The low but uncertain measured benefits of US water quality policy

The Missing Piece of the Puzzle: How Different Water-related Public Concerns Contribute to Water Governance in China

Public participation is crucial to improving the performance of water governance systems, especially in a governance model dominated by a top-down hierarchical structure. Public concerns, as a vital form of public participation, have been acknowledged as an essential component in contributing to water governance. However, few studies explore the varying effects of diverse public concerns in leading to different water governance outcomes. This study addresses this gap by exploring the direct and indirect effects of water-related public concerns on water pollution control and governments' pollution mitigating actions, using citizens' water-related posts crawled from China's social media. Results show that public water-related concerns contribute to water governance both through its direct effects on reducing water pollution and indirect effects by promoting policy actions. Specifically, the concerns related to water pollution hazards, water pollution monitoring, prevention products, and water pollution control measures have more positive impacts on water pollution reduction compared to other types of concern. Meanwhile, public concerns demonstrate stronger effects in triggering economic-related and infrastructure-related water pollution mitigation actions. This study provides nuanced insights to understand the role of public participation in improving water governance, the findings of which are insightful to enhance accountability of water governance systems through a bottom-up approach.

Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States

Recent advancements in DNA techniques, metabarcoding, and bioinformatics could help expand the use of benthic diatoms in monitoring and assessment programs by providing relatively quick and increasingly cost-effective ways to quantify diatom diversity in environmental samples. However, such applications of DNA-based approaches are relatively new, and in the United States, unknowns regarding their applications at large scales exist because only a few small-scale studies have been done. Here, we present results from the first nationwide survey to use DNA metabarcoding (rbcL) of benthic diatoms, which were collected from 1788 streams and rivers across nine ecoregions spanning the conterminous USA. At the national scale, we found that diatom assemblage structure (1) was strongly associated with total phosphorus and total nitrogen concentrations, conductivity, and pH and (2) had clear patterns that corresponded with differences in these variables among the nine ecoregions. These four variables were strong predictors of diatom assemblage structure in ecoregion-specific analyses, but our results also showed that diatom-environment relationships, the importance of environmental variables, and the ranges of these variables within which assemblage changes occurred differed among ecoregions. To further examine how assemblage data could be used for biomonitoring purposes, we used indicator species analysis to identify ecoregion-specific taxa that decreased or increased along each environmental gradient, and we used their relative abundances of gene reads in samples as metrics. These metrics were strongly correlated with their corresponding variable of interest (e.g., low phosphorus diatoms with total phosphorus concentrations), and generalized additive models showed how their relationships compared among ecoregions. These large-scale national patterns and nine sets of ecoregional results demonstrated that diatom DNA metabarcoding is a robust approach that could be useful to monitoring and assessment programs spanning the variety of conditions that exist throughout the conterminous United States.

Tripartite evolutionary game and simulation analysis of agricultural non-point source pollution control

Agricultural non-point source pollution control (ANSPC) is a complex, long-term and dynamic environmental protection process. In order to motivate multiple subjects to participate in ANSPC, this paper constructs a tripartite evolutionary game model of local government, village collectives and farmers, which explores the strategic choices and influencing factors of different subjects through simulation analysis. The results indicate that: There are five stable strategy points in the ANSPC game system, which can be divided into four stages based on subject interactions. Village collectives should play an intermediary role in ANSPC and try to coordinate the behaviour of different subjects. The ideal and stable evolution state is "weak supervise, positive response, and active participate", but it cannot be realized at present. The strategy selection of subjects is determined by relative net income. Providing penalties requires considering the heterogeneity of subjects, but incentives are beneficial for achieving tripartite governance. This study provides new evidence for understanding the role of multi-agency participation in agricultural non-point source pollution control, and provides theoretical guidance for the government to formulate differentiated intervention mechanisms, which is an important reference for achieving sustainable development goals.

Strategies for integrating scientific evidence in water policy and law in the face of uncertainty

Understanding how human actions and environmental change affect water resources is crucial for addressing complex water management issues. The scientific tools that can produce the necessary information are ecological indicators, referring to measurable properties of the ecosystem state; environmental monitoring, the data collection process that is required to evaluate the progress towards reaching water management goals; mathematical models, linking human disturbances with the ecosystem state to predict environmental impacts; and scenarios, assisting in long-term management and policy implementation. Paradoxically, despite the rapid generation of data, evolving scientific understanding, and recent advancements in systems modeling, there is a striking imbalance between knowledge production and knowledge utilization in decision-making. In this paper, we examine the role and potential capacity of scientific tools in guiding governmental decision-making processes and identify the most critical disparities between water management, policy, law, and science. We demonstrate how the complex, uncertain, and gradually evolving nature of scientific knowledge might not always fit aptly to the legislative and policy processes and structures. We contend that the solution towards increased understanding of socio-ecological systems and reduced uncertainty lies in strengthening the connections between water management theory and practice, among the scientific tools themselves, among different stakeholders, and among the social, economic, and ecological facets of water quality management, law, and policy. We conclude by tying in three knowledge-exchange strategies, namely - adaptive management, Driver-Pressure-Status-Impact-Response (DPSIR) framework, and participatory modeling - that offer complementary perspectives to bridge the gap between science and policy.

