A surge response function approach to coastal hazard assessment – part 1: basic concepts

This paper reviews historical methods for estimating surge hazards and concludes that the class of solutions produced with Joint Probability Method (JPM) solutions provides a much more stable estimate of hazard levels than alternative methods. We proceed to describe changes in our understanding of the winds in hurricanes approaching a coast and the physics of surge generation that have required recent modifications to procedures utilized in earlier JPM studies. Of critical importance to the accuracy of hazard estimates is the ability to maintain a high level of fidelity in the numerical simulations while allowing for a sufficient number of simulations to populate the joint probability matrices for the surges. To accomplish this, it is important to maximize the information content in the sample storm set to be simulated. This paper introduces the fundamentals of a method based on the functional specification of the surge response for this purpose, along with an example of its application in the New Orleans area. A companion paper in this special issue (Irish et al. 2009) provides details of the portion of this new method related to interpolating/extrapolating along spatial dimensions.     

Multiobjective analysis of a public wellfield using artificial neural networks

As competition for increasingly scarce ground water resources grows, many decision makers may come to rely upon rigorous multiobjective techniques to help identify appropriate and defensible policies, particularly when disparate stakeholder groups are involved. In this study, decision analysis was conducted on a public water supply wellfield to balance water supply needs with well vulnerability to contamination from a nearby ground water contaminant plume. With few alternative water sources, decision makers must balance the conflicting objectives of maximizing water supply volume from noncontaminated wells while minimizing their vulnerability to contamination from the plume. Artificial neural networks (ANNs) were developed with simulation data from a numerical ground water flow model developed for the study area. The ANN-derived state transition equations were embedded into a multiobjective optimization model, from which the Pareto frontier or trade-off curve between water supply and wellfield vulnerability was identified. Relative preference values and power factors were assigned to the three stakeholders, namely the company whose waste contaminated the aquifer, the community supplied by the wells, and the water utility company that owns and operates the wells. A compromise pumping policy that effectively balances the two conflicting objectives in accordance with the preferences of the three stakeholder groups was then identified using various distance-based methods.     

An assessment of aquifer storage recovery using ground water flow models

Owing to increased demands on ground water accompanied by increased drawdowns, technologies that use recharge options, such as aquifer storage recovery (ASR), are being used to optimize available water resources and reduce adverse effects of pumping. In this paper, three representative ground water flow models were created to assess the impact of hydrogeologic and operational parameters/factors on recovery efficiency of ASR systems. Flow/particle tracking and solute transport models were used to track the movement of water during injection, storage, and recovery. Results from particle tracking models consistently produced higher recovery efficiency than the solute transport models for the parameters/properties examined because the particle tracking models neglected mixing of the injected and ambient water. Mixing between injected and ambient water affected recovery efficiency. Results from this study demonstrate the interactions between hydrogeologic and operational parameters on predictions of recovery efficiency. These interactions are best simulated using coupled numerical ground water flow and transport models that include the effects of mixing of injected water and ambient ground water.     

The practical use of simplicity in developing ground water models

The advantages of starting with simple models and building complexity slowly can be significant in the development of ground water models. In many circumstances, simpler models are characterized by fewer defined parameters and shorter execution times. In this work, the number of parameters is used as the primary measure of simplicity and complexity; the advantages of shorter execution times also are considered. The ideas are presented in the context of constructing ground water models but are applicable to many fields. Simplicity first is put in perspective as part of the entire modeling process using 14 guidelines for effective model calibration. It is noted that neither very simple nor very complex models generally produce the most accurate predictions and that determining the appropriate level of complexity is an ill-defined process. It is suggested that a thorough evaluation of observation errors is essential to model development. Finally, specific ways are discussed to design useful ground water models that have fewer parameters and shorter execution times.     

Multidecadal biological monitoring and abatement program\ assessing human impacts on aquatic ecosystems within the Oak Ridge Reservation in eastern Tennessee,USA

Human activities can be powerful drivers of ecosystem change within catchments. While most long-term catchment studies have been conducted at pristine sites, such studies are less common from sites more impacted by human activity. The Oak Ridge National Laboratory's Biological Monitoring and Abatement Program (BMAP) was developed in the mid-1980s to (1) assess compliance with environmental regulations, (2) identify causes of adverse ecological impacts, (3) provide data for human and ecological risk assessments, and (4) evaluate the effectiveness of remedial actions taken to mitigate the impacts of contaminants in soils, groundwater, and surface water by documenting ecological recovery on the Oak Ridge Reservation (ORR), a federally owned 33 476-acre site in eastern Tennessee, managed by the US Department of Energy. The ORR is composed of multiple watersheds containing many small to mid-size streams. BMAP uses an integrated approach for determining stream health; its databases include long-term seasonal records of contaminant concentrations in water and biota, data from aquatic toxicity testing, and surveys of macroinvertebrate and fish assemblages from impacted and reference streams. These long-term data provide valuable records of degradation and recovery in catchment ecosystems. Our objective here is to describe our study system and data series in order to increase awareness of the availability of these long-term data to the catchment science community.     

The effect of rate of change, variability, and extreme events on the pace of adaptation to a changing climate

When is it time to adopt different technologies, management strategies, and resource use practices as underlying climate change occurs? We apply risk and decision analysis to test hypotheses about the timing and pace of adaption in response to different profiles of climate change and extremes expressed as yield and income variation for a simulated dryland wheat farm in the United States Great Plains. Climate scenarios include gradual change with typical or increased noise (standard deviation), rapid and large change, and gradual change with extreme events stepped through the simulation. We test decision strategies that might logically be utilized by farmers facing a climate trend that worsens crop enterprise outcomes. Adaptation quickens with the rate of change, especially for decision strategies based on performance thresholds, but is delayed by larger climate variability, especially for decision strategies based on recognizing growing differential between adaptive and non-adaptive performance. Extreme events evoke adaptation sooner than gradual change alone, and in some scenarios extremes evoke premature, inefficient, adaptation.     

Middle to late Holocene initiation of the annual flood pulse in Tonle Sap Lake,Cambodia

Tonle Sap Lake, Cambodia, possesses one of the most productive inland fisheries in the world and is a vital natural resource for the country. The lake is connected to the Mekong River via the Tonle Sap River. Flow in the Tonle Sap River reverses seasonally, with water exiting the lake in the dry season and entering the lake during the summer monsoon. This flood pulse drives the lake’s biological productivity. We used Sr, Nd, and Pb isotopes and elemental concentrations in lake sediment cores to track changes in the provenance of deposits in Tonle Sap Lake. We sought to determine when the lake first began to receive water and sediment input via the Mekong River, which initiated flood pulse processes. The transition from a non-pulsing lake to the Mekong-connected system is marked by shifts to values of ⁸⁷Sr/⁸⁶Sr, ε_Nd, and ²⁰⁷Pb/²⁰⁴Pb that are characteristic of Mekong River sediments. In addition, magnetic susceptibility increased and sediment elemental composition changed. Elemental (P) measures point to enhanced phosphorus loading and C/N and isotope ratios of bulk organic matter indicate a shift to greater relative contribution of organic material from aquatic versus terrestrial environments, coinciding with the initiation of flood pulse processes. On the basis of radiocarbon dating in two cores, we estimate the initiation of the annual flood pulse occurred between ~4,450 and 3,910 cal year BP.