[1] Market prices contain information about supply and demand, the institutions that influence both these elements, and the operation of the market. Prices also allocate scarce resources to higher-valued uses. In this paper we analyze the price history of three water markets in the arid Southwest: Arizona's Central Arizona Project, Colorado's Colorado Big Thompson Project, and New Mexico's Middle Rio Grande Conservancy District. Using water transfers over 11 years, we estimate a simultaneous system of market equations, one for price and the other for quantity demanded. Comparison of the institutional characteristics of each market reveals that Colorado's market is well developed, with many trades and rising prices that respond to market conditions, and New Mexico's market is developing well, with lower prices, but showing some response to supply and demand factors. Arizona's market is the least developed, with few trades and very low prices. Our empirical findings support our claim that markets are becoming more efficient in these regions despite the considerable institutional and historical impediments to the evolution of water markets. Markets for Water[2] Faced with limited water supplies and ever increasing populations, all western states are looking for ways to allocate and manage their water more effectively. Although few would disagree that water is a commodity, water markets and related institutions have been slow to evolve because of a combination of inexperience and social and political resistance. There are many vested interests in the historical distribution of water rights and usage patterns of water in the western United States, and new interests are emerging all the time. Despite the most compelling arguments that water right markets will increase the efficiency with which this scarce and valuable resource is allocated, such a change necessitates a redistribution of rights and the associated wealth they represent. There is evidence, however, from the increasing number of water rights transfers that markets are emerging and will continue to develop to meet the needs of the region.[3] In principle, markets form to facilitate the efficient allocation of goods and services among producers and consumers. With relatively few, simple conditions, buyers and sellers pursuing their own self-interest will pay a single price that fully compensates sellers and provides the commodity to those who value it highest. Unfortunately, these simple conditions are rarely present in real world markets; however, markets can still achieve outcomes that are preferred and more efficient than without markets. While emerging water markets are often informal [Howe and Goemans, 2003, p.2], involve large institutional buyers such as municipalities or cities, and can be heavily institutionalized through regulation and legal machinations, the experience of markets reported in this study suggests that water rights prices are performing their dual role by providing information to buyers and sellers and encouraging the movement of w...

The current COVID-19 pandemic contains an unprecedented amount of uncertainty and variability and thus, there is a critical need for understanding of the variation documented in the biological, policy, sociological, and infrastructure responses during an epidemic to support decisions at all levels. With the significant asymptomatic spread of the virus and without an immediate vaccine and pharmaceuticals available, the best feasible strategies for testing and diagnostics, contact tracing, and quarantine need to be optimized. With potentially high false negative test results, infected people would not be enrolled in contact-trace programs and thus, may not be quarantined. Similarly, without broad testing, asymptomatic people are not identified and quarantined. Interconnected system dynamics models can be used to optimize strategies for mitigations for decision support during a pandemic. We use a systems dynamics epidemiology model along with other interconnected system models within public health including hospitals, intensive care units, masks, contact tracing, social distancing, and a newly developed testing and diagnostics model to investigate the uncertainties with testing and to optimize strategies for detecting and diagnosing infected people. Using an orthogonal array Latin Hypercube experimental design, we ran 54 simulations each for two scenarios of 10% and 30% asymptomatic people, varying important inputs for testing and social distancing. Systems dynamics modeling, coupled with computer experimental design and statistical analysis can provide rapid and quantitative results for decision support. Our results show that widespread testing, contacting tracing and quarantine can curtail the pandemic through identifying asymptomatic people in the population.

Decision makers, faced with highly complex alternatives for protecting our nation's critical infrastructures need to understand the consequences of policy and investment options before they enact solutions designed to prevent and mitigate disasters. An effective way to examine these tradeoffs is to use a computer simulation that integrates high level representations of each critical infrastructure, their interdependencies and reactions to a variety of potential disruptions.

The majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines. Numerous studies have developed optimization methods for design of these systems in order to minimize construction costs while meeting capacity requirements. Here, we formulate problems to optimize the operations of existing single liquid commodity pipeline systems subject to physical flow and pump engineering constraints. The objectives are to maximize the economic value created for users of the system and to minimize operating costs. We present a general computational method for this class of continuous, non‐convex nonlinear programs, and examine the use of pump operating settings and flow allocations as decision variables. The approach is applied to compute optimal operating regimes and perform engineering economic sensitivity analyses for a case study of a crude oil pipeline developed using publicly available data.

Pipelines perform a critical function in the petroleum business by transporting hydrocarbon commodities between oil fields, refineries, and consumer markets. We formulate an optimization problem for determining the optimal pumping modes and flow configuration for liquid pipeline operations. Based on requested flow rates and commodity prices submitted by users of the pipeline system, the system manager can solve an optimization problem to determine flow rates allocated to all customers, flows on each pipeline section, and pumps station operating settings in order to maximize economic value provided by a pipeline while adhering to limitations of pump machinery and the physics of fluid flow. In particular, the optimal solution will maximize the economic benefit for the pipeline transport network users and utilization of system capacity while also minimizing the energy expended in operation. This problem is nonconvex, and solutions are only guaranteed to be locally optimal. In this study we pose a mathematical optimization formulation with minimal modeling that captures the basic phenomena involved, and an algorithm based on general-purpose interior point optimization is proposed for efficient solution. We demonstrate our approach on a realistic case study based on a pipeline system in the United States.