HS2.4.2

It is common to test hydrologic models under contrasting historical periods as an indicator of likely performance under climate change. For example, a model calibrated under average conditions may be tested under increasingly dry subsets of the observational record. Any decline in performance as the testing conditions deviate further from the calibration conditions is then assumed to represent likely performance degradation under climate change scenarios with comparable rainfall decreases. Many studies have inherently applied the assumption that past rainfall variability can be used as a proxy for future climate change, but the analogy may be flawed for three main reasons:

• Due to lagged hydrologic response to meteorological shifts, catchment behaviour under long-term wetting or drying may not be fully represented over shorter wet or dry periods.
• Subsets of the past record selected based on rainfall are unlikely to reflect future temperature increases.
• Past observations do not include expected increases in carbon dioxide levels.

If any of these factors substantially impacts catchment response, subsets of the historical record with equivalent rainfall will not be accurate proxies for future climate scenarios. We tested the impact of each factor using the ecohydrologic model RHESSys. RHESSys dynamically simulates vegetation growth, subsurface flow and nutrient cycling and is thus able to capture the key processes that could drive nonstationary catchment response in the future. We found that all three future climate factors (rainfall change persistence, temperature, and carbon dioxide) altered catchment response substantially, especially for drier future scenarios. For our study catchment, persistence of dry conditions over many decades led to different subsurface water storage levels than the same rainfall experienced over shorter timeframes, leading to different streamflow. The impacts of increased temperature and carbon dioxide concentrations on vegetation further altered runoff behaviour. This means that long-term climate change effects will not necessarily emerge over short historical periods with equivalent rainfall. In our example, ignoring persistence in rainfall changes, rising temperatures, and higher carbon dioxide levels could lead us to underestimate model performance degradation in terms of Nash-Sutcliffe efficiency by as much as 0.41. Therefore, the uncertainty introduced in hydrologic models by future climate change has probably been underestimated in the current literature.

How to cite: Stephens, C., Marshall, L., Johnson, F., Lin, L., Band, L., and Ajami, H.: Can examining past variability help us understand catchment response to future climate change?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3319, https://doi.org/10.5194/egusphere-egu22-3319, 2022.

The widely-used Budyko framework synthesizes the competition between water and energy availability simply using climatological mean precipitation (P) and potential evaporation (PE). While PE within the Budyko framework is often regarded as the atmospheric evaporative demand (AED), AED can substantially differ from PE assuming ample water availability due to its responsive behavior to soil moisture. This could violate the independence assumption between P and PE underpinning the Budyko framework, potentially leading to ill-posed parameterization of land-surface properties. Here, we showed that the use of AED as PE in a Budyko equation could significantly disturb a global runoff sensitivity assessment to climatic and land-property changes. By linking a two-parameter Budyko equation and the complementary evaporation principle (CEP), we found that climatic changes play a more important role in altering runoff than a prior assessment would suggest. This study also suggests that linking the Budyko equation with CEP can isolate the responsiveness of AED to soil moisture, allowing more proper consideration of surface energy balance.

How to cite: Kim, D. and Chun, J. A.: Linking the Budyko framework with the complementary evaporation principle for proper consideration of surface energy availability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10695, https://doi.org/10.5194/egusphere-egu22-10695, 2022.

Heavy rainfall in East Africa between late 2019 and mid 2020 caused devastating floods and landslides throughout the region. These rains drove the level of Lake Victoria to a record-breaking maximum in the second half of May 2020, when the lake reached its highest level since measurements began in 1948. The high lake levels and consequent shoreline flooding triggered international attention, with media sources proposing a causal link with climate change. However, a formal attribution study identifying the possible role of anthropogenic climate change in increasing the likelihood of such record-breaking water levels has not been carried out so far.

We present an attribution study that estimates how anthropogenic climate change influenced the likelihood of observing the rate of change in Lake Victoria’s level that was recorded in 2020. To this end, we reconstruct the record-high lake level using an observational water balance model for Lake Victoria. We first investigate the influence of the different water balance terms on the resulting lake level. Then, we apply the water balance model in a probabilistic event attribution framework by forcing it with historical and natural forcing only (hist-nat) bias-adjusted precipitation from six Earth system models from the Coupled Model Intercomparison Project phase 6 (CMIP6) ensemble, as made available through the Inter-Sectoral Impact Model Intercomparison Project phase 3b (ISIMIP3b). The study contributes to a better understanding of impacts caused by climate and weather extremes in the Greater Horn of Africa by disentangling the role of anthropogenic climate change and natural internal variability in a high-impact flood event.

