Visualisation of flooding along an unvegetated, ephemeral river using Google Earth Engine: Implications for assessment of channel-floodplain dynamics in a time of rapid environmental change

Abstract

Given rapid environmental change, the development of new, data-driven, interdisciplinary approaches is essential for improving assessment and management of river systems, especially with respect to flooding. In the world's extensive drylands, difficulties in obtaining field observations of major hydrological events mean that remote sensing techniques are commonly used to map river floods and assess flood impacts. Such techniques, however, are dependent on available cloud-free imagery during or immediately after peak discharge, and single images may omit important flood-related hydrogeomorphological events. Here, we combine multiple Landsat images from Google Earth Engine (GEE) with precipitation datasets and high-resolution (<0.65 m) satellite imagery to visualise flooding and assess the associated channel-floodplain dynamics along a 25 km reach of the unvegetated, ephemeral Río Colorado, Bolivia. After cloud and shadow removal, Landsat surface reflectance data were used to calculate the Modified Normalized Difference Water Index (MNDWI) and map flood extents and patterns. From 2004 through 2016, annual flooding area along the narrow (<30 m), shallow (<1.7 m), fine-grained (dominantly silt/clay) channels was positively correlated (R2 = 0.83) with 2-day maximum precipitation totals. Rapid meander bend migration, bank erosion, and frequent overbank flooding was associated with formation of crevasse channels, splays, and headward-eroding channels, and with avulsion (shifting of flow from one channel to another). These processes demonstrate ongoing, widespread channel-floodplain dynamics despite low stream powers and cohesive sediments. Application of our study approaches to other dryland rivers will help generate comparative data on the controls, rates, patterns and timescales of channel-floodplain dynamics under scenarios of climate change and direct human impacts, with potential implications for improved river management.