC model had a poor performance compared to other models. The evaluation of biased correction data by quantile mapping method also indicated an improvement in evaluation of the indices compared to the results obtained without applying this method. Furthermore, in estimating the displacement error, the volume and spatial pattern of the global numerical models, the ECMWF, NCEP, and CMC models performed better than the UK model, respectively.

One of the most important steps in planning and implementation of integrated water resources management is water resource system assessment. To do an integrated assessment, system problems and cause and effect relationships should be detected and defined. But since different levels of assessment, specially the strategic level, is generally ignored, the cause and effect relationships are not properly defined which may result in problems in modeling and policy making, and finally in system management. In this paper to do an integrated assessment of water resources systems in a strategic level, Goal Oriented Framework (GOF) is applied. GOF includes scale, domain, dimension, generic theme, theme, and sub-themes. Considering all these parts, the cause and effect relationships are defined and the indicators are developed. The south Khorasan province is considered as a case study. The indicators are determined using statistics and then the trend of each indicator is studied. The results showed that although the increased withdraw has occurred in agriculture sector, the production and the value added per unit of cultivated area had a decreasing trend. This means that the surplus water withdrawal was used to increase cultivated areas, while the efficiency was decreased inspite of the prospects. It was noticeable that the agricultural policy was to increase the orchard area where the indicators showed that the efficiency of orchards was decreased. The consequences of these problems were noticeable in economic and social sectors, so that the agricultural sector employment has decreased and rural-urban migration has occurred.

This study investigates the Buffer area of Lake Uremia main southern streams including Siminehroud, Gadarchay and Mahabadchay as south western streams, Zarinehroud and Mardoughchay as southern streams and Ghalechay and Soufichay as south eastern streams. Buffer zone area is located between maximum extent and daily extent of Lake Uremia which is selected as the study area. The study is done based on images from 143 days in the year 2010 in which the buffer area and the extent of the southern streams were not cloudy. Using available data from Bonab meteorological station and tail-end hydrometry stations, changes of the Buffer area were analyzed. The aim of this study is to determine the daily variations of the river flood plains in the southern buffer zone of Uremia Lake. Temporal Analysis of flood plains showed that from late May, most southern feeder streams got dried. Also, the analysis of time-discharge charts have shown that similarly the registered discharge at terminal hydrometry stations is recorded as zero. Also, analysis of discharge-time graphs showed that prportionable to dried flood plains, registered discharge in tail-end stations became zero. Results of investigation of daily precipitaton showed that effective rainfall occured in the first 135 days i. e. from early February to Early June, and during summer the daily precipitation is decreased proportionable to discharge and floodplain. Based on the study findings, southern streams including Zarinerood and Mardoogh-chaii rivers, was more stable than the two other western and eastern streams and were connected to the lake in the total duration of 143 study days.

Iran, with an arid and semi-arid climate, is one of the countries facing serious water problems. Obviously, in order to cope with this crucial environmental issue, the proper approach in decision making and implementation is very important, as it may be impossible to have other opportunities to compensate the mistakes. Policy-making as the first stage of decision-making for management and problem solving is based on some basic principles, and disregarding these principles in policy formulation can greatly affect implementation and operation of the plans. Policy coherence is one of the most important principles in sound policy making today among policy makers. This research is focused on identification of the policy coherence factors in Iran's water domain and thier relations. Due to the qualitative nature and exploratory approach of this research, the "Grounded Theory" method is used for this purpose. Repetition of concepts occurred and sampling was saturated after 22 open and deep interviews with Iranian water experts. Based on a theoretical sampling carried out based on the Grounded Theory, 231 primary codes, 69 secondary codes, 29 concepts, 23 categories or sub categories, and finally 8 main categories were extracted. The main issues that were extracted were identified as policy coherence generators in Iran's water domain, and after selective coding, a pattern of relationship between these factors was also presented. Finally, using the Interpretive Structural Modelling (ISM) Technique, the extraction pattern was evaluated and the factors were ranked. Reforming the Water and Agriculture Policy institution in order to formulate, manage and monitor the implementation of efficient policies was identified as the most important factor.

