Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan‐Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 year ...period beginning in January and ending in December of the following year. This historic event coincided with below‐average air temperatures and extensive winter ice cover across the Great Lakes. It also brought an end to a 15 year period of persistently below‐average water levels on Lakes Superior and Michigan‐Huron that included several months of record‐low water levels. To differentiate hydrological drivers behind the recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferring historical estimates of the major components of each lake's water budget. Our results indicate that, in 2013, the water level rise on Lake Superior was driven by increased spring runoff and over‐lake precipitation. In 2014, reduced over‐lake evaporation played a more significant role in Lake Superior's water level rise. The water level rise on Lake Michigan‐Huron in 2013 was also due to above‐average spring runoff and persistent over‐lake precipitation, while in 2014, it was due to a rare combination of below‐average evaporation, above‐average runoff and precipitation, and very high inflow rates from Lake Superior through the St. Marys River. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes, and to Earth's other large freshwater basins as well.
Key Points
Between January 2013 and December 2014, the two largest lakes on Earth rose at a record‐setting rate
We developed a Bayesian MCMC routine for inferring estimates of the water budget for this period
The cold 2013–2014 winter contributed to reduced evaporation rates and rising water levels
Intensification of the global hydrological cycle and increase in precipitation for some regions around the world, including the northern mid- to high latitudes, is expected in a changing climate. ...Changes in the amount of seasonal precipitation and the intensity and frequency of extreme precipitation events directly affect the magnitude of seasonal streamflows and the timing and severity of floods and droughts. In this study, the Canadian Regional Climate Model (CRCM) projected changes to streamflow characteristics (i.e., hydrologic regime, mean annual streamflows, and the timing, frequency, and magnitude of extreme flows—low and high) over selected basins in western Canada and assessment of errors associated with these characteristics in the current climate are presented. An ensemble of five current (1961–90) and five future (2041–70) simulations, corresponding to the Special Report on Emissions Scenarios (SRES) A2 scenario, are used in the assessment of projected changes; the ensemble of simulations allows better quantification of uncertainty in projected changes. Results of the study suggest an increase in the magnitude of winter streamflows and an earlier snowmelt peak for the northern basins. In addition, study of selected return levels of extreme flows suggest important changes to the timing, frequency, and magnitude of both low and high flows, with significant increases in 10-yr 15-day winter and fall low flows and 1-day high flows, for all the high-latitude west Canadian basins. The level of confidence in projected changes to mean annual streamflows is relatively higher compared to that for extreme flows for most of the basins studied.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Model intercomparison studies are carried out to test and compare the simulated outputs of various model setups over the same study domain. The Great Lakes region is such a domain of high public ...interest as it not only resembles a challenging region to model with its transboundary location, strong lake effects, and regions of strong human impact but is also one of the most densely populated areas in the USA and Canada. This study brought together a wide range of researchers setting up their models of choice in a highly standardized experimental setup using the same geophysical datasets, forcings, common routing product, and locations of performance evaluation across the 1×106 km2 study domain. The study comprises 13 models covering a wide range of model types from machine-learning-based, basin-wise, subbasin-based, and gridded models that are either locally or globally calibrated or calibrated for one of each of the six predefined regions of the watershed. Unlike most hydrologically focused model intercomparisons, this study not only compares models regarding their capability to simulate streamflow (Q) but also evaluates the quality of simulated actual evapotranspiration (AET), surface soil moisture (SSM), and snow water equivalent (SWE). The latter three outputs are compared against gridded reference datasets. The comparisons are performed in two ways – either by aggregating model outputs and the reference to basin level or by regridding all model outputs to the reference grid and comparing the model simulations at each grid-cell. The main results of this study are as follows:
The comparison of models regarding streamflow reveals the superior quality of the machine-learning-based model in the performance of all experiments; even for the most challenging spatiotemporal validation, the machine learning (ML) model outperforms any other physically based model. While the locally calibrated models lead to good performance in calibration and temporal validation (even outperforming several regionally calibrated models), they lose performance when they are transferred to locations that the model has not been calibrated on. This is likely to be improved with more advanced strategies to transfer these models in space. The regionally calibrated models – while losing less performance in spatial and spatiotemporal validation than locally calibrated models – exhibit low performances in highly regulated and urban areas and agricultural regions in the USA. Comparisons of additional model outputs (AET, SSM, and SWE) against gridded reference datasets show that aggregating model outputs and the reference dataset to the basin scale can lead to different conclusions than a comparison at the native grid scale. The latter is deemed preferable, especially for variables with large spatial variability such as SWE. A multi-objective-based analysis of the model performances across all variables (Q, AET, SSM, and SWE) reveals overall well-performing locally calibrated models (i.e., HYMOD2-lumped) and regionally calibrated models (i.e., MESH-SVS-Raven and GEM-Hydro-Watroute) due to varying reasons. The machine-learning-based model was not included here as it is not set up to simulate AET, SSM, and SWE. All basin-aggregated model outputs and observations for the model variables evaluated in this study are available on an interactive website that enables users to visualize results and download the data and model outputs.
