Abstract:
Runoff is the water that flows across the land’s surface due to gravity, replenishing groundwater
and surface water as it seeps into aquifers or moves into rivers, streams, and watersheds. This
phenomenon occurs when the amount of water exceeds the land’s capacity to absorb it, leading
to excess water flowing into nearby creeks, streams, or ponds. Runoff can result from both
natural processes and human activities. This study aimed to estimate the surface runoff volume
of the
Kirimbi River using Geographic Information Systems (GIS) and remote sensing techniques. The
specific objectives were to identify the factors influencing surface water runoff, assess the effects
of surface runoff volume, evaluate runoff using the SCS-CN method, and analyse the
relationship between rainfall and runoff. By utilizing advanced remote sensing and GIS
techniques, the study estimated surface runoff based on various parameters, including land
use/land cover (LULC), hydrological soil characteristics, rainfall data (P), potential maximum
retention (S), antecedent moisture condition (AMC), and weighted curve number (CN). The
LULC map was classified into five categories: water body, agriculture, built-up areas, forest, and
bare soil, revealing that water bodies have low runoff potential while bare soil exhibits high
runoff. The hydrologic soil groups (HSG) were classified into four categories: A, B, C, and D,
with group a showing low runoff and group D showing high runoff. Integrating LULC and HSG
allowed for the determination of CN values, with a weighted curve number calculated using
normal antecedent moisture condition II (AMC II). The average CN under these conditions was
found to be 8.42. Monthly rainfall data from 2022 was used to calculate runoff, revealing an
average runoff volume of 462.182 mm³. The findings conclude that the integration of the SCS-
CN method and GIS effectively evaluates surface runoff volume. It is recommended that
government and non-government organizations promote the establishment of rainwater
reservoirs, as water is scarce and essential for daily human activities. Additionally, further
research should explore alternative methods for estimating runoff to compare -+*the results from
different approaches.
