DIFFUSE POLLUTION MONITORING AND ABATEMENT IN THE FUTURE CITIES

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1 Keynote paper at the International Workshop on TMDL Monitoring and Abatement Program presented at Konkuk University, Seoul (Korea0 on May 16, 2008 DIFFUSE POLLUTION MONITORING AND ABATEMENT IN THE FUTURE CITIES Vladimir Novotny Center for Urban Environmental Studies Northeastern University, Boston, MA (USA) INTRODUCTION In the US Clean Water Act, pollution has been defined as any manmade or man induced alteration of integrity of physical, chemical and biological integrity or receiving waters. The Clean Water Act also calls for providing conditions in these waters for primary contact recreation (swimming, water skiing, wading) while considering other uses such as water supply and navigation. Quality of receiving waters, used for water supply, is also covered in the Safe Drinking Water Act. The work of Karr et al. (1986) lead to the definition of integrity as a state of the water body that provides conditions for balanced unimpaired aquatic life and good water quality in adequate amounts for human uses. Integrity has three dimensions: physical/habitat, chemical, and biological. In the US, physical/habitat and biotic integrity components are expressed by multimetric indices. The chemical integrity is traditionally expressed by a probability of meeting an established chemical specific standard or by measuring whole effluent or in stream toxicity. Maintaining integrity is the main goal of the Clean Water Act (CWA). Similar, but not identical, is the EU concept of the ecological potential. Similar legislation has been passed in Japan and other countries. Figure 1 taken from Karr et al (1986) shows the components of integrity. This figure outlines the most important parameters affecting integrity and the stresses. Watersheds and their water bodies impacted by anthropogenic effects are subjected to external and internal stresses. These stresses can lead to impairment, i.e., damage to the ecosystem or diminishing of the beneficial uses of the resources (loss of sustainability). Pollution in the context of the Clean Water Act, according to its definition, is defined as any human action that downgrades the water body integrity or ecologic status. The term pollution implies many adverse impacts on integrity that generally could be generally categorized as (1) pollutants originating mostly from external sources such as effluent discharges, urban and agricultural runoff, construction erosion runoff, flow from open and deep mines, cooling water discharges, snowmelt containing deicing chemicals from highways; and (2) other causes of pollution that do not involve pollutants such as channel and habitat alteration, loss of riparian zones and wetlands. The term nonpoint pollution comes from an ambiguity of the definition of point source pollution in the Clean Water Act that states The term point source means any discernible, confined and discrete conveyance, including but not limited to any pipe, ditch, channel, tunnel, conduit, well, discrete fissure, container, concentrated animal feeding operation, or vessel or other floating craft from which pollutants are or can be discharged. This term does not include agricultural stormwater and return from irrigated agriculture. The nonpoint sources were then defined as everything else. Two common characteristics of the definition of point sources are they enter the receiving water bodies at 1

2 some identifiable single-or multiple point locations and they carry pollutants. But they can be vastly different and some, e.g., urban runoff or runoff from animal operations, may resemble nonpoint sources. Legally, in the US point sources under this CWA definition could be regulated and permits can be issued while nonpoint sources cannot be regulated and the controls are mostly voluntary. This is not true in many other countries, including the European Community and Japan, that can regulate and enforce controls of nonpoint pollution. Figure 1 Integrity concepts and the stressors (from Kar et al., 1986) Therefore, the IWA international group of specialists proposed a categorization of pollution sources as traditional point and diffuse sources. The traditional point source category strictly includes wastewater effluents from municipal and industrial effluents. The flow and pollution loads from these sources may vary in time; however, in most cases they are continuous, uninterrupted discharges, variability is not greatly related to meteorological factors and variability is not great. The primary parameters of interest for control and regulation are degradable organics (measured as BOD 5 or COD), suspended solids, ph, nitrogen and phosphorus and toxic compounds (both organic and inorganic). The prevalent control is treatment (Novotny and Olem, 1997). Diffuse pollution can be characterized as follows: Diffuse discharges enter the receiving surface waters in a diffuse manner at interrupted intervals that are related mostly to the occurrence of meteorological events. Highway snowmelt can be induced by application of deicing chemicals. Waste generation (pollution) arises over an extensive area of land and may be in transit overland before it reaches surface waters or infiltrates into shallow aquaifers. Diffuse sources are difficult to monitor at the point of origin of the polluted flow. Unlike the traditional point source, where treatment is the most effective method of pollution control, abatement of diffuse pollution is focused on land and runoff management practices and restriction of polluting land use activities. Compliance (performance) monitoring is carried out on land rather than in water. Waste emissions and discharges cannot be measured in terms of effluent limitations. The extent of diffuse waste emissions (pollution) is related to certain uncontrollable climatic events, as well as geographic and geologic conditions, and may differ greatly from place to place and from year to year. 2

3 The most important constituents from diffuse sources, subject to the management, are suspended solids, nutrients, salinity (from deicing chemicals and irrigation return flow), and toxic compounds. Many countries have developed and implemented or are planning to implement a water quality abatement and control planning similar to the Total Maximum Daily Load process in the US, Japan, or Water Framework Directive in the European Community. These programs require agencies to identify water bodies where effluent point source controls and mandated nonpoint pollution controls will not achieve the water quality goals specified by the national ambient water quality standards and criteria. These programs generally require the following steps (National Research Council, 2001): water body status assessment, estimating loads from point and nonpoint sources, development of models for estimating the loading (waste assimilative) capacity of the water body that would attain and keep the water body in compliance with the standing water quality standards and criteria related to the designated use of the water body, and allocating the loading capacity among the point, nonpoint and background (natural) pollution loads with a margin of safety. Figure 2 shows the TMDL process and the phases that require monitoring. Figure 2 Schematics of the rotating TMDL process and monitoring phases (from National Research Council, 2001; Novotny, 2003) 3

