فهرست مطالب سمیرا میرشفیعی

Surface water resource planning requires estimatiof of water balance components at different spatial and temporal scales. Moreover, due to the inadequacy of the stations in terms of number, dispersion and temporal data recording, numerical modeling of land surface is necessary. In this study, the Noah-MP model was used to compare the simulated runoff by SIMTOP and BATS schemes and to evaluate the dynamic vegetation scheme for estimating actual evapotranspiration in Neishaboor watershed at monthly scale in 2000-2009. Due to low accuracy and dispersion of hydrometric stations, the SWAT model output was used for evaluation. In order to develop the model, first, the sensitivity analysis of the modeled runoff to parameters of model was performed. The model showed the highest and least sensitivity respectively to the soil parameter in the Clapp-Hornberger relation (b) and runoff decay factor (f), respectively. the best and first performance of simulated runoff by BATS scheme were in mountainous areas and the evaluation criteria including R2, NSE and RMSE were respectively 0.81, 0.64 and 1.91. The second grade of performance was for the plain and The lowest values for simulated runoff were in foothills regions. Results indicate that BATS scheme shows better results in the plain and foothills areas and the results of SIMTOP scheme in the mountainous regions were similar to BATS results. The dynamic vegetation scheme has been able to simulate evapotranspiration changes along with the stages of plant growth. the mean of annual evapotranspiration estimated by Noah-MP model was 305 mm.

In many climate studies, land surface models are forced by meteorological data, and there is no attempt to check the quality of the data. The purpose of this study is to evaluation of GLDAS1 meteorological forcing data and application of bias correction method for these data. The weather data corrected will be input into the Noah-MP model in the next study.
Observations for the Neyshaboor Basin have been collected at a temporal resolution of one day during the period 2000–2009 for ten years from fourteen stations and evaporation stations and a meteorological station in the basin. The variables of temperature, relative humidity, short solar wavelength, and air pressure, with correlation coefficients of 0.94, 0.77, 0.74 and 0.6, respectively, were in good agreement with the observations. The GLDAS1 precipitation data for most of this basin is less than observations. The precipitation has been corrected by matching the mean and the coefficient of variation of GLDAS data with observational data. The results of applying the correction method were satisfactory, so that difference in average daily precipitate between GLDAS1 data and observational data was effectively reduced to 0.048 mm. Also, the correlation between the number of wet days (precipitation over 0.3 mm) in the observational data with the corrected data compared to the uncorrected data improved from -1.17 to 0.93 and the first-order autocorrelation in the observational data with corrected data has improved better than uncorrected data and has grown from -2.4 to 0.41. The corrections were the highest during January, February, October, November and December. the bias correction applied seems to correct the precipitation well during May to September.

Conflict over shared water resources has been occured in result of mismanagement,bad governance and increasing water demand. Therefore, equitable water allocation is one of the important tools reducing conflict. In this paper, we investigate application of six methods of bankruptcy theory:Proportional (PRO), Adjusted proportional (AP), Talmud (TaL), Pinile (Pin), Random arrival (RA), Sequential sharing rules (SSR based on PRO). The area study includesfive regions along Atrak riverin Golestan province. Total available water depending on water requirementsof each region is divided with bankruptcy theory. Since each method has different definition of fairness, so different results can be obtained. According to Plurality Rule, it shows that the results of PRO, AP, RA, Pin theories are the superior ones in this case study. Results of this study can be a starting point for negotiations and making agents’ final decision.

The agricultural water price plays a key role in the optimal allocation of water resources، financial independence of irrigation networks، water costs supply and increase water productivity. The main aim of the present study is to develop a multi-criteria fuzzy model for water pricing in irrigation networks. The model was used for analyzing water price of Varamin irrigation command area. For this purpose، thirteen effective criteria on water price of irrigation schemes were considered. The most important steps of the development process included determination of the criteria’s values and normalizing them، computing weight of the criteria، definition of classes and classification، forming membership vector، forming price vector، and combination of the vectors. The results showed that the criterion of irrigation network type، independence of public support، and income per unit of area had the greatest impact on water price. The proposed model estimated the water price of the study area 547. 33 Rls/m3، as well the water price obtained 944. 33 Rls/m3 based on water harvesting cost approach. The findings indicated that the current water price of command area (96 Rls/m3) has a large difference in compare to the developed model and water harvesting cost approach. It is emphasized that there is a major distance between the real water value and the current water price. The multi-criteria fuzzy model with considering the actual conditions of irrigation district، in which almost all criteria have a value less than the ideal value، can accurately estimate the agricultural water price. The water price obtained with the proposed model may be utilized as the real water price of irrigation network، but the requirement frameworks have t be prepared. The proposed model has a desirable accuracy for assessing the effective parameters of water price in irrigation networks and can be utilized to determine the water price of these systems.