Unveiling gully erosion susceptibility: A semi-quantitative modeling approach integrated with field data in contrasting landscapes and climate regions

IF 3.1 2区 地球科学 Q2 GEOGRAPHY, PHYSICAL Geomorphology Pub Date : 2024-10-31 DOI:10.1016/j.geomorph.2024.109485
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Abstract

This study addresses the challenge of mapping gully erosion susceptibility, which is often hindered by limited observed data, the complexity of controlling factors, and the uncertainties associated with characterizing these factors. We utilized a semi-quantitative modeling approach that integrates field-based data and ten controlling factors in the Chemoga watershed of Ethiopia's Upper Blue Nile basin. The resulting gully erosion susceptibility map was compared with a random forest-based approach to assess the methodological applicability. Additionally, an independent dataset from adjacent watersheds was used to validate the approach. The findings revealed that certain landscape positions with specific elevation ranges and slope steepness were more susceptible to gully erosion due to factors such as rainfall, lithological formations, soil characteristics, and agricultural activities. Approximately 10 % of the watershed area was affected by gully erosion, with varying susceptibility levels. The comparison between the semi-quantitative and random forest approaches demonstrates a total agreement of around 58 %, with minimal differences in susceptibility classes. The study also highlights a strong agreement between simulated and observed susceptibility maps, with a 76 % PBIAS (Percent Bias) value for the simulation and a lower 48 % agreement for the random forest approach. Furthermore, in the adjacent watershed, 65 % of the area exhibits no discrepancies between observed and simulated maps. This suggests that the semi-quantitative approach is effective in extrapolating gully erosion susceptibility when detailed data is limited, offering a cost-effective and efficient solution. The study emphasizes the utility of the semi-quantitative modeling approach in mapping gully erosion susceptibility and its potential for practical applications in land management and intervention strategies.
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揭示沟谷侵蚀的易发性:半定量建模方法与对比地貌和气候区域的实地数据相结合
这项研究解决了绘制沟谷侵蚀易发性地图所面临的挑战,因为观测数据有限、控制因素复杂以及描述这些因素所带来的不确定性往往会阻碍绘制工作。我们采用了一种半定量建模方法,将埃塞俄比亚青尼罗河上游流域 Chemoga 流域的实地数据和十个控制因素整合在一起。我们将绘制的沟壑侵蚀易感性地图与基于随机森林的方法进行了比较,以评估该方法的适用性。此外,还使用了邻近流域的独立数据集来验证该方法。研究结果表明,受降雨、岩层、土壤特性和农业活动等因素的影响,某些具有特定海拔范围和坡度的地貌位置更容易受到沟壑侵蚀。约有 10% 的流域面积受到沟壑侵蚀的影响,易受影响的程度各不相同。半定量方法与随机森林方法之间的比较显示,两者之间的总体一致性约为 58%,易受侵蚀程度等级之间的差异极小。研究还强调了模拟和观测易感性地图之间的高度一致性,模拟的 PBIAS(偏差百分比)值为 76%,而随机森林方法的一致性较低,仅为 48%。此外,在邻近流域,65% 的区域观测到的地图与模拟地图没有差异。这表明,在详细数据有限的情况下,半定量方法可有效推断沟谷侵蚀易发性,是一种经济高效的解决方案。这项研究强调了半定量建模方法在绘制沟壑侵蚀易发性地图方面的实用性,以及在土地管理和干预策略方面的实际应用潜力。
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来源期刊
Geomorphology
Geomorphology 地学-地球科学综合
CiteScore
8.00
自引率
10.30%
发文量
309
审稿时长
3.4 months
期刊介绍: Our journal''s scope includes geomorphic themes of: tectonics and regional structure; glacial processes and landforms; fluvial sequences, Quaternary environmental change and dating; fluvial processes and landforms; mass movement, slopes and periglacial processes; hillslopes and soil erosion; weathering, karst and soils; aeolian processes and landforms, coastal dunes and arid environments; coastal and marine processes, estuaries and lakes; modelling, theoretical and quantitative geomorphology; DEM, GIS and remote sensing methods and applications; hazards, applied and planetary geomorphology; and volcanics.
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