scholarly journals Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models

2021 ◽  
Vol 25 (9) ◽  
pp. 5013-5027
Author(s):  
Pierre Nicolle ◽  
Vazken Andréassian ◽  
Paul Royer-Gaspard ◽  
Charles Perrin ◽  
Guillaume Thirel ◽  
...  
Keyword(s):  
Technical Note ◽  
Evaluation Framework ◽  
Hydrological Models ◽  
Climate Conditions ◽  
Evaluation Approach ◽  
Physically Based ◽  
Sample Test ◽  
Change Impact ◽  
Robustness Assessment ◽  
Past Conditions

Abstract. Prior to their use under future changing climate conditions, all hydrological models should be thoroughly evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). This note presents a straightforward evaluation framework aimed at detecting potential undesirable climate dependencies in hydrological models: the robustness assessment test (RAT). Although it is conceptually inspired by the classic differential split-sample test of Klemeš (1986), the RAT presents the advantage of being applicable to all types of models, be they calibrated or not (i.e. regionalized or physically based). In this note, we present the RAT, illustrate its application on a set of 21 catchments, verify its applicability hypotheses and compare it to previously published tests. Results show that the RAT is an efficient evaluation approach, passing it successfully can be considered a prerequisite for any hydrological model to be used for climate change impact studies.

scholarly journals Technical Note – RAT: a Robustness Assessment Test for calibrated and uncalibrated hydrological models

2021 ◽  
Author(s):  
Pierre Nicolle ◽  
Vazken Andréassian ◽  
Paul Royer-Gaspard ◽  
Charles Perrin ◽  
Guillaume Thirel ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Hydrological Model ◽  
Technical Note ◽  
New Method ◽  
Hydrological Models ◽  
Split Sample ◽  
Sample Test ◽  
Change Impact ◽  
Robustness Assessment

Abstract. In this note, we present RAT, a new method to assess the robustness of hydrological models. RAT can be seen as an alternative to the classical split-sample test widely used in hydrology. And because the RAT method does not require multiple calibrations, we suggest that it can be applied even to uncalibrated models. The RAT method can be used to determine whether a hydrological model is "safe" for being used for climate change impact studies.

scholarly journals Is bias correction of Regional Climate Model (RCM) simulations possible for non-stationary conditions?

2012 ◽  
Vol 9 (11) ◽  
pp. 12765-12795 ◽  
Author(s):  
C. Teutschbein ◽  
J. Seibert
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Change Impact ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Conditions ◽  
Impact Studies ◽  
Split Sample ◽  
Sample Test ◽  
Change Impact

Abstract. In hydrological climate-change impact studies, Regional Climate Models (RCMs) are commonly used to transfer large-scale Global Climate Model (GCM) data to smaller scales and to provide more detailed regional information. However, there are often considerable biases in RCM simulations, which have led to the development of a number of bias correction approaches to provide more realistic climate simulations for impact studies. Bias correction procedures rely on the assumption that RCM biases do not change over time, because correction algorithms and their parameterizations are derived for current climate conditions and assumed to apply also for future climate conditions. This underlying assumption of bias stationarity is the main concern when using bias correction procedures. It is in principle not possible to test whether this assumption is actually fulfilled for future climate conditions. In this study, however, we demonstrate that it is possible to evaluate how well bias correction methods perform for conditions different from those used for calibration. For five Swedish catchments, several time series of RCM simulated precipitation and temperature were obtained from the ENSEMBLES data base and different commonly-used bias correction methods were applied. We then performed a differential split-sample test by dividing the data series into cold and warm respective dry and wet years. This enabled us to evaluate the performance of different bias correction procedures under systematically varying climate conditions. The differential split-sample test resulted in a large spread and a clear bias for some of the correction methods during validation years. More advanced correction methods such as distribution mapping performed relatively well even in the validation period, whereas simpler approaches resulted in the largest deviations and least reliable corrections for changed conditions. Therefore, we question the use of simple bias correction methods such as the widely used delta-change approach and linear scaling for RCM-based climate-change impact studies and recommend using higher-skill bias correction methods.

scholarly journals Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions

2012 ◽  
Vol 16 (4) ◽  
pp. 1171-1189 ◽  
Author(s):  
G. Seiller ◽  
F. Anctil ◽  
C. Perrin
Keyword(s):  
Test Procedure ◽  
Model Performance ◽  
Flow Simulation ◽  
Added Value ◽  
Hydrological Models ◽  
Model Ensemble ◽  
Climate Conditions ◽  
Sample Test ◽  
Improved Performance ◽  
The Individual

Abstract. This paper investigates the temporal transposability of hydrological models under contrasted climate conditions and evaluates the added value of using an ensemble of model structures for flow simulation. This is achieved by applying the Differential Split Sample Test procedure to twenty lumped conceptual models on a catchment in the Province of Québec (Canada) and another one in the State of Bavaria (Germany). First, a calibration/validation procedure was applied on four historical non-continuous periods with contrasted climate conditions. Then, model efficiency was quantified individually (for each model) and collectively (for the model ensemble). The individual analysis evaluated model performance and robustness. The ensemble investigation, based on the average of simulated discharges, focused on the twenty-member ensemble and all possible model subsets. Results showed that using a single model may provide hazardous results when the model is to be applied in contrasted conditions. Overall, some models turned out as a good compromise in terms of performance and robustness, but generally not as much as the twenty-model ensemble. Model subsets offered yet improved performance over the twenty-model ensemble, but at the expanse of spatial transposability (i.e. need of site-specific analysis).

