Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study

Abstract

Abstract. Climate change and land cover changes are influencing the hydrological regime of our rivers. The intensification of the hydrological cycle caused by climate change is projected to cause more flooding in winters and an increased urbanization could amplify these effects by a quicker runoff on paved surfaces. The relative importance of both drivers, however, is still uncertain and interaction effects between both drivers are not yet well understood.In order to better understand the hydrological impact of climate variability and land cover changes, including their interaction 10 effects, we fitted a statistical model to historical data over 3 decades for 29 catchments in Flanders, covering various catchment characteristics. It was found that the catchment characteristics explain up to 18% of changes in river peak flows, climate variability 6% and land cover changes 8%. Interaction terms explain up to 32%. An increase in urban area of +1% might cause increases in river peak flows up to +5%. Introduction 15Our environment has undergone unprecedented changes over the past decades, and it is very likely that further changes will take place in the coming decades. With respect to the climate system, increases in frequency, intensity and/or amount of heavy precipitation are globally reported for the majority of the land areas (IPCC, 2014); for Flanders (Belgium) in particular, extreme precipitation might increase with +50% in winter and +100% in summer by the late 21 st century (Tabari et al., 2015). With respect to the built environment, the world continues to urbanize, with nowadays 55% of the world's population living in urban 20areas. This is in shear contrast with 1950, where only 30% of the world's population was urban (United Nations, 2018). For Flanders, this is translated into a 300% increase in built-up area over the past four decades (Poelmans, 2010;Ruimte Vlaanderen, 2017).Changes in climate and urbanization both cause changes in the hydrological regime of catchments in general and changes in flood frequencies in particular. Here, we aim to attribute observed changes in river peak flows to drivers related to the climate 25 and to a changed land use/land cover. Previous attribution studies related to trends in flood hazards faced several challenges.These were, among others, summarized by Merz et al. (2012). The attribution process typically involves two steps: detection of change and attribution of that change to its various drivers. In the first step, the detection of change is often challenging: the signal of flood time series (or river peak flows in general) typically shows a high natural variability, with a low signal-to-noise 2 ratio. Moreover, floods form part the larger hydrological system and, as such, show a quite complex behavior. With respect to the attribution issue in the second step: in a complex hydrological system, different drivers act in parallel, with interactions between them. The integral response of the system to all these drivers and interactions governs the changed hydrological ...

Statistical Attribution of the Influence of Urban and Tree Cover Change on Streamflow: A Comparison of Large Sample Statistical Approaches

“…Panel regression models have recently been applied in hydrological research (Blum et al., 2020; Davenport et al., 2020; De Niel & Willems, 2019; Ferreira & Ghimire, 2012; Levy et al., 2018; Müller & Levy, 2019; Yang et al., 2021). The approach allows consideration of the data across both time and space; here we quantify the average effects of individual drivers (changes in tree cover and urban area) across all sites while controlling for the influence of a wide range of confounding variables (Figure 2).…”

“…First, a single‐catchment approach involves fitting distinct regression models to often “lumped” time‐series data for individual catchments, then assessing the fit of these models and signs of their coefficients (e.g., Neri et al., 2019; Prosdocimi et al., 2015; Slater, Anderson, et al., 2021; Villarini et al., 2009). Alternatively, a combined multi‐catchment approach involves fitting panel regression models to estimate average causal effects across many sites (recent examples in hydrology include: Bassiouni et al., 2016; Blum et al., 2020; Brady et al., 2019; De Niel & Willems, 2019; Lombard & Holtschlag, 2018; Steinschneider et al., 2013; Yang et al., 2021). The deceptively simple nature of regression approaches means that they have been widely applied, however, while both single‐catchment and multi‐catchment approaches have their unique benefits, they are best suited to slightly different questions.…”