The rainfall-runoff relationship is often simplistically represented through “elasticity”, defined most frequently as the proportional change expected in average streamflow associated with a 1% change in precipitation over a given time period. Elasticity is typically estimated from the average annual streamflow, but may differ along the flow duration curve, indicating, for instance, that precipitation change has less of an effect on low flows as compared to high flows when particular catchment characteristics are present. We estimate elasticity at multiple points across the annual and seasonal streamflow distributions of 805 river gauging locations in the United States to create elasticity curves which graphically represent the responsiveness of low to high streamflow to precipitation. We show that elasticity curve type (the overall shape of the curve) corresponds closely with water storage and catchment flashiness; curve shape varies independently of the magnitude of response; and that the elasticity curves exhibit a regional pattern. We are further investigating whether elasticity curve shape and elasticity magnitude change over time. This assessment suggests that historical changes in water storage, and groundwater-surface water interaction may have led to substantial shifts in elasticity curves over time. This implies probable underestimation of future streamflow under climate change, unless relevant catchment characteristics are adequately considered 

How to cite: Anderson, B., Brunner, M., Slater, L., and Dadson, S.: Elasticity curves describe streamflow sensitivity to precipitation across the entire flow distribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6555, https://doi.org/10.5194/egusphere-egu23-6555, 2023.

The Murray-Darling Basin in south-eastern Australia is one of the world’s largest rivers, draining an area of just over 1 million square kilometres. The basin drains about one-seventh of the Australian land mass and is the 16th longest river in the world. However, being located on the driest continent on Earth, its discharge is relatively small, averaging just 767 m3/s, far smaller than the discharge from any other similarly sized river worldwide.

Despite the relative lack of water, the Murray-Darling Basin is one of the most significant agricultural areas in Australia. In order to manage the water in the basin, in 2008 the Murray-Darling Basin Authority was formed with a mandate to manage the Murray-Darling Basin in an integrated and sustainable manner. Water reform in the basin has been a world-first in terms of the scale of intervention, but it has led to numerous conflicts in terms of access to water. The ability to manage the basin adequately relies on appropriate research being carried out in order todetermine how much water is currently available, where it is currently being used, and how water availability and use are likely to change into the future.

Like much of southern Australia, the Murray-Darling Basin is already feeling the impacts of climate change, with more hotter days, fewer cold days, and a reduction in cool-season precipitation. These changes are only likely to increase over the coming decades and adaptation options to cope with less water availability are needed.

Additionally, the Murray-Darling Basin Plan which was brought into force in 2012 is due for evaluation in 2025 and review in 2026. CSIRO is carrying out research across multiple disciplines in order to assist in this evaluation and review. This presentation will summarise the management of the basin to date, review likely climate change impacts and assess potential adaptation options moving forward.

How to cite: Post, D.: Adapting to reductions in water availability under climate change in the Murray-Darling Basin, Australia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3871, https://doi.org/10.5194/egusphere-egu23-3871, 2023.

Earth satellites have observed continuous increasing vegetation growth during the past four decades, a phenomenon called Earth greening. Nearly all Earth System Models (ESMs) participated in Coupled Model Intercomparison Project (CMIP) for Intergovernmental Panel on Climate Change (IPCC) project a continuous greening of the planet during the 21^st century. To investigate the hydrological feedback from projected Earth greening, we prescribed the increase in leaf area index (LAI) in the 21^st century as projected by CMIP5 ESMs into a state-of-the-art ESM (IPSLCM), and simulated equilibrium climates for current CO₂ and LAI, an increase of CO₂ alone, an increase of LAI alone, and increases of both CO₂ and LAI, respectively. We find that the greening simultaneously intensifies evapotranspiration and precipitation over land. In terms of soil moisture content, the spatial difference between the responses of evapotranspiration and precipitation causes a hydrological response of the "dry gets drier, wet gets wetter" (DDWW) paradigm. Increasing LAI significantly decreases soil moisture content over dry regions, including Western North America, Southern South America, East Siberia, Central Asia, South Asia, Northern China, Sahel, Southern Africa and Australia. Over wet regions particularly Amazon and Congo rainforests, the greening-induced increase of terrestrial evapotranspiration favors more convective precipitation, so that the new equilibrium does not decrease soil moisture content. The DDWW paradigm in terms of P-ET response does not hold over wet areas. To mitigate climate with forestry, policymakers should prevent degradation of existing forests, support afforestation over wet regions, and avoid planting trees in dry regions.

