scholarly journals High-resolution hydrometeorological modelling of the June 2013 flood in southern Alberta, Canada

2019 ◽  
Author(s):  
Vincent Vionnet ◽  
Vincent Fortin ◽  
Etienne Gaborit ◽  
Guy Roy ◽  
Maria Abrahamowicz ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Peak Flow ◽  
Extreme Event ◽  
Accurate Estimation ◽  
Western Canada ◽  
Hydrological Forecasting ◽  
Southern Alberta ◽  
Precipitation Estimation ◽  
Snow Conditions ◽  
High Elevations

Abstract. From June 19 to June 22, 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia. The complexity of the topography in the mountain headwaters, presence of snow at high elevations and other factors challenged hydrological forecasting of this extreme event. In this study, the ability of the Global Environmental Multi-scale hydrological modelling platform (GEM-Hydro), running at a 1-km grid spacing, to simulate hydrometeorological conditions in several Alberta rivers during this event is assessed. Four quantitative precipitation estimation (QPE) products were generated using the Canadian Precipitation Analysis (CaPA) system by varying (i) station density and (ii) horizontal resolutions (10, 2.5 and 1 km) of the GEM precipitation background. CaPA at 2.5 and 1 km including all available stations in the headwaters provided the most accurate estimation of intensity and total amount of precipitation during the flooding event. Using these products to drive GEM-Hydro, it is shown that QPE accuracy dominates the ability to predict flood volumes. Initial snow conditions also represent a large additional source of uncertainty. Default GEM-Hydro simulations starting with almost no snowpack at high-elevations led to a systematic underestimation of flood volume and peak flow. Gridded estimates of snow water equivalent from the Snow Data Assimilation System (SNODAS) were also considered. They led to contrasting abilities to simulate flood discharge volumes and a consistent overestimation in the headwater catchments, illustrating the strong need for a reference snow product in the mountains of Western Canada. Finally, GEM-Hydro did not predict peak flow timing and hydrograph shape well. Model sensitivity tests show that it could be improved by adjusting the Manning coefficients, suggesting the need to revisit the routing parameters. There may be a need to include water management effects on flood hydrographs as well. These results will guide the development of GEM-Hydro as a hydrological forecasting system in Western Canada.

Impact of cultivars and herbicides on weed management in alfalfa

2006 ◽  
Vol 86 (3) ◽  
pp. 875-885 ◽  
Author(s):  
J. R. Moyer ◽  
S. N. Acharya
Keyword(s):  
British Columbia ◽  
Weed Control ◽  
Weed Management ◽  
Forage Quality ◽  
Western Canada ◽  
Downy Brome ◽  
Weed Species ◽  
Standard Type ◽  
Southern Alberta ◽  
Medicago Sativa L

Weeds, especially dandelion (Taraxacum officinale Weber in F.H. Wigg.), tend to infest a forage alfalfa (Medicago sativa L.) stand 2 to 4 yr after establishment. To develop better weed management systems, experiments were conducted at Lethbridge, Alberta, from 1995 to 2002 and Creston, British Columbia, from 1998 to 2001, which included the alfalfa cultivars Beaver (standard type) and AC Blue J (Flemish type) and annual applications of metribuzin and hexazinone. These herbicides are registered for weed control in irrigated alfalfa in Alberta and alfalfa grown for seed. In addition, two sulfonylurea herbicides, metsulfuron and sulfosulfuron, and glyphosate were included. All of the herbicides except glyphosate controlled or suppressed dandelion and mustard family weeds. Metsulfuron at 5 g a.i. ha-1 almost completely controlled dandelion at both locations. However, after metsulfuron application at Lethbridge, dandelion was replaced with an infestation of downy brome, which is unpalatable for cattle. None of the herbicides increased total forage (alfalfa + weed) yield, and in some instances herbicides reduced forage quality by causing a shift from a palatable to an unpalatable weed species. However, it was observed that AC Blue J consistently yielded more than Beaver, and weed biomass was consistently less in the higher-yielding cultivar. AC Blue J was developed primarily for the irrigated area in southern Alberta and for southern British Columbia. Therefore, additional experiments should be conducted to determine which alfalfa cultivars have the greatest ability to compete with weeds in other regions of western Canada. Key words: Alfalfa yield, dandelion, forage quality, weed control

