COUNTY COMMISSIONERS' WATER KNOWLEDGE1

ABSTRACT: This study examines the social construction of county commissioners' knowledge about water. Factors that influence what commissioners know about water include each commissioner's personal characteristics, education, experience in natural resources management, involvement in policy making, and use and evaluation of various sources of information. This study focused on county commissioners representing rural, mixed, and urban counties in Arizona, Nevada, and Utah and collected data through mail surveys and interviews. County commissioners in the survey were well educated; however, few had taken college courses directly addressing technical, management, or legal aspects of water issues. Approximately one-third had direct experience in farming and ranching; nearly two-thirds indicated that farming and ranching played a major role in their communities. Respondents had experience with a broad range of water policy issues. In evaluating thirteen information sources in terms of their frequency of use, relevancy, and reliability, respondents assessed fellow commissioners and local government staff and managers most positively and nonprofit organizations most negatively. The media was also broadly rated as less relevant and reliable than other sources of information. The commissioners in the study expressed a high level of general concern about water issues and a strung preference for local sources of information.     

ESTIMATING THE BENEFITS OF PHOSPHORUS POLLUTION REDUCTIONS: AN APPLICATION IN THE MINNESOTA RIVER1

ABSTRACT: In order to make economically efficient decisions about water quality improvements, data on both the costs and benefits of these improvements is needed. However, there has been little research on the benefits of reducing phosphorus pollution which implies that policy decisions are not able to make the comparison of costs and benefits that is essential for economic efficiency. This research attempts to ameliorate this situation by providing an estimate of the benefits of a 40 percent reduction in phosphorus pollution in the Minnesota River. A 1997 mail survey gathered information on Minnesota residents'use of a recreational site on the Minnesota River, the Minnesota Valley National Wildlife Refuge, and their willingness to pay for phosphorus reductions in the Minnesota River. The random effects probit model used in this research to investigate household willingness to pay for phosphorus pollution reductions in the Minnesota River incorporates recent innovations in nonmarket valuation methodology by using both revealed and stated preference data. This model estimated annual household willingness to pay for phosphorus reductions in the Minnesota River at $140. These results may be used in combination with cost estimates to determine the economic efficiency of phosphorus clean up.     

Developing Nutrient Criteria for Streams: An Evaluation of the Frequency Distribution Method1

Abstract: The U.S. Environmental Protection Agency recommends two statistical methods to States and Tribes for developing nutrient criteria. One establishes a criterion as the 75th percentile of a reference‐population frequency distribution, the other uses the 25th percentile of a general‐population distribution; the U.S. Environmental Protection Agency suggests either method results in similar criteria. To evaluate each method, the Montana Department of Environmental Quality (MT DEQ) assembled data from STORET and other sources to create a nutrient general population. MT DEQ’s reference‐stream project provided reference population data. Data were partitioned by ecoregions, and by seasons (winter, runoff, and growing) defined for the project. For each ecoregion and season, nutrient concentrations at the 75th percentile of the reference population were matched to their corresponding concentrations in the general population. Additionally, nutrient concentrations from five regional scientific studies were matched to their corresponding reference population concentrations; each study linked nutrients to impacts on water uses. Reference‐to‐general population matches were highly variable between ecoregions, as nutrients at the 75th percentile of reference corresponded to percentiles ranging from the 4th to the 97th of the general population. In contrast, case studies‐to‐reference matches were more consistent, matching on average to the 86th percentile of reference, with a coefficient of variation of 13%.     

WATERSHED SCALE INVENTORY OF EXISTING RIPARIAN BUFFERS IN NORTHEAST MISSOURI USING GIS1

An observational study was conducted at the watershed scale using land cover (vegetation) data to assess the absence or presence of riparian buffers in three northeastern Missouri watersheds. Forests and grasslands lying within a 61 m (200 ft) parallel band directly adjacent to streams were considered “buffers” for improving or protecting water quality and were characterized according to their length, width, and vegetation type. Results indicated that riparian buffers were abundant throughout the watersheds but were typically narrow along first‐order and second‐order streams; in many cases they may not have been wide enough to provide adequate stream protection. At least 90 percent of all streams had buffer vegetation immediately adjacent to the streambanks, but as few as 31 percent of first‐order streams had buffers extending to 61 m from the stream on at least one side. On‐site evaluations are needed to determine the condition of these forests and grasslands and their ability to process nonpoint source pollutants. The results will be useful for providing natural resource managers with knowledge of current watershed conditions as well as in identifying specific locations for future conservation efforts within each watershed.     

