Developing flood vulnerability curve for rice crop using remote sensing and hydrodynamic modeling. (15th February 2021)

• Record Type: Journal Article
• Authors: Hendrawan, Vempi Satriya Adi; Komori, Daisuke
• Is Part Of: International journal of disaster risk reduction. Volume 54(2021)
• Publication Date: 2021-02-15
• Subjects: Crop yield loss -- Flood -- Remote sensing -- Submergence -- Vulnerability curve; Emergency management -- Periodicals; Risk management -- Periodicals; Disaster relief -- Periodicals; Hazard mitigation -- Periodicals; 363.34
• DOI: 10.1016/j.ijdrr.2021.102058
• Languages: English
• ISSNs: 2212-4209

Abstract

Abstract: The use of flood damage functions, or vulnerability curves, as a relationship between the intensity of the process (hazard) and the degree of potential loss of the exposed elements plays an important role in flood risk assessment. In terms of disaster risk reduction, a vulnerability curve is a helpful tool to quickly evaluate loss and conduct immediate decision making. This study proposes flood vulnerability curves for rice crop using crop yield loss estimated by crop statistics and remote-sensing modeling as a loss indicator. Flood parameters (depth, velocity, and duration) were simulated using a hydrodynamic model. Thus, the degree of crop yield loss and flood characteristics could be compared to derive vulnerability curves. In this study, we used a case study of the 2007 flood in the Solo river basin of Indonesia. Our results show that the relationship between the intensity of flood parameters and the degree of rice crop yield loss fits logarithmic regression functions, where water depth is considered the most significant parameter in loss estimation. Moreover, the minimum values of water depth, flow velocity, and duration relationship, that induce loss are 0.2 m, 0.03 m/s, and 8 days, respectively, while the maximum values, that induce complete yield loss, are 5.2 m, 0.08 m/s, and 22 days. This study's framework can be potentially used to obtain flood vulnerability curve or flood damage function, particularly for data-scarce regions.