JWSS - Journal of Water and Soil Science

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Of the applications of remote sensing and satellite images in natural resources is distinguishing and detection of changes in land surface. The image classification using Maximum Likelihood (MLC) is one the prevalent method which is used in a study of the application of TM and ETM+ satellite images to detect sediment deposition on an implemented floodwater spreading scheme. In order to implement the research, field sampling and checking were done using transect networking method by selection of 30 sample points in floodwater spreading area as well as another 30 control points in the study area. The results of the study are shown that detection of sediment deposition using MLC method by application of LANDSAT TM and ETM+ can lead to increase the precision of change detection up to 82 percent. Furthermore, the results also show that the trend and changes due to sediment deposition on water spreading area can be precisely detected. Considering the present and potential applicability of the applied method in distinguishing changes due to sediment deposition on land surface which is absorbed on 450 hectares of water spreading area in this research study, it can be pointed out that the use of this method in larger area could be tend to increase the precision of change detection and to decrease the required time.

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Shortage of rainfall and also relatively high intensity precipitations in short-term are characteristics of arid regions of the world, such as central of Iran. Studies have indicated that massive flooding causes great loss of life and properties every year. Also, Water scarcity in arid and semiarid regions of the world will cause fragile living conditions in these areas. Therefore, it is needed to reduce runoff rates using actions such as dam construction or artificial recharge techniques. In this study, seven factors were applied such as the slope, surface permeability, transmissibility in alluvium, alluvial quality, land use, runoff volume and thickness of the unsaturated layer to determine suitable areas and site selection for flood spreading and artificial recharge in south of Kashan plain. After preparing the digital layers, criteria weights were determined using Fuzzy AHP. The weighted maps were acquired and merged together. Results indicated that land use criterion with the greatest weight (0.22) was determined as the first priority in the site selection for flood speading. The parameters of runoff volume, permeability, slope, depth of the unsaturated layer, alluvial quality, and transfer coefficient were accounted as the second to seventh priorities. 

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In this research, to locate and prioritize suitable areas for flood spreading in Mashhad plain, 10 criteria were used including land use, slope, alluvium thickness, distance to well, distance to subterranean, distance from the village, water table drawdown, permeability coefficient, electrical conductivity, and drainage density. Weighting process was done by Analytic Network Process (ANP) and fuzzy logic. After preparing and weighting the maps of all appropriate measures for locating suitable areas of flood spreading maps based on fuzzy logic and analytic network process model, the final map was prepared for prioritizing suitable areas for flood spreading. Then by applying the limiting layer that is a combination of three criteria of land use, slope and geomorphology, the final map of suitable areas for flood spreading was prepared and prioritized. The results showed that among the 10 factors influencing flood spreading, the thickness of alluvium criteria by weight of 0.27 was identified as the most effective layer in suitable areas for flood spreading. Most of the suitable regions located in slope less than 3% that represents its considerable impact in implementation of flood spreading. Mashhad plain potential for flood spreading, after removing exception areas (40.8% of total area), were defined in four inappropriate, relatively appropriate, appropriate and perfectly appropriate classes, that include 2.7, 25.9, 26.5 and 1.5% of the plain area, respectively.

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The basis of spatial planning is the geomorphological zoning of ground surface, in which the first phase is determining the homogeneous zones of the ground surface in terms of geomorphological characteristics. The current study aimed at determining the proper zones for artificial feeding in Gahar mountainous region and Garebayegan plains in Fars province by the use of zoning the ground by Evans-Chezy quantitative coefficients. The quantitative zoning of ground surface plays a vital role in more accurate determination of the land capabilities due to precise determination and division of the types, facies, and surface terrains. For this study, the elevation numeral data with 10m resolution obtained from the National Cartographic Center was used. By the use of surface fitting tools in MATLAB software, the equation for each form was fitted to limited fragments of the surface and the program was applied. Then, each of the quantitative coefficients was illustrated as some zones. For determination of fitting degree, the total squared difference between the rate parameter was used and by the use of fitness degree, the propriety degree of the surface for optimal positioning of flood spreading with surface morphological view was determined. The results indicate that the surface downstream the alluvial fans and plains located on the southern region of the studied land is the most appropriate zone for the Flood Spreading. This area constitutes a surface of 10% of the total area of the region.

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