A Framework for Assessing Climate Change Impacts on Water and Watershed Systems

In this article we present a framework for assessing climate change impacts on water and watershed systems to support management decision-making. The framework addresses three issues complicating assessments of climate change impacts—linkages across spatial scales, linkages across temporal scales, and linkages across scientific and management disciplines. A major theme underlying the framework is that, due to current limitations in modeling capabilities, assessing and responding to climate change should be approached from the perspective of risk assessment and management rather than as a prediction problem. The framework is based generally on ecological risk assessment and similar approaches. A second theme underlying the framework is the need for close collaboration among climate scientists, scientists interested in assessing impacts, and resource managers and decision makers. A case study illustrating an application of the framework is also presented that provides a specific, practical example of how the framework was used to assess the impacts of climate change on water quality in a mid-Atlantic, U.S., watershed.     

Mercury cycling and species mass balances in four North American lakes

A mass balance model for mercury based on the fugacity concept is applied to Lake Superior, Lake Michigan, Onondaga Lake and Little Rock Lake to evaluate model performance, analyze cycling of three mercury species groups (elemental, divalent and methyl mercury), and identify important processes that determine the source-to-concentration relationship of the three mercury species groups in these lakes. This model application to four disparate ecosystems is an extension of previous applications of fugacity-based models describing mercury cycling. The model performs satisfactorily following site-specific parameterization, and provides an estimate of minimum rates of species interconversion that compare well with literature. Volatilization and sediment burial are the main processes removing mercury from the lakes, and uncertainty analyses indicate that air-water exchange of elemental mercury and water-sediment exchange of divalent mercury attached to particles are influential in governing mercury concentrations in water. Any new model application or field campaign to quantify mercury cycling in a lake should consider these processes as important.     

Flood inundation uncertainty: The case of a 0.5% annual probability flood event

Aging coastal defences around the UK are challenging managers to redesign schemes to be resilient to extreme events and climate change, be cost-effective, and have minimal or beneficial environmental impact. To enable effective design, reduced uncertainty in the assessment of flood risk due to natural variability within the coastal forcing is required to focus on conditions that pose highest threat. The typical UK standard of protection for coastal defences is to withstand a 0.5% annual probability event, historically also known as a 1 in 200 year return period event. However, joint wave-water level probability curves provide a range of conditions that meet this criterion. We examine the Dungeness and Romney Marsh coastal zone, a region of high value in terms of habitat and energy assets, to quantify the uncertainty in flood depth and extent generated by a 0.5% probability event, and to explore which combinations of wave and water levels generate the greatest threat.     

Toward Integrative Management Advice of Water Quality, Oil Spills, and Fishery in the Gulf of Finland: A Bayesian Approach

Understanding and managing ecosystems affected by several anthropogenic stressors require methods that enable analyzing the joint effects of different factors in one framework. Further, as scientific knowledge about natural systems is loaded with uncertainty, it is essential that analyses are based on a probabilistic approach. We describe in this article about building a Bayesian decision model, which includes three stressors present in the Gulf of Finland. The outcome of the integrative model is a set of probability distributions for future nutrient concentrations, herring stock biomass, and achieving the water quality targets set by HELCOM Baltic Sea Action Plan. These distributions can then be used to derive the probability of reaching the management targets for each alternative combination of management actions.     

Inexact rough-interval two-stage stochastic programming for conjunctive water allocation problems

An inexact rough-interval two-stage stochastic programming (IRTSP) method is developed for conjunctive water allocation problems. Rough intervals (RIs), as a particular case of rough sets, are introduced into the modeling framework to tackle dual-layer information provided by decision makers. Through embeding upper and lower approximation intervals, rough intervals are capable of reflecting complex parameters with the most reliable and possible variation ranges being identified. An interactive solution method is also derived. A conjunctive water-allocation system is then structured for characterizing the proposed model. Solutions indicate a detailed optimal allocation scheme with a rough-interval form; a total of [[1048.83, 2078.29]:[1482.26, 2020.60]] would be obtained under the pre-regulated inputs. Comparisons of the proposed model to a conventional and an interval two-stage stochastic programming model are also conducted. The results indicate that the optimal objective function values of TSP and ITSP always fall into the range of , while they are sometimes out of the range of ; the optimal solutions of decision variables also present this feature. This implies the reliability of IRTSP in handling conjunctive water allocation problems.     

Best policy response to environmental shocks: Applying a stochastic framework

The paper develops a general framework for the analysis of environmental shocks in growing economies. Endogenous capital investments allow identifying the dual role of capital as a buffer against shocks and a source of pollution. We study the effects of recurring natural disasters on optimal growth and efficient environmental policies. Emissions may cause continuous fluctuations, entail discrete and recurring jumps, or trigger so-called “tipping points” with large costs to the economy. Closed-form solutions are provided for all the model variants. We discuss possible applications in environmental economics and identify current research gaps.     

