19 research outputs found

    Arctic HYCOS – 1st Workshop on Improved Monitoring, Accuracy and Data Availability in the Arctic Drainage Basin: Meeting Summary Report and Implementation Plan

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    The World Hydrological Cycle Observing System (WHYCOS) is a global programme, developed in response to the scarcity or absence of accurate, timely and accessible data and information in real or near real time on freshwater resources in many parts of the world. The programme is implemented through various components (HYCOSs) at the regional and/or basin scale. It is guided by the WHYCOS International Advisory Group (WIAG). The Arctic-HYCOS program is being promoted through this Workshop. For more information on the WHYCOS, please see http://www.whycos.org/cms/. The main goal of the Arctic-HYCOS program is to improve monitoring, data accuracy, availability and dissemination of information in the pan-arctic drainage basin. This project is science-driven and is aimed at monitoring freshwater fluxes and pollutants into the Arctic Ocean with the objective of improving climate predictions in the Northern Hemisphere and assessing the pollution of the Arctic coastal areas and the open Arctic Ocean. Arctic-HYCOS is currently organized along three main activities. 1. Develop and optimal design fro hydro-meteorological monitoring networks to capture the essential variability of the Arctic hydrological system and to enable accurate and efficient assessment of change 2. Estimate uncertainty of available in situ and possible remote sensing data including analysis of accuracy and systematic errors of new observation technology 3. Develop an integrated pan-arctic data consolidation and analysis system for the water cycle uniting data from various in-situ and other sources

    Translating hydrology research into practice: A Canadian Perspective

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    EGU23-4485 https://doi.org/10.5194/egusphere-egu23-4485 EGU General Assembly 2023 © Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.Peer ReviewedHydrology research is regarded as vital for advancing human development and environmental conservation through improved hydrological process understanding and by devising solutions to address water management challenges. This is particularly acute in a time of global change and the need to find pathways to water sustainability. Success for research in hydrology is often measured through quantitative research outputs, such as the number of journal publications, citation indices, number of students trained, patents, and external research funding. User involvement in the research and development process is rarely considered a metric for success in hydrology. Despite successful scientific or engineering advancements, a greater scientific understanding of hydrology and ever-increasing publications, much of the research has limited uptake by practitioners and implementation into practice, leading to a growing gap between research and practice. This lack of utilisation is not due to a lack of need by users, but rather is a symptom of the disconnect between these advances and research that would most add value to practitioners and their application needs. We explore some outstanding challenges in translating academic research into practice and make some recommendations to bridge the increasing gaps between research and practice through a transdisciplinary approach, user engagement metrics in funded research and strong knowledge mobilization. We also discuss the success and challenges of these approaches in the Global Water Futures program along with lessons learned

    Physically based cold regions river flood prediction in data-sparse regions: The Yukon River Basin flow forecasting system

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    Global Water Futures; Yukon EnvironmentPeer ReviewedThe Yukon River Basin (YRB) is one of the most important river networks shared between Canada and The United States, and is one of the largest river basins in the subarctic region of North America. The Canadian part of the YRB is characterized by steeply sloped, partly glaciated mountain headwaters that generate considerable runoff during melt of glaciers and seasonal snow-cover. Snow redistribution, snowmelt, glacier melt and freezing–thawing soil processes in winter and spring along with summertime rainfall-runoff and evapotranspiration processes are thus key components of streamflow generation in the basin, making conceptual rainfall-runoff models unsuitable for this cold region. Due to the remote high latitudes and high altitudes of the basin, there is a paucity of observational data, making heavily calibrated conceptual modeling approaches infeasible. At the request of the Yukon Government, this project developed and operationalized a streamflow forecasting system for the Yukon River and several of its tributary rivers using a distributed land surface modeling approach developed for large-scale implementation in cold regions. This represents a substantial advance in bringing operational hydrological forecasting to the Canadian subarctic for the first time. This experience will inform future research to operation improvements as Canada develops a nationally coordinated flood forecast system

    Diagnosis of Historical and Future Flow Regimes of the Bow River at Calgary Using a Dynamically Downscaled Climate Model and a Physically Based Land Surface Hydrological Model : Final Report

