A GIS-based decision support system for rainwater harvesting (RHADESS)

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Abstract

Rainwater harvesting (RWH) is an unconventional water source that is increasingly adopted in South Africa. Its implementation is promoted by non-governmental organisations and government programmes to alleviate temporal and spatial water scarcity for domestic, crop and livestock production and support the overall water resources management. Unreliable water supply is one of the elements central to the poverty level of rural population. As the potential of RWH to improve water access for drinking and other basic human needs is still untapped, the technique will spread further in the coming decades. Studies on the hydrological impacts of RWH are focused on plot scale and very little is known about its impacts at catchment scale. To integrate RWH into the development and management of water resources in South Africa, there is a need to develop tools and methodologies that not only assist planners with the identification of areas suitable but also quantify the associated hydrological impacts of its wide scale adoption.

This paper presents the rainwater harvesting decision support system (RHADESS) that was built to assist decision makers and stakeholders by indicating the suitability of RWH in any selected part of South Africa and quantifying the potential impacts associated with its adoption at catchment scale. RHADESS is GIS-based and uses ArcView 3.3 as a platform to assess the RWH suitability of any given area of South Africa. Results are thereafter exported into an Excel spreadsheet that contains the hydrological impact, as runoff reduction, of different levels of adoption of RWH assessed by using the Pitman model. The decision support system guides the implementation of the following RWH categories: Infield RWH and ex-field RWH and domestic RWH. RHADESS was tested in two selected quaternary catchments C52A and V13D located in the Upper Orange water management area and the Thukela water management area, respectively.

Introduction

South Africa is experiencing growing pressure on water resources caused by increasing water demand for agricultural, domestic and industrial consumption that has brought about the need to maximise and augment the use of existing or unexploited sources of freshwater. Furthermore, the current energy crisis prevents the implementation of agriculture and water projects requiring high input of fossil energy and electricity. Water is at the heart of the Millennium Development Goals (MDGs) numbers 1, 3 and 7, and indirectly associated with the achievement of the others. To improve food security, alleviate malnourishment and meet the first MDG, South Africa’s small-scale rainfed agriculture must be upgraded. To address the challenge of obtaining the highest yield under variable and low rainfall conditions prevailing in South Africa, interdisciplinary approaches are required: (1) to increase the amount of water made available to crops to satisfy their requirements over time with improved water management through rainwater harvesting (RWH); (2) to maximise water infiltration and holding capacity of soils coupled with improved soil management through conservation tillage, mulching, etc. and; (3) to increase crop access to water – with improved crop management through selection of crop species, planting date, etc.

The best strategy is to combine the various techniques and practices to obtain the highest yield (intersection of the three circles, Fig. 1) and, often, it is an iterative process to achieve this combination (FAO, 2008). RWH is a general term, which describes the concentration, collection, storage, and use of rainwater runoff for both domestic and agricultural purposes (Gould and Nissen-Petersen, 1999). According to the type of catchment surface used, it is classified into infield RWH (IRWH), ex-field RWH (XRWH), and domestic RWH (DRWH). DRWH systems collect water from rooftops, courtyards, compacted or treated surfaces, store it in RWH tanks for domestic uses. IRWH systems use part of the target area as the catchment area, while XRWH systems use an uncultivated area as its catchment area (Mwenge Kahinda et al., 2008). The focus of this paper is on IRWH and XRWH referred to as field RWH (FRWH).

A number of scholars have confirmed the potential of RWH to enhance water productivity by mitigating temporal and spatial variability of rainfall (Makurira et al., 2009, Mwenge Kahinda et al., 2007a, Rockström and Barron, 2007, Ngigi, 2006, Oweis and Hachum, 2006, Rosegrant et al., 2002). RWH also offers an alternative for South Africa to meet the Millennium Development Goals of halving by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation (MDG 7, Target 1), and provide the first 6 kl of water at no cost to poor households (households with less than USD 112 income/month) (Mwenge Kahinda et al., 2007b).

In South Africa, the implementation of RWH is promoted by non-governmental organisations and government programmes to alleviate temporal and spatial water scarcity for domestic, crop and livestock production and support the overall water resources management. Increased adoption of RWH is expected in the coming decades as its potential to improve water access has been identified. With wider scale adoption of RWH in the horizon, there is the need to have better understanding of its likely impact on catchment hydrology, ecology, geomorphology, groundwater and catchment yields. Within a national framework of integrating development and management of water resources in South Africa, tools and methodologies are therefore required to identify suitable areas for the practice and as well as its associated hydrological impacts.

The paper presents the GIS-based RWH decision support system (RHADESS) which indicates suitable areas of different types of RWH and quantifies their hydrological impact in terms of change in runoff. The paper also presents the application of RHADESS in two quaternary catchments C52A and V13D located in semi-arid and humid zones, respectively, in South Africa.

Section snippets

Site description

The C52A quaternary catchment (Fig. 2) has an area of 938 km2 that drains into the Rustfontein dam. It is part of the Upper Orange water management area (WMA) (92,269 km2), and its main land cover is grassland. Extensive sheep and cattle farming characterise the area. Rainfed cultivation occurs where the rainfall and soils are favourable, but sizeable areas below the main storage dams are under irrigation (DWAF, 2004).

The land use of C52A consists of nine dominant land cover classes namely bare

Results and discussion

Results of the RSM are presented in Fig. 6, Fig. 7. Suitable IRWH areas cover about 14% (12% high and 2% Moderate) of C52A and 67% (47% high and 20% moderate) of V13D while XRWH areas cover 14% (12% high and 2% moderate) of C52A and 67% (35% high and 32% moderate) of V13D.

Considering the high level of adoption scenario for which RWH is implemented on 100% of the very suitable area, 75% of the suitable area, 50% of the moderate suitable area, 25% of the low suitable area and 0% of the very low

Conclusions and recommendation

The study aimed at developing a GIS-based decision support system that indicates the areas of South Africa suitable for RWH and quantifies its hydrological impact, as runoff reduction, for any selected percentage of adoption. Applications of RHADESS in semi-arid catchment (C52A) and in humid catchment (V13D) indicate its ability to assist in the implementation of RWH in water resources management. In adjoining catchments to C52A, namely C52B and C52C where the most concerted IRWH practices have

Acknowledgments

This study is part of the Water Research Commission funded project K5/1563: “Water Resources Management in Rainwater Harvesting an integrated systems approach”. The authors thank the Department of Water Affairs and Forestry, Statistics South Africa, the Agricultural Research Council (ARC), the Council for Scientific and Industrial Research (CSIR), the Smallholder system innovations in integrated watershed management: (SSI-program) as well as the School of Bioresources Engineering and

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