فهرست مطالب محمدرضا جرگه

The purpose of this study was to survey the spatial quantities of 22 crop in seven major agricultural crops in 13 major cities of Golestan province and to study its 9-year mean virtual water flow from 2007 to 2015. The priority of crop cultivation was also ranked based on its virtual water values. The results of this study showed that the virtual water of different crops in the cities of the province is different according to the performance. The results of this study showed that rice with virtual water content of 1740 m3 / ton in Ali Abad and Gorgan up to 2840 m3 / ton in Maraveh-Tapeh area had the highest amount of virtual water. Cereals with an average virtual water of 1500 m3 / ton also have high levels of virtual water and Cucurbits and vegetable products with the average virtual water of 100 and 350 m3 / ton have the lowest amounts of virtual water. The results also showed that exports and imports of agricultural products are currently incorrect and Golestan province, despite having a shortage of water, is an average 396 MM3 of virtual water exporter annually, largely driven by exports of cereal and rice products. Ranking the pattern of crop cultivation from the perspective of virtual water also showed that in this province, cucurbits and vegetable crops in all cities are in the top priority and crops such as cereals and rice are last priority.

Unsustainable use of water resources including inefficient irrigation, overexploitation of groundwater resources, damming, evaporating, river piping and pumping, lakes and wetlands shrinking, has become a global problem. Scientists have been studying hydrology without considering the role and impacts of human interventions and the coupling of human-nature effects. But it has been shown later that without it, the investigation of a hydrological cycle would be accompanied by error. For this reason, a novel concept of socio-hydrology was proposed to investigate the two-way coupling of human-water systems. Based on the results of studies and considering the importance of the human role in causing environmental changes, particularly in hydrological responses of basins, it seems necessary to study river basins in the form of socio-hydrology. Therefore, water experts in hydrology, water resources management, sociology, and economics need to become familiar with new interdisciplinary concepts, including socio-hydrology in order to tackle water challenges in river basins. In this paper, in addition to introducing the concept of socio-hydrology, the differences between socio-hydrology, integrated water resources management, and phytosociology are addressed. Furthermore, the different kinds of coupling human-water systems investigation including historical socio-hydrology, comparative socio-hydrology, and process socio-hydrology are introduced. Finally, the challenges that socio-hydrology encounters with; were argued.

