浏阳河土地利用变化对非点源污染负荷的影响

以红壤丘陵区典型流域——浏阳河流域为研究区域,利用1986、2000、2005年3个时段的土地利用数据,分析土地利用方式的变化,并结合土壤普查图和降雨数据,在RS和GIS的支持下,利用长期水文影响评价(L-THIA)模型,评估区域长期水文响应,采用相似流域的营养盐输出系数估算非点源污染负荷。结果表明,从1986～2005年期间,林地和草地有向城镇、农村居民点用地和农业用地转化的趋势,其中农业用地由13.75%增加到20%左右,城镇用地和农村居民用地分别由原来的1.34%和0.10%变为2.56%和0.80%,期间非点源污染敏感区面积不断扩大,污染负荷不断增加,TN由1986年的675.56 t增加到2005年的1 001.02 t,TP从15.52 t增加到了23.41 t。     

Linking Hydrologic Alteration to Biological Impairment in Urbanizing Streams of the Puget Lowland,Washington, USA1

Abstract: We used a retrospective approach to identify hydrologic metrics with the greatest potential for ecological relevance for use as resource management tools (i.e., hydrologic indicators) in rapidly urbanizing basins of the Puget Lowland. We proposed four criteria for identifying useful hydrologic indicators: (1) sensitive to urbanization consistent with expected hydrologic response, (2) demonstrate statistically significant trends in urbanizing basins (and not in undeveloped basins), (3) be correlated with measures of biological response to urbanization, and (4) be relatively insensitive to potentially confounding variables like basin area. Data utilized in the analysis included gauged flow and benthic macroinvertebrate data collected at 16 locations in 11 King County stream basins. Fifteen hydrologic metrics were calculated from daily average flow data and the Pacific Northwest Benthic Index of Biological Integrity (B‐IBI) was used to represent the gradient of response of stream macroinvertebrates to urbanization. Urbanization was represented by percent Total Impervious Area (%TIA) and percent urban land cover (%Urban). We found eight hydrologic metrics that were significantly correlated with B‐IBI scores (Low Pulse Count and Duration; High Pulse Count, Duration, and Range; Flow Reversals, T_Qmean, and R‐B Index). Although there appeared to be a great deal of redundancy among these metrics with respect to their response to urbanization, only two of the metrics tested – High Pulse Count and High Pulse Range – best met all four criteria we established for selecting hydrologic indicators. The increase in these high pulse metrics with respect to urbanization is the result of an increase in winter high pulses and the occurrence of high pulse events during summer (increasing the frequency and range of high pulses), when practically none would have occurred prior to development. We performed an initial evaluation of the usefulness of our hydrologic indicators by calculating and comparing hydrologic metrics derived from continuous hydrologic simulations of selected basin management alternatives for Miller Creek, one of the most highly urbanized basins used in our study. We found that the preferred basin management alternative appeared to be effective in restoring some flow metrics close to simulated fully forested conditions (e.g., T_Qmean), but less effective in restoring other metrics such as High Pulse Count and Range. If future research continues to support our hypothesis that the flow regime, particularly High Pulse Count and Range, is an important control of biotic integrity in Puget Lowland streams, it would have significant implications for stormwater management.     

A Tool for Automated Load Duration Curve Creation1

Abstract: A recent study by the Texas Bacteria Total Maximum Daily Load (TMDL) Task Force has recommended the use of load duration curves as a primary tool in calculating bacterial TMDLs. This method is attractive because it effectively integrates flow regimes into TMDL analyses, clearly communicates data through a method that is understandable to the general public, and has been successfully applied in TMDL studies in other states. To ease the creation of load duration curves, an automated load duration curve creation tool called LDCurve has been created within a Microsoft Excel framework. Web services and a webscraper are used to retrieve U.S. Geological Survey streamflow data and Texas Commission on Environmental Quality water quality data. Data are imported to the spreadsheet, combined to create flow and load duration curves, and plotted. Final steps result in a preliminary estimate of the overall load reductions needed to meet water quality standards in the modeled segment. LDCurve is currently only applicable in the state of Texas, but may be updated to model water quality throughout the nation using analogous web services from the EPA STORET database. By using automated data retrievals and computations, the LDCurve tool reduces the amount of time required to create curves and calculate load reductions to a matter of minutes. LDCurve and all supporting materials are available online for free download at: http://tools.crwr.utexas.edu/LDCurve/ .     

