Satellite LiDAR reveals patterns in water table depth and flood risk in SE Asia coastal lowland and peatland plantations

Abstract

Agriculture in SE Asian coastal lowlands is vulnerable to inundation and associated crop production loss. Quantifying and managing flood risk, surface subsidence and carbon emission (in peatlands) requires an understanding of water table depth patterns and controls, for which no comprehensive data currently exists. Here, we present a new dataset of 15,449 measurements of canal water table depth below the soil surface (CWD) in large-scale industrial tree plantations across the islands of Sumatra and Borneo, derived from ICESat-2 satellite LiDAR data. A pronounced relation is evident between CWD and land surface elevation, that applies equally in different regions, both in peatlands and mineral soil areas, and in oil palm as well as Acacia plantations. Mean CWD varies consistently across elevation zones, from -0.4 to -0.8 m where the surface is 5‒9 m above global mean sea level, to ~-0.2 m at 1–3 m elevation near mean sea level. The area of industrial plantations in the 1–3 m elevation range alone, that likely has the highest flood risk, is 836,900 hectares. Accounting for larger areas of smallholder plantations, and for areas at higher elevations with impeded drainage, the total area of lowland plantations likely experiencing flooding could be up to 4 million hectares. This indicates that water levels, especially in lowest-lying plantations, are often controlled by landscape drainability conditions rather than management targets, and optimum water table depth conditions for production are not achieved over large areas. We propose that such hard to manage landscape controls on water table depth are considered in yield projections as well as fire and peat carbon emission reduction policies, with unproductive flood prone plantations as well as peatlands with low water tables being logical priority targets for restoration planning.