Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins

Abstract

Floods are among the most catastrophic natural disasters around the globe impacting human lives and infrastructure. Implementation of a flood prediction system can potentially help mitigate flood-induced hazards. Such a system typically requires implementation and calibration of a hydrologic model using in situ observations (i.e., rain and stream gauges). Recently, satellite remote sensing data have emerged as a viable alternative or supplement to in situ observations due to their availability over vast ungauged regions. The focus of this study is to integrate the best available satellite products within a distributed hydrologic model to characterize the spatial extent of flooding and associated hazards over sparsely gauged or ungauged basins. We present a methodology based entirely on satellite remote sensing data to set up and calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inundated areas. A raster-based distributed hydrologic model, Coupled Routing and Excess STorage (CREST), was implemented for the Nzoia basin, a subbasin of Lake Victoria in Africa. Moderate Resolution Imaging Spectroradiometer Terra-based and Advanced Spaceborne Thermal Emission and Reflection Radiometer-based flood inundation maps were produced over the region and used to benchmark the distributed hydrologic model simulations of inundation areas. The analysis showed the value of integrating satellite data such as precipitation, land cover type, topography, and other products along with space-based flood inundation extents as inputs to the distributed hydrologic model. We conclude that the quantification of flooding spatial extent through optical sensors can help to calibrate and evaluate hydrologic models and, hence, potentially improve hydrologic prediction and flood management strategies in ungauged catchments.

Modeling of Coastal Inundation, Storm Surge, and Relative Sea-Level Rise at Naval Station Norfolk, Norfolk, Virginia, U.S.A.

“…The analysis showed the value of integrating satellite data such as precipitation, land cover type, topography, and other products with space-based flood inundation extents as inputs to the distributed hydrologic model. The results confirmed that the quantification of flooding extent through remote sensors can help to calibrate and evaluate hydrologic models and, therefore, improve hydrologic prediction and flood management strategies, especially in poorly gauged catchments (Khan et al, 2011).…”

“…For example, Khan et al (2011) implemented a raster-based distributed hydrologic model, coupled routing and excess storage (CREST) for the Nzoia basin, a subbasin of Lake Victoria in Africa. Terra satellitebased MODIS data and advanced spaceborne thermal emission and reflection radiometer (ASTER) data were used to produce flood inundation maps over the region.…”

Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data

“…However, the ability to calibrate a model using satellite data, even in combination with traditional in situ data, is still a challenging topic. Scientific work in this field goes in many directions: Rhoads et al (2001) used satellite-derived LST to validate a land-surface model, Caparrini et al (2004) and Sini et al (2008) assimilated remotely sensed measurements into a land-surface model to estimate the surface turbulent fluxes, Brocca et al (2011a) analyzed different remotely sensed soil humidity estimations with the perspective of using them in hydrological modeling, White and Lewis (2011) used satellite imagery to monitor the dynamics of wetlands of the Australian Great Artesian basin and Khan et al (2011) have recently proposed a procedure to calibrate a fully distributed hydrological model using satellite-derived flood maps.…”

37 Fusion of SAR images for flood extent mapping in northern peninsula Malaysia

“…*Floods are among the most destructive natural hazards that affect humans, property and settlements (Khan et al, 2011;Dano Umar et al, 2011, Dano Umar et al, 2014Ayobami and Rabi'u 2012). Flooding is a devastating natural phenomenon that affects and disrupts the wellbeing of the societies especially poor people who are vulnerable to disaster due to limitation of their resources.…”