Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins

Vetter, Tobias; Reinhardt, Julia; Flörke, Martina; Griensven, Ann van; Hattermann, Fred F.; Huang, Shaochun; Koch, Hagen; Pechlivanidis, Ilias; Plötner, Stefan; Seidou, Ousmane; Su, Buda; Vervoort, W.; Krysanova, Valentina

doi:10.1007/s10584-016-1794-y

Cited by 223 publications

(144 citation statements)

References 36 publications

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“…Additionally, the current study simulated the hydrological variables via a single hydrological model, and a study conducted by Vetter et al . () noted that the uncertainty arising from the multiple hydrological models was relatively less. In contrast, Bastola et al .…”

Section: Discussionmentioning

confidence: 99%

Understanding the cascade of GCM and downscaling uncertainties in hydro‐climatic projections over India

Sharma

Hari

Chhabra

et al. 2017

Intl Journal of Climatology

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India is a major agrarian country strongly impacted by spatio‐temporal variations in the Indian monsoon. The impact assessment is usually accomplished by implementing projections from general circulation models (GCMs). Unfortunately, these projections cannot capture the dynamicity of the monsoon and require either statistical (SD) or dynamical (DD) downscaling of the GCM projections to a finer resolution. Both downscaling techniques can capture the spatio‐temporal variation in climatic variables but are marred by uncertainty in the projections resulting from the choice of the GCM and downscaling method, which affects climate change adaptations. Here, we assessed uncertainties in the projections of hydro‐climatic variables over India by considering multiple downscaling techniques, multiple GCMs, and their combined effects (referred as the total uncertainty). Multiple hydrological variables were simulated by implementing the variable infiltration capacity model that considered outputs from DD (derived by the coordinated regional climate downscaling experiment, CORDEX) and SD forced with multiple GCM simulations. Our results showed that the SD projections captured the observed spatio‐temporal variability of hydro‐climatic variables more efficiently than the DD projections. Importantly, contribution from the downscaled projections to the total uncertainty was significantly smaller compared to the inter‐GCM uncertainty. We believe uncertainty analysis is an important component of good scientific practice; however, several researchers appear to be rather reluctant to embrace the concept of uncertainty in making projections, predictions, and forecasting. It remains a common practice to show climate change exercises to decision‐makers/stakeholders, without uncertainty bounds. Here, a successful attempt was made to identify the key sources of uncertainty and adequately bracket the uncertainty, indicating a requirement of the code of practice to provide formal guidance, particularly for climate‐change impact assessments. This consequently emphasized the importance of follow‐up research to understand the inter‐GCM uncertainty, which has a significant impact on sustainable agriculture and water resources management in India.

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Section: Discussionmentioning

confidence: 99%

Understanding the cascade of GCM and downscaling uncertainties in hydro‐climatic projections over India

Sharma

Hari

Chhabra

et al. 2017

Intl Journal of Climatology

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“…We used only one hydrological model, which is also a source of uncertainty. However, variation in climate signals between GCMs and emissions scenarios, particularly precipitation projections, may be a larger source of uncertainty than the choice of hydrology model (Thompson et al, 2014;Vetter et al, 2016).…”

Section: Sources Of Uncertaintymentioning

confidence: 99%

Simulated hydrologic response to projected changes in precipitation and temperature in the Congo River basin

Aloysius

Saiers

2017

Hydrol. Earth Syst. Sci.