In this study the Best Management Practices (BMP) and Low Impact Development (LID) were employed to optimize the management and control of urban runoff. The hydraulic and hydrological models of urban runoff were simulated by the Storm Water Management Model (SWMM) and combined with None-dominated Sorting Genetic Algorithm (NSGAII). Three objective functions were defined as: minimizing the cost of BMP (Investment) in dollar, minimizing the runoff volume over the catchment in m3, and minimizing the pollutant load at external node. The urban catchment studied was part of the northeast of Karaj city namely Azimiyeh located in Alborz Province. In order to achieve more accuracy, the catchment was splitted into 67 sub-catchment using ArcGIS software based on the urban stream network. In this research five types of LID-BMP structures with various types and areas were defined into NSGAII. The NSGAII presented a proper combination of LID-BMP structures considering land use of the 67 sub-catchments and produced suitable solutions. Finally, seven scenarios were defined to assess the NSGAII. The results showed that by applying the solution obtained by NSGAII for the study area, the quantity and quality of flood decreased by 41% and 23%, respectively. Also, the use of LID-BMP structures in separated form, could only fulfill one of the objective functions but did not resulted in any optimal choice. The use of LID-BMP structures in combination form with appropriate area had a better performance compared to separated mode. Moreover, higher cost did not result in more efficiency, especially in the flood quantity. In addition, with reducing the amount of flood, pollution was not always reduced and depended on the type and area of the BMP.

Sustainable management of water resources in various basins depends on accurate estimation of water balance. Reviewing literature of water balance models reveals that most published works are focused on hydro-climatologic water balance models, which consider aquifers like tanks with one or two soil layers. These models use empirical equations to calculate the effects of groundwater on hydro-climatological water balance. In this study, we have tried to advance previous studies by linking previously developed hydro-climatological and groundwater balance models. In the developed model, the aquifers were modeled more accurately in water balance model by using the tank-model approach. Optimizaing the parameters of the joint water balance model is an important step for achieving proper water balance model performance. In order to assess the performance of the recommended model, hydro-climatological and groundwater water balance in Neyshabur and Rokh plains were modeled for a nine-year period. The results proved that the proposed approach can be used for modeling water balance of other basins in the country. Although distributed modeling is suggested which allows considering interactions between surface water and groundwater resources.

In this study, the possibility of snow estimation using the snow-rain phase separation models which usually is integrated into the snowmelt models or in the numerical weather prediction (NWP) models are evaluated for the Zagros region, Iran. For this purpose, daily precipitation (rain and snow) and temperature data from 36 weather stations distributed over Zagros having data records over the period 1951-2015 is used. The performances of the snow-rain phase separation models in accurately predicting the phase of precipitation at the studied stations were evaluated through constructing contingency tables between predictions and observations, and eventually evaluating the results using a set of statistical skill scores. A statistically significant relationship was found between the phase of precipitation predicted by the models and the snow occurrences observed at all selected stations. The USACE, Pipes and Quick, Hyperbolic tangent function and Kienzle were found as the best models, while the Mccabe and Wolock model and the Brown model resulted in the weaker predictions based on the maximum and minimum temperature. The snow-rain separation temperature threshold at the selected stations varied from-1. 7 to 5 degree Celsius, nonetheless, between 0 and 2 degree Celsius in more than 75% of the stations. It was also found that the temperature range within which both snow and rain can occur simultaneously varies among stations, but in most of the stations it is between 9 and 13 degrees Celsius.

Water problems and issues due to droughts and over-exploitation brought up the importance of developing Research and Executive Fields on water resources protection and farmers’ water protective behaviors. Present study aimed to analyze farmers’ water protective behaviors in Khorram-Abad County using survey technique and questionnaire for gathering data form 310 samples. These samples were collected from the statistical population of the active farmers in Khorram-Abad County during 2016-2017 i. e. 22812 persons. The questionnaire validity has confirmed by 4 members of the Agricultural Extension and Education faculty at Shiraz University. The reliability of the questionnaire has assessed by a pilot study with 30 samples outside the statistical population. Results showed that the mean of protective behavior variable is 1. 02 (in range 0-4) which implied low water protective behavior among farmers. Also, the results based on path analysis showed that variables such as behavioral tendency, awareness of protective behaviors’ desirable effects, following rural models and leaders, access to water information resources, and technical knowledge of water protection have direct effect on water protective behavior while variables such as moral values, moral reasoning, awareness of water laws and agricultural income have indirect effect on such behaviors. Totally, these variables could predict 57 percent of the changes in farmers' water protective behaviors. Therefore, solutions such as increasing farmers’ awareness to protective behaviors’ desirable effects, technical knowledge of water protection, activating the potential of rural models and leaders for extension of water protective behaviors, improving moral judgment and diffusion of moral values related to water consumption can lead to extend protective behavior among farmers.