Exploring the use of gpr and satellite-based snow data for snowmelt runoff predictions

2021 ◽  
Author(s):  
Ilaria Clemenzi ◽  
David Gustafsson ◽  
Jie Zhang ◽  
Björn Norell ◽  
Wolf Marchand ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Data Assimilation ◽  
Snow Water Equivalent ◽  
Distribution Model ◽  
Accurate Estimation ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Distribution ◽  
The Impact

<p>Snow in the mountains is the result of the interplay between meteorological conditions, e.g., precipitation, wind and solar radiation, and landscape features, e.g., vegetation and topography. For this reason, it is highly variable in time and space. It represents an important water storage for several sectors of the society including tourism, ecology and hydropower. The estimation of the amount of snow stored in winter and available in the form of snowmelt runoff can be strategic for their sustainability. In the hydropower sector, for example, the occurrence of higher snow and snowmelt runoff volumes at the end of the spring and in the early summer compared to the estimated one can substantially impact reservoir regulation with energy and economical losses. An accurate estimation of the snow volumes and their spatial and temporal distribution is thus essential for spring flood runoff prediction. Despite the increasing effort in the development of new acquisition techniques, the availability of extensive and representative snow and density measurements for snow water equivalent estimations is still limited. Hydrological models in combination with data assimilation of ground or remote sensing observations is a way to overcome these limitations. However, the impact of using different types of snow observations on snowmelt runoff predictions is, little understood. In this study we investigated the potential of assimilating in situ and remote sensing snow observations to improve snow water equivalent estimates and snowmelt runoff predictions. We modelled the seasonal snow water equivalent distribution in the Lake Överuman catchment, Northern Sweden, which is used for hydropower production. Simulations were performed using the semi-distributed hydrological model HYPE for the snow seasons 2017-2020. For this purpose, a snowfall distribution model based on wind-shelter factors was included to represent snow spatial distribution within model units. The units consist of 2.5x2.5 km<sup>2</sup> grid cells, which were further divided into hydrological response units based on elevation, vegetation and aspect. The impact on the estimation of the total catchment mean snow water equivalent and snowmelt runoff volume were evaluated using for data assimilation, gpr-based snow water equivalent data acquired along survey lines in the catchment in the early spring of the four years, snow water equivalent data obtained by a machine learning algorithm and satellite-based fractional snow cover data. Results show that the wind-shelter based snow distribution model was able to represent a similar spatial distribution as the gpr survey lines, when assessed on the catchment level. Deviations in the model performance within and between specific gpr survey lines indicate issues with the spatial distribution of input precipitation, and/or need to include explicit representation of snow drift between model units. The explicit snow distribution model also improved runoff simulations, and the ability of the model to improve forecast through data assimilation.</p>

scholarly journals Estimating snow water equivalent over long mountain transects using snowmobile-mounted ground-penetrating radar

Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. WA183-WA193 ◽  
Author(s):  
W. Steven Holbrook ◽  
Scott N. Miller ◽  
Matthew A. Provart
Keyword(s):  
Ground Penetrating Radar ◽  
Snow Water Equivalent ◽  
Ground Surface ◽  
Snow Accumulation ◽  
Accurate Estimation ◽  
Snow Density ◽  
Snow Stratigraphy ◽  
Flood Estimation ◽  
Snow Water ◽  
Ground Penetrating