Fate and Transport Modeling of Potential Pathogens: The Contribution From Sediments1

Abstract: Escherichia coli was used as a bacterial tracer for the development, calibration, and validation of a watershed scale fate and transport model to be extended to a suite of reference pathogens (Cryptosporidium, Giardia, Campylobacter, E. coli O157:H7). E. coli densities in water and sediments from the Blackstone River Watershed, Massachusetts, were measured at three sites for a total of five wet weather events and three dry weather events covering three seasons. The confirmed E. coli strains were identified by ribotyping for tracking the sources of E. coli and for determining the association of downstream E. coli isolates with isolates from upstream sediments. A large number of downstream samples were associated with upstream sediment sources of E. coli. E. coli densities ranged from 71 to 6,401 MPN/100 ml in water samples and from 2 to 335 MPN/g in sediments. Pearson correlation analysis revealed significant correlations between E. coli and total coliforms in water (r = 0.777, p < 0.01) and sediments (r = 0.728, p < 0.01). In addition, E. coli concentrations in water were weakly correlated with sediment particle size and sediment concentrations (r = 0.298, p < 0.01). A hydrologic model, WATFLOOD/SPL9, was used to predict the temporal and spatial variation of E. coli in the Blackstone River. The rapid rise of stream E. coli densities was more accurately predicted by the model with the inclusion of sediment resuspension, thus demonstrating the importance of the process.     

The Watershed Deposition Tool: A Tool for Incorporating Atmospheric Deposition in Water‐Quality Analyses1

Abstract: A tool for providing the linkage between air and water‐quality modeling needed for determining the Total Maximum Daily Load (TMDL) and for analyzing related nonpoint‐source impacts on watersheds has been developed. Using gridded output of atmospheric deposition from the Community Multiscale Air Quality (CMAQ) model, the Watershed Deposition Tool (WDT) calculates average per unit area and total deposition to selected watersheds and subwatersheds. CMAQ estimates the wet and dry deposition for all of its gaseous and particulate chemical species, including ozone, sulfur species, nitrogen species, secondary organic aerosols, and hazardous air pollutants at grid scale sizes ranging from 4 to 36 km. An overview of the CMAQ model is provided. The somewhat specialized format of the CMAQ files is not easily imported into standard spatial analysis tools. The WDT provides a graphical user interface that allows users to visualize CMAQ gridded data and perform further analyses on selected watersheds or simply convert CMAQ gridded data to a shapefile for use in other programs. Shapefiles for the 8‐digit (cataloging unit) hydrologic unit code polygons for the United States are provided with the WDT; however, other user‐supplied closed polygons may be used. An example application of the WDT for assessing the contributions of different source categories to deposition estimates, the contributions of wet and dry deposition to total deposition, and the potential reductions in total nitrogen deposition to the Albemarle‐Pamlico basin stemming from future air emissions reductions is used to illustrate the WDT capabilities.     

Stochastic Watershed Water Quality Simulation for TMDL Development – A Case Study in the Newport Bay Watershed1

Abstract: Systematic consideration of uncertainty in data, model structure, and other factors is generally unaddressed in most Total Maximum Daily Load (TMDL) calculations. Our previous studies developed the Management Objectives Constrained Analysis of Uncertainty (MOCAU) approach as an uncertainty analysis technique specifically for watershed water quality models, based on a synthetic case. In this study, we applied MOCAU to analyze diazinon loading in the Newport Bay watershed (Southern California). The study objectives included (1) demonstrating the value of performing stochastic simulation and uncertainty analysis for TMDL development, using MOCAU as the technique and (2) evaluating the existing diazinon TMDL and generating insights for the development of scientifically sound TMDLs, considering uncertainty. The Watershed Analysis Risk Management Framework model was used as an example of a complex watershed model. The study revealed the importance and feasibility of conducting stochastic watershed water quality simulation for TMDL development. The critical role of management objectives in a systematic uncertainty assessment was well demonstrated. The results of this study are intuitive to TMDL calculation, model structure improvement and sampling strategy design.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

