A critical assessment of geological weighing lysimeters: Part 2—Modelling field scale soil moisture storage and hydrological fluxes

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(10)

Published: Oct. 1, 2024

Abstract Land surface models (LSMs) are used to simulate the terrestrial component of water, energy, and biogeochemical cycles. These simulations useful for water resources management, drought flood prediction, numerical climate/weather prediction. However, usefulness LSMs dependent by their ability reproduce states fluxes realistically. Accurate measurements storage calibrate validate outputs. Geological weighing lysimeters (GWLs) instruments that can provide field‐scale estimates integrated total within a soil profile. We use field subsurface critically evaluate two different land models: Modélisation Environnementale communautaire—Surface Hydrology (MESH) which uses Canadian Surface Scheme (CLASS), Structure Unifying Multiple Modeling Alternatives: (SUMMA). have differences in how processes properties represented. attempted parameterize each model an equivalent manner, minimize differences. Both were able observations reasonably well. there inconsistencies simulated timing snowmelt; depth freezing; evapotranspiration; partitioning evaporation between intercepted water; drainage. No one emerged as better overall, though had specific strengths weaknesses we describe. Insights from this study be improve physics performance.

Language: Английский

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Spatial heterogeneity and partitioning of soil health indicators in the Northern Great Plains using self-organizing map and change point methods

Earth Science Informatics, Journal Year: 2023, Volume and Issue: 16(3), P. 2017 - 2031

Published: April 27, 2023

Language: Английский

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The Ability of Hydrologic-Land Surface Models to Concurrently Simulate Permafrost and Hydrology

Published: March 21, 2023

Abstract. Hydrologic-land surface models (H-LSMs) provide physically-based understanding and predictions of the current future states world’s vast high-latitude permafrost regions. Two major challenges, however, hamper their parametrization validation when concurrently representing hydrology permafrost. One is high computational complexity, exacerbated by need to include a deep soil profile adequately capture freeze/thaw cycles heat storage. The other that soil-temperature data are severely limited, traditional model validation, based on streamflow, can show right fit these for wrong reasons. There few observational sites such vast, heterogeneous regions, remote sensing provides only limited support. In light we develop 16 parametrizations Canadian H-LSM, MESH, sub-arctic Liard River Basin validate them using three sources: streamflows at multiple gauges, temperature profiles from available boreholes, maps. different favor sources it challenging configure faithful all sources, which times inconsistent with each other. Overall, results that: (1) insulation through snow cover primarily regulates dynamics after initialization effects decay over, relatively long time (2) yield partitioning patterns solid-vs-liquid soil-water produce low-flow but similar high-flow regimes. We conclude that, given scarcity, an ensemble essential reliable picture spatio-temporal co-evolution hydrology.

Language: Английский

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On the optimal level of complexity for the representation of wetland systems in land surface models

Published: March 27, 2023

Abstract. Wetland systems are among the largest stores of carbon on planet, most biologically diverse all ecosystems, and dominant controls hydrologic cycle. However, their representation in land surface models (LSMs), which terrestrial lower boundary Earth system (ESMs) that inform climate actions, is limited. Here, we explore different possible parametrizations to represent wetland-groundwater-upland interactions with varying levels computational complexity. We perform a series numerical experiments informed by field observations from wetlands well-instrumented White Gull Creek Saskatchewan, boreal region North America. show typical LSMs, ignores groundwater uplands, can be inadequate. optimal level model complexity depends cover, soil type, ultimate modelling purpose, being nowcasting prediction, scenario analysis, or diagnostic learning.

Language: Английский

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Assimilation of Satellite Albedo to Improve Simulations of Glacier Hydrology

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: March 24, 2024

Wildfires and heatwaves have recently affected the hydrological system in unprecedented ways due to climate change. In cold regions, these extremes cause rapid reductions snow ice albedo soot deposition unseasonal melt. Snow dynamics control net shortwave radiation available energy for melt runoff generation. Many algorithms models cannot accurately simulate because they were developed or parameterised based on historical observations. Remotely sensed data assimilation (DA) can potentially improve model performance by updating modelled with This study seeks diagnose effects of remotely DA prediction streamflow from glacierized basins during wildfires heatwaves. Sentinel-2 20-m estimates assimilated into a glacio-hydrological created using Cold Regions Hydrological Modelling Platform (CRHM) two Canadian Rockies basins, Athabasca Glacier Research Basin (AGRB) Peyto (PGRB). The was conducted 2018 (wildfires), 2019 (soot/algae), 2020 (normal), 2021 (heatwaves). employed assimilate CRHM compared run (CTRL) off-the-shelf parameters. Albedo benefited predictions both KGE coefficient improvement 0.18 0.20 AGRB PGRB, respectively. Four-year superior CTRL but slightly better AGRB. not beneficial These results show that reveal otherwise unknown snowpack occurring remote glacier accumulation zones are well simulated alone. findings corroborate power observational tools incorporate near real-time information inform water managers response

Language: Английский

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