How to cite: Pietroiusti, R., Vanderkelen, I., and Thiery, W.: Was the 2020 Lake Victoria flooding linked to anthropogenic climate change? An event attribution study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2300, https://doi.org/10.5194/egusphere-egu22-2300, 2022.

Around 60 percent of terrestrial precipitation on the global average transforms into evapotranspiration. However, reliable estimation of actual evapotranspiration (AET) is challenging as it depends on multiple climatic and biophysical factors. Despite developments such as remotely sensed AET products, AET responses to prolonged drought is still poorly understood. Therefore, this study focuses on understanding long-term changes and variability of AET prior to and during the Millennium Drought in Victoria, Australia. We also investigate the capability of commonly used rainfall-runoff models to simulate AET under multiyear droughts. Therefore, we employ simple sensitivity analysis to examine four different water balance approaches between pre-drought and drought periods in six different study catchments in Victoria. The first water balance approach is the simplest long-term water balance approach, partitioning long-term precipitation into evapotranspiration and runoff. The second water balance approach adopts a long-term change in storage to the water balance during the Millennium Drought by employing regional-scale change in GRACE estimates derived from Fowler et al. (2020). The third and fourth water balances are based on simulations from SIMHYD and SACRAMENTO. Surprisingly, the adoption of long-term change in storage during the Millennium Drought indicates that the annual rates of pre-drought AET were largely maintained throughout the drought; i.e. the rate was relatively constant with time. This suggests that AET gets priority over streamflow following a drying shift in precipitation partitioning; resulting in a relatively constant AET under multiyear drought. In contrast, the rainfall-runoff models underestimated AET during the drought compared to both water balance approaches. These results broadly acknowledge the need for model improvements to provide more realistic AET estimates under future drying climates and provide a new perspective on recent hydrological phenomena such as changing rainfall-runoff relationships in these regions. Furthermore, this sensitivity analysis was augmented and confirmed by a regional-scale water balance approach.

Keywords: Catchment water balance, Evapotranspiration, Change in storage, Rainfall-runoff models

References: Fowler, K., Knoben, W., Peel, M., Peterson, T., Ryu, D., Saft, M., Seo, K.W., Western, A., 2020. Many Commonly Used Rainfall-Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections. Water Resour. Res. 56. https://doi.org/10.1029/2019WR025286

How to cite: Gardiya Weligamage, H., Fowler, K., Peterson, T., Saft, M., Ryu, D., and Peel, M.: Towards Understanding Evapotranspiration Shifts Under a Drying Climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13013, https://doi.org/10.5194/egusphere-egu22-13013, 2022.

Australia's Millennium Drought (1997-2010) was a multi-year event notable for causing persistent shifts in the relationship between rainfall and runoff in many catchments.  Here, we describe a multi-disciplinary eWorkshop held in late 2020 to discuss the hydrology of the Millennium Drought and explore the hydrological processes leading to the hydrological shifts.  Research to date has successfully characterised where and when shifts occurred, explored which catchment attributes are statistically related to the shifts, and noted changes in rainfall partitioning.  However, a physical explanation for the changes in catchment behaviour is still lacking, hence the need for this workshop.  

Integrating perspectives from hydrogeology, ecohydrology, remote sensing, hydroclimatology, experimental hydrology and hydrological modelling, the workshop aimed to share and discuss “perceptual models” of flow response that could explain the Millennium Drought streamflow observations, considering both the spatial and temporal patterns of hydrological shifts. We considered a range of perceptual models of flow response, and then evaluated the models against available evidence. The models consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. Perceptual models were assessed both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall-runoff relationships shift in some catchments but not in others?). 

The results point to the unprecedented length of the drought (10+ years) as the primary climatic driver, paired with interrelated groundwater processes: declines in groundwater storage, reduced recharge associated with vadose zone expansion/drying, and reduced connection between subsurface and surface water processes.  An additional contributor is increased evaporative demand, and minor contributors may include farm dams, salinity recovery, and drainage via regional groundwater systems.  The roles of deep-rooted vegetation, wildfire, rainfall patterns, and land use change, among others, were discounted on various grounds.  

There is a need to confirm these landscape-scale evaluations with local long-term field monitoring, particularly of subsurface dynamics, faced with a lack of such monitoring during the drought itself.  A decline in monitoring meant that many variables went unmeasured that could have aided diagnosis.  Thus, the drought provides an example to other countries of the value of continued investment, particularly to build up and retain multi-decadal records in as many sites and variables as possible.  We strongly recommend investment in understanding of hydrological shifts through such monitoring, which is particularly important given the relevance of hydrological shifts to water planning under climate variability and change. 

