Browsing by Author "Kaitho, R."

Now showing 1 - 4 of 4
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    Agricultural climate change impact: General concerns and findings from Mali, Kenya, Uganda, and Senegal
    Butt, T.; Angerer, Jay; Dyke, P.; Kim, M.; Kaitho, R.; Stuth, Jerry (2004)
    This paper discusses concerns about the impact of climate change on agriculture. Methods for assessing the impacts of climate change and the results from impact assessments in Mali, Kenya, Uganda, and Senegal are presented.
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    Impacts of reforestation policy and agro-forestry technology on the environment and food security in the Upper Tana river basin of Kenya
    Srinivasan, R.; Jacobs, J.; Stuth, Jerry; Angerer, Jay; Kaitho, R.; Clarke, N. (2004)
    This presentation is on a study to explore the hydrologic impacts on the Masinga reservoir in response to land use interventions in the Upper Tana River catchment with a focus on varying levels of reforestation.
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    Policy and technology options for dairy systems in East Africa: Economic and environmental assessment
    Kaitho, R.; Eddleman, B.; Chen, Chi Chung; McCarl, Bruce A.; Angerer, Jay; Stuth, Jerry (2001)
    Assessment of smallholder dairy technology was used as a case study to develop models in the SANREM decision support system. Scenarios depicting the industry before current improvements, the current situation, and forecasted improvements resulting from further adoption of technology were evaluated. GIS methods were used to establish appropriate sampling frames for field studies and analysis. Forage and livestock models supplemented reported data as input to economic and environmental models. Assessment of the impact of alternative smallholder dairy technology packages was evaluated in the Sondu river basin using watershed models driven by economic and environmental models. With demand growth from projected population increases, full adoption of the improved dairy technology package would generate total economic welfare of KS 4,206 million. Full adoption of the technology package in the Sondu river basin would increase sediment loads in the basin by 5% over a 21-year period and stream flow would increase slightly. The general models developed from initial smallholder dairy studies predict annual increases in productivity of between 0.3 and 0.5% per year would be required to sustain food prices at current levels with 2015 demand. Intensification and extensification strategies were evaluated to achieve these levels of productivity. Combinations of strategies were predicted to be the most rational in meeting future food security demands with sustainable use of natural resources.
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    Use of satellite-derived data to improve biophysical model output: An example from Southern Kenya
    Angerer, Jay; Stuth, Jerry; Wandera, F.; Kaitho, R. (Watkinsville, GA: SANREM CRSP, 2001)
    The use of satellite data products produced by the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) was explored to determine if these products could be used to provide plant growth model output for large landscapes. The use of satellite-derived data is generally advantageous because it is spatially dense (i.e., many measurements for a large landscape). Gridded daily temperature (0.1 x 0.1 degree) and rainfall (8x8 km), derived from the METEOSAT satellite, were used as inputs into the PHYGROW plant growth model for 30 pastoral households in southern Kenya. After model runs were completed, cokriging was used to determine if model output, coupled with NASAï'½s Normalized Difference Vegetation Index (NDVI) product (a greenness index), could be used to create forage production maps for a large landscape. Cokriging is a geostatistical technique that allows one to take advantage of spatial autocorrelation (i.e., things closer together in space are usually similar than those farther apart), and the similarity between a small number of data points (model output in our case) and a one that is spatially dense (NDVI). Using cokriging, the majority of ten-day averages for year 2000 had moderate to high similarity between model output and NDVI. A comparison of model output and estimates from cokriging indicated that cokriging generally did a good job of estimating forage available for the 30 pastoral households. Mapped surfaces of the cokriging output successfully identified areas of drought in year 2000. Institutions at all levels could use these mapped surfaces as part of their GIS, which can then be linked to economic models, natural resource management assessments, or used for drought early warning systems.