scholarly journals Supplementary material to "Technical Note – RAT: a Robustness Assessment Test for calibrated and uncalibrated hydrological models"

2021 ◽  
Author(s):  
Pierre Nicolle ◽  
Vazken Andréassian ◽  
Paul Royer-Gaspard ◽  
Charles Perrin ◽  
Guillaume Thirel ◽  
...  
Keyword(s):  
Technical Note ◽  
Hydrological Models ◽  
Supplementary Material ◽  
Robustness Assessment

scholarly journals Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions?

2013 ◽  
Vol 17 (12) ◽  
pp. 5061-5077 ◽  
Author(s):  
C. Teutschbein ◽  
J. Seibert
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Change Impact ◽  
Climate Model ◽  
Regional Climate ◽  
Model Errors ◽  
Climate Conditions ◽  
Split Sample ◽  
Sample Test ◽  
Change Impact

Abstract. In hydrological climate-change impact studies, regional climate models (RCMs) are commonly used to transfer large-scale global climate model (GCM) data to smaller scales and to provide more detailed regional information. Due to systematic and random model errors, however, RCM simulations often show considerable deviations from observations. This has led to the development of a number of correction approaches that rely on the assumption that RCM errors do not change over time. It is in principle not possible to test whether this underlying assumption of error stationarity is actually fulfilled for future climate conditions. In this study, however, we demonstrate that it is possible to evaluate how well correction methods perform for conditions different from those used for calibration with the relatively simple differential split-sample test. For five Swedish catchments, precipitation and temperature simulations from 15 different RCMs driven by ERA40 (the 40 yr reanalysis product of the European Centre for Medium-Range Weather Forecasts (ECMWF)) were corrected with different commonly used bias correction methods. We then performed differential split-sample tests by dividing the data series into cold and warm respective dry and wet years. This enabled us to cross-evaluate the performance of different correction procedures under systematically varying climate conditions. The differential split-sample test identified major differences in the ability of the applied correction methods to reduce model errors and to cope with non-stationary biases. More advanced correction methods performed better, whereas large deviations remained for climate model simulations corrected with simpler approaches. Therefore, we question the use of simple correction methods such as the widely used delta-change approach and linear transformation for RCM-based climate-change impact studies. Instead, we recommend using higher-skill correction methods such as distribution mapping.

Communicating water-related climate change hazards to local stakeholders

2021 ◽  
Author(s):  
Laura Müller ◽  
Petra Döll
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Climate Change Impact ◽  
Biosphere Reserve ◽  
Hydrological Models ◽  
Model Ensemble ◽  
Hydrological Hazards ◽  
Local Stakeholders ◽  
Change Impact ◽  
The Impact

<p>Due to climate change, the water cycle is changing which requires to adapt water management in many regions. The transdisciplinary project KlimaRhön aims at assessing water-related risks and developing adaptation measures in water management in the UNESCO Biosphere Reserve Rhön in Central Germany. One of the challenges is to inform local stakeholders about hydrological hazards in in the biosphere reserve, which has an area of only 2433 km² and for which no regional hydrological simulations are available. To overcome the lack of local simulations of the impact of climate change on water resources, existing simulations by a number of global hydrological models (GHMs) were evaluated for the study area. While the coarse model resolution of 0.5°x0.5° (55 km x 55 km at the equator) is certainly problematic for the small study area, the advantage is that both the uncertainty of climate simulations and hydrological models can be taken into account to provide a best estimate of future hazards and their (large) uncertainties. This is different from most local hydrological climate change impact assessments, where only one hydrological model is used, which leads to an underestimation of future uncertainty as different hydrological models translate climatic changes differently into hydrological changes and, for example, mostly do not take into account the effect of changing atmospheric CO<sub>2</sub> on evapotranspiration and thus runoff.   </p><p>The global climate change impact simulations were performed in a consistent manner by various international modeling groups following a protocol developed by ISIMIP (ISIMIP 2b, www.isimip.org); the simulation results are freely available for download. We processed, analyzed and visualized the results of the multi-model ensemble, which consists of eight GHMs driven by the bias-adjusted output of four general circulation models. The ensemble of potential changes of total runoff and groundwater recharge were calculated for two 30-year future periods relative to a reference period, analyzing annual and seasonal means as well as interannual variability. Moreover, the two representative concentration pathways RCP 2.6 and 8.5 were chosen to inform stakeholders about two possible courses of anthropogenic emissions.</p><p>To communicate the results to local stakeholders effectively, the way to present modeling results and their uncertainty is crucial. The visualization and textual/oral presentation should not be overwhelming but comprehensive, comprehensible and engaging. It should help the stakeholder to understand the likelihood of particular hazards that can be derived from multi-model ensemble projections. In this contribution, we present the communication approach we applied during a stakeholder workshop as well as its evaluation by the stakeholders.</p>

scholarly journals Climate change impact on water resource extremes in a headwater region of the Tarim basin in China

