1,721,068 research outputs found
Fostering cooperation in power asymmetrical water systems by the use of direct release rules and index-based insurance schemes
No full textIn river basin systems, power asymmetry is often responsible of inefficient and unbalanced water allocations. Climate change and anthropogenic pressure will possibly exacerbate such disparities as the dominant party controls an increasingly limited shared resource. In this context, the deployment of cooperation mechanisms giving greater consideration to a balanced distribution of the benefits, while improving system-wide efficiency, may be desirable. This often implies the intervention of a third party (e.g., the river basin water authority) imposing normative constraints (e.g., a minimum release) on the party in the dominant position. However, this imposition will be more acceptable to the dominant party if coupled with some form of compensation. For a public agency, compensation may be burdensome, especially when the allowance is triggered by natural events whose timing and magnitude are highly uncertain. In this context, index-based insurance contracts may represent a viable alternative and reduce the cost of achieving socially desirable outcomes. In this paper, we develop a hybrid cooperation mechanism composed of i) a direct normative constraint imposed by a regulator, and ii) an indirect financial tool, an index-based insurance contract, to be used as a compensation measure. The approach is developed for the Lake Como multi-purpose water system, Italy: a complex Alpine river basin, supporting several hydropower reservoirs and finally flowing into a regulated lake which supplies water to several downstream uses, mostly irrigated agriculture. The system is characterized by a manifest geographic power asymmetry: the upstream hydropower companies are free to release their stored water in time irrespective of the timing of the downstream demands. This situation can lead to financial losses by the downstream users and undesirable social outcomes. Results suggest that financial instruments may offer a reliable and relatively inexpensive alternative to other forms of compensation, and thereby favor more balanced management of multi-purpose water systems characterized by power asymmetry. This finding is especially relevant in times when granting of licenses to use/withdrawal water are often being reviewed with attention to environmental protection and equity issues
Designing and assessing weather-based financial hedging contracts to mitigate water conflicts at the river basin scale. A case study in the Italian Alps
No full textGrowing water demands and more frequent and severe droughts are increasingly challenging water management in many regions worldwide, exacerbating water disputes and reducing the space for negotiated agreements at the catchment scale. In the lack of a centralized controller, the design and deployment of coordination and/or regulatory mechanisms is a way to improve system-wide efficiency while preserving the distributed nature of the decision making setting, and facilitating cooperation among institutionally independent decision-makers. Recent years have witnessed an increased interest in index-based insurance contracts as mechanisms for sharing hydro-meteorological risk in complex and heterogeneous decision making context (e.g. multiple stakeholders and institutionally independent decision makers). In this study, we explore the potential for index-based insurance contracts to mitigate the conflict in a water system characterized by (political) power asymmetry between hydropower companies upstream and farmers downstream. The Lake Como basin in the Italian Alps is considered as a case study. We generated alternative regulatory mechanisms in the form of minimum release constraints to the hydropower facilities, and designed an insurance contract for hedging against hydropower relative revenue losses. The fundamental step in designing this type of insurance contracts is the identification of a suitable index, which triggers the payouts as well as the payout function, defined by strike level and slope (e.g., euros/index unit). A portfolio of index-based contracts was designed for the case study and evaluated in terms of revenue floor, basis risk and revenue fluctuation around the mean, both with and without insurance. Over the long term, the insurance proved to be capable to keep the minimum revenue above a specified level while providing a greater certainty on the revenue trend. This result shows the possibility to augment farmer's supply with little loss for hydropower companies, thus helping in mitigating the conflict between the stakeholders
Microbial partitioning in urban stormwaters
Full text linkContamination by high concentrations of fecal indicator bacteria has been identified as one of the most common causes of surface water quality impairment in the United States; however, there is currently very little quantitative data available for use in designing watershed restoration plans that detail microbial transport in receiving waters. In this study, association with settleable particles (partitioning), a behavior frequently neglected in water quality models that can affect in-stream fate and transport, is more thoroughly characterized through the analysis of samples from several watersheds. Results suggest that while intermittent, stormwater flows contribute the majority of indicator organism inputs to receiving waters, as cumulative storm loadings can be equal to several years' worth of equivalent background loadings. Loadings