Model Calculations of Total Maximum Daily Loads of Mercury for Drainage Lakes1

Abstract: The Watershed Analysis Risk Management Framework watershed model was enhanced to simulate the transport and fate of mercury and to calculate the fish mercury concentrations (FMC) attained by fish through the food web. The model was applied to Western Lake Superior Basin of Minnesota, which has many peat lands and lakes. Topographic, land use, and soil data were used to set up the model. Meteorology and precipitation chemistry data from nearby monitoring stations were compiled to drive the model. Simulated flow and mercury concentrations for several stream stations were comparable to available data. The model was used to perform mercury total maximum daily load calculations for two contrasting drainage lakes (Wild Rice Lake and Whiteface Reservoir). The model results for wet deposition, dry deposition, evasion, watershed yield, and soil sequestration of mercury were comparable with available actual data. The model predicted lake ice cover from November to April and weak stratification in summer, typical of shallow lakes in cold regions. The simulated sulfate decrease and methylmercury increase near the lake bottom in late summer are caused by sulfate reduction and mercury methylation that occur in the surficial sediment. Simulated FMC were within the range of observed values and the R² of correlation between the simulated and observed FMC was 0.77. Under the 1989‐2004 base condition, the average simulated FMC of four‐year‐old walleye was 0.31 μg/g for Whiteface Reservoir and 0.15 μg/g for Wild Rice Lake. The FMC criterion in Minnesota is 0.2 μg/g. Wild Rice Lake already meets this criterion without any load reduction. The model showed that a 65% reduction in atmospheric mercury deposition will not, by itself, allow Whiteface Reservoir to meet the criterion in 15 years. Additional best management practices will be needed to reduce 50% of the watershed input.     

Modeling Effects of Natural Flow Restoration on Metals Fate and Transport in a Mountain Stream Impacted by Mine Waste1

Abstract: The effects of natural flow restoration on metals fate and transport in the Upper Tenmile Creek Watershed, Montana, were modeled using the Water Quality Analysis Simulation Program developed by the U.S. Environmental Protection Agency (USEPA). This 50‐km² watershed has over 150 historic abandoned mines, including mine waste rock and tailings, as well as adits discharging acid mine drainage, and is the primary drinking water supply for the City of Helena. Water supply diversions almost completely dewater some stream reaches during summer low flows, but the city is considering a new drinking water source and restoration of natural flows in Tenmile Creek as part of acid mine drainage remediation and broader aquatic habitat restoration. One dimensional steady‐state simulation of total recoverable cadmium, copper, lead, and zinc in the mainstem was performed, and the model was calibrated to June 2000 base‐flow data. Representative low‐flows in August and high‐flow snowmelt conditions in June were modeled using mean monthly natural flow estimates from the U.S. Geological Survey and representative USEPA metals concentrations data. The modeling showed that total recoverable metals concentrations, and especially loads, can vary significantly among input locations and over time in the watershed. Some data gaps limit evaluation of variability and increase uncertainty in several locations. Model results indicated, however, that natural low‐ and high‐flow restoration by itself can reduce some metals concentrations in the mainstem compared to June 2000 values, which were influenced by significant water diversion. Some values (such as Zn) may still exceed standards during natural August low flow due to the remaining high concentrations and loads in the primary inputs to the mainstem. Others (such as Cu) can increase during high flow due to remaining mine waste sources and loading of particulate Cu associated with erosion and transport of solids. Greater than 50% reduction in concentrations and loads from some of the main tributaries may be necessary to meet all standards, especially for potential particulate loads with higher flows in June.     

Adaptive Management and Watersheds: A Social Science Perspective1

Abstract:  Adaptive management is often proposed as the most effective way to manage complex watersheds. However, our experience suggests that social and institutional factors constrain the search for, and integration of, the genuine learning that defines adaptive management. Drawing on our work as social scientists, and on a guided panel discussion at a recent AWRA conference, we suggest that watershed‐scale adaptive management must be recognized as a radical departure from established ways of managing natural resources if it is to achieve its promise. Successful implementation will require new ways of thinking about management, new organizational structures and new implementation processes and tools. Adaptive management encourages scrutiny of prevailing social and organizational norms and this is unlikely to occur without a change in the culture of natural resource management and research. Planners and managers require educational, administrative, and political support as they seek to understand and implement adaptive management. Learning and reflection must be valued and rewarded, and fora established where learning through adaptive management can be shared and explored. The creation of new institutions, including educational curricula, organizational policies and practices, and professional norms and beliefs, will require support from within bureaucracies and from politicians. For adaptive management to be effective researchers and managers alike must work together at the watershed‐scale to bridge the gaps between theory and practice, and between social and technical understandings of watersheds and the people who occupy and use them.