Abstract
Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth system above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths, and limitations, so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities, and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when, or where large-scale models achieve their purpose or where opportunities for improvements exist so that such models better achieve their purpose. We suggest that reproducing the spatiotemporal details of regional-scale models and matching local data are not relevant goals. Instead, it is important to decide on reasonable model expectations regarding when a large-scale model is performing “well enough” in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria are quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and we subsequently discuss the value of three evaluation strategies: (1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation), (2) comparing several models with each other with or without reference to actual observations (model-based evaluation), and (3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning, and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models, thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.
Highlights
Groundwater is the largest human- and ecosystem-accessible freshwater storage component of the hydrologic cycle (UNESCO, 1978; Margat and Van der Gun, 2013; Gleeson et al, 2016)
Groundwater is often considered to be an inherently regional rather than global resource or system. This is partially reasonable because local to regional peculiarities of hydrology, politics, and culture are paramount to groundwater resource management (Foster et al, 2013), and groundwater dynamics in different continents are less directly connected and coupled than atmospheric dynamics
We focus on model evaluation because this is the heart of model trust and reproducibility (Hutton et al, 2016), and improved model evaluation will guide how and where it is most important to focus future model development
Summary
Various large-scale models exist along a spectrum of model complexity, which can make it difficult to determine the most appropriate model for a specific application. We developed a simple but systematic classification of current large-scale groundwater models (Table 1) to summarize the main characteristics of existing models for the interdisciplinary audience of GMD. This classification builds on other reviews (Bierkens 2015; Condon et al, 2021) and is not exhaustive, nor is it the only way to classify large-scale groundwater models. We note atmospheric coupling, which involves coupling a groundwater– surface model with an atmospheric model to propagate the influence of groundwater from the surface to the atmosphere and the resulting feedback onto the surface and groundwater This classification scheme (which could be called a model typology) is based on a number of model characteristics such as the fluxes, stores, and other features (Table 1)
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