4 MONITORING The overall objective of monitoring is to gather observational knowledge about the aquatic and terrestrial ecosystems and their stressor. Diffuse pollution has been recognized as the major stressor and diffuse pollution, however, focusing on the diffuse pollution ignoring other major stressors such as the point sources, habitat and riparian zone degradation, land use transition, ecosystem fragmentation (e.g., by dams, weir, and impassable culverts) would not provide the total knowledge about the system and could lead to imperfect and inefficient solutions. Thus, monitoring is a comprehensive and inclusive process. Diffuse pollution and its sources have been characterized as being intermittent (with the exception of polluted groundwater discharge into perennial streams) and distributed over the land. At some point the runoff enters into a channel with concentrated flow. The monitoring program is always designed with the objectives in mind which are: Developing hydrological budgets and pollution mass balance of sources and receiving water bodies. Horn (2000) described a methodology, using readily available public domain data, on development of water budgets including inter- and intrabasin transfers. Urban basing are impacted by long distance transfers of water and wastewater. Potable water is delivered by aqueducts from larger distances and, after use, wastewater is typically transported to distant regional wastewater plants. Water and wastewater transport is mostly underground and strongly affected by leakages that can be in two directions, i.e., infiltration (I-I) inputs of often contaminated groundwater and exfiltration of clean drinking water from the water supply lines and wastewater that contaminates groundwater. Water body, watershed and pollution assessment. In the integrated watershed management context, attaining and preserving the ecological and public health integrity is the goal. As defined previously, integrity has physical (habitat), chemical and biological components. If the integrity is impaired, water body assessment reveals the physical, chemical and biological status of the water body and of the watershed and identifies the internal stresses such as habitat impairment, poor water and sediment quality, imbalanced biota shifted toward more tolerant species or even absence of indigenous species. It also looks into the watershed to qualitatively and quantitatively identify external stresses that cause the impairment such as pollution generating land use and land use activities, effluent discharges, mine water discharges, contaminated land, etc. It assesses the habitat and fragmentation of it. Water body assessment is an integral and revolving (continuous) activity. Research and development of diffuse pollution and water quality models describing pollution generation and its movement overland and in the channels. Such models can be used for calculating the loads. In conjunction with the receiving water quality models, such models then calculate the total maximum daily load. By back calculating, the loading capacity of the loading capacity of the receiving water bodies. Such monitoring is done o In the air, such as measurements of quantity and quality of wet and dry deposition; meteorological factors; o On the land generating diffuse pollution loads such as street and highway dust and dirt accumulation, soil and surface cover characterization for erosion estimates, soil pollutant content; o In the ephemeral (flowing only occasionally during wet weather) streams or conveyance channel or sewer; o In the receiving water body upstream and downstream from the outfalls or discharge conduits. 4

5 Continuous or periodic monitoring by agencies and universities. Such monitoring is generally done in the receiving water bodies or groundwater wells and not on land. Continuous monitoring by agencies measures at selected points include flow, ph, temperature, dissolved oxygen, conductivity, turbidity and possibly others. Periodic monitoring may involve a plethora of parameters ranging from organic biodegradable pollutants (BOD, COD), oil and grease, ions (chloride, sodium), nutrients (nitrogen compound and phosphorus), minerals (calcium and magnesium, hardness), toxic metals (total and dissolved), cyanides (deicing salt additive), polyaromatic hydrocarbons (PAHs), petroleum hydrocarbons, pesticides, bacteria, protozoa, algae, macroinvertebrate organisms and fish. Data Needs Almost all monitoring programs are site or region specific; hence, the monitoring program must be designed to fit the objectives and provide the specific data needs that would lead to good knowledge. Because of the three dimensions of integrity, data may be needed for I. Assessment of the physical integrity of the water body that includes habitat conditions, hydraulic and hydrologic conditions, substrate, slope, etc. II. Assessment of the biological integrity. Biological surveys are needed to identify the composition of the biota living in water (fish, macroinvertebate, zooplankton, phytoplankton, and peryphyton) and in the benthic layer (benthic macroinvertebrate composition). III. Assessment of chemical integrity. Routine monitoring and survey data are needed on key water quality parameters that are generally divided into physical (e.g, temperature, turbidity or clarity, color, ph), biodegradable organics (BOD, COD, TOC), nutrients (organic and inorganic nitrogen compounds and phosphorus), and organic and inorganic priority pollutants. In some cases, information on radiological parameters is also being collected. Role of GIS Unlike point source impacts on receiving water bodies, which is in most cases one dimensional, diffuse sources generate loads from land segments of the watershed, hence, the problem is at least two dimensional. In this case, Geographical Information Systems (GIS) play a very important role. The Geographical Information System (GIS) is a powerful mapping, presentation and analytical software that can be conveniently used for many purposes from which the following are important for diffuse pollution abatement planning and TMDLs (Novotny, 2003) Storage and display of pertinent watershed characteristics Storage and display of meteorological, hydrological, and water quality data Mapping and inventory of point sources and polluting land segments throughout the watershed Mapping of habitat and riparian buffers and corridors Development of input data for loading and water quality models and the display of model outputs Development of one dimensional and two dimensional models for many processes generating pollution loads from diffuse sources such as erosion, land use changes, vegetation impact, watershed ecological fragmentation, source modeling and identification. 5

