Assessment of hydrological water balance in Lower Nzoia Sub-catchment using SWAT-model: towards improved water governace in Kenya

Abstract

Kenya's catchments has both natural and disturbed environments. Within these environments, there has been interaction between hydrological, physical and ecological characteristics. Therefore, impacts of Land Use Land Cover (LULC) change on surface and sub - surface hydrology needs to be well understood due to the increasing population competing for scarce natural resources such as water, trees and forest land. The water balance components' spatial and temporal dynamics in relationship to the LULC change between 2003 and 2018 in the Lower Nzoia Sub - Catchment (LNSC) in Kenya was therefore assessed. Landsat data with 30 m (m) spatial resolution was used in understanding LULC dynamics of the study area using Supervised Classification Approach (Interactive Classification Method) in ArcGIS 10.5. After landsat image classification, key water balance components including; surface runoff (SURFQ), lateral flow (LATQ), groundwater recharge (BASEQ), deep acquifer recharge (DEEPQ), evapotranspiration (ET) and groundwater revap (REVAP) for years 2003 and 2018 were estimated using SWAT model in ArcSWAT. The overall accuracies for 2003 and 2018 classified images were 75.9% and 98.9% respectively which are showing good values. The results of the study showed that agricultural land coverage reduced from 83.1% in 2003 to 78.6% in 2018. Rangeland on the hand increased from 6.3% to 9.8% while urban/built - up area increasing from 10.6% to 11.6%. The annual water balance components from the LULC distribution of the two time periods shows that ET reduced, SURFQ increased, BASEQ reduced, DEEPQ reduced, LATQ reduced and REVAP reduced. At catchment level, results show that 2018 had a higher water balance than 2003 which can partly be explained by land cover decrease. The relationship between rainfall distribution, Land Surface Temperature (LST) and LULC change were further compared. At the same time, the study found out that there is limited focus to date on rural communities climate adaptive capacity. Hence, water institutions in the sub - catchment such as Water Resources Authority (WRA) are yet to fully mainstream adaptive capacity into their organizational structure and policies.

Keywords: Accuracy assessment; Adaptive capacity; Land use/ land cover; Lower Nzoia sub- catchment; Water availability; Water balance.

Figure 1

Map of lower Nzoia Sub – Catchment in Kenya.

Figure 2

(a) SWAT model calibration using observed and simulated flow of Wuoroya River from 1991-2006. (b) SWAT model validation using observed and simulated flow of Wuoroya River from 2007-2013.

Figure 3

Temporal and spatial distribution of various LULC in LNSC over the last 30 years (1988–2018).

Figure 4

Six water balance components of LNSC as a percentage of annual rainfall in 2003 and 2018 as derived from simulated SWAT model.

Figure 5

LST, rainfall distribution and LULC comparative analysis in LNSC for years 2003 and 2018.

Figure 6

Wuoroya River Flow Duration Curve between 1974 – 2014 using observed flow.

Figure 7

Population trend in Nzoia Catchment between 1989 and 2019.

Figure 8

State of adaptive capacity in LNSC using adoptive capacity components (adopted from Cinner et al., 2018).