How to cite: Fowler, K., Peel, M., Peterson, T., Saft, M., and Nathan, R. and the additional coauthors listed below: Explaining rainfall runoff changes associated with the Millennium Drought, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12742, https://doi.org/10.5194/egusphere-egu22-12742, 2022.

Global change has different effects on inland water bodies. In the case of lakes, the water level is a variable frequently affected. Lakes in semi-arid zones are susceptible to climatic and anthropic forcing. Understanding how these factors modulate changes in lakes is essential to develop forecasts and generate management and conservation programs. However, lakes evolution under external forcing may differ despite belonging to the same system. The differences highlight the importance of developing particular management plans for each lake. Therefore, it is necessary to understand the factors that modulate these peculiarities. An example in central Mexico is the six maar lakes found in the easternmost basin of the Mexican Plateau, the Serdán Oriental Basin: Alchichica, Quechulac, La Preciosa, Atexcac, Tecuitlapa, and Aljojuca. Groundwater flow is essential in the water balances of these lakes. However, intensive groundwater exploitation for agriculture has occurred since the '80s in this semi-arid basin. Several studies have revealed that these lakes' trophic states, biota, and chemical compositions differ remarkably. Both locals and researchers have noted water-level declines in all lakes in recent decades. Water level evolution also seems to be particular in each lake. Data on the lakes water levels from 1960 to 1992 and subsequent changes are analyzed. We assessed physical (e.g., climatic, geological, hydrogeological, vegetation) and anthropic (land-use changes and groundwater exploitation) factors that could modulate the water level evolution differences. Time series analysis, remote sensing, and statistical methods were applied. This work represents a conceptual framework for further studies oriented to the numerical modeling of the lake system and the exploration of future change scenarios.

How to cite: Silva Aguilera, R. A., Escolero, O., and Alcocer, J.: Long-term differential water level responses of a group of tropical maar lakes in a semi-arid basin (Cuenca Serdán Oriental, México), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11088, https://doi.org/10.5194/egusphere-egu22-11088, 2022.

Since the middle of the last century extreme rainfall events have intensified in many parts of the world (Martel et al., 2021), and increasing temperature is considered to let this development continue in the next decades. The Clausius-Clapeyron relationship, i.e. an about 7% increase per additional degree centigrade, yields an order of magnitude of what to expect, with convective rainfalls being likely to grow in a still more pronounced manner (Martel et al., op.cit.). Convective cells are, typically, associated with rainfalls of short duration and small spatial extent, which makes them particularly important for microcatchments.

Combining Green-Ampt type infiltration with kinematic overland flow, the relationship between a square-topped hyetograph and runoff is modelled. Frequently, design rainfall duration is chosen equal to the time of concentration. In case of an infiltrating surface, however, maximum peak runoff may result from shorter rainfall. There may, thus, be partial area runoff only, in which case the Schmid (1997) design storm equation yields the critical rainfall duration needed to determine maximum peak flow.

The study started from a chosen present-day IDF relationship of 20 years' return interval in Austria and a (rectangular) grass plot (hillslope) of 50 m length, 10% slope and an initial loss of 0.5 mm. Simulations were made using soil data from Columbia sandy loam, Guelph loam and Ida silt loam, in turn. Rainfall was assumed to be subject to Clausius-Clapeyron scaling and variable warming between 0.0 and 2.0 K.

In the case of the most pervious soil of the three (Columbia sandy loam, vertical saturated permeability K_sv = 0.0139 mm/s) flow was laminar and described by the Dary-Weisbach friction law (K = 4000). Contributing area remained small throughout (length 0.9 m for 0 K and 8.3 m for 2 K temperature increase). Corresponding peak flow showed above-linear growth and increased strongly from 0.013 L/(s.m) for 0 K to 0.17 L/(s.m) for 2 K.

The 'medium' soil, Guelph loam (K_sv = 0.00367 mm/s), was associated with contributing hillslope length growing from 35 m to the full 50 m as temperature increase varied from 0 to 2 K. Corresponding peak flows increased from 0.69 to 1.16 L/(s.m), i.e. by 68%. Flows over Guelph loam and Ida solt loam were turbulent (Manning's n = 0.4).

In case of the finest soil, Ida silt loam (K_sv = 0.000292 mm/s), all of the microcatchment contributed to overland flow from the start (DT = 0 K). Peak flow increased almost linearly with temperature from 2.31 to 2.77 L/(s.m), i.e. by 20%.

Consequently, it may be concluded that a future rise in temperature up to 2 K is likely to trigger strong increases in peak flows from infiltrating microcatchments. The present study indicates that Clausius-Clapeyron rainfall scaling may result in peak flows increasing much in excess of the 7% / K.