6 GIS connected to the internet can retrieve and download many important data sources, e.g., land use distribution, vegetative cover, soil type and hydrologic characterization, streams and lakes, wetlands, location of point sources, highways and railroads, imperviousness, topographical maps, slope and elevation. Field Monitoring A typical monitoring station (Figure 3) has the following component: 1. Rain gauge (typically tipping bucket). 2. Wet and dry atmospheric deposition collector. 3. Flow monitoring device. 4. Quality monitoring device (continuous monitoring probes and automatic samplers). 5. Power source. 6. Telecommunication link or recorder of data. Automatic flow activated samplers and flow meters are available from several vendors. These sampling stations retrieve discretionally small amounts of sample from the conduit (channel or sewer) at either uniform intervals or in proportion to the flow. On site analyses are typical only for few constituents (DO, turbidity, conductivity, ph and temperature) while the other analyses are done in the laboratory. For this purpose the samples must be preserved either by cold temperatures or chemically. A composite sample is a mixture of the grab samples collected by the sampler. Analyzing the mixture of flow proportional samples taken during a runoff or snowmelt event will yield an Event Man Concentration which is the most important pollution strength characteristic. Figure 3 Typical field monitoring station in rural setting. Field monitoring stations are often temporal and collect data for various purposes but mainly for characterization of wet weather discharges. They are located mostly at the storm sewer outlets, in the manholes or catch basins of sewers or small channels into which the outlets are directed. Continuous monitoring such as that for dissolved oxygen concentrations, conductivity, ph, temperature, etc., can be accomplished by submerged probes connected to recording and/or transmission devices. However, continuous monitoring requires perennial flow, not typical for diffuse pollution that is generated by precipitation. The data are used for developing hydrographs and pollutographs of the wet weather events. Collecting data can be activated by flow. The monitoring stations in a watershed can be connected and form a network. 6

7 One of the most important and pioneering monitoring studies characterizing diffuse pollution by urban runoff was the Nationwide Urban Runoff Project NURP (US EPA, 1983). This approximately three year study established numerous monitoring stations in 28 municipalities throughout the US. For example, a study in Milwaukee (WI) had 8 pairs of monitoring stations on storm sewers draining streets with different traffic densities located in various neighborhoods (low, medium, and high density, commercial, industrial) in addition to small watersheds undergoing development such as construction pollution and parking lots. The NURP study has proven that urban stormwater runoff is a significant source of diffuse pollution and gave an impetus to the US Congress and US Environmental Protection Agency to implement urban stormwater discharge permitting. The US Geological Survey has established throughout the US many gauging and quality monitoring stations for routine and continuous data gathering on larger (2 order and higher) perennial streams. Establishing Environmental Observatories An urban environmental observatory is a system that addresses the need for addressing comprehensive fundamental scientific questions on a watershed scale, where data are collected in a coherent coordinated fashion and the use of sensor networks and cyberinfrastructure are key system elements (Welty et al., 2007). The observatory employs a network of monitoring stations and sampling points that address the knowledge gathering laterally and vertically. Lateral data gathering implies a geographically distributed network of interconnected monitoring stations supplemented by grab sampling points, vertical sampling implied data gathering in groundwater, surface water and the atmosphere. Sampling is also conducted on land segments characterizing the watershed. Urbanization and other land conversion activities by man dramatically changed the conditions of the watersheds. The most dramatic change has been the change in imperviousness. However, there have been few comprehensive studies characterizing these changes and resulting in a good understanding of the effects of imperviousness, infrastructure and other large scale land uses on the overall ecological status of the watershed. We know the symptoms of urbanization and by the same reasoning of the conversion to agriculture but have only a rough qualitative understanding of root cause effects and processes that lead to the overall impairment of integrity of receiving waters. For example, until recently, many authors who studied the effects of urbanization on the integrity of the receiving waters expressed by the Index of Biotic Integrity IBI (Karr et al., 1986) simply related IBIs to the percent of imperviousness or percent of urbanization. Novotny et al. (2005) argued that percent imperviousness is not a direct cause of impairment; it is an imperfect surrogate for a plethora of direct effects impacting habitat, pollution levels, watershed and water body fragmentation, street salting practices and other factors and processes. In order to find a meaningful relationship between the integrity expressed by the Indices of Biological Integrity and main stressors a large number of parameters on land use, diffuse pollution, in stream water quality, habitat, and riparian quality must be collected. The monitoring program essentially measures components and processes of the hydrologic cycle. If the land use changes from the pristine (natural) land to urban, surface mining, agriculture or other disturbing land uses, hydrologic cycle and mass balance of pollutant inputs from diffuse sources changes dramatically. The hydrologic cycle is often illustrated by a conceptual sketch of a landscape or a block diagram of processes that transform precipitation to the three components of flow in the receiving water body: (1) surface runoff; (2) interflow and (3) groundwater flow (Figure 4). Diffuse pollution is an integral part of the hydrologic cycle. The built-in and impervious area has significant impact 7

8 on the magnitude and the peak flows and the time to the peak and often on the magnitude of the Event Mean Concentrations of the pollutants. The diffuse pollution generation process is complex and the knowledge of the sources strength and the transport processes from the source to the receiving water bodies is useful in the abatement plans. On the other hand, pollution generation is a statistical process that has a great degree of randomness; therefore the monitoring programs and frequency of data acquisition should be such that would also reveal the random component, because it is more difficult to control and it plays a great role in determining the exceedance of the water quality standards. Figure 4 Hydrologic cycle and diffuse pollution generation components However, the hydrologic cycle is also connected to landscape and the quality of the riparian corridor and all of these affect the integrity of the receiving waters. Thus the monitoring program must also cover the landscape hydrology and ecology and their interconnectivity with the aquatic systems. In the US, two multimillion urban observatories sponsored by the National Science Foundation were implemented and have now operated for several years in Baltimore (MD) and Phoenix (AZ) (Welty at al., 2007). Monitoring of reference water bodies and watersheds The definition of pollution in the US Clean Water Act stipulates that the infringement of integrity should be caused by humans currently or in the past. This differentiates pollution from water quality impairment by natural causes such as mud slides caused by extreme meteorological events, earthquakes, tsunamis or lack of flow in arid regions or dystrophic conditions of wetlands. In the TMDL process, aquatic integrity standards or criteria must be attained if pollution is caused by pollutants. The water quality standards regulations established a process known as Use Attainability Analysis (US EPA, 1994; Novotny et al, 1997) which, if approved, can modify the standards to reflect the contributions from natural sources such as high sediment loads in arid areas, water contamination by metals in areas with metal ore deposits, streams draining wetlands with naturally dystrophic (low DO) conditions, etc. Monitoring of reference water bodies that are least impacted by humans provides information on natural and global (uncontrollable) background pollution. 8