The water balance in alpine watersheds is dominated by snowmelt, which provides infiltration, recharges aquifers, controls peak runoff, and is responsible for most of the annual water flow downstream. Accurate estimation of snow water equivalent (SWE) is necessary for runoff and flood estimation, but acquiring enough measurements is challenging due to the variability of snow accumulation, ablation, and redistribution at a range of scales in mountainous terrain. We have developed a method for imaging snow stratigraphy and estimating SWE over large distances from a ground-penetrating radar (GPR) system mounted on a snowmobile. We mounted commercial GPR systems (500 and 800 MHz) to the front of the snowmobile to provide maximum mobility and ensure that measurements were taken on pristine snow. Images showed detailed snow stratigraphy down to the ground surface over snow depths up to at least 8 m, enabling the elucidation of snow accumulation and redistribution processes. We estimated snow density (and thus SWE, assuming no liquid water) by measuring radar velocity of the snowpack through migration focusing analysis. Results from the Medicine Bow Mountains of southeast Wyoming showed that estimates of snow density from GPR ([Formula: see text]) were in good agreement with those from coincident snow cores ([Formula: see text]). Using this method, snow thickness, snow density, and SWE can be measured over large areas solely from rapidly acquired common-offset GPR profiles, without the need for common-midpoint acquisition or snow cores.

scholarly journals Hydro-meteorological characteristics and occurrence probability of extreme flood events in Moroccan High Atlas

2020 ◽  
Vol 11 (S1) ◽  
pp. 310-321 ◽  
Author(s):  
Mohamed El Mehdi Saidi ◽  
Tarik Saouabe ◽  
Abdelhafid El Alaoui El Fels ◽  
El Mahdi El Khalki ◽  
Abdessamad Hadri
Keyword(s):  
Return Period ◽  
Peak Flow ◽  
Extreme Event ◽  
Rare Event ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
High Atlas ◽  
Flood Water ◽  
Extreme Flood ◽  
Water Volumes

Abstract Flood frequency analysis could be a tool to help decision-makers to size hydraulic structures. To this end, this article aims to compare two analysis methods to see how rare an extreme hydrometeorological event is, and what could be its return period. This event caused many deadly floods in southwestern Morocco. It was the result of unusual atmospheric conditions, characterized by a very low atmospheric pressure off the Moroccan coast and the passage of the jet stream further south. Assessment of frequency and return period of this extreme event is performed in a High Atlas watershed (the Ghdat Wadi) using historical floods. We took into account, on the one hand, flood peak flows and, on the other hand, flood water volumes. Statistically, both parameters are better adjusted respectively to Gamma and Log Normal distributions. However, the peak flow approach underestimates the return period of long-duration hydrographs that do not have a high peak flow, like the 2014 event. The latter is indeed better evaluated, as a rare event, by taking into account the flood water volumes. Therefore, this parameter should not be omitted in the calculation of flood probabilities for watershed management and the sizing of flood protection infrastructure.

Foraminiferal response to Albian relative sea-level changes in northwestern and central Alberta, Canada

1999 ◽  
Vol 36 (10) ◽  
pp. 1617-1643 ◽  
Author(s):  
Rebecca A Stritch ◽  
Claudia J Schröder-Adams
Keyword(s):  
Sea Level ◽  
Bottom Water ◽  
Gradual Increase ◽  
Western Canada ◽  
Sea Level Changes ◽  
Relative Sea Level ◽  
Sea Level Fluctuations ◽  
Faunal Assemblages ◽  
Water Oxygen ◽  
Southern Alberta

Albian foraminiferal assemblages from three wells in northwestern (Imperial Spirit River No. 1, 12-20-78-6W6), central (AngloHome C&E Fort Augustus No. 1, 7-29-55-21W4), and southern Alberta (Amoco B1 Youngstown, 6-34-30-8W4) provide the basis to track a fluctuating sea-level history in western Canada. Two global second-order marine cycles (Kiowa - Skull Creek and Greenhorn) were punctuated by higher frequency relative sea-level cycles expressed during the time of the Moosebar-Clearwater, Hulcross, Joli Fou, and Mowry seas. A total of 34 genera and 93 subgeneric taxa are recognized in these Albian-age strata. Foraminiferal abundance and species diversity of the latest Albian Mowry Sea were higher than in the early to middle Albian Moosebar-Clearwater and Hulcross seas. The two earliest paleo-seas were shallow embayments of the Boreal Sea, and relative sea-level fluctuations caused variable marine to brackish conditions expressed in a variety of faunal assemblages. Towards the late Albian, relative sea level rose, deepening the basin and establishing increased marine conditions and more favourable habitats for foraminifera. In the deeper Joli Fou Seaway and Mowry Sea, however, reduced bottom water oxygen through stratification or stagnant circulation caused times of diminished benthic faunas. The Bluesky Formation in northwestern Alberta contains the initial transgression of the early Albian Moosebar-Clearwater Sea and is marked by a sudden faunal increase. In contrast, transgression by the late late Albian Mowry Sea was associated with a gradual increase of foraminiferal faunas. Numerous agglutinated species range throughout the entire Albian, absent only at times of basin shallowing. However, each major marine incursion throughout the Albian introduced new taxa.

