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Abstract Having a realistic estimation of snow cover by conceptual hydrological models continues to challenge hydrologists. The calibration of the free model parameters is an unavoidable step and the uncertainties resulting from the use of this optimal set remains a source of concern, especially in forecasting applications and climate changes impact assessments. This study seeks to improve the calibration of the conceptual hydrological model GR4J coupled with the Cemaneige snow model, in order to obtain a more realistic simulation of the snow water equivalent (SWE) and to reduce the uncertainty of the free parameters. The performance of the two models was tested over twelve snow-dominated basins in southern Quebec, Canada. Four calibration strategies were adopted and compared. In the first two strategies, the parameters were calibrated against observed streamflow alone using a local and a global algorithm. In the third and fourth strategies the calibration of snow and hydrological parameters was performed against observed streamflow and snow water equivalent (SWE) measured at snow course transects, first separately, and then with a multiobjective approach. An ensemble of equifinal parameters was used to compare the capacity of the global and multiobjective algorithms to improve the parameters identifiability and to assess the impact of parameter equifinality on the temperature sensitivity of spring peak streamflow. The large number of equifinal parameters found during calibration underscores the importance of structural non-identifiability of the coupled GR4J-Cemaneige model. The inclusion of snow observations within a multiobjective calibration improved the simulation of SWE, the identifiability of the parameters and their correlation with basins characteristics. Parameter equifinality caused a small but non negligible uncertainty in the simulated response of spring peak flow to warming temperatures. Parameter equifinality should be considered in climate impact studies in snow-dominated basins where poorly constrained snow parameters can affect the temperature sensitivity of streamflow.
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Abstract. In the semiarid Andes of Chile, farmers and industry in the cordillera lowlands depend on water from snowmelt, as annual rainfall is insufficient to meet their needs. Despite the importance of snow cover for water resources in this region, understanding of snow depth distribution and snow mass balance is limited. Whilst the effect of wind on snow cover pattern distribution has been assessed, the relative importance of melt versus sublimation has only been studied at the point scale over one catchment. Analyzing relative ablation rates and evaluating uncertainties are critical for understanding snow depth sensitivity to variations in climate and simulating the evolution of the snowpack over a larger area and over time. Using a distributed snowpack model (SnowModel), this study aims to simulate melt and sublimation rates over the instrumented watershed of La Laguna (513 km2, 3150–5630 m a.s.l., 30∘ S, 70∘ W), during two hydrologically contrasting years (i.e., dry vs. wet). The model is calibrated and forced with meteorological data from nine Automatic Weather Stations (AWSs) located in the watershed and atmospheric simulation outputs from the Weather Research and Forecasting (WRF) model. Results of simulations indicate first a large uncertainty in sublimation-to-melt ratios depending on the forcing as the WRF data have a cold bias and overestimate precipitation in this region. These input differences cause a doubling of the sublimation-to-melt ratio using WRF forcing inputs compared to AWS. Therefore, the use of WRF model output in such environments must be carefully adjusted so as to reduce errors caused by inherent bias in the model data. For both input datasets, the simulations indicate a similar sublimation fraction for both study years, but ratios of sublimation to melt vary with elevation as melt rates decrease with elevation due to decreasing temperatures. Finally results indicate that snow persistence during the spring period decreases the ratio of sublimation due to higher melt rates.
