REGIONAL SCALE MODELING OF SURFACE AND GROUND WATER INTERACTION IN THE SNAKE RIVER BASIN1

ABSTRACT: Changes in irrigation and land use may impact discharge of the Snake River Plain aquifer, which is a major contributor to flow of the Snake River in southern Idaho. The Snake River Basin planning and management model (SRBM) has been expanded to include the spatial distribution and temporal attenuation that occurs as aquifer stresses propagate through the aquifer to the river. The SRBM is a network flow model in which aquifer characteristics have been introduced through a matrix of response functions. The response functions were determined by independently simulating the effect of a unit stress in each cell of a finite difference groundwater flow model on six reaches of the Snake River. Cells were aggregated into 20 aquifer zones and average response functions for each river reach were included in the SRBM. This approach links many of the capabilities of surface and ground water flow models. Evaluation of an artificial recharge scenario approximately reproduced estimates made by direct simulation in a ground water flow model. The example demonstrated that the method can produce reasonable results but interpretation of the results can be biased if the simulation period is not of adequate duration.     

UN/ECE ICP Materials Dose-response Functions for the Multi-pollutant Situation

A “multi-pollutant exposure programme” reflecting the new pollution situation where SO₂ is no longer the dominating pollutant has been performed by the International Co-operative Programme on Effects on Materials, including Historic and Cultural Monuments (ICP Materials) within the activities of the Convention on Long-range Transboundary Air Pollution. The main results obtained in the period 1997–2003 are summarised. Dose-response functions are presented for carbon steel, zinc, copper, bronze and limestone. Parameters involved in the functions include besides SO₂ and pH, which were included in the previously developed functions from ICP Materials, also the effect of particulate matter and HNO₃.     

和声搜索算法参数的均匀设计

和声搜索算法的参数设置主要是依靠经验和试验来确定,造成试验工作量大且难以得到最优的参数组合,影响了算法的应用.文中通过将和声搜索算法参数设置问题描述成均匀设计中多因素、多水平的试验设计,从而能够用较少的试验很快设置算法参数的取值.仿真试验表明,利用均匀设计得到的参数组合可使算法获得较优的寻优性能,说明了该方法的可行性和有效性.     

Network inclusion probabilities and Horvitz-Thompson estimation for adaptive simple Latin square sampling

Consider a survey of a plant or animal species in which abundance or presence/absence will be recorded. Further assume that the presence of the plant or animal is rare and tends to cluster. A sampling design will be implemented to determine which units to sample within the study region. Adaptive cluster sampling designs Thompson (1990) are sampling designs that are implemented by first selecting a sample of units according to some conventional probability sampling design. Then, whenever a specified criterion is satisfied upon measuring the variable of interest, additional units are adaptively sampled in neighborhoods of those units satisfying the criterion. The success of these adaptive designs depends on the probabilities of finding the rare clustered events, called networks. This research uses combinatorial generating functions to calculate network inclusion probabilities associated with a simple Latin square sample. It will be shown that, in general, adaptive simple Latin square sampling when compared to adaptive simple random sampling will (i) yield higher network inclusion probabilities and (ii) provide Horvitz-Thompson estimators with smaller variability.     

Groundwater Monitoring Strategies for Variable Versus Constant Contaminant Loading Functions

Contaminant plumes were derived for constant and variable loading functions at locations within a landfill. Annually, the alternative loading functions injected the same volume of contaminated water. Mass transport modeling was used to evaluate the detection efficiencies of 25 monitoring transects, spaced evenly between the landfill and a downgradient compliance boundary. Respectively, the most efficient transects (requiring the fewest monitoring wells) for constant and variable loading were located at 60–64 and 40 percent of the distance to the compliance boundary. The mean detection efficiency was 29 percent higher for variable loading, but the variation in detection efficiency was similar for constant and variable loading. At the most efficient transects, the minimum number of detection wells was 20 percent lower for variable loading. Given the influence of source loading on monitoring efficiency, alternative loading functions should be considered when designing detection monitoring networks in aquifers.     

Hydrogen explosion incident mitigation in steam reforming units through enhanced inspection and forecasting corrosion tools implementation

Hydrogen (H₂) explosion effects recently examined, are confirming the devastating loss scenarios to humans, environment, assets, and associated business interruption. H₂ production is a core process in refineries used in further process steps. Steam reforming of natural gas or a mix with naphtha or LPG is a common hydrogen production technique, where the latest technologies have adopted enhanced metallurgies to minimize explosion risk and the associated maintenance cost following plant degradation owing to corrosion effects. However, corrosion rates are still high in specific areas of piping and process equipment. The aim of this paper is to present a methodology based on semi-quantitative RBI modeling according to regulations by API and recent EN standards, adopting a family of linear regression forecasting models that depict the yearly corrosion rate (per corrosion loop) of a hydrogen production steam reforming unit; this is done under different operating conditions (e.g., temperature, pressure, and fluid speed), metallurgy and other related physicochemical variables. The model is based on the examination of both ultrasonic wall thinning measurements and the examination of quantitative crosslinking total corrosion effects along with the physicochemical properties prevailing in different plant corrosion loops. The outcome of the regression analysis is an expansive family of multivariable equations describing, with a defined accuracy, the yearly corrosion rate and associated lifespan forecast per corrosion loop, and per examined part. These equations were further utilized in a custom-made database that can be used as an additional loss prevention tool by the hydrogen production unit management team. Evaluation results regarding the tool efficiency are presented in the following of this paper.     

