灰色聚类法在水环境质量评价中的应用

用灰色聚类法对乐山市境内的岷江、大渡河、体泉河的水环境质量进行评价，并与水质距离评价法、综合污染指数法进行比较。结果表明，灰色聚类法也是一种对水环境质量评价的实用方法。     

The South‐to‐North Water Transfer Project of China: Environmental Implications and Monitoring Strategy1

Abstract: In 2002, China launched the South‐to‐North Water Transfer Project after completing a 50‐year feasibility study. By 2050, the three‐route (i.e., East, Middle, and West) project will be capable of transferring 44.8 billion m³/year of water from the water rich Yangtze River to the arid north to alleviate water shortage and help secure a balanced social and economic development across the nation. However, diversion of such a large quantity of water could profoundly change the riverine environment of the upper Yellow River and the lower reach of the Han River, a tributary of the Yangtze River and the water supplying area of the project’s Middle Route, because of changes in the annual discharge. Secondary salinization seems inevitable in the water receiving areas of the North China Plain, and decrease in the discharge of the Yangtze River will result in seawater intrusion into the Yangtze Delta. This paper describes the project and discusses its environmental implications. Additionally, a long‐term monitoring strategy under the umbrella of the Chinese Ecological Research Network is proposed for environmental monitoring.     

地面水(河流)环境影响评价中水质模式选择

本文定性分析了连续排放污染物于均匀平直河流中的扩散过程,并对其划分出三个混合阶段,分别给出相应的水质模式,并重点描述了横向混合阶段所预测的主要内容,并根据预测断面所处的混合阶段,提出水质模式的选择方法。     

Evaluation of Rio Grande Management Alternatives Using a Surface‐Water/Ground‐Water Model1

Abstract: Previous investigations observed significant seepage losses from the Rio Grande to the shallow aquifer between Socorro and San Antonio, New Mexico. High‐resolution telescopic modeling was used along a 10‐km reach of the Rio Grande and associated drains and canals to evaluate several management alternatives aimed at improving river conveyance efficiency. Observed data consisted of ground‐water and surface‐water elevations, seepage rates along the Rio Grande and associated canals and drains, and borehole geology. Model calibration was achieved by adjusting hydraulic conductivity and specific storage until the output matched observed data. Sensitivity analyses indicated that the system was responsive to changes in hydrogeologic properties, especially when such alterations increased vertical connectivity between layers. The calibrated model predicted that removal of the low flow conveyance channel, a major channel draining the valley, would not only decrease river seepage by 67%, but also decrease total flow through the reach by 75%. The decreased flow through the reach would result in increased water logging and an average increase in ground‐water elevations of 1.21 meter. Simulations of the system with reduced riparian evapotranspiration rates or a relocated river channel also predicted decreased river seepage, but to a much lesser degree.     

Water Dispatch Model for Middle Route of a South‐to‐North Water Transfer Project in China1

Chang, Jian‐xia, Yi‐min Wang, and Qiang Huang, 2011. Water Dispatch Model for Middle Route of a South‐to‐North Water Transfer Project in China. Journal of the American Water Resources Association (JAWRA) 47(1):70‐80. DOI: 10.1111/j.1752‐1688.2010.00478.x Abstract: The objective of this paper is to present a simulation model to address the water dispatch problem of the south‐to‐north water transfer project for the Middle Route system in China. Reasonable rules and a system network structure are established. This model consists of five modules: (1) a data‐processing module, (2) an initial control module, (3) a multisource simulation dispatch module, (4) a system identification module, and (5) a revision module. Water allocated to each province and city along the route is obtained by simulation, and the long‐term operation results show that water supply reliabilities are significantly improved if the transferred water is jointly dispatched with the local water resources.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Field Testing the Riparian Ecosystem Management Model on a Riparian Buffer in the North Carolina Upper Coastal Plain

