Developing GIS Models for Rainwater Harvesting
By Melinda Laituri & Joel Murray, Colorado State University
In late 2008, GISCorps volunteer Melinda Laituri, a Colorado State University professor, and one of her students, Joel Murray, started working on a GISCorps mission. The new mission was commissioned by EnterpriseWorks/VITA (EWV), an international not-for-profit organization based in Washington DC working to combat poverty through economic development programs based on sustainable, enterprise-oriented solutions.
EWV plans to undertake desk studies in 20 countries/regions to consolidate the information and lessons learned from former and current rainwater harvesting programs, with a view to disseminating the information widely and to support the design of a pilot project. The pilot project will test whether domestic rainwater harvesting (DRWH) has the potential to be an affordable and sustainable option for the poor with limited access to groundwater when supported through a market-based approach. The market-based approach includes developing a sustainable supply chain to support the delivery of DRWH goods and services, stimulating demand for such services by leveraging consumer preferences, and applying sustainable business models and with user fees that ensure full cost recovery. This approach has been successful in other sectors and EWV would like to determine whether and how it can be successful with DRWH.
Two African countries were selected for the pilot project; Kenya and Ethiopia (Figure 1) and a variety of datasets including but not limited to population, precipitation, and terrain were compiled and used in several GIS models to determine the feasibility of DRWH in these countries.
|Figure 1: Two Selected Countries for the Pilot Project|
Two sets of suitability models were developed in ArcGIS environment; one for Rooftop RWH and the other for Ponds/Pans RWH (Figure 2). Preliminary results of the study indicate that over 95% of Ethiopia is suitable for Rooftop RWH, but only 57% is suitable for Ponds/Pans RWH. Kenya is over 80% suitable for both Rooftop and Ponds/Pans RWH (see figures 3 and 4).
|Figure 2: Two Suitability Models|
Although RWH potential maps for Ethiopia and Kenya look promising the models are extremely simplistic and a review of model criteria should be considered. Other datasets such as land use and rooftop types as well as RWH system installation costs can be added as model parameters to improve accuracy. NDVI and higher resolution temporal data such as monthly precipitation grids can also be used to examine seasonality effects.
|Figure 3: Ethiopia Rainwater Harvesting Map|
Overall, this project has successfully shown that GIS is a cost effective method to identify RWH as a viable option to improve water supply in both Ethiopia and Kenya. Furthermore, through the use of a market-based approach, a sustainable supply chain to support the delivery of RWH goods and services can be promoted.
EWV is interested in expanding the existing models and/or developing additional models to include other variables such as rooftop type, land use, and socio economic parameters. GISCorps volunteers with expertise in this subject may contact us at: email@example.com.
A complete account of the study can be found at: http://www.cwi.colostate.edu/newsletters/2009/ColoradoWater_26_2.pdf (Page 28)