MUNICIPAL WATER USE AND WATER RATES DRIVEN BY SEVERE DROUGHT: A CASE STUDY1

ABSTRACT: This paper synthesizes and interprets data pertaining to the evolution of average water revenue, water use, and the average cost of water supply in the City of Santa Barbara, California, from 1986 to 1996, a period which included one of the most devastating droughts in California this century. The 1987–1992 drought hit the study area particularly hard. The City of Santa Barbara was dependent exclusively on local sources for its water supply. That made it vulnerable as the regional climate is prone to extreme variability and recurrent droughts. The 1986–1992 drought provided a rare opportunity to assess the sensitivity of municipal water use to pricing, conservation, and other water management measures under extreme drought conditions. Our analysis indicates that the average cost of water rose more than three-fold in real terms from 1986 to 1996, while the gap between the average cost of supply and the average revenue per unit of water (= 100 cubic feet) rose in real terms from $0.14 in 1986 to $ 0.75 in 1996. The rise of $3.08 in the average cost of supplying one unit of water between 1986 and 1996 measures the cost of hedging drought risk in the study area. Water use dropped 46 percent at the height of the drought relative to pro-drought water use, and remains at 61 percent of the pre-drought level. The data derived from the 1987–1992 California drought are unique and valuable insofar as shedding light on drought/water demand adaptive interactions. The experience garnered on drought management during that unique period points to the possibilities available for future water management in the Arid West where dwindling water supplies and burgeoning populations are facts that we must deal with.     

IMPLICATIONS OF C.A.R.E. VS. SOUTHVIEW FARM ON THE U.S. LIVESTOCK AND POULTRY INDUSTRY1

ABSTRACT: On May 19, 1993, a jury in the U.S. District Court for the Western District of New York found Southview Farm and Richard H. Popp guilty of violating the Clean Water Act on five occasions. The violations were the result of storm water runoff from a site used for disposal of dairy cattle manure from an unpermitted concentrated animal feeding operation. The presiding District Court judge later dismissed the jury verdict, and subsequently a U.S. Court of Appeals for the Second Circuit reversed the dismissal. The Court of Appeals concluded that the discharges were not exempt as agricultural storm water discharges, and that the manure spreaders involved were point sources. Because the use of animal manures in crop production activities will result, unavoidably, in the discharge of some pollutants to adjacent surface waters, a rational and universally applicable basis is needed to determine when such discharges are point versus nonpoint source. Current statutes and regulations do not delineate clearly such a boundary. To address this lack of specificity, I propose that application rates be based on recommended crop nutrient needs.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.     

Use of decision analysis interviews to support the sustainable use of the forests in Finnish Upper Lapland

Controversy between alternative uses of forests in Finnish Upper Lapland has been going on for decades, and in recent years it has been escalated to a serious conflict. The core of the conflict is the adverse impacts of forestry on old forests which are important grazing areas for reindeer and which are regarded as intact nature and wilderness areas. This paper describes the experiences of applying multi-criteria decision analysis interview approach on this conflict. The approach provides tools for structuring the problem and preferences of the stakeholders as well as for analyzing the effects of different alternatives in a common framework. We focus on the practical experiences gained from the application of this approach in this context. Multi-criteria decision analysis was found to be a useful approach to evaluate the economic, ecological and cultural aspects of this intense conflict. The obtained experiences also support the view that the approach works best when tightly integrated into the planning process.     

A resilience-based approach for comparing expert preferences across two large-scale coastal management programs

This report proposes a method for assessing resilience-building components in coastal social–ecological systems. Using the proposed model, the preferences of experts in Masan Bay (South Korea) and Puget Sound (USA) are compared. A total of 30 management objectives were determined and used to build a hierarchic tree designed using the principles of the Analytic Hierarchy Process (AHP). Surveys were performed with 35 Puget Sound experts using face-to-face interviews and with 28 Masan Bay experts by mail. The results demonstrate that the legal objective, which enables legislation, was the highest preferred component in both regions. The knowledge translation variable was also given a high preference score in both regions. An analysis of variance (ANOVA) showed that the Puget Sound experts significantly favored attention to education, habitat restoration and species protection objectives in comparison to the Masan Bay experts. The Masan Bay experts placed greater emphasis on legislation and the type of institutional design than did the Puget Sound experts. Using cluster analysis, four distinct groups of respondents were independently identified in Puget Sound and three groups were identified in Masan Bay. One unique subgroup in the Puget Sound experts group, which was characterized by its high preferences for habitat restoration and species protection, was not observed in Masan Bay. Demographic variables (length of career and role in coastal issue) failed to account for the differences in groupings and preferences in either region, except for the variable ‘favoring information source’ in the Puget Sound group. This finding implies that the demographic information was not related to differences in group opinions in both regions. The analysis framework presented here was effective in identifying expert preferences regarding the overall structure and emphasis in coastal management programs. Thus, this framework can be applied towards coastal policy development.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Adaptive management for a turbulent future