Sensitivity of Thermal Habitat of a Trout Stream to Potential Climate Change,Wisconsin, United States1

Abstract: Airborne thermal remote sensing from four flights on a single day from a single‐engine airplane was used to collect thermal infrared data of a 10.47‐km reach of the upper East Branch Pecatonica River in southwest Wisconsin. The study uses a one‐dimensional stream temperature model calibrated with the longitudinal profiles of stream temperature created from the four thermal imaging flights and validated with three days of continuous stream temperature data from instream data loggers on the days surrounding the thermal remote‐sensing campaign. Model simulations were used to quantify the sensitivity of stream thermal habitat to increases in air and groundwater temperature and changes in base flow. The simulations indicate that stream temperatures may reach critical maximum thresholds for brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) mortality, particularly if both air temperature increases and base flow declines. The approach demonstrates that thermal infrared data can greatly assist stream temperature model validation due to its high spatial resolution, and that this spatially continuous stream temperature data can be used to pinpoint spatial heterogeneity in groundwater inflow to streams. With this spatially distributed data on thermal heterogeneity and base‐flow accretion, stream temperature models considering various climate change scenarios are able to identify thermal refugia that will be critical for fisheries management under a changing climate.     

MODEL ACCURACY IN SNOWMELT-RUNOFF FORECASTS EXTENDING FROM 1 TO 20 DAYS1

ABSTRACT: This paper examines the performance of snowmelt-runoff models in conditions approximating real-time forecast situations. These tests are one part of an intercomparison of models recently conducted by the World Meteorological Organization (WMO). Daily runoff from the Canadian snowmelt basin Illecille. waet (1155 km², 509–3150 m a.s.l.) was forecast for 1 to 20 days ahead. The performance of models was better than in a previous WMO project, which dealt with runoff simulations from historical data, for the following reasons: (1) conditions for models were more favorable than a real-time forecast situation because measured input data and not meteorological forecast inputs were distributed to the modelers; (2) the selected test basin was relatively easy to handle and familiar from the previous WMO project; and (3) all kinds of updating were allowed so that some models even improved their accuracy towards longer forecast times. Based on this experience, a more realistic follow-up project can be imagined which would include temperature forecasts and quantitative precipitation forecasts instead of measured data.     

Land-Use and Land-Cover Change in Montane Mainland Southeast Asia

This paper summarizes land-cover and land-use change at eight sites in Thailand, Yunnan (China), Vietnam, Cambodia, and Laos over the last 50 years. Project methodology included incorporating information collected from a combination of semiformal, key informant, and formal household interviews with the development of spatial databases based on aerial photographs, satellite images, topographic maps, and GPS data. Results suggest that land use (e.g. swidden cultivation) and land cover (e.g. secondary vegetation) have remained stable and the minor amount of land-use change that has occurred has been a change from swidden to monocultural cash crops. Results suggest that two forces will increasingly determine land-use systems in this region. First, national land tenure policies—the nationalization of forest lands and efforts to increase control over upland resources by central governments—will provide a push factor making it increasingly difficult for farmers to maintain their traditional swidden land-use practices. Second, market pressures—the commercialization of subsistence resources and the substitution of commercial crops for subsistence crops—will provide a pull factor encouraging farmers to engage in new and different forms of commercial agriculture. These results appear to be robust as they come from eight studies conducted over the last decade. But important questions remain in terms of what research protocols are needed, if any, when linking social science data with remotely sensed data for understanding human-environment interactions.     

QUALITY OF 1995 SPRING TOTAL DISSOLVED GAS DATA: COLUMBIA AND SNAKE RWERS1

ABSTRACT: The quality of the U.S. Army Corps of Engineers' (Corps) total dissolved gas (TDG) data base for the 1995 spring spill season was reviewed to determine the value of this information in real-time management decisions regarding river operations. We concluded that problems in transmitting, archiving, correcting and interpreting the records constitute significant sources of data anomalies that affect the accuracy and reliability of information necessary to manage spill and TDG in the Columbia and Snake rivers. The data base that was reviewed covers 25 selected Columbia and Snake river stations, and includes real-time TDG data needed to regulate spill operations to maintain gas levels within state water quality standards and to monitor effects on fish and aquatic life during the salmon migration season. A wide range of anomalies (daily averages missing or in error or based on incomplete records) was detected in more than one-third (37 percent) of the Corps' gas data base. Extreme anomalies (daily averages including errors and discontinuities for more than eight hours in a day) were found in 16 percent of the data base. The Fish Passage Center, also reviewed the Corps' data and reported an overall 33 percent incidence of anomalous days. Despite arriving at similar findings about the Corps' data base, we detected a 28 percent discrepancy in the type of data anomalies between our analyses. Real. time improvements in the quality of the dissolved gas data base are necessary to provide managers with a reliable product from this monitoring effort.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Managing for Desired Experiences and Site Preferences: The Case of Fee-Fishing Anglers