9 The notion of reference water bodies should be expanded to the watersheds. Reference water bodies and watersheds are usually in pristine nature areas and they usually contain smaller headwater streams. In the US, a network of reference water quality monitoring stations was established under the National Water Quality Assessment (NAWQA) program ( NAWQA is identifying how the natural features and human activities affect water quality, and where those effects are most pronounced. Having information on reference water bodies is especially important for establishing the magnitude and water quality effects of diffuse pollution whereby, for example, erosion can be caused by anthropogenic activities (e.g, agriculture, construction activities) and, hence, it constitutes pollution, or be natural and not be considered as pollution. Reference monitoring may not be limited only to pristine watersheds that often may not be available for a given setting and land uses. Reference sites can be established upstream of a disturbing site, area or discharge, or even far downstream where the effects of the disturbance or discharge are fully attenuated by selfpurification and/or dilution. Chemical Integrity The TMDL process requires several types of modeling efforts and supporting data (Figure 5) Figure 5 Type of models used in describing diffuse sources of pollution and their impact on receiving waters. Pollutant loads Many scientists and graduate students are using and still developing runoff (snowmelt) quantity and quality models. Most of these models are mechanistic or deterministic. Deterministic (mechanistic) models are generically a priori developed from an assembly of known processes, for example, hydrologic processes included in rainfall/runoff transformation, accumulation of pollutants in the watershed, vegetation growth and hydrological and pollution impact, etc. The model components are then tested by special field monitoring and, in the final stage, the entire model is then calibrated and verified by field data for modeling a specific watershed. Hence, development of these models requires a detailed monitoring of the inputs (precipitation, atmospheric wet and dry deposition) and outputs (hydrograph and pollutographs) in addition to measurements of various system parameters such as soil 9

10 erodibility, slope of the terrain, imperviousness, vegetation cover, and pollutant content of soils. These models are either lumped parameter or distributed parameter models. The sampling must be taken throughout the runoff event and in between. Many models focused on characterizing the first flush of the pollutant load. Deterministic models do not consider random variables and for each unique set of input data they produce fixed repeatable results. A mechanistic model is a representation of the physical, biological, or mechanistic theory governing the system; in contrast, a statistical model accounts for the statistical fitting of equations to the available data. The National Urban Runoff Project NURP (US EPA, 1983), after analyzing hundreds of storms, established that intra event concentrations of pollutants do not follow any pattern and existence of a consistent first flush in urban runoff is questionable. Instead, NURP scientists proposed to monitor, model and analyze the event mean concentrations (EMCs). Water and sediment quality standards/criteria 1 and monitoring support Water quality standards regulation in the United States allows states to develop numerical criteria of their own or modify EPA's recommended criteria to account for site specificity or other scientifically defensible factors (US EPA, 1994). The criteria may be based on chemical specific numeric values for the priority pollutants or on the whole effluent toxicity (the term effluent applies to point discharges regardless of whether these are of diffuse or traditional point origin). The ambient water quality standards are related to the designated use of the water body. The federal standards for the priority (toxic) pollutants and several other key water quality compounds are expressed in three statistical dimensions: I. Dimension of magnitude - specifies the numeric magnitude of the standard expressed commonly as the limiting concentration. This dimension puts a limit on extremes such as high concentrations of compounds that are toxic at higher concentrations or minimum concentrations that are needed to sustain healthy aquatic life. II. Dimension of frequency of allowable excursions - is how often the standard can be exceeded. Typical frequency of allowable excursions may be once in three years. This dimension is related to survivability or well being of the aquatic biota to repeated stresses or the level or maximum survivability and recovery after an extreme stress. III. Dimension of duration - specifies for how long the standard can be exceeded. The dimension of duration is important for standards that are based on chronic long term exposure. The US standards recognize one day (instantaneous grab sample) duration for all acute toxicity standards, and consecutive four or thirty day average for chronic toxicity standards. Many states are still using a simplified and distorted frequency/duration component by substituting the rule that a numeric standard must be maintained (not exceeded) at all times. Such an unlimited limitation is a statistical impossibility because there is always a chance albeit very remote that a water/sediment quality parameter a high, but statistically possible, value exceeds an established standard (National Research Council, 2001; Novotny, 2004). Insisting on no excursions at all makes TMDL unworkable, especially for wet weather sources which constitute most of diffuse pollution. These sources can only be defined in terms of statistical terms and include a strong random component. 1 In the US the term criterion refers to a limiting values derived from scientific knowledge or experience. A standard is a legal limit issued by an authority such as a state or federal government or a court. 10

11 The requirement of nonexcursion at all, when applied to measured data also brings a lot of ambiguity as to how many samples are required for describing the nonexceedance at all times. For example, Figure 6 shows that if someone samples the water quality process in a receiving water body, conclusions on exceedance may be different if only 9 or 10 samples are available over the period of three years then if 50 or more samples are available of the same series and over the same time period. In this presentation it is assumed that the statistical distribution of sample values of the series follows the so called log-normal Gaussian distribution which is exhibited on Figure 6 by plotting logarithms of sample values on Y - axis and probabilistic scale on X - axis. A small number of samples by chance may result in no excursions while with 50 or more samples, violations could occur. Concentrations of constituents in runoff and in many streams can be satisfactorily fitted to the Log normal Gaussian probability models and plotting (US EPA, 1983; Novotny, 2004). Thus, the excursions of extreme concentrations typically can not be realistically ascertained from a small number of samples and without fitting the data to a probabilistic model. Figure 6 Concept of log normal probability plotting and analysis. 99.8% probability of being equal or less corresponds to once in three years exceedance if the samples represent grab samples, 24 hour composites or EMCs. If the data are random and log-normally distributed, then a frequency of once in 3 years of allowable excursions corresponds to a probability of 1/(365x3) = or 0.1% probability of being exceeded or 0.2 of being equaled or exceeded. The = 99.8% probability should be the minimum probability of compliance (see Figure 6). It is quite possible that different countries may have different requirements of the mandatory compliance. Furthermore, the 99.8% compliance requirement only applies to acute toxicity criteria for a set of 127 priority pollutants defined in the US. Pollutants such as dissolved 11