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    Final Report developed under Agreement #AP744 for the Natural Resources Canada Climate Change Adaptation Program.Developed under Agreement #AP744 for the Natural Resources Canada Climate Change Adaptation Program, with financial and in-kind assistance from Natural Resources Canada, Alberta Environment and Parks, the City of Calgary, Environment and Climate Change Canada and the Global Water Futures program.Non-Peer ReviewedThis report assesses the impacts of projected climate change on the hydrology, including the flood frequencies, of the Bow and Elbow Rivers above Calgary, Alberta. It reports on investigations of the effects of projected climate change on the runoff mechanisms for the Bow and Elbow River basins, which are important mountain headwaters in Alberta, Canada. The study developed a methodology and applied a case study for incorporating climate change into flood frequency estimates that can be applied to a variety of river basins across Canada

    Towards a coherent flood forecasting framework for Canada: Local to global implications

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    Alberta Innovates; Government of Canada Budget of 2018 measure “Adapting Canada's Weather and Water Services to Climate Change and the National Hydrological Service Transformation Initiative”; Canada First Research Excellence Fund, Global Water Futures Program; Canada Research Chairs Program; Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; Yukon EnvironmentPeer ReviewedOperational flood forecasting in Canada is a provincial responsibility that is carried out by several entities across the country. However, the increasing costs and impacts of floods require better and nationally coordinated flood prediction systems. A more coherent flood forecasting framework for Canada can enable implementing advanced prediction capabilities across the different entities with responsibility for flood forecasting. Recently, the Canadian meteorological and hydrological services were tasked to develop a national flow guidance system. Alongside this initiative, the Global Water Futures program has been advancing cold regions process understanding, hydrological modeling, and forecasting. A community of practice was established for industry, academia, and decision-makers to share viewpoints on hydrological challenges. Taken together, these initiatives are paving the way towards a national flood forecasting framework. In this article, forecasting challenges are identified (with a focus on cold regions), and recommendations are made to promote the creation of this framework. These include the need for cooperation, well-defined governance, and better knowledge mobilization. Opportunities and challenges posed by the increasing data availability globally are also highlighted. Advances in each of these areas are positioning Canada as a major contributor to the international operational flood forecasting landscape. This article highlights a route towards the deployment of capacities across large geographical domains

    Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)

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    Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experienced recent flooding and shoreline erosion alongside excessive nutrient loads that have contributed to lake eutrophication. Understanding the sources and pathways of flows is critical to solve the complex issues facing this watershed. Seventeen hydrologic and land-surface models of different complexity are set up over this domain using the same meteorological forcings, and their simulated streamflows at 46 calibration and seven independent validation stations are compared. Results show that: (1) the good performance of Machine Learning models during calibration decreases significantly in validation due to the limited amount of training data; (2) models calibrated at individual stations perform equally well in validation; and (3) most distributed models calibrated over the entire domain have problems in simulating urban areas but outperform the other models in validation

    Summary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 2: Future change in cryosphere, vegetation, and hydrology

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    CCRN from the Natural Sciences and Engineering Research Council of Canada (NSERC) through their Climate Change and Atmospheric Research (CCAR) programPeer ReviewedThe interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land– hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century

    Yukon River Basin Streamflow Forecasting System - Advancing, Calibrating, Demonstrating Snow Assimilation and Estimating Ungauged Basin Flow: The Vector-Based MESH Model of the Yukon River Basin

