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NDVI as a proxy for Hydrological Drought Monitoring in the Okavango Delta

Louis Quigley, (He/Him),University of Illinois Chicago Chicago Illinois, United States. lquigl3@uic.edu

Groundwater is a key water source, particularly in arid regions such as southern Africa, but direct monitoring is limited. Groundwater monitoring becomes increasingly valuable as rising water demand meets more frequent and severe droughts under climate change. This project explores the potential of vegetation indices, particularly NDVI, as a proxy for hydrological drought . We calculate monthly NDVI anomalies at a 250 m spatial resolution and 16 day composite temporal resolution from NASA’s MOD13Q1 dataset over a 2.5° × 2.5° area covering the Okavango Delta in Botswana. These anomalies are plotted over time and compared with a recorded drought period beginning in 2019 to assess vegetation response to water scarcity. The high spatiotemporal resolution of NDVI products and the satellite imagery from which they are derived makes them useful for understanding where hydrological drought may be occurring, even in the absence of groundwater wells. In ongoing work, we plan to simulate changing water table elevations at a monthly timescale using the Water Table Model (WTM) to determine how local and regional water table elevations respond to drought conditions. Further work will incorporate well data and lake surface elevations to validate model accuracy. This approach aims to develop an accessible method for groundwater monitoring and drought assessment in data-limited regions.

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 |CSDMS Pronouns=He/Him
 |CSDMS meeting institute=University of Illinois Chicago
-|CSDMS meeting city=Elmwood Park
+|CSDMS meeting city=Chicago
 |CSDMS meeting country=United States
 |CSDMS meeting state=Illinois
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 {{CSDMS meeting abstract title temp2025
-|CSDMS meeting abstract title=The Depression Connection: Mapping the Interplay between Topographical Depressions and Hydrologic Connectivity
+|CSDMS meeting abstract title=NDVI as a proxy for Hydrological Drought Monitoring in the Okavango Delta
 |Working_group_member_WG_FRG=Hydrology Focus Research Group
 }}
 {{CSDMS meeting abstract template 2025
-|CSDMS meeting abstract=Hydrologic connectivity is dictated by depression structure in a landscape and changes in response to variations in runoff at storm, seasonal, or longer timescales. In this work, we analyzed watershed characteristics across the Illinois, Platte, Arkansas and Susquehanna river watersheds. Utilizing the Fill-Spill-Merge model, our research moves beyond traditional approaches that arbitrarily fill topographic depressions. Instead, it employs Fill-Spill-Merge to simulate depression filling based on selected runoff values using a depression hierarchy data structure for rapid water routing into depressions. This innovative approach offers a nuanced model of water movement and accumulation.
+|CSDMS meeting abstract=Groundwater is a key water source, particularly in arid regions such as southern Africa, but direct monitoring is limited. Groundwater monitoring becomes increasingly valuable as rising water demand meets more frequent and severe droughts under climate change. This project explores the potential of vegetation indices, particularly NDVI, as a proxy for hydrological drought . We calculate monthly NDVI anomalies at a 250 m spatial resolution and 16 day composite temporal resolution from NASA’s MOD13Q1 dataset over a 2.5° × 2.5° area covering the Okavango Delta in Botswana. These anomalies are plotted over time and compared with a recorded drought period beginning in 2019 to assess vegetation response to water scarcity. The high spatiotemporal resolution of NDVI products and the satellite imagery from which they are derived makes them useful for understanding where hydrological drought may be occurring, even in the absence of groundwater wells. In ongoing work, we plan to simulate changing water table elevations at a monthly timescale using the Water Table Model (WTM) to determine how local and regional water table elevations respond to drought conditions. Further work will incorporate well data and lake surface elevations to validate model accuracy. This approach aims to develop an accessible method for groundwater monitoring and drought assessment in data-limited regions.
-We explored correlations between depression characteristics and watershed landscape features, such as shape, slope, and area. This exploration attempts to demonstrate the impact of topographical attributes on runoff and storage. Our findings indicate consistent relationships between depression fill and other landscape characteristics.
-This research provides support to new hydrological models by providing more precise predictions of the impact of depressions on surface hydrologic connectivity. By moving away from conventional depression filling techniques to a more dynamic simulation, this study highlights the importance of technological advancements in improving our understanding of natural phenomena like watershed dynamics with implications for improving water management practices.
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2025 CSDMS meeting-052: Difference between revisions

Revision as of 17:38, 31 March 2025

NDVI as a proxy for Hydrological Drought Monitoring in the Okavango Delta