A5085387219- Soil Moisture and Remote Sensing
- Soil and Unsaturated Flow
- Hydrology and Watershed Management Studies
- Climate change and permafrost
- Precipitation Measurement and Analysis
- Cryospheric studies and observations
- Meteorological Phenomena and Simulations
- Water resources management and optimization
- Hydrological Forecasting Using AI
- Research Data Management Practices
- Atmospheric and Environmental Gas Dynamics
- Groundwater flow and contamination studies
- Flood Risk Assessment and Management
- Geological Modeling and Analysis
- Groundwater and Isotope Geochemistry
- Hydrology and Drought Analysis
- Water Systems and Optimization
- Climate variability and models
- Scientific Computing and Data Management
Ontario Power Generation
2018-2023
University of Waterloo
2020
McMaster University
2012-2019
Natural Sciences and Engineering Research Council
2017
Abstract The soil moisture state partitions both mass and energy fluxes is important for many hydro‐geochemical cycles, but often only measured within the surface layer. Estimating amount of in root‐zone from this information difficult due to nonlinear heterogeneous nature various processes which alter state. Data‐driven methods, such as artificial neural networks (ANN), mine data interdependencies have potential estimating observations. To create an ANN model that was nonsite‐specific...
Abstract The Canadian Surface Prediction Archive (CaSPAr) is an archive of numerical weather predictions issued by Environment and Climate Change Canada. Among the products archived on a daily basis are five operational forecasts, three analyses, one reanalysis product. have hourly to temporal resolution 2.5–50-km spatial resolution. To date contains 394 TB data while 368 GB new added every night. in CF-1.6-compliant netCDF-4 format. available online ( https://caspar-data.ca ) since June...
Missing values in situ monitoring data is a problem often encountered hydrologic research and applications. Values set may be missing because of sensor error or failure recording devices. Whereas various imputation techniques have focused on hydrometeorological data, very few studies investigated gap-filling methods for soil moisture data. This paper aims to fill that gap by investigating well-established statistical data-driven infilling high resolution, time series. Since 2006, the authors...
Abstract This study investigates the feasibility of artificial neural networks ( ANN s) to retrieve root zone soil moisture RZSM ) at depths 20 cm SM 20) and 50 50) a continental scale, using surface information. To train s capture interactions between land various climatic patterns, data 557 stations over United States were collected. A sensitivity analysis revealed that able identify input variables directly affect water energy balance in zone. The important for retrieval large area...
Many methods have been proposed to select sites for grid-scale soil moisture monitoring networks; however, calibration/validation activities also require information about where place grid representative sites. In order design a network this task in the Great Lakes Basin (522 000 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), dual-entropy multiobjective optimization algorithm was used maximize content and minimize redundancy of...
Abstract. This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by McMaster Mesonet located in Hamilton-Halton Watershed Southern Ontario, Canada. The consists of a network time domain reflectometer (TDR) probes collecting hourly data at six depths between 10 cm 100 nine locations per site, spread across four sites 1250 km2 watershed. for arrays are designed to further improve understanding dynamics seasonal climate capture transitions...
Abstract Passive microwave satellites such as Soil Moisture and Ocean Salinity or Active observe brightness temperature (TB) retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed simple method to disaggregate scale more appropriate for applications. Temporal stability of TB was demonstrated the Little Washita River Experimental Watersheds using in situ observations Community Microwave Emissions Model. Decomposition mean square...
The assimilation of soil moisture and brightness temperature (TB) are expected to improve the modeling land surface processes, but only available at a resolution that is far coarser than scale many hydrological processes. Due systematic differences between model states satellite observations, bias correction operator necessary step in data schemes was evaluated as method disaggregate coarse-scale observations fine-scale grid cells (~800 m). This done by coupling Modélisation Environmentale...
Natural streamflow data is required in many hydrological applications. However, basins are located data-scarce regions or impacted by human construction and activities. In this paper, we explore three machine learning algorithms, namely artificial neural networks, random forest light gradient boosting machine, to simultaneously estimate all the parameters of coupled modèle du Génie Rural à 4 paramètres Journaliers (GR4J) snow accounting routine called CemaNeige model. A database 675 USA...
The monitoring of in situ soil moisture is an important task for hydro-climatic forecasting and the calibration/validation satellite based missions such as Soil Moisture Ocean Salinity (SMOS) mission. Many techniques have been explored to select a single site station that representative watershed characteristics. To objectively design entire network, this paper presents dual-entropy multi-objective optimization (DEMO) system using data retrieved from SMOS. resulting optimal networks are...
The Soil Moisture and Ocean Salinity (SMOS) microwave radiometer is used to retrieve surface soil moisture with a grid resolution of 15 km. Due various contributing factors SMOS known have bias respect in situ measurements land models. For this reason it common practice match the cumulative distribution function (CDF) retrieved prior analysis. Using concept temporal stability study demonstrates that CDF matching effective for correcting at both sub-grid scales minimal impact on time...
ydrologic, land surface, and other environmental models require meteorological input data-for example, precipitation temperature to estimate discharge soil moisture.In a hindcast these data are usually provided by ground observations, but in forecast mode, they forecasted inputs from numerical weather prediction (NWP) models.Archived predictions required evaluate or improve such forecasting systems.However, archives of NWP rare.Furthermore, while disseminated the agencies producing...
Abstract. This paper introduces and describes the hourly high resolution soil moisture dataset continuously recorded by McMaster Mesonet located in Hamilton-Halton Watershed Southern Ontario, Canada. The consists of a network time domain reflectometer (TDR) probes collecting data at six depths between 10 cm 100 nine locations per site spread across four sites 1250 km2 watershed. for arrays are designed to further improve understanding dynamics cold snowy climate capture transitions areas...