12 oxygen (not an issue in diffuse pollution assessment) or nutrients are assessed using different duration and frequency dimensions but the concepts may be the same as those developed for toxic pollutants. Furthermore, toxic pollutants in urban runoff are of major concern. The time series of data generally contain four underlying components (Novotny et al, 1976): o A trend, i.e., the parameter is generally increasing, decreasing or is steady over the time. o Several periodicities or seasonalities such as annual, seasonal, weekly or daily, may also be variable with the time. For example, annual seasonality of a parameter can be affected by global warming or by expansion of the city or by intensification of agriculture. o Autocorrelation component (a high value is very likely followed by another high and low value is followed by another low). o Random component that can exhibit wide bend or short bend fluctuations. The data of one parameter in a time series can also be cross-correlated to another parameter or parameters. Strong cross-correlations can be found between turbidity and suspended solids, conductivity and salinity and chloride concentrations; however, some perceived cross-correlations such as suspended solids (turbidity) to nitrogen or phosphorus are typically weak or none. Some correlations may be spurious such as the well known and frequent attempts to correlate logarithms of sediment load (concentration of suspended sediment time flow) to the logarithm of flow. Theoretically, only the random component (white noise) would follow a Gaussian normal distribution (with or without a logarithmic transformation). Trends, periodicities and autocorrelation should be identified and incorporated into a model. If the data are taken frequently enough and in regular time intervals, they can be expressed by an ARMA (autocorrelation-moving average) or ARMA-Transfer Function (cross-correlated) model (Box and Jenkins, 1976). Missing data substitution In the US, the standards/criteria for chronic toxicity require 4, 7 or 30 day moving average (composite) samples. Seven day averaging is typical for the dissolved oxygen standard, 4 day averaging is used for assessment of chronic toxicity of priority pollutants and 30 averaging are for chronic toxicity of ammonium/ammonia. Such standards require daily or, in an extreme, continuous sampling, so that compositing or averaging over the 4,7 or 30 days period can be made, which is not available or possible in most cases. Furthermore, the effect of diffuse pollution is intermittent and averaging is not possible. Hence, the monitoring program should provide enough data to discover and retrieve the three components and their stochastic characteristics, thus enabling to ascertain the extreme values for the standards that require averaging. The most simple and popular method is Monte Carlo simulation (Novotny, 2004). Example of Urban Monitoring Monitoring flow and quality of road/highway runoff A metropolitan urban area in the US of 3 million inhabitants has a dense network of urban highways and freeways. Its highway agency has embarked on a study to quantify the pollution strength of the highway runoff. The monitoring was contracted to a federal agency responsible for flow and water quality monitoring. 12

13 The monitoring agency established 12 monitoring stations on the state highways. The selected sites for each highway contained a well-defined impervious area that included a single catch basin or several catch basins that shared a common outlet pipe. The sites had limited shoulder runoff which reduced the chemical and hydrologic bias associated with local soils and vegetation. Each station monitoring highway flow from a catch basin was equipped by instrumentation to measure water level, water temperature, air temperature, specific conductance, turbidity and rainfall. Each of these parameters, during the event, were measured in one minute intervals but recorded and averaged in much longer time intervals (in hours). Flow was estimated from water level measurements using a level-discharge relationship. Each station was equipped with an automatic sampler containing a 20-liter Teflon lined bottle. The datalogger was programmed to take a sample in proportion to flow, approximately 24 samples were taken and mixed with the bottle content for every centimeter of rainfall. Hence the sampler provided measurement of the Event Mean Concentrations. The type of roads and highways sampled ranged from two lane roads with medium traffic density per lane (6000 to vehicles per lane per day) to high density four to eight lane freeways with the high traffic density ranging from to vehicles per lane per day. The constituents, analyzed as EMCs by monitoring, included nitrogen compounds, phosphorus, toxic metals, iron, suspended sediment, PAHs, potassium, sodium, sulfate, calcium, chloride, manganese, magnesium, and alkalinity. Figure 7 shows the probability distribution of the EMCs for the toxic metal copper compared with the water quality standard for copper (which in the US is site specific and is computed from hardness of the flow). The plot shows that roughly 85 % of samples would not meet the water quality standard if the highway flow was the only flow in the receiving water body. The ambient (water quality) standards are applicable only to the receiving waters and not directly to the road/highway flow. This probability plotting and numeric analyses are compatible with the water quality standards expressed in three dimensions of magnitude, frequency and duration. For the acute toxicity standard exhibited in Figure 7, the duration is one hour which implies that in some cases the EMC may be somewhat less than the hourly maximum. For estimating the actual impact on a receiving water body, a section of a highway discharging into a selected small river section was identified. The section was a four lane highway with the traffic Figure 7 Log normal probability plot of road/highway copper concentrations with water quality standard density of about vehicles per lane per day. The section of the road contributing flow to the receiving water body was about 2 km long. A mass balance model concept of which is presented on Figure 8 was used for the analysis. For the modeling, a three year period of measured river flows and calculated highway flows by a well known TR -55 runoff curve were calculated and entered into the Excel spread sheet. Using the daily mass balance of river (natural/background) and highway flow copper loads, the downstream concentrations were calculated for each day on the record. In the Monte Carlo calculation, once the highway flow was calculated from measured precipitations a random 13