Economic risks hidden in local water pollution and global markets: A retrospective analysis (1995-2010) and future perspectives on sustainable development goal 6

Pollution from untreated wastewater discharges depletes clean water supply for humans and the environment. It poses adverse economic impacts by determining agricultural yields, manufacturing productivity, and ecosystem functionality. Current studies mainly focus on quantity-related water scarcity assessment. It is unknown how low water quality amplifies local water stress and induces cascading economic risks globally. In this study, we estimated both quality and quantity-related water scarcity index (WSI), local economic water scarcity risk (WSR), and cascading virtual WSR evident in global trade markets across 40 major economies from 1995 to 2010. We find developing countries, e.g., India and China, witnessed fast growth in both quantity and quality-related WSI. Major developed economies, e.g., the US and Germany, experienced a modest increase in water stress but alleviated quality-related risks. Local economic risk (WSR) grew from $116B to $380B, with quality-related risks rising from 20 % to 30 %. Virtual economic WSR in global supply chains increased from $39B to $160B, with quality-related risks increasing from 19 % to 27 %. China became the top exporter of economic WSR, ranked above the US, France, and Japan, and the second-largest position as an importer, trailing only the US. We finally conducted scenario modeling by 2030, assuming different progresses on SDG 6 targets. The findings suggest that only the most ambitious progress in both water quality enhancement and efficiency improvement helps to alleviate ∼20 % economic WSR globally. Our findings underscore the necessity for strategies that integrate management of untreated wastewater flows, improved water use efficiency, and diversification of supply chain networks to enhance global economic resilience to water challenges in the future.

Water quality trends of streams in Puerto Rico: Evaluating 50 years of the Clean Water Act

Water quality regulations entail a substantial commitment of resources from governments and private entities. It is important to continually evaluate the effectiveness of these regulations to ensure they are having the intended impact. In this paper, we evaluated nutrient data as indicators of primary productivity and dissolved oxygen (DO) concentrations and pH as response variables to assess historical water quality trends from 55 stations of Puerto Rico. The stations were divided into impaired versus non-impaired categories based on their historical total phosphorus (TP) mean concentration. Mean TP and total nitrogen (TN) concentrations were significantly higher in the impaired stations relative to the non-impaired stations. In contrast, DO mean concentrations and mean pH values were significantly lower in the impaired stations. A generalized additive mixed model was used to demonstrate temporal trends. A significant decrease in TP and TN concentrations was observed with time at the impaired stations. This was accompanied by significant increases in DO concentrations and pH. The non-impaired stations showed a marginal (statistically nonsignificant) decreasing trend with time. The large reductions in nutrient concentrations observed at the impaired stations seem to be related to the closure of several primary wastewater treatment plants (WWTPs) across the island. The conversion of abandoned crop agricultural lands into secondary forest in recent decades has resulted in small but significant decreases in TN (not TP) in receiving streams. We conclude that the Clean Water Act has promoted improvements in water quality in Puerto Rico by advancing upgrades in sanitary infrastructure and the regulation of point sources of pollution.

Novel pollution prevention process for regulating industrial wastewater for better protection of the environment and public health

Regulating the concentrations of pollutants in industrial wastewater through wastewater treatment as practiced worldwide without regulating their pollution loads and wastewater discharge rate alongside, is not enough for protection of the environment and public health. This work investigated why some companies in the Niger Delta do not treat their wastewater; with the aim of providing a solution. The aforesaid prompted this work to invent the "Novel Pollution Prevention Process for Regulating Industrial Wastewater" introducing additional controls namely pollution load and wastewater discharge rate controls for better protection of the environment and public health. Questionnaire survey, wastewater analysis, discharge rate measurement, mathematical modeling and design were the methods adopted. Results revealed that pollution load and wastewater discharge rate should be regulated alongside concentrations of pollutants. Results showed that cost is the major factor responsible for the inability of some companies to treat their wastewater in the Niger Delta. Results revealed that pollution load is a qualitative measure of environmental damage caused by a pollutant and that the larger the pollution load, the larger the environmental damage and vice versa. Results showed that industry can apply the novel pollution prevention process to determine the environmentally-friendly wastewater discharge rate, environmentally-friendly pollution load of pollutants and the corresponding production rate of finished goods. Results revealed that when the concentration of a pollutant in industrial wastewater is not compliant and discharge rate is excessive, pollution load control can protect the environment and public health while regulatory agencies take appropriate measures to make the company comply with the allowable concentration limits of the pollutant. The "novel pollution prevention process for regulating industrial wastewater" has global applicability. It can be applied in every country.

