Browsing by Author "Konje, Martha Muthoni"

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Adoption of Machine Learning Technologies in Mitigation of Climate Change Risks in North Rift, Kenya
(International Journal of Applied Science and Engineering Review, 2025-07-07) Siunduh, Eric Sifuna; Ikoha, Peters Anselemo; Konje, Martha Muthoni
This study examines the implementation and effectiveness of Machine Learning (ML) technologies in addressing climate change risks within Kenya's North Rift region. The research investigates how ML applications are being utilized to enhance climate resilience, improve agricultural practices, and support decision-making processes in climate risk management. Through a mixed-methods approach combining quantitative data analysis and qualitative stakeholder interviews, this study evaluates the current state of ML adoption, identifies key challenges, and assesses the impact on local communities. Findings indicate that while ML adoption is still in its early stages, there is significant potential for these technologies to improve climate risk prediction, optimize resource allocation, and enhance adaptation strategies. The study reveals that successful implementation requires addressing infrastructure limitations, building local capacity, and ensuring community engagement. This research contributes to the growing body of knowledge on technological solutions for climate change adaptation in developing regions and provides practical recommendations for policymakers and practitioners.
Assessing the Long-Term Changes in Selected Meteorological Parameters over the North-Rift, Kenya: A Regional Climatology Perspective
(Hydrology, 2024-12-03) Makokha, John Wanjala; Masayi, Nelly Nambande; Barasa, Peter; Ikoha, Peters Anselemo; Konje, Martha Muthoni; Mutonyi, Jonathan; Okello, Victor Samuel; Wechuli, Alice Nambiro; Majengo, Collins Otieno; Khamala, Geoffrey Wanjala
Understanding long-term trends in climatic variables is essential for assessing climate change impacts on regional ecosystems and human livelihoods. A regional analysis of climatic variables over some domains is inevitable due to their geographical location and importance to the agricultural sector. Due to the aforementioned demands, the current study analyzes, trends in precipitation (from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS)), and minimum and maximum temperatures (from TerraClimate) over the North-Rift region of Kenya for over thirty (30) years using satellite data. The seasonal decomposition analysis was performed for each variable to explore the trends and residual components. The findings by the current study indicate that most counties, have experienced enhance precipitation which corresponds to a declining diurnal temperature from 2019 onwards. The seasonality component reveals repeated patterns or variations occurring at steady intervals within each region's data, hence suggesting a distinct regional seasonal trend in the selected meteorological parameters over time. Basically, all counties have reported a relatively constant variability in both maximum and minimum temperatures during the study period except from 2017 onwards where significant variability in the two properties is recorded. In conclusion, the foregoing results that the selected climatic variables exhibit significant spatiotemporal and interannual variability
Assessment of Mathematical Model for Predicting Climate Change Impact on Water Availability and Quality: A SWAT-SEIR Framework
(Iconic Research and Engineering Journals, 2025-07-07) Nyongesa, Fatuma Nandaha; Mulambula, Andanje; Konje, Martha Muthoni
This paper critically reviews and assesses various mathematical and computational modeling techniques applied to analyze the impacts of climate change on water security. Emphasis is placed on integrating dynamic hydrological processes with contamination propagation under changing climatic conditions. The study employs a SWAT-SEIR-type model, analyzed by both analytical and numerical methods like the Fourth-Order Runge-Kutta (RK4) scheme, simulate water system dynamics and evaluate stability conditions, particularly focusing on the basic reproduction number R0 as an index of contamination spread. The analysis contributes to understanding the complex interplay between climate-induced stressors and water resources, providing a foundation for developing robust water security strategies in the face of climate change.
Development of an Integrated SWAT-SEIR Mathematical Model for Assessing Climate Change Impacts on Water Security: A Lake Victoria Basin Case Study
(Iconic Research and Engineering Journals, 2025-07-07) Nyongesa, Fatuma Nandaha; Mulambula, Andanje; Konje, Martha Muthoni
Climate change poses significant threats to water security globally, with the Lake Victoria Basin experiencing intensified droughts, floods, and water quality degradation. This study developed an integrated mathematical model combining the Soil and Water Assessment Tool (SWAT) with a Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiological framework to assess complex interactions between climate change and hydrological processes. The hybrid model captures both water quantity dynamics through SWAT's physically-based approach and water quality contamination dynamics through the SEIR compartmental structure. Model validation achieved excellent performance with Nash-Sutcliffe Efficiency of 0.85 for streamflow and satisfactory performance for water quality parameters (NSE =0.59-0.67). The basic reproduction number (R₀ =4.69) indicated endemic contamination conditions requiring active management intervention. Sensitivity analysis revealed environmental degradation factor (μ* = 0.342) and precipitation input (μ* = 0.298) as the most influential parameters. The integrated framework successfully represents threshold behaviors and system transitions critical for climate adaptation planning.
