Decision Support System for Runoff Water Harvesting and Irrigation

Abstract

Despite the prevailing versatility of agro-hydrological Decision Support Systems (DSS) in the agricultural sector, a number of associated deficiencies do exist. The deficiencies are due to lack of synchronization of runoff affecting rainfall, catchment factors, reservoir capacity and irrigation field area in the face of recurring droughts and dry spells in several areas of Sub-Saharan Africa (SSA). The study focused on designing and validating a Decision Support System, by adding water reservoir and irrigation sub-routines to an Agro-hydrological Nedbor Afstromnings Model (NAM) to assist in screening best-bet options for either crop field area or reservoir size using a case study of common beans (Phaseolus vulgaris, L.) at Ukwe Area in Malawi. Microsoft excel spreadsheet (MS excel) was  used to compute cumulative runoff inflows into the dam, seasonal open surface water storage, water losses and withdrawal and reservoir water available for the bean crop. Computer simulation using soil, vegetation and topographical characteristics, and crop water requirements revealed proportion of catchment to irrigation command area of 10:1 with bean water productivity of 0.7 g/l (0.7 kg/m3), indicating low water demand. The NAM simulated values were in agreement with calculated ones. Post-DSS gross margin analysis indicated that 2.42 times more crop returns were obtained from irrigated than rain-fed bean crops despite additional costs associated with reservoir maintenance and irrigation operations. The DSS is, hence, found potential for users in drought prone Sub-Saharan African countries such as Malawi.