Monitoring Rainwater Harvesting Systems in India Using Satellite Remote Sensing Observations
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The building of small reservoirs is a typical measure taken by farmers to moderate the extremes of the hydrologic regime of a semiarid climate, which is characterized by the alternation of a short rainy season with long periods of dryness. South India is an example of a region that has utilized ancient village-level small rainwater harvesting (RWH) reservoirs (also known as tanks) for seasonal water storage. Decades of increasing dependence on groundwater has caused these tanks to fall into a state of disrepair. Now the severity of depleted groundwater resources is driving renewed efforts at the state and national levels to revive RWH systems. Critical to the success of the revival efforts and tank management is the regular monitoring of the water volume variations. Although synthetic aperture radar (SAR) observations have long been recognized as an important source of remote sensing (RS) data for monitoring surface water (SW) under all-weather conditions, and is used operationally for SW mapping applications, limited information is available about the limits of SAR RS technologies for small reservoirs for irrigation purposes. This thesis describes a RS approach to water volume monitoring in small reservoirs (5-80 ha in size) in the Gundar river basin, Tamil Nadu state in S. India. Empirically-derived water storage relationships were evaluated using TanDEM-X digital elevation model (DEM) data combined with estimates of SW extent from C-band Sentinel-1A (S1-A) SAR observations, and Landsat-8, Sentinel-2, and PlanetScope visible/infra-red observations. The TanDEM-X DEM data revealed strong power-type relationships between SW extent and storage volume, and were combined with satellite SW observations to estimate and monitor tank volumes. Three models of volume-area (V–A) relationship(s) were assessed: a tank specific (TS) model, a size-dependent categorical (CAT) model and a generalized (GEN) model for all tanks. For volume estimation, the CAT model produced the lowest root mean squared error (RMSE) as a percentage, VERR, of volume for the basin. While tank SW area was estimated using S-1A data, the narrow SW area of some tanks, especially close to the retaining wall presented challenges for operational use. Two examples demonstrate the approach: 1) the maximum volume of water in 559 tanks in the basin for two monsoon seasons shows tank structures significantly under-performing and 2) a time-series analysis using a high-volume of satellite observations shows the cycle of water (inflow and outflow) at the tank scale. This thesis illustrates the applicability of using a satellite RS observation approach to continuously monitor RWH, and beyond this, the critical need of an adopted multi-sensor approach (optical and radar) to retrieve high spatio-temporal resolution monitoring. The ability to estimate reservoir volumes using satellite RS has wide reaching implications in transboundary water management. RWH tank systems are currently not continuously monitored and thus, our findings represent a unique contribution to the hydrologic science community by illustrating the applicability of using a satellite RS observation approach to monitor RWH structures during monsoon, habitually cloud-covered, seasons.
Cite this version of the work
Vicky Vanthof (2018). Monitoring Rainwater Harvesting Systems in India Using Satellite Remote Sensing Observations. UWSpace. http://hdl.handle.net/10012/14077