Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters

• Published in: Hydrology and earth system sciences Vol. 26; no. 5; pp. 1295 - 1318
• Main Authors: Bouaziz, Laurène J. E, Aalbers, Emma E, Weerts, Albrecht H, Hegnauer, Mark, Buiteveld, Hendrik, Lammersen, Rita, Stam, Jasper, Sprokkereef, Eric, Savenije, Hubert H. G, Hrachowitz, Markus
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 09.03.2022; Copernicus Publications
• Subjects: Adaptation; Analysis; Anthropogenic factors; Catchment area; Catchment scale; Climate and land use; Climate and vegetation; Climate change; Climatic conditions; Climatic data; Dynamic models; Ecosystems; Environmental aspects; Environmental conditions; Environmental testing; Evaporation; Global warming; Groundwater; Groundwater storage; Human influences; Hydrologic models; Hydrologic observations; Hydrologic processes; Hydrology; Hypotheses; Land use; Modelling; Parameter sensitivity; Parameters; Precipitation; Predictions; Properties; Root zone; Seasonal variation; Seasonal variations; Seasonality; Sensitivity; Sensitivity analysis; Storage capacity; Storage conditions; Stream discharge; Stream flow; Summer; Terrestrial environments; Vegetation; Water balance; Water balance (Hydrology); Belgium; Europe
• ISSN: 1607-7938; 1027-5606; 1607-7938
• DOI: 10.5194/hess-26-1295-2022

Future hydrological behavior in a changing world is typically predicted based on models that are calibrated on past observations, disregarding that hydrological systems and, therefore, model parameters may change as well. In reality, hydrological systems experience almost continuous change over a wide spectrum of temporal and spatial scales. In particular, there is growing evidence that vegetation adapts to changing climatic conditions by adjusting its root zone storage capacity, which is the key parameter of any terrestrial hydrological system. In addition, other species may become dominant, both under natural and anthropogenic influence. In this study, we test the sensitivity of hydrological model predictions to changes in vegetation parameters that reflect ecosystem adaptation to climate and potential land use changes. We propose a top-down approach, which directly uses projected climate data to estimate how vegetation adapts its root zone storage capacity at the catchment scale in response to changes in the magnitude and seasonality of hydro-climatic variables. Additionally, long-term water balance characteristics of different dominant ecosystems are used to predict the hydrological behavior of potential future land use change in a space-for-time exchange. We hypothesize that changes in the predicted hydrological response as a result of 2 K global warming are more pronounced when explicitly considering changes in the subsurface system properties induced by vegetation adaptation to changing environmental conditions. We test our hypothesis in the Meuse basin in four scenarios designed to predict the hydrological response to 2 K global warming in comparison to current-day conditions, using a process-based hydrological model with (a) a stationary system, i.e., no assumed changes in the root zone storage capacity of vegetation and historical land use, (b) an adapted root zone storage capacity in response to a changing climate but with historical land use and (c, d) an adapted root zone storage capacity considering two hypothetical changes in land use. We found that the larger root zone storage capacities (+34 %) in response to a more pronounced climatic seasonality with warmer summers under 2 K global warming result in strong seasonal changes in the hydrological response. More specifically, streamflow and groundwater storage are up to -15 % and -10 % lower in autumn, respectively, due to an up to +14 % higher summer evaporation in the non-stationary scenarios compared to the stationary benchmark scenario. By integrating a time-dynamic representation of changing vegetation properties in hydrological models, we make a potential step towards more reliable hydrological predictions under change.