DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

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.     

BASE FLOW TRENDS IN URBANIZING WATERSHEDS OF THE DELAWARE RIVER BASIN1

Rapid land development is raising concern regarding the ability of urbanizing watersheds to sustain adequate base flow during periods of drought. Long term streamflow records from unregulated watersheds of the lower to middle Delaware River basin are examined to evaluate the impact of urbanization and imperviousness on base flow. Trends in annual base flow volumes, seven‐day low flows, and runoff ratios are determined for six urbanizing watersheds and four reference watersheds across three distinct physiographic regions. Hydrograph separation is used to determine annual base flow and stormflow volumes, and nonparametric trend tests are conducted on the resulting time series. Of the watersheds examined, the expected effects of declining base flow volumes and seven‐day low flows and increasing stormflows are seen in only one watershed that is approximately 20 percent impervious and has been subject to a net water export over the past 15 years. Both interbasin transfers and hydrologic mechanisms are invoked to explain these results. The results show that increases in impervious area may not result in measurable reductions in base flow at the watershed scale.     

Techniques for accuracy assessment of tree locations extracted from remotely sensed imagery

Remotely sensed imagery is becoming a common source of environmental data. Consequently, there is an increasing need for tools to assess the accuracy and information content of such data. Particularly when the spatial resolution of imagery is fine, the accuracy of image processing is determined by comparisons with field data. However, the nature of error is more difficult to assess. In this paper we describe a set of tools intended for such an assessment when tree objects are extracted and field data are available for comparison. These techniques are demonstrated on individual tree locations extracted from an IKONOS image via local maximum filtering. The locations of the extracted trees are compared with field data to determine the number of found and missed trees. Aspatial and spatial (Voronoi) analysis methods are used to examine the nature of errors by searching for trends in characteristics of found and missed trees. As well, analysis is conducted to assess the information content of found trees.     

Estimating the economic burden from illnesses associated with recreational coastal water pollution--a case study in Orange County, California

A cost-of-illness framework was applied to health and income data to quantify the health burden from illnesses associated with exposure to polluted recreational marine waters. Using data on illness severity due to exposure to polluted coastal water and estimates of mean annual salaries and medical costs (adjusted to 2001 values) for residents of Orange County, California, we estimated that the economic burden per gastrointestinal illness (GI) amounts to 36.58 dollars, the burden per acute respiratory disease is 76.76 dollars, the burden per ear ailment is 37.86 dollars, and the burden per eye ailment is 27.31 dollars. These costs can become a substantial public health burden when millions of exposures per year to polluted coastal waters result in hundreds of thousands of illnesses. For example, exposures to polluted waters at Orange County's Newport and Huntington Beaches were estimated to generate an average of 36,778 GI episodes per year. At this GI illness rate, one can also expect that approximately 38,000 more illness episodes occurred per year of other types, including respiratory, eye, and ear infections. The combination of excess illnesses associated with coastal water pollution resulted in a cumulative public health burden of 3.3 million dollars per year for these two beaches. This paper introduces a public health cost variable that can be applied in cost-benefit analyses when evaluating pollution abatement strategies.     

Increased bioavailability of metals in two contrasting agricultural soils treated with waste wood-derived biochar and ash

Recycled waste wood is being increasingly used for energy production; however, organic and metal contaminants in by-products produced from the combustion/pyrolysis residue may pose a significant environmental risk if they are disposed of to land. Here we conducted a study to evaluate if highly polluted biochar (from pyrolysis) and ash (from incineration) derived from Cu-based preservative-treated wood led to different metal (e.g., Cu, As, Ni, Cd, Pb, and Zn) bioavailability and accumulation in sunflower (Helianthus annuus L.). In a pot experiment, biochar at a common rate of 2 % w/w, corresponding to ～50 t ha^?1, and an equivalent pre-combustion dose of wood ash (0.2 % w/w) were added to a Eutric Cambisol (pH 6.02) and a Haplic Podzol (pH 4.95), respectively. Both amendments initially raised soil pH, although this effect was relatively short-term, with pH returning close to the unamended control within about 7 weeks. The addition of both amendments resulted in an exceedance of soil Cu statutory limit, together with a significant increase of Cu and plant nutrient (e.g., K) bioavailability. The metal-sorbing capacity of the biochar, and the temporary increase in soil pH caused by adding the ash and biochar were insufficient to offset the amount of free metal released into solution. Sunflower plants were negatively affected by the addition of metal-treated wood-derived biochar and led to elevated concentration of metals in plant tissue, and reduced above- and below-ground biomass, while sunflower did not grow at all in the Haplic Podzol. Biochar and ash derived from wood treated with Cu-based preservatives can lead to extremely high Cu concentrations in soil and negatively affect plant growth. Identifying sources of contaminated wood in waste stream feedstocks is crucial before large-scale application of biochar or wood ash to soil is considered.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.