Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover changes (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC that happened during 25 years was investigated, comparing the situation in three reference years: 1994, 2004, and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM, and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated, the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 20.0% between the years 1994–2004, and it decreased by 11.8% in the following period 2004–2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 hydrologic response units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.

中文翻译：

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埃塞俄比亚 Fincha'a 流域土地利用土地覆盖变化的水文响应

土地利用土地覆盖 (LULC) 变化在非洲国家非常明显，因为它们的特点是以农业为基础的经济和快速增长的人口。了解土地利用/覆盖变化 (LULCC) 如何影响流域水文将使地方政府和决策者能够制定和实施有效和适当的响应策略，以最大限度地减少未来土地利用/覆盖变化或修改的不良影响，并维持当地的社会经济状况. 调查了埃塞俄比亚 Fincha'a 流域对 LULCC 25 年的水文响应，比较了三个参考年的情况：1994、2004 和 2018。信息来自 Landsat 传感器，分别来自 Landsat 5 TM、Landsat 7 ETM 和 Landsat 8 OLI/TIRS。使用监督分类系统通过 ArcGIS 推导出各种 LULC 类，并使用混淆矩阵进行准确性评估。在所有调查年份中，总体准确率和 kappa 系数均高于 80%，其中 2018 年为更准确的年份。LULCC 的分析表明，1994-2004 年间森林减少了 20.0%，随后的 2004-2018 年减少了 11.8%。森林覆盖面积的减少与耕地面积分别扩大了 16.4% 和 10.81% 相关。在流域尺度评估 LULCC 后，流域被划分为 18 个子流域，其中包含 176 个具有特定 LULC 的水文响应单元 (HRU)。考虑到 Fincha'a 流域的如此详细的细分，SWAT 模型首先根据过去的数据进行校准和验证，然后应用于推断 LULCC 上每个 HRU 的水文响应信息。建模结果表明，由于土地覆盖从森林和草地向定居点和建筑区转移，平均水流量在旱季和雨季普遍增加。目前的分析指出，在为流域尺度的河流水文响应建模时需要考虑过去和未来的 LULCC。