Effects of land use practices on soil organic carbon, nitrogen and phosphorus in river Nzoia drainage basin, Kenya
(Agriculture, Forestry and Fisheries, 2015-05-07) Wabusya, Moses; Nyongesa, Humphrey; Konje, Martha Muthoni; Agevi, Humphrey; Tsingalia, Mugatsia
Land use activities along River Nzoia Drainage Basin, Kenya, include cultivation along the river banks, over grazing, deforestation, draining of wetlands for horticulture, harvesting of sand and brick-making. These activities have brought about changes in soil properties in the drainage basin adversely affecting farming output and the ecosystem in general. Consequently, it is important to understand how the different land use activities influence the soil properties in order to design and implement effective soil management strategies. This study examined the effects of land use practices on selected soil nutrients in Nzoia River Drainage Basin in Bungoma County. Cultivation and grazing were identified as important land use practices, while undisturbed sites were treated as controls. Land use practices along the river were identified by actual surveying of the study area. Secondary data on land use practices were obtained from technical reports, from local authorities and government offices. Soil samples were collected from different land use areas using randomly placed 5mx5m quadrats. Solis were collected at depths of 15cm in zigzag grid layout in each sample quadrat using soil auger. A total of 72 soil samples were collected in the study sites and analyzed for total nitrogen (N), available phosphorus (P) and organic carbon (C). Analysis of variance and correlation were performed to determine the significant land use practices affecting soil N, C and P. Cultivation had a significant effect on soil organic C mean value of 1.91 but negatively correlated with total Nitrogen and soil C while undisturbed sites exhibited positive correlation with C (P≤ 0.05). On the basis of our findings, it is recommended that conservation agriculture be practiced in the River Nzoia and its drainage system.
Forage Availability and Quality for the Impala (Aepyceros Melampus (Brian) Kathryh) of Impala Sanctuary, Kenya
(International Journal of Recent Scientific Research, 2014-10-07) Obiet, Lenard; Konje, Martha Muthoni; Francis, Muyekho; Danyuku, Esther; Kigen, Charles; Wamalwa, Stella; Kassilly, Fredrick; Wabusya, Moses
Forage availability and grazing pattern for the impala (Aepyceros melampus (Brian) Kathryh) in three ecosystems of the Impala sanctuary, Kenya was assessed during the wet and dry seasons. The grazing behavior of the impalas was observed to identify the preferred forage species and patterns grazing between seasons and ecosystems. Preferred grass species were sampled to determine percentage dry matter, neutral detergent fiber, acid detergent fibers, and Crude protein. Data was subjected to Analysis of Variance using SAS version 9.0. The results showed that impala sanctuary had 37 different grass species but Cynodon dactylon, Eragrostis curvula, Digitaris scalarum, Eleusine indica, Pennisetum setaceum and Hyparrhenia filipendula were most grazed on by the Impala. Grassland ecosystem had significantly high forage availability during the wet season, but in the dry season the marshes ecosystem was the one with the most nutritious forages. Grazing patterns varied with seasons, with most impalas preferring to graze in the grassland during the wet season and in the marshes during the dry season. The study suggests management practices that favor dominance of species that are most foraged in order to increase forage availability for the impalas in the sanctuary.
Mathematical Model for Predicting Climate Change Impact on Water Availability and Quality: A SWATSEIR Framework
(Iconic Research and Engineering Journals, 2025-07-07) Nyongesa, Fatuma Nandaha; Mulambula, Andanje; Konje, Martha Muthoni
Flood-prone regions, such as Budalangi in the Lake Victoria Basin, frequently experience endemic contamination of their water resources due to recurrent flooding events. Consequently, effective water management strategies in such regions must address not only acute contamination during flood events but also the persistent, chronic nature of waterborne contamination driven by climatic variability and infrastructural challenges. The framework successfully demonstrated the capacity to simulate the dynamic behavior of water systems influenced by environmental stressors, making it suitable for comprehensive climate water interaction assessments. This paper presents an integrated mathematical model that captures the dynamics between climate change and water security and analyze the impact of climate change on water security in Budalangi.
