Rainwater Harvesting Sites Research Articles

Selection of Rainwater Harvesting Sites by Using Remote Sensing and GIS Techniques: A Case Study of Dawa Sub Basin Southern Ethiopia

Water is one of the vital requirements for life, economic and social development. Water scarcity affects the environmental, economic and developmental activities of an area. The rainfall in the sub-basins is often very local, erratic, unreliable and unevenly distributed over the whole area of Dawa sub-basin. The pastoral and agro-pastoral communities are usually vulnerable to drought. The present study was an attempt to describe the state of Rain Water Harvesting (RWH) techniques and the contribution of Remote Sensing and GIS technologies for this RWH in the Dawa Sub basin. The study was conducted using physiographic factors of Dawa sub basin. Landsat image with spatial resolution 30m were used to identify LU/LC types. The thematic layers used were land use/land cover, slope, soil, drainage and runoff from derived from Landsat and collateral data. The image processing software Erdas IMAGINE and GIS software were used to process the image and to establish a geo information system by comprising digital data set of satellite image, topography, soil, metrology, drainage density and metrology. This data was used to study RWH was used to study the watershed network in the Dawa sub basin and to identify areas generally suitable for water harvesting in order to determine water harvesting techniques for those sites. Analytical Hierarchy Process (AHP) was used to calculate weighting and the analysis result indicates that the sub-basin supports promising opportunity for the establishment and development of RWH structures. From the total area of 17,402.7 km², The GIS evaluation predicts that 3,092.342 km² (22.853%) is extremely suitable, 4,524.221 km² (33.435%) is very suitable, 2,968.685 km² (21.939%) is suitable, 1,988.986 km² (14.7%) is less Suitable and 957.18 km² (7.07%) is not suitable for RWH.

A multi-criteria decision analysis approach towards efficient rainwater harvesting

Rainwater Harvesting (RWH) is becoming one of the most promising alternative sources of fresh water which can be potentially captured and utilized, particularly in arid and semi-arid regions (ASARs). However, identification of potential sites for RWH on a large scale has always been a great challenge, and therefore, requires further studies. Most recent studies on this topic select RWH zones employing Geographic Information Systems (GIS), combined with multi-criteria analysis and hydrological models. Nevertheless, there are a few studies, mostly in small catchments, that locate potential zones considering socio-economic factors. In this paper, a GIS-based Multi-Criteria Decision Analysis (MCDA) is presented to identify potential RWH areas incorporating socio-economic factors including distance from drainage networks, roads, urban areas, faults, farms and wells. The proposed methodology was implemented at a large catchment scale in Mashhad Plain Basin with an area of 9762 (km2) located in the northeast of Iran. Results show that 48% of the study area is not suitable for RWH. The rest of the study area is divided into three potential zones that are poor, moderate and good for RWH, covering 31%, 43%, and 26% of the potential areas, respectively. Ponds and pans, check dams and terracing were considered as the best practices for the good RWH potential areas. Preliminary estimates suggest that up to 158, 135 and 110 M m3 of precipitation could be received respectively by each system.

Estimation of Rooftop Rainwater Harvesting Potential using Applications of Google Earth Pro and GIS

In the present scenario of global warming, the availability of drinking water is the main concern. The problem of water shortage tackled in reliable scientific approaches. Rainwater harvesting is one of the best practices in collecting and storing rainwater. This method is cost-effective in the planning and development of rainwater harvesting facilities in water-scarce areas for future needs. In this paper, a case study of Vardhaman College of Engineering, Hyderabad, in Telangana state has taken to estimate the rooftop rainwater harvesting potential. In this study, In this study to digitize the various types of rooftops, Google Earth Pro is used. The overall potential quantity of rainwater harvestable at the institutional level can be assessed by using ArcGIS. Total water demand for the study area is calculated considering the existing population. Rainwater harvesting sites are identified and proposed according to the lowest elevation and drainage direction of the study area. The volume of the storage tank is designed based on daily discharge by assuming the length, breadth and height. The results of this study will demonstrate the Applications of Google Earth Pro and GIS in estimating rainwater harvesting potential to tackle the prevailing water shortage in the study area. Rainwater harvesting provides water at the point of demand, minimizes the stress on existing natural resources and also an eco-friendly solution.

