TITLE:
Trends in Rainfall and Discharge over Zaaba Sub Catchment, Vihiga County, Kenya
AUTHORS:
Joel Philip Aholi, Mary Makokha, Kennedy Obiero
KEYWORDS:
Land Cover Changes, Mann Kendall, Rainfall Variability, Sen’s Slope, Streamflow, Zaaba River
JOURNAL NAME:
Open Access Library Journal,
Vol.11 No.10,
October
11,
2024
ABSTRACT: Temporal variation of rainfall has a direct influence on discharge of a river; however, considerable land cover changes through conversion of natural vegetation to agricultural land, settlement and commercial usage like urbanization have led to encroachment into forested, river riparian and other wetland areas therefore altering runoff generation through variation of rates of vegetal interception, infiltration, evapotranspiration and surface detention. This study determined rainfall trends and discharge from 1991 to 2020 and factors determining response of streamflow to rainfall variability in Zaaba river sub catchment in Vihiga County, Western Kenya. Rainfall data was sourced from Kenya Meteorological Department, discharge data was sourced from Water Resources Authority and land cover data was downloaded from USGS website http://www.earthexplorer.usgs.gov/. Trend analysis was determined by Z-Test, p-value and Sen’s slope estimator. Regression analysis determined the correlation between rainfall and discharge. Data from Key informant interviews, questionnaires and Focus Group Discussions was analysed through SPSS by computing totals and percentages and drawing charts. Rainfall trend analysis at α = 0.05 revealed rainfall was variable at monthly (p-value = 0.037 and Sen’s slope = 0.182), seasonal (Sen’s slope = −0.030 and p-value = 0.043 for MAM and Sen’s slope = 0.136 and p-value = 0.046 for OND) and annual (Sen’s slope = 1.081 and p-value = 0.010) time steps. Discharge trend analysis at α = 0.05 revealed existence of trend on seasonal (Sen’s slope = 0.51 and p-value = 0.009 for MAM and Sen’s slope = 0.521 and p-value = 0.008 for OND) and annual (Sen’s slope = 0.085 and p-value = 0.001). Regression analysis revealed insignificant seasonal correlation (MAM and OND with r = −0.124 and 0.067) and annual correlation (r = 0.051). Statistical analysis revealed that major land cover changes were agricultural area that decreased from 50.05% (2001) to 41.07% (2011) and 32.8% (2020) and increased buildup areas from 5.06% (2001) to 9.29% (2011) to 17.68% (2020) attributed to increased population, expansion of urban areas and encroachment into river riparian that decreased from 5.18% (2001) to 1.18% (2011) and 0.87% (2020). These findings would encourage capacity building on increasing rainfall trends and take measures to control floods.