2011 ◽  
Vol 15 (11) ◽  
pp. 3511-3527 ◽  
Author(s):  
T. Liu ◽  
P. Willems ◽  
X. L. Pan ◽  
An. M. Bao ◽  
X. Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Ground Water ◽  
Climate Change Impact ◽  
Snow Accumulation ◽  
Tarim River Basin ◽  
Hydrological Models ◽  
Snow Melting ◽  
Change Impact ◽  
Ipcc Sres

Abstract. The Tarim river basin in China is a huge inland arid basin, which is expected to be highly vulnerable to climatic changes, given that most water resources originate from the upper mountainous headwater regions. This paper focuses on one of these headwaters: the Kaidu river subbasin. The climate change impact on the surface and ground water resources of that basin and more specifically on the hydrological extremes were studied by using both lumped and spatially distributed hydrological models, after simulation of the IPCC SRES greenhouse gas scenarios till the 2050s. The models include processes of snow and glacier melting. The climate change signals were extracted from the grid-based results of general circulation models (GCMs) and applied on the station-based, observed historical data using a perturbation approach. For precipitation, the time series perturbation involves both a wet-day frequency perturbation and a quantile perturbation to the wet-day rainfall intensities. For temperature and potential evapotranspiration, the climate change signals only involve quantile based changes. The perturbed series were input into the hydrological models and the impacts on the surface and ground water resources studied. The range of impact results (after considering 36 GCM runs) were summarized in high, mean, and low results. It was found that due to increasing precipitation in winter, snow accumulation increases in the upper mountainous areas. Due to temperature rise, snow melting rates increase and the snow melting periods are pushed forward in time. Although the qualitive impact results are highly consistent among the different GCM runs considered, the precise quantitative impact results varied significantly depending on the GCM run and the hydrological model.

scholarly journals Investigation of Climate and Land Use Change Impacts on Stream Flow of Guder Catchment, Ethiopia

2021 ◽  
Author(s):  
Bekam Bekele Gulti ◽  
Boja Mokonnen Manyazew ◽  
Abdulkerim Bedewi Serur
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Stream Flow ◽  
Open Space ◽  
Smart Growth ◽  
Assessment Model ◽  
Study Region ◽  
Climate Conditions ◽  
Change Impact ◽  
The Impact

Abstract Climate change (CC) and land use/cover change (LUCC) are the main drivers of streamflow change. In this paper, we investigate the impact of climate and LULC change impact on stream flow of Guder catchment by using Soil and Water Assessment model (SWAT). The scenarios were designed in a way that LULC was changed while climate conditions remain constant; LULC was then held constant under a changing climate and combined effect of both. The result shows that, the combined impacts of climate change and LULC dynamics can be rather different from the effects that follow-on from LULC or climate change alone. Streamflow would be more sensitive to climate change than to the LULC changes scenario, even though changes in LULC have far-reaching influences on streamflow in the study region. A comprehensive strategy of low impact developments, smart growth, and open space is critical to handle future changes to streamflow systems.

scholarly journals Technical note: PMR – a proxy metric to assess hydrological model robustness in a changing climate

2021 ◽  
Author(s):  
Paul Royer-Gaspard ◽  
Vazken Andréassian ◽  
Guillaume Thirel
Keyword(s):  
Hydrological Model ◽  
Evaluation Studies ◽  
Computational Cost ◽  
Climatic Conditions ◽  
Technical Note ◽  
Performance Metric ◽  
Reliable Assessment ◽  
Sample Test ◽  
The Impact ◽  
Model Robustness

Abstract. The ability of hydrological models to perform in climatic conditions different from those encountered in calibration is crucial to ensure a reliable assessment of the impact of climate change in water management sectors. However, most evaluation studies based on the Differential Split-Sample Test (DSST) endorsed the consensus that rainfall-runoff models lack climatic robustness. Models typically exhibit substantial errors on streamflow volumes applied under climatologically different conditions. In this technical note, we propose a new performance metric to evaluate model robustness without applying the DSST and which performs with a single hydrological model calibration. The Proxy for Model Robustness (PMR) is based on the systematic computation of model error on sliding sub-periods of the whole streamflow time series. We demonstrate that the metric shows patterns similar to those obtained with the DSST for a conceptual model on a set of 377 French catchments. An analysis of sensitivity to the length of the sub-periods shows that this length influences the values of the PMR and its adequation with DSST biases. We recommend a range of a few years for the choice of sub-period lengths, although this should be context-dependent. Our work makes it possible to evaluate the temporal transferability of any hydrological model, including uncalibrated models, at a very low computational cost.

scholarly journals Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

2012 ◽  
Vol 13 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Jin Teng ◽  
Jai Vaze ◽  
Francis H. S. Chiew ◽  
Biao Wang ◽  
Jean-Michel Perraud
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Daily Rainfall ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Runoff Modeling ◽  
Change Impact ◽  
The Difference ◽  
Climate Series

Abstract This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

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