scholarly journals Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures

2014 ◽  
Vol 18 (6) ◽  
pp. 2033-2047 ◽  
Author(s):  
G. Seiller ◽  
F. Anctil
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Variability ◽  
Hydrological Model ◽  
Potential Evapotranspiration ◽  
Hydrological Models ◽  
Natural Climate Variability ◽  
Natural Climate ◽  
Model Structures ◽  
Impacts Of Climate Change

Abstract. Diagnosing the impacts of climate change on water resources is a difficult task pertaining to the uncertainties arising from the different modelling steps. Lumped hydrological model structures contribute to this uncertainty as well as the natural climate variability, illustrated by several members from the same Global Circulation Model. In this paper, the hydroclimatic modelling chain consists of twenty-four potential evapotranspiration formulations, twenty lumped conceptual hydrological models, and seven snowmelt modules. These structures are applied on a natural Canadian sub-catchment to address related uncertainties and compare them to the natural internal variability of simulated climate system as depicted by five climatic members. Uncertainty in simulated streamflow under current and projected climates is assessed. They rely on interannual hydrographs and hydrological indicators analysis. Results show that natural climate variability is the major source of uncertainty, followed by potential evapotranspiration formulations and hydrological models. The selected snowmelt modules, however, do not contribute much to the uncertainty. The analysis also illustrates that the streamflow simulation over the current climate period is already conditioned by the tools' selection. This uncertainty is propagated to reference simulations and future projections, amplified by climatic members. These findings demonstrate the importance of opting for several climatic members to encompass the important uncertainty related to the climate natural variability, but also of selecting multiple modelling tools to provide a trustworthy diagnosis of the impacts of climate change on water resources.

scholarly journals Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures

2013 ◽  
Vol 10 (11) ◽  
pp. 14189-14227 ◽  
Author(s):  
G. Seiller ◽  
F. Anctil
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Hydrological Model ◽  
Potential Evapotranspiration ◽  
Natural Variability ◽  
Hydrological Models ◽  
Natural Climate Variability ◽  
Natural Climate ◽  
Model Structures ◽  
Impacts Of Climate Change

Abstract. Diagnosing the impacts of climate change on water resources is a difficult task pertaining to the uncertainties arising from the different modeling steps. Lumped hydrological model structures contribute to this uncertainty as well as the natural climate variability, illustrated by several members from the same Global Circulation Model. In this paper, the hydroclimatic modeling chain consist of twenty-four potential evapotranspiration formulations, twenty lumped conceptual hydrological models, and seven snowmelt modules. These structures are applied on a natural Canadian sub-catchment to address related uncertainties and compare them to the natural variability as depicted by five climatic members. Uncertainties are commented on the observation period and on simulated and projected climates. They rely on interannual hydrographs and hydrological indicators analysis. Results show that the natural climate variability is the major source of uncertainty, followed by the potential evapotranspiration formulations and hydrological models. The selected snowmelt modules, however, do not contribute much to the uncertainty. The analysis also illustrates that the streamflow simulation over the current climate period is already conditioned by tools' selection, propagating this uncertainty on reference and future projection, while climatic members add over it. These findings demonstrate the importance of opting for several climatic members to encompass the important uncertainty related to the climate natural variability, but also of selecting multiple modeling tools to provide a trustworthy diagnosis of the impacts of climate change on water resources.

scholarly journals Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments

2018 ◽  
Vol 19 (1) ◽  
pp. 27-46 ◽  
Author(s):  
Magali Troin ◽  
Richard Arsenault ◽  
Jean-Luc Martel ◽  
François Brissette
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Substantial Contribution ◽  
Climate Change Signal ◽  
Natural Climate Variability ◽  
Degree Day ◽  
Natural Climate

Abstract Projected climate change effects on hydrology are investigated for the 2041–60 horizon under the A2 emission scenarios using a multimodel approach over two snowmelt-dominated catchments in Canada. An ensemble of 105 members was obtained by combining seven snow models (SMs), five potential evapotranspiration (PET) methods, and three hydrological model (HM) structures. The study was performed using high-resolution simulations from the Canadian Regional Climate Model (CRCM–15 km) driven by two members of the third-generation Canadian Coupled Global Climate Model (CGCM3). This study aims to compare various combinations of SM–PET–HM in terms of their ability to simulate streamflows under the current climate and to evaluate how they affect the assessment of the climate change–induced hydrological impacts at the catchment scale. The variability of streamflow response caused by the use of different SMs (degree-day versus degree-day/energy balance), PET methods (temperature-based versus radiation-based methods), and HM structures is evaluated, as well as the uncertainty due to the natural climate variability (CRCM intermember variability). The hydroclimatic simulations cover 1961–90 in the present period and 2041–60 in the future period. The ensemble spread of the climate change signal on streamflow is large and varies with catchments. Using the variance decomposition on three hydrologic indicators, the HM structure was found to make the most substantial contribution to uncertainty, followed by the choice of the PET methods or natural climate variability, depending on the hydrologic indicator and the catchment. Snow models played a minor, almost negligible role in the assessment of the climate change impacts on streamflow for the study catchments.

scholarly journals Natural climate variability is an important aspect of future projections of snow water resources and rain-on-snow events