14 number ranging from 0 to 1 was generated by the computer and converted to the percent of probability of being less or equal. According to the probability, the highway copper concentration was selected from the probability plot on Figure 7 using a formula. The downstream concentration calculated by the mass balance model was then compared with the water quality standard and the number of exceedances in the three year period was counted. Although the three year period represents about 1095 river concentrations, only about 210 are impacted by the wet weather flows and could potentially encounter an exceedance. Because the concentration in the highway is randomly selected for each day with highway runoff, the calculations were repeated 10 times which provided estimates equivalent to more than 6300 wet days. The results of the Monte Carlo simulations revealed that the stream concentrations of copper receiving highway runoff would violate the water quality standard on average 25 times over a three year period while only one to two exceedances would be allowed by the frequency component of the water quality standard. Figure 8 A simple mass balance model for calculating stream concentration impacted by highway runoff Monitoring Physical and Biological Integrity Physical habitat quality In-stream habitat quality is usually measured with a multi-metric index. In the US, each state may have its own variant or calibration of this index to account for specific regional reference conditions. Examples are the Qualitative Habitat Evaluation Indices (QHEI) in Ohio, or the Physical Habitat Indices (PHI) in Maryland (Rankin, 1989; Hall Jr. et al., 1999, Paul et al., 2003). Even though a great variety of stream habitat indices and sampling methodologies exists, efforts have been made to unify criteria and simplify habitat quality evaluation with methodologies such as the Rapid Bioassessment Protocols for Use in Wadeable Streams and Rivers by Barbour et al. (1999). Habitat indices are mostly based on qualitative evaluation of different physical parameters, which are suspected to have an impact on the stream s fauna. The parameters are scored by experts on a scale depending on their degree of variation from reference sites. The scores for the different parameters (called metrics) are then summed and scaled. In the case of Minnesota and Ohio s QHEI and Maryland s PHI, the index ranges from 0 (very poor) to

15 (excellent). This multimetric approach is used in more than 85% of water quality programs in the US (Southerland and Stribling, 1995). Measurement of some or all of the large scale variables such as upstream drainage area and riparian corridor land uses are usually missing when the physical habitat is evaluated. Habitat indices usually measure the physical quality of a stream reach in which biological sampling is performed. Not only land use might be important, according to some authors, streamflow and hydrologic alterations can be considered as a key factor that limits the distribution and abundance of riverine species (Power et al., 1995;Poff et al., 1997). Protection of the natural flow regime has been historically ignored by conservation agencies and only focused on one aspect: minimum flow. However, five critical components of the flow regime regulate ecological processes in the river ecosystems: magnitude, frequency, duration, timing, and rate of change of hydrologic conditions (Poff and Ward, 1989; Richter et al., 1996). Efforts trying to link flow regime to the distribution of fish assemblages have been made by Poff and Ward (1989) and Poff and Alan (1995). Some indices of human hydrologic alteration have been developed (Richter et al., 1996). Diffuse pollution can affect the habitat in several ways; Increased peak flows and more frequent high flows cause channel and stream bank erosion which impacts adversely habitat. Increased sediment inputs cause bottom siltation which is expressed in the habitat index as bottom substrate quality or embeddedness. These two parameters have been found as the top stressors affecting biotic integrity. Urban streams do not typically have adequate and healthy riparian zones and have channels altered by dikes, vertical masonry banks that prevent spawning. Biotic integrity monitoring A fish IBI is constructed from fieldmeasured component metrics that include parameters related to species richness and composition, trophic composition, and organism abundance and condition, and is based upon the premise that fish respond to environmental stressors in a species- or guildspecific manner. Metrics are scaled relative to covariation with natural factors (e.g. stream size or Figure 9 A field crew sampling aquatic biota (fish and geographical distinctions), macroinvertebrates) by electric shocking for estimation and when properly Indices of Biotic Integrity calibrated, allow for the calculation of a rating that describes the streams ecological health relative to best case, or non-impacted ecoregional reference. Thus IBIs can provide a biological response signature for monitoring compliance 15

16 with antipollution regulations (Yoder and Rankin, 1999). Many states have developed their own fish IBI (Ohio EPA, 1987; Niemela and Feist, 2002, Roth et al., 2000). Also numerous benthic community indices exist. Some examples are the Hilsenhoff index (Hilsenhoff, 1987), the ICI or Ohio s Invertebrate Community Index (Ohio EPA, 1987), the Benthic Index of Biotic Integrity (BIBI) in Maryland (Stribling et al., 1998), or the Macroinvertebrate Index of Biological Integrity (MIBI) in Minnesota (Chirart, 2003; Genet and Chirart, 2004). The advantages of measuring macroinvertebrates instead of fish are that they are relatively immobile, easy to collect at low cost, and occupy all stream habitats and are quick to react to environmental change (Ohio EPA, 1987, Mason, 1991). In the last ten years, USEPA and state agencies have conducted extensive monitoring of the physical, landscape and chemical parameters along with measuring the metrics of the IBI (fish and macroinvertebrates). Since the early 1990s there has been a considerable interest among scientists to develop models that would correlate the indices with various stressors; for example, degree of imperviousness or urbanization in the watershed (Wang et al., 2000; Novotny et al., 2005). However, very few water bodies, streams and impoundments (both man made reservoirs and natural lakes) are being degraded only by one stressor. Furthermore an increase in one stress may affect one group of organisms negatively but some other group, e.g., species with pollution tolerance, positively. In the US, the Index of Biotic Integrity (IBI) contains twelve fish metrics (Barbour et al., 1999) and the index itself is a composite of metric scores (Table 1). A cluster contains sites that have some distinct similarities, either in fish endpoints (IBI metrics) or stress effects (e.g. land use, geomorphology, and high loads of pollutants). Table 1 Metrics of the Index of Biotic Integrity (Karr et al., 1986) Metrics Function Comment Species Richness Number of darter species Number of sunfish species Number of sucker species Community Composition Intolerant species Percent green sunfish Environmental Tolerance Percent omnivores Percent Insectivores Community Function % Top carnivores Percent Hybrids % Diseased individuals Community Condition Number of fish Metric scoring is 1, 3, 5 Maximum scoring range for the IBI is 12 (no fish) to 60 (excellent) IBI is calibrated on a regional basis Scoring adjustment is needed for very low numbers Analyses of large monitoring data bases knowledge mining Very few water bodies, streams and impoundments (both manmade reservoirs and natural lakes) are being degraded only by one stressor. Diffuse pollution represents a multiplicity of stressors such as a change of hydrology and pollution loads that not only affect water quality but also habitat (siltation, substrate, embeddedness, bank stability) and physical parameters such as temperature and turbidity. Each stressor affects the biotic population or water quality in an individual way. Furthermore, an increase in one stress may affect one group of organisms negatively but some other group, e.g., species with a higher pollution 16

