Accurate and Efficient Numerical Simulation of Land Models Using SUMMA With SUNDIALS.

Numerical simulation of land models without error control can be highly inaccurate. We present the incorporation of the Suite of Nonlinear and Differential-Algebraic Equation Solvers (SUNDIALS) package to solve the equations that simulate thermodynamics and hydrologic processes in the Structure for Unifying Multiple Modeling Alternatives (SUMMA) land model. The algorithmic features of SUNDIALS, such as error estimation and adaptive order and step-size control, result in a SUMMA-SUNDIALS model that delivers substantially improved accuracy and relative computational efficiency compared to integration with the previous SUMMA model, which uses the low-order backward Euler method with no rigorous error control.

Impacts of agriculture and snow dynamics on catchment water balance in the U.S. and Great Britain.

The Budyko water balance is a fundamental concept in hydrology that links aridity to how precipitation is divided between evapotranspiration and streamflow. While the model is powerful, its ability to explain temporal changes and the influence of human activities and climate change is limited. Here we introduce a causal discovery algorithm to explore deviations from the Budyko water balance, attributing them to human interventions such as agricultural activities and snow dynamics.

Resilience and vulnerabilities of urban food environments in the Asia-Pacific region.

Rapid urbanisation in the Asia-Pacific region is associated with complex changes to urban food environments. The impact of changing food environments on food purchasing and consumption and the diets and nutritional status of vulnerable groups, especially women and young children, is not well researched in low- and middle-income country cities. This paper aimed to examine: the risks and opportunities for healthy diets for low income populations offered by modernising urban centres; the concept of food deserts in relation to urban food environments in the Asia-Pacific region and how these could be mitigated; and measures to strengthen the resilience of food environments in the region using a case study of the impact of COVID-19 on informal food vendors.

Probabilistic Evaluation of Drought in CMIP6 Simulations.

As droughts have widespread social and ecological impacts, it is critical to develop long-term adaptation and mitigation strategies to reduce drought vulnerability. Climate models are important in quantifying drought changes. Here, we assess the ability of 285 CMIP6 historical simulations, from 17 models, to reproduce drought duration and severity in three observational data sets using the Standardized Precipitation Index (SPI).

Compilation of climate data from heterogeneous networks across the Hawaiian Islands.

Long-term, accurate observations of atmospheric phenomena are essential for a myriad of applications, including historic and future climate assessments, resource management, and infrastructure planning. In Hawai'i, climate data are available from individual researchers, local, State, and Federal agencies, and from large electronic repositories such as the National Centers for Environmental Information (NCEI). Researchers attempting to make use of available data are faced with a series of challenges that include: (1) identifying potential data sources; (2) acquiring data; (3) establishing data quality assurance and quality control (QA/QC) protocols; and (4) implementing robust gap filling techniques.

Scaling, Similarity, and the Fourth Paradigm for Hydrology.

In this synthesis paper addressing hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third paradigm), and assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modelling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing, describe a mutual information framework for testing these hypotheses, describe boundary condition, state/flux, and parameter data requirements across scales to support testing these hypotheses, and discuss some challenges to overcome while pursuing the fourth hydrological paradigm.

Practical Use of Computationally Frugal Model Analysis Methods.

Three challenges compromise the utility of mathematical models of groundwater and other environmental systems: (1) a dizzying array of model analysis methods and metrics make it difficult to compare evaluations of model adequacy, sensitivity, and uncertainty; (2) the high computational demands of many popular model analysis methods (requiring 1000's, 10,000 s, or more model runs) make them difficult to apply to complex models; and (3) many models are plagued by unrealistic nonlinearities arising from the numerical model formulation and implementation. This study proposes a strategy to address these challenges through a careful combination of model analysis and implementation methods. In this strategy, computationally frugal model analysis methods (often requiring a few dozen parallelizable model runs) play a major role, and computationally demanding methods are used for problems where (relatively) inexpensive diagnostics suggest the frugal methods are unreliable.