A5042453849- Hydrology and Watershed Management Studies
- Hydrological Forecasting Using AI
- Water Systems and Optimization
- Target Tracking and Data Fusion in Sensor Networks
- Soil and Water Nutrient Dynamics
- Meteorological Phenomena and Simulations
- Environmental Monitoring and Data Management
- Reservoir Engineering and Simulation Methods
- Flood Risk Assessment and Management
- Climate variability and models
- Ecology and biodiversity studies
- Soil erosion and sediment transport
University of Calgary
2023-2025
University of Saskatchewan
2023
Abstract. We present a new data set aimed at hydrologic studies across North America, with particular focus on facilitating spatially distributed studies. The includes basin outlines, stream observations, meteorological and geospatial for 1426 basins in the United States Canada. To facilitate wide variety of studies, we provide outlines lumped semi-distributed resolution; streamflow observations daily hourly time steps; variables suitable running range models obtained derived from different...
AI enhanced environmental modelling workflows: Towards Automated Scientific Exploration in HydrologyAuthors: Darri Eythorsson, Kasra Keshavarz, Cyril Thébault, Mohamed Ismaiel Ahmed, Raymond Spiteri, Alain Pietroniro and Martyn ClarkModern hydrological modeling has evolved into a complex scientific endeavour requiring sophisticated workflows that span multiple scales, processes, computational paradigms. While existing workflow solutions address specific technical challenges, the...
The St. Mary and Milk River (SMM) basin is an international transboundary watershed flowing between Canada the United States. composed of 2 distinct headwater basins that flow into Saskatchewan Nelson Mississippi basin, respectively. A diversion constructed in 1909 conveys water from higher-yielding lower-yielding River. Boundary Waters Treaty USA allowed for specific entitlements each country, allowing sharing combined resource both countries. Lack storage, conveyance changing hydrological...
High-resolution and high-complexity process-based hydrological models play a pivotal role in advancing our understanding prediction of water cycle dynamics, particularly ungauged basins under nonstationary climate conditions. However, the configuration, application, evaluation these are often hindered by intricate inconsistent nature priori information available various datasets, necessitating extensive preprocessing steps. These challenges can limit reproducibility, applicability,...
The Earth System modeling community uses different methods to discretize a landscape in model elements, such as square grids, triangles, or irregular shapes. Mapping data from one spatial configuration another is an essential part of environmental modeling, and can be time-consuming cumbersome. In this work, we present Python package called EASYMORE. EASYMORE stands for EArth SYstem MOdeling REmapper enables users quickly efficiently remap variables, precipitation temperature, representation...
Configuring process-based hydrologic models can be a cumbersome task, especially for larger domains. In the past model inputs (data), configuration and analysis code, as well source code of themselves were only rarely openly available. More recently, hydrology community is moving toward more open culture, focused on shareable data, tools code. Here we present various recent open-source advances along entire modeling chain. These include: Workflows large-domain models, data-driven seasonal...
Large-domain hydrological modelling is vital to understand and predict water resources under a changing climate. Here we summarize our efforts develop model configuration workflow for the Hydrological Predictions Environment (HYPE) as proof-of-concept of “bottom-up” approach community large-scale modelling. The initiative Community Workflows Advance Reproducibility in Hydrologic Modeling (CWARHM, Knoben et al. 2022) provides blueprint workflow, separating model-agnostic...