Linkages between land cover change, lake shrinkage, and sublacustrine influence determined from remote sensing of select Rift Valley Lakes in Kenya

Kiage, Lawrence M.; Douglas, Paul H.

doi:10.1016/j.scitotenv.2019.136022

Cited by 30 publications

(30 citation statements)

References 33 publications

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“…With this, it is further argued that increased sediment activation and erosion in the lake watersheds and in consequent higher siltation rates have impacted the lake volumes leading to the water levels rises. This theory follows recent independent studies that have shown dwindled forest cover in upstream headlands due to human encroachment, with agricultural land and peri-urban areas having almost proportionately increased (Boitt, 2016;Kiage and Douglas, 2020). Higher sediment inputs from the degraded lands, consequently, could probable be in favour of higher sediment yields.…”

Section: Introductionsupporting

confidence: 83%

“…Gichuru and Waithaka (2015) similar to Moturi (2015) -focused their analyses on the trends of Lake Nakuru water surface variations between 1984 and 2013, concluding that no direct correlation between rainfall and changes in the lake surface area could be found. More recently, Kiage and Douglas (2020) assessed changes in land cover within the catchments of Lake Baringo, Bogoria, Nakuru, and Elementaita as a potential driver of the increasing lake water levels. Odongo et al (2015) analysed time series of precipitation and flow, as well as annual mean lake volumes for the period 1960-2010 for Lake Naivasha to uncover possible abrupt shifts and gradual trends.…”

Section: Introductionmentioning

confidence: 99%

“…Variations in lake volume is an integral response to potential changes, not only in the catchment, but also in the lake water balance. Whatever the cause for the lake level changes is - Kiage and Douglas (2020) argue that all the above can potentially play a role in the lake level fluctuations a quantifiable magnitude can be derived by analysing changes in lake volume, since they constitute an integrated catchment response. Changes in lake volume reflect potential influences due to deviations from an equilibrium regarding inflow and outflow, LULC changes, or hydro-climatic changes.…”

Section: Introductionmentioning

confidence: 99%

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Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya

Herrnegger¹,

Stecher²,

Schwatke³

et al. 2022

Preprint

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Study RegionThe Great Rift Valley lakes of Kenya have recently experienced significant increases in their water levels, negatively impacting the local communities. This has provoked renewed concerns about the causations, with various geological, anthropogenic and hydro-climatic influences hypothesized as potential causes of the water level rises. Study FocusThis study analyses and documents water level fluctuations in Lakes Baringo, Bogoria, Nakuru, Solai, Elementaita and Naivasha. Hydrometeorological analyses are undertaken to understand potential causes and lake volume data is used to derive the "Integrated Catchment Response" (ICR), a magnitude which allows to relate changes in water balance components to signals observed in the lake volume changes. New Hydrological Insights for the RegionCompared to 1984-2009, the recent increases in lake areas range from 21% for Lake Naivasha to an extraordinary 123% for Lake Solai. Mean annual rainfall for 2010-2020 increased by up to 30%. Actual evapotranspiration also increased, but to lesser extent compared to rainfall. The results illustrate that changes in catchment properties due to anthropogenic influences or changes in underground permeability are not necessary to explain the lake level rises. Based on the ICR only surprisingly minor changes in the water balance are necessary to explain the lake level rises, since an increase of only 0.4 -2% of mean annual effective rainfall leads to the observed phenomena.

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Section: Introductionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya

Herrnegger¹,

Stecher²,

Schwatke³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Kiage and Douglas [60] also applied MNDWI and NDVI, and found that MNDWI provides more reliable results compared to NDVI; in our methodology, we used MNDWI to identify water surfaces and NDVI was used to calculate biomass. However, further comparison with the similarities or differences of other authors' findings is difficult, as studies dealing with lakes and wetlands are usually performed at the catchment level, or larger areas, and aim to reveal change in land cover categories and its consequences [71][72][73].…”

Section: Discussionmentioning

confidence: 99%

“…Although NDVI was used to identify aquatic vegetation, MNDWI provided a better index for determining open water surface [60,61]. Calculations were therefore performed in two steps.…”

Section: Data Processingmentioning

confidence: 99%

NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades

et al. 2020

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Observing wetland areas and monitoring changes are crucial to understand hydrological and ecological processes. Sedimentation-induced vegetation spread is a typical process in the succession of lakes endangering these habitats. We aimed to survey the tendencies of vegetation spread of a Hungarian lake using satellite images, and to develop a method to identify the areas of risk. Accordingly, we performed a 33-year long vegetation spread monitoring survey. We used the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI) to assess vegetation and open water characteristics of the basins. We used these spectral indices to evaluate sedimentation risk of water basins combined with the fact that the most abundant plant species of the basins was the water caltrop (Trapa natans) indicating shallow water. We proposed a 12-scale Level of Sedimentation Risk Index (LoSRI) composed from vegetation cover data derived from satellite images to determine sedimentation risk within any given water basin. We validated our results with average water basin water depth values, which showed an r = 0.6 (p < 0.05) correlation. We also pointed on the most endangered locations of these sedimentation-threatened areas, which can provide crucial information for management planning of water directorates and management organizations.

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Water security in sub‐Saharan Africa: Understanding the status of sustainable development goal 6

et al. 2021

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The world is nearing the 2030 target‐year by which sustainable development goals (SDGs) should be achieved. While other developing regions seem to be making progress toward achieving SDG6, sub‐Saharan Africa (SSA) is lagging behind significantly, particularly with regard to access to water supply and sanitation (WSS). As a result, most studies evaluating progress toward the achievement of water security SDGs in SSA have focused on WSS while the rest of the SDG6 targets have received scant attention, often using fragmented or incomplete evidence. Here, we fill this knowledge gap by conducting a comprehensive assessment of the status of SDG6 in all 48 countries in SSA. We provide a review of the progress made, the challenges affecting each SDG6 target and examine the different political, socioeconomic, and environmental factors with potential to undermine the achievement of SDG6 in the region. Our review clearly demonstrates that it is likely that most countries may not achieve water security by 2030. The complex nature of the challenges and factors impeding the achievement of water security in SSA outlined here suggests that a holistic intervention involving local, national, and international stakeholders and the research community is urgently needed to address SDG6 if the 2030 target date is to be met. Approaches to enhance water security may equally consider: (a) underpinning peace and security in SSA and (b) the commitment of more financial resources by donors particularly during this period of COVID‐19 pandemic. This article is categorized under: Human Water Human Water > Water Governance Engineering Water > Planning Water

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Linkages between land cover change, lake shrinkage, and sublacustrine influence determined from remote sensing of select Rift Valley Lakes in Kenya

Cited by 30 publications

References 33 publications

Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya

Hydroclimatic Analysis of Rising Water Levels in the Great Rift Valley Lakes of Kenya

NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes—Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades

Water security in sub‐Saharan Africa: Understanding the status of sustainable development goal 6

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