Sharif Digital Repository

Rainfall characteristics, which include spatial variability, exert a major influence on runoff properties. Many techniques have been proposed for determining the spatial distribution of daily rainfall. One of these techniques is spatial modeling, based on rainfall data measured by rain-gauge networks. In this study, application of different interpolation methods in the GIS environment, for estimating the spatial distribution of daily rainfall in the southwest of Iran with low rain-gauge density, have been compared on a regional scale. The cross validation technique was selected as an accuracy index and statistical parameters, such as MAE (Mean Absolute Error) and MBE (Mean Bias Error), were... 

Digital Elevation Models (DEMs) play a significant role in hydraulic modeling and flood risk management. This study initially investigated the effect of Unmanned Aerial Vehicle (UAV) DEM resolutions, ranging from 1 m to 30 m, on flood characteristics, including the inundation area, mean flow depth, and mean flow velocity. Then, the errors of flood characteristics for global DEMs, comprising ALOS (30 m), ASTER (30 m), SRTM (30 m), and TDX (12 m) were quantified using UAV DEM measurements. For these purposes, the HEC-RAS 2D model in steady-state conditions was used to simulate the flood with return periods of 5- to 200 years along 20 km reach of Atrak River located in northeastern Iran.... 

Urmia Lake River Basin (ULRB) is one of the most important habitats in the world and one of the major agricultural regions in Iran. On average, the ratio of irrigation to evapotranspiration in this basin is more than 73%. Investigating the irrigation water requirement pattern changes and the spatial distribution of evapotranspiration during the basin development period on a regional scale play important roles in understanding the basin situation. In this study, the actual evapotranspiration has been estimated by SEBAL model. By estimating the precipitation distribution in the basin, the agricultural irrigation water requirement pattern has been calculated using the land use map in 1995, 2010... 

In this study, a coupling of a hydrologic and hydraulic model was utilized to assess the impacts of river geometry data resolution on the flood inundation characteristics in a data-scarce environment. Hydrological modeling incorporates soil conservation service curve-number (SCS-CN) and the geomorphologic based instantaneous unit hydrograph model (GIUH) to compute the direct runoff hydrograph in Kashkan river basin located in western Iran. 1D HEC-Geo-RAS model was used and performed to simulate inundation extent of 100-yr floods (~1800 m3/s) along 40 km reach of Kashkan river with a ground survey of river cross-section (2000 cross-sections, each including 500 data-points). The effect of... 

The Karkheh River Basin is one of the Iranian river basins with a high potential for hydropower production. While Iran is actively constructing large dams in the Basin for hydropower production, climate change is putting the future status of hydropower production in the Basin in question. Using MODSIM, sensitivity of the Basin to climate change is investigated by estimating stream flow changes and the resulting impacts on hydropower production for different climate change scenarios. Results indicate considerable reductions in annual and seasonal hydropower production due to the expected dry climatic conditions under the existing operation rules. Findings highlight the necessity for revision... 

In this study Active Learning Method (ALM) as a novel fuzzy modeling approach is compared with optimized Support Vector Machine (SVM) using simple Genetic Algorithm (GA), as a well known datadriven model for long term simulation of daily streamflow in Karoon River. The daily discharge data from 1991 to 1996 and from 1996 to 1999 were utilized for training and testing of the models, respectively. Values of the Nash-Sutcliffe, Bias, R 2, MPAE and PTVE of ALM model with 16 fuzzy rules were 0.81, 5.5 m 3 s -1, 0.81, 12.9%, and 1.9%, respectively. Following the same order of parameters, these criteria for optimized SVM model were 0.8, -10.7 m 3 s -1, 0.81, 7.3%, and -3.6%, respectively. The... 

Observatory-scale data collection efforts allow unprecedented opportunities for integrative, multidisciplinary investigations in large, complex watersheds, which can affect management decisions and policy. Through the National Science Foundation-funded REACH (REsilience under Accelerated CHange) project, in collaboration with the Intensively Managed Landscapes-Critical Zone Observatory, we have collected a series of multidisciplinary data sets throughout the Minnesota River Basin in south-central Minnesota, USA, a 43,400-km2 tributary to the Upper Mississippi River. Postglacial incision within the Minnesota River valley created an erosional landscape highly responsive to hydrologic change,... 

This paper addresses the impacts of climate change on hydrology and water resources in the Karkheh River Basin (KRB), which is the third most productive basin in Iran and has great potential for hydropower generation. The total potential capacity of reservoirs in this basin is more than 15 ×109 Mm3, of which 40% has been built. The sensitivity of the KRB to potential climate change is investigated by simulating basin streamflow response under different climate change scenarios. A conceptual rainfall-runoff model (IHACRES) was first calibrated by using hydrological and streamflow observations. The model was then applied by downscaling two general circulation model outputs (CGCM3 and HadCM3)... 

The inherent complexities of multi-reservoir flood control systems and their operation conditions along with the improvements of optimization methods have led to a positive trend on better development of these models. This trend tends to provide the operators of these systems with more practical solutions. Although optimization models can provide appropriate solutions for operation of multi-reservoir systems, the exact implementation of these solutions in real world is not guaranteed. This arises mainly due to high level risk of flood situation, real time operation constraints, high level uncertainties of inflows that usually are overlooked in optimization models, and so on. These problems... 

Flood control as an important purpose of reservoir systems faces a wide range of natural, social and political challenges, mainly due to different uncertainties. Over the time, these uncertainties call for necessary changes in the original plan of the systems. Therefore, construction of new flood control systems as well as the storage reallocation and reservoir reoperation of existing ones are essential for adapting the systems to new information, conditions and policies. Furthermore, multipurpose nature of the multi-reservoir systems requires considering conflicts among various purposes. In this paper, a multiobjective optimization model is developed for analyzing such conflicts in a... 

Flood as a natural disaster causes heavy human and economic losses and social unrests in most areas of the world. As flood control cost and flood damage compensation is a heavy burden over countries' budget, traditional flood design methods are being replaced by more reliable risk-based methods employing comprehensive risk analysis. In this respect, flood damage estimation is an important step in flood control systems design and analysis. In large river basins with complex reservoir systems and various land uses, flood damage estimation is complex, data-intensive, time demanding, and uncertain task requiring an intensive hydrologic and hydraulic analysis. In this study a simple approach is... 

This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM... 

The accuracy of five soft computing techniques was assessed for the prediction of monthly streamflow of the Gilgit river basin by a cross-validation method. The five techniques assessed were the feed-forward neural network (FFNN), the radial basis neural network (RBNN), the generalised regression neural network (GRNN), the adaptive neuro fuzzy inference system with grid partition (Anfis-GP) and the adaptive neuro fuzzy inference system with subtractive clustering (Anfis-SC). The interaction between temperature and streamflow was considered in the study. Two statistical indexes, mean square error (MSE) and coefficient of determination (R2), were used to evaluate the performances of the... 

Water-quality modeling and prediction is a complicated task because of inherent randomness and uncertainties associated with various processes and variables throughout the stream environment and the lack of appropriate data. Hence, the results of mathematical models are always approximate, lying within an uncertainty. This paper describes and demonstrates the application of the U.S. Environmental Protection Agency's water-quality model, QUAL2E-UNCAS, to the Zayandeh-Rood River in Iran. First-order reliability analysis is used to examine the variability of predicted water-quality parameters of total dissolved solids, dissolved oxygen, and biochemical oxygen demand. This analysis also...