The main purpose of scenario as a tool for planning is to increase the efficiency and quality of planning in respets to the uncertainty of the future. One of the practical strategies in this field is to identify the key factors of the future studies. The present study dealt with the effects of water transfer from Sirvan River to tropical areas of Mehran County in Ilam province (as part of the Garmsiri Project). The research is categorized as practical in terms of purpose, as combinational (documentary and scrolling methods) in terms of methodology, and as analytical and explorative in terms of its nature. The study is based on new approaches to future studies which use a combination of quantitative and qualitative models. Due to the nature of this research, Delphi methods and structural analysis has been used. The researchers tried to provide a model for identifying the key factors affecting the spatial-temporal changes in a regional scale, as well as a ground for developing scenarios for the future of locational-spatial evolutions due to the implementation of the water transfer system. The data of this research consisted of 30 factors that Delphi methodology used to collect the views of the planning experts active in county’ s development and water affairs. The data were analyzed with the help of MicMac software which finally presented 13 factors of locational-spatial changes as mass media, population and migration, employment creation, investment security, income developments, demand and sales market, productivity, rural infrastructure, border security, cultivation area, agricultural machinery, production capacity, new settlements, and improvement of the physical texture of villages. The probable state of these factors was formulated for the horizon of 1408 (Iranian Calendar) which is, ten years after the full implementation of the Garmsiri water transfer system.

Prediction of drought is a main challenge even for those countries with dynamic monthly prediction modeling systems. In such meteorologically advanced countries, prediction of monthly precipitation through dynamical methods is the first step in prediction of drought indices such as SPI and SPEI. Since southwestern basins of Iran including Great Karoon, Jarrahi and Zohreh have significant contribution in providing water for agriculture, drinking, industrial and hydropower demands, so having a seasonal prediction of precipitation and drought is of vital importance for management of water resources in these basins. In this study, the raw output of CFSv2 seasonal forecast model were calibrated in the base period and then monthly precipitation forecasts for the next three months were corrected based on the monthly derived equations. The corrected monthly precipitation was used for three months SPI forecasts. Observed precipitation corrected by APHRODITE dataset and historical forecast were used for calibration. Results showed that the highest efficiency of drought forecast with 81. 5% were occurred in the case of normal precipitation condition over the basin. Efficiency of the drought forecast were respectively 62. 3 and 42. 3 percent for the precipitation in in wet or drought conditions. Taking into account the frequency of observed drought events for normal, wet, and dry cases which were 76. 4, 12. 5 and 8 percent, respectively, the overall skill of SPI index were found to be 73. 4 percent.

The concept of eco-efficiency is used as a tool to analyze farm sustainability to relate economic value of an activity to its impact on the environment. The practical concept of eco-efficiency is used according to the method of irrigation, the conveyance of water in agricultural fields, the environmental effects of crop productions and the economic value of the crop yield. SEAT and EVAT software are two modeling tools which combine both economic and environmental viewpoints into a single modeling framework and allow the user to evaluate the water consumption system. In this research, the eco-efficiency index with regard to the environmental impacts of diesel fuel was evaluated in one of command areas in Sefidroud Irrigation and Drainage Network. The agricultural lands in this area include paddy rice, tea-garden, and fish-culture ponds. The environmental performance of the system was evaluated for climate change due to greenhouse gas emissions from diesel consumption while the economic performance was measured by using the total value added to the system's final products in relation to the water used and the adopted management practices. Then, the vulnerability of the area was assessed according to eco-efficiency index of climate change. The results showed that the eco-efficiency index in the baseline for paddy rice, tea-garden and fish-culture were calculated as 3. 46, 0. 76 and 0. 02 Million Rials/kg CO2 eq, respectively. The results showed that eco-efficiency indicator for scenarios 3 (where the paddy rice percent of irrigation efficiency and return flow recycling were considered as 63% and 5%, respectively) and 4 (by replacing 50% of diesel engines with electric motors in fish farming) were increased respectively by 17 and 86% overall in F1 unit, in comparison to the base scenarios. Therefore, to improve the eco-efficiency indicator concern should be given to the management of the agricultural water system, replacement of the diesel engine pumps with electric pumps for groundwater abstraction, adopting new water pricing policies, and increase in the degree of agricultural mechanization.