The riparian ecosystem management model (REMM) was field tested using five years (2005‐2009) of measured hydrologic and water quality data on a riparian buffer located in the Tar‐Pamlico River Basin, North Carolina. The buffer site received NO₃‐N loading from an agricultural field that was fertilized with inorganic fertilizer. Field results showed the buffer reduced groundwater NO₃‐N concentration moving to the stream over a five‐year period. REMM was calibrated hydrologically using daily field‐measured water table depths (WTDs), and with monthly NO₃‐N concentrations in groundwater wells. Results showed simulated WTDs and NO₃‐N concentrations in good agreement with measured values. The mean absolute error and Willmott's index of agreement for WTDs varied from 13‐45 cm and 0.72‐0.92, respectively, while the root mean square error and Willmott's index of agreement for NO₃‐N concentrations ranged from 1.04‐5.92 mg/l and 0.1‐0.86, respectively, over the five‐year period. REMM predicted plant nitrogen (N) uptake and denitrification were within ranges reported in other riparian buffer field studies. The calibrated and validated REMM was used to simulate 33 years of buffer performance at the site. Results showed that on average the buffer reduced NO₃‐N concentrations from 12 mg/l at the field edge to 0.7 mg/l at the stream edge over the simulation period, while the total N and NO₃‐N load reductions from the field edge to the stream were 77 and 82%, respectively.     

遗传和模拟退火算法在水质模型参数确定中的应用简介

水质模型参数的确定是构建水质模型的基础。相对于传统优化方法,现代优化算法的优势日趋明显。本文在基于现代优化算法的水质模型参数确定研究背景下,介绍了具有代表性的遗传算法和模拟退火算法,并对该两种算法的应用现状进行综述,旨在推进该领域的进一步探索。     

Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program1

Kardos, Josef S. and Christopher C. Obropta, 2011. Water Quality Model Uncertainty Analysis of a Point‐Point Source Phosphorus Trading Program. Journal of the American Water Resources Association (JAWRA) 47(6):1317–1337. DOI: 10.1111/j.1752‐1688.2011.00591.x Abstract: Water quality modeling is a major source of scientific uncertainty in the Total Maximum Daily Load (TMDL) process. The effects of these uncertainties extend to water quality trading programs designed to implement TMDLs. This study examines the effects of water quality model uncertainty on a nutrient trading program. The study builds on previous work to design a phosphorus trading program for the Nontidal Passaic River Basin in New Jersey that would implement the watershed TMDL for total phosphorus (TP). The study identified how water quality model uncertainty affects outcomes of potential trades of TP between wastewater treatment plants. The uncertainty analysis found no evidence to suggest that the outcome of trades between wastewater treatment plants, as compared with command and control regulation, will significantly increase uncertainty in the attainment of dissolved oxygen surface water quality standards, site‐specific chlorophyll a criteria, and reduction targets for diverted TP load at potential hot spots in the watershed. Each simulated trading scenario demonstrated parity with or improvement from the command and control approach at the TMDL critical locations, and low risk of hot spots elsewhere.     

Field‐Scale Application of Three Types of Neural Networks to Predict Ground‐Water Levels1

Abstract: In this paper, a field‐scale applicability of three forms of artificial neural network algorithms in forecasting short‐term ground‐water levels at specific control points is presented. These algorithms are the feed‐forward back propagation (FFBP), radial basis networks (RBN), and generalized regression networks (GRN). Ground‐water level predictions from these algorithms are in turn to be used in an Optimized Regional Operations Plan that prescribes scheduled wellfield production for the coming four weeks. These models are up against each other for their accuracy of ground‐water level predictions on lead times ranging from a week to four weeks, ease of implementation, and execution times (mainly training time). In total, 208 networks of each of the three algorithms were developed for the study. It is shown that although learning algorithms have emerged as a viable solution at field scale much larger than previously studied, no single algorithm performs consistently better than others on all the criteria. On average, FFBP networks are 20 and 26%, respectively, more accurate than RBN and GRN in forecasting one week ahead water levels and this advantage drops to 5 and 9% accuracy in forecasting four weeks ahead water levels, whereas GRN posted a training time that is only 5% of the training time taken by that of FFBP networks. This may suggest that in field‐scale applications one may have to trade between the type of algorithm to be used and the degree to which a given objective is honored.     