Modeling the Spatial Impact of Climate Change on Grevy’s Zebra (Equus grevyi) niche in Kenya
(Elixir Remote Sensing, 2013-09-07) Kigen, C.; Okoth, P.; Konje, Martha Muthoni; Shivoga, W.; Ochieno, D.; Wanjala, S.; Agevi, H.; Onyando, Z.; Soy, B.; Kisoyan, P.; Makindi, S.
Although Grevy’s zebra (Equus grevyi) is listed as endangered species and is an important attraction in Kenya’s tourism industry, there have been no attempts to model the implications of climate change on their niche. This study modeled the potential current and future (the year 2080) distribution in Kenya. The E. grevyi location data were sourced from published literature and climate data was downloaded from world climate database website and analysis done using MaxEnt and DIVA-GIS. The model generated an excellent AUC of 0.984 and the future niche is shown to expand. The main five variables contributing more than 2% of change in niche expansion are isothermality, precipitation of coldest quarter, annual mean temperature, annual precipitation, min temperature of coldest period and precipitation of wettest quarter. The generated information will assist conservation policy makers to make informed decisions.
Modelling AI Technologies towards Prediction of Disasters Related to Climate Change: Case Study of North Rift, Kenya
(International Journal of Applied Science and Engineering Review, 2025-08-07) Siunduh, Eric Sifuna; Ikoha, Peters Anselemo; Konje, Martha Muthoni
The study explores the application of artificial intelligence (AI) technologies for predicting climate change-induced disasters in Kenya's North Rift region. The North Rift, characterized by diverse topography including highlands, valleys, and arid plains, has experienced increasing frequency and severity of climate-related disasters such as floods, droughts, and landslides over the past decade. These events have significantly impacted agricultural productivity, water resources, infrastructure, and community livelihoods. The study employs machine learning algorithms, including random forests, convolutional neural networks, and long short-term memory (LSTM) networks, to analyze historical meteorological data, satellite imagery, and ground-based observations. This multi-modal approach enables the integration of traditional climate indicators with novel predictive features derived from remote sensing. The research leverages data from Kenya Meteorological Department stations, climate analysis products, and Earth observation satellites to develop regionally calibrated prediction models. Preliminary findings demonstrate that AI-based systems outperform conventional statistical methods in predicting the onset, intensity, and spatial distribution of climate disasters in the region. Notably, the LSTM models achieved 78% accuracy in forecasting drought conditions three months in advance, while CNN-based image analysis shows promising results in identifying flood-prone areas with 82% precision. The research addresses challenges related to data availability and quality through novel data fusion techniques and transfer learning approaches that adapt global climate models to local contexts. The study further examines the integration of AI predictions into existing early warning systems and disaster management frameworks. Stakeholder interviews with local government officials, community representatives, and disaster management agencies reveal both opportunities and barriers for effective implementation. Key recommendations include capacity building for local meteorological services, development of user friendly prediction interfaces, and community-based participatory approaches for validation and refinement of AI outputs. This research contributes to the growing field of climate AI and demonstrates the potential of machine learning in enhancing disaster preparedness and resilience in vulnerable regions. The findings provide a foundation for developing scalable AI-based early warning systems that can be adapted to similar ecological contexts across East Africa
Physicochemical characteristics and Biodegradability of organic fraction of solid wastes generated in Eldoret Municipality, Kenya
(Research Journal of Environmental and Earth Sciences, 2016-05-13) Khatiebi, Sandra; Siamba, Donald Namasaka; Konje, Martha Muthoni; Mulambalah, Chrispinus Siteti
This study was designed to characterise and assess the biodegradability of the organic portion of the waste from a fast growing agricultural urban centre, Eldoret, in North Rift of Kenya. This is because new strategies for waste management are aimed at integrating mechanical, thermal and biological processing for energy and reduction of the volume of waste to be disposed. Therefore bbiological methods are designed degrade organic carbon of MSW under controlled conditions to produce desired quality for final disposal should take into account, the proportions and characteristics of the components as a factor that would influence the biodegradability of the wastes. The study was carried out in Eldoret municipality, a fast expanding urban setting in Western Kenya that serves as an administrative centre of Uasin Gishu County. Waste samples were collected on delivery at dumpsite and categorised by source of waste based on the economic status of the households. Waste composition, proximate analysis for crude nutrients, volatile solids and biochemical gas potential of the waste were carried out to estimate the physicochemical and biodegradability characteristics of the waste. Results showed that putrescible/organic material constituted the largest component of the waste irrespective of the source. Its moisture content was expectedly high (> 50%). The organic fraction contains high levels of crude nutrients that can support microbial activities thus biodegradability. This was supported by the volatile solids profiles and the biochemical gas potential. Statistically, biodegradability of wastes from central business district was significantly (p<0.05) more degradable than from residential areas. This was attributable to the high organic carbon content.