Incorporating uncertainty in a chemical leaching assessment

Pesticide leaching models are being used to assist in the regulation and management of pesticides by indicating their potential for leaching to groundwater. Uncertainty in model input data is not, regrettably, included in most pesticide leaching assessments. In the work described here, we use logarithmic transformations of the attenuation factor (AF), a simple process-based index model, to represent uncertainty in a pesticide leaching assessment. Characterization of a wide range of pesticides as `leachers' or `non-leachers' for a specific Hawaii hydrogeological setting is facilitated by comparing the log-transformed AF, designated AFR, for each chemical with two reference chemicals for which leaching behavior in Hawaii is known. Defining a mean and uncertainty interval for the AFR index of each chemical being ranked provides a practical method of incorporating data uncertainty into a regulatory protocol.     

Estimate of the uncertainty in measurement for the determination of mercury in seafood by TDA AAS

An approach for the estimate of the uncertainty in measurement considering the individual sources related to the different steps of the method under evaluation as well as the uncertainties estimated from the validation data for the determination of mercury in seafood by using thermal decomposition/amalgamation atomic absorption spectrometry (TDA AAS) is proposed. The considered method has been fully optimized and validated in an official laboratory of the Ministry of Agriculture, Livestock and Food Supply of Brazil, in order to comply with national and international food regulations and quality assurance. The referred method has been accredited under the ISO/IEC 17025 norm since 2010. The approach of the present work in order to reach the aim of estimating of the uncertainty in measurement was based on six sources of uncertainty for mercury determination in seafood by TDA AAS, following the validation process, which were: Linear least square regression, Repeatability, Intermediate precision, Correction factor of the analytical curve, Sample mass, and Standard reference solution. Those that most influenced the uncertainty in measurement were sample weight, repeatability, intermediate precision and calibration curve. The obtained result for the estimate of uncertainty in measurement in the present work reached a value of 13.39%, which complies with the European Regulation EC 836/2011. This figure represents a very realistic estimate of the routine conditions, since it fairly encompasses the dispersion obtained from the value attributed to the sample and the value measured by the laboratory analysts. From this outcome, it is possible to infer that the validation data (based on calibration curve, recovery and precision), together with the variation on sample mass, can offer a proper estimate of uncertainty in measurement.     

Probabilistic distribution coefficients (Kds) in freshwater for radioisotopes of Ag,Am, Ba,Be, Ce,Co, Cs,I, Mn,Pu, Ra,Ru, Sb,Sr and Th – implications for uncertainty analysis of models simulating the transport of radionuclides in rivers

The objective of this study was to provide operational probability density functions (PDFs) for distribution coefficients (K_ds) in freshwater, representing the partition of radionuclides between the particulate and the dissolved phases respectively. Accordingly, the K_d variability should be considered in uncertainty analysis of transport and risk assessment models. The construction of PDFs for 8 elements (Ag, Am, Co, Cs, I, Mn, Pu and Sr) was established according to the procedure already tested in Durrieu et al. [2006. A weighted bootstrap method for the determination of probability density functions of freshwater distribution coefficients (K_ds) of Co, Cs, Sr and I radioisotopes. Chemosphere 65 (8), 1308–1320]: (i) construction of a comprehensive database where K_ds values obtained under various environments and parametric conditions were collected; (ii) scoring procedure to account for the ‘quality’ of each datapoint (according to several criteria such as the presentation of data (e.g. raw data vs mean with or without replicates), contact time, pH, solid-to-liquid ratio, expert judgement) in the construction of the PDF; (iii) weighted bootstrapping procedure to build the PDFs, in order to give more importance to the most relevant datapoints. Two types of PDFs were constructed: (i) non-conditional, usable when no knowledge about the site of concern is available; (ii) conditional PDFs corresponding to a limited range of parameters such as pH or contact time; conditional PDFs can thus be used when some parametric information is known on the site under study. For 7 other radionuclides (Ba, Be, Ce, Ra, Ru, Sb and Th), a simplified procedure was adopted because of the scarcity of data: only non-conditional PDFs were built, without incorporating a scoring procedure.     

Adaptation pathways in planning for uncertain climate change: Applications in Portugal,the Czech Republic and the Netherlands

Adaptation pathways are developed to design adaptive policies to handle climate change uncertainty. Use of this tool varies across planning practices and adaptation challenges and adjusting the tool to particular practices can foster its adequate use. To gain insight into the use of adaptation pathways, we compared four initiatives (one each in Portugal and the Czech Republic and two in the Netherlands) with regard to design choices made. We found six design choices which need to be considered when adjusting adaptation pathways. Design choices about the geographic scale, inclusion of sectors, the generation and delineation of adaptation options, specification of possible pathways, the related performance metrics and the type of assessment are interdependent, but they are also influenced by contextual aspects. Analysis of the institutional diversity, planning culture and framing shows that the use of adaptation pathways is flexible enough to be adjusted for diverging planning practices. However, the tool is best suited to deliver local adaptation solutions, and adequate use depends on consensus about the adaptation problem, setting objective thresholds and determining uncertainty about future change. We conclude that understanding the customised use of tools for local planning practices is essential for adaptive policy design.