Adaptation of root zone storage capacity to climate change and its effects on future streamflow in Alpine catchments: towards non-stationary model parameters

Published: Aug. 27, 2024

Abstract. Hydrological models play a vital role in projecting future changes streamflow. Despite the strong awareness of non-stationarity hydrological system characteristics, model parameters are typically assumed to be stationary and derived through calibration on past conditions. Integrating dynamics change remains challenging due uncertainties related climate ecosystems. Nevertheless, there is increasing evidence that vegetation adjusts its root zone storage capacity – considered critical parameter prevailing hydroclimatic This adaptation moisture deficits can estimated by Memory Method. When combined with long-term water budget estimates Budyko framework, method offers promising approach estimate climate-vegetation interaction thus time-variable process-based models. Our study provides an exploratory analysis non-stationary for streamflow six catchments Austrian Alps, specifically investigating how impact modeled Using method, we derive climate-based under historical projected These then implemented our assess resultant findings indicate estimations significantly narrow ranges linked capacity. contrasts broader obtained solely calibration. Moreover, using projections from 14 models, substantial increase across all future, ranging +10 % +100 %. these alterations, performance relatively consistent when evaluating streamflow, independent calibrated or parameter. Additionally, no significant differences found modeling including climate-induced model. Variations annual mean, maximum, minimum flows remain within 5 range, slight increases monthly runoff coefficients. research shows although occur, they do not notably affect Alpine study. suggest incorporating dynamic representation may crucial humid energy-limited catchments. However, observations larger less catchments, corresponding higher variations suggests potentially importance representations characteristics arid regions underscores necessity further regions.

Language: Английский

Global patterns in vegetation accessible subsurface water storage emerge from spatially varying importance of individual drivers

Environmental Research Letters, Journal Year: 2024, Volume and Issue: 19(12), P. 124018 - 124018

Published: Oct. 17, 2024

Abstract Vegetation roots play an essential role in regulating the hydrological cycle by removing water from subsurface and releasing it to atmosphere. However, present understanding of drivers ecosystem-scale root development their spatial variability globally is limited. This study investigates varying roles climate, landscape, vegetation on magnitude zone storage capacity ( S r ) worldwide, which defined as maximum volume moisture accessible roots. To this aim, we quantified evaluated 21 possible controls for 3612 river catchments worldwide using a random forest machine learning model. Our findings reveal climate primary, but spatially varying, driver ecosystem scale with landscape characteristics playing minor role. More specifically, found mean inter-storm duration most dominant control globally, followed temperature, precipitation, topographic slope. While duration, slope exhibit consistent relation between precipitation varies spatially. Based variability, classified two different regimes: driven energy The precipitation-driven regime exhibits positive up 3 mm mathvariant="normal">d − 1 , above flattens eventually becomes negative. energy-limited strictly negative . Using model based these three variables variable slope, generated global gridded dataset closely resembles other datasets characteristics. suggests that our parsimonious approach four available estimate has potential be readily easily integrated into parameterization land surface models. may enhance accuracy predictions land–atmosphere exchange fluxes extremes providing robust representation both temporal

Language: Английский