Development of a decision support system for runoff water storage and irrigation – case study of Common bean at Ukwe, Malawi

Temporally and spatially poor rainfall distribution in sub-Saharan Africa (SSA) has had serious repercussions on crop production resulting in high negative consequences on food production and financial returns for farmers. Harvesting and storing of rainwater for irrigation of crops (such as cereals and legumes) is, therefore, needed. One of the important legumes in sub-Saharan Africa, which serves as both food and cash crop, is the common bean (Phaseolus vulgaris, L). Demand for common bean in SSA outstrips production due to erratic and inadequate rainfall which results in yield reduction or loss of harvests. It is widely known in many SSA areas, such as Central Malawi Plains, that positive relationship between harvested watershed runoff and rainfall prevails, and that runoff water harvesting technique can contribute to food security through irrigation of beans and maize. However, among reviewed agro-hydrological models there is none being functional for relative processing of rainwater runoff, open surface water long-term storage and irrigation of common beans. Consequently, no decision support system concerning these processes is in use by farmers and agricultural field staff. The study using common bean at Ukwe Area, as a case study crop and site respectively, for semi-arid SSA, relates runoff, water storage and its potential irrigation field area. Main methodology involved assessment of catchment area attributes for runoff rainwater, measuring and calculating of volume of water harvested and determination of irrigation water and crop water productivity. A number of instruments were used for surveying the catchment characteristics and measuring prevailing climate conditions, reservoir water volumes and crop parameters. The study also premised on development of an agro-hydrological model component for strategic and tactical decision making to provide ‘what if’ solutions for the above-mentioned relationships. It was based on conceptualization, documentation and description, program coding and use of subroutines through incorporation of irrigation and socio-economic subroutines to Nedbor Afstromnings Model (NAM). Furthermore, the study focused on designing and validating a Decision Support System (DSS) for synchronization of catchment characteristics, reservoir capacity and irrigable field size. Results are conclusive that rainfall in the drought prone areas is unreliable and poorly distributed over a season, and is also frequented by dry spells. Findings showed that runoff water was highly related to seasonal rainfall amount with confidence limit (R2) of 0.75. It is illustrated that drought prone areas are sometimes flood prone as well. Total volume of water harvested led to estimation of field area at common bean water productivity of 0.71 g/L, slightly lower than values of higher than 1 g/L reported in Malawi and elsewhere. Socio-economic analysis demonstrated higher yield from irrigation than from rain-fed production, but fewer farmers expressed maximum willingness to be paying the current annual water harvesting contribution cost of US$ 17. Modified NAM demonstrated effectiveness in simulating rainfall - runoff, runoff- reservoir water volume, and volume - bean crop field size relationships. This was achieved through adjustment of the model parameters and time constants. With optimization of catchment parameters and runoff routing constants the model effectively simulated runoff with computed value magnitudes largely matching the measured values, from minimum of 0.5 m3/day in drought year of 1988 to the highest 16 m3/day in the highest rainfall in 1987. The added component of sub-routines for reservoir water losses and uses enables the model to simulate compute seasonal water balance and crop water productivity. The model is therefore agro-hydrological tool for making informed prediction relating to runoff, open rainwater storage and irrigation crop water productivity. The developed Decision Support System, based on excel spreadsheet operation, reliably relates irrigation water to gross runoff rainwater stored (70%). For two dry season crop production cycles, at the same crop water productivity of 0.7 g/L, potential crop command field area of 1.5 ha is simulated. It is established that stakeholders can use the DSS developed information to support their decisions in planning field area for farmers based on reservoir capacity or build a reservoir to suffice crop land area to mitigate drought and dry spell impacts.
Case study of Common bean at Ukwe, Malawi
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Region Focus: 
Southern Africa
RUFORUM Theses and Dissertations
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Open Access
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Prof. Siza D. Tumbo, Prof Henry Fatael Mahoo, Prof. Filbert Rwehumbiza
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A PhD Thesis