جستجوی مقالات مرتبط با کلیدواژه « Boolean logic » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

In arid and semi-arid regions where there is low rainfall with inappropriate distribution, one of the ways to use floods is to spread them in susceptible areas. The aim of this study is to find the best place for flood spreading using GIS and decision-making methods in Farimaneh watershed. For this purpose, the slope, topography (altitude levels), geology, land use type, soil permeability, geomorphology, geological formations, vegetation, and soil factors were used. For weighting the quantitative variables, fuzzy logic with trapezoidal and triangular membership function, and for qualitative variables, fuzzy logic with hierarchical analysis was used. Flood spreading prone areas were presented using GIS and the concepts of layer integration from fuzzy logic, Boolean logic, and overlay index methods. To determine and prioritize susceptible areas the Boolean operators AND OR, fuzzy AND OR, Fuzzy algebraic and sum-product, fuzzy gamma from 0.1 to 0.9, and multi-criteria evaluation was used. By comparing the obtained results with the observational data, it was concluded that the Fuzzy and, multi-criteria evaluation and fuzzy gamma 0.8 and 0.9 methods were most consistent with the observational data and among these methods, the multivariate evaluation method was found to be more appropriate. Also, among the parameters, slope, vegetation cover, and permeability had the highest weights.

Inadequate temporal and spatial distribution of precipitation in arid and semi-arid regions, cause destructive floods in addition to loss of surface runoff. Therefore, controlling surface runoff and its proper utilization through the construction of rainwater catchment systems can be a good way to prevent water loss. Traditional methods may be time wasting and concise. Geographic information systems provide new methods and models of using huge number of maps and data for analysis in a short time with best results and conciseness. This project was implemented in Kan Basin as a pilot which covers an area about 197 km2. Different maps including slope, land use, precipitation, vegetation cover, soil hydrologic groups and geology were overlayed. Land use maps were extracted from ETM+ 8 satellite images of 2014 along with field controls. Then layers were weighted according to their importance and role of each map. Suitable areas for establishing rainwater catchment systems in each model were determined by overlaying in the frameworks of different models including Boolean logic, Index overlay and Fuzzy logic and compared with control points which were implemented with Ministry of Jihad Agriculture. The results showed that the operators gamma=0.2, gamma=0.3 and Product from Fuzzy logic model had the most overlap with the control areas, the best integrated model for determining the appropriate locations for the construction of rainwater catchment systems in the study region.

Controlling and managing of seasonal and sudden floods in arid and semi-arid regions, especially in areas where surface water is out of reach is necessary. Flood spreading is one of the best ways to control surface runoff and recharge groundwater resources. In the present study, the appropriate sites for flood spreading project in border area of Taybad county in Khorasan Razavi province is selected using Boolean logic .For prioritization the suitable locations, TOPSIS and VIKOR multi-criteria decision making methods were used. Firstly, using Boolean logic inappropriate areas based were removed on criteria (slopes greater than 8%, urban area, agriculture and covered pediment). Then, 11 zones were selected as the suitable areas of using TOPSIS and VIKOR models based on the criteria  of slope, groundwater quality, geology, alluvium thickness, transmission capability, drainage density, surface permeability, groundwater loss, distance from the village, distance from wells and land use.. Results showed that most suitable areas are located in alluvial fans. Based on the TOPSIS model, location J with value of 0.75 was selected as the best site, and using the VIKOR model, location K with a value of 0.96 was selected as the best location for flood spreading projects.