Establishing flood damage functions for agricultural crops using estimated inundation depth and flood disaster statistics in data-scarce regions

Abstract

Abstract:Flood damage functions form the core of flood risk assessment. This study proposes a method for establishing flood damage functions for agricultural crops in data-scarce regions. The method assumes that the flood damage ratio is a function of inundation depth only and utilizes inundation depth estimated from flood extent information and hydro dynamic simulations. The parameters of the damage functions are calibrated through the SCEUA method (Shuffled Complex Evolution method developed at The University of Arizona) so that the calculated flood damages match observations compiled in flood disaster statistics. The established three functions show good agreement with actual agricultural damages caused by a rainfall event in 2010 and are validated against another rainfall event in 2009. The results indicate that the established damage functions are capable of estimating flood damage at the district scale, while damage estimations at finer spatial resolution differ between the functions, suggesting that detailed statistical data need to be incorporated to reduce the estimation uncertainty at fine scales.

A GIS-based Spatial Multi-criteria Approach for Flash Flood Risk Assessment in the Ngan Sau-Ngan Pho Mountainous River Basin, North Central of Vietnam

“…Specifically, high and very high flash flood risk areas were detected which accounts for 42%, 26.5%, 22.9% and 8.6% of Huong Khe, Huong Son, Duc Tho, and Vu Quang Districts, respectively. This finding is similar to flash flood records ussually reported annually in Huong Khe (Nguyen and Ha, 2017;Nguyen et al, 2011;Nguyen et al, 2017b;Thuy and Mui, 2018), Huong Son (Nguyen et al, 2017a), Duc Tho (Thao et al, 2014) and Vu Quang (Nguyen et al, 2011). Most of these areas were located in Son Hong, Son Tay Huong Khe District: the total area of low risk was 90,928 ha accounting for 68.1.8% of the district area, followed by 21.1% (very low risk), 8.9% (medium risk), and 1.9% (high and very high risk).…”

Bottom-up approach for flood-risk management in developing countries: a case study in the Gianh River watershed of Vietnam

“…Because agricultural losses depend so much on the type of agriculture -e.g. aquaculture and livestock lose more than crops -the extent to which oods affects crops also varies (Klaus et al, 2016;Nguyen et al, 2017). In general, crop losses are controlled by ood characteristics (e.g.…”

A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

“…Dutta et al [61] validated flood extents with the model-driven flood of the 100-year return period. Some studies validated their estimated flood depth and crop loss function using point data from field surveys [30,78]. Since crop-specific flood loss estimation relies on crop cover mapping from remote sensing images, the accuracy of crop mapping is crucial for the precise crop-specific loss assessment.…”

“…Schematic stage-damage function for flood crop loss assessment. (a) Conceptual example of depth-duration-damage curve adapted from Shrestha et al[66] and Kwak et al[64]; (b) example of depth-damage curve showing a linear piecewise curve adapted from Amadio et al[12] and Mao et al[14]; (c) example of some other depth-damage curves (exponential, quadratic, and S-shape) adapted from Dutta et al[61], Van der Sande et al[49], Forte et al[29], Nguyen et al[78], and Win et al[68]; (d) conceptual example of tabular format of stage-damage function of loss assessment[62,65,70].…”