Using GIS to map impacts upon agriculture from extreme floods in Vietnam

Abstract

The frequency of extreme weather events has been increasing in Vietnam, with 1:10, 1:20 and 1:100 year floods all experienced in central Vietnam in the last decade. A geo-spatial model is used in a case study to assess the impacts of extreme flood events on agricultural production in the Quang Nam province of Vietnam. Eighty-six flood depth marks were interpolated by the inverse distance weighting (IDW) algorithm to generate the water surface, and a digital elevation model (DEM) was employed to create the flood inundation map. Another overlay algorithm used the flood inundation map and land use map to estimate the potential impact of floods on agricultural land. The study demonstrates the value of geographic information system (GIS) modeling, particularly when meteorological and hydrological data are limited, and remote sensing images taken during flood events are unavailable. The maps that were generated showed that the 1:10, 1:20 and 1:100 year floods led to 27%, 31% and 33%, respectively, of arable land being inundated. Wet rice was the crop most affected, with the flooded area accounting for more than 40% of the province's supply under each flood scenario. Whilst the exact loss of agricultural production will depend upon a number of factors including crop variety, stage of plant development, length of flooding period and level of inundation, this study provides valuable information for flood disaster planning, mitigation and recovery activities in Vietnam.