The Canadian Regional Climate Model has been used to estimate surface water balance over the Mackenzie River basin during the water year 1998–99 in support of the Canadian Global Energy and Water ...Cycle Experiment (GEWEX) Enhanced Study (CAGES). The model makes use of a developmental third-generation physics parameterization package from the Canadian Centre for Climate Modelling and Analysis GCM, as well as a high-resolution land surface dataset. The surface water balance is simulated reasonably well, though Mackenzie basin annual mean daily maximum and minimum temperatures were both colder than observed by 1.7°C. The cold bias contributed to a longer snow-covered season and larger peak snow water equivalent than was observed, though snow accumulated realistically compared with two independently observed estimates after 1 November. Mackenzie basin annual precipitation was simulated as 496 mm, about 9% larger than observed, andP – Ewas 225 mm. Net soil moisture change during this water year was found to be −26 mm, though because of a spinup problem in the Liard subbasin, the value is more likely closer to −14 mm.
The simulation was used to drive offline two different hydrologic models in order to simulate streamflow hydrographs at key stations within the Mackenzie basin. Results suggest that when subgrid-scale routing and interflow are included, streamflow timing is improved. This study highlights the importance of orographic processes and land surface initialization for climate modeling within the Mackenzie GEWEX Study.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC) over the last decade. More precisely, the aim is to ...develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow) land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE) but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE √ (Nash–Sutcliffe criterion computed on the square root of the flows) is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE √ in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the complexity and computation burden of the calibration procedure. This work contributes to the Great Lakes Runoff Inter-comparison Project for Lake Ontario (GRIP-O), which aims at improving Lake Ontario basin runoff simulations by comparing different models using the same input forcings. The main outcome of this study consists in a new generalizable methodology for implementing a distributed hydrologic model with a high computation cost in an efficient and reliable manner, over a large area with ungauged portions, using global calibration and a unit hydrograph to replace the routing component.
Second generation land surface schemes are the subject of much development activity among atmospheric modellers. This work is aimed at, among other things, improving the representation of the soil ...water balance in order to simulate, more properly, exchanges with the atmosphere and to permit the use of model output to generate streamflow for model validation. The Canadian development program is centred on CLASS, the Canadian Land Surface Scheme, developed at Environment Canada. This paper focuses on the improvement of hydrology in CLASS. This was accomplished by designing a two-way interface to WATFLOOD, a distributed hydrologic model developed at the University of Waterloo. The two models share many features, which facilitated the coupling procedure.
The interface retains the three-layer vertical moisture budget representation in CLASS but adds three horizontal runoff possibilities. Runoff from the surface water follows Manning's equation for overland flow. Interflow is generated from the near-surface soil layer using a parametrization of Richard's equation and base flow is produced by Darcian flow from the bottom of layer 3. An approximation of the internal topography of grid elements is used to supply horizontal gradients for the runoff components.