How to cite: Wu, J., Wang, D., Li, L. Z. X., and Zeng, Z.: Hydrological feedback from projected Earth greening in the 21st century, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3103, https://doi.org/10.5194/egusphere-egu23-3103, 2023.

Global bias-adjusted daily climate projections have been recently set up as part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) phase 3 based on CMIP6 projections (Lange et Büchner., 2021). This dataset is aimed at being used as input to global hydrological models, and their coarse resolution however prevents them to be used for catchment-scale and reach-scale applications.

This work proposes to downscale these global climate projections through multivariate analog downscaling method and to derive catchment-scale streamflow time series through a fully-distributed hydrological model. The final objective is to produce future daily streamflow series over a high-resolution hydrographic network of 6 European catchment case studies for the DRYvER project (Datry et al., 2021). The method is applied on precipitation, temperature, and potential evapotranspiration serving as input to the distributed JAMS-J2K model (Krause et al., 2006).

This setup led to the creation of daily hydrological projections at high spatial resolution over the 1985-2100 period. These experiments are conducted using one run from 5 different global climate models and 3 emission/socio-economic scenarios (SSP1-RCP2.6, SSP3-RCP7.0 and SSP5-RCP8.5) from the CMIP6 experiments. This methodology allows to grasp the range of future changes in daily streamflow over the entire catchments. The comparison between the historical period (1985-2014) and future periods is used to describe possible changes over seasonal discharge and low flow characteristics.

This approach provides hydrological projections with a spatial resolution sufficiently high to apply flow intermittence detection, thus allowing to study plausible futures for European intermittent rivers in terms of hydrology, biodiversity, ecosystem functioning and services, and adaptive management. Future steps will refine such futures using an innovative downscaling approach combining global and catchment-scale transient projections to better grasp the joint influence of climate change and climate variability on reach-scale intermittence.

Datry et al. (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes. https://doi.org/10.3897/rio.7.e77750.

Krause et al. (2006) Multiscale investigations in a mesoscale catchment: hydrological modelling in the Gera catchment. Advances in Geosciences. doi:10.5194/adgeo-9-53-2006.

Lange et Büchner (2021) ISIMIP3b bias-adjusted atmospheric climate input data (v1.1), ISIMIP Repository. doi:10.48364/ISIMIP.842396.1.

Clemins et al. (2019) An analog approach for weather estimation using climate projections and reanalysis data. Journal of Applied Meteorology and Climatology. doi:10.1175/JAMC-D-18-0255.1

How to cite: Devers, A., Mimeau, L., Künne, A., Vidal, J.-P., Lauvernet, C., Branger, F., and Kralisch, S.: Reach-scale streamflow projections in intermittent riversthrough a multivariate dowscaling method and a distributed hydrologcal model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12779, https://doi.org/10.5194/egusphere-egu23-12779, 2023.