Population Status And Conservation Hotspots Of Prunus Africana (Hook. F.) Kalkman In South Nandi Forest, Western Kenya
(Researchjournali’s Journal of Forestry, 2016-06-07) Koros, Hillary K.; Konje, Martha Muthoni; Wambua, Margaret M.; Chesire, Christopher K.; Odeny, Dickens; Malombe, Itambo B.
Prunus africana is assessed as vulnerable globally by the International Union for Conservation of Nature. The conservation status is however general and under-illustrated. It lacks details on the actual threats that cause precarious spatial distribution of the population in certain localities such as South Nandi Forest, Western Kenya. This study assessed the population structure of P. africana by correlation of biometric variable including Diameter at Breast Height and height class distribution and regeneration with the diversity and frequency of threats in spatial context of the plant species. Stratified Random Sampling was used to establish three belt transects of 400 m by 2 km within the forest and 1 km buffer zone in farmlands. The measure of mean, spread, normal distribution and correlation of biometric variables of P. africana was analysed using PAST (Version 4.3). Population structure was summarised using histograms and bar charts. Frequency distribution table was used to analyse the number of incidence of the threats to P. africana at plot level. T-test was used to test for differences in P. africana parameters among transects. The spatial distribution model of P. africana in the forest and buffer zone was mapped using the maximum entropy suitability mapping method as implemented in MAXENT software (Version 3.3.3k) and QGIS Brighton (version 2.6). Prunus africana population was highly concentrated in North eastern part of the forest and surrounding farmlands with admirable number of mature individuals. The Diameter at Breast Height distribution of P. africana in the forest showed unstable and intermittent population structure unlike a stable population in the surrounding farmlands. Although the seeds germinated profusely, there was poor establishment and survival. Key conservation threats were overgrazing, firewood collection, logging and charcoal burning. The study recommends both in-situ and ex-situ conservation measures.
Rainfall and Soils, Not Grazing Intensity, Determine the Composition and Productivity of Annual Plants in a Biodiverse Arid Winter Rainfall Region
(Journal of Natural Sciences Research, 2021-05-07) Konje, Martha Muthoni; Muoria, Paul K.; Wabuyele, Emily; Griffin, Neil; Vetter, Susanne
Concentration of grazer activity around watering points and stock posts has led to well-documented vegetation impacts in arid and semi-arid rangelands. Effect of grazing and abiotic factors on perennial plant diversity have been reported in the bio-diverse winter rainfall vegetation of the Succulent Karoo in South Africa, but the impact on annuals had not been investigated. The aim of this study was to assess the effect of rainfall, soil nutrients, land forms and grazing on forage depletion, soil chemistry and the composition, diversity, richness and biomass production of annual plants in the Richtersveld National park, which is a contractual national park used by seminomadic pastoralists to herd goats and sheep. A grazing gradient away from stock posts at 100m, 500m and 1000m on sandy plains and rocky foothills at five study sites with different mean annual rainfall and vegetation types were used. Distance from stock posts corresponded to a gradient of forage depletion and resulted in changes in soil chemistry with distance. Biomass production, richness and diversity of annuals were correlated with rainfall but not significantly affected by landform or distance from stock posts. Rainfall and soil variables had a greater influence on species composition than grazing in this arid ecosystem. The decrease in perennial cover and richness near the stock posts was not accompanied by increase in biomass production or richness of annuals, which is expected to have adverse effects on overall plant diversity and forage availability.