2021 ◽  
Author(s):  
Michael Schirmer ◽  
Adam Winstral ◽  
Tobias Jonas ◽  
Paolo Burlando ◽  
Nadav Peleg
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Variability ◽  
Weather Generator ◽  
Climate Change Signal ◽  
Natural Climate Variability ◽  
Sources Of Uncertainty ◽  
Snow Water ◽  
Snow Model ◽  
Natural Climate

Abstract. Climate projection studies of future changes in snow conditions and resulting rain-on-snow (ROS) flood events are subject to large uncertainties. Typically, emission scenario uncertainties and climate model uncertainties are included. This is the first study on this topic to also include quantification of natural climate variability, which is the dominant uncertainty for precipitation at local scales with large implications for e.g. runoff projections. To quantify natural climate variability, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 × 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The climate change signal for snow water resources stands out as early as mid-century from the noise originating from the three sources of uncertainty investigated, namely uncertainty in emission scenarios, uncertainty in climate models, and natural climate variability. For ROS events, a climate change signal toward more frequent and intense events was found for an RCP 8.5 scenario at high elevations at the end of the century, consistently with other studies. However, for ROS events with a substantial contribution of snowmelt to runoff (>20 %), the climate change signal was largely masked by sources of uncertainty. Only those ROS events where snowmelt does not play an important role during the event will occur considerably more frequently in the future, while ROS events with substantial snowmelt contribution will mainly occur earlier in the year but not more frequently. There are two reasons for this: first, although it will rain more frequently in midwinter, the snowpack will typically still be too cold and dry and thus cannot contribute significantly to runoff; second, the very rapid decline in snowpack toward early summer, when conditions typically prevail for substantial contributions from snowmelt, will result in a large decrease in ROS events at that time of the year. Finally, natural climate variability is the primary source of uncertainty in projections of ROS metrics until the end of the century, contributing more than 70 % of the total uncertainty. These results imply that both the inclusion of natural climate variability and the use of a snow model, which includes a physically-based processes representation of water retention, are important for ROS projections at the local scale.

scholarly journals Recent natural variability in global warming weakened phenological mismatch and selection on seasonal timing in great tits ( Parus major )

2021 ◽  
Vol 288 (1963) ◽  
Author(s):  
Marcel E. Visser ◽  
Melanie Lindner ◽  
Phillip Gienapp ◽  
Matthew C. Long ◽  
Stephanie Jenouvrier
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Variability ◽  
Parus Major ◽  
Great Tit ◽  
Trophic Levels ◽  
Natural Climate Variability ◽  
Seasonal Timing ◽  
Phenological Mismatch ◽  
Natural Climate

Climate change has led to phenological shifts in many species, but with large variation in magnitude among species and trophic levels. The poster child example of the resulting phenological mismatches between the phenology of predators and their prey is the great tit ( Parus major ), where this mismatch led to directional selection for earlier seasonal breeding. Natural climate variability can obscure the impacts of climate change over certain periods, weakening phenological mismatching and selection. Here, we show that selection on seasonal timing indeed weakened significantly over the past two decades as increases in late spring temperatures have slowed down. Consequently, there has been no further advancement in the date of peak caterpillar food abundance, while great tit phenology has continued to advance, thereby weakening the phenological mismatch. We thus show that the relationships between temperature, phenologies of prey and predator, and selection on predator phenology are robust, also in times of a slowdown of warming. Using projected temperatures from a large ensemble of climate simulations that take natural climate variability into account, we show that prey phenology is again projected to advance faster than great tit phenology in the coming decades, and therefore that long-term global warming will intensify phenological mismatches.

scholarly journals A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

2010 ◽  
Vol 7 (5) ◽  
pp. 7191-7229 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Model ◽  
Annual Runoff ◽  
Structural Uncertainty ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Monthly Runoff ◽  
Global Mean ◽  
Impacts Of Climate Change

Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.

scholarly journals An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

2013 ◽  
Vol 17 (2) ◽  
pp. 565-578 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Hydrological Model ◽  
Global Climate ◽  
Regional Climate ◽  
Structural Complexity ◽  
Global Climate Models ◽  
Hydrological Models ◽  
The Impact

Abstract. Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971–2000) and a future (2041–2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model.

Relative impacts of human-induced climate change and natural climate variability

Nature ◽  
10.1038/17789 ◽  
1999 ◽  
Vol 397 (6721) ◽  
pp. 688-691 ◽  
Author(s):  
Mike Hulme ◽  
Elaine M. Barrow ◽  
Nigel W. Arnell ◽  
Paula A. Harrison ◽  
Timothy C. Johns ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Natural Climate Variability ◽  
Natural Climate

scholarly journals A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

2011 ◽  
Vol 15 (1) ◽  
pp. 279-294 ◽  
Author(s):  
S. N. Gosling ◽  
R. G. Taylor ◽  
N. W. Arnell ◽  
M. C. Todd
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Climate Model ◽  
Annual Runoff ◽  
Structural Uncertainty ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Monthly Runoff ◽  
Global Mean ◽  
Impacts Of Climate Change

Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM (Mac-PDM.09 here) as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.

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