A More Cost-Effective Emap Benthic Macrofaunal Sampling Protocol

Benthic macrofaunal sampling protocols in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) are to collect 30 to 50 random benthic macrofauna [defined as animals retained on a 0.5 mm (East and Gulf Coasts, USA) or a 1.0 mm mesh sieve (West Coast, USA)] samples per reporting unit using a 0.044 m² (East and Gulf Coasts) or 0.1 m² (West Coast) grab. Benthic macrofaunal community conditions in the reporting unit are characterized by cumulative distribution functions (CDFs) on end points of interest, such as number of species (S), abundance (A), and Shannon--Wiener diversity (H′). An EMAP and a companion field study were conducted concurrently in Tillamook Bay (Oregon, USA) to compare the cost effectiveness of benthic macrofauna samples collected using the EMAP West Coast (0.1 m² × ≥7 cm deep, 1.0 mm mesh), a 0.01 m² × 5 cm deep, 1.0 mm mesh, and a 0.01 m² × 5 cm deep, 0.5 mm mesh sampling protocol. Cost was estimated in relative laboratory sample-processing time. Sampling protocols were judged equally effective for EMAP purposes if, after linear transformation to adjust for scale changes in end point distributions, their S, A, and H′ CDFs were not significantly different. The 0.01 m² × 5 cm deep, 1.0 mm mesh sampling protocol was the most cost effective.     

Climate Impact Response Functions for Terrestrial Ecosystems

We introduce climate impact response functions as a means for summarizing and visualizing the responses of climate-sensitive sectors to changes in fundamental drivers of global climate change. In an inverse application, they allow the translation of thresholds for climate change impacts (‘impact guard-rails’) into constraints for climate and atmospheric composition parameters (‘climate windows’). It thus becomes feasible to specify long-term objectives for climate protection with respect to the impacts of climate change instead of crude proxy variables, like the change in global mean temperature. We apply the method to assess impacts on terrestrial ecosystems, using the threat to protected areas as the central impact indicator. Future climate states are characterized by geographically and seasonally explicit climate change patterns for temperature, precipitation and cloud cover, and by their atmospheric CO₂ concentration. The patterns are based on the results of coupled general circulation models. We study the sensitivity of the impact indicators and the corresponding climate windows to the spatial coverage of the analysis and to different climate change projections. This enables us to identify the most sensitive biomes and regions, and to determine those factors which significantly influence the results of the impact assessment. Based on the analysis, we conclude that climate impact response functions are a valuable means for the representation of climate change impacts across a wide range of plausible futures. They are particularly useful in integrated assessment models of climate change based on optimizing or inverse approaches where the on-line simulation of climate impacts by sophisticated impact models is infeasible due to their high computational demand. This revised version was published online in July 2006 with corrections to the Cover Date.     

A Critical Review of Assumptions About the Prairie Dog as a Keystone Species

Cynomys spp.) have been labeled as keystone species because of their influence on biological diversity and ecosystem function. However, the validity of several assumptions used to support keystone status is questionable. We review the strength of the evidence and the magnitude of the prairie dog's effects on ecosystem structure and function. We use this review to reevaluate the keystone role for prairie dogs. Our goal is to encourage sound management of the prairie dog ecosystem by improving the ecological foundation of their keystone status. Our review confirms that prairie dogs affect a number of ecosystem-level functions but that their influence on prairie vertebrates may be less than previously suggested. Species richness and abundance patterns were variable among plants, mammals, and birds and were not consistently higher on prairie dog colonies compared to uncolonized areas. In addition, only nine of the 208 species listed in the literature as observed on or near prairie dogs colonies had quantitative evidence of dependence on prairie dogs. Abundance data indicated opportunistic use of colonies for an additional 20 species. A total of 117 species may have some relationship with prairie dogs, but we lacked sufficient data to evaluate the strength of this relationship. The remaining 62 species may be accidental or alien to the system. Despite our conclusion that some prairie dog functions may be smaller than previously assumed, collectively these functions are quite large compared to other herbivores in the system. We suggest that prairie dogs also provide some unique functions not duplicated by any other species and that continued decline of prairie dogs may lead to a substantial erosion of biological diversity and landscape heterogeneity across prairie and shrub-steppe landscapes. Thus, we concur that keystone status for prairie dogs is appropriate and may aid conservation efforts that help protect species dependent on prairie dogs and support other important ecosystem functions.