The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) proposes new shared pathways (SSPs) that incorporate socioeconomic development with more comprehensive and scientific experimental designs; however, few studies have been performed on the projection of future multibasin hydrological changes in China based on CMIP6 models. In this paper, we use the Equidistant Cumulative Distribution Function method (EDCDFm) to perform downscaling and bias correction in daily precipitation, daily maximum temperature, and daily minimum temperature for six CMIP6 models based on the historical gridded data from the high-resolution China Meteorological Forcing Dataset (CMFD). We use the bias-corrected precipitation, temperature, and daily mean wind speed to drive the variable infiltration capacity (VIC) hydrological model, and study the changes in multiyear average annual precipitation, annual evapotranspiration and total annual runoff depth relative to the historical baseline period (1985–2014) for the Chinese mainland, basins and grid scales in the 21st century future under the SSP2-4.5 and SSP5-8.5 scenarios. The study shows that the VIC model accurately simulates runoff in major Chinese basins; the model data accuracy improves substantially after downscaling bias correction; and the future multimodel-mean multiyear average annual precipitation, annual evapotranspiration, and total annual runoff depth for the Chinese mainland and each basin increase relative to the historical period in near future (2020–2049) and far future (2070–2099) under the SSP2-4.5 and SSP5-8.5 scenarios. The new CMIP6-based results of this paper can provide a strong reference for extreme event prevention, water resource utilization and management in China in the 21st century.

How to cite: Zhou, J., Lu, H., Yang, K., Jiang, R., Yang, Y., Wang, W., and Zhang, X.: Projection of China’s future runoff based on the CMIP6 mid-high warming scenarios, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1851, https://doi.org/10.5194/egusphere-egu23-1851, 2023.

Objective: Estimate the error introduced by the misrepresentation of soil freezing characteristic curves (SFCCs) in hydrological models and propose an improved method for modelling freezing soils.

Key Findings

• Most SFCCs used in numerical modelling studies are chosen based on convergence behaviour as opposed to physical soil properties.
• The choice of SFCC affects model outcomes, including governing the ice content of soils, which in turn controls the permeability and the discharge from a hydrogeologic model.

Abstract

More than half of the global terrestrial surface is subject to freezing processes, either as seasonally frozen soils or as permafrost. Soil freezing processes are represented by the soil freezing characteristic curve (SFCC) that relates soil temperature to its unfrozen water content. Unfortunately, SFCCs are frequently misrepresented in models, and often chosen based on ease of model convergence behavior as opposed to physical soil properties. With climate change and increased frequency of midwinter melt, SFCCs are becoming increasingly important in accurately predicting the hydrological response of catchments.

Two synthetic hillslopes, one for a permafrost system and one for a permafrost-free system affected by seasonal freezing, are simulated using SUTRA-ice and a selection of widely accepted SFCCs. SFCCs are drawn from literature values as well as a repository of collected SFCC data: "A Repository of 100+ Years of Measured Soil Freezing Characteristic Curves". The resulting discharge is compared for each simulation, showing that the choice of SFCC is important in controlling streamflow generation in these landscapes, and the choice of SFCC may be a previously overlooked controlling process in the hydrological behaviour of catchments with freezing soils. Further work upscaling these results to catchment and larger scales is needed.

How to cite: Devoie, É., McKenzie, J., Lamontagne-Hallé, P., and Woo, A.: Understanding the hydrological response of groundwater discharge from freezing soils to a warming climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7424, https://doi.org/10.5194/egusphere-egu23-7424, 2023.

Global climate models (GCMs) provide potential climate scenarios and are used to understand effects of future climate change. A large number of GCMs is included in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), and these models simulated both the historical and future climate. For the future climate, multiple scenarios are simulated based on different shared socioeconomic pathways and representative concentration pathways. The daily output from these models can be used to force hydrological models, to understand how the hydrological system responds to a changing climate. For this study we focus on the use of the available state-of-the-art ensemble of GCMs to obtain a first climate change signal for the changes in mean and extreme flows of the river Rhine.

However, as the CMIP6 models are all global models, they are known to contain biases at regional scales. Yet, by directly using the GCMs we can obtain the full projection space of the CMIP6 models. Output from the CMIP6 models is often bias-corrected to ensure accurate values for regional applications. For an application in the Netherlands, we investigated the role of bias correction on the hydrological response of the Rhine and Meuse river basins, as these basins play a vital role for the Dutch water safety and security. The hydrological model wflow_sbm is used to simulate both basins and is forced with the CMIP6 data for both the historical and future climate (following the SSP5-8.5 pathway). The results from these simulations highlight the role of bias-corrected forcing data on the simulated discharge characteristics for both the Rhine and Meuse river basins. In the near future the work will be extended with RCM simulations.

