Ernest KIPLANGAT RONOH

Ernest KIPLANGAT RONOH

Ernest Kiplangat Ronoh has a background in Agricultural Biosystems with a specialization in Soil and Water Management. Currently serving as a hydrologist at the Kenya Forestry Research Institute (KEFRI), he joined the Department of Water and Climate in 2023 as a Ph.D. researcher under the guidance of Prof. Ann van Griensven within the Surface Water Group. His research focuses on catchment-scale flux analysis in a tropical river basin. It involves analyzing both new and existing (in situ and remote sensing) data alongside modeling techniques to quantify and understand the fluxes of water, sediment, carbon, and nutrients, particularly in relation to climate dynamics, land use/cover changes, and nature-based solutions (NbS).

Projects

PhD research

Engeneering Science

Date 2023 - 2027
Supervisors Ann VAN GRIENSVEN , Douglas NYOLEI , Stefaan Dondeyne
Funds VLIR-UOS

Ernest's research investigates the impacts of climate and land use/cover changes on catchment-scale sediment transport and carbon and nutrient fluxes in Kenyan equatorial streams. These streams face challenges such as water scarcity, deteriorating quality, downstream flooding, and unsustainable management practices. The study employs a triangulated approach combining modeling, remote sensing, and in situ data for a comprehensive analysis of the Yala River Basin in western Kenya.

Key objectives include:

  1. Assessing the effectiveness of integrating remote sensing, modeling, and in situ data for water quality monitoring.
  2. Evaluating the role of citizen science in catchment water quality monitoring.
  3. Investigating the application of nature-based solutions (NbS) for catchment water quality management.
  4. Analyzing the impacts of climate and land use/cover changes on the catchment.

The study is guided by specific research questions aimed at providing critical insights for effective water quality management and sustainable resource utilization. The methodology combines remote sensing, in situ data collection, and modeling techniques to achieve its objectives.

The anticipated outcomes include a validated model for predicting various water quality parameters under different land use scenarios. This research aims to contribute significantly to the sustainable development and conservation of the Yala River Basin, benefiting both the environment and the millions of people who depend on its resources for their livelihoods.