GIS-Based MIF Technique for informed Water Resource Management.

Research Review "Assessing the effect of change in climate and landuse on groundwater recharge suitability in the Thiba River Sub-Basin, Kenya"

I have a particular interest in this topic- not only because it’s a research paper done by my previous Project Manager Abel Omanga , on the multi-influencing factor (MIF) technique, a tool for advancing climate-informed policy advisory, but also because my early research years were rooted in the SDG6 targets within the Water, Sanitation and Health (WASH) sector.

This study, through the application of the Multi-Influencing Factor (MIF) technique, examines how variations in climate and land use over time and space (different geographic locations) affect the ability of different areas within the Thiba River sub-basin to support groundwater recharge.This comprehensive approach results in detailed spatial maps that showcase how water resource availability evolves over time.

It identifies, where and when conditions are most or least favorable for groundwater replenishment, offering valuable insights for sustainable water resource management

The study area, located within the larger Tana Basin, spans Kirinyaga and Embu counties along the slopes of Mount Kenya. It’s a region where the stakes are high—water availability, particularly during the dry season, is increasingly uncertain.

The study explores the spatial-temporal variability in groundwater recharge potential across the Thiba River Sub-Basin in three key timelines: the past (1986), the present (2020), and the future (2050).

In this article, we will cover:

1. PART 1 : Assessment of Land Use Changes on Thiba River Sub-Basin using GIS techniques and specialized datasets/models
2. PART 2 : Assessment of Climate Change on Thiba River Sub-Basin
3. Application of the Multi-Influencing Factors (MIF) technique
4. Evident Impacts of Climate Change and Land Use Changes
5. The Role of GIS in Decision-Making
6. Personal Reflections: Bridging Academic Insights with Real-World Challenges
7. A Call to Action: Building Resilient Communities
8. Reference
9. Disclaimer

This article explores the use multi-faceted approach to understand and quantify these impacts, using a combination of historical climate data analysis, climate change projections, and a sophisticated spatial modeling technique.

PART 1: Assessment of the Land Use Changes

Raw satellite imagery was from LANDSAT repository for Landsat 4-5(TM), and Landsat 8(OLI) 30m, to map and analyze land use changes over time. Using a supervised classification method, the researchers categorized land cover into six classes: bare land, grassland, cropland, forest, built-up areas, and wetlands.

Land cover maps were generated for three distinct years (1986, 2003, and 2020), enabling the researchers to track the conversion of natural land cover to more intensive uses. To predict future land use patterns, a CA-Markov model was employed, which uses transition probability matrices to forecast changes based on historical trends.

By combining the temporal predictions of the Markov chain with the spatial considerations of the CA model, the model predicts continued expansion of cropland and built-up areas at the expense of forest and grassland. Evident from the lowland/plain land zone, cropland coverage increased dramatically from cropland area increased from 369.05 km2 in 1986 to 969.99 km2 in 2020. This expansion of cropland, often associated with reduced infiltration due to tillage and compaction, directly impacts recharge potential.

This map revealed continued trends of agricultural expansion and urbanization at the cost of forests and grasslands, in the hills and mountain foot ridge zone and the lowland/plain land zone.

PART 2 : Assessment of Climate Change on Thiba River Sub-Basin,

The study incorporates climate change projections from the CORDEX (Coordinated Regional Downscaling Experiment) Africa experiment. Focusing on a moderate emissions scenario (RCP 4.5), the model provided rainfall projections for the period 2021-2050 at a 25 km resolution.

To assess the historical trends in rainfall and temperature, researchers used CHIRPS for rainfall data from 1986 to 2020, while ERA5 provided temperature data for the same period. They identified two distinct rainy seasons (MAM and OND) and a significant warming trend in the sub-basin.

A key finding from the CORDEX model is a projected increase in rainfall in the mountainous zone: The mean annual rainfall is predicted to rise from 1453mm/yr to 1460mm/yr by 2050. While this might suggest a positive influence on recharge, the study cautions against over-optimism.

Application of the Multi-Influencing Factors (MIF) technique

The core of the study's analysis lies in the application of the Multi-Influencing Factors (MIF) technique, a widely used Multi-Criteria Decision Making (MCDM) technique for environmental management

Here the spatial modeling approach integrates eight factors that influence groundwater recharge suitability in the Thiba River sub-basin, including:

• Rainfall: Projected rainfall data from the CORDEX model, along with historical rainfall patterns, were crucial inputs to understand the availability of water for recharge.
• Lineament Density: The density of lineaments (fractures, faults) was analyzed as it influences the permeability of the subsurface and the pathways for water to infiltrate.
• Slope: The slope of the terrain was considered as it affects the rate of surface runoff and the time available for water to percolate into the ground.
• Drainage Density: This factor represents the density of streams in the area, which can indicate areas of high runoff and potentially lower infiltration rates.
• Land Use/Land Cover: Land use maps derived from Landsat imagery were used to assess how the conversion of natural land cover to cropland or built-up areas impacts recharge potential.
• Lithology: The geological characteristics of the area, specifically the rock types, were considered due to their influence on permeability and water storage capacity.
• Landforms: The broader topographical features, categorized as mountains, hills, and plains, were included to account for their influence on runoff patterns and infiltration.
• Soil Type: The texture of the soil was analyzed as it directly impacts the infiltration rate and water holding capacity of the ground.