Spatial-temporal variation of biomass production by shrubs in the succulent karoo, South Africa
(Journal of Biodiversity and Environmental Sciences, 2021-04-30) Konje, Martha Muthoni; Muoria, Paul; Wabuyele, E.; Vetter, Susanne
Forage production in arid and semi-arid rangelands is not uniform but varies with seasons and in various landscapes. The aim of this study was to investigate the spatial and temporal variation in forage production in RNP. Plants sampling was carried out in 225 plots distributed in each of the five vegetation types. In each vegetation strata, sampling points was based on proximity to an occupied stock post, a rain gauge, a foothill and flat plains. A total of were measured in the 5 study sites. Line Intercept Method in combination with harvest method were used in ground measurement of biomass production. To assess biomass production using remote sensing technique, par values were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) imageries which consisted of 8 days composite images at spatial resolution of 1km² pixel size. There was positive correlation between line intercepts and biomass production Biomass production was higher in succulent Karoo biome than in desert biome. There was a strong relationship between biomass production with rainfall and with fpar values. Since leaf and stem succulents’ plants were found to contribute the highest amount of forage production in RNP, they should be given conservation priority.
Spatio-Temporal Variation In Forage Production In A Key Resource Area In Succulent Karoo Rangeland, South Africa
(Researchjournali’s Journal of Ecology, 2021-03-07) Konje, Martha Muthoni; Muoria, Paul; Wabuyele, Emily; Vetter, Susanne
For herbivores to survive in arid rangelands, they largely depend on landscapes that act as grazing reserves during the dry seasons. In Richtersveld National Park, the dry season forage consists of browse from tree branches, litter and grass that grow along the Orange River. The aim of the study was to determine how browse production by tree species along the riparian zone (a key resource area), vary between the sites, with time and among the tree species, as well as the implication of a dry season key resource in management of rangelands. Sampling of tree species took place at three study sites along the riparian zone. In each site, temporal available standing biomass, browse and litter production by the seven dominant tree species were sampled. To calculate the total biomass production per tree canopy area, branch-count method was used up to a height of 1.5 m. Browse production differed between the tree species and between sampling periods but not between the sampling sites. Key resource area was found to play an important role in sustaining herbivores populations during the dry seasons as well as to reduce the negative effects associated with continuous grazing on the landscapes.
The Role of Nyayo Tea Belt as A Buffer Zone in Sustainable Conservation of Kakamega Forest, Kenya
(Iconic Research and Engineering Journals, 2025-01-07) Vuyiya, Esther; Konje, Martha Muthoni
This study investigated the effectiveness of the Nyayo Tea Zone (NTZ) as a buffer zone in the conservation and management of Kakamega forest, Kenya, and assessed the impact of human activities on forest health. The research employed a mixedmethods approach, combining questionnaires administered to 339 randomly selected households within 5km of the NTZ boundary, structured interviews with key stakeholders, and experimental vegetation sampling. Four study sites were selected: Handidi, Lukusi, and Isecheno (adjacent to NTZ) and a Kenya Wildlife Service (KWS) site as control. Vegetation sampling used belt transects to assess tree species diversity, richness, canopy surface area, and seedling density. Results revealed that only 22.19% of the cleared forest land was utilized for tea plantation, while 59.02% was allocated to exotic forest species. All study sites adjacent to NTZ showed significantly lower species diversity, richness, canopy surface area, and seedling density compared to the KWS control site. Human activities (logging, grazing, debarking, and charcoal burning) demonstrated significant negative correlations with forest health indicators. Furthermore, 80% of respondents reported continued forest access despite the NTZ's presence, with only 2.5% recognizing its role as a conservation barrier. The study concludes that the NTZ buffer zone has not effectively achieved its conservation objectives, highlighting the need for more integrated approaches to forest protection and community engagement.
