气候变化领域集成服务门户(CCPortal): A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors-a case study for Kenya and Uganda

CCPortal

DOI	10.5194/hess-24-4463-2020
	A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors-a case study for Kenya and Uganda
	Schürz C.; Mehdi B.; Kiesel J.; Schulz K.; Herrnegger M.
发表日期	2020
ISSN	1027-5606
起始页码	4463
结束页码	4489
卷号	24 期号:9
英文摘要	The Universal Soil Loss Equation (USLE) is the most commonly used model to assess soil erosion by water. The model equation quantifies long-term average annual soil loss as a product of the rainfall erosivity R, soil erodibility K, slope length and steepness LS, soil cover C, and support measures P. A large variety of methods exist to derive these model inputs from readily available data. However, the estimated values of a respective model input can strongly differ when employing different methods and can eventually introduce large uncertainties in the estimated soil loss. The potential to evaluate soil loss estimates at a large scale is very limited due to scarce in-field observations and their comparability to long-term soil estimates. In this work we addressed (i) the uncertainties in the soil loss estimates that can potentially be introduced by different representations of the USLE input factors and (ii) challenges that can arise in the evaluation of uncertain soil loss estimates with observed data. In a systematic analysis we developed different representations of USLE inputs for the study domain of Kenya and Uganda. All combinations of the generated USLE inputs resulted in 972 USLE model setups. We assessed the resulting distributions in soil loss, both spatially distributed and on the administrative level for Kenya and Uganda. In a sensitivity analysis we analyzed the contributions of the USLE model inputs to the ranges in soil loss and analyzed their spatial patterns. We compared the calculated USLE ensemble soil estimates to available in-field data and other study results and addressed possibilities and limitations of the USLE model evaluation. The USLE model ensemble resulted in wide ranges of estimated soil loss, exceeding the mean soil loss by over an order of magnitude, particularly in hilly topographies. The study implies that a soil loss assessment with the USLE is highly uncertain and strongly depends on the realizations of the model input factors. The employed sensitivity analysis enabled us to identify spatial patterns in the importance of the USLE input factors. The C and K factors showed largescale patterns of importance in the densely vegetated part of Uganda and the dry north of Kenya, respectively, while LS was relevant in small-scale heterogeneous patterns. Major challenges for the evaluation of the estimated soil losses with in-field data were due to spatial and temporal limitations of the observation data but also due to measured soil losses describing processes that are different to the ones that are represented by the USLE. © 2020 Author(s).
语种	英语
scopus关键词	Erosion; Sediment transport; Sensitivity analysis; Soils; Uncertainty analysis; Observation data; Rainfall erosivity; Soil erodibility; Spatial patterns; Support measure; Systematic analysis; Systematic assessment; Universal soil loss equation; Soil surveys; assessment method; erosivity; estimation method; rainfall; soil cover; soil erosion; uncertainty analysis; Universal Soil Loss Equation; Kenya; Uganda
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159309
作者单位	Schürz, C., Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria; Mehdi, B., Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria, Institute of Agronomy, University of Natural Resources and Life Sciences, Vienna (BOKU), Tulln, Austria; Kiesel, J., Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany, Institute of Natural Resource Conservation, Department of Hydrology and Water Resources Management, Christian Albrechts University of Kiel, Kiel, Germany; Schulz, K., Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria; Herrnegger, M., Institute for Hydrology and Water Management, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
推荐引用方式 GB/T 7714	Schürz C.,Mehdi B.,Kiesel J.,et al. A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors-a case study for Kenya and Uganda[J],2020,24(9).
APA	Schürz C.,Mehdi B.,Kiesel J.,Schulz K.,&Herrnegger M..(2020).A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors-a case study for Kenya and Uganda.Hydrology and Earth System Sciences,24(9).
MLA	Schürz C.,et al."A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors-a case study for Kenya and Uganda".Hydrology and Earth System Sciences 24.9(2020).