of microorganisms associated with settleable particles appear to be largely transported in the initial first flush of storm events. Observations of particle association by fecal indicator bacteria appear to be a reasonable approximation of the partitioning behavior of Salmonella; however, Salmonella bacteria, as well as the protozoan pathogens Cryptosporidium and Giardia, were readily recoverable from samples meeting current water quality standards. Monitoring data from two suburban detention basins suggest that settleable indicator organisms and Salmonella are removed at a higher rate than their free-phase counterparts, indicating that sedimentation may be an important microbial removal mechanism in stormwater treatment structures. However, despite mean removals by one pond near the USEPA's typical rate of 65%, effluent concentrations remained several orders of magnitude greater than recommended levels. Comparisons of free phase and settleable E. coli concentrations as measured by a culture-based technique and the quantitative polymerase chain reaction (qPCR) may support previous studies suggesting that particle association reduces cell die-off in addition to accelerating sedimentation in the water column, although further investigation of potential inhibition of the PCR reaction is required. Despite significant differences between enumeration techniques in free phase E. coli concentrations, measures of total concentration were equivalent and produced similar conclusions regarding water body impairment. Regardless of detection method or indicator organism used in assessment, compiled data indicate that all four study watersheds will be in violation of recommended standards following storm events
Probability-based Approaches for Incorporating Uncertainty into Water Resource Models
Full text linkUncertainty in information used to make decisions is unavoidable; however it can be reduced by integrating information from multiple sources, and model techniques incorporating uncertainty and variability can produce more useful probabilistic outcome estimates. This work demonstrates the use of methods for decreasing uncertainty and for using probabilistic outcome data effectively in understanding the water quality and quantity in the Catawba River system in western North Carolina. Sparse monitoring data and error inherent in water quality models makes the identification of waters not meeting regulatory standards difficult. This work uses the Bayesian Maximum Entropy (BME) method of modern geostatistics to integrate water quality monitoring data together with model predictions to determine the likely status of a water (i.e. impaired or not impaired) and to estimate the level of monitoring needed to characterize the water for regulatory purposes. Although the model predictions used to augment the measured data has a high degree of uncertainty, their inclusion reduces the uncertainty in chlorophyll a estimates enough that the likely impairment status of all sections in all but one reservoir can be determined. For the remaining reservoir, probabilistic predictions of future chlorophyll levels are used to illustrate how monitoring costs can be reduced using a BME framework. Rainfall-inflow models used for analyzing water availability often have complex forms that can inhibit a thorough analysis of uncertainty in model results because of long model run times and the large number of parameters that are not known with precision. This work demonstrates a rainfall-inflow model that uses reduced spatial and temporal resolution to facilitate model construction and to allow for a robust assessment of model uncertainty. Uncertainty is captured in 2000 116-year inflow scenarios generated using Markov Chain Monte Carlo methods and scenario-specific estimates of model residual error. These scenarios were incorporated into a multi-reservoir management model. Although the median system behavior agrees with prior work that did not include uncertainty, including a distribution of possible outcomes results in a doubling of the estimate of the number of times reservoirs fall below target minimum levels and an increase in the likelihood of reaching critical levels
Dynamic Hydrologic Economic Modeling of Tradeoffs in Hydroelectric Systems
Full text linkHydropower producers face a future beset by unprecedented changes in the electric power industry, including the rapid growth of installed wind power capacity and a vastly increased supply of natural gas due to horizontal hydraulic fracturing (or fracking). There is also increased concern surrounding the potential for climate change to impact the magnitude and frequency of droughts. These developments may significantly alter the financial landscape for hydropower producers and have important ramifications for the environmental impacts of dams. Incorporating wind energy into electric power systems has the potential to affect price dynamics in electricity markets and, in so doing, alter the short-term financial signals on which dam operators rely to schedule reservoir releases. Chapter 1 of this doctoral dissertation develops an integrated reservoir-power system model for assessing the impact of large scale wind power integration of hydropower resources. Chapter 2 explores how efforts to reduce the carbon footprint of electric power systems by using wind energy to displace fossil fuel-based generation may inadvertently yield further impacts to river ecosystems by disrupting downstream flow patterns. Increased concern about the potential for climate change to alter the frequency and magnitude of droughts has led to growing interest in index insurance that compensates hydropower producers when values of an environmental variable (or index), such as reservoir inflows, crosses an agreed upon threshold (e.g., low flow conditions). Chapter 3 demonstrates the need for such index insurance contracts to also account for changes in natural gas prices in order to be cost-effective. Chapter 4 of this dissertation analyzes how recent low natural gas prices (partly attributable to fracking) have reduced the cost of implementing ramp rate restrictions at dams, which help restore sub-daily variability in river flows by limiting the flexibility of dam operators in scheduling reservoir releases concurrent with peak electricity demand.Doctor of Philosoph
