فهرست مطالب مهدی شیخ گودرزی

Rainfall-runoff hydrological models are important tools in water resources projects. Generally, performance of this group of models is dependent on the proper selection of parameters. Accordingly, several methods have been developed to estimate hydrological parameters. The present study aimed to compare the performance of conceptual hydrologic models such as TANK, SIMHYD and AWBM which benefit from the indirect model parameters estimation approach in discharge simulation of Babolroud watershed, Mazandaran province, Iran. The automatic calibration process of these models was designed using genetic evolutionary search algorithm and objective functions (NSE and RMSE) as error thresholds determinants. Hence, meteorological and hydrological data consist of temperature, evapotranspiration, precipitation and discharge (in daily scale) were gathered from authorities. Input data was also divided into warm-up, train and test steps after preliminary validation and recovery. Based on the results, NSE metric introduced TANK model as the best simulator respectively for train and test step (0.59 to 0.72). Depends on RMSE metric, SIMHYD (0.83) and TANK (0.15) models were introduced as the best simulator respectively for train and test step either. According to the catchment flow signatures, general simulation of low-flow (excluding the Model TANK), mean-flow and high-flow were conducted with acceptable agreement. While simulation of the flow duration curve slope which represents an intensity of changes (excluding TANK model in train step), did not provide acceptable results. Given the weaknesses and strengths of the proposed models, they can be used as an acceptable simulator in water resources management especially in terms of ungauged basins, after preliminary verification in different climatic conditions.

Urbanization is one of the most significant global changes. The rapid urban growth has been imposing high pressure to land and their resources. Neural networks are a powerful tool for understanding the spatial processes and patterns. Hence, the neural network model called multi-layer perceptron was applied as a tool for simulating the urban growth in Hashtpar township. The Root Mean Square Error (RMSE) was used as an index in design and stopping the training process of the network in this study. After normalization and removal of the covariate variables, distance to city center, main transportation and hydrographical networks, agriculture, grassland, barren land and slope were chosen as effective variables on the urban growth for study area. Architecture of the network has been designed as 7-14-1, which stands for number of input, hidden and output nodes, respectively. The training process was conducted by implementation of the sigmoid function and extracting the training samples of the urban change (1989-2000) and then simulating the urban growth for 2007. Investigating the performance of the model and analyzing the pattern of the simulated landscape was carried out using the relative operating characteristic and the landscape ecological metrics. The values of the ROC and landscape Ecological metrics indicate an acceptable spatial agreement between the simulated and classified maps. Accordingly, the neural network model has a good reliability in simulation of the class area, Euclidean nearest distance and fractal dimension index of the urban patches, as well. Finally, sensitivity of the model was examined using stepwise independent variable elimination and comparing the results with the full model. The results revealed that the distance to city center and the main transport network can be considered as the most effective variables in simulating the urban growth in the study area.

Environmental impact assessment will be considered as one of the most important management and decisions making tools in planning and construction of industrial projects. Construction of the dam will be considered as one of the large industrial and construction projects which are According to the Environmental Protection Council need for and approval of environmental impact assessment report before Construction. The implementations of such projects even if selected as the best place, have impacts on the environment. The first steps in this article predict potential environmental effects in this region were considered by two options in construction and operation by Implementation of check List methods. The possible effects were predicted of the separation of physical, biological and economic - social environment and construction and operation phases. Then was determined intensity and importance of the impacts due to implementation of the project on the environment in each of the physical, biological and economic - social environment during the two options of Implementation and lack of implementation in construction and operation stages of plan once using the modified Leopold matrix (Iranian matrix) and others with ICOLD matrix and then the results of this two methods were compared. In this study the purpose of compare two methods of assessment, the comparison of their results. Comparing the results from two matrixes indicated that highest negative effects and consequences related to the physical environment in the construction phase and the most positive outcomes observed in the economic environment - social exploitation phase.

Environmental degradation model is one of the Environmental Impact Assessment (EIA) methods in which ecological cumulative effects of human activities on his surrounding nature could be evaluated and quantified. As a special trait of Landscape Ecological Metrics is the ability of rapid assess and recognize of human activities in the shortest time. Thus in this study, we used a landscape degradation model to environmental impact assessment and degradation analysis of Korganroud watershed. To achieve this goal, the study area was divided into 12 sub-watershed depend on river system, as a working unit. In next step the ecological vulnerability, degradation factor and its intensity was computed for each region, using Landscape ecological metrics and classified depend on median. By using degradation table and importing model component, degradation coefficient was calculated and classified for each zone. By this way, each zone was ranked and Compared by degradation state into development and conservation level. Finally, from whole study area, 32% prone to further development level 1 and 27% level 2, 21% need to be rehabilitated and 20% area that needs for conservation, are measured.

Changes in groundwater quality, is caused destruction of other resources, either directly or indirectly, due to bad management of groundwater extractions. Considering the importance of groundwater resources, especially in arid and semiarid regions, this research was done to modeling the spatial distribution of some groundwater qualitative factors with emphasis on drinking using geostatistical methods. Qualitative variables selected are: total hardness, chloride, sulfate and nitrate ions. First of all, normality of data investigated based on Kolmogrov-Smirnov test and non-normal variables were transformed to normal by using logarithmic transform. Then variography and cross-variogram analysis of variables was done. Accuracy assessment of results was investigated based on cross validation and root mean square error (RMSE). Results showed that Cokriging Method (using auxiliary variables) compared with other Geostatistical methods is a more accurate estimator, so interpolating and zoning of variables were done by using Cokriging Method and drinking water standards.

Urbanization is one of the most significant global changes. The rapid growth in urban area is imposing high pressure to land and their resources. With regard to various ecological services of the Hyrcanian ecosystems and the necessity to conserve them, this research aimed to investigate the growth trend of urban areas and their impacts on land suitability of the conservational patches in Korganroud watershed, Guilan Province. First, the undeveloped parts of the watershed were divided into two main ecosystem types of forest and rangeland. Then, for each ecosystem type, required parameters of the CAPS Model (land capability and ecological parameters) were calculated and combined using linear combination approach. In total, 14 different zones with an area o 64,541 hectare (19% of the watershed‘s area: 13% jungle and 6% rangeland ecosystems) were distinguished as conservational patches. Simulation of the urban growth was done using a Markov-Cellular Automata Urban Change Modeling method called SLEUTH. We designed three different scenarios of historical, managed and ecologically sustainable growth for the period of 2008 - 2050. Finally, integration of the results of two approaches was implemented using a loose coupling approach. Results reflect a general trend in decline of patch suitability influenced by type and size of the urban area growth. According to the results, the observed changes in urban growth for the historical scenario provide a development approach different to the changes for the other two scenarios which collectively fall in another approach to development. Thus, conservational suitability of the area can be preserved by changing the development approach and harnessingcurrent trend of the urban area growth.