Effect of national COVID-19 control measures on water quality in China using an improved dual difference-in-differences method

The impact of COVID-19 on the natural environment, particularly the aquatic environment, is a major concern. However, there is a lack of national-level research on the impact of COVID-19 on the aquatic environment. This study analysed the impacts of COVID-19 on water quality using an improved dual spatial-temporal Difference-in-Differences Method (DDiD) models in cities with and without formal lockdown policies all over the China. The study found that the effectiveness of national COVID-19 control measures varied spatially for different types of pollutants. The lockdown measure resulted in a 0.052-point decline in TN concentration and a 0.056-point decline in CODMn concentration, while the non-formal lockdown measures led to a 0.2-point increase in TN concentration and a 0.016-point decline in CODMn. Spatial-temporal analysis revealed that COVID-19 and control measures immediately reduced TN concentration. The decrease effect of non-formal lockdown measures was lower than that of the lockdown measure and caused an opposite overall effect of TN concentration change. The impact of COVID-19 and control measures on CODMn concentration had a time lag effect, as it maintained or slightly increased local CODMn concentration once the lockdown measure was implemented, and then decreased after 4 weeks. Heterogeneity analysis showed that the reduction effect on TN was more significant in cities that rely more on industrial activities, while the increase effect on CODMn was more significant in cities that rely more on general and domestic services industries, revealing the diversity of water pollution sources. Overall, the impact of the COVID-19 pandemic on water quality is not as significant as that on the atmospheric environment due to the diversity of pollution sources. The study partially proves that China has achieved excellent point source control for water pollution, but there is little potential reduction of water pollution at point sources, especially industrial sources. The best way to improve the aquatic environment is still to enhance its capacity by increasing water flow and storage ability and reducing the amount of discharge from every pollution source by improving production levels and pollution treatment ratios, especially for nonpoint sources.

HUM: A review of hydrochemical analysis using ultraviolet-visible absorption spectroscopy and machine learning

There is a need to develop improved methods for water quality analysis. Traditionally, water quality analysis is performed in a laboratory on discrete samples or in the field with simple sensors, but these methods have inherent limitations. Ultraviolet-visible absorption spectroscopy (UVAS) is a commonly used laboratory technique for water quality analysis and is being applied more broadly in combination with machine learning (ML) to allow for the detection of multiple analytes without sample pretreatments. This methodology (referred to here as Hydrochemical analysis using Ultraviolet-visible absorption spectroscopy and Machine learning; 'HUM') can be applied in the laboratory or in situ while requiring less time, labor, and materials compared to traditional laboratory analysis. HUM has been used for the quantification of a variety of chemicals in a variety of settings, but information is lacking related to instrumental setup, sample requirements, and data analysis procedures. For instance, there is a need to investigate the influence of spectral parameters (e.g., sensitivity, signal-to-noise ratio, and spectral resolution) on measurement error. There is also a lack of research aimed at developing ML algorithms specifically for HUM. Finally, there are emerging concepts such as sensor fusion and model-sensor fusion which have been applied to similar fields but are not common in studies involving HUM. This review suggests the need for further studies to better understand the factors that influence HUM measurement accuracy along with the need for hardware and software developments so that the methodology can ultimately become more robust and standardized. This, in turn, could increase its adoption in both academic and non-academic settings. Once the HUM methodology has matured, it could help to reduce the environmental impacts of society by improving our understanding and management of environmental systems through high-frequency data collection and automated control of water quality in environmentally relevant systems.

Valuing water quality in the United States using a national dataset on property values

High-quality water resources provide a wide range of benefits, but the value of water quality is often not fully represented in environmental policy decisions, due in large part to an absence of water quality valuation estimates at large, policy relevant scales. Using data on property values with nationwide coverage across the contiguous United States, we estimate the benefits of lake water quality as measured through capitalization in housing markets. We find compelling evidence that homeowners place a premium on improved water quality. This premium is largest for lakefront property and decays with distance from the waterbody. In aggregate, we estimate that 10% improvement of water quality for the contiguous United States has a value of $6 to 9 billion to property owners. This study provides credible evidence for policymakers to incorporate lake water quality value estimates in environmental decision-making.

