IMPLEMENTATION OF BIORETENTION SYSTEMS: A WISCONSIN CASE STUDY1

ABSTRACT: The implementation of various bioretention systems was analyzed, including rain gardens, vegetated swales, trenches, and infiltration basins in the St. Francis subdivision, Cross Plains, Wisconsin. Through the examination of archival data and interviews with key participants, it was found that although regulatory and political pressures encouraged the inclusion of bioretention, current standards for storm water management prevailed. The developers had to meet both existing requirements and anticipated rules requiring infiltration. As a result, bioretention systems simply supplemented, rather than replaced, traditional storm water practices. The confusion surrounding dual standards contributed to substantial delays in the negotiations among relevant stakeholders in the watershed. It is concluded that the St. Francis subdivision serves as both a cautionary tale and a bioretention success story. As a caution, this situation demonstrates the need for careful review and refinement of existing storm water ordinances to incorporate water quality improvement technologies, such as bioretention. The demonstrated success of the St. Francis development, however, is that it became a positive prototype for best management storm water practices elsewhere in the region. In addition, the water quality monitoring data from the site has contributed to development of a new county ordinance, the first in Wisconsin to address both quantity and quality of storm water runoff.     

MULTIVARIATE ANALYSIS OF WATER QUALITY IN THE RICHIBUCTO DRAINAGE BASIN (NEW BRUNSWICK,CANADA)1

ABSTRACT: Specific conductivity, pH, dissolved oxygen, carbon, phosphorous, and nitrogen species were measured at 36 stations in the Richibucto River drainage basin, including the estuary, in New Brunswick, Canada, over the six‐year period 1996 through 2001. Each station was sampled between 1 and 26 times (mean = 7.5, standard deviation = 6.0) during the ice free seasons without regard to tide. There was significant variance among stations in most parameters. Principal component analysis (PCA) was used to identify the processes explaining the observed variance in water quality. Because of the high variability in specific conductance, stations were first grouped in a freshwater subset and an estuarine (brackish water) subset. For freshwater stations, most of the variance in water quality was explained by pH and total organic carbon, as well as high nutrient concentrations. These high nutrient concentrations, along with water salinity, which varies with flow and tides, are also important in determining water quality variability in brackish water. It is recommended that water quality parameters that were found to explain most of the variance by PCA be monitored more closely, as they are key elements in understanding the variability in water quality in the Richibucto drainage basin. Cluster analyses showed that high phosphorous and nitrate concentrations were mostly found in areas of peat runoff, tributaries receiving treated municipal effluent, and lentic zones upstream of culverts. Peat runoff was also shown to be acidic, whether it is runoff from a harvested area or a natural bog.     

WATER QUALITY MODELING FOR THE FEITSUI RESERVOIR IN NORTHERN TAIWAN1

ABSTRACT: Field data collected from the Feitsui Reservoir in Taiwan indicate that the water is at a stage between mesotrophic and eutrophic. Recent measurements such as total phosphorus, chlorophyll a and Secchi depth levels suggest that the water quality has been declining. A two‐dimensional, laterally averaged, finite difference hydrodynamic and water quality model was used to simulate the water quality in the Feitsui Reservoir in an effort to determine sound water quality management strategies. The model was calibrated and verified using data collected in 1996 and 1997. The calibrated model was used to simulate algal biomass (in terms of chlorophyll a) levels under various wasteload reduction scenarios. Model results show that 50 percent reduction of the total phosphorus load will improve the existing water quality, shifting the trophic status from eutrophic/mesotrophic to oligotrophic. The modeling effort has yielded valuable information that can be used by decision makers for the evaluation of different management strategies of reducing watershed nutrient loads.     

TWO PRACTICAL APPROACHES FOR DETERMINING THE CONFIDENCE INTERVAL OF RAINFALL DEPTH PERCENTILES1

ABSTRACT: A simple simulation type approach and a statistical method are proposed for determining the confidence interval of the T‐year frequency rainfall percentiles (or precipitation extremes) for generalized extreme value (GEV) distributions. The former method is based on the Monte Carlo testing procedure. To generate realizations, the covariance structure of the three parameters of GEV is investigated using an observed information matrix of the likelihood function. For distributions with realistic parameters, the correlation between the location and the scale parameters is practically constant when the shape parameter varies around values close to its optimal value. The latter method is based on likelihood ratio statistics. In the case where the joint confidence surface for shape parameters and estimates is plotted with lines of best estimates, the region where the estimated best percentile value can be chosen as a possible estimate is part of the joint confidence surface. The projection of this bounded region on axis of percentile is defined as the effective confidence interval in this research. The use of this effective interval as the confidence interval of the percentile of T‐year frequency rainfall is particularly recommended because it is stable for T and it reflects variations in all three parameters of GEV appropriately.     

