جستجوی مقالات مرتبط با کلیدواژه « دالاهو » در نشریات گروه « جغرافیا »

After United States of America, China and Turkey,Iran has the highest karst percentage, and karst formations cover more than 11%of our country. The volume of water stored in these areas can supply the water demand of many cities and villages. Characteristics of karst aquifers’feeding area determine the type of feed, flow andvulnerability of the aquifer tocontamination.Therefore, identification of feeding areas in karst aquifers plays a key role in understanding their hydrodynamic and hydrochemical characteristics, along with management and optimal scientific exploitation of them. Given the critical impact of karst water resources on human life and limited number of researcheson karst, any fundamental, applied, and developmental research performed with the aim of modelingkarst landforms and investigating the potential of karst water resources in these areas seems necessary. In order to assess andevaluatethe potential of karst water resources from a qualitativeand quantitative perspective, understand pollution, and vulnerability and also assessrisks facing aquifers,the present study models feeding areas of Dalahoowasaquifer using KARSTLOP model.

The present applied-developmental study is based on library research, field observation, and evaluation methods and seeks to prepare the map of karst water resourcesfeeding Dalahookarst aquifer. Fuzzy logic and gamma operator model were used to produce a zoning map for surface karst development. And finally, a map was produced for the feeding areas of Dalahoowaskarst aquifer using KARSTLOP model.

Using Natural Breaks method, the zoning map of Dalahoo’ssurface karst development divides the study area are into four classes: areas without karst formations (0-0.224), karst formations with low development (0.224-0.558), karst formations with moderate development (0.588-0.777) and developed karstformations(0.777-0.982).The final map of Dalahoo’sfeeding areas indicates that Bistoon karst aquifer has anannual charge rate of 37 to 81 percent.

Systematic study of karst aquifer’s water tables is very important, especially for drinking and agricultural purposes. The final mapof feeding areas, as well as the layers obtained from KARSTLOP method can be used as inputs for modeling groundwater. They may also be used to address practical issues of karst in relation to water management, including water supply, spatial distribution of watersheds, transboundary management of water, and initial assessment of groundwater vulnerability. Results obtained from zoning of feeding areas are consistent with the results obtained from zoning of surface karst development. High feeding values as well as spatial distribution of the aquifer’s feeding zones indicate that the aquifer has a high potential to store groundwater resources.This potentialityshould be properly managed to makeharvestingand protecting groundwaterpossible.

Landslide susceptibility mapping is  essential for  land use  planning and decision-making especially in  the mountainous areas. The main objective of this  study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran  using two statistical models such as an  index of entropy and Logistic Regression and to compare the  obtained results. At the  first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and  lithology  were extracted from the spatial database. Using these factors,  landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and  the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use  planning in the Dalahoo basin, Iran.