In this study, to evaluate the effects of climate change on temperature, precipitation and future droughts in Shadegan Basin, output of the MPI-ESM-LR, BCC-CSM1-1 and NORESM1-M general circulation models under diffusion scenarios RCP4. 5 and RCP8. 5 is used. The outputs of general circulation models are downscaled using LARS-WG software. To evaluate the drought, the standardized precipitation index (SPI) was used for the base period (1986-2005) and future period (2020-2039) in time scales of 6, 12 and 24 months. The results showed that the maximum and minimum temperature in Shadegan Basin were increased in all months of the future period under RCP4. 5 and RCP8. 5 scenarios. Precipitation changes do not show a general increasing or decreasing trend. The results showed that under RCP4. 5 scenario and in 6, 12, and 24-month time scales, respectively 17. 16, 14. 70 and 18. 74 percent of all months in the future period would be dry. In addition, under RCP8. 5 scenario and in 6, 12, and 24-mont time scales, respectively 16. 45, 17. 03 and 15. 21 percent of all months in the future period will be dry. Under RCP4. 5 and RCP8. 5 scenarios, the number of dry months in the future period compared to the base period will respectively increase by 2. 27 and 1. 56 percent in 6-month time scale, decrease by 2. 77 and 0. 44 percent in 12-month time scale, and decrease by 2. 00 and 5. 53 percent in 24-month time scale. So under the climate change condition in future period, it is expected that the number of drought months is less than the number of months with normal and wet conditions.

This study assessed the satellite rainfall data as input for developing a reliable rainfall-runoff model to provide information for early warning flood in the Voshmgir Dam basin in Iran. Two satellite based rainfall estimates (TRMM and PERSIANN) were assessed to evaluate which rainfall product better represents the actual rainfall pattern and intensity of the basin. After evaluation based on statistical parameters such as the Root Mean Square Error (RMSE), Mean Average Error (MAE), Mean Bias Error (MBE) and Correlation coefficient (R2), TRMM were selected for rainfall-runoff simulations. Among six years of available discharge data from 2002 to 2007, period of 2002 to 2004 was used for calibration whereas data from 2005 to 2007 were used for validation. In additional to continuous daily rainfall-runoff model development using HEC-HMS, an event based flood model was also developed. Also simulations based on daily TRMM versus 3-hourly TRMM were compared to evaluate the effect of input time-step on the results. Results showed that the deficit constant loss method successfully predicted gauged catchment runoff and peak flows for calibration (NSE= 0. 413, R2=0. 482, RVE=-0. 246 %) and validation (NSE= 0. 621, R2=0. 670, RVE=-0. 329 %) periods. Also the developed model estimated the rainfall-runoff process for the monthly or longer time scales better than the daily scale. In addition, the event based HEC-HMS model developed using TRMM data with shorter time steps (3-hourly) showed good capability to simulate daily peak discharges. The study demonstrated the suitability of HEC-HMS for continuous runoff simulation in a complex watershed. Therefore, this work will have a significant contribution for the future development of water resources programs in this catchment in particular as well as in other data-scarce catchments.

The prediction of snow cover is fundamental for runoff prediction in terms of the snow melting role. The purpose of this study was to assess the feasibility of using snow cover output of the WRF numerical prediction model in order to predict snow melting. Since there are a few snow monitoring stations in the mountainous areas of Iran, satellite data were the only widespread observation data. Accordingly, the extraction of snow cover data using MODIS sensor was addressed. Afterwards, the data was compared to the snow cover of the WRF model outputs for a case study. Finally, the results were assessed using the probability table. The studied area is located on Chalous Road, Alborz province, and the study was made for the period of January 28 to January 30, 2017 with heavy snowfall. Synoptic analysis indicated a strong pressure gradient in surface level associated with cold air in the middle layer of the atmosphere. Overlapping of satellite snow cover data with model output showed the linear correlation coefficient 0f 0. 7 at a significant level of 0. 01 in a 90 × 78 points network with 5 km resolution. The probability of detecting snow on 3 day average was 87% and the probability of false detection was about 20%. Heidke Skill Score was about 0. 7 for days with clear sky (January 29th and January 30th. ) which was the best result in January 28th. The Heidke Skill Score was reduced to 57% which may be the result of inaccurate satellite observation due to cloudiness or inaccurate forecasting. Since there is no ground station in the selected area, one cannot properly comment on this.