Development and assessment of rainwater harvesting suitability map using analytical hierarchy process, GIS and RS techniques

Rainwater harvesting (RWH), which is the collection and storage of rainwater for multiple purposes, is gaining recognition in water supply issues. Selection of harvesting sites is the most critical factor in RWH projects. The objective of this study is to develop a suitability map of RWH sites for a basin in Saudi Arabia. The method used, constitute the identification and assigning weights to criteria, and generation of suitability map using Analytical Hierarchy Process (AHP). Eight appropriate criteria were considered. Results showed that excellent and good sites covered about 40.6% of the total available sites. Sensitivity analysis showed that the curve number (CN), slope, rainfall and soil were the most influential criteria. The maximum increase in the percentage area of excellent sites was 92% while good and moderate classes decreased by 43 and 53%, respectively. The developed suitability maps provide useful information to the decision maker for use in water management.

Integrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques

Rainwater harvesting (RWH) is one of the major techniques that is investigated in the present study using Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methods as two tools for decision-making, weighting and combining different thematic layers include land use, slope, drainage density and hydrological soil groups (HSG). The runoff map obtained by the distributed spatial-physical WetSpa model is considered as a useful layer that is integrated with other thematic layers in the geographic information system (GIS) environment for identifying RWH sites. Kakareza watershed (1132 km2) in Iran was selected as a study area to carry out the foregoing approach. The results showed that 256 km2 of the study area is good for RWH, 360 km2 is moderate and 516 km2 is poor. Thus, about 22.61% (256 km2) of Kakareza watershed is highly suitable for farm ponds. This article recommends the RWH suitable sites to a judicious decision for better water management in the area.

Assessment of rainwater harvesting sites in a part of North-West Delhi, India using geomatic tools

The study was conducted with an aim to provide practical solution for the groundwater management in three villages namely Singhola, Ghoga and Dhirpur of the North-West Delhi, India. LANDSAT remote-sensing datasets for the last four decades (1977–2018) were assessed to determine changes in vegetation cover at the selected sites. The Google Earth Engine was used to determine how values of the Normalized Difference Vegetation Index (NDVI) were found to have varied spatially and over time for the selected sites. Strong correlations were found between the NDVI values of surface features including waterbodies, forest land, agricultural land and urban areas in Singhola, Ghoga and Dhirpur, respectively. The relative infiltration capacity of soils was highest (92.9%) and lowest (57%) for Singhola and Dhirpur, respectively, due to spatial differences in soil texture. In each village, locations exhibiting a higher soil infiltration capacity could be used for implementing managed aquifer recharge schemes using rainwater harvested from rooftops in the villages. This assessment indicated that the village of Ghoga has the highest potential (3,76,98,013.08 m3) for aquifer recharge through rooftop rainwater harvesting as compared to the other two villages.

GIS-based approach for identification of potential rainwater harvesting sites in Arsi Zone, Central Ethiopia

Water plays a crucial role in fulfilling basic human needs, for socio-economic developments and for ecosystem services. Ethiopia is experiencing pressure on water shortage for agricultural and domestic uses. Arsi Zone frequently faces drought and crop failure due to lack of water sources. Eleven physical characteristics of the study area layers were adopted integrating multi criteria decision analysis, which uses analytical hierarchy processes with a fuzzy logic approach and geographical information system. Soil conservation service model was used to estimate the runoff depth layer of the study area. Weighting was made based on environmental, socio-economical and hydro-geological characteristics of the study area, and available literature. Results show that potential suitability class was not suitable with constraints 5769.8 km2 (27.88%), less suitable 3104.34 km2 (15%), suitable 5695.42 km2 (27.52%), very suitable 4097 km2 (19.8%) and extremely suitable 2027.38 km2 (9.8%). The area coverage of constraints were 4540.37 km2 (21.94%) of the study area. Outcome of this study emphasized the importance of geospatial modeling in assessing rainwater harvesting potential sites, proposed to assist in planning water facility and to address water scarcity problem in the study area. The model developed in this research can be used in other areas to determine the potential of rainwater harvesting and integrate rainwater as an alternative water source to ensure availability for domestic, agricultural and industrial uses. It is recommended that detailed ground validation and socio-economic factors should be analyzed to increase its effectiveness before implementation.

