Dept. of Civil, Environmental and Architectural Engineering, University of Kansas, United States of America.
Dept. of Civil, Environmental and Architectural Engineering, University of Kansas, United States of America.
Sci Total Environ. 2021 Apr 10;764:144255. doi: 10.1016/j.scitotenv.2020.144255. Epub 2020 Dec 24.
Erosion and connectivity are spatially varied processes key to determining sediment transport and delivery to downstream waterbodies. However, we find few studies that explicitly model the linkages of where erosion and connectivity coincide and where they contradict, particularly in urbanizing settings. In this study, we couple in-stream aquatic sensing, the Revised Universal Soil Loss Equation (RUSLE), the Index of Connectivity (IC), and the Sediment Delivery Ratio (SDR), together with Monte Carlo uncertainty analysis, to generate a new Erosion-Connectivity Mapping (ECM) framework. We evaluate ECM accuracy with field assessment of thirty-five sites spread across five lowland watersheds (mean slope <5°) in Johnson County, Kansas, USA, which differ primarily in their land use, ranging from 21% to 89% urban. RUSLE modeling results indicate erosion is controlled by topography with high risk areas near streambanks roadway systems. SDR and IC were positively related at the five sites (R2 = 0.78, p < 0.05) with the highest values in the most urbanized watershed, indicating that anthropogenic change augments connectivity. The ECM results indicate that while only 5±1% of the study area is both highly erodible and highly connected, these areas represent 37±4% of total watershed-scale erosion. Our modeling results indicate that erosion is more likely to be the limiting factor in sediment transport, as opposed to connectivity, as there are generally more locations that are well-connected to hydrologic transport but resistant to erosion. Our field assessment provided broad support for the ECMs; however, field assessment indicated that geospatial modeling underpredicts how closely related erosion and connectivity are in the field and we suggest that future models consider this coupling more explicitly. This study provides a method for combining RUSLE and IC in a new tool (ECM) to identify spatial patterns in sediment erosion-connectivity to aid in the understanding and management of watershed sedimentation.
侵蚀和连通性是决定泥沙输送和向下游水体输送的空间变化过程的关键。然而，我们发现很少有研究明确模拟侵蚀和连通性一致和矛盾的地方，特别是在城市化环境中。在这项研究中，我们将溪流中的水感测、修正的通用土壤流失方程（RUSLE）、连通指数（IC）和泥沙输送比（SDR）结合在一起，并进行蒙特卡罗不确定性分析，以生成一个新的侵蚀-连通性映射（ECM）框架。我们使用在美国堪萨斯州约翰逊县的五个低地流域（平均坡度<5°）的三十五处实地评估来评估 ECM 的准确性，这些流域的土地利用主要从 21%到 89%的城市化程度不等。RUSLE 模型结果表明，侵蚀受到地形的控制，靠近河岸和道路系统的地方风险较高。SDR 和 IC 在五个地点呈正相关（R2=0.78，p<0.05），在城市化程度最高的流域中值最高，表明人为变化增强了连通性。ECM 结果表明，虽然只有 5±1%的研究区域既高度易侵蚀又高度连通，但这些区域代表了总流域尺度侵蚀的 37±4%。我们的建模结果表明，侵蚀更有可能成为泥沙输送的限制因素，而不是连通性，因为通常有更多的位置与水文输送密切相关，但抗侵蚀性更强。我们的实地评估为 ECM 提供了广泛的支持；然而，实地评估表明，地理空间模型在多大程度上低估了侵蚀和连通性在实地的密切关系，我们建议未来的模型更明确地考虑这种耦合。本研究提供了一种将 RUSLE 和 IC 结合在一个新工具（ECM）中识别泥沙侵蚀-连通性空间模式的方法，以帮助理解和管理流域泥沙沉积。
