Geospatial analysis of groundwater depth for manual well drilling suitability in the Zinder Region, Niger

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.

Table 1: Soil chemical properties of the analysed depth profiles in the Venice lagoon

Visual traces of iron reduction and oxidation are linked to the redox status of soils and have been used to characterise the quality of agricultural soils.We tested whether this feature could also be used to explain the spatial pattern of the natural vegetation of tidal habitats. If so, an easy assessment of the effect of rising sea level on tidal ecosystems would be possible. Our study was conducted at the salt marshes of the northern lagoon of Venice, which are strongly threatened by erosion and rising sea level and are part of the world heritage 'Venice and its lagoon'. We analysed the abundance of plant species at 255 sampling points along a land-sea gradient. In addition, we surveyed the redox morphology (presence/absence of red iron oxide mottles in the greyish topsoil horizons) of the soils and the presence of disturbances. We used indicator species analysis, correlation trees and multivariate regression trees to analyse relations between soil properties and plant species distribution. Plant species with known sensitivity to anaerobic conditions (e.g. Halimione portulacoides) were identified as indicators for oxic soils (showing iron oxide mottles within a greyish soil matrix). Plant species that tolerate a low redox potential (e.g. Spartina maritima) were identified as indicators for anoxic soils (greyish matrix without oxide mottles). Correlation trees and multivariate regression trees indicate the dominant role of the redox morphology of the soils in plant species distribution. In addition, the distance from the mainland and the presence of disturbances were identified as tree-splitting variables. The small-scale variation of oxygen availability plays a key role for the biodiversity of salt marsh ecosystems. Our results suggest that the redox morphology of salt marsh soils indicates the plant availability of oxygen. Thus, the consideration of this indicator may enable an understanding of the heterogeneity of biological processes in oxygen-limited systems and may be a sensitive and easy-to-use tool to assess human impacts on salt marsh ecosystems.