This work advances the incorporation and cross-model deployment of multi-biogeochemistry and ecological simulations in existing process-based hydro-modelling tools. It aims to transform the current practice of water quality modelling as an isolated research effort into a more integrated and collaborative activity between science communities. Our approach, which we call “Open Water Quality” (OpenWQ), enables existing hydrological, hydrodynamic, and groundwater models to extend their capabilities to water quality simulations, which can be set up to examine a variety of water-related pollution problems. OpenWQ’s objective is to provide a flexible biogeochemical model representation that can be used to test different modelling hypotheses in a multi-disciplinary co-creative process. In this paper, we introduce the general approach used in OpenWQ. We detail aspects of its architecture that enable its coupling with existing models. This integration enables water quality models to benefit from advances made by hydrologic- and hydrodynamic-focused groups, strengthening collaboration between the hydrological, biogeochemistry, and soil science communities. We also detail innovative aspects of OpenWQ’s modules that enable biogeochemistry lab-like capabilities, where modellers can define the pollution problem(s) of interest, the appropriate complexity of the biogeochemistry routines, and test different modelling hypotheses. In a companion paper, we demonstrate how OpenWQ has been coupled to two hydrological models, the “Structure for Unifying Multiple Modelling Alternatives” (SUMMA) and the “Cold Regions Hydrological Model” (CRHM), demonstrating the innovative aspects of OpenWQ, the flexibility of its couplers and internal spatiotemporal data structures, and the versatile eco-modelling lab capabilities that can be used to study different pollution problems.

This work advances the cross-model deployment of ecological and biogeochemical simulation capabilities in existing process-based hydro-modeling tools, which we term “Open Water Quality” (OpenWQ). The companion paper details aspects of the OpenWQ architecture that enables its plug-in type incorporation into existing models, along with its innovative aspects that enable biogeochemistry lab-like capabilities. OpenWQ’s innovative aspects allow modelers to define the pollution problem(s) of interest, the appropriate complexity of the biogeochemistry routines, test different modeling hypotheses, and deploy them across different hydro-models. In this second paper, we implemented the coupling recipe described in the first paper to integrate OpenWQ into two hydro-models, SUMMA and CRHM. Here we explain how the implemented coupling interface between the two models provides water quality simulation capacities in the host hydro-models but, more importantly, establishes a direct and permanent link for the transfer of innovation between the modeling communities. Example applications of different pollution studies enabled by our coupling recipe are also provided to address some of these fundamental water quality modeling challenges.

not-yet-known not-yet-known not-yet-known unknown Land surface models (LSMs) are used to simulate water and energy fluxes between the land surface and atmosphere. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological Weighing Lysimeters (GWLs) are instruments that can provide field-scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire - Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land surface are represented. We attempted to parameterize each model in an equivalent manner, to minimize model differences. Both models were able to reproduce observations of total water storage and subsurface storage reasonably well. However, there were inconsistencies in the simulated timing of snowmelt; depth of soil freezing; total evapotranspiration; partitioning of evaporation between soil evaporation and evaporation of intercepted water; and soil drainage. No one model emerged as better overall, though each model had specific strengths and weaknesses that we describe. Insights from this study can be used to improve model physics and performance.

The phenomenon of freezing point depression in frozen soils results in the co-existence of ice and liquid water in soil pores at temperatures below 273.15 K, and is thought to have two causes: i) capillary effects, where the phase transition relationship is modified due to soil-air-water-ice interactions, and ii) solute effects, where the presence of salts lowers the freezing temperature. The soil freezing characteristic curve (SFC) characterizes the relationship between liquid water content and temperature in frozen soils. Most hydrological models represent the SFC using only capillary effects with a relationship known as the Generalized Clapeyron Equation (GCE). In this study, we develop and test a salt exclusion model for characterizing the SFC, comparing this with the GCE-based model and a combined capillary-solute effect model. We test these models against measured SFCs in laboratory and field experiments with diverse soil textures and salinities. We consistently found that the GCE-based models under-predicted freezing-point depression. We were able to match the observations with the salt exclusion model and the combined model, suggesting that salinity is a dominant control on the SFC in real soils that always contain solutes. In modelling applications where the salinity is unknown, the soil bulk solute concentration can be treated as a single fitting parameter. Improved characterization of the SFC may result in improvements in coupled mass-heat transport models for simulating hydrological processes in cold regions, particularly the hydraulic properties of frozen soils and the hydraulic head in frozen soils that drives cryosuction.

Cold regions provide water resources for half the global population yet face rapid change. Their hydrology is dominated by snow, ice and frozen soils, and climate warming is having profound effects. Hydrological models have a key role in predicting changing water resources, but are challenged in cold regions. Ground-based data to quantify meteorological forcing and constrain model parameterization are limited, while hydrological processes are complex, often controlled by phase change energetics. River flows are impacted by poorly quantified human activities. This paper reports scientific developments over the past decade of MESH, the Canadian community hydrological land surface scheme. New cold region process representation includes improved blowing snow transport and sublimation, lateral land-surface flow, prairie pothole storage dynamics, frozen ground infiltration and thermodynamics, and improved glacier modelling. New algorithms to represent water management include multi-stage reservoir operation. Parameterization has been supported by field observations and remotely sensed data; new methods for parameter identification have been used to evaluate model uncertainty and support regionalization. Additionally, MESH has been linked to broader decision-support frameworks, including river ice simulation and hydrological forecasting. The paper also reports various applications to the Saskatchewan and Mackenzie River basins in western Canada (0.4 and 1.8 million km2). These basins arise in glaciated mountain headwaters, are partly underlain by permafrost, and include remote and incompletely understood forested, wetland, agricultural and tundra ecoregions. This imposes extraordinary challenges to prediction, including the need to overcoming biases in forcing data sets, which can have disproportionate effects on the simulated hydrology.

Using data from five long-term field sites measuring soil moisture, we show the limitations of using soil moisture observations alone to constrain modelled hydrological fluxes. We test a land surface model, MESH/CLASS, with two configurations: one where the soil hydraulic properties are determined using a pedotransfer function (the texture-based calibration) and one where they are assigned directly (the hydraulic properties-based calibration). The hydraulic properties-based calibration outperforms the texture-based calibration in terms of reproducing changes in soil moisture storage within a 1.6 m deep profile at each site, but both perform reasonably well, especially in the summer months. When the models are constrained using observations of changes in soil moisture, the predicted hydrological fluxes are subject to very large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties-based calibration, even though the performance was better. We argue that since the pedotransfer functions constrain the model parameters in the texture-based calibrations in an unrealistic way, the texture-based calibration underestimates the uncertainty in the fluxes. We recommend that reproducing observed cumulative changes in soil moisture storage should be considered a necessary but insufficient criterion of model success. Additional sources of information are needed to reduce uncertainties, and these could include improved estimation of the soil hydraulic properties and direct observations of fluxes, particularly evapotranspiration.