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This study examines the hydrological sensitivity of an agroforested catchment to changes in temperature and precipitation. A physically based hydrological model was created using the Cold Regions Hydrological Modelling platform to simulate the hydrological processes over 23 years in the Acadie River Catchment in southern Quebec. The observed air temperature and precipitation were perturbed linearly based on existing climate change projections, with warming of up to 8 °C and an increase in total precipitation up to 20%. The results show that warming causes a decrease in blowing snow transport and sublimation losses from blowing snow, canopy-intercepted snowfall and the snowpack. Decreasing blowing snow transport leads to reduced spatial variability in peak snow water equivalent (SWE) and a more synchronized snow cover depletion across the catchment. A 20% increase in precipitation is not sufficient to counteract the decline in annual peak SWE caused by a 1 °C warming. On the other hand, peak spring streamflow increases by 7% and occurs 20 days earlier with a 1 °C warming and a 20% increase in precipitation. However, when warming exceeds 1.5 °C, the catchment becomes more rainfall dominated and the peak flow and its timing follows the rainfall rather than snowmelt regime. Results from this study can be used for sustainable farming development and planning in regions with hydroclimatic characteristics similar to the Acadie River Catchment, where climate change may have a significant impact on the dominating hydrological processes.
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Excluding Antarctica and Greenland, 3.8% of the world’s glacier area is concentrated in Chile. The country has been strongly affected by the mega drought, which affects the south-central area and has produced an increase in dependence on water resources from snow and glacier melting in dry periods. Recent climate change has led to an elevation of the zero-degree isotherm, a decrease in solid-state precipitation amounts and an accelerated loss of glacier and snow storage in the Chilean Andes. This situation calls for a better understanding of future water discharge in Andean headwater catchments in order to improve water resources management in glacier-fed populated areas. The present study uses hydrological modeling to characterize the hydrological processes occurring in a glacio-nival watershed of the central Andes and to examine the impact of different climate change scenarios on discharge. The study site is the upper sub-watershed of the Tinguiririca River (area: 141 km2), of which nearly 20% is covered by Universidad Glacier. The semi-distributed Snowmelt Runoff Model + Glacier (SRM+G) was forced with local meteorological data to simulate catchment runoff. The model was calibrated on even years and validated on odd years during the 2008–2014 period and found to correctly reproduce daily runoff. The model was then forced with downscaled ensemble projected precipitation and temperature series under the RCP 4.5 and RCP 8.5 scenarios, and the glacier adjusted using a volume-area scaling relationship. The results obtained for 2050 indicate a decrease in mean annual discharge (MAD) of 18.1% for the lowest emission scenario and 43.3% for the most pessimistic emission scenario, while for 2100 the MAD decreases by 31.4 and 54.2%, respectively, for each emission scenario. Results show that decreasing precipitation lead to reduced rainfall and snowmelt contributions to discharge. Glacier melt thus partly buffers the drying climate trend, but our results show that the peak water occurs near 2040, after which glacier depletion leads to reducing discharge, threatening the long-term water resource availability in this region.
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Cold region hydrology is conditioned by distinct cryospheric and hydrological processes. While snowmelt is the main contributor to both surface and subsurface flows, seasonally frozen soil also influences the partition of meltwater and rain between these flows. Cold regions of the Northern Hemisphere midlatitudes have been shown to be sensitive to climate change. Assessing the impacts of climate change on the hydrology of this region is therefore crucial, as it supports a significant amount of population relying on hydrological services and subjected to changing hydrological risks. We present an exhaustive review of the literature on historical and projected future changes on cold region hydrology in response to climate change. Changes in snow, soil, and streamflow key metrics were investigated and summarized at the hemispheric scale, down to the basin scale. We found substantial evidence of both historical and projected changes in the reviewed hydrological metrics. These metrics were shown to display different sensitivities to climate change, depending on the cold season temperature regime of a given region. Given the historical and projected future warming during the 21st century, the most drastic changes were found to be occurring over regions with near-freezing air temperatures. Colder regions, on the other hand, were found to be comparatively less sensitive to climate change. The complex interactions between the snow and soil metrics resulted in either colder or warmer soils, which led to increasing or decreasing frost depths, influencing the partitioning rates between the surface and subsurface flows. The most consistent and salient hydrological responses to both historical and projected climate change were an earlier occurrence of snowmelt floods, an overall increase in water availability and streamflow during winter, and a decrease in water availability and streamflow during the warm season, which calls for renewed assessments of existing water supply and flood risk management strategies.