References

Martel, J.-L. et al.: Climate change and rainfall intensity-duration-frequency curves: overview of science and guidelines for adaption. J. Hydrol. Eng. 26(10), DOI: 10.1061/(ASCE)HE.1943-5584.0002122, 2021.

Schmid, B.H.: Critical rainfall duration for overland flow from an infiltrating plane surface. J. Hydrol. 193, 45-60, 1997.

How to cite: Schmid, B.: On climate change affecting the dynamics of overland flow from infiltrating microcatchments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2033, https://doi.org/10.5194/egusphere-egu22-2033, 2022.

This study tends to attribute the spatial patterns of hydrologic alteration in mid-latitude montane basins to the key driving forces being the climate and land use change. Physically-based distributed modeling system MIKE SHE was used for the analysis of changing spatiotemporal patterns of extreme runoff processes in montane catchments by using time series of hydrometeorological  observations, and spatially distributed MODIS data for evapotranspiration (ET) and leaf area index (LAI) as key resources for the model setup.

Czech Republic is surrounded by mountain ranges from all sides but the southeastern border, which is drained towards the Danube. Due to this concentric orientation of topography each mountain range has different aspect and exposition due to atmospheric processes. Does the basin hydrological reaction on changing the environment depend on the aspect or is there an overall trend present in all basins? In order to answer such a question, it is necessary to understand the main drivers of changes and to quantify the effect of each separately. 

8 headwater basins were analyzed of average size of 73 km2 where significant trends of hydrologic processes were detected from long-termed time series (1952 to 2018). Some of the trends are common for all basins such as seasonal shift of snowmelt period but other trends are rather site specific such as frequency of peak flows. Previous studies show that the hydrologic reaction on climate signal is the most dominant driver of the hydrologic alterations however there are other drivers such as forest disturbances that can mislead the interpretation of trend behavior. 

The aim of the study was to separate the effects of those main drivers by a detailed distributed physically-based modeling system MIKE SHE. Input data originated from official and publicly available sources in order to design a methodology that could be reproduced in other basins of comparable properties. Models are bent together thus results of similar spatial-temporal quality were obtained for further analysis. Stational data but also remote sensed data in the grid format were gathered in a comprehensive database. 

Two groups of scenarios were applied. First group was focused on climate signals (namely trends in precipitation, mean daily temperature and potential evapotranspiration) and the second group included land use changes such as bark beetle outbreak. Effect of both groups was quantified and compared with baseline simulation across all basins.

The model proved the long-term shifts in runoff seasonality, driven by the air temperature rise, and apparent across the mountain ranges. The seasonal runoff changes are marked by the shift of spring snowmelt toward an earlier season and a decline in spring flows. The second aspect of the changing seasonality is an earlier and prolonged period of summer low flows.

The results proved the dominancy of climate change as a main factor of runoff alteration, acting in large scale patterns, despite the local variations in physiography and land use.

How to cite: Bernsteinová, J. and Langhammer, J.: Attributing the spatial patterns of hydrological change to the effects of climate and land use change by distributed modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7753, https://doi.org/10.5194/egusphere-egu22-7753, 2022.

Accelerated climate and land use land cover (LULC) changes are anticipated to have large impacts on water resources in the Colorado River Basin (CRB). Since land use is a result of complex socio-ecological factors, accurately predicting future patterns of LULC is challenging. In addition, substantial differences among a large number of climate models necessitate a screening process for impact and adaptation studies. As a result, limitations of conventional ‘top-down’ approaches are becoming increasingly apparent. More recently, ‘bottom-up’ assessments are gaining popularity for exploring climate and LULC conditions using a few selected cases that consider a range of possibilities. Here, we improved and employed the Variable Infiltration Capacity (VIC) model to generate streamflow projections across the CRB under multiple cases of climate and LULC changes. We integrated advances in the model using Landsat- and MODIS- based products to produce more realistic land surface conditions. Meteorological datasets were drawn from statistically downscaled projections (2006-2099) to represent ‘hot and dry’ and ‘warm and wet’ futures. Vegetation parameters were modified by using regional projections of a LULC model upon which more drastic disturbances were applied to forest cover types. Water managers in the CRB were consulted to ensure that a range of views were captured in the modeled storylines and to maximize the legitimacy and credibility of the research for decision-makers. Analyses were conducted to identify system vulnerabilities and unexpected outcomes that pose the greatest consequences to long-term water supplies in the CRB. Results indicated that forest disturbances partially offset warming effects to streamflow (basin-wide mean annual streamflow was up to 9% larger than the case without disturbance by end of century), allowing more neutral impacts under warming.