How to cite: Buitink, J. and Sperna Weiland, F.: Hydrological response to bias-corrected global climate projections data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15133, https://doi.org/10.5194/egusphere-egu23-15133, 2023.

To predict and manage the evolution of water resources is a high stake for society in the context of climate change and largely managed rivers. A first step in this endeavour is to be able to determine in the past records which of both processes has dominated changes.
We propose an innovative way to detect and quantify the changes in river discharge due to climate processes or to non climatic factors over the past century for European catchments. The Land surface model (LSM) ORCHIDEE forced with a century long climate data set is used to simulate the complex hydrological response of natural catchments to change in climatic variables. The Budyko framework is applied with a time-moving window to decompose the direct discharge response to changes in precipitation P and potential evapotranspiration PET and the indirect response due to climate induced changes in the evaporation efficiency of the watersheds. We then apply the same methodology to discharge observations from gauging stations over Europe. It enables to highlight the areas where the model misrepresents (or omits) important catchment processes and where non-natural changing factors impacting the watershed’s apparent evaporation efficiency significantly contribute to trends in the observed discharge over the century. Results over Europe show that long-term changes and variability in discharge due to climate processes are dominated by changes in P. The second main climatic driver is PET except over the Mediterranean area where water is more limiting and where intra-annual changes in the distribution of P outweigh the effect of PET trends on discharge changes. Over most catchments however and mostly in southern Spain, the changes due to factors not accounted for in the "natural" system dominate over the  century. When the focus is on decadal periods, the effect of non-climatic factors is still significant but small compare to the high effect of climate variability. Attempts to attribute non-climatic changes in the catchments evaporation efficiencies are presented. For instance, good correlations are found  between changes in the evaporation efficiency of Spain catchment with the evolution of water stored in dams showing that it is a reliable indicator of the effect of human activities on the hydrological changes of watersheds in that area. Adding the effect of land-use and land-cover changes in the current implementation of the LSM has no significant effects on the hydrological behaviour of the watersheds at the studied scale of this study. Many processes especially related to human factors impact the watershed’s apparent evaporation efficiency, often with complex and inter-correlated feedback effects and further studies are needed to better attribute the non-climatic trends detected. Further developments in LSM would allow to better include these factors. 

How to cite: Collignan, J., Polcher, J., Quintana Seguí, P., and Bastin, S.: Method to identify and quantify the effect of climatic and non-climatic drivers on river discharge in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6687, https://doi.org/10.5194/egusphere-egu23-6687, 2023.

Understanding hydrological and biogeochemical ecosystem process variability in response to a changing climate is important to improve land surface models and assess current and future states of ecosystem functioning. However, the representation of spatial heterogeneity of ecosystem processes in state-of-the-art land-surface models has not been evaluated thoroughly until today. Here we compare gross primary production (GPP) and evapotranspiration (ET) simulated by the Community Land Model version 5 (CLM5) for the period 1995-2018 over the Euro-CORDEX domain with in-situ data from eddy-covariance sites as well as remote sensing and reanalysis data. Additionally, we conducted a parameter sensitivity analysis to identify the impact of uncertainty coming from ecosystem parameters (in particular default parameters for given plant functional types) for selected sites in Europe. 

Our results show that GPP and ET variation across hydroclimates show in general a good agreement between CLM5 and remote sensing and reanalysis products. However, both GPP and ET simulated by CLM5 show large differences with measured in-situ data, depending on the ecosystem type. Further, we identify sensitive parameters that will be adjusted to improve ecosystem representation in CLM5 in a future study. This work is important to improve land surface models and parameterization of plant functional types to understand and improve predictions of ecosystem functioning.

