Abstract:
Information on land use/land cover change, climate change and hydrology are required to make
decisions on land use planning, climate change adaptation and mitigation measures and for
sustainable water resources management. Nevertheless, such information collected at a scale
that enables to make site-specific decisions is lacking in Ethiopia in general and the Fafan
cathcment in particular. Cognizant of this gap, this study intended to investigate the impacts of
land use/land cover and climate changes on the hydrology of the Fafan catchment in the Wabi
Shebele River Basin of Ethiopia.
Landsat 5, 7, 8, and 9 imagery, along with field survey data, were utilized to detect and predict
land use/land cover (LULC) changes from 1990 to 2050. Methods applied included the maximum
likelihood classifier, post-classification analysis, multi-layer perceptron artificial neural
network, and cellular automata-Markov chain. The Land Change Modeler (LCM) in IDRISI was
used for change analysis, transition potential modeling, and change prediction. To assess the
impacts of LULC change on the catchment’s hydrology, satellite imagery and hydro-climatic
data were analyzed using the Mann-Kendall trend test, Sen’s slope estimator, the HBV Light
hydrological model, and other statistical tools. Spatio-temporal climate variability and trends
were examined using methods like the coefficient of variation, standardized temperature and
anomaly indices, Pearson correlation, the Mann-Kendall trend test, and Inverse Distance
Weighting (IDW). For analyzing the impact of projected climate change, historical hydro climatic data were acquired from local and nearby stations, while projected Global Circulation
Models (GCMs) data were sourced from the Coupled Model Intercomparison Project (CMIP-5).
An ensemble of 17 GCMs for the period 2022–2050 was downscaled using the MarkSim model
into RCP 4.5 and RCP 8.5 scenarios. The HBV Light model was employed to simulate
hydrological processes in response to the projected climate change.
The land use/land cover (LULC) change analysis revealed that between 1990 and 2021, forest,
grassland, and shrubland decreased by -13.2%, -4.6%, and -18%, respectively, while cropland,
settlement, and barren land increased by 19.2%, 11.7%, and 4.9%. Between 2022 and 2050,
cropland, settlement, and barren land are projected to increase by 9.1%, 3.5%, and 2.2%, while
shrubland, forest, and grassland are expected to decrease by -1.3%, -3.65%, and -10.1%,
respectively. The impacts of LULC change on hydrology showed a reduction of -51% in
vegetation zone one, while zones two and three increased by 385% and 62%, respectively. The
HBV Light model demonstrated good performance with NSE values of 0.61 and 0.66 and R²
values of 0.60 and 0.65 for calibration and validation periods, respectively. From 1990 to 2021,
annual and Kiremt surface runoff increased by 17% and 25%, respectively, while the Bega
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season saw a decrease of -15%. Evapotranspiration slightly increased, while seasonal soil
moisture decreased by -32% during the Belg season and increased by 14% during the Kiremt
season. Climate variability and trends (1991–2020) indicated low temperature variation and
high rainfall variation. Maximum and minimum temperatures showed increasing trends during
the Kiremt and Belg seasons. Extreme annual and seasonal temperature conditions were
identified, along with moderate wet and extreme-to-severe dry rainfall conditions. Rainfall
showed a positive correlation with sea surface temperature indices during the Kiremt and a
negative correlation in other seasons. Projected climate change impacts on hydrology showed
that annual minimum temperature is expected to increase by 25% (RCP 4.5) and 34% (RCP 8.5),
while annual maximum temperature is projected to decrease by -4% (RCP 4.5) and -2% (RCP
8.5). Annual rainfall is expected to increase by 1% (RCP 4.5) and 3% (RCP 8.5). The HBV
model predicts an annual surface runoff increase of 34% (RCP 4.5) and 42% (RCP 8.5), along
with a rise in potential evapotranspiration of 62% (RCP 4.5) and 63% (RCP 8.5). Groundwater
recharge is projected to decrease annually by -42% (RCP 4.5) and -33% (RCP 8.5), while soil
moisture may decrease by -11% and -47% under the respective scenarios. The study emphasizes
the substantial impacts of LULC and climate changes on catchment hydrology, underscoring the
need for sustainable land and water management practices such as reforestation, soil
conservation, controlled agricultural expansion, and adaptive water management strategies like
constructing water storage systems to address projected hydrological shifts.