How to cite: Whitney, K., Vivoni, E., Wang, Z., and Mascaro, G.: Assessing Future Climate and Land Use Impacts to the Colorado River using a Bottom-up Modelling Approach Informed by Water Managers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5757, https://doi.org/10.5194/egusphere-egu22-5757, 2022.

We studied the effect of a 13-year long dry period on the performance of five conceptual rainfall-runoff models in 155 catchments in the Australian state of Victoria in order to identify (1) which aspects of the flow regime are harder for models to reproduce during and after the drought; and (2) how model performance during this persistent drought compares to that during similarly dry individual years in the historical record. Persistent dry conditions in recent decades have affected hydrological processes and water partitioning in several regions globally; given the increased risk of drought posed by climate change, studying these historical long-lasting droughts and their effects on model reliability can inform climate adaptation strategies in many drought-prone regions worldwide.

The Millennium drought (MD), which affected more than 1×10⁶ km² of south-eastern Australia between 1997-2009, is one of such events and arguably the most reported on in literature. Research to date identifies significant shifts in catchment-level annual rainfall-runoff relationships in most catchments affected by the MD, many of which have failed to recover several years after the end of the meteorological anomaly. These shifts affect the reliability of models’ projections; however, by focusing on a handful of performance metrics only, currently published research falls short on identifying which specific aspects of model performance are affected and how.

Here, we focused on a wider range of performance metrics to assess models’ ability to represent a variety of aspects of the hydrograph and the flow-duration curve during and after the MD. For objective (1), we used a statistical metric derived from Wilcoxon signed-rank test (known as matched-pairs rank-biserial correlation coefficient) to compare changes in model performance during and after the drought from a pre-drought benchmark across metrics and catchments. For objective (2), we analysed changes in the relationship between annual model performance and annual rainfall using a regression technique.

We observed extensive degradation of model performance during the drought across most of the metrics studied. Overestimation of flow volumes drives the decline, while representation of shape and variability of the hydrograph and the flow-duration curve are more resilient to prolonged drought. This means that volumes’ overestimation is not associated to specific flow regimes, but results from flow declining proportionally throughout the hydrograph, suggesting that multiple catchment processes interact to cause the observed changes across high and low flows as well as through faster and slower routes. We obtained very similar results in the decade after the drought, indicating that model performance, similarly to rainfall-runoff relationships, often does not recover after the dry spell ends. Additionally, regression analysis of annual performance and rainfall showed disproportional decline of model reliability during the multi-year event compared to single dry years before the drought, suggesting that the persistency of the drought is likely responsible for exacerbated performance decline due to accumulation and aggravation of errors over subsequent dry years.

How to cite: Trotter, L., Saft, M., Peel, M., and Fowler, K.: How does the performance of rainfall-runoff models degrade due to multi-annual drought? A large-sample, multi-model study., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6866, https://doi.org/10.5194/egusphere-egu22-6866, 2022.

The H2020 project DRYvER (https://doi.org/10.3897/rio.7.e77750) on drying river networks and climate change aims at understanding the impact of climate change on intermittent rivers and ephemeral streams in six mesoscale river basins between 200~km² and 350~km² in different European countries (Croatia, Czech Republic, Finland, France, Hungary, Spain). 
One of the objectives of the DRYvER project is to compare the evolution of streamflow intermittence under climate change in the six study areas.
To do so we are developing a common modelling framework, using the distributed and physically based hydrological model J2000 (Krause et al., 2006), which is able to represent processes at the reach scale, and therefore, simulate flow intermittence at a high spatio-temporal resolution.

A challenge here is to use a climate forcing dataset (precipitation and temperature) that has a sufficiently large coverage to cover all the catchment case studies, but that also accurately represents the spatial and temporal variability of the meteorological variables in order to accurately simulate the local hydrological response.

In this study, we analyze the impact of using datasets with global or European coverage (ERA5-land, WFDE5, UERRA-MESCAN, E-obs) versus using local observed data or local gridded datasets (e.g. SAFRAN reanalysis for France, Nordic Gridded Climate Dataset for Finland).
First, we compare the climate datasets at the catchment scale, and then analyze the impact of using them on the simulated runoff.
Results show variable differences between the datasets for the six catchment case studies, with larger gaps in mountain basins with a larger range of elevations.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 869226.

How to cite: Mimeau, L., Künne, A., Kralisch, S., Branger, F., and Vidal, J.-P.: Inter-comparison of climatological datasets for the hydrological modelling of six european catchments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9782, https://doi.org/10.5194/egusphere-egu22-9782, 2022.

