Pakistan and other regions facing alternation of droughts and floods (as described in this challenge) are usually arid and semi-arid that are mainly dependent on rain-fed agriculture and are facing water scarcity issues, rainwater harvesting is critically important for these areas.
For determining optimum sites for rainwater harvesting and potential of rainwater harvesting structures, data on landcover/land-use, elevation and topography, geo-chemical formation of soils, stream runoff and various hydro-meteorological variables are required. High quality data of landcover/land-use, elevation, stream identification, water potential of individual watersheds, and slope with fine spatial resolution can be derived from space-based satellite imagery. Although stream runoff and hydro-meteorological variable statistics with sufficient accuracy can only be obtained through ground based in-situ sensors, these measurements also need space based location services to make them input in the spatial analysis along with the satellite derived products.
In many cases however, satellite remote sensing represents a critical source of information, especially in regions with limited sensor networks and where information on hydrologic conditions is not accessible. Remote sensing and geographical information technologies can play an immensely powerful role in addressing major challenges, since spatial patterns of aridity, climatic uncertainty or rapid climatic variability are not vividly understood or considered by local farmers or municipal authorities while planning for agriculture or domestic water use. Robust modelling is possible when space technologies are applied to identify suitable locations and harvesting potentials for ponds and pans, check dams, terracing, percolation tanks, and Nala-bunds; with very less amount of time, effort and overhead assessment cost.
Steps to be taken:
1. Identify satellite data sources for
- landcover/land-use
- elevation
- stream identification
- water potential of individual watersheds
- slope with fine spatial resolution
2. Modeling
to be completed.