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Showing 3 results for Plasjan

V. Rahdari, A. Soffianian, S. Pormanafi, H. Ghayomi Mohammadi, S. Maleki, V. Pormardan,
Volume 23, Issue 4 (2-2020)
Abstract

In this study, to evaluate the rain- fed land capability in the west of Gavkhooni basin and Plasjn sub- basin, a multi- criteria evaluation method was used. First, by reviewing the literature and expert knowledge, proper data were determined. Criteria and constraint were standardized by Fuzzy and Boolean methods repeatedly and the criteria weights were determined using the analytic hierarchy process. Calculated weights showed that soil and climate criteria with 0.27 and 0.26 had the highest weights among other criteria. Criteria and constraints were combined by considering criteria weights and using the weighted linear combination method; then the rain- fed land capability model was prepared. By re- classing the prepared model, the rain- fed land capability map was produced in 6 capability classes. The results showed that 178430 hectares of the study area was related to very high and high rain- fed capability classes. To determine the rain-fed agriculture sustainability, rain- fed agriculture locations were determined in each land rain- fed capability map. The results showed that 19686 hectares of rain- fed areas were located in high and very high capability and 5999 hectares were the in lower classes.

S. Toghiani Khorasgani, S. Eslamian, M.j Zareian,
Volume 25, Issue 4 (3-2022)
Abstract

In recent decades, water scarcity has become a global problem due to the growth of the world's population as well as the increase in per capita water consumption. Therefore, planning and managing water resources to prevent potential risks such as floods and drought in the future is one of the important measures of water resources management. One of the important measures to avoid potential risks and predict the future is rainfall-runoff modeling. The objective of this study was to investigate the efficiency of the WetSpa hydrological model in estimating surface runoff in the Eskandari watershed, which is one of the important sub-basins of the Zayandehrood watershed. In this study, Daran and Fereydunshahr synoptic stations have been used to collect meteorological information in the Eskandari watershed. Also, to study the flow of the Plasjan river, daily data of Eskandari hydrometric station, located at the outlet of the basin, have been used. Climatic data along with digital maps of altitude, soil texture, and land use were entered as input to the WetSpa model. Finally, the ability of the WetSpa model was evaluated in estimating river surface runoff. The observed flow at the basin outlet in the hydrometric station was used to evaluate and calibrate the model. The model was calibrated for the statistical period (1992-2000) and its validation was performed for the statistical period (2001-2004). In the calibration period, the trial and error method were used to calibrate the model parameters. The simulation results showed a good correlation between the simulated flow and the measured flow. In the present study, the Nash Sutcliffe coefficient in the calibration and validation stages was equal to 0.73 and 0.75, respectively which shows the good and acceptable ability of the model in estimating the surface runoff of the study basin.

V. Rahdari, A.r. Soffianian, S. Pormanafi, S. Maleki,
Volume 27, Issue 3 (12-2023)
Abstract

Industrial development is necessary to create employment and achieve welfare. Nevertheless, due to the important environmental effects of these uses, it is necessary to consider the environmental issues in industrial area land allocation. The current research used the multi-criteria evaluation method and the combination with fuzzy concepts to investigate the land capability for industrial development in the Plasjan sub-basin in the Zayandeh-rood river basin. Evaluation criteria were determined by literature reviewing and using experts' knowledge, and standard applying fuzzy method via proportional functions and weighted using the hierarchical method. The combined classification of satellite images prepared the land use and land cover map. Then, the standardized criteria were combined in the form of a weighted linear combination and the industrial development capability model was prepared for this area and classified into five land capability classes. The results showed that environmental considerations have the most weight with 0.23, and geological and soil texture criteria have the least weight with 0.06. According to the results, only 213 hectares of the region were allocated for industrial and mining use at the time of the study. In comparison, 2325 hectares of the region have very high industrial potential which shows the capability for increasing industrial areas. Also, the highest class of land capability was related to areas without the capability for industrial development with an area of 246375 ha, equivalent to 60% of the entire region, which shows the importance of conservation of the important functions of this region in water supply and ecological resources.


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