scholarly journals Implication of calibration period on modelling climate change impact on future runoff

Author(s):  
F. H. S. Chiew ◽  
H. Zheng ◽  
J. Vaze

Abstract. This paper explores the consideration and implication of calibration period on the modelled climate change impact on future runoff. The results show that modelled runoff and hydrologic responses can be influenced by the choice of historical data period used to calibrate and develop the hydrological model. Modelling approaches that do not take this into account may therefore underestimate the range and uncertainty in future runoff projections. Nevertheless, the uncertainty associated with the choice of hydrological models and consideration of calibration dataset for modelling climate change impact on runoff is likely to be small compared to the uncertainty in the future rainfall projections.

2018 ◽  
Vol 20 (3) ◽  
pp. 597-607 ◽  
Author(s):  
Moon-Hwan Lee ◽  
Deg-Hyo Bae

Abstract Quantifying the uncertainty of future projection is important to assess the reliable climate change impact. In this sense, this study is aimed at investigating the uncertainty sources of various water variables (seasonal dam inflow, 1-day maximum dam inflow, and 30-day minimum dam inflow) according to downscaling methods and hydrological modeling. Five regional climate models (RCMs), five statistical post-processing methods and two hydrological models were applied for the uncertainty analysis. The changes for seasonal dam inflow are 0.1, 58.8, 5.1, and 1.1 mm for the SWAT model and 2.1, 76.1, −8.5, and −2.9 mm for the VIC model in spring, summer, autumn, and winter, respectively. The effects of the hydrological model is smaller than that of RCM for future projections of the seasonal dam inflow. The changes of annual 1-day maximum dam inflow vary according to the selection of RCM whereas the changes of annual 30-day minimum dam inflow are sensitive to the selection of hydrological model. The RCM is the dominant source of uncertainty of all seasonal dam inflow (except for winter) and high flow, whereas the hydrological model is the dominant source of uncertainty in winter dam inflow and low flow. Considering these results, the appropriate multi-model ensemble chain according to target variable will be necessary for reliable climate change impact assessment.


2021 ◽  
Author(s):  
Pierre Nicolle ◽  
Vazken Andréassian ◽  
Paul Royer-Gaspard ◽  
Charles Perrin ◽  
Guillaume Thirel ◽  
...  

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.


2021 ◽  
Author(s):  
Laura Müller ◽  
Petra Döll

<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>


2014 ◽  
Vol 18 (8) ◽  
pp. 3301-3317 ◽  
Author(s):  
M. Honti ◽  
A. Scheidegger ◽  
C. Stamm

Abstract. Climate change impact assessments have become more and more popular in hydrology since the middle 1980s with a recent boost after the publication of the IPCC AR4 report. From hundreds of impact studies a quasi-standard methodology has emerged, to a large extent shaped by the growing public demand for predicting how water resources management or flood protection should change in the coming decades. The "standard" workflow relies on a model cascade from global circulation model (GCM) predictions for selected IPCC scenarios to future catchment hydrology. Uncertainty is present at each level and propagates through the model cascade. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. Our hypothesis was that the relative importance of climatic and hydrologic uncertainty is (among other factors) heavily influenced by the uncertainty assessment method. To test this we carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on two small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment with two different likelihood functions. One was a time series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was an approximate likelihood function for the flow quantiles. The results showed that the expected climatic impact on flow quantiles was small compared to prediction uncertainty. The choice of uncertainty assessment method actually determined what sources of uncertainty could be identified at all. This demonstrated that one could arrive at rather different conclusions about the causes behind predictive uncertainty for the same hydrological model and calibration data when considering different objective functions for calibration.


2011 ◽  
Vol 15 (11) ◽  
pp. 3511-3527 ◽  
Author(s):  
T. Liu ◽  
P. Willems ◽  
X. L. Pan ◽  
An. M. Bao ◽  
X. Chen ◽  
...  

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.


2012 ◽  
Vol 13 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Jin Teng ◽  
Jai Vaze ◽  
Francis H. S. Chiew ◽  
Biao Wang ◽  
Jean-Michel Perraud

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.


2018 ◽  
Vol 10 (4) ◽  
pp. 759-781 ◽  
Author(s):  
Hadush K. Meresa ◽  
Mulusew T. Gatachew

Abstract This paper aims to study climate change impact on the hydrological extremes and projected precipitation extremes in far future (2071–2100) period in the Upper Blue Nile River basin (UBNRB). The changes in precipitation extremes were derived from the most recent AFROCORDEX climate data base projection scenarios compared to the reference period (1971–2000). The climate change impacts on the hydrological extremes were evaluated using three conceptual hydrological models: GR4 J, HBV, and HMETS; and two objective functions: NSE and LogNSE. These hydrological models are calibrated and validated in the periods 1971–2000 and 2001–2010, respectively. The results indicate that the wet/dry spell will significantly decrease/increase due to climate change in some sites of the region, while in others, there is increase/decrease in wet/dry spell but not significantly, respectively. The extreme river flow will be less attenuated and more variable in terms of magnitude, and more irregular in terms of seasonal occurrence than at present. Low flows are projected to increase most prominently for lowland sites, due to the combined effects of projected decreases in Belg and Bega precipitation, and projected increases in evapotranspiration that will reduce residual soil moisture in Bega and Belg seasons.


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