Rhetoric and Reality of Water Quality Trading and the Potential for Market‐like Reform1

Stephenson, Kurt and Leonard Shabman, 2011. Rhetoric and Reality of Water Quality Trading and the Potential for Market‐Like Reform. Journal of the American Water Resources Association (JAWRA) 47(1):15‐28. DOI: 10.1111/j.1752‐1688.2010.00492.x Abstract: Many public interest groups, government agencies, and professional economists argue that current approaches to water quality trading are a cost‐effective, politically practical innovation for achieving water quality standards, in part by addressing one of the most difficult water quality improvement challenges – limiting the discharge from nonpoint sources. A critical analysis shows that these claims for current water quality trading programs are often unrealized. This rhetoric, without adherence to principles of market‐like reform, can undermine the support of regulated parties for meaningful water quality policy reform, contribute to missed opportunities to implement cost‐effective programs, and postpone successfully meeting the challenge of limiting nonpoint source discharges. A better understanding and application of market‐like principles can result in an improved design of trading as well as general water quality management programs.     

A Simple Process‐Based Snowmelt Routine to Model Spatially Distributed Snow Depth and Snowmelt in the SWAT Model1

Abstract: We present a method to integrate a process‐based (PB) snowmelt model that requires only daily temperature and elevation information into the Soil and Water Assessment Tool (SWAT) model. The model predicts the spatiotemporal snowpack distribution without adding additional complexity, and in fact reduces the number of calibrated parameters. To demonstrate the utility of the PB model, we calibrate the PB and temperature‐index (TI) SWAT models to optimize agreement with stream discharge on a 46‐km² watershed in northwestern Idaho, United States, for 10 individual years and use the calibrated parameters for the year with the best agreement to run the model for 15 remaining years. Stream discharge predictions by the PB and TI model were similar, although the PB model simulated snowmelt more accurately than the TI model for the remaining 15‐year period. Spatial snow distributions predicted by the PB model better matched observations from LandSat imagery and a SNOTEL station. Results for this watershed show that including PB snowmelt in watershed models is feasible, and calibration of TI‐based watershed models against discharge can incorrectly predict snow cover.     

A Multi‐Scale Analysis of Single‐Family Residential Water Use in the Phoenix Metropolitan Area

Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management.     

Application of a DPSIR Modeling Framework to Assess Spatial–Temporal Differences of Water Poverty in China

Water shortage is a common problem around the world, especially in developing countries. Water shortage is closely linked to natural and social conditions, but the linkages between these natural and social conditions and their underlying temporal and spatial variation are less well explored. This paper details an application of the Driving‐Force‐Pressure‐State‐Impact‐Response (DPSIR) model, a holistic and sustainable tool for resources planning and management, and uses comprehensive weights to evaluate the water poverty (wp) in China from 1997 to 2014. This study applies the Kernel density estimation model to analyze the temporal variation trend and uses the least square error model to analyze the spatial pattern of wp. The results show the level of wp is gradually declining over time and the improvements in the coastal and inland wp situation are not spatially harmonious, and there are four primary types of wp in China based on drivers and causal mechanisms: D‐P‐I, D‐P‐I‐R, D‐P‐S‐I, and D‐P‐S‐I‐R. Furthermore, we analyze the main causes of spatial difference of wp and put forward corresponding countermeasures. The research findings are intended to provide a new insight for the evaluation of wp in the context of sustainable development, breaking past limitations that arise in simplified analyses using a single method, and to provide a strategy for regional water resources management to relieve wp.     