In this study, the water balance component of the Palmer Drought Severity Index (PDSI) was replaced by the Atmosphere-Land Surface Interaction Scheme (ALSIS) and the modified Palmer Drought Severity Index (AL-PDSI) was compared with the self-calibrating version of Palmer Drought Severity Index (SC-PDSI). The evaluation of drought indices in Karkheh River basin for the period of 1983-2011 revealed more severe droughts reported for certain duration by the AL-PDSI in comparison with the SC-PDSI. The AL-PDSI could capture seasonal variations in relative frequency of droughts. Moreover, the relative frequency of mild, moderate, and severe droughts for the AL-PDSI were higher compared to SC-PDSI. However, the AL-PDSI and SC-PDSI did not show a remarkable difference in terms of the correlation with vegetation and soil moisture variations. The more physical mechanism of AL-PDSI helps in more comprehensive understanding of drought characteristics and in studying the effects of climate and land use change scenarios on droughts.

This paper deals with developing a hydro-economic simulation-optimization model for optimal design of water resource development projects and policies of Helleh (Shapoor-Dalaki) River Basin, located at south of Iran, over a long-term planning horizon. We employed Particle Swarm Optimization (PSO) coupled with a simulation model which is a combination of WEAP water allocation software and three computational modules for soil and water salt routing at basin scale, crop yield production, and economic analysis. Finally we applied the developed simulation-optimization model to optimize infrastructural projects and measures, e. g. construction of dams and irrigation districts and utilization of modern technologies, and also operation policies, e. g. irrigation and leaching strategies, reservoir rule curves, and water allocation priorities. Model application results suggested construction of Chorom, Dalaki and Nargesi dams with normal water volumes equal to 43. 5, 305. 5 and 76. 8 million cubic meters, respectively. In spite of economic efficiency of the optimal solution achieved (18% enhancement of net benefit), the associated economic value of water was reduced with respect to business-as-usual condition. Also optimal irrigation and leaching strategies led to 35% reduction in total gross irrigation requirement under development condition.

This study examined Urmia aquifer in respect with changes in the concentration of Uranium (U) in three different periods, and the mechanisms of speciation, distribution, and potential sources of uranium in the groundwater resources. The results showed that the U content is generally more than 1 mg/kg in igneous and metamorphic rocks and typically 2– 5 mg/kg in sedimentary rocks. Uranium concentration in all groundwater samples were below the maximum levels in drinking water recommended by WHO, USEPA, and Iranian standard (30 ppb). The spatial distribution of U indicated that the maximum concentrations of U can be found in the vicinity of igneous rocks. Investigation of uranium speciation in this aquifer for three consecutive sampling periods showed that Uraninite (UO2) is the dominant species in Urmia aquifer in all three periods. The inverse geochemical modeling of groundwater samples clearly demonstrated that all samples were under-saturated in respect with all uranium species. Based on the results, the mobility of uranium in groundwater is controlled by some factors such as Eh, pH, and concentrations of coexisting dissolved ions. In general, the three main mechanisms for controlling the mobility or deposition of uranium include desorption of uranium absorbed onto ferric minerals (e. g. hematite and goethite), desorption of uranium adsorbed onto clay minerals, and the release of uranium from the carbonate lattice structure due to replacement with calcium.