Identifying important ecological areas for potential rainwater harvesting in the semi-arid area of Chifeng, China.

Global water shortage is becoming increasingly severe, so the identification and protection of potential areas for harvesting water play important roles in alleviating drought. Suitable sites for potential water harvesting require a high runoff potential. Avoiding soil erosion caused by high surface runoff, however, is also necessary. We therefore developed a procedure for the continuous accounting of runoff potential based on the Soil Conservation Service curve number and potential risks of water and soil loss based on the universal soil loss equation to evaluate the potential for water harvesting. Suitable sites for rainwater harvesting covered 24.90% of the semi-arid area of Chifeng, southeastern Inner Mongolia, China. The best areas accounted for 8.4% of the study area. The southern part of the Greater Hinggnan Mountains in northern Chifeng had a large rainwater harvesting area, and the western and eastern parts of the Chifeng area belonging to Horqin Sandy Land and Hunshandake Sandy Land, respectively, had smaller rainwater-harvesting areas. The eight reservoirs in the Xilamulun River Basin were further analyzed as an example. Derived sites investigated by ground-truth field verification indicated a method accuracy of 87.5%. This methodology could be effective in other areas with similar requirements due to the increasing demand for water resources and requirements for the protection of soil-water resources.

GIS-based multi-criteria approach for identification of rainwater harvesting zones in upper Betwa sub-basin of Madhya Pradesh, India

The emergent water paucity calls for more resourceful alternatives of water conservation. Rainwater harvesting (RWH) is one of the most capable systems to increase availability of water and agriculture output in the semi-arid regions. Nevertheless, the assessment of RWH potential and selection of appropriate RWH locations pose a great challenge for the water managers due to lacking biophysical data and infrastructure. The present study attempts to assess the RWH potential and identifying probable RWH locations in the Betwa sub-basin using geospatial and multiple criteria decision analysis techniques (MCDA). The spatial theme such as land use land cover was derived by supervised classification method and lineament and drainage by edge enhancement method from Landsat ETM + satellite image and other secondary published maps. The surface runoff was determined from modified Soil Conservation Service Curve Number (SCS-CN) method. These parameters were assigned suitable weights and integrated with a geospatial (GIS) technique to generate RWH site suitability map and to identify possible locations for RWH structures. SCS-CN technique displays that the water-body and built-up areas have high runoff potential, while forest area shows low runoff. The analysis indicates that 5.6% (87.7 km2) is suitable for percolation tanks, 3% (46.6 km2) suitable for farm ponds and for check dams (0.7 km2) of the study area. The study reveals combined methodology of geospatial and MCDA procedures in planning of rainwater harvesting at a regional scale.

Seasonal Forecasting of Rainfall and Runoff Volumes in Riyadh Region, KSA

Analyses of Total Quarterly Rainfall (TQR) depth time series (1964–2014) at four gauges surrounding one potential rainwater harvesting site in this region show strong temporal and spatial variability. Using Box-Jenkins Methodology, three best-fit seasonal ARIMA models for 10-year predictions of TQR were selected; among more than 20 models, based on criteria of minimum values of variance, AIC and SBC. Comparisons between the forecasted and the actual TQR show good agreement. Data analyses show that spring records have the heaviest rainfall. Accuracy assessment results of the models indicate that for the most favorable model 58% of the residuals are within ± 10 mm, and 74% are within ± 20 mm. Making use of these results, it was possible to obtain seasonal predictions of runoff volumes for water harvesting at the potential site. The results indicate that the largest runoff volumes are expected to occur during the springs of 2016, 2019 and 2022 with an estimate of approximately 3.764 Mm3. Such results are useful for the design and maintenance of the storage facilities of the harvested water.