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    Yukon Environment, Global Water Futures ProgramNon-Peer ReviewedThe Yukon River Basin the second largest river in the Arctic region of North America and is shared between Canada and the US. The Canadian part covers almost half of the Yukon Territory in addition to a small portion of the province of British Columbia, while the US part falls totally within the state of Alaska. This study is concerned with Canadian part of the Yukon River with its outlet at Eagle, Alaska - just downstream of the international boundary (288,000 km2). The southern part of the Yukon River basin is characterized by extensive icefields and snowfields at high elevations (up to 4700 m above sea level) with steep slopes, and thus generates considerable runoff. There are also mountain ranges on the eastern and northern boundaries of the basin, while the western areas are milder in slope and partially forested. Snow redistribution by wind, snowmelt, glacier melt and frozen soil processes in winter and spring along with summertime rainfall-runoff and evapotranspiration processes are thus key to the simulation of streamflow in the basin. This supplement shows further development of a vector-based MESH setup for the Canadian portion of the Yukon River Basin down to Eagle, Alaska. For operational forecasting, MESH is driven by the Environment and Climate Change Canada Global Multiscale Model (GEM) weather model forecasts with precipitation replaced with the Canadian Precipitation Analysis (CaPA) which assimilates local precipitation observations where they exist, collectively referred to as GEM-CaPA. Additionally, the newly developed Regional Deterministic Reforecast System v2.1 (RDRS v2.1) forcing has been extended to span the period 1980-2018 enabling long-term assessments of hydrology. The revised vector-based model was calibrated for operational use based on the GEM-CaPA forcing dataset, and for performing historical simulations based on the RDRS v2.1 forcing dataset, using the period 2004-2011 in both cases. Performance was compared to the previously generated grid-based MESH model whose development was documented in Centre for Hydrology Report #16. A long-term historical simulation was then performed using RDRS v2.1 from which streamflow exceedance return periods for 15 important stations were calculated and presented in this supplement. Calibration has generally improved the performance of the vector-based setup compared to the previous simulations presented in supplement #1 of report #16. Parameter sets are slightly different when the model is calibrated to RDRS v2.1 compared to GEM-CaPA due to differences between the two datasets. A pilot study of the potential benefits of snow data assimilation into the existing MESH forecast system was conducted using historical data and the gridded MESH product that is used operationally by Yukon Environment. This test showed benefits to assimilating surface snowpack observations into MESH to correct winter precipitation. Outputs with assimilation showed improved snowpack simulations and improved streamflow forecasts

    Yukon River Basin Streamflow Forecasting System - Vector-Based MESH Model Setup for Yukon River Basin

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    Yukon Environment, Global Water Futures ProgramNon-Peer ReviewedThe Yukon River Basin the second largest river in the Arctic region of North America and is shared between Canada and the US. The Canadian part covers almost half of the Yukon Territory in addition to a small portion of the province of British Columbia, while the US part falls totally within the state of Alaska. This study is concerned with Canadian part of the Yukon River with its outlet at Eagle, Alaska - just downstream of the international boundary (288,000 km2). The southern part of the Yukon River basin is characterized by extensive icefields and snowfields at high elevations (up to 4700 m above sea level) with steep slopes, and thus generates considerable runoff. There are also mountain ranges on the eastern and northern boundaries of the basin, while the western areas are milder in slope and partially forested. Snow redistribution by wind, snowmelt, glacier melt and frozen soil processes in winter and spring along with summertime rainfall-runoff and evapotranspiration processes are thus key to the simulation of streamflow in the basin. This supplement shows the development of a vector-based MESH setup for the Canadian portion of the Yukon River Basin at Eagle. Without additional calibration, the vector-based model performance was compared to the previously generated grid-based MESH model whose development was documented in Centre for Hydrology Report #16. MESH was driven by the Environment and Climate Change Canada Global Multiscale Model (GEM) weather model forecasts with precipitation replaced with the Canadian Precipitation Analysis (CaPA) which assimilates local precipitation observations where they exist, collectively referred to as GEM-CaPA. Additionally, the models were run, without additional calibration using the newly developed Regional Deterministic Reforecast System v2 (RDRS v2) forcing. RDRS v2 forcing is being extended as a hindcast by ECCC to approx. 1980 and so will permit 40 year runs of MESH from which streamflow exceedance return periods can be calculated. Model performance was slightly inferior for the vector-based setup compared to the original grid-based one. This may be due to the full calibration applied to the grid-based model and parameter transfer to the vector-based model without recalibration. Model performance also deteriorated when the RDRS v2 was used as forcing data, as the model was originally calibrated to GEM-CaPA. It is expected that model performance will improve once it is fully calibrated using the RDRS v2 forcing data
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