How to cite: Poppe Terán, C., S. Naz, B., Hendricks-Franssen, H.-J., and Vereecken, H.: Uncertainty in representation of ecosystem processes in Europe by the Community Land Model v5, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13465, https://doi.org/10.5194/egusphere-egu23-13465, 2023.

In light of the complex interactions of multiple biotic and abiotic processes acting at different spatio-temporal scales and the high spatial variability in their biophysical features, our ability to describe catchment dynamics is still limited. Such a limitation stems, on one side, from the mismatch of scales between key small-scale processes and their current parameterization and the large scales of many modeling applications, and, on the other, from the challenge of considering the spatial configurations in an explicit manner. As a motivating example, we will discuss here the issue of representing the effect of biologically-induced soil structure in the parameterization of soil hydraulic properties (SHPs) for large scale applications. Currently available parameterizations based on soil pedotransfer functions (PTFs) do not account for the effects of soil structure, thus limiting their applicability in vegetated areas in which macropores are expected to significantly increase soil saturated hydraulic conductivity. Considering the strong links between vegetation and soil structure, we propose a systematic approach for incorporating structural effects on PTF-derived SHPs. We will show that, under certain soil and climatic conditions, small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must explicitly consider the spatial variability of soil and vegetation attributes. Lastly, opportunities in the representation of multiple small‐scale ecohydrological processes for regional and global applications will be discussed. Progress on this front is key for establishing more complete causal links between landscape attributes and heterogeneities in physical properties, thus providing a mechanistic strategy for model parameterization and process description across scales and a path forward for more reliable large-scale modeling under future scenarios.

How to cite: Bonetti, S. and Or, D.: On the representation of small-scale soil biophysical features for large-scale applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4099, https://doi.org/10.5194/egusphere-egu23-4099, 2023.

With persistent global warming, more precipitation will land on the earth's surface as rainfall instead of snowfall. Here, based on observations from hundreds of catchments, we proposed a framework (the second-order Budyko framework) to investigate hydro-climatic relationships between annual streamflow and snowfall fraction. Results show that in addition to the mean annual streamflow, the inter-annual streamflow variability will also decrease with lower snowfall fraction in the context of warming. The positive relationship between streamflow variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years. To our knowledge, it is the first attempt to detect the role of snowfall on the streamflow variability. This study provides new way and understandings of the second-order hydro-climatic effects, and these findings will facilitate decisions for water resource management in a changing climate.

How to cite: Liu, Z., Wang, T., Han, J., Yang, W., and Yang, H.: Decreased inter-annual streamflow variability are found in snow-affected catchments by using the second-order Budyko framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2248, https://doi.org/10.5194/egusphere-egu23-2248, 2023.

It is almost axiomatic that catchment response to precipitation is nonlinear and nonstationary, implying that each drop of rain may affect streamflow differently, depending on how it fits into the sequence of past and future precipitation.  But do most catchments exhibit similar patterns of nonlinearity and nonstationarity, or not?  If not, which ones are more nonstationary (i.e., more sensitive to antecedent precipitation)?  Which ones are more nonlinear?  And why? 

Understanding catchments’ nonlinear and nonstationary behavior requires widely applicable tools for characterizing and quantifying that behavior in the first place. Here show how catchment nonstationarity and nonlinearity can be quantified using Ensemble Rainfall-Runoff Analysis (ERRA), a data-driven, model-independent method for quantifying rainfall-runoff relationships across a spectrum of time lags.  ERRA is superficially similar to classical unit hydrograph methods, but whereas unit hydrographs assume linearity (runoff response is proportional to precipitation) and stationarity (runoff response to a given unit of rainfall is identical, regardless of when it falls), ERRA can explicitly quantify the nonlinearity and nonstationarity in rainfall-runoff relationships, directly from data.  This approach combines least-squares deconvolution (to un-scramble each input's temporally overlapping effects) with demixing techniques (to separate the effects of individual inputs, or inputs occurring under different antecedent conditions) and broken-stick regression (to quantify nonlinear dependencies). 