Rainwater harvesting in catchments for agro-forestry uses: A study focused on the balance between sustainability values and storage capacity

Rainwater harvesting (RWH) is used to support small-scale agriculture and handle seasonal water availability, especially in regions where populations are scattered or the costs to develop surface or groundwater resources are high. However, questions may arise as whether this technique can support larger-scale irrigation projects and in complement help the struggle against wildfires in agro-forested watersheds. The issue is relevant because harvested rainwater in catchments is usually accumulated in small-capacity reservoirs created by small-height dams. In this study, a RWH site allocation method was improved from a previous model, by introducing the dam wall height as evaluation parameter. The studied watershed (Sabor River basin) is mostly located in the Northeast of Portugal. This is a rural watershed where agriculture and forestry uses are dominant and where ecologically relevant regions (e.g., Montezinho natural park) need to be protected from wildfires. The study aimed at ranking 384 rainfall collection sub-catchments as regards installation of RWH sites for crop irrigation and forest fire combat. The height parameter was set to 3m because this value is a reference to detention basins that hold sustainability values (e.g., landscape integration, environmental protection), but the irrigation capacity under these settings was smaller than 10ha in 50% of cases, while continuous arable lands in the Sabor basin cover on average 222ha. Besides, the number of sub-catchments capable to irrigate the average arable land was solely 7. When the dam wall height increased to 6 and 12m, the irrigation capacity increased to 46 and 124 sub-catchments, respectively, meaning that more engineered dams may not always ensure all sustainability values but warrant much better storage. The limiting parameter was the dam wall height because 217 sub-catchments were found to drain enough water for irrigation and capable to store it if proper dam wall heights were used.

Robust approach for optimal positioning and ranking potential rainwater harvesting structure (RWH): a case study of Iraq

Rainwater harvesting (RWH) structure is considered as the best solution to conserve water for arid regions. The selection of RWH location is based on several key determinants such as hydrology, environment, topography, and socio-economic. This study proposed a robust methodology to identify and select the location of RWH using geographical information systems (GIS) and remote sensing (RS) with multi-criteria decision techniques in areas where data are scarce. Several thematic maps were extracted such as vegetation cover, soil group, slope, land use, and digital elevation (DEM). The RWH sites were ranked based on four major indexes: evaporation, cost-benefit, sediment, and hydrological index. Sensitivity analysis shows that the variance inverse (VI) and rank order method (ROM) considered all indices that effect ranking as compared to the analytic hierarchy process (AHP) and fuzzy-AHP. Sensitivity analysis also proved that the proposed method is suitable to be used for RWH site selection in arid regions.

Improved framework model to allocate optimal rainwater harvesting sites in small watersheds for agro-forestry uses

This study introduces an improved rainwater harvesting (RWH) suitability model to help the implementation of agro-forestry projects (irrigation, wildfire combat) in catchments. The model combines a planning workflow to define suitability of catchments based on physical, socio-economic and ecologic variables, with an allocation workflow to constrain suitable RWH sites as function of project specific features (e.g., distance from rainfall collection to application area). The planning workflow comprises a Multi Criteria Analysis (MCA) implemented on a Geographic Information System (GIS), whereas the allocation workflow is based on a multiple-parameter ranking analysis. When compared to other similar models, improvement comes with the flexible weights of MCA and the entire allocation workflow. The method is tested in a contaminated watershed (the Ave River basin) located in Portugal. The pilot project encompasses the irrigation of a 400ha crop land that consumes 2.69Mm3 of water per year. The application of harvested water in the irrigation replaces the use of stream water with excessive anthropogenic nutrients that may raise nitrosamines in the food and accumulation in the food chain, with severe consequences to human health (cancer). The selected rainfall collection catchment is capable to harvest 12Mm3·yr−1 (≈ 4.5×the requirement) and is roughly 3km far from the application area assuring crop irrigation by gravity flow with modest transport costs. The RWH system is an 8-meter high that can be built in earth with reduced costs.

Multi-criteria analysis and GIS modeling for identifying prospective water harvesting and artificial recharge sites for sustainable water supply