17 tolerance level, positively. The well known sequence of algal population shifts or shifts in fish population from salmonid to carp dominated fish populations, continuing then to fish disappearance at very high levels of stress, are well known. However, the complex nonlinear multiple effects are not quantitatively known. The multiple effects of stress and shifting composition, diversity and density of the fish, macroinvertebrate and algae population are not gradual and may have several intermediate semi-resilient states. This leads to the concept of ecological clustering which is explained on Figure 10. MSR is the maximum species richness parameter, which expresses the risk of species disappearance from the system due to the stress by one stressor. The figure shows that multiple stressors with different thresholds can cause clustering of the responses. A cluster is a group of sites exhibiting similar multiparametric response to a multiplicity of stressors. A methodology and software was developed to identify clusters and cluster dominating environmental variables (Manolakos, Novotny and Virani, 2007; Virani et al., 2005). A cluster may also express a resilience of the status and shifts from one cluster to another are mostly not linear but not yet quantitatively known. The concept follows the hierarchical, four layer progression from landscape and hydrologic/hydraulic allochthonous stresses, and diffuse and point pollutant inputs to instream impacts causing risks to aquatic biota. Figure 10 Concept of the impact of multiple risk stressors on multi metrics index of biotic integrity and justification for clustering Figure 11 Distribution of the fish IBI for Ohio (left) on the SOM and the corresponding boxplots (right) of IBIs for the individual clusters. Four risks can be considered: habitat degradation, water pollution by pollutants, sediment contamination and fragmentation. The layered hierarchical structure was explained in Novotny et al. (2005). Using the unsupervised Artificial Neural Network modeling, large data bases from Ohio, Maryland, Wisconsin and Minnesota, containing water quality, habitat, and landscape as inputs into the model and fish macroinvertebrate metrics as outputs were analyzed and organized into clusters in the Self Organizing Map (SOM). The Ohio SOM is shown on Figure 11. The data bases in each analyzed state contained more than one thousand sites with up to fifty parameters each. The subsequent analysis of the effects of the environmental variables by the Canonical Correspondence Analysis can then reveal the cluster dominating parameters out of about forty environmental variables affecting the biotic integrity by overlying the SOM of fish metrics by SOM mapping of the environmental variables. CCA then linked 17

18 the stressors to the SOM and quantitatively ranked the stressors as to their impact on IBIs and their metrics (Figure 12). Through a SOM of fish metrics it was possible to divide the sites in Maryland and Ohio into three clusters that reflected the quality of the fish community. The overall fish IBIs in the clusters indicated that Cluster I had superior fish composition, Cluster II was intermediate, and Cluster III was inferior. The environmental variables (habitat, chemical, landscape) were then superimposed on each cluster and determined which variables play the major role on fish assemblages within the cluster. For example, Cluster I was Figure 12 Cluster Dominating Parameters in relation to SOM of IBI metrics for Ohio. The length of the arrow is a measure of the degree of impact of the parameter (Virani et al, 2005) predominantly affected by physical/habitat parameters and DO, and Cluster III is impaired by chemical (pollutant) parameters. These parameters are then Cluster Dominating Parameters (CDP). It is interesting to note that the majority of the variables that had the greatest impact on the integrity of investigated streams were in the category of habitat parameters (e.g., substrate quality, gradient, cover, pool and riffle quality) and not pollutant concentrations. Many parameters were cross-correlated. Because each neuron of the SOM contains several physical monitoring sites, it was possible to locate the clusters regionally and put them on the map and to identify the top 25 CDPs. Best Management Practices (BMPs) for Urban Areas and Highways The BMPS for control of urban and highway diffuse pollution are extensively featured in Novotny (2003) and many other texts and manuals, some of them downloadable from the internet. Pollution by urban and highway runoff may be controlled by a large number of BMPs and usually one BMP may not be enough nor may be universally applicable. The control measures can be structural (hard) and expensive or nonstructural (soft) and less expensive. The original classification in Novotny (2003) divided best management practices into the following categories: 1. Prevention. These are practices that prevent deposition of pollutants on the urban landscape o Removal of harmful compounds from atmospheric emissions by industries and traffic (e.g., banning lead from gasoline) o Ban on production and application of harmful chemicals (e.g., PCBs, DDT) o Education of the public on prevention of illicit disposal of chemicals into drainage systems and litter disposal o Reduction of the use of harmful road deicing chemicals o Adoption of site disturbance prevention ordinances and programs o Implementation of programs minimizing infiltration/inflow into storm sewers 2. Source control. Some practices prevent pollutants from coming into contact with precipitation and stormwater runoff o Surface protection of construction sites by mulching or temporary seeding o Street/highway sweeping 18