Fee-fishing involves paying a fee for the privilege of fishing a body of water where fish populations are enhanced by stocking fish. Past literature on this activity has focused more on the operation of the enterprise and management of the fish than the people and site characteristics. The objectives of the study were to profile anglers and describe their site/management preferences. This study utilized an on-site interview and mail-back questionnaire at fee-fishing establishments in West Virginia (n = 212). Factor analysis of desired recreation experiences yielded five factors: Experience nature & adventure, Stress release & relaxation, Trophy fishing, Escape, and Family time. Cluster analysis showed that these anglers can be segmented into two distinct clusters, differing by sociodemographic characteristics, fishing behavior, and site/management preferences. The findings from this study provide baseline data to aid public resource managers and fee-fishing business owners in determining how to provide satisfying outdoor experiences and deliver desired services on-site. Future research will be needed from additional fee-fishing sites to obtain more detail about this outdoor recreation cohort and be able to generalize to a larger population of participants.     

ESTIMATION OF COASTAL WATER CONTAMINATION LONG-TERM TREND USING SEASONAL LINEAR MODELS1

ABSTRACT: Bivalves are used as bioindicators to assess trends of the chemical quality of coastal and marine environments due to their ability to concentrate chemicals. These shellfish are subject to seasonal physiological changes influencing the chemical concentration. Using quarterly data, we model concentration via linear regression with a biologically based seasonal component. This was applied to cadmium concentration measured in the blue mussel (Mytilus edulis) at three sites in the Seine estuary (Normandy, France). In this case we have a high concentration season from January to June and a “low concentration” season from July to December. This season definition was checked a posteriori, using box-and-whisker plots and a statistical test of comparison of pair-wise adjusted least-squares mean differences, and it appears to be very reasonable. We averaged data by season and across sites. Our final model (R²= 0.846 with N= 27 observations) includes highly significant terms: a season effect, which accounts for 45% of the total variability, a linear and a quadratic time term. Outliers were identified by high Studentized residual values and attributed to bias in the temporal sampling schemes. The methodology developed will further be used with other shellfish and/or other trace elements and organic chemicals.     

汽车内饰材料老化试验研究

本文介绍了汽车内饰材料常见的老化试验方法:人工加速老化试验、IP/DP箱暴晒和整车暴晒,分别讨论三种试验方法涉及的规范以及操作性.人工加速老化试验能快速掌握汽车内饰材料老化性能,缩短材料研发周期;IP/DP箱和整车对内饰件或其装配件进行的老化试验降低内饰材料加工工艺存在的风险,确保了内饰材料质量.整车暴晒收集的数据为人...     

DOWNSCALED CLIMATE AND STREAMFLOW STUDY OF THE SOUTHWESTERN UNITED STATES1

ABSTRACT: Downscaling coarse resolution climate data to scales that are useful for impact assessment studies is receiving increased attention. Basin-scale hydrologic processes and other local climate impacts related to water resources such as reservoir management, crop and forest productivity, and ecosystem response require climate information at scales that are much finer than current and future GCM resolutions. The Regional Climate System Model (RCSM) is a dynamic downscaling system that has been used since 1994 for short-term precipitation and streamflow predictions and seasonal hindcast analysis with good skill. During the 1997–1998 winter, experimental seasonal forecasts were made in collaboration with the NOAA Climate Prediction Center and UCLA with promising results. Preliminary studies of a control and 2°CO₂ perturbation for the southwestern U.S. have been performed.     

Moving Beyond Strawmen and Artificial Dichotomies: Adaptive Management When an Endangered Species Uses an Invasive One

Evans et al. (Journal of Agricultural and Environmental Ethics, 2008) have attempted to enmesh me in their dispute with the Florida Bureau of Invasive Plant Management about a specific system, Kings Bay/Crystal River. In so doing, they repeatedly mischaracterize my positions in order to depict, incorrectly, invasion biology as monolithic and me as a representative of one extreme of a false dichotomy about management of introduced species. In addition, they introduce an issue irrelevant in this case (extinctions) and cite incorrect data. Proposing to manage people, manatees, introduced plants, and cyanobacteria in Kings Bay by participative adaptive management, they ignore the fact that living organisms can both disperse autonomously and hitchhike. Finally, they present few details on any aspect of their management proposal and do not address the myriad problems that have beset previous attempts at scientific adaptive management, especially at large scales. Until such a management approach is fleshed out and implemented, it is impossible to assess its validity for Kings Bay, and it is very premature to suggest it as a general model for dealing with invasive species disputes.     

