Browsing by Author "Raude, James"

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  • Publication
    Publication
    Analysis of spatial and temporal drought variability in a tropical river basin using Palmer Drought Severity Index (PDSI)
    (Acadamic Journals, 2017-08-31) Wambua, Raphael; Mutua, Benedict; Raude, James
    Analysis of spatial and temporal drought variability in the upper Tana River basin using Palmer Drought Severity Index (PDSI) was conducted. The drought is critical for formulation of mitigation measures in the river basin. A monthly temporal and 90-m spatial resolution was applied. This was achieved within ArcGIS environment. Climatic data for 1970 to 2010 was used for computation of the PDSI while the missing data sets were filled using Artificial Neural Networks (ANNs). The results of PDSI for dry and wet seasons at meteorological stations indicate that the time series plots for the PDSI values for dry season are generally lower than those for the wet seasons. The PDSI values for meteorological stations located at the lower elevation of the basin are lower than those located at higher elevation. On the other hand, spatially distributed drought severity based on PDSI show that the ranges of maximum and minimum drought severity values in 1970 are -0.868 to -0.804 and -0.675 to -0.610 respectively. These values of drought severity occur respectively in the north-western and south-eastern areas of the basin. PDSI values increased from the range -0.675 to -0.610 in 1970 and from -1.087 to 0.957 in 2010 for the north-eastern areas of the upper basin. The south eastern areas of the basin are more prone to drought risks than north-western parts. Use of the PDSI reflects the spatial heterogeneity and temporal variability of drought across the basin. The drought assessment offer technical approach for comprehensive understanding of drought for effective drought-induced disaster mitigation and its management, with a view to reducing adverse effects on livelihoods.
  • Publication
    Publication
    Assessing the Impact of land-use types on the groundwater quality: a case study of Mid River Njoro Catchment, Kenya
    (acque sotterranee, 2020-12-22) Rendilicha, Halake; Home, Patrick; Raude, James; M'Erimba, Charles; Muthoka, Stellamaris
    The study assessed the impact of land-use types on the groundwater quality of the mid River Njoro catchment, Kenya. Groundwater samples were collected from eight boreholes between the period of October 2017 to February 2018 and analyzed for pH, temperature, electrical conductivity, dissolved oxygen, nitrate, ammonium, and total phosphorus. These parameters were used to calculate the Groundwater Quality Index (GQI) value of the study area. The concentration maps (“primary maps I”) were constructed using Kriging interpolation of ArcGIS software from the seven groundwater quality parameters. The “primary maps I” were standardized with the KEBS and WHO standards to the “primary maps II” for ease of integration into a GIS environment. The “primary maps II” were then rated and weighted using a polynomial function to generate “rank maps” before calculating the GQI using spatial analyst tools of ArcGIS software. The land use map was prepared from a high-resolution Google earth satellite imagery of 2015. The mean GQI values for the different land use polygons were calculated and compared using GIS techniques. The GQI ranged from 68.38 to 70.92, indicating a high groundwater quality of mid River Njoro catchment. The major land-use types identified include settlement area, forest cover, agricultural land and mixed area. The agricultural land dominated the study area, followed by settlement area, forest cover and finally mixed area. The mean GQI value in each land use type varied minimally and this could be because of the diffuse nature of the land use types of the study area. Settlement area had low GQI, followed by agricultural land, mixed area and the forest cover had the highest mean GQI value, which corresponds to good quality of groundwater. Even though the variation is insignificant in this particular study, it somehow indicates the adverse effects of different land use on the quality of groundwater.