Assessment of Temporal and Spatial Variability of Groundwater in the Mbagathi River Catchment

Abstract

Groundwater is increasingly an important source of water. Assessment of its variability helps in guiding decisions on exploitation. Groundwater varies over space and time. Groundwater contains multiple range of chemical parameters which influence its quality. This study entails indexing of groundwater quality parameters in Geographic Information Systems (GIS) based environment using Kriging geostatistical analyst. The study was conducted in the Mbagathi River catchment, a metropolitan area, Southwest of Nairobi, Kenya. Existing boreholes data was obtained from the regulator to provide yield and water rest level characteristics. Data on groundwater quality parameters were analyzed according to the KS EAS 12:2018 standard from sampled boreholes. Quality, yield and water rest level data was analyzed and modeled in ArcGIS 10.1 software geostatistical wizard for spatial and temporal variability. Prediction maps were generated from which it was deduced that spatial and temporal variability of groundwater in the study area exists. Temporal variability largely follows the rainfall patterns. Groundwater quality deteriorated with decrease in rainfall by 5% on average from wet to dry seasons. It was deduced that groundwater is mainly fair to good quality. There was no excellent or very poor groundwater quality observed. Spatial variability predominantly followed the river flow regime in the drainage basin. 57% of the boreholes had a good yield of at least 8.3m3/hr. Modelling with associated prediction maps done on periodic basis is strongly recommended as a means of communicating groundwater characteristics. Smart level sensors, digital quality sensors and smart water meters are suggested as a means to collect and transmit data in a programmed manner over longer periods of time.