19 3. Hydrologic Modifications. These practices minimize runoff formation from precipitation o Infiltration devices (porous pavement, infiltration trenches and ponds, infiltration surfaces, manholes, and inlets) o Minimizing directly connected impervious areas by diverting runoff onto pervious surfaces and/or into infiltration devices (e.g., disconnecting roof drains from storm drainage with or without rain water harvesting) o Storm sewer inlet restrictions and minor surface storage on streets, flat roofs, or parking lots, green roofs 4. Reduction of pollutant and flows in the conveyance systems. Once the flows enter the conveyance systems (sewers and/or drainage channels), controls become limited and more costly. Examples of BMPs include: o Swales, grassed channels and filters, raingardens o A swirl concentrator that removes larger particles from flow o CSO control by filters o Real-time control (RTC) of flows in combined sewers o Use of off-line and in-line retention basins that are a part of the sewer system (e.g., first flush control basins) 5. End of pipe flow and pollution controls. These are the most expensive controls that may include: o Wetlands (for treatment and storage of stormwater or treated wastewater) o Surface storage and treatment for stormwater o Underground storage and treatment of combined sewer overflows followed by conveyance for treatment. Matching Diffuse Pollution Abatement, Drainage and Resilient Urban Landscape Until recently, diffuse pollution abatement, urban landscape architecture and engineered drainage were not integrated. Under the current urban drainage paradigm, drainage was based on the principle of fast conveyance, urban landscape architecture was oriented towards maximizing imperviousness, diffuse pollution controls relied mostly on street sweeping, end of pipe stormwater controls and getting water from the urban areas as fast as possible. However, diverting all rainfall into drains and sewers, and preventing groundwater recharge, leads to lower groundwater tables and deprives urban streams of valuable base flow. Falling groundwater tables exacerbated by impervious urban surfaces are preventing rainwater from recharging aquifers and increasing the variability of flows. Depleted aquifers can undermine historic buildings that depend on wood pilings; when not submerged in groundwater, those pilings can rot away, as they have in Boston, Philadelphia, Venice, Mexico City and other cities. For all of these reasons, restoring natural functions to the hydrology of urban areas will have far-reaching benefits. Extreme precipitation events can render existing underground urban drainage with a capacity to handle a five year precipitation inconsequential, as exemplified by hurricane Katrina in New Orleans. More generally, in urban areas, the hydrologic connection with the landscape is fragmented or nonexistent and provides little buffering protection. Scientific predictions indicate that the frequency and force of extreme hydrologic events (hurricanes, typhoons) will increase with global warming. The consequences were thousands of lives lost, dislocation of survivors, and billions of dollars in damages (Van Heerden, Kemp and Mashriquiri, 2007). 19

20 New Ecocity Concepts An ecocity is a city or an autonomous part of a city that balances social, economic and environmental factors (triple bottom) to achieve sustainable development. An ecocity can be a cluster or contain several clusters of sustainable management. An ecocity is ecologically and hydrologically sustainable and resilient. It has become clear that the fourth paradigm of wastewater and stormwater drainage is not suitable and does not fit the ecocity concepts. The time has come to critically evaluate what has been developed during the last twenty five years in the field of urban drainage and diffuse pollution with the green city concepts and come up with a new approach to drainage that would mimic nature and the pre-development hydrology. Other trends can also be considered such as dramatically reduced emission from vehicles powered by hydrogen fuel cells, improved public transportation, energy production from wind, solar, biofuell and recycled city waste. The new drainage will make a switch from strictly engineered systems (sewers) to ecologic systems (rain gardens, surface wetlands, ponds restored and daylighted water bodies). The municipal stormwater and sewage management is expected to be decentralized into city clusters rather than regionalized. At some point the drainage and the buffers and flood plains will become a sequence of ecotones connected to the major receiving water body (Hill, 2007; Ahern, 2007; Novotny and Hill, 2006). Some concepts also consider organic farms surrounding the cities and significant reduction of nonpoint pollution from farms supplying food to the cities. Ecocities are now emerging on subdivision or urban levels in reality and on large city levels (up millions of people) in planning. China is looking for urban housing for up to 300 million people in the next 30 years because of intensification of agriculture (loss of jobs of indigenous population) and a large increase of GNP being derived by industries in the cities. Essentially, it is a planned attempt to manage migration from rural to urban areas that has been so devastating in several other fast developing countries, including Brazil, Mexico, India, etc. The City of New Wuhan or Dongtan, both on the Yangtze River, will be the first new ecocities. The intent of Chinese planners working with the Chinese Academy of Science, is to make the New Wuhan City, with its lakes and rivers, a water centric ecocity. The ecocity on a large scale is still a vision but the realities are fast emerging in Sweden Figure 13 Restored 2 nd order Lincoln Creek in Milwaukee, WI (Hammarby Sjöstad), USA, Canada, Germany, Australia, China, and Japan. In developed countries, the movement towards ecocities is based on the realization that the limits of the current paradigm have been reached, population will be increasing, technology (e.g., high level treatment is available), new architectural diffuse pollution controls are functioning and desirable by public, intensity and frequency of catastrophic storms will be increasing, and population desires these developments (Novotny and Brown, 2007). On the other side, in spite of a lot of interest and work being done in academia, the progress is still a piece meal approach mostly by individual 20

21 developers or some agencies trying to use technologies that have not yet been developed and scientifically tested. For example, the restoration and integrated management of the Lincoln Creek in Milwaukee (WI, USA) has been impressive (Figure 13) but partially failed because the restoration was not based on the total hydrologic balance, the creek was lacking sufficient base flow that was reduced by urbanization within the watershed. Drainage and Water Management It has become clear that the current paradigm of fast conveyance drainage end of pipe treatment is not suitable and does not fit the ecocity concepts. The time has come to critically evaluate what has been developed during the last twenty five years in the field of urban drainage and diffuse pollution with the green city concepts and come up with a new approach to drainage that would be mimicking nature and the pre-development hydrology. Other trends can also be considered such as reduced emission from vehicles and improved public transportation. The new drainage will make a switch from strictly engineered systems (sewers) to ecologic systems (rain gardens, surface wetlands, ponds restored and daylighted water bodies). The municipal sewage management is expected to be decentralized into city clusters rather than regionalized. At some point surface drainage containing BMPs must become a sequence of ecotones connected to the major receiving water body (Hill, 2007; Ahern, 2007; Novotny and Hill, 2006). Figure 14 shows a visionary drainage in Toronto (Ontario, Canada). The emerging drainage systems will be mostly on the surface. Such systems will Figure 14 New stormwater management for Toronto (Toronto Waterfront Regeneration Trust) o eliminate or dramatically reduce the needs for pollution combined and storm sewers, o mitigate pollution by urban runoff and reduce flooding, and o enhance aesthetic. How to mimic nature in the Cities of the Future? The natural drainage systems begin with ephemeral small vegetated channels and gullies. At some point several of these channels will form a first order perennial stream. A second order stream is formed when several first order stream join together. Springs and wetlands feed and provide perennial flows to natural streams. It is possible to do the same in the urban areas but then it would be called integrated 21