Newsha K. Ajami

Multimodel Combination Techniques for Analysis of Hydrological Simulations: Application to Distributed Model Intercomparison Project Results

This paper examines several multimodel combination techniques that are used for streamflow forecasting: the simple model average (SMA), the multimodel superensemble (MMSE), modified multimodel superensemble (M3SE), and the weighted average method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multimodel combination results were obtained using uncalibrated DMIP model simulations and were compared against the best-uncalibrated as well as the best-calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the accuracy levels of the multimodel simulations. This study revealed that the multimodel simulations obtained from uncalibrated single-model simulations are generally better than any single-member model simulations, even the bestcalibrated single-model simulations. Furthermore, more sophisticated multimodel combination techniques that incorporated bias correction step work better than simple multimodel average simulations or multimodel simulations without bias correction.

Hydrologic ensemble prediction experiment focuses on reliable forecasts

The Hydrologic Ensemble Prediction Experiment (HEPEX), an effort involving meteorological and hydrological scientists from research, operational, and user communities around the globe, is building a research project focused on advancing probabilistic hydrologic forecasting. HEPEX was launched in March 2004 at a meeting hosted by the European Centre for Medium-Range Weather Forecasts (ECMWF), in Reading, United Kingdom http://www.ecmwf.int/newsevents/meetings/workshops/2004/HEPEX/). The goal of HEPEX is “to bring the international hydrological and meteorological communities together to demonstrate how to produce reliable hydrological ensemble forecasts that can be used with confidence by the emergency management and water resources sectors to make decisions that have important consequences for the economy, public health, and safety.”

Changes in water consumption linked to heavy news media coverage of extreme climatic events

Media-related public awareness of extreme drought in California is linked to changes in urban water use behavior. Public awareness of water- and drought-related issues is an important yet relatively unexplored component of water use behavior. To examine this relationship, we first quantified news media coverage of drought in California from 2005 to 2015, a period with two distinct droughts; the later drought received unprecedentedly high media coverage, whereas the earlier drought did not, as the United States was experiencing an economic downturn coinciding with a historic presidential election. Comparing this coverage to Google search frequency confirmed that public attention followed news media trends. We then modeled single-family residential water consumption in 20 service areas in the San Francisco Bay Area during the same period using geospatially explicit data and including news media coverage as a covariate. Model outputs revealed the factors affecting water use for populations of varying demographics. Importantly, the models estimated that an increase of 100 drought-related articles in a bimonthly period was associated with an 11 to 18% reduction in water use. Then, we evaluated high-resolution water consumption data from smart meters, known as advanced metering infrastructure, in one of the previously modeled service areas to evaluate breakpoints in water use trends. Results demonstrated that whereas nonresidential commercial irrigation customers responded to changes in climate, single-family residential customers decreased water use at the fastest rate following heavy drought-related news media coverage. These results highlight the need for water resource planners and decision makers to further consider the importance of effective, internally and externally driven, public awareness and education in water demand behavior and management.

Coordinating water conservation efforts through tradable credits: A proof of concept for drought response in the San Francisco Bay area

Water utilities are increasingly relying on water efficiency and conservation to extend the availability of supplies. Despite spatial and institutional inter-dependency of many utilities, these demand-side management initiatives have traditionally been tackled by individual utilities operating in isolation. In this study, we introduce a policy framework for water conservation credits that enables collaboration at the regional scale. Under the proposed approach, utilities have the flexibility to invest in water conservation measures that are appropriate for their specific service area. When utilities have insufficient capacity for local cost-effective measures, they may opt to purchase credits, contributing to fund subsidies for utilities that do have that capacity and can provide the credits, while the region as a whole benefits from more reliable water supplies. This work aims to provide insights on the potential impacts of a water conservation credit policy framework when utilities are given the option to collaborate in their efforts. We model utility decisions as rational cost-minimizing actors subject to different decision-making dynamics and water demand scenarios, and demonstrate the institutional characteristics needed for the proposed policy to be effective. We apply this model to a counterfactual case study of water utility members of the Bay Area Water Supply and Conservation Agency in California during the drought period of June 2015 to May 2016. Our scenario analysis indicates that, when the institutional structure and incentives are appropriately defined, water agencies can achieve economic benefits from collaborating in their conservation efforts, especially if they coordinate more closely in their decision-making.

Accelerating the Integration of Distributed Water Solutions: A Conceptual Financing Model from the Electricity Sector

Modern challenges require new approaches to urban water management. One solution in the portfolio of potential strategies is the integration of distributed water infrastructure, practices, and technologies into existing systems. However, many practical barriers have prevented the widespread adoption of these systems in the US. The objective of this paper is to address these challenges by developing a conceptual model encompassing regulatory, financial, and governance components that can be used to incorporate new distributed water solutions into our current network. To construct the model, case studies of successfully implemented distributed electricity systems, specifically energy efficiency and renewable energy technologies, were examined to determine how these solutions have become prominent in recent years and what lessons can be applied to the water sector in a similar pursuit. The proposed model includes four action-oriented elements: catalyzing change, establishing funding sources, using resource pathways, and creating innovative governance structures. As illustrated in the model, the water sector should use suite of coordinated policies to promote change, engage end users through fiscal incentives, and encourage research, development and dissemination of new technologies over time.

A case-study based framework for assessing the multi-sector performance of green infrastructure

Green infrastructure is emerging as a holistic stormwater management strategy that can also provide multi-sector benefits. Robust demonstration of project success can help leverage the appeal of green infrastructure to different sectors and open the door to a variety of funding opportunities. Yet comprehensively assessing the performance of these natural systems can be challenging, especially when communicating the benefits to a wide variety of stakeholders. A cohesive, well-described assessment structure may promote a higher degree of investor confidence by more comprehensively monitoring and measuring green infrastructure success. This paper develops a conceptual framework that incorporates a robust assessment component for communicating with potential investors through the inclusion of multiple evaluation methods, performance metrics, and risk categories. The applied performance of this framework is then validated using fourteen U.S. and international case studies. We found that our framework fit a wide range of projects while maintaining a degree of flexibility that did not sacrifice specificity when applied to individual case studies. This suggests that: 1) some GI projects already incorporate one or more evaluation methods; 2) a number of highly specific metrics-particularly social and economic performance metrics-exist that are capable of capturing a wide-range of benefits that can be easily integrated into a framework; 3) the incorporation of risk and risk management technique identification could be emphasized to increase investor confidence; 4) at least some degree of standardization across projects exists already which can help future project implementers design GI strategies that best fit their needs.

A novel search algorithm for quantifying news media coverage as a measure of environmental issue salience

Abstract News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform model development or provide additional model inputs. This paper presents Articulate, an open-source, flexible tool for discovering, compiling, and quantifying newspaper coverage on a user-specified topic. Articulate is written in Python and interfaces with Google Custom Search Engine API. We demonstrate the tools application and validate its performance on two case studies of news media coverage in the New York Times about drought in California and flooding in Houston, Texas in recent years. Our results show that Articulate can generate data similar to or better than proprietary databases. Thus, Articulate can help researchers and environmental managers gain important insights to better understand and quantify changing socio-environmental dynamics.