Zahra Sharifi; Raoof Mostafazadeh; Abazar Esmali Ouri; Zeinab Hazbavi; Mohammad Golshan
Abstract
Daily flow data are a prerequisite for water resources management, but it is not possible to measure it in many upstream watersheds. In this study, different optimization algorithms have been used to evaluate the efficiency of the SIMHYD model. Therefore, the discharge data of Kouzetopraghi rive gauge ...
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Daily flow data are a prerequisite for water resources management, but it is not possible to measure it in many upstream watersheds. In this study, different optimization algorithms have been used to evaluate the efficiency of the SIMHYD model. Therefore, the discharge data of Kouzetopraghi rive gauge station was selected as the study data (805 km2) located in Ardabil province. The daily data of rainfall, evapotranspiration of the meteorological stations in the study area were used to simulate the daily river flow data. Optimization methods including genetic algorithm, comprehensive competitive evolution, search pattern, multi-start search pattern, uniform random sampling, Rosenbrook, multi-start Rosenbrook optimization were evaluated based on statistical efficiency criteria. The mean value of discharge values by genetic algorithms, multi-year pattern search, uniform random sampling, multi-start Rosenbark, Rosenbork, comprehensive competitive evolution, search pattern were 0.031, 0.023, 0.085, 0.032, 0.024, 0.032, 0.031, respectively. The results showed that the change of optimization algorithms has a significant effect on the calibration accuracy of the model, so that the values of the Nash-Sutcliffe efficiency criteria for the employed algorithms were 0.42, 0.31, -8.55, 0.38, 0.56, 0.023, and 0.24, respectively. The Rosenbrook algorithm had higher accuracy in calibrating the SIMHYD hydrological model compared to other algorithms used. A part of the modeling error can be related to the inconsistency of precipitation and runoff data due to the multiplicity of stations.
Hydrogeomorphology
Vahideh Moradzadeh; Zeinab Hazbavi; Abazar Esmali Ouri; Raoof Mostafazadeh; Shirin Zarei; Nazila Alaei
Abstract
Ecological indicators have become important tools for evaluating and monitoring natural resources. Understanding the relationship between biological activities and ecological interactions is essential to their structure. On the other hand, human activities have significant effects on landscape evolution ...
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Ecological indicators have become important tools for evaluating and monitoring natural resources. Understanding the relationship between biological activities and ecological interactions is essential to their structure. On the other hand, human activities have significant effects on landscape evolution through changes in sediment production, transport, and storage. Therefore, this issue should be considered in the comprehensive management of different watersheds and ecosystems. Accordingly, the present study was conducted to evaluate the spatial heterogeneity of the hydro-sedimentologic disturbance index (HSDI) in the watershed located in the central part of Ardabil province. For this purpose, sediment transport (ST), hydrological stress (HS), recharge potential of groundwater (Rec), and soil erosion potential (SEP) were first calculated for 27 different sub-watersheds. Then, these factors were weighted using the Shannon entropy method. The hydro-sedimentologic disturbance index (HSDI) was calculated and zoned using the weighted average. The results showed that the mean, maximum and minimum values of the HSDI index in the Samian watershed were 10.17, 45.67, and 0.20, respectively. In addition, 87.67, 5.33, 5.32, and 1.68% of the watershed area were classified into very low, low, medium, and high levels of disturbances, respectively. Sub-watershed 19 located in the northern part, and sub-watersheds 20 and 21 located in the central part of the Samian watershed have the most disturbances, so they are prioritized for management actions. The present research framework can be used as a potential tool to support decisions that should focus on improving natural resource management.