Not only can this approach quantify the impulse response of streamflow to precipitation, it can also quantify how this impulse response changes with rainfall rates (nonlinearity), how it varies with catchment wetness (nonstationarity), and how it differs for rain falling on different parts of the landscape (heterogeneity), even if these signals are all overprinted on one another at the catchment outlet.  Results from this approach may be informative for catchment characterization and runoff forecasting; they may also lead to a better understanding of short-term storage dynamics and landscape-scale connectivity.  Applications of these methods will be illustrated using large multi-catchment data sets from Switzerland and North America.

How to cite: Kirchner, J.: Signatures of catchment nonlinearity and nonstationarity, quantified using Ensemble Rainfall-Runoff Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9794, https://doi.org/10.5194/egusphere-egu23-9794, 2023.

The importance of evapotranspiration (ET) for hydrology, agriculture, and meteorology has long been recognized. In fact, most of our current understanding of the physics of evaporation originated in early experiments during the past two centuries. Potential ET (PET) is a concept extendedly used for predicting ET and defined as the evaporation in case of an unlimited amount of water available. Different potential evapotranspiration (PET) formulas were developed for different purposes and are currently applied far beyond their origin. Accordingly, these formulas also result in different PET estimates due to their different assumptions and inputs requirements; hence, the regularities of the formulas should be re-assessed when applied for new scales or environmental conditions.

In the current study, we experimented with three simplified PET models over the globe: Jensen-Haise, Hargreaves, and Priestly-Taylor. The World-Wide HYPE (WW-HYPE) global catchment hydrological model is applied as a virtual laboratory where we keep all other hydrological predictors constant except for PET to examine its influence on the model performance in term of streamflow and ET. 15 years of observations from 5,338 streamflow gauges and global evapotranspiration from Earth-observations (MOD16) were used as independent datasets. We tested model performance in a multi-process approach to select the best formula for catchments covering the global landmass. Catchment physiography and a classification in the Budyko space were used to explain differences in the model results.

From comparing the results with land-cover, climate classification, water-energy limitations, we found that climate is the main driver behind the spatial patterns in model performance. We found a strong connection between the five main Köppen regions and the PET formulas, further supported by landcover analysis. The selection of a PET formula seems to be more critical in tropical regions close to the equator, where the differences in performance are above 50%. This is also where PET is highest. Hargreaves was the best PET formula in 50% of the catchments, most of them located in the Amazonas, central Europe, and Oceania. Jensen-Haise was better for catchments in northern latitudes (36%). Finally, Priestly-Taylor was the best formula for India and latitudes above 65⁰ N. Hence, the PET formulas differed in their capacity to provide useful input to the water balance modelling, with complex formulas only giving improved predictions in temperate and polar regions; however, for the rest of the globe simpler formulas were better. We thus recommend applying different PET formulas based on climatic regions world-wide.

References:

Arheimer et al., 2020: Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, HESS 24, 535–559, https://doi.org/10.5194/hess-24-535-2020   

Pimentel et al., 2023: Which Evapotranspiration Formula to Use in Hydrological Modelling World-wide? WRR (in review)

How to cite: Arheimer, B., Pimentel, R., Crochemore, L., Andersson, J., Pechlevanidis, I., and Gustafsson, D.: Re-assessing PET regularities at the global scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16055, https://doi.org/10.5194/egusphere-egu23-16055, 2023.