Evaluating likely hydrological consequences of predicted and current actual climatic change is a complex challenge, not only because of uncertainties about societal, land-use and vegetational responses and feedbacks, but also because lack of information on some climatic variables that influence hydrological processes.  With a focus on the humid tropics, this paper addresses the influence of changes in rainstorm size-frequency on the interception component of evapotranspiration - and how this can in turn influences the nature and magnitude of impact of rainfall change on catchment water budgets.  This is critical for two reasons.  First, both climatic modelling predictions and current trends for annual rainfall in the humid tropics vary greatly between regions from significant increases to major declines.  Second, because of the ability of a warmer atmosphere to hold more water vapour, IPCC confidently predicts that extreme rainstorms worldwide will increase regardless of annual rainfall trends and it is also arguable that rainstorms in general will increase in intensity and storm total. Thus changes in rainstorm size-frequency distribution are to be expected.   

This paper focuses on the primary and disturbed equatorial rainforest environment of Sabah, Malaysian Borneo.  The paper (1) uses long-term daily rainfall series at four stations in Sabah (from 1906 for Sandakan, Tawau and Kota Kinabalu; and from 1985 for Danum) to assess the magnitude of recent changes in rainstorm size-frequency distribution in Sabah and (2) presents and uses a simple Excel-based model to translate these data into estimated changes in interception (and also total evapotranspiration and river flow).  The underlying principle of the model is that Interception (as a percentage of storm rainfall) falls with increasing storm size, as interception storage capacity is filled.  Results of previous rainforest interception studies (including by one of the authors at Danum in Sabah) are used to calibrate the model, whereby percentage interception reduces in steps from 100 % for storms of < 1 mm and 80 % for storms of 1-2 mm, to 13.6 % for storms of 10-14.9 mm and the interception capacity of 2.2 mm (5.5 % or less) for storms of >40 mm.  It follows that annual interception, both in mm and as a percentage of annual rainfall, will be much greater if most rainstorms are small, but progressively lower as the percentage of rain falling in big storms increases.  Differences in rainstorm size-frequency distribution help to account for the big range (7-27 % of annual rainfall) in annual interception found between different rainforest locations.  The Pico presentation first presents the model and demonstrates the magnitude by which simulated annual interception values vary between individual years of contrasting annual rainfall and rainstorm size-frequency distribution at the four locations.  Then the temporal changes in daily rainfall size-frequency at the four stations are presented and compared and  (using model outputs) changes in seasonal and annual interception and other water budget variables are assessed.  Finally, problems with, possible improvements to, and the wider applicability of the approach adopted are discussed.       

How to cite: Walsh, R., Bidin, K., Safjankova, A., and Nainar, A.: Modelling effects of changing rainstorm size-frequency on annual interception and catchment water budgets in Sabah, Malaysian Borneo, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12824, https://doi.org/10.5194/egusphere-egu22-12824, 2022.

As one of the world’s driest continents, Australia’s water resources need to be carefully managed to ensure sustainable access to water for livelihoods, human well-being, and ecosystem health. Australia is also a land of extremes from floods to droughts and catastrophic wildfires which are all becoming more frequent and destructive. It is essential to understand future changes in water availability and hydrologic extremes to support the development of mitigation strategies and the planning for water infrastructure and policies. To build this understanding, the Bureau of Meteorology has released the Australian Water Outlook (AWO), a seamless national landscape water service. The AWO includes National Hydrological Projections, as well as seasonal forecast and historical products, all using the Bureau’s Australian Water Landscape Water Balance model (awo.bom.gov.au).

Projection results feature many sources of uncertainty, including how future greenhouse gas emissions will develop, how a changing climate will lead to changes to hydrological features and feedback loops, and the climate and hydrological models used to simulate those changes. Acknowledging these uncertainties, the Bureau's National Hydrological Projections ensemble provides a unique opportunity to examine impacts of future changes on Australia’s hydroclimate and its water resources. It allows nationally consistent impact assessments across multiple spatial and temporal scales. To produce these projections, three bias-correction approaches were used as well as a regional downscaling model. These methods were in turn applied to four global climate models in an operational framework resulting in a nationally consistent future change dataset for climate (rainfall, solar radiation, temperature, and wind) and hydrological (soil moisture, evapotranspiration, and runoff) variables. 

An overview of the National Hydrological Projections methods and results, including a series of 8 regional water resource assessment reports, will be presented. The reports were created to facilitate understanding and use of the data and describe future changes in regional hydrology using a novel storyline approach. The storyline approach is used to improve the communication of plausible impacts to Australia's future water availability. Plausible futures portend a drier climate for large parts of Australia which could pose challenges for future water resource management.