Use of Remote Sensing (MODIS) Data and Rainfall to Estimate Forage Production in Arid Rangeland
(Iconic Research and Engineering Journals, 2025-03-07) Konje, Martha Muthoni
This study investigated the use of remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and rainfall data to estimate forage production in the arid rangelands of the Richtersveld National Park, South Africa. The research aimed to assess the spatial and temporal variability in forage production across five vegetation types and three landscape units, and to examine the relationships between the fraction of photosynthetically active radiation (fPAR), rainfall, and biomass production. Field measurements of above-ground biomass were collected during the peak growing season in 2007 and compared with corresponding MODIS fPAR data. The results revealed significant spatial heterogeneity in forage production, with higher biomass observed in the Central Richtersveld Mountain and Northern Richtersveld Scorpionstailveld vegetation types, and in the mountain landscape unit. Leaf and stem succulents contributed the most to the available forage, while grasses and forbs dominated in the desert vegetation types. A strong positive linear relationship was found between MODIS fPAR and field biomass measurements, indicating the potential of using remote sensing data as a reliable proxy for forage production. Rainfall emerged as a key driver of vegetation dynamics, with both fPAR and biomass showing strong positive correlations with precipitation. The study highlights the importance of understanding the spatial and temporal variability in forage resources for effective rangeland management and conservation planning in arid environments. The findings suggest that the integration of remote sensing data and rainfall records can provide valuable insights into the dynamics of arid rangelands and support the development of adaptive management strategies in the face of increasing climate variability and land use pressures.
Uses, Threats and Conservation of Plant Species in Kisere Catchment Area of Kakamega Forest, Kenya
(International Journal of Science and Research, 2022-02-07) Bwambok, Eliud; Konje, Martha Muthoni
Tropical rainforests are under threat from human encouragement and anthropogenic activities in sub-Saharan Africa. Despite the importance of tropical rainforests, anthropogenic activities are changing vegetation dynamics of tropical rainforests such as Kakamega forest. The aim of the study was to determine the most exploited tree species in Kisere Forest by the local communities and their uses; to assess the impact of anthropogenic activities on plant species in Kisere Forest, to evaluate the contribution of Village Economic Enterprises on conservation of Kisere Forest. To determine the most targeted tree species by the local communities and their uses, semi-structured questionnaires were used and ethno-botanical survey was conducted. The Impact of Village Enterprise funded microenterprises on conservation of Kisere Forest was determined by comparing exploitation of the forest by funded households and unfunded households. This was done by assessing the time spent in the forest and the frequency of visiting forest to collect forest products and the collection of forest products for sale versus subsistence by the funded and unfunded households. Impacts of Village enterprise was also assessed by monitoring trends in forest disturbance. It was found out that most plant species were used for firewood, poles, charcoal burning and source o f medicine. Integrated conservation strategies aimed at providing people living around biodiversity hotspots with knowledge, skills and economic opportunities should be encouraged so that local communities can live sustainably with the forest ecosystems and protect local resources against future threats.
Using Digital Tools to Assess Soil Variables in Selected Counties in North Rift, Kenya
(AgroEnvironmental Sustainability, 2025-03-15) Mutonyi, Jonathan; Masayi, Nelly Nambande; Majengo, Collins Otieno; Konje, Martha Muthoni; Makokha, John Wanjala
The need for techniques and instruments that enable rapid soil testing has gained attention in the face of climate change and environmental degradation. This could improve efficiency and productivity by providing real-time, high-quality, and accessible data for decision-making. This study used GPS tools to visualize, analyze, and gather essential field information and applied Near Infra-Red Spectrometry to assess soil parameters and recommend corrective action for sustainable livelihood in five Counties in North Rift Kenya. Soil reaction varied from 5.5 in Kaptega, Transnzoia, to 7.8 in Kospir, Turkana counties. Low soil pH and CEC were recorded in parts of Nandi and Transnzoia counties. Soils from the dryland ecologies in Turkana, W. Pokot, and Samburu were predominantly alkaline. Total organic Carbon was generally low in the dryland ecologies of Samburu and Turkana. Low soil fertility was generally indicated in Samburu, Turkana, and W. Pokot. This was attributable to the low organic carbon levels and low precipitation, which may have negatively influenced soil microbial activity. Sustainable farming practices such as crop rotation, mulching, mixed farming, cover cropping, and minimum/conservation tillage are recommended in areas where crop cultivation is feasible. Amelioration of soils with agricultural lime and organic matter is highly recommended in the affected areas within the agropastoral counties for improved production to guarantee food security and sustainable livelihoods