Reducing the costs of meeting regional water supply reliability goals through risk-based water transfer agreements
Full text linkUrban growth and economic development have fueled concerns over meeting future water supply needs. Water transfers offer one method of addressing the growing scarcity by moderating the temporal and spatial inequities in water supply. Effective management of water transfers among inter-connected utilities requires well developed rules describing when and how much water will be transferred. The nature of the decision rules (e.g. agreement terms) used to manage water transfers impacts the amount of water transferred and capacity of the treatment and conveyance infrastructure required to execute the transfers. This study uses simulation to identify infrastructure-agreement combinations that provide high reliability at low cost. Three agreement types are evaluated: Take-or-Pay, Days of Supply Remaining (DSR), and Risk-of-Failure (ROF). Results show the DSR and ROF agreements reduce the volume of water transferred by nearly 60% and 80%, respectively, and translate into average cost savings of 41% and 49%, respectively, over Take-or-Pay agreements
Optimization of nonpoint source best management practices selection through a calibrated HSPF modeling approach
Full text linkNonpoint source pollution is the leading cause of in-stream water quality impairments, with pathogens alone responsible for more than 40% of all such impairments in North Carolina. Without a concerted effort to assess and manage these overland pollutant sources from a comprehensive approach, there will continue to be minimal progress toward finally realizing the goals of the Clean Water Act. This work addresses nonpoint source pollution through the development of a fully calibrated and validated Hydrological Simulation Program-FORTRAN model for Northeast Creek Watershed, as well as the creation of a linear optimization model for microbial nonpoint source Best Management Practice (BMP) selection. Based upon optimized model results, there would need to be an investment in structural and non-structural BMPs of over $20,000,000 throughout the course of the next twenty years in order for Northeast Creek to meet in-stream regulatory requirements
Analytical Tools for Integrating Transfers into Water Resource Management Strategies
Full text linkMany municipalities within the United States anticipate rising demand for water as populations grow. Traditionally, rising demand has often been addressed via infrastructure projects, such as reservoirs. However, a variety of factors has combined to make such projects less attractive, such as increased development costs, stricter environmental regulation, and greater public opposition. By contrast, transfers of water from existing sources can be used to more efficiently manage risk posed by rising demand, allowing water to be acquired on more of an as-needed basis. When developing transfer agreements, however, questions of timing, quantity, and type of transfers must be settled if transfers are to be effectively employed. Regional differences in water law, the nature of the available resources and the degree of hydrologic variability further determine how transfers might be applied. This research contributes to knowledge in three specific areas: (i) This work examines the manner in which different types of market-based transfers can be combined with firm capacity to form minimum expected cost "portfolios" of different transfer types (e.g., permanent rights, leases, options) that meet defined reliability and/or cost variability constraints. In doing so, a Monte Carlo simulation is paired with the "implicit filtering" optimization routine, designed to optimize portfolios despite the sampling error, or "noise", inherent in searching for an optimal expected value. (ii)The second phase of research applies a modified technique (control variate) to reduce the level of noise inherent in the simulation, thereby improving the efficiency and accuracy of the optimization approach. This method is applied to the study region as the simulation is expanded from a one-year to a 10-year model, and results in a significant reduction in computational burden (as much as 50%). (iii)A technique is developed to generate synthetic streamflow time series in a manner that reproduces autocorrelation in the historic record. This method is used to develop streamflow records representative of future climate scenarios, which are then used as inputs for a model that assesses different risk-based transfer agreements within the Research Triangle region of North Carolina. Results demonstrate that even minor changes in expected streamflows can significantly impact transfer activity and costs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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