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Study area: aridity zones (Gichuki et al., 2002), rivers, commercial export farms in the Upper Ewaso Ng'iro catchment.
Source publication
In the Horn of Africa Drylands (HAD) conflict over water and vegetation is prominent. Additionally, large-scale land acquisitions (LSLAs) are increasing the competition of water, putting local communities at greater risk. A key impact of increasing LSLA's is the decrease in water and land availability for vulnerable agropastoral communities. Despit...
Contexts in source publication
Context 1
... Ewaso Ng'iro North catchment, spanning 210,000 km2 , sources its water primarily from Mount Kenya and the Aberdare Range ( Kiteme et al., 2021). These main water towers, located to the south of the catchment, contribute to the varied climatic zones observed in the region (Fig. 1). The upstream areas exhibit a humid climate with an altitude up to 5000 m and mean annual rainfall of 1500 mm, transitioning to semi-arid and arid conditions downstream with a minimum altitude of 500 m and mean annual rainfall of 350 mm (Mungai et al., 2004). This climatic gradient is essential in determining land use and the 70 ...
Context 2
... higher rainfall and more stable water supplies, are dominated by cropland and forests. This area supports large commercial export farms, particularly horticulture and floriculture, which benefit from the favourable 75 year-round climate and abundant water resources ( , Wiesmann et al. 2000. They are indicated in red south east of the catchment in Fig. 1. These farms are primarily concentrated in sub-catchments 1 and 2, with greenhouse operations spread throughout these areas. Sub-catchment 3 has similar conditions but only upstream, while sub-catchment 4 houses open farms, such as those cultivating wheat. Conversely, the downstream regions (sampling area), marked by arid conditions ...
Context 3
... export farms are included in the model as water and land users in the upstream areas of the catchment (Fig. 1). ...
Context 4
... of parameters in all model components is performed using the Distributed Evolutionary Algorithms in Python (DEAP) software (Fortin et al, 2012), which makes use of the Non-Dominated Sorting Genetic Algorithm known as NSGA-II ( Deb et al., 2002). Discharge at the outlet of the catchment, milk production, and crop production are the variables used for calibration and validation. ...
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