There are many springs in Iran contaminated by arsenic and therefore not suitable for drinking purposes. Garu spring around Masjed Soleyman city is an indicator of such springs. In order to study the concentration of arsenic, 20 samples were collected from the spring and Asmari anticline observation wells. Concentration of major and trace elements (i. e. As, Fe, Mn, Ni, V, and Li) in the samples were measured. ICP-OES studies were carried out on 3 samples of the surrounding formation. The results showed that Garu spring has arsenic levels higher than 10ppb. Hydrochemical and statistical analysis of water samples and sediment as well as significant correlation of arsenic with main cations (i. e. Nickel and Vanadium) showed that anthropogenic factors do not have an effect on the amount of arsenic. It is found, that the origin of arsenic is geogenic (Gachsaran formation and oil brine influx). The mechanism of arsenic mobility during wet season is the anaerobic respiration of Fe+3 reducing bacteria, whereas, in dry season, the environment is further reduced and as a result the activity of the SRB and IRB in the span of springs leads to the reduction of iron by sulfide from sulfate respiration, which causes arsenic deposition.

Dissolved oxygen in rivers is one of the most effective parameters in determining water quality and its control is one of the most important factors in development of water resources in each region. For this reason, we investigated the performance of wavelet neural network models, support vector machines, and gene expression programming for estimating the dissolved oxygen in Cumberland River in Tennessee. The indicators of the Cumberland River, including DO, flow rate and temperature during 10-year period (2006-2016), were simulated in monthly time scale. Also for evaluation and performance of the models, the correlation coefficient, root mean square error and mean absolute magnitude error were applied. The results showed that integrated input structures into models in all three models offer better performance than other structures. Also, the results of the evaluation criteria showed that the wavelet neural network model showed the highest correlation coefficient (0. 960), lowest root mean square error (0. 668), and the lowest mean error magnitude (519. 0). In general, the results showed that due to the high ability of the wavelet neural network and the elimination of time series noise in the estimation of river water quality parameters, this model could be a suitable and rapid solution for water resource quality management.

In this study, a combination of SWAT and WEAP models were utilized for planning and integrated water resources allocation management in Hablehroud Basin. The SWAT model was calibrated and validated using the monthly discharge at the basin outlet in the period of 1998-2012. In validation phase, the coefficient of determination, the Nash– Sutcliffe efficiency coefficient, root mean square error, and model efficiency were calculated as 0. 80, 0. 71, 1. 81 and 0. 89, respectively. These values suggested that the model performance can be classified as “ good” . To simulate the supply and demand in the basin and to assess different management scenarios, the estimated flows produced by SWAT for each subbasin were considered as the input for the WEAP model and the percentage of met demand in the present situation (reference scenario) for each demand node was obtained. The results showed that the agricultural lands of Firoozkouh and Garmsar irrigation and drainage network are facing a shortage of water, especially in the warm months of the year. Therefore, scenarios such as changing cropping pattern, reducing crop area, reducing water per capita in urban and rural demand nodes, increasing irrigation efficiency, and combined scenarios were considered to balance the supply and demand of water. The results showed that water consumption reduction and striking a balance between the supply and demand in the basin can be better achieved if simultaneous use of different water management strategies (increasing irrigation efficiency, per capita reduction, and crop pattern change) are to be considered in the basin.

The regional water markets as economic instruments, promote the development of decentralization and optimal allocation of water resources among farmers. For this purpose, in present study the effects of forming regional water markets in Sistan region were investigated and the potential of irrigation water transfer under stressed irrigation conditions in the region were analyzed. For this purpose, an economic-hydrologic modeling system was employed comprising of positive mathematical programming (PMP) model and constant elasticity of substitution (CES) production function approach. The data and information used for this research were cross-sectional and related to the 2015-2016 crops which were collected from relevant authorities in Sistan region. The presented economic-hydrologic modeling system was solved in the GAMS 24. 1 software. The results showed that with establishment of the regional water markets in Sistan region, in addition to the supply-demand balance for irrigation water and equilibrated water trading among the studied regions, the acrage of wheat and barley was increased and the acrage of alfalfa, onion, watermelon and melon was decreased compared to the conditions without water market. This result provided the possibility of lands development up to 23. 4 percent compared to the base year conditions. The farmers’ total net profits were also improved under conditions of establishment of regional water markets and changed from 22039 to 23242 million rials. It is suggested that the supportive and constructive role of regional water markets, provids the required grounds to establish and optimally use this mechanism in Sistan region and other regions in the country where shared water resources is being used.

