Emmanuel C. Kipkorir

Multitemporal comparative analysis of TRMM-3B42 satellite-estimated rainfall with surface gauge data at basin scales: daily, decadal and monthly evaluations

In order to examine the reliability and applicability of Tropical Rainfall Measuring Mission (TRMM) and Other Satellites Precipitation Product (3B42) Version 6 (TRMM-3B42) at basin scales, satellite rainfall estimates were compared with geostatistically interpolated reference data from 12 rain gauge stations for three consecutive years: 2005, 2006 and 2007. Gauge–TRMM-3B42 statistical properties for daily, decadal and monthly multitemporal precipitations were compared using the following cross-validation continuous statistical measures: mean bias error (MBE), root mean square difference (RMSD), mean absolute difference (MAD) and coefficient of determination (r 2) metrics. The averaged spatial–temporal comparisons showed that the TRMM-3B42 rainfall estimates were much closer to the geostatistically interpolated gauge data, with minimal biases of −0.40 mm day−1, −1.78 mm decad−1 and −6.72 mm month−1 being observed in 2006. In the same year, the gauge and TRMM-3B42 rainfall estimates marginally correlated better than in 2005 and 2007, with the daily, decadal and monthly coefficients of determination being 82.2%, 93.9% and 96.5%, respectively. The results showed that the correlations between the gauge-derived precipitation and the TRMM-3B42-derived precipitation increased with increasing temporal intervals for all three considered years. Quantitatively, the TRMM-3B42 observations slightly overestimated the precipitations during the wet seasons and underestimated the observed rainfall during the dry seasons. The results of the study show that the estimates from TRMM-3B42 precipitation retrievals can effectively be applied in the interpolation of missing gauge data, and in the verification of precipitation uncertainties at the basin scales with minor adjustments, depending on the timescales considered.

MCDA-GIS integrated approach for optimized landfill site selection for growing urban regions: an application of neighborhood-proximity analysis

The exponential rise in urban population and the resulting urban waste generation in developing countries over the past few decades, and the resulting accelerated urbanization phenomenon has brought to the fore the necessity to engineer environmentally sustainable and efficient urban waste disposal and management systems. Intelligent and integrated landfill siting is a difficult, complex, tedious, and protracted process requiring evaluation of many different criteria. Optimized siting decisions have gained considerable importance in ensuring minimum damage to the various environmental sub-components as well as reducing the stigma associated with the residents living in its vicinity. This article addresses the siting of a new landfill using a multi-criteria decision analysis integrated with overlay analysis within a geographical information system. The integrated multi-criteria decision analysis–geographical information system employs a two-stage analysis, synergistically, to form a spatial decision support system for landfill siting in fast-growing urban centers. Several correlated factors are considered in the siting process including transportation systems, water resources, land use, sensitive sites, and air quality. Weightings were assigned to each criterion depending upon their relative significance and ratings in accordance with the relative magnitude of impact. The results, analyzed using neighborhood-proximity analysis, show the effectiveness of the system in the site-selection process for Eldoret Municipality (Kenya), in the short- and long-term solid waste disposal siting options.

Integration of Indigenous Knowledge Systems into Climate Change Adaptation and Enhancing Food Security in Nandi and Keiyo Districts, Kenya

The increasing changes in the frequency, intensity and persistence of rainfall and temperature extremes are key determinants of food security vulnerability in Kenya. Shorter growing seasons and prolonged intra-seasonal dry spells often trigger much larger and more frequent harvest collapses than subsistence households can cope with, leading to declining crop production and increased food insecurity risks. To survive these climate-induced shocks, communities in Nandi and Keiyo districts have developed indigenous practices that enable them reduce vulnerability to food insecurity and adapt to changing climatic conditions. Despite the critical role the indigenous knowledge system (IKS) plays in sustaining household food security, it is rarely considered or integrated into the design of scientific strategies for climate change adaptation. This paper highlights indigenous strategies used by the Nandi and Keiyo communities and explores opportunities for integrating IKS with scientific strategies for climate change adaptation in order to sustain efforts for climate change adaptation and food security risk reduction. Participatory rural appraisal comprising focus group discussions, key informant interviews and household questionnaire surveys were used in the study. The results indicate that while the impacts of climate change directly affect food security, most households integrate both indigenous and modern practices in adapting to climate change and coping with the resulting risks associated with food insecurity. As such, there is a need to reinforce the integration of indigenous and scientific techniques in order to enhance efforts for climate change adaptation, food security risk management and perpetuate intra/intergenerational transfer of IKS.

Improving the Participation of Agro-Pastoralists in Climate Change Adaptation and Disaster Risk Reduction Policy Formulation: A Case Study from Keiyo District, Kenya

Growing scientific evidence suggests that climate change will accelerate weather extremes and increase human vulnerability to disasters. Exposure of agro-pastoralists to erratic rainfall and cyclical droughts leads to frequent crop failures and livestock losses, with additional shocks from economic perturbations and erosion of household assets depriving this vulnerable group of “insurance” against adverse risks, driving them from a state of vulnerability to destitution. Despite the growing global agitation to mainstream community-based strategies for climate change adaptation (CCA) and disaster risk reduction (DRR) in Kenya, existing institutional and policy formulation processes rarely incorporate the views and experiences of agro-pastoralists. This leads to policies that are neither responsive nor accountable to vulnerable groups. This paper identifies existing community strategies for CCA and DRR in Keiyo district and assesses their level of participation in policymaking, as well as key challenges and opportunities for mainstreaming agro-pastoralist involvement in policy formulation. The data was obtained through participatory approaches involving focus group discussions (FGDs), questionnaires and structured interviews. It is evident from the findings of the study that while agro-pastoralists have developed localised strategies for CCA and DRR, these are not fully recognised by existing government policy processes. Therefore, efforts should be made to mainstream the participation of agro-pastoralists in CCA and DRR policy formulation processes.