Disentangling climate change & land use change effects on river flows: A probabilistic approach

水流 气候变化 土地利用、土地利用的变化和林业 环境科学 流域 概率逻辑 降水 概率密度函数 土地利用 水文学(农业) 自然地理学 地理 气象学 数学 统计 地质学 生态学 海洋学 生物 岩土工程 地图学
作者
Nicholas Wray,Duncan Bowie,Ian Pattison,Athanasios Angeloudis,Lindsay Beevers
出处
期刊:Journal of Hydrology [Elsevier BV]
卷期号:639: 131665-131665 被引量:4
标识
DOI:10.1016/j.jhydrol.2024.131665
摘要

Determining the respective attribution proportions of climate change and land use change to streamflow variations in river systems is of increasing interest to researchers and practitioners tasked with managing river basins. This paper proposes an extension to established techniques of attributing the relative proportions of climate change (CC) and land use change (LUC) drivers to streamflow change by instead considering these proportions as distributed through a probability density function (pdf), rather than as a point value. The novel method is demonstrated for the River Tweed in the UK. Results are determined by the flow, temperature and precipitation data, and upon the algorithms used to identify change points in these vectors. The ratio of the LUC and CC attribution proportions (Land Use and Climate Change Attribution Proportions, LCAP) is more appropriately expressed as a vector of values, each associated with its own probability value within a probability density function. The paper demonstrates that the LCAP ratio pdf can vary considerably over time and that it is possible to track physical changes in the catchment in the evolution of the probability density function. Results show that the land-use change/climate change attribution proportion (LCAP) ratio varies over time and can be expressed as probabilistic estimate. It can be concluded, with a high degree of confidence, that for the Tweed catchment the LUC is a significant driver of streamflow change. Hence this finding may have implications for future catchment flood management utilising nature based solutions (NbS) to reverse landscape degradation and mitigate effects of climate change, provided that the economic and social costs are outweighed by the benefits.
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