Regional Analysis

Water Supply Infrastructure Planning: Decision-Making Framework to Classify Multiple Uncertainties and Evaluate Flexible Design

Urban planners face challenges in water infrastructure development decisions due to short-term variation in water availability and demand, long-term uncertainty in climate and population growth, and differing perspectives on the value of water. This paper classifies these multiple uncertainties and develops a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multistage decision analysis for uncertainties reduced over time with additional information. This framework is applied to a case from Melbourne, Australia, where a drought from 1997 to 2009 prompted investment in a $5 billion desalination plant completed in 2012 after the drought ended. The results show opportunities for significant reduction in capital investment using flexible design. Building no infrastructure is best in most simulations. However, in 10% of simulations, building no infrastructure leads to regret of greater than $10 billion compared with a small, flexible desalination plant. Scenario analysis for deep uncertainties underlines the significant impact of assumptions about the future and also on value judgments about the cost of water scarcity in evaluating infrastructure performance.

Spanning Eastern Europe, Scandinavia, the former Soviet Union and Northern China, Northern Eurasia is a bellwether for the future of climate change. Having undergone the fastest rate of climate change in the human-populated world in the past few decades, the region has endured dramatic natural disturbances and significantly altered its land-management practices. And that may be just the beginning.

Understanding climate change’s ground zero
The Future Water Risks Under Global Change in Southern and Eastern Asia: Implications of Mitigation

Understanding and predicting the future vulnerability of freshwater resources is a major challenge with important societal implications. Many studies have identified Asia as a hotspot of severe water stress in the coming decades, and also highlighted the large uncertainty associated with water resource assessment based on limited multi-model projections. Here we provide a more comprehensive risk-based assessment of water use and availability in response to future climate change, socioeconomic growth, and their combination in Southern and Eastern Asia. We employ a large ensemble of scenarios that capture the spectrum of regional climate response as well as a range of economic projections and climate policies in a consistent, integrated modeling framework. We show that economic growth increases water stress ubiquitously. The climate-only and combined climate-growth effects on water stress remain largely negative in China and Indus Basin, but largely positive in India, Indochina, and Ganges Basin. However, climate poses substantially large uncertainty in water stress changes than socioeconomic growth. By 2050, socioeconomic growth alone can lead to an additional 650 million people living under at least “heavy” water stress, with most of these located in India, Indus Basin, and China. The combined effects of socioeconomic growth and climate change reduce people under water stress to an additional 200 million, attributed mainly to the beneficial climate in India that moves its heavily-stressed condition into the slightly or moderately‑stressed conditions. These 200 million people primarily reside in Indus Basin and China under at least overly exploited water conditions— where total water requirements will consistently exceed surface water supply. Climate mitigation helps alleviating the risks of increasing water scarcity by midcentury, but to a limited extent. Therefore, adaptive measures need to be taken to meet these surface water shortfalls, or a combination of both approaches may be most effective.

A new study by MIT climate scientists, economists, and agriculture experts finds that certain hotspots in the country will experience severe reductions in crop yields by 2050, due to climate change’s impact on irrigation.

The most adversely affected region, according to the researchers, will be the Southwest. Already a water-stressed part of the country, this region is projected to experience reduced precipitation by midcentury. Less rainfall to the area will mean reduced runoff into water basins that feed irrigated fields.

Climate change to deplete some US water basins, reduce irrigated crop yields
Impact of Canopy Representations on Regional Modeling of Evapotranspiration using the WRF-ACASA Coupled Model

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model, to investigate the impact of canopy representation on regional evapotranspiration. The WRF-ACASA model uses a multilayer structure to represent the canopy, consequently allowing microenvironmental variables such as leaf area index (LAI), air and canopy temperature, wind speed and humidity to vary both horizontally and vertically. The improvement in canopy representation and canopy-atmosphere interaction allow for more realistic simulation of evapotranspiration on both regional and local scales. The coupled WRF-ACASA model is compared with the widely used intermediate complexity Noah land surface model in WRF (WRF-Noah) for both potential (ETo) and actual evapotranspiration (ETa). Two LAI datasets (USGS and MODIS) are used to study the model responses to surface conditions. Model evaluations over a diverse surface stations from the CIMIS and AmeriFlux networks show that an increase surface representations increase the model accuracy in ETa more so than ETo. Overall, while the high complexity of WRF-ACASA increases the realism of plant physiological processes, the model sensitivity to surface representation in input data such as LAI also increases.

A review of and perspectives on global change modeling for Northern Eurasia

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

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