Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Thomas, SA; McGwire, KC; Lutz, A; Kratt, C; Trammell, EJ; Thomas, JM; Mckay, WA (2012). Geospatial and regression tree analysis to map groundwater depth for manual well drilling suitability in the Zinder region of Niger. JOURNAL OF HYDROLOGY, 446, 35-47.

Abstract
Manual and low-tech well drilling techniques have potential to assist in reaching the United Nations' millennium development goal for water in sub-Saharan Africa. This study used publicly available geospatial data in a regression tree analysis to predict groundwater depth in the Zinder region of Niger to identify suitable areas for manual well drilling. Regression trees were developed and tested on a database for 3681 wells in the Zinder region. A tree with 17 terminal leaves provided a range of ground water depth estimates that were appropriate for manual drilling, though much of the tree's complexity was associated with depths that were beyond manual methods. A natural log transformation of groundwater depth was tested to see if rescaling dataset variance would result in finer distinctions for regions of shallow groundwater. The RMSE for a log-transformed tree with only 10 terminal leaves was almost half that of the untransformed 17 leaf tree for groundwater depths less than 10 m. This analysis indicated important groundwater relationships for commonly available maps of geology, soils, elevation, and enhanced vegetation index from the MODIS satellite imaging system. (C) 2012 Elsevier B.V. All rights reserved.

DOI:
0022-1694

ISSN:
10.1016/j.jhydrol.2012.04.023

NASA Home Page Goddard Space Flight Center Home Page