Modeling of the relationship between physical characteristics of a catchment and water quality parameters plays a significant role in integrated watershed management. There is always an inevitable level of uncertainty in the process of such modeling caused by errors in the input data, parameters, and the structure of the model. Therefore, quantifying the uncertainty in the output of the model is essential in order to reach certain forecasts in modeling. In this research, water quality data, land use/land cover, land suitability map and geological map of catchments discharging to hydrometric stations located in the western part of the Caspian Sea were used. The modeling was done using Multiple Linear Regression Stepwise Method, while the model uncertainty analysis was examined using Monte Carlo simulation. Based on the results of the correlation and regression analyses, it could be concluded that all these parameters have a strong positive correlation with a variety of human activities such as agriculture and urban development. This indicated that an increase in agricultural land or a decline in forest areas will ultimately lead to a decline in water quality. The results of the Monte Carlo simulation showed that although some models had high R-squared values, the possibility of negative outputs (Pr<0) generated by the model was also approximately high (merely positive values make sense regarding the water quality variables). Moreover, the visual assessment of the CDF curves implied that models of Ca2+, Mg2+and EC had higher uncertainty in predictability compared to Na+.

The present study aimed the evaluation and zoning the evapotranspiration based on mass transfer methods in different climates of Iran and presented it in the form of zoning maps as a basic tool for water management. For this purpose, the long-term means of climate variables were used for 150 synoptic stations in Iran during 15-years of statistical period (1990 to 2013). De Martonne method was used for climate zoning in different parts of the country. The results of the study showed that dry, semi-arid, Mediterranean, semi-humid, moist, and very humid climates were covering 75. 7, 21, 0. 8, 0. 6, 0. 8 and 1% of the country's land area. Evapotranspiration of the reference plant was calculated based on the climatic information of each station using the methods of mass transfer including Dalton, Trabert, Meyer, Rohwer, Penman, Albrecht, Romanenko, Brockamp and Wenner, World Meteorological Organization, and Mahringer. The most appropriate and inappropriate computational methods in each climate were selected among the abovementioned methods, compared to the FAO-Penman-Monteith equation as a reference method. Based on the calculations and statistical analysis conducted for dry climates by the World Meteorological Organization and Albert, the semi-dry methods of the Meyer and Romanenko, Mediterranean methods of the World Meteorological Organization and Albert, the semi-wet and wet methods of Rohwer and Romanenko methods the very humid methods of Brockamp and Wenner and Penman were chosen as the most appropriate and inappropriate methods respectively. Meanwhile, the resulting lysimetric data confirmed the selection of suggested methods in a semi-arid climate.

In recent decades, drought and weak management of water resources has caused many lakes and wetlands to enter critical conditions. Surface water level prediction, although an important and complex hydrological process, is vitally required for better management and improvement of such ecosystems. In this research, four soft-computing techniques including Wavelet Artificial Neural Network (WANN), Artificial Neural Network (ANN), Adaptive-Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) were used to predict 2-month water level fluctuations of Zarebar Lake. The predicted water levels in each technique were compared with observed data and statistical indicators; RMSE, MAE, and R2, were used to evaluate the performance of each method. The results proved that WANN performed considerably better and its prediction was more accurate followed by ANFIS, GEO and ANN, in regards of accuracy corresponded to observed data. The selected technique in this research can be recommended for prediction of the water levels in lakes and wetlands with significant accuracy.

In this study, effects of climate change on thermal stratification of Latian Dam Reservoir have been evaluated in the period of 2020-2039 and the water temperature in the reservoir has been simulated for this period. For this purpose, temperature data, precipitation, wind speed and dew point from two general circulation models of MIROC-ESM and EC-EARTH were used under RCP8. 5 scenario. The results of the two models in scenario RCP8. 5 showed that the air temperature in the upcoming period increases by 0. 31 degrees, mean annual precipitation decreases about 8. 6 percent, and the inflow to the dam increases about 2 percent compared to the baseline period. The simulation results by two-dimensional model of CE-QUAL-W2 in the period of 2020-2039 showed that under the impact of climate change, thermal stratification period increased by 28 days and depth of the thermocline is decreased. Also, the mean value of temperature has increased by 0. 14 0C in epilimnion and has decreased by 0. 08 0C in hypolimnion. The obtained results can be applied for more effective water quality management of reservoir under the climate change effects.