Identifying hydrological regularities, such as patterns and laws that explain the observed variability in catchment response, is an important objective of catchment hydrology. These insights could contribute regional knowledge that can be exploited in catchment classification studies and improve model realism and parsimony. But how to infer such regularities, and to what extent are they generalizable, in view of the evidence of uniqueness of place? In this presentation, we propose the development of a regional scale perceptual model as a framework to stimulate the search of hydrological regularities and to represent them visually. Our approach is intended for nested catchments, a scale that we consider is sufficiently large to provide an interesting contrast in hydrological responses, but sufficiently small to encompass local dominant process that may be different elsewhere. Our perceptual model development approach is demonstrated in the 27,000 km² Moselle catchment, using streamflow data at 26 nested subcatchments, and commonly available data of landscape properties, including topography, vegetation, geology and soil. The identified signatures of streamflow spatial variability highlighted the role of precipitation, geology and topography, which affected, respectively the average flows, base runoff and lag time. Soil and vegetation, on the other hand, were not found to be a dominant cause of hydrograph variability, which might appear surprising, considering that soil properties are one of the key ingredients of many distributed models. The framework undertaken in this study may be useful to develop perceptual models in other basins at regional scale, and to map and regularize the variety of dominant hydrological processes.

How to cite: Fenicia, F. and McDonnell, J. J.: Identifying hydrological regularities via perceptual models at the regional scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11988, https://doi.org/10.5194/egusphere-egu23-11988, 2023.

Hydrological processes leading to flow in river channels are extremely complex, which is why hydrologists have not yet found any fundamental law to explain river flow dynamics at basin-scale. Hydrological models generally keep a set of free parameters that need to be calibrated using observed discharge time series data. The underlying assumption is that each catchment is unique and that each model parameter represents certain catchment characteristics. Thus, prediction in ungauged basins is a challenge. In this study, it is argued that we should focus on developing calibration-free hydrological models. In other words, we hypothesize that hydrological response is primarily determined by climatic inputs. We compared the dynamic Budyko (DB) rainfall-runoff model with the HBV model considering a global dataset. The two models showed very similar performance across geographical regions, supporting our hypothesis. We conclude that more efforts should be made to develop rainfall-runoff models that exploit climatic information for explaining streamflow variation.

How to cite: Biswal, B. and Istalkar, P.: Climatic origin of hydrological response, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16897, https://doi.org/10.5194/egusphere-egu23-16897, 2023.

Drought-induced vegetation responses are often hypothesized as one of the key drivers of hydrological changes under multiyear droughts. However, until now, this hypothesis has not been systematically tested on areas that experienced significant drought-induced reductions in streamflow generation. Our results do not support this hypothesis and suggest that vegetation changes are unlikely to be the main driver of observed hydrological changes.

We employed multiple remotely sensed vegetation indices (AVHRR NDVI & fPAR, MODIS NDVI & EVI, and Ku-VOD from multiple microwave satellite sensors) and rainfall-runoff shift indicators to investigate vegetation responses and their influences on streamflow generation during the Millennium Drought (from 1997 to 2009) in 156 catchments in Victoria, Australia. Many of these catchments experienced significant shifts in their rainfall-runoff relationship by severely reducing streamflow generation during the Millennium Drought. However, we show that vegetation indices are statistically similar or higher in many catchments during the Millennium Drought compared to pre-drought, consistent with published literature. Moreover, the spatial pattern of increase in vegetation indices does not match the spatial distribution of hydrological shifts, measured by significant streamflow reductions for a given rainfall. We argue that vegetation response is unlikely to be a primary driver of the observed hydrological shifts, although they are regarded as crucial in determining hydrological behaviour more generally. This finding has important implications for better understanding and modelling hydrological responses under future climate changes.

How to cite: Gardiya Weligamage, H., Fowler, K., Saft, M., Ryu, D., Peterson, T., and Peel, M.: Role of vegetation responses in hydrological shifts under multiyear droughts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10029, https://doi.org/10.5194/egusphere-egu23-10029, 2023.

We studied changes in the recession behaviour of catchments that experienced multi-annual drought conditions to explore their relationship with previously observed drought-induced shifts in catchments’ hydrological response (as measured by annual rainfall-runoff relationships). We found that recession behaviour can change significantly during persistent drought, highlighting the role of subsurface storage dynamics and catchment conductivity in determining catchments’ hydrological response to prolonged dry periods.