Rainwater harvesting (RWH) is a promising tool for supplementing surface water and groundwater supply to overcome imbalance between water supply and demand under changing climatic conditions. The main aim of this study is to present a technically robust and pragmatic methodology for evaluating rainwater harvesting potential and identifying suitable sites for RWH and artificial recharge structures using Geographic Information System (GIS)-based multi-criteria decision analysis (MCDA). Unlike past studies, this study proposes an approach to prioritize zones/sites for RWH and recharge structures, which is of great importance for the effective implementation of RWH strategies. The derived themes ‘runoff coefficient’ and the basic themes of ‘slope’ and ‘drainage density’ were used for mapping rainwater harvesting potential. Thereafter, suitable zones and sites for feasible RWH and recharge structures were identified using suitability criteria and GIS-based Boolean logic. In addition, identified zones/sites were prioritized based on the themes of key factors viz., post-monsoon groundwater level, groundwater fluctuation and water demand. After normalizing the weights of the themes and their features, the themes were integrated in GIS environment. The study area was divided into four RWH potential zones with 47% and 38% of the study area falling under ‘high’ and ‘moderate’ RWH potential, respectively. On the other hand, the study area was classified into four rainwater harvesting demand zones namely, (a) ‘very high’ (29% of the study area), (b) ‘high’ (26.4%), (c) ‘moderate’ (21.3%), and (d) ‘low’ (23.6%). The zones suitable for constructing farm ponds cover 2314 km2 and those for percolation tanks on the ground cover 42 km2. Further, 69 sites for percolation tanks along the streams and 33 sites for check dams were also identified as suitable locations over the study area. Framework for the prioritization of suitable zones/sites for RWH and groundwater recharge is proposed in this study by integrating ‘rainwater harvesting potential’ and ‘rainwater harvesting demand’ maps. The integrated geospatial and MCDA approach is not only time saving and cost-effective but also very helpful for the efficient planning and management of rainwater at a larger scale.

Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques

This study presents a method to identify potential sites for soil and water conservation techniques for the demarcation of suitable sites for artificial recharge of groundwater aquifers, in the study area. The run-off derived by the Soil Conservation Service Curve Number method is a function of run-off potential which can be expressed in terms of run-off coefficient. The augmentation of water resource is proposed by the construction of rainwater harvesting structures like check dam, percolation pond, farm pond and gully check dam. The site suitability for different water harvesting structures is determined by considering spatially varying parameters like slope, infiltration, run-off potential, landuse/land cover, stream order, soil texture, land capability class, hydrological soil group and micro-watershed area. The determined suitable site has been validated with existing recharge structures of the study area. Accuracy assessment of the suitable sites for recharge structures potential maps of the Bindra watershed is 82.60%.

A Methodology to Assess and Evaluate Rainwater Harvesting Techniques in (Semi-) Arid Regions

Arid and semi-arid regions around the world face water scarcity problems due to lack of precipitation and unpredictable rainfall patterns. For thousands of years, rainwater harvesting (RWH) techniques have been applied to cope with water scarcity. Researchers have used many different methodologies for determining suitable sites and techniques for RWH. However, limited attention has been given to the evaluation of RWH structure performance. The aim of this research was to design a scientifically-based, generally applicable methodology to better evaluate the performance of existing RWH techniques in (semi-) arid regions. The methodology integrates engineering, biophysical and socio-economic criteria using the Analytical Hierarchy Process (AHP) supported by the Geographic Information System (GIS). Jessour/Tabias are the most traditional RWH techniques in the Oum Zessar watershed in south-eastern Tunisia, which were used to test this evaluation tool. Fifty-eight RWH locations (14 jessr and 44 tabia) in three main sub-catchments of the watershed were assessed and evaluated. Based on the criteria selected, more than 95% of the assessed sites received low or moderate suitability scores, with only two sites receiving high suitability scores. This integrated methodology, which is highly flexible, saves time and costs, is easy to adapt to different regions and can support designers and decision makers aiming to improve the performance of existing and new RWH sites.

Potential Rainwater Harvesting: An Adaptation Measure for Urban Areas in Jordan

This study investigated the potential of harvesting rainwater from the roofs of nonresidential buildings in populated urban areas in Amman, Jordan, using geographic information system (GIS) techniques. Amman has a mean annual rainfall of 378 mm, which makes rainwater harvesting viable and feasible. The rainfall data recorded at seven different weather stations were processed statistically to produce reliable averaging surface and isohyetal maps for rainfall over Amman. The GIS layer was generated for roofs and catchments to identify the suitable rainwater harvesting sites. Results show that the potential water collected by rainwater harvesting is five times less expensive than that collected via the conventional water supply system. The net total water savings by rainwater harvesting is 3.45 × 106 m3/year, and this could reduce the nonrevenue water and other losses by ∼1%. Furthermore, rainwater harvesting has a potential positive environmental impact by reducing CO2 emissions by about 6.57 tons.