Techniques and Models Used in the Analysis

1. Thematic Layer Creation: The process begins with creating thematic layers for eight critical factors influencing water resource dynamics, which are then converted into standardized 1 km² grid rasters.
2. Weight Assignment: Expert opinions and prior research inform the assignment of weights to these factors, initially categorized as minor (0.5) or major (1). The weights are normalized into percentages for consistency.
3. Sensitivity Analysis: Using the Map Removal Sensitivity Analysis (MRSA), each factor’s influence is assessed by observing changes in the results when a factor is removed. This allows for refinement of the weights and ensures the accuracy of the model.
4. Weighted Overlay Analysis: The final water resource potential maps are generated by multiplying individual cell values for each factor by their respective weights and summing them across all layers.

These detailed spatial maps were validated against borehole yield data, demonstrating a strong correlation between recharge potential and observed water availability. The analysis also provides a stark visual representation of the declining suitability for water recharge in certain areas, driven by climate change and land use conversions.

Evident Impacts of Climate Change and Land Use Changes

The MIF analysis reveals a complex interplay of environmental factors:

• Shrinking Suitable Zones: The area classified as "most suitable" for water recharge is projected to decrease by 2% between 2020 and 2050.
• Land Use Conversion: Middle and lower zones of the sub-basin are experiencing significant declines in recharge suitability due to urbanization and agricultural expansion.
• Climate Change Effects: Shifting rainfall patterns and increasing temperatures exacerbate the challenges, further reducing the recharge potential in vulnerable areas.

The finding highlight the future of groundwater recharge in the sub-basin remains uncertain, as it will depend on the interaction of these various factors, including future temperature and rainfall trends, as well as land management practices.

The Role of GIS in Decision-Making

GIS tools and MIF techniques transform raw environmental data into actionable insights. By visualizing spatial and temporal trends, decision-makers can:

• Identify priority areas for intervention.
• Develop targeted policies that address specific vulnerabilities.
• Monitor the effectiveness of implemented strategies over time.

For example, maps generated from the Thiba River sub-basin analysis provide a clear basis for recommending reforestation in mountainous zones, promoting sustainable agricultural practices, and integrating green infrastructure in urban planning.

Personal Reflections: Bridging Academic Insights with Real-World Challenges

This topic resonates deeply with me. During my time at JKUAT, Professor Hosea Mwangi’s lectures on Integrated Water Resources Management (IWRM) sparked my fascination with the intricate yet essential balance of water systems. Fast forward to today, I am equally inspired by how GIS techniques like MIF empower us to address pressing environmental challenges. My introduction to GIS in water resource management projects, from “Addressing urban coastal flooding challenges in Mombasa” to “Implementing green infrastructure planning for urban stormwater flooding in Dallas, Embu”—has allowed me to blend my deep-rooted interest in water resource management with innovative technological tools to find meaningful solutions.

A Call to Action: Building Resilient Communities

The Thiba River sub-basin’s analysis underscores the urgent need for proactive measures to safeguard water resources in the face of climate change and land use pressures. Key recommendations include:

• Reforestation: Protect and expand forested areas to enhance water retention and recharge potential.
• Sustainable Land Management: Implement agricultural practices that minimize soil degradation and promote ecological balance.
• Urban Planning: Design urban landscapes with green infrastructure to mitigate the impacts of land use changes.

The insights from GIS and MIF analyses not only inform policy but also empower communities to adapt and thrive amidst growing environmental uncertainties.

As someone deeply passionate about this field, I believe that my journey to embracing GIS, particularly QGIS tools and methodologies is not just an option—it is a necessity for an impact-driven contribution in securing our shared future.

Reference

Omanga, A. M., Sichangi, A. W., Makokha, G. O., & Waswa, R. N. (2024). Assessing the effect of change in climate and land use has on groundwater recharge suitability in the Thiba River Sub Basin, Kenya.

Disclaimer

The views and interpretations shared in this article are based on my personal understanding and assessment of the study reviewed, as well as my current experience in the water resource management field. The summary and analysis provided reflect my perspective and are not an exhaustive or definitive interpretation of the research. Only the referenced study is cited, as the focus of this review is on that specific research.

For any assistance in article writing or research review feel free to reach out to me directly via LinkedIn messages.