BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

SUMMER LOW FLOWS IN NEW ENGLAND DURING THE 20TH CENTURY1

ABSTRACT: High springtime river flows came earlier by one to two weeks in large parts of northern New England during the 20th Century. In this study it was hypothesized that late spring/early summer recessional flows and late summer/early fall low flows could also be occurring earlier. This could result in a longer period of low flow recession and a decrease in the magnitude of low flows. To test this hypothesis, variations over time in the magnitude and timing of low flows were analyzed. To help understand the relation between low flows and climatic variables in New England, low flows were correlated with air temperatures and precipitation. Analysis of data from 23 rural, unregulated rivers across New England indicated little evidence of consistent changes in the timing or magnitude of late summer/early fall low flows during the 20th Century. The interannual variability in the timing and magnitude of the low flows in northern New England was explained much more by the interannual variability in precipitation than by the interannual variability of air temperatures. The highest correlation between the magnitude of the low flows and air temperatures was with May through November temperatures (r =?0.37, p= 0.0017), while the highest correlation with precipitation was with July through August precipitation (r = 0.67, p > 0.0001).     

DEVELOPMENT OF EMPIRICAL,GEOGRAPHICALLY SPECIFIC WATER QUALITY CRITERIA: A CONDITIONAL PROBABILITY ANALYSIS APPROACH1

The need for scientifically defensible water quality standards for nonpoint source pollution control continues to be a pressing environmental issue. The probability of impact at differing levels of nonpoint source pollution was determined using the biological response of instream organisms empirically obtained from a statistical survey. A conditional probability analysis was used to calculate a biological threshold of impact as a function of the likelihood of exceeding a given value of pollution metric for a specified geographic area. Uncertainty and natural variability were inherently incorporated into the analysis through the use of data from a probabilistic survey. Data from wadable streams in the mid‐Atlantic area of the U.S. were used to demonstrate the approach. Benthic macroinvertebrate community index values (EPT taxa richness) were used to identify impacted stream communities. Percent fines in substrate (silt/clay fraction, > 0.06 mm) were used as a surrogate indicator for sedimentation. Thresholds of impact due to sedimentation were identified by three different techniques, and were in the range of 12 to 15 percent fines. These values were consistent with existing literature from laboratory and field studies on the impact of sediments on aquatic life in freshwater streams. All results were different from values determined from current regulatory guidance. Finally, it was illustrated how these thresholds could be used to develop criterion for protection of aquatic life in streams.     

A comparative study of US EPA 1996 and 1999 emission inventories in the west Gulf of Mexico coast region, USA

Emission inventory is one of the required inputs to air quality models. To assist in the urban and regional modeling efforts, United States Environmental Protection Agency (EPA) has compiled a National Emission Inventory (NEI) for criterion pollutants, and the precursors of ozone and particulate matter (PM). In December 2002, EPA released the 1999 NEI estimates (NEI99), which represent the most recent national emission data. However, the data sets are not in model-ready format for air quality simulations. This present work converts the NEI99 Final Version 2 data sets into Inventory Data Analyzer (IDA) format and processes the data using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system to generate a gridded emission inventory in a domain covering the west Gulf Coast Region, USA. The spatial and diurnal emission characteristics of the gridded emission inventories are then assessed and compared with those of the National Emission Trend 1996 (NET96). The NEI99 database contains more complete emission records in both area and point sources. It is also found that NEI99 data exhibit greater emissions with respect to point and mobile sources but smaller emissions with respect to area sources when compared to the corresponding gridded NET96 data in the same study domain. The most distinct differences between the NEI99 and NET96 databases are CO emission of mobile sources, SO2 emissions of point sources, and VOC/PM/NH3/NOx emissions of area and non-road sources. The gridded NEI99 data show low VOC/NOx ratios (<2-5) in the urban areas of the study domain.     

The role of scientists in statutory interpretation of the U.S. Endangered Species Act

Like many federal statutes, the U.S. Endangered Species Act (ESA) contains vague or ambiguous language. The meaning imparted to the ESA's unclear language can profoundly impact the fates of endangered and threatened species. Hence, conservation scientists should contribute to the interpretation of the ESA when vague or ambiguous language contains scientific words or refers to scientific concepts. Scientists need to know at least these 2 facts about statutory interpretation: statutory interpretation is subjective and the potential influence of normative values results in different expectations for the parties involved. With the possible exception of judges, all conventional participants in statutory interpretation are serving their own interests, advocating for their preferred policies, or biased. Hence, scientists can play a unique role by informing the interpretative process with objective, policy‐neutral information. Conversely, scientists may act as advocates for their preferred interpretation of unclear statutory language. The different roles scientists might play in statutory interpretation raise the issues of advocacy and competency. Advocating for a preferred statutory interpretation is legitimate political behavior by scientists, but statutory interpretation can be strongly influenced by normative values. Therefore, scientists must be careful not to commit stealth policy advocacy. Most conservation scientists lack demonstrable competence in statutory interpretation and therefore should consult or collaborate with lawyers when interpreting statutes. Professional scientific societies are widely perceived by the public as unbiased sources of objective information. Therefore, professional scientific societies should remain policy neutral and present all interpretations of unclear statutory language; explain the semantics and science both supporting and contradicting each interpretation; and describe the potential consequences of implementing each interpretation. A review of scientists’ interpretations of the phrase “significant portion of its range” in the ESA is used to critique the role of scientists and professional societies in statutory interpretation.     

Emerging technology for increasing glucosinolates in arugula and mustard greens

Two plant species, arugula (Eruca sativa) and mustard (Brassica juncea) were field-grown under four soil management practices: soil mixed with municipal sewage sludge (SS), soil mixed with horse manure (HM), soil mixed with chicken manure (CM), and no-mulch bare soil (NM) to investigate the impact of soil amendments on the concentration of glucosinolates (GSLs) in their shoots. GSLs, hydrophilic plant secondary metabolites in arugula and mustard were extracted using boiling methanol and separated by adsorption on sephadex ion exchange disposable pipette tips filled with DEAE, a weak base, with a net positive charge that exchange anions such as GSLs. Quantification of GSLs was based on inactivation of arugula and mustard myrosinase and liberation of the glucose moiety from the GSLs molecule by addition of standardized myrosinase (thioglucosidase) and spectrophotometric quantification of the liberated glucose moiety. Overall, GSLs concentrations were significantly greater (1287 µg g^?1 fresh shoots) in plants grown in SS compared to 929, 890, and 981 µg g^?1 fresh shoots in plants grown in CM, HM, and NM soil, respectively. Results also revealed that mustard shoots contained greater concentrations of GSLs (974 µg g^?1 fresh shoots) compared to arugula (651 µg g^?1 fresh shoots).     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas