Environmental Monitoring and Assessment

, Volume 186, Issue 5, pp 3123–3138 | Cite as

Application of geographically weighted regression model to analysis of spatiotemporal varying relationships between groundwater quantity and land use changes (case study: Khanmirza Plain, Iran)

  • Shahabeddin Taghipour Javi
  • Bahram Malekmohammadi
  • Hadi Mokhtari
Article

Abstract

Understanding the spatiotemporal relationships between land use/cover changes (LUCC) and groundwater resources is necessary for effective and efficient land use management. In this paper, geographically weighted regression (GWR) and ordinary least squares (OLS) models have been expanded to analyze varying spatial relationships between groundwater quantity changes and LUCC for three periods: 1987–2000, 2000–2010, and 1987–2010 in the Khanmirza Plain of southwestern Iran. For this purpose, TM images were used to generate LUCC (rainfed, irrigated, meadow, and bare lands). Groundwater quantity variables, including groundwater level changes (GLC) and groundwater withdrawal differences (GWD), were gathered from piezometric and agricultural wells data. The analysis of spatial autocorrelation (Moran’s I and local indicators of spatial association ) demonstrated that GWR has a better ability to model spatially varying data with very minimal clustering of residuals. The results R 2 and corrected Akaike’s Information Criterion parameters revealed that the GWR has the lowest similarity in space and time in neighboring situations and it has the high ability to explain more variance in the LUCC as a function of the groundwater quantity changes. All results of the distribution of local R 2 values from GWR confirm our assertion that there is a spatiotemporal relationship between types of land use and each of groundwater quantity variables within the region. According to the t test results from GWR, there are significant differences between the GLC and GWD and the land use types in different places of region in each of the three time series. The GWR results can help decision-makers to make appropriate decisions for future planning.

Keywords

Geographical weighted regression (GWR) Land use/cover changes (LUCC) Groundwater quantity changes Remote sensing Geographic information system (GIS) Khanmirza Plain 

Notes

Acknowledgments

The authors would like to thank the two anonymous reviewers for their constructive comments on correction and improvement of the manuscript. The authors would like to express their gratitude to the technical experts of Regional Water Company of Chaharmahal-Bakhtyari Province for provide data and technical assistance.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Shahabeddin Taghipour Javi
    • 1
  • Bahram Malekmohammadi
    • 1
  • Hadi Mokhtari
    • 1
  1. 1.Graduate Faculty of EnvironmentUniversity of TehranTehranIran

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