scholarly journals Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

2018 ◽  
Vol 22 (2) ◽  
pp. 1593-1614 ◽  
Author(s):  
Florian Hanzer ◽  
Kristian Förster ◽  
Johanna Nemec ◽  
Ulrich Strasser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climate Projections ◽  
Early 21St Century ◽  
Physically Based ◽  
Snow Water ◽  
High Elevations

Abstract. A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios as forcing data, making this – to date – the most detailed study for this region in terms of process representation and range of considered climate projections. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862–3770 m a.s.l.) as well as for seven catchments in the area with varying size (11–165 km2) and glacierization (24–77 %). Results show generally declining snow amounts with moderate decreases (0–20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century. The largest decreases, amounting to up to 25–80 %, are projected to occur in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4–20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011–2040) with simulated decreases (compared to 1997–2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071–2100), accompanied by a shift in peak flows from July towards June.

scholarly journals Assessing the factors governing the ability to predict late-spring flooding in cold-region mountain basins

2020 ◽  
Vol 24 (4) ◽  
pp. 2141-2165 ◽  
Author(s):  
Vincent Vionnet ◽  
Vincent Fortin ◽  
Etienne Gaborit ◽  
Guy Roy ◽  
Maria Abrahamowicz ◽  
...  
Keyword(s):  
Soil Texture ◽  
Peak Flow ◽  
River Basins ◽  
Late Spring ◽  
Atmospheric Forcing ◽  
Cold Region ◽  
Flooding Event ◽  
Southern Alberta ◽  
Precipitation Analysis ◽  
Headwater Basins

Abstract. From 19 to 22 June 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia, Canada. Such an event is typical of late-spring floods in cold-region mountain headwater, combining intense precipitation with rapid melting of late-lying snowpack, and represents a challenge for hydrological forecasting systems. This study investigated the factors governing the ability to predict such an event. Three sources of uncertainty, other than the hydrological model processes and parameters, were considered: (i) the resolution of the atmospheric forcings, (ii) the snow and soil moisture initial conditions (ICs) and (iii) the representation of the soil texture. The Global Environmental Multiscale hydrological modeling platform (GEM-Hydro), running at a 1 km grid spacing, was used to simulate hydrometeorological conditions in the main headwater basins of southern Alberta during this event. The GEM atmospheric model and the Canadian Precipitation Analysis (CaPA) system were combined to generate atmospheric forcing at 10, 2.5 and 1 km over southern Alberta. Gridded estimates of snow water equivalent (SWE) from the Snow Data Assimilation System (SNODAS) were used to replace the model SWE at peak snow accumulation and generate alternative snow and soil moisture ICs before the event. Two global soil texture datasets were also used. Overall 12 simulations of the flooding event were carried out. Results show that the resolution of the atmospheric forcing affected primarily the flood volume and peak flow in all river basins due to a more accurate estimation of intensity and total amount of precipitation during the flooding event provided by CaPA analysis at convection-permitting scales (2.5 and 1 km). Basin-averaged snowmelt also changed with the resolution due to changes in near-surface wind and resulting turbulent fluxes contributing to snowmelt. Snow ICs were the main sources of uncertainty for half of the headwater basins. Finally, the soil texture had less impact and only affected peak flow magnitude and timing for some stations. These results highlight the need to combine atmospheric forcing at convection-permitting scales with high-quality snow ICs to provide accurate streamflow predictions during late-spring floods in cold-region mountain river basins. The predictive improvement by inclusion of high-elevation weather stations in the precipitation analysis and the need for accurate mountain snow information suggest the necessity of integrated observation and prediction systems for forecasting extreme events in mountain river basins.

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