Surface water dynamics of Africa: Analysing continental trends and identifying drivers for major lakes and reservoirs

Africa has the most dynamic demographic development world-wide. Current projections predict a population of > 3 billion peopleby the end of the century. Sub-Saharan Africa alone will likely seea 40% increase in population between 2020 and 2050. Although it iswell known that large parts of Africa are in a constant state of waterstress, its surface water resources remain understudied. This studyanalyses long-term trends of surface water in Africa. It identifiescausal impacts on major lakes and reservoirs for the timeframe2003–2020, as well as dynamic and causal similarities between thevarious lakes. For this, a set of daily time series based on Earthobservation is employed. Global WaterPack data is used for a dailyuninterrupted time series of the continent’s surface water area.Additionally, an array of relevant independent variables, namelyprecipitation, total evapotranspiration, groundwater, soil moisture,and gross primary productivity (GPP) in different land use areas isanalysed. For causal identification, the Peter and Clark MomentaryConditional Independence algorithm is used. Findings show that >42% of African countries and > 34% of African ecoregions experi-ence shrinking surface water area. Over 80% of investigated surfacewater bodies are driven by the surface water in their upstreamsubbasins and GPP in agriculturally used areas. About 85% ofinvestigated lakes are significantly driven by agricultural usage,often in the form of water abstraction, as referenced regionalstudies confirm. Our analysis demonstrates the feasibility of con-ducting causal analyses of surface water dynamics using Earthobservation data. Dynamically similar lakes are often impacted bythe same drivers, forming regional lake clusters. Considering thecauses identified may greatly help adapt strategies for sustainabledevelopment. A causality analysis to identify drivers of surfacewater dynamics has, to our knowledge, never been performedbefore on this scale and at such high temporal resolution.

Authors

Institutions

Publication Details

Journal
International Journal of Remote Sensing
Published
2024-10-18
DOI
https://doi.org/10.1080/01431161.2024.2412802
Citations
6
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.70

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Surface water dynamics of Africa: Analysing continental trends and identifying drivers for major lakes and reservoirs

Igor Klein, Soner Uereyen, Patrick Sogno, Claudia Kuenzer et al.
6 citations
International Journal of Remote Sensing
Flood Risk Assessment and Management
1.70
article

Surface water dynamics of Africa: Analysing continental trends and identifying drivers for major lakes and reservoirs

Igor Klein, Soner Uereyen, Patrick Sogno, Claudia Kuenzer, Felix Bachofer
article en
6 citations

Abstract

Africa has the most dynamic demographic development world-wide. Current projections predict a population of > 3 billion peopleby the end of the century. Sub-Saharan Africa alone will likely seea 40% increase in population between 2020 and 2050. Although it iswell known that large parts of Africa are in a constant state of waterstress, its surface water resources remain understudied. This studyanalyses long-term trends of surface water in Africa. It identifiescausal impacts on major lakes and reservoirs for the timeframe2003–2020, as well as dynamic and causal similarities between thevarious lakes. For this, a set of daily time series based on Earthobservation is employed. Global WaterPack data is used for a dailyuninterrupted time series of the continent’s surface water area.Additionally, an array of relevant independent variables, namelyprecipitation, total evapotranspiration, groundwater, soil moisture,and gross primary productivity (GPP) in different land use areas isanalysed. For causal identification, the Peter and Clark MomentaryConditional Independence algorithm is used. Findings show that >42% of African countries and > 34% of African ecoregions experi-ence shrinking surface water area. Over 80% of investigated surfacewater bodies are driven by the surface water in their upstreamsubbasins and GPP in agriculturally used areas. About 85% ofinvestigated lakes are significantly driven by agricultural usage,often in the form of water abstraction, as referenced regionalstudies confirm. Our analysis demonstrates the feasibility of con-ducting causal analyses of surface water dynamics using Earthobservation data. Dynamically similar lakes are often impacted bythe same drivers, forming regional lake clusters. Considering thecauses identified may greatly help adapt strategies for sustainabledevelopment. A causality analysis to identify drivers of surfacewater dynamics has, to our knowledge, never been performedbefore on this scale and at such high temporal resolution.

International Journal of Remote SensingVol. 45(24)
University of Würzburg (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Deutsche Forschungsgemeinschaft
Clean water and sanitation
Openalex Percentile: Top 16%
Flood Risk Assessment and Management
1.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.