气候变化领域集成服务门户(CCPortal): Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool

CCPortal

DOI	10.5194/hess-28-139-2024
	Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
	Schmidt, Lena Katharina; Francke, Till; Grosse, Peter Martin; Bronstert, Axel
发表日期	2024
ISSN	1027-5606
EISSN	1607-7938
起始页码	28
结束页码	1
卷号	28 期号:1
英文摘要	Future changes in suspended sediment export from deglaciating high-alpine catchments affect downstream hydropower reservoirs, flood hazard, ecosystems and water quality. Yet, quantitative projections of future sediment export have so far been hindered by the lack of process-based models that can take into account all relevant processes within the complex systems determining sediment dynamics at the catchment scale. As a promising alternative, machine-learning (ML) approaches have recently been successfully applied to modeling suspended sediment yields (SSYs).This study is the first, to our knowledge, exploring a machine-learning approach to derive sediment export projections until the year 2100. We employ quantile regression forest (QRF), which proved to be a powerful method to model past SSYs in previous studies, for two nested glaciated high-alpine catchments in the otztal, Austria, above gauge Vent (98.1 km 2 ) and gauge Vernagt (11.4 km 2 ). As predictors, we use temperature and precipitation projections (EURO-CORDEX) and discharge projections (AMUNDSEN physically based hydroclimatological and snow model) for the two gauges. We address uncertainties associated with the known limitation of QRF that underestimates can be expected if values in the projection period exceed the range represented in the training data (out-of-observation-range days, OOOR). For this, we assess the frequency and extent of these exceedances and the sensitivity of the resulting mean annual suspended sediment concentration (SSC) estimates. We examine the resulting SSY projections for trends, the estimated timing of peak sediment and changes in the seasonal distribution.Our results show that the uncertainties associated with the OOOR data points are small before 2070 (max. 3 % change in estimated mean annual SSC). Results after 2070 have to be treated more cautiously as OOOR data points occur more frequently, and glaciers are projected to have (nearly) vanished by then in some projections, which likely substantially alters sediment dynamics in the area. The resulting projections suggest decreasing sediment export at both gauges in the coming decades, regardless of the emission scenario, which implies that peak sediment has already passed or is underway. This is linked to substantial decreases in discharge volumes, especially during the glacier melt phase in late summer, as a result of increasing temperatures and thus shrinking glaciers. Nevertheless, high(er) annual yields can occur in response to heavy summer precipitation, and both developments would need to be considered in managing sediments, as well as e.g., flood hazard. While we chose the predictors to act as proxies for sediment-relevant processes, future studies are encouraged to try and include geomorphological changes more explicitly, e.g., changes in connectivity, landsliding, rockfalls or vegetation colonization, as these could improve the reliability of the projections.
语种	英语
WOS研究方向	Geology ; Water Resources
WOS类目	Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:001168871300001
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/306566
作者单位	University of Potsdam
推荐引用方式 GB/T 7714	Schmidt, Lena Katharina,Francke, Till,Grosse, Peter Martin,et al. Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool[J],2024,28(1).
APA	Schmidt, Lena Katharina,Francke, Till,Grosse, Peter Martin,&Bronstert, Axel.(2024).Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool.HYDROLOGY AND EARTH SYSTEM SCIENCES,28(1).
MLA	Schmidt, Lena Katharina,et al."Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool".HYDROLOGY AND EARTH SYSTEM SCIENCES 28.1(2024).