HYDROLOGICAL UNDERSTANDING AND SOCIETAL ACTION1

ABSTRACT: Hydrology is both an applied practical science and a pure geophysical science. The goal of hydrology, as a geophysical science, is to achieve theories capable of explaining with satisfactory accuracy the phenomena of interest. Through the rapidly accelerating power and versatility of digital computing technology, theory development and application are immensely facilitated via increasingly sophisticated predictive modeling schemes, which are now the principal operating tools both for applied management hydrology and for basic geophysical hydrology. While this approach treats phenomena as classes or generalizations, social and behavioral scientists have long argued that human beings base their actions on percepts, i.e., on the concrete specifics of their experience. Thus, the commonly held ideal of basing policy, decisions, and public actions on the best possible science encounters a conflict in belief systems. A possible resolution of this dilemma lies in the use of observational components, which in concept-centered science serve as data to test or calibrate models. These components also serve as a great repository of natural experience that is closely attuned to the perceptual reality that propels societal action. Landscapes and sediments provide indices of real processes, whose occurrence can be expected by continuity to extend to present and future activity. More attention to research on such indices is warranted as a means of triggering perception-based action by responsible decision-makers. Grounded in reality, and tempered by their intrinsic fallibility, the scientifically powerful conceptual schemes (models) will then serve as guides to further action. The full societal benefit of hydrological science requires a balanced approach in which subdisciplines focused on environmental indices are afforded equal attention to those focused on conceptual idealization.     

Historical Groundwater Trends in Northern New England and Relations with Streamflow and Climatic Variables

Water‐level trends spanning 20, 30, 40, and 50 years were tested using month‐end groundwater levels in 26, 12, 10, and 3 wells in northern New England (Maine, New Hampshire, and Vermont), respectively. Groundwater levels for 77 wells were used in interannual correlations with meteorological and hydrologic variables related to groundwater. Trends in the contemporary groundwater record (20 and 30 years) indicate increases (rises) or no substantial change in groundwater levels in all months for most wells throughout northern New England. The highest percentage of increasing 20‐year trends was in February through March, May through August, and October through November. Forty‐year trend results were mixed, whereas 50‐year trends indicated increasing groundwater levels. Whereas most monthly groundwater levels correlate strongly with the previous month's level, monthly levels also correlate strongly with monthly streamflows in the same month; correlations of levels with monthly precipitation are less frequent and weaker than those with streamflow. Groundwater levels in May through August correlate strongly with annual (water year) streamflow. Correlations of groundwater levels with streamflow data and the relative richness of 50‐ to 100‐year historical streamflow data suggest useful proxies for quantifying historical groundwater levels in light of the relatively short and fragmented groundwater data records presently available.     

Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

Potential Economic Impacts of Environmental Flows Following a Possible Listing of Endangered Texas Freshwater Mussels

Texas water resources, already taxed by drought and population growth, could be further stressed by possible listings of endangered aquatic species. This study estimated potential economic impacts of environmental flows (EFs) for five freshwater unionid mussels in three Central Texas basins (Brazos, Colorado, and Guadalupe‐San Antonio Rivers) that encompass 36% of Texas (~246,000 km²). A water availability model projected reductions in water supply to power, commercial and industrial, municipal, and agriculture sectors in response to possible EFs for mussels. Single‐year economic impacts were calculated using publicly available data with and without water transfers. Benefits of EFs should also be assessed, should critical habitat be proposed. Potential economic losses were highest during droughts, but were nominal (<$1 M) in wetter years — even with high EFs. Reduced supplies to San Antonio area power plants caused worst‐case impacts of a single‐year shutdown up to $107 million (M) during drought with high EFs. For other sectors in the study area, water transfers reduced worst‐case losses from $80 to $11 M per year. Implementing innovative water management strategies such as water markets, conjunctive use of surface water and groundwater, aquifer storage and recovery could mitigate economic impacts if mussels — or other widely distributed aquatic species — were listed. However, approaches for defining EFs and strategies for mitigating economic impacts of EFs are needed.     

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds1

Maurer, Edwin P., Levi D. Brekke, and Tom Pruitt, 2010. Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds. Journal of the American Water Resources Association (JAWRA) 46(5):1024–1035. DOI: 10.1111/j.1752-1688.2010.00473.x Abstract: We compare the projected changes to streamflows for three Sierra Nevada rivers using statistically downscaled output from 22 global climate projections. The downscaled meteorological data are used to drive two hydrology models: the Sacramento Soil Moisture Accounting model and the variable infiltration capacity model. These two models differ in their spatial resolution, computational time step, and degree and objective of calibration, thus producing significantly different simulations of current and future streamflow. However, the projected percentage changes in monthly streamflows through mid-21st Century generally did not differ, with the exceptions of streamflow during low flow months, and extreme low flows. These findings suggest that for physically based hydrology models applied to snow-dominated basins in Mediterranean climate regimes like the Sierra Nevada, California, model formulation, resolution, and calibration are secondary factors for estimating projected changes in extreme flows (seasonal or daily). For low flows, hydrology model selection and calibration can be significant factors in assessing impacts of projected climate change.