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.
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.
Computing the velocity field is an expensive process for mantle convection codes. This has implications for particle methods used to model the advection of quantities such as temperature or composition. A common choice for the numerical treatment of particle trajectories is classical fourth-order Runge–Kutta (ERK4) integration, which involves a velocity computation at each of its four stages. To reduce the cost per time step, it is possible to evaluate the velocity for a subset of the four time integration stages. We explore two such alternative schemes, in which velocities are only computed for: a) stage 1 on odd-numbered time steps and stages 2–4 for even-numbered time steps, and b) stage 1 for all time steps. A theoretical analysis of stability and accuracy is presented for all schemes. It was found that the alternative schemes are first-order accurate with stability regions different from that of ERK4. The efficiency and accuracy of the alternate schemes were compared against ERK4 in four test problems covering isothermal, thermal, and thermochemical flows. Exact solutions were used as reference solutions when available. In agreement with theory, the alternate schemes were observed to be first-order accurate for all test problems. Accordingly, they may be used to efficiently compute solutions to within modest error tolerances. For small error tolerances, however, ERK4 was the most efficient.
Despite the proliferation of computer-based research on hydrology and water resources, such research is typically poorly reproducible. Published studies have low reproducibility due to incomplete availability of data and computer code, and a lack of documentation of workflow processes. This leads to a lack of transparency and efficiency because existing code can neither be quality controlled nor re-used. Given the commonalities between existing process-based hydrological models in terms of their required input data and preprocessing steps, open sharing of code can lead to large efficiency gains for the modeling community. Here we present a model configuration workflow that provides full reproducibility of the resulting model instantiations in a way that separates the model-agnostic preprocessing of specific datasets from the model-specific requirements that models impose on their input files. We use this workflow to create large-domain (global, continental) and local configurations of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model connected to the mizuRoute routing model. These examples show how a relatively complex model setup over a large domain can be organized in a reproducible and structured way that has the potential to accelerate advances in hydrologic modeling for the community as a whole. We provide a tentative blueprint of how community modeling initiatives can be built on top of workflows such as this. We term our workflow the “Community Workflows to Advance Reproducibility in Hydrologic Modeling’‘ (CWARHM; pronounced “swarm”).
The next generation of Earth System models promisesunprecedented predictive power through the application of improvedphysical representations, data collection, and high-performancecomputing. A key component to the accuracy, efficiency, and robustnessof the Earth System simulations is the time integration ofdifferential equations describing the physical processes. Manyexisting Earth System models are simulated using low-order,constant-stepsize time-integration methods with no error control,opening them up to being inaccurate, inefficient, or require aninfeasible amount of manual tweaking when run over multipleheterogeneous domains or scales. We have implemented the variable-stepize, variable-order differentialequation solver SUNDIALS as the time integrator within the Structurefor Unifying Multiple Modelling Alternatives (SUMMA) modelframework. The model equations in SUMMA were modified and augmented toexpress conservation of mass and enthalpy. Water and energy balanceerrors were tracked and kept below a strict tolerance. The resultingSUMMA-SUNDIALS software was successfully run in a fully automatedfashion to simulate hydrological processes on the North Americancontinent, sub-divided into over 500,000 catchments. We compared the performance of SUMMA-SUNDIALS with a version (calledSUMMA-BE) that used the backward Euler method with a fixed stepsize asthe time-integration method. We find that SUMMA-BE required two ordersof magnitude more CPU time to produce solutions of comparable accuracyto SUMMA-SUNDIALS. Solutions obtained with SUMMA-BE in a similar orshorter amount of CPU time than SUMMA-SUNDIALS often contained largediscrepancies. We conclude that sufficient accuracy, efficiency, and robustness ofnext-generation Earth System model simulations can realistically onlybe obtained through the use of adaptive solvers. Furthermore, wesuggest simulations produced with low-order, constant-stepsizesolvers deserve more scrutiny in terms of their accuracy.