Alireza Eslami; Rahim Kazemi
Abstract
Regional flood frequency analysis is a powerful tool for estimating and analyzing flood flow in watersheds. In this research, different methods of regional flood analysis and hydrological homogeneity of catchments that has been done in the country has been investigated. Among the many methods for determining ...
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Regional flood frequency analysis is a powerful tool for estimating and analyzing flood flow in watersheds. In this research, different methods of regional flood analysis and hydrological homogeneity of catchments that has been done in the country has been investigated. Among the many methods for determining the homogeneity of sub-catchments, cluster analysis due to the ability of factor analysis to select the most important factors, simplicity of considering various factors, independence of effective factors, accuracy of separation of homogeneous groups, and advantage of using proper diagnostic functions, was the most appropriate method. Multivariate regression method, especially when the homogeneity of catchments have been accurately determined, has shown good performance in regional flood analysis. L-moment method, due to uniqueness and existence has good performance in estimating parameters and selecting appropriate statistical distributions. So that in the regional flood frequency analysis, the L-moment method performs better than other methods, particularly in the case of shortage and skewed data. The analysis of the intelligent models such as artificial neural networks (ANNs) and fuzzy logic, showed the high ability to establish nonlinear relationships between multiple input variables. The results of the Investigation of different factors used in regional analysis methods showed that Physiographic factors were highest (72.11%) followed by climatic factors (17.69%) and land cover parameters (7.48%). Also, the lowest contribution was related to hydrological factor with 2.72%. Among the physiographic parameters, the area factor with 30.19% of the contribution had the most influence on the regional flood analysis. Among the climatic factors, the highest application was related to the average annual rainfall factor with 73.08% contribution.
Rahim Kazemi; Ali Reza Eslami
Abstract
Base flow and related index is influenced by morphometric, geologic and hydroclimatological factors. As a result, it is precondition data for planning and water resources management. In this research, base flow and related index were extracted from daily stream flow data using one parameter recursive ...
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Base flow and related index is influenced by morphometric, geologic and hydroclimatological factors. As a result, it is precondition data for planning and water resources management. In this research, base flow and related index were extracted from daily stream flow data using one parameter recursive digital filter in eighteen hydrometric stations of the Caspian Basin. Physiographic, climatic, hydrological, and geological factors were calculated in GIS environment. Using factor analysis of the eighteen parameters, five factors were selected as independent factors. Statistical models were formulated to calculate several regressions between hydroclimatological and physiographic parameters. Further, residual analysis method was used to compare and evaluate the accuracy and efficiency of the models. Results showed that Hard Formations, the average height of basin, drainage density, and coverage of forest were the best predictors of the base flow index. Statistical models highlights importance of Q90/Q50 ratio as the suitable hydrologic index to estimate the base flow index. Besides, this model confirmed controlling role of Hard formations and the forest coverage on the base flow index.
Ali Reza Eslami; Ali Reza Shokoohi
Abstract
According to diversity and complexity of hydrological processes, more information and data for analysis of this aspect of drought, is needed. Hence, to achieve an index using observed data, simplicity and robustness, which is also capable analysis of this kind of drought, can be valuable. In this research, ...
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According to diversity and complexity of hydrological processes, more information and data for analysis of this aspect of drought, is needed. Hence, to achieve an index using observed data, simplicity and robustness, which is also capable analysis of this kind of drought, can be valuable. In this research, an index that includes both environmental and hydrological drought aspects was introduced. The foundation of the proposed method using flow duration curve as a method of analysis of hydrological drought and low flows is proposed. Performance of the desired Index (FDCI), with a proposed new Streamflow drought index (SDI) has been compared. To implement the method, three areas (Chalus, Joestan and Frizi river) with different aspects of size, climates and length of records, which are located in various regions of Iran, were selected. The results showed that the correlation between the proposed index and SDI (R2= 0.98, S.E=0.02) is highly significant. The superiority of the proposed method is the use of all available historical data without changing the original data. Hence, the application of FDCI for the analysis of hydrological droughts in rivers located in the Mediterranean and semi-arid regions should be consider as a main result of this research.
Ali Reza Eslami; Abdol Rasoul Telvari
Abstract
The hydrologic events and physical structure of a basin is related to governing climatic conditions. Basins have different hydrologic responses considering their various morphologic and climatic characteristics. It is recommended to separate basins with respect to their major factors into homogenous ...
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The hydrologic events and physical structure of a basin is related to governing climatic conditions. Basins have different hydrologic responses considering their various morphologic and climatic characteristics. It is recommended to separate basins with respect to their major factors into homogenous groups with the same hydrologic conditions. This grouping is effective so that models for estimating flood peak discharge in each homogenous group have higher performance than a single model for all basins. In this research, firstly different morphological characteristic of selected basins were derived using GIS. Based on factor analysis, major variables (factors) including; basin area, weighted-average slope, drainage density and annual mean precipitation were selected. Then, all basins were classified in homogenous groups with respect to major factors using cluster analysis and discriminate functions analysis, statistical methods, and Andrew’s curve as a graphical method. To investigate on the efficiency of grouping, two control basins were selected and their similarity to each homogenous group was carried out using above methods. By applying regression models developed for whole region and homogenous groups, flood peak discharges for two basins with different return periods were estimated. Simulated values compared with observed data and showed that models for homogenous groups have better performance than those for the whole region.