How to cite: Bende-Michl, U., Wilson, L., Sharples, W., Oke, A., Hope, P., Matic, V., Turner, M., Khan, Z., Kociuba, G., and Carrara, E.: Assessing patterns of future hydrological change for Australia: insights from the National Hydrological projections, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6710, https://doi.org/10.5194/egusphere-egu22-6710, 2022.

High and low flows are hydrological flow extremes threatening human being by causing floods and droughts. They are caused by meteorological extremes and human activities.  Changes in meteorological conditions will inevitably impact the frequency of hydrological extremes and exacerbate their associated hydrological impacts.

This study focuses on modelling projected change in both frequency and magnitude of flow extremes as consequence to change in climate condition in the Siliana catchment in Tunisia. The SWAT and HBV hydrological models were calibrated using historical data and fed with an ensemble of high resolution CORDEX climate models. Results project a warmer and drier hydrometeorological conditions in the Siliana catchment. The precipitation is expected to decrease in the future by an average of 10% in dry season and 12% in wet season. In contrast, temperature is expected to increase by an average of +2°C in dry season and 1.8°C in wet period.

The two models show that while magnitude and frequency of high flows are expected to decrease, low flows frequency is expected to increase which affirms that the Siliana catchment is likely to experience severe hydrological conditions with reduction in water availability and increase in drought frequency.

How to cite: EL Ghoul, I., Tliha, F., Sellami, H., Mounir, K., Khlifi, S., and Vanclooster, M.: Climate change induced impacts on hydrological extremes at the catchment scale: case of Wadi Siliana (North western Tunisia), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8676, https://doi.org/10.5194/egusphere-egu22-8676, 2022.

Changes in climatic forcing will change regional hydrological responses, both long-term seasonal dynamics and extreme events. Impact assessments are urgently needed by decision makers for climate adaptation planning, despite the uncertainties in the impact model chain. Therefore, uncertainties in impact assessments need to be evaluated and communicated along with the actual results in a transparent and user-friendly way.

Here, we show results from a hydrological climate impact study for Sweden, which is communicated to regional planners through a web-based assessment tool (smhi.se/en/climate/future-climate/advanced-climate-change-scenario-service/hyd). Climate change impacts are expected to alter seasonal hydrological dynamics as well as hydrological extremes in the region. We use a modelling framework based on a calibrated national hydrological model, S-HYPE, which divides the domain into  ~ 35000 computational sub-basins, for which hydrological states and fluxes are computed using a conceptual process model including lake and river management routines. S-HYPE is forced with an ensemble of Euro-CORDEX regional climate forcing for a 1971 to 2100 assessment period and representative concentration pathways 2.6, 4.5, and 8.5. All forcing is bias-corrected to a gridded reference forcing data set using quantile mapping. Results are communicated in a spatially aggregated form for ~ 250 river basins using climate impact indicators (CII), which highlight expected change patterns for specific parts of the hydrolgical cycle, e.g. change in maximum annual snow water equivalent or summer discharges. Uncertainties are communicated through ensemble spread and robustness measures, allowing users to directly assess at least parts of the uncertainty in the model results.

We also use the modelled results for a comparative analysis of change impacts across river basins in Sweden, taking advantage of the north-south climate gradient across the domain. This allows for a direct comparison of modelled today and future behaviour of similar river basins across that gradient to evaluate the uncertainty in future impacts which orginate in the model representation of interactions and feedbacks between climate and hydrological system within the S-HYPE model framework.

How to cite: Capell, R., Musuuza, J., Berg, P., Bosshard, T., and Lindström, G.: Regional hydrological response to climate change across Sweden - impact modelling and communication, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8143, https://doi.org/10.5194/egusphere-egu22-8143, 2022.

Typically, the future hydrological behavior of a river basin, for example as a result of climate change, is predicted using hydrological models calibrated with historical observations. In reality, hydrological systems, and hence model parameters, experience almost continuous change in time and space. More specifically, there is growing evidence that vegetation adapts to changing conditions by adjusting its root-zone storage capacity, i.e. the amount of water in the unsaturated subsurface which is available to the roots of vegetation for transpiration. Additionally, other species may become dominant 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. In other words, if the climate changes, how should our models change and what is the effect on the hydrological response? Our methodology directly uses projected climate data to estimate how vegetation adapts its root-zone storage capacity at the catchment scale to changes in hydro-climatic variables and potential land-use change. We test the hypothesis that changes in the hydrological response under global warming are more pronounced when explicitly considering changes reflecting adaptation of the root-zone storage capacity of vegetation. We compare a stationary benchmark model with several non-stationary model scenarios reflecting climate and potential land-use changes in the Meuse basin. We found that the larger root-zone storage capacities (+34%) in response to warmer summers under projected +2K global warming result in up to -15% less streamflow in autumn due to 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.