Snowmelt runoff plays an important role in providing water and agricultural resources, especially in mountainous areas. There are different methods to simulate the process of snowmelt. Inter alia, degree-day model, based on temperature-index is more cited. Snowmelt Runoff Model is a conceptual hydrological model to simulate and predict the daily flow of rivers in the mountainous basins on the basis of comparing the accuracy of AVHRR and TM satellite images to determine snow cover in Karun Basin. Additionally, overestimation of snow-covered area decreased with increasing spatial resolution of satellite data.Studies conducted in the Zayandehrood watershed dam, showed that in the calculation of the snow map cover, changes from MODIS satellite imagery, at the time that the image does not exist, using the digital elevation model and regression analysis can provide to estimate the appropriate data from satellites. In the study of snow cover in eastern Turkey, in the mountainous regions of the Euphrates River, data from five meteorological stations and MODIS images were used with a resolution of 500 m. The results showed that satellite images have a good accuracy in estimating snow cover. In a Watershed in northern Pakistan in the period from 2000 to 2006, SRM model was used to estimate the snow cover using MODIS images. The purpose of this study was to evaluate the snowmelt runoff using remote sensing data and SRM model for flow simulation, based on statistical parameters in the Kardeh dam basin.
Kardeh dam basin has an area of about 560 square kilometers and is located in the north of Mashhad. This area is in the East of Hezarmasjed – kopehdagh zone that is one of the main basins of Kashafrood. This basin is a mountainous area. About 261 km of the basin is located at above 2000 m. The lowest point of the basin is at the watershed outlet with1300 meters and the highest point in the basin, in the North West part of the basin with 2962 meters above sea level. Kardeh dam was primarily constructed on the Kardehriver for providing drinking and agriculture water demand with an annual volume rate of 21.23 million cubic meters.
Satellite image: To estimate the level of snow cover, the satellite Landsat ETM data at path 35-159, rows 34-159 over the period 2001-2002 were used. Surfaces covered with snow were separated bysnow distinction normalized index (NDSI), But due to the lack of training data for image classification (areas with snow and no snow), the k-means unsupervised classification algorithm was used.
Extracting the data from the meteorological and hydrological Since only a gauging station exists at the Kardeh dam site, the daily discharge data recorded at these stations was used. To extract meteorological parameters such as precipitation and temperature data, the records of the three stations Golmakan, Mashhad and Ghouchan, as the stations closest to the dam basin Kardeh were used. The purpose of this study was to simulate snowmelt runoff using SRM hydrological models and to compare the results with the outputs of the neural network models such as the ANN and the ANFIS model. Flow simulation was carried out using SRM, ANN model with the Multilayer Perceptron with back-propagation algorithm, and Sugeno type ANFIS. To evaluate the performance of the models in addition to the standard statistics such as mean square error or mean absolute percentage error, the regression coefficient measures and the difference in volume were used. The results showed that all three models are almost similar in terms of statistical parameters MSE and R and the differences were negligible.
SRM model: SRM model is a daily hydrological model. This equation is composed of different components including 14 parameters. The input values were calculated based on the equations of degree-day factor. The evaluation of the model was performed with flow subside factor, coefficient and subtracting volume.
After determining the study area, the DEM in GIS software was produced and was divided into 4 height classes with 500 meterintervals based on the basin area. Thus, the hypsometric map of the region with slope and aspect maps wasobtained from DEM. The parameters that were entered into the SRM model included area, the average height of DEM and area of slope directions. Weighted average altitude was about 2007 m in the basin. Height classes of 2000-1500 comprise about 47 percent of the total area, with the highest frequency. The main slope happens in the southwestern region(SE). The results show that the model has properly simulated the daily flow hydrograph at the time of the study period. Factor subtracting volume was modeled based on daily discharge hydrograph at a 17-year period. The best x and y values of the simulated hydrograph for watershed dam Kardeh were respectively 0/79 and 0/084 and finally entered into the model. To evaluate the model for the period of 79-80, the subtracting volume was about 0.21 percent, the regression coefficient was 0.91, the calculated runoff volume was 4/876 million cubic meters and calculated discharge was estimated 0.212 cubic meters per seconds, that indicated a very good agreement with observed values. In addition, it was shown that between the parameters introduced into the model, change of the snow runoff coefficient and the coefficient of flow subsidence have the highest sensitivity, and then two parameters were accurately calibrated, to reach more conformity with ground truth. The results showed that the use of images with high spatial resolution, results in relatively good results in determination of snow-covered surfaces. These results were in agreement with other studies. SRM model is relatively successful so that changes in daily flow modeling provide a better quality. The comparison of the mean absolute percent error between the three models of ANFIS than the ANN model by 40 percent compared to15 percent SRM model has reduced the error of the simulation process and the difference in volume between ANN and ANFIS models were better than the SRM model and the value of this parameter for both models are low.

Water resource management, especially in groundwater, is very important in arid and semiarid regions. Natural and anthropogenic phenomena have caused critical conditions and fall in groundwater table within last decades in many places of country such as Khorasan Razavi Province. Therefore for assessment of falling of groundwater table, Mashhad Plain, which is one of the important and largest plain in province, was chosen. To do this research, 70 piezometers well were studied during 2 ten-years periods (1987-97 and 1997-2007). Statistical data were first collected and arranged. Afterwards, isopieses and classification of groundwater level were performed by interpolation method in GIS environment using geology, topography and mountain-plain limit maps. Also water level hydrograph were drawn in Excel software. The result of classification of groundwater level maps indicated that groundwater table decreased about 30 meters in central and western regions of aquifer. The concentration of exploitation wells with high debits in this region, has confirmed former findings according to the classification of exploitation map. According to hydrographs, groundwater table has decreased to 12.1 meters during 20 years, 60 cm water level fall annually. Drought, overexploitation, growth of population, increase in agricultural lands and increasing number of wells are the most important factors in decreasing of groundwater table.