Analysis of streamflow recessions is commonly used to characterise catchment behaviour, and to explore the role that catchment storage plays in streamflow production. Recession techniques characterise average catchment behaviour over sufficiently long periods of recorded data, making them generally unsuitable for analysis of nonstationary hydrological conditions. Nevertheless, in the context of long-term drought, where nonstationarity arises over decadal periods, analysis of changes in catchment recession behaviour over time is possible. For this study, we consider nonstationarities in the catchment-level annual rainfall-runoff relationships induced by prolonged drought. These have been observed during multi-annual droughts worldwide and often persist long after the end of the dry spell. In this context, recession analysis is a useful tool to study the effects of persistent drought on catchment processes.

We applied recession analysis methods to assess changes in average recession behaviour of catchments affected by multi-annual drought in Sout-Eastern Australia. We compare recession behaviour before the drought to a 10-year period straddling the end of the drought. We focussed on how significant changes in recession behaviour over time correlate to drought-induced shifts in annual rainfall-runoff relationships. We apply two distinct methods, drawn from the vast methodological literature on recession analysis. These were chosen specifically for their different data requirements (hourly or daily) and approaches to recession analysis (one based on a master recession curve and the other based on recession plots).

Despite the differences, results from both methods are consistent. We found that recession behaviour changed significantly in the majority of the catchments studied, with recessions becoming faster late in the drought compared to the pre-drought period. These changes, in particular, affected catchments that were shown to exhibit significant shifts in rainfall-runoff relationship during the extended drought. Conversely, in the catchments whose rainfall-runoff relationship had remained stable, the changes in recession behaviour are much smaller and largely limited to the low-flow portion of the recession curve. This suggests that the widespread increase in recession rates observed in shifted catchments is only in small proportion attributable to increased evaporative demand (which is comparable between the two sets of catchments) and is instead likely caused by a combination of decreased connectivity between catchment surface water and subsurface storage and increased transmission losses through the streambed.

How to cite: Trotter, L., Saft, M., Peel, M., and Fowler, K.: Recession constants are not constant: the impacts of multi-annual drought on recession behaviour and catchment storage., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3753, https://doi.org/10.5194/egusphere-egu23-3753, 2023.

In order to investigate how annual precipitation amount (P) and potential evapotranspiration (ET_p) influence the partitioning of water fluxes into flow, evaporation and transpiration, we employed the physically-based spatially explicit 3D model HydroGeoSphere in a virtual catchment running 100 scenarios with different combinations of catchment and climate properties. In addition, we looked at the changes in the transit times of the different fluxes.

Unsurprisingly, the fraction of flow increases with larger P and decreases with stronger ET_p. Both transpiration and evaporation fractions generally decrease with larger P and increase with stronger ET_p. However, the increase in the evaporation fraction ends for dryness indices (ET_p/P) larger than 1 while the increase in the transpiration fraction continues. With regard to the transit times we found that on the one hand transpiration becomes younger in catchments with more P while it becomes older when ET_p increases (vegetation has to resort to all potential water sources, also the ones deeper down and older). Evaporation and flow on the other hand become younger with larger P but become older with weaker ET_p (basically, the decrease in transpiration leaves water longer in the system which is then available for older evaporation and streamflow).

This also means that an acceleration of the hydrologic cycle can be caused both by an increase or decrease in the dryness index – depending on whether this change is caused by a change in P or ET_p. This can have significant impacts for predicting catchment response and solute transport in light of future climate variability.

How to cite: Heidbüchel, I., Yang, J., and Fleckenstein, J. H.: The impact of precipitation and potential evapotranspiration on water flux partitioning and transit times at the catchment scale – a modeling study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9827, https://doi.org/10.5194/egusphere-egu23-9827, 2023.