A Satellite-Based Framework to Investigate the Impact of Sand Dams on Landscapes in Semi-arid Regions

Abstract

AbstractSince many regions of the Earth underlie pronounced seasonality, the availability of rainwater is often limited to a short period. This imbalance is additionally intensified by climate change and increasing pressure on land use in dryland ecosystems. Sand dams have gained attention as an adaptation measure to prevent the runoff and loss of rainwater during the rainy season. Yet, the long-term effects of these structures are rarely investigated. One major challenge is to decouple local ecosystem changes caused by higher availability of rainwater from superimposing long-term trends of climate changes. To tackle this problem, we proposed a method implemented within the Google Earth Engine to utilize time series of Landsat satellite images and track the effectiveness of sand dams over the last two decades. Within this big-data approach, we systematically compared the normalized difference vegetation index (NDVI) in our study area with at a control site in the Makueni District in Kenya. Our results show that vegetation vitality and coverage are higher at sites with matured sand dams. Furthermore, vegetation suffers less and recovers more quickly from extensive dry periods as the Landsat time series of the NDVI from 2000 to 2019 shows. Our findings indicate sand dams as a significant mitigation measure against climate change and their potential to increase the resilience of communities by ensuring water security.KeywordsSand damsRemote sensingLandscape monitoringHydrologyNDVICloud computing