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Updated: Apr 11, 2026

In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
Improved Recharge Estimation from Portable, Low-Cost Weather Stations
Hartmut M Holländer, Zijian Wang1, Kibreab A Assefa1
1Department of Civil Engineering, University of Manitoba, 15 Gillson St, Winnipeg, Manitoba, R3T 5V6, Canada.
Groundwater recharge estimation is crucial for sustainable water management. A HYDRUS-1D model, using weather station data and soil parameters, accurately estimated annual recharge in Abbotsford, BC.
Area of Science:
- Hydrology
- Environmental Science
- Water Resource Management
Background:
- Accurate groundwater recharge estimation is vital for sustainable water resource management.
- Physical-based modeling offers a robust approach for assessing groundwater recharge.
- Low-cost weather stations and remote sensing techniques enhance data acquisition for hydrological studies.
Purpose of the Study:
- To evaluate the feasibility and robustness of groundwater recharge estimation using physical-based modeling.
- To assess recharge using data from a low-cost weather station and remote sensing in Southern Abbotsford, BC.
- To validate model performance with observed soil moisture and temperature data.
Main Methods:
- Employed the Richards-based vadose zone hydrological model, HYDRUS-1D.
- Utilized meteorological data from a HOBO weather station (1 year) and Abbotsford A weather station (27 years).
- Incorporated soil hydraulic parameters derived from undisturbed soil cores and validated with remote sensor data.
Main Results:
- Estimated short-term recharge at 863 and 816 mm.
- Calculated mean annual recharge over 27 years as 848 and 859 mm/year.
- Determined annual recharge-precipitation ratios between 43% and 69%, with 80% occurring in winter.
Conclusions:
- The HYDRUS-1D model, with local data, provides reliable groundwater recharge estimates.
- The method is robust and suitable for transient recharge predictions.
- This approach can aid in estimating nutrient leaching, particularly nitrate, influenced by precipitation events.
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