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Abstract. Despite their global significance, the impacts of climate change on water resources and associated ecosystem services in the Congo River basin (CRB) have been understudied. Of particular need for decision makers is the availability of spatial and temporal variability of runoff projections. Here, with the aid of a spatially explicit hydrological model forced with precipitation and temperature projections from 25 global climate models (GCMs) under two greenhouse gas emission scenarios, we explore the variability in modeled runoff in the near future (2016-2035) and mid-century (2046-2065). We find that total runoff from the CRB is projected to increase by 5 % [−9 %; 20 %] (mean -min and max -across model ensembles) over the next two decades and by 7 % [−12 %; 24 %] by mid-century. Projected changes in runoff from subwatersheds distributed within the CRB vary in magnitude and sign. Over the equatorial region and in parts of northern and southwestern CRB, most models project an overall increase in precipitation and, subsequently, runoff. A simulated decrease in precipitation leads to a decline in runoff from headwater regions located in the northeastern and southeastern CRB. Climate model selection plays an important role in future projections for both magnitude and direction of change. The multimodel ensemble approach reveals that precipitation and runoff changes under business-as-usual and avoided greenhouse gas emission scenarios (RCP8.5 vs. RCP4.5) are relatively similar in the near term but deviate in the midterm, which underscores the need for rapid action on climate change adaptation. Our assessment demonstrates the need to include uncertainties in climate model and emission scenario selection during decision-making processes related to climate change mitigation and adaptation.

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“…As a consequence, several studies have shown the impacts of future climate change on freshwater budgets [5,[33][34][35][36], streamflow [2,6,7,37,38], and hydrological extremes [6,[8][9][10]39,40] at large-scale continental watersheds. In small-scale Pacific island watersheds, such as in Hawaii, a few studies [3,4,41] have also assessed the impact of climate change on water budgets but focused at monthly and yearly mean values.…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Change on Daily Streamflow and Its Extreme Values in Pacific Island Watersheds

2018

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Abstract:The integration of hydrology and climate is important for understanding the present and future impact of climate on streamflow, which may cause frequent flooding, droughts, and shortage of water supply. In view of this, we assessed the impact of climate change on daily streamflow duration curves as well as extreme peak and low flow values. The objectives were to assess how climate change impacts watershed-wide streamflow and its extreme values and to provide an overview of the impacts of different climate change scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5) on streamflow and hydrological extremes when compared with the baseline values. We used the Soil and Water Assessment Tool (SWAT) model for daily streamflow and its extreme value modeling of two watersheds located on the Island of Oahu (Hawaii). Following successful calibration and validation of SWAT at three USGS flow gauging stations, we simulated the impact of climate change by the 2050s (2041-2070) and the 2080s (2071-2100). We used climate change perturbation factors and applied the factors to the historical time series data of 1980-2014. SWAT adequately reproduced observed daily streamflow with Nash-Sutcliffe Efficiency (NSE) values of greater than 0.5 and bracketed >80% of observed streamflow data at 95% model prediction uncertainty at all flow gauging stations, indicating the applicability of the model for future daily streamflow prediction. We found that while the considered climate change scenarios generally show considerable negative impacts on daily streamflow and its extreme values, the extreme peak flows are expected to increase by as much as 22% especially under the RCP 8.5 scenario. However, a consistent decrease in extreme low flows by as much as 60% compared to the baseline values is projected. Larger negative changes of low flows are expected in the upstream part of the watersheds where higher groundwater contributions are expected. Consequently, severe problems, such as frequent hydrological droughts (groundwater scarcity), reduction in agricultural crop productivity, and increase in drinking water demand, are significantly expected on Oahu. Furthermore, the extreme values are more sensitive to rainfall change in comparison to temperature and solar radiation changes. Overall, findings generally indicated that climate change impacts will be amplified by the end of this century and may cause earlier occurrence of hydrological droughts when compared to the current hydrological regime, suggesting water resources managers, ecosystem conservationists, and ecologists to implement mitigation measures to climate change in Hawaii and similar Islands.

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Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins

Cited by 223 publications

References 36 publications

Understanding the cascade of GCM and downscaling uncertainties in hydro‐climatic projections over India

Understanding the cascade of GCM and downscaling uncertainties in hydro‐climatic projections over India

Simulated hydrologic response to projected changes in precipitation and temperature in the Congo River basin

Impact of Climate Change on Daily Streamflow and Its Extreme Values in Pacific Island Watersheds

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