Investigating the Fate and Transport of Escherichia coli in the Charles River,Boston, Using High‐Resolution Observation and Modeling1

Abstract: The processes affecting the fate and transport of Escherichia coli in surface waters were investigated using high‐resolution observation and modeling. The concentration patterns in Boston’s Charles River were observed during four sampling events with a total of 757 samples, including two spatial surveys with two along‐river (1,500 m length) and three across‐river (600 m length) transects at approximately 25‐m intervals, and two temporal surveys at a fixed location (Community Boating) over seven days at hourly intervals. The data reveal significant spatial and temporal structure at scales not resolved by typical monitoring programs. A mechanistic, time‐variable, three‐dimensional coupled hydrodynamic and water quality model was developed using the ECOMSED and RCA modeling frameworks. The computational grid consists of 3,066 grid cells with average length dimension of 25 m. Forcing functions include upstream and downstream boundary conditions, Stony Brook, and Muddy River (major tributaries) combined sewer overflow (CSO) and non‐CSO discharge and wind. The model generally reproduces the observed spatial and temporal patterns. This includes the presence and absence of a plume in the study area under similar loading, but different hydrodynamic conditions caused by operation of the New Charles River Dam (downstream) and wind. The model also correctly predicts an episode of high concentrations at the time‐series station following seven days of no rainfall. The model has an overall root mean square error (RMSE) of 250 CFU/100 ml and an error rate (above or below the USEPA‐recommended single sample criteria value of 235 CFU/100 ml) of 9.4%. At the time series station, the model has an RMSE of 370 CFU/100 ml and an error rate of 15%.     

A Regional‐Scale Habitat Suitability Model to Assess the Effects of Flow Reduction on Fish Assemblages in Michigan Streams1

Zorn, Troy G., Paul W. Seelbach, and Edward S. Rutherford, 2012. A Regional‐Scale Habitat Suitability Model to Assess the Effects of Flow Reduction on Fish Assemblages in Michigan Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 871‐895. DOI: 10.1111/j.1752‐1688.2012.00656.x Abstract: In response to concerns over increased use and potential diversion of Michigan’s freshwater resources, and the resulting state legislative mandate, an advisory council created an integrated assessment model to determine the potential for water withdrawals to cause an adverse resource impact to fish assemblages in Michigan’s streams. As part of this effort, we developed a model to predict how fish assemblages characteristic of different stream types would change in response to decreased stream base flows. We describe model development and use in this case study. The model uses habitat suitability information (i.e., catchment size, base‐flow yield, and July mean water temperature) for over 40 fish species to predict assemblage structure in an individual river segment under a range of base‐flow reductions. By synthesizing model runs for individual fish species at representative segments for each of Michigan’s 11 ecological stream types, we developed curves describing how typical fish assemblages in each type respond to flow reduction. Each stream type‐specific, fish response curve was used to identify streamflow reduction levels resulting in adverse resource impacts to characteristic fish populations, the regulatory standard. Used together with a statewide map of stream types, our model provided a spatially comprehensive framework for evaluating impacts of flow withdrawals on biotic communities across a diverse regional landscape.     

Evaluation of Gauge‐Radar Merging Methods Using a Semi‐Distributed Hydrological Model in the Upper Thames River Basin,Canada

Gauge‐radar merging methods combine rainfall estimates from rain gauges and radar to capitalize on the strengths of the individual instruments. The performance of four well‐known gauge‐radar merging methods, including mean field bias correction, Brandes spatial adjustment, local bias correction using kriging, and conditional merging, are examined using Environment Canada radar and the Upper Thames River Basin in southwestern Ontario, Canada, as a case study. The analysis assesses the effect of gauge‐radar merging methods on: (1) the accuracy of predicted rainfall accumulations; and (2) the accuracy of predicted streamflows using a semi‐distributed hydrological model. In addition, several influencing factors (i.e., gauge density, storm type, basin type, proximity to the radar tower, and time‐step of adjustment) are analyzed to determine their effect on the performance of the rainfall estimation techniques. Confirming results of previous studies, the merging methods provide an increase in the accuracy of both rainfall accumulation estimations and predicted streamflows. The results also indicate specific factors such as gauge density, rainfall intensity, and time‐step of adjustment can reduce the accuracy of merging methods and play a key role in the examination of its use for operational purposes. Results provide guidance for hydrologists and engineers assessing how best to apply corrected radar products to improve rainfall estimation and hydrological modeling accuracy.     