How to cite: Bouaziz, L. J. E., Aalbers, E. E., Weerts, A. H., Hegnauer, M., Buiteveld, H., Lammersen, R., Stam, J., Sprokkereef, E., Savenije, H. H. G., and Hrachowitz, M.: Sensitivity of hydrological predictions to ecosystem adaptation in response to climate change: the effect of time-dynamic model parameters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4613, https://doi.org/10.5194/egusphere-egu22-4613, 2022.

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 a pragmatic delta change approach 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 advanced delta change approach (van Pelt et al., 2012) is selected here as it allows to create differential change factor according to distribution quantiles. 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 is first applied to the Ain catchment case study (France) that includes the intermittent Albarine river, considering a control period (1985-2014) and two future periods (2021-2050 and 2071-2100). These experiments are conducted using one run from 5 different global climate models and 2 emission/socio-economic scenarios (SSP1-RCP2.6 and SSP5-RCP8.5) from the CMIP6 experiments. This methodology allows to grasp the range of future changes in daily streamflow over the entire catchment. The comparison between the control period and the two future periods is used to describe possible changes over seasonal discharge and low flow characteristics.

This approach is a preliminary step providing first and rapid insights into 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 way to better grasp the joint influence of climate change and climate variability on reach-scale intermittence.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 869226

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.

van Pelt et al., (2012) Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations. Hydrology and Earth System Sciences. doi:10.5194/hess-16-4517-2012.

How to cite: Devers, A., Lauvernet, C., and Vidal, J.-P.: Using the advanced delta change approach and a distributed model for a rapid assessment of reach-scale streamflow projections in intermittent rivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3950, https://doi.org/10.5194/egusphere-egu22-3950, 2022.

UN Sustainable Development Goal (SDG) 6.1 aims to achieve universal and equitable access to safe and affordable drinking water for all by 2030. However, even in a developed nation such as Scotland, climate change, and the water systems resilience to it, is putting achieving this goal at risk. Despite being abundantly blessed in terms of water resources, Scotland is facing an accelerated increase in the frequency of extreme weather events. The UK Climate Projections 2018 indicate that Scotland’s climate will become warmer, with drier summers, and increased occurrence of drought events. Recent water scarcity events prove the surge and are evidence for the projected weather patterns. Unlike drought indicators which are parameters describing meteorological, hydrological or agricultural drought conditions, like precipitation amounts, streamflow levels, soil moisture information, drought indices derive value based on statistical calculations. Once such meteorological drought index is the Standardised Precipitation and Evapotranspiration Index (SPEI) which is similar to the Standardised Precipitation Index (SPI). Unlike SPI, SPEI incorporates changes in evapotranspiration as it includes both precipitation and temperature as input data for calculation. Hence, SPEI makes a good choice for projecting future changes in a warming world and allows us to see the impact of climate change in inducing drought. Regional-scale analysis of SPEI across 36 sites using a 50 km grid generated drought scenarios for the longer term 2041-2080 using all 12 model members the UKCP18 dataset using 1981-2020 as the baseline period. These UKCP 18 projections were bias-corrected and downscaled to a 1km grid across Scotland before we acquired the data for analysis, thus enabling the calculation of SPEI at a finer scale. SPEI was then calculated at a 6-month timestep across the 36 sites in Scotland. The number of extreme drought months was computed for the baseline and the future periods. The drought month was defined as any month which has SPEI ≤ -2.  After calculating the extreme drought months for baseline and future periods, the metrics from 1981-2020 were subtracted from the future period for each model member to demonstrate the amount of change in the number of drought months from the baseline period. Results were calculated separately for the individual member and not averaged to avoid incorporating uncertainty associated with projections. The majority of the sites across the spatial extent showed projected increases in the number of drought months for the future period for each of the model members. Sites in the southwest and western Scottish islands showed a greater increase compared to other sites where extreme drought months were observed with little or no change. Results highlighted the need for better preparedness for water scarcity situations which are going to be exacerbated by climate change.

How to cite: Pawar, S., Halliday, S., Glendell, M., and Ovando Pol, P.: What does the future hold? Using Standardised Precipitation and Evapotranspiration Index (SPEI) to project drought in Scotland., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3707, https://doi.org/10.5194/egusphere-egu22-3707, 2022.