SELECTION OF RAINWATER HARVESTING SITES BY USING REMOTE SENSING AND GIS TECHNIQUES: A CASE STUDY OF KIRKUK, IRAQ

Arid and semi-arid areas such as Iraq suffer not only from limited precipitation but also from poor management of rainwater for agricultural use. One technique for rainwater harvesting (RWH) is to collect excess runoff water during the rainy season and store it for agricultural purposes during dry spells. Remote sensing (RS) and geographic information systems (GIS) are widely used to identify suitable RWH sites. In this study, an integrated approach was adopted to determine suitable RWH sites in Kirkuk City, Iraq. The methods were integrated with the multi-criteria decision analysis (MCDA) method to evaluate the parameters that significantly contribute to RWH site selection. Thematic layers, such as runoff depth, slope, drainage, and land use/land cover, as well as their features were assigned suitable weights and then integrated in a GIS to generate a RWH potential map of the study area. Suitable sites for different RWH structures, such as farm ponds and check dams, were also identified. The study area can be classified into three potential RWH zones: high suitability zone (8.2% or 399.75 ), moderate suitability zone (63.4% or 3,090.75 ), and low suitability zone (28.4% or 1,384.5 ). Around 3.7% of the study area (181.6 ) is suitable for farm ponds while 4% (197 ) is suitable for check dams. The integrated RS, GIS, and MCDA techniques were found to be a cost-effective and environmentally friendly way to recover rainwater and select suitable RWH sites.

Using Landscape Metrics Analysis and Analytic Hierarchy Process to Assess Water Harvesting Potential Sites in Jordan

Jordan is characterized as a “water scarce” country. Therefore, conserving ecosystem services such as water regulation and soil retention is challenging. In Jordan, rainwater harvesting has been adapted to meet those challenges. However, the spatial composition and configuration features of a target landscape are rarely considered when selecting a rainwater-harvesting site. This study aimed to introduce landscape spatial features into the schemes for selecting a proper water-harvesting site. Landscape metrics analysis was used to quantify 10 metrics for three potential landscapes (i.e., Watershed 104 (WS 104), Watershed 59 (WS 59), and Watershed 108 (WS 108)) located in the Jordanian Badia region. Results of the metrics analysis showed that the three non–vegetative land cover types in the three landscapes were highly suitable for serving as rainwater harvesting sites. Furthermore, Analytic Hierarchy Process (AHP) was used to prioritize the fitness of the three target sites by comparing their landscape metrics. Results of AHP indicate that the non-vegetative land cover in the WS 104 landscape was the most suitable site for rainwater harvesting intervention, based on its dominance, connectivity, shape, and low degree of fragmentation. Our study advances the water harvesting network design by considering its landscape spatial pattern.

GIS methods for sustainable stormwater harvesting and storage using remote sensing for land cover data - location assessment.

Identification of potential sites for rainwater harvesting (RWH) is an important step toward maximizing water availability and land productivity in arid semiarid regions. Characterised as a "water scarce" country, Egypt has limited fresh water supplies, and is expected to suffer from water stress by the year 2030. Therefore, it is important to develop any means available to supply water and maintain human habitability in a sustainable manner. Practiced or simply indispensable in many countries around the world, rainwater harvesting (RWH) promotes a sustainable and efficient manner of exploiting water resources. In the present study, suitable areas for sustainable stormwater harvesting and storage in Egypt were identified using remote sensing for land cover data - location assessment linked to a decision support system (DSS). The DSS took into consideration a combination of thematic layers such as rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, and soil texture. Taking into account five thematic layers, the spatial extents of RWH suitability areas were identified by an analytical hierarchy process (AHP). The model generated a RWH map with five categories of suitability: excellent, good, moderate, poor and unsuitable. The spatial distribution of these categories in the area investigated was such that 4.8% (47910 km(2)) and 14% (139739 km(2)) of the study area was classified as excellent or good in terms of RWH, respectively, while 30.1% (300439 km(2)), 47.6% (474116 km(2)) and 3.5% (34935 km(2)) of the area were classified as moderate, unsuitable and poor, respectively. Most of the areas with excellent to good suitability had slopes of between 2% and 8% and were intensively cultivated areas. The major soil type in the excellent suitability areas was loam, while rainfall ranged from 100 to 200 mm yr(-1). The use of a number of RWH sites in the excellent areas is recommended to ensure successful implementation of RWH systems.