Tests are in progress in four Canadian study areas. Initial results are presented for the summer of 1993 for the Saugeen River in southwestern Ontario. The new scheme produces realistic hydrographs, whereas the old scheme did not. Bare ground evaporation is reduced by about 17% as a consequence of reduced water availability in layer 1. Evapotranspiration is not affected because the rooting depth extends into layer 3, in which soil moisture does not change appreciably with the new scheme. These results suggest that the new scheme improves the representation of streamflow in WATFLOOD/CLASS and of the soil moisture budget in CLASS. Work is in progress to validate this result over basins, such as the BOREAS study watersheds, where both runoff and evapotranspiration measurements are available.
A particularly elusive science objective for the Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS) has been to close the atmospheric moisture budget and rationalize it against ...the surface water budget at annual or even monthly timescales. The task, while not difficult in principle, is complicated by two factors. First is the importance of basin snow-cover, soil and water-body storage in the surface water budget. Month-to-month changes in these components are frequently greater than the atmospheric flux terms, for example, during spring snowmelt. Furthermore, there is approximately a six-week lag before local changes are evident in the discharge at the mouth of the basin. Second, the coarse resolution of all of the supporting data may add significant systematic errors. For example, the two radiosonde soundings per day available to the project are unlikely to account adequately for all the moisture generated locally through evapotranspiration during the summer convective season.
This analysis will directly address these two main issues by applying hydrologic and atmospheric computations to assess the storage question, and by using additional soundings at a single site to sample the diurnal signature in atmospheric moisture caused by evapotranspiration. Resulting modifications to the atmospheric moisture and surface water budgets then allow near closure of the MAGS monthly water budget within acceptable error limits.
This paper presents the results of a modeling study that is part of a collaborative distributed precipitation–snowmelt–runoff modeling study initiated by B.C. Hydro (the electric utilities company in ...British Columbia). Meteorological data were generated for a 23 year period by a high-resolution boundary layer model using a grid size of
2
min
latitude×4
min
longitude
(3.7×4.7
km)
. The distributed daily precipitation and temperature–time sequences generated by this model were used as input to the WATFLOOD/SPL hydrological model, resulting in computed streamflows that were compared to measured streamflow at 32 flow gauging sites and four reservoirs. In this way, through a number of calibration and validation runs, the whole sequence of generating the meteorological data and their subsequent use to drive the hydrological model was tested. The study shows the importance of using both models in combination. Although the boundary layer model used the observed meteorological data to the fullest extent, the hydrologic simulations revealed a significant north–south trend in the precipitation error field. This resulted in streamflow errors as high as 60%. A reanalysis of the fields using the modeled streamflow reduced the error substantially. With the exception of a few streamflow stations, the computed flows matched the observed streamflows and reservoir inflows very well.
The Canadian Regional Climate Model has been used to estimate surface water balance over the Mackenzie River basin during the water year 1998-99 in support of the Canadian Global Energy and Water ...Cycle Experiment (GEWEX) Enhanced Study (CAGES). The model makes use of a developmental third-generation physics parameterization package from the Canadian Centre for Climate Modelling and Analysis GCM, as well as a high-resolution land surface dataset. The surface water balance is simulated reasonably well, though Mackenzie basin annual mean daily maximum and minimum temperatures were both colder than observed by 1.7 degree C. The cold bias contributed to a longer snow-covered season and larger peak snow water equivalent than was observed, though snow accumulated realistically compared with two independently observed estimates after 1 November. Mackenzie basin annual precipitation was simulated as 496 mm, about 9% larger than observed, and P - E was 225 mm. Net soil moisture change during this water year was found to be -26 mm, though because of a spinup problem in the Liard subbasin, the value is more likely closer to -14 mm. theta he simulation was used to drive offline two different hydrologic models in order to simulate streamflow hydrographs at key stations within the Mackenzie basin. Results suggest that when subgrid-scale routing and interflow are included, streamflow timing is improved. This study highlights the importance of orographic processes and land surface initialization for climate modeling within the Mackenzie GEWEX Study.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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