GENETIC PROGRAMMING: A NEW PARADIGM IN RAINFALL RUNOFF MODELING1

ABSTRACT: Genetic Programming (GP) is a domain‐independent evolutionary programming technique that evolves computer programs to solve, or approximately solve, problems. To verify GP's capability, a simple example with known relation in the area of symbolic regression, is considered first. GP is then utilized as a flow forecasting tool. A catchment in Singapore with a drainage area of about 6 km² is considered in this study. Six storms of different intensities and durations are used to train GP and then verify the trained GP. Analysis of the GP induced rainfall and runoff relationship shows that the cause and effect relationship between rainfall and runoff is consistent with the hydrologic process. The result shows that the runoff prediction accuracy of symbolic regression based models, measured in terms of root mean square error and correlation coefficient, is reasonably high. Thus, GP induced rainfall runoff relationships can be a viable alternative to traditional rainfall runoff models.     

AN INTEGRATIVE APPROACH TOWARDS UNDERSTANDING ECOLOGICAL RESPONSES TO DAM REMOVAL: THE MANATAWNY CREEK STUDY1

ABSTRACT: Dam removal has been proposed as an effective method of river restoration, but few integrative studies have examined ecological responses to the removal of dams. In 1999, we initiated an interdisciplinary study to determine ecological responses to the removal of a 2 m high dam on lower Manatawny Creek in southeastern Pennsylvania. We used an integrative monitoring program to assess the physical, chemical, and biological responses to dam removal. Following removal in 2000, increased sediment transport has led to major changes in channel form in the former impoundment and downstream reaches. Water quality did not change markedly following removal, probably because of the impoundment's short hydraulic residence time (less than two hours at base flow) and infrequent temperature stratification. When the impoundment was converted to a free flowing reach, the composition of the benthic macroinvertebrate and fish assemblages in this portion of Manatawny Creek shifted dramatically from lentic to lotic taxa. Some fish species inhabiting the free flowing reach downstream from the dam were negatively affected by large scale sediment transport and habitat alteration following dam removal, but this appears to be a short term response. Based on our observations and experiences in this study, we provide a list of issues to evaluate when considering future dam removals.     

Bird Conservation in Brazil

Abstract:  Brazil has one of the richest avifaunas in the world, with recent estimates varying from 1696 to 1731 species. About 10% (193 taxa) of these are threatened. The Amazon has the highest number of species, followed by the Atlantic Forest and the Cerrado; most of Brazil's endemic birds, however, are in the Atlantic Forest. Brazil's threatened species occur mostly in the Atlantic Forest, especially in the southeast lowlands and the northeast. The Cerrado has the second highest number of threatened species. The two major threats to Brazilian birds are habitat loss, degradation, and fragmentation and hunting, most especially for illegal commerce. A number of conservation and research initiatives over the last 20 years have significantly improved our capacity to address and resolve major issues for bird conservation. Brazil requires a National Bird Conservation Plan to draw up priorities for research and conservation over the next decade.     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.     

Gastrointestinal Bacterial Transmission among Humans,Mountain Gorillas,and Livestock in Bwindi Impenetrable National Park,Uganda

Abstract: Habitat overlap can increase the risks of anthroponotic and zoonotic pathogen transmission between humans, livestock, and wild apes. We collected Escherichia coli bacteria from humans, livestock, and mountain gorillas (Gorilla gorilla beringei) in Bwindi Impenetrable National Park, Uganda, from May to August 2005 to examine whether habitat overlap influences rates and patterns of pathogen transmission between humans and apes and whether livestock might facilitate transmission. We genotyped 496 E. coli isolates with repetitive extragenic palindromic polymerase chain reaction fingerprinting and measured susceptibility to 11 antibiotics with the disc‐diffusion method. We conducted population genetic analyses to examine genetic differences among populations of bacteria from different hosts and locations. Gorilla populations that overlapped in their use of habitat at high rates with people and livestock harbored E. coli that were genetically similar to E. coli from those people and livestock, whereas E. coli from gorillas that did not overlap in their use of habitats with people and livestock were more distantly related to human or livestock bacteria. Thirty‐five percent of isolates from humans, 27% of isolates from livestock, and 17% of isolates from gorillas were clinically resistant to at least one antibiotic used by local people, and the proportion of individual gorillas harboring resistant isolates declined across populations in proportion to decreasing degrees of habitat overlap with humans. These patterns of genetic similarity and antibiotic resistance among E. coli from populations of apes, humans, and livestock indicate that habitat overlap between species affects the dynamics of gastrointestinal bacterial transmission, perhaps through domestic animal intermediates and the physical environment. Limiting such transmission would benefit human and domestic animal health and ape conservation.