Integrating multi-criteria decision analysis (MCDA) with kriging and entropy methods for optimising streamflow measurement in a scantly monitored river basin

Abstract

ABSTRACT Streamflow data is one of the most important inputs for the management of water resources in river basins. In this study, a GIS-based multi-criteria decision analysis (MCDA) was integrated with kriging and entropy methods for optimising a streamflow monitoring network in the upper Tekeze River basin, north-western Ethiopia. An initial evaluation based on the WMO (2008) guideline showed that the density of existing streamflow monitoring network for the upper Tekeze River basin was inadequate. Hence, 41 new streamflow monitoring stations were needed. The most important criteria for identifying suitable streamflow monitoring sites in the upper Tekeze River basin were stream order, accessibility (distance to roads), slope gradient, land use/cover and soil texture. The required number of new streamflow monitoring stations for the upper Tekeze River basin was reduced from 41 to 33 after an optimisation using ordinary kriging and entropy. The optimal number of monitoring stations for the upper Tekeze River basin including the existing ones was therefore 47. An integrated application of MCDA, kriging and entropy methods aids to optimise the location and number of streamflow monitoring stations in a catchment. The use of optimisation techniques for designing streamflow monitoring network is essential for collecting adequate streamflow data in scantly monitored basins.