A Self-Calibrating Runoff and Streamflow Remote Sensing Model for Ungauged Basins Using Open-Access Earth Observation Data

Abstract

Due to increasing pressures on water resources, there is a need to monitor regional water resource availability in a spatially and temporally explicit manner. However, for many parts of the world, there is insufficient data to quantify stream flow or ground water infiltration rates. We present the results of a pixel-based water balance formulation to partition rainfall into evapotranspiration, surface water runoff and potential ground water infiltration. The method leverages remote sensing derived estimates of precipitation, evapotranspiration, soil moisture, Leaf Area Index, and a single F coefficient to distinguish between runoff and storage changes. The study produced significant correlations between the remote sensing method and field based measurements of river flow in two Vietnamese river basins. For the Ca basin, we found R 2 values ranging from 0.88-0.97 and Nash-Sutcliffe efficiency (NSE) values varying between 0.44-0.88. The R 2 for the Red River varied between 0.87-0.93 and NSE values between 0.61 and 0.79. Based on these findings, we conclude that the method allows for a fast and cost-effective way to map water resource availability in basins with no gauges or monitoring infrastructure, without the need for application of sophisticated hydrological models or resource-intensive data.

The spatial variability of actual evapotranspiration across the Amazon River Basin based on remote sensing products validated with flux towers

“…The conversion of precipitation into streamflow is classically done by means of rainfall-runoff models (e.g., Duan et al 1992). More recently, results were published where runoff is determined from remotely sensed rainfall and ET values in ungauged basins (e.g., Simons et al 2016;Poortinga et al 2017). Predictions of ET in conjunction with satellite estimates of precipitation and water storage provide a new methodology to predict streamflow in river basin (e.g., Liu et al 2016).…”

An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale

“…The protection of forests and their resources is important as local and distant human populations benefit directly from food, fuel, fiber and eco-tourism from healthy ecosystems. Functioning ecosystems also stabilize the climate, provide fresh water, control floods, and provide non-material benefits such as aesthetic views and recreational opportunities [4][5][6][7][8]. Deforestation and degradation are a major source of greenhouse gas emissions, while forest management and restoration programs can improve livelihoods, create jobs, and improve economic growth in local communities.…”

Operational Flood Risk Index Mapping for Disaster Risk Reduction Using Earth Observations and Cloud Computing Technologies: A Case Study on Myanmar

“…The damages from these events were also found to be the largest at an estimated 2 billion lives affected, which accounted for 45% of the total impacts from all disasters (Wannous and Velasquez, 2017). Developing countries are particularly vulnerable to floods due to the lack of resources to prevent, mitigate, and adequately respond to floods (Adger et al, 2003;Douglas et al, 2008;Poortinga et al, 2017).…”