A Hierarchical Model for Estimating Long‐Term Trend of Atrazine Concentration in the Surface Water of the Contiguous U.S.

Atrazine is a herbicide frequently detected in both surface and groundwater in the United States (U.S.), but its spatiotemporal distribution and concentration trends have only been analyzed recently at regional or local scales. We employed a Bayesian hierarchical modeling approach to assess spatial and seasonal variation in atrazine concentration trends between 1990 and 2010 for the contiguous U.S. A Markov chain Monte Carlo simulation algorithm was used to address the problem of left‐censored data (i.e., atrazine concentration values below method reporting levels). We observed opposing temporal trends in the northern (flat or decreasing) and southern (increasing) regions of the U.S. This spatial variation in temporal trends can be partially explained by the relative amount of cropland in the region. Flat or decreasing trends in the north are more likely in regions with high cropland coverage while positive trends in the south are more likely in regions with low cropland coverage.     

An Application of the T‐TEL Assessment Method to Evaluate Connectivity in a Lake‐Dominated Watershed after Drought

Lakes are landscape features that influence connectivity of mass and energy by being foci for the reception, mixing, and provision of water and material. Where lake fractions are high, they influence hydrological connectivity. This behavior was exemplified in the Baker Creek watershed in Canada's Northwest Territories during a two‐year drought in which many lake levels declined below outlet elevations. This study evaluated how lakes controlled surface runoff connectivity reestablishment following the drought using a new assessment method, T‐TEL (time scales — thresholds, excesses, losses). Analysis of daily data showed that during a summer period following the drought, connectivity occurred between 0% and 41% of the time. The size of run‐of‐the‐river lakes relative to their upstream watershed area, and the upstream lake fraction, are two factors for connectivity. These terms represent a lake's ability to control the size of storage deficits relative to rainfall, and evaporation and storage losses along pathways. The connectivity magnitude–duration curve only aligned with the watershed flow duration curve during high‐water conditions, implying lakes functioned as individuals rather than as part of a perennial watercourse during much of the study. The T‐TEL method can be used to quantify consistent metrics of hydrologic connectivity that can be used for regionalization exercises and understanding hydrologic controls on material transport.     

Evaluating the Applicability of a Two‐dimensional Flow Model of a Highly Heterogeneous Domain to Flow and Environmental Management

Two‐dimensional simulation of highly heterogeneous domains, especially those with disparate length scales, roughness conditions, and geometries, often leads to challenges such as long computation times and numerical instability. Simulation of challenging domains is often needed to guide flood management and environmental regulation agencies in operation and potential domain modifications. This work evaluates the ability of a two‐dimensional unsteady hydrodynamic model to represent long‐duration transient flows over a domain with highly heterogeneous roughness, geometric characteristics, and length scales through bed roughness representation. The domain includes 13 km of Cache Creek and the 14.5 km² Cache Creek Settling Basin, which traps both sediment and mercury. Calibration under different bed roughness methods, validation, and modeling results of bathymetric modification scenarios are presented. The modeling approach's performance supports its application as a tool for management of similar domains, such as settling basins, leveed floodplains, and reservoirs. Accurate representation of flow dynamics can also inform environmental management that involves transport of sediments, nutrients, and heavy metals. This study found that a two‐dimensional unsteady flow model can accurately represent long‐duration transient flow in a large settling basin with highly heterogeneous characteristics without parsing of the domain or flow events simulated.