The challenges that face humanity today differ from the past because as the scale of human influence has increased, our biggest challenges have become global in nature, and formerly local problems that could be addressed by shifting populations or switching resources, now aggregate (i.e., "scale up") limiting potential management options. Adaptive management is an approach to natural resource management that emphasizes learning through management based on the philosophy that knowledge is incomplete and much of what we think we know is actually wrong. Adaptive management has explicit structure, including careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. It is evident that adaptive management has matured, but it has also reached a crossroads. Practitioners and scientists have developed adaptive management and structured decision making techniques, and mathematicians have developed methods to reduce the uncertainties encountered in resource management, yet there continues to be misapplication of the method and misunderstanding of its purpose. Ironically, the confusion over the term "adaptive management" may stem from the flexibility inherent in the approach, which has resulted in multiple interpretations of "adaptive management" that fall along a continuum of complexity and a priori design. Adaptive management is not a panacea for the navigation of 'wicked problems' as it does not produce easy answers, and is only appropriate in a subset of natural resource management problems where both uncertainty and controllability are high. Nonetheless, the conceptual underpinnings of adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex social-ecological systems, but management decisions must still be made, and whenever possible, we should incorporate learning into management.     

ARE RURAL RESIDENTS WILLING TO PAY ENOUGH TO IMPROVE DRINKING WATER QUALITY?1

ABSTRACT: The concentrations of iron and sulfate in community water supplies are a concern for a number of areas in southwestern Minnesota. This study used the contingent valuation method to determine how much consumers would be willing to pay to improve their drinking water quality. On average, individuals were willing to pay US$5.25 per month (in 1995 U.S. dollars) to reduce the level of iron and US$4.33 per month to reduce the level of sulfate in their water to the USEPA's secondary standards for drinking water quality. Respondents with negative perceptions of their drinking water quality were willing to pay more to improve water quality. The aggregate annual willingness to pay (WTP) for all consumers in community water systems in southwestern Minnesota that were out of compliance with water quality standards were estimated to be US$2.4 million and US$2.0 million (in 1995 dollars) for reducing the levels of iron and sulfate, respectively. Yet the total WTP of consumers who use small community water systems may not be enough to pay the full cost of providing improved water in those systems. Economies of scale in water treatment and difficulties in financing improvements mean that technical innovation, government assistance, or institutional changes may be needed to improve water quality in these areas.     

Using Multicriteria Methods in Environmental Planning and Management

In environmental planning and decision processes several alternatives are analyzed in terms of multiple noncommensurate criteria, and many different stakeholders with conflicting preferences are involved. Based on our experience in real-life applications, we discuss how multicriteria decision aid (MCDA) methods can be used successfully in such processes. MCDA methods support these processes by providing a framework for collecting, storing, and processing all relevant information, thus making the decision process traceable and transparent. It is therefore possible to understand and explain why, under several conflicting preferences, a particular decision was made. The MCDA framework also makes the requirements for new information explicit, thus supporting the allocation of resources for the process.     

DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA1

ABSTRACT: A methodology for obtaining the optimal design value to allow for sediment storage in a reservoir is presented for the situation where no data on sediment loads in the incoming streams are available. Information concerning the amount of sediment delivered to the reservoir over its life-time is obtained by a sediment yield model which uses data on rainfall amount and duration obtained from a nearby experimental watershed. Bayesian Decision Theory is used to obtain the optimal storage requirements in order to consider the natural variation of rainfall and the sampling error due to the short rainfall record available. The normally difficult calculations involved were made tractable by the use of simplifications and approximations valid in the context of the problem. Results show that sediment storage requirements can be calculated in this manner and that consideration of the uncertainties involved leads to a storage requirement substantially larger than that calculated without such consideration.