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| Created: | Feb 25, 2026 at 8:36 p.m. (UTC) | |
| Last updated: | Feb 25, 2026 at 8:39 p.m. (UTC) | |
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| Sharing Status: | Public |
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Abstract
Ephemeral surface water recurrence (ESWr) data files for the dry season (May - October), the wet season (November - April), and all times (2019-2025). Recurrence is given pixel-wise as a proportion of all time periods in which that pixel was filled (0.0 to 1.0).
Paper abstract
Reliable freshwater access drives terrestrial wildlife movements and habitat use globally. However, the small, rain-fed seasonal pools critical for dryland wildlife persistence are vulnerable to the rising temperatures and unstable precipitation regimes under climate change. In southern Africa, drying surface water may impact area-sensitive and water-dependent mammals by inhibiting seasonal migrations and increasing resource competition and human-wildlife conflict.
We present a framework and empirical analysis of fine-scale surface water mapping in the 520,000km2 Kavango Zambezi Transfrontier Conservation Area (KAZA), the world's largest terrestrial conservation area. From 2019-2025, we implemented Otsu thresholding on median Automated Water Extraction Index imagery from 10m Sentinel-2 MSI, leveraging high wet season contrast between vegetation and water as a dry season positive mask. We created >35 quasi-monthly KAZA-wide Ephemeral Surface Water (ESW) rasters (mean classification accuracy 87%), and found wet-season precipitation drivers of fill levels did not extend into the dry season. Then, using GPS data from 27 African savanna elephants (Loxodonta africana), which typically visit water every 48 hours, we compared elephant water visitation rates based on ESW to existing 30m Global Surface Water (GSW) maps. Models using ESW estimated 99% of elephant data came within a 48-hour window, compared to 42% for GSW, suggesting that ESW is a better proxy for actual water use.
Subject Keywords
Coverage
Spatial
Temporal
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| Title | Owners | Sharing Status | My Permission |
|---|---|---|---|
| KAZA Surface Water Maps | Maggie Swift | Public & Shareable | Open Access |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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