Journal of Hydrogeology & Hydrologic Engineering.ISSN: 2325-9647

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Research Article, J Hydrogeol Hydrol Eng Vol: 8 Issue: 3

Monitoring the Effects of Drought on Vegetation Cover and Groundwater Using MODIS Satellite Images and ANN

Atta Areffian1, Maryam Kianysadr2, Saeid Eslamian1,3, Ali Khoshfetrat4 and Saleh Yousefi5*

1Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2Department of Environmental Science, College of Basic Science, Hamedan, Islamic Azad University, Hamedan, Iran

3Department of Water Engineering, Collage of Agriculture, Isfahan University of Technology, Isfahan, Iran

4Department of Technical & Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

5Department of Soil Conservation and Watershed Management Research, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, AREEO, Shahrekord, Iran

*Corresponding Author : Saleh Yousefi
Department of Soil Conservation and Watershed Management Research, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, AREEO, Shahrekord, Iran
Tel: 989188700283
E-mail: [email protected]

Received: October 29, 2019; Accepted: November 15, 2019; Published: November 25, 2019

Citation: Areffian A, Kianysadr M, Eslamian S, Khoshfetrat A, Yousefi S (2019) Monitoring the Effects of Drought on Vegetation Cover and Groundwater Using MODIS Satellite Images and ANN. J Hydrogeol Hydrol Eng 8:3.

Abstract

The main aim of present study was investigation on the effects of drought on vegetation cover and groundwater resources. In present study an available climatic data series (2001-2017) for 9 synoptic stations in Lorestan province were analyzed to detect wet and dry years by SPI. Also a long data series of MODIS data were analyzed by remote sensing data and the NDVI maps have been produced for study period (2001-2017). In addition the relationship between rainfall and groundwater level was investigated. Results of present study show that there is a direct significant correlation (R2=0.83) between SPI and the NDVI. In addition, results show that there is a significant correlation between groundwater level and three months ago precipitation at 95% confidence level. During study period 2008 and 2015 were selected as dry and wet years based on SPI values, respectively. The values of the NDVI in the wet year (2015) significantly are higher than the values in the dry year (2008) in 99% confidence level. Spatial variation of SPI show that for intensive drought conditions (2008) and wet year (2015) the north part of Lorestan province have the highest variation in compare with other parts of study area. Generally, the results of present study show that MODIS data in a mountainous area could be a key tool to detect effects of intensive droughts on natural vegetation cover, also groundwater level show a significant correlation with 3-months delay of monthly precipitation.

Keywords: Artificial Neural Network; NDVI; SPI; Remote sensing; Water recourses; Lorestan.

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