Past and recent farming degrades aquatic insect genetic diversity

Recent declines in once-common species are triggering concern that an environmental crisis point has been reached. Yet, the lack of long abundance time series data for most species can make it difficult to attribute these changes to anthropogenic causes, and to separate them from normal cycles. Genetic diversity, on the other hand, is sensitive to past and recent environmental changes, and reflects a measure of a populations' potential to adapt to future stressors. Here, we consider whether patterns of genetic diversity among aquatic insects can be linked to historical and recent patterns of land use change. We collated mitochondrial cytochrome c oxidase subunit I (COI) variation for >700 aquatic insect species across the United States, where patterns of agricultural expansion and intensification have been documented since the 1800s. We found that genetic diversity was lowest in regions where cropland was historically (pre-1950) most extensive, suggesting a legacy of past environmental harm. Genetic diversity further declined where cropland has since expanded, even after accounting for climate and sampling effects. Notably though, genetic diversity also appeared to rebound where cropland has diminished. Our study suggests that genetic diversity at the community level can be a powerful tool to infer potential population declines and rebounds over longer time spans than is typically possible with ecological data. For the aquatic insects that we considered, patterns of land use many decades ago appear to have left long-lasting damage to genetic diversity that could threaten evolutionary responses to rapid global change.

Linking Water Quality to Drinking Water Treatment Costs Using Time Series Analysis: Examining the Effect of a Treatment Plant Upgrade in Ohio

We estimate a cost function for a water treatment plant in Ohio to assess the avoided-treatment costs resulting from improved source water quality. Regulations and source water concerns motivated the treatment plant to upgrade its treatment process by adding a granular activated carbon building in 2012. The cost function uses daily observations from 2013 to 2016; this allows us to compare the results to a cost function estimated for 2007-2011 for the same plant. Both models focus on understanding the relationship between treatment costs per 1,000 gallons (per 3.79 m3) of produced drinking water and predictor variables such as turbidity, pH, total organic carbon, deviations from target pool elevation, final production, and seasonal variables. Different from the 2007-2011 model, the 2013-2016 model includes a harmful algal bloom toxin variable. We find that the new treatment process leads to a different cost model than the one that covers 2007-2011. Both total organic carbon and algal toxin are important drivers for the 2013-2016 treatment costs. This reflects a significant increase in cyanobacteria cell densities capable of producing toxins in the source water between time periods. The 2013-2016 model also reveals that positive and negative shocks to treatment costs affect volatility, the changes in the variance of costs through time, differently. Positive shocks, or increased costs, lead to higher volatility compared to negative shocks, or decreased costs, of similar magnitude. After quantifying the changes in treatment costs due to changes in source water quality, we discuss how the study results inform policy-relevant decisions.

Water quality monitoring with purpose: Using a novel framework and leveraging long-term data

Water quality monitoring programs are developed to meet goals including attaining regulatory compliance, evaluating long-term environmental changes, or quantifying the impact of an emergency event. Methods for developing these programs often fail to address multiple aspects of development (hazard identification, parameter selection, monitoring locations/frequency) simultaneously. We develop a framework for monitoring program development that is both versatile and systematic, the Hazard Based Water Quality Monitoring Planning framework, and apply it to the Quabbin watershed in Massachusetts, USA. We use a novel application of dataset deconstruction of long-term water quality datasets and the Seasonal Kendall test for trends to evaluate the effects of sampling frequency on long-term trend detection at several watershed sites. Results showed that when sampling frequency is decreased, ability to detect statistically significant trends often decreases. Absolute error in trend slopes between biweekly (twice monthly) and reduced sampling frequencies was relatively small for specific conductance and turbidity but was high for total coliform, likely due to interannual variation in rainfall and temperature We found that no one sampling reduction method resulted in a consistently lower absolute error compared to the "truth" (biweekly sampling), highlighting the importance of evaluating conditions that may affect water quality at sites in different parts of a watershed. We demonstrate the framework's usefulness, particularly for parameter and sampling frequency selection, using methods that can be readily applied to other watershed systems.

Exploring Trade-Offs Between Profit, Yield, and the Environmental Footprint of Potential Nitrogen Fertilizer Regulations in the US Midwest

Multiple strategies are available that could reduce nitrogen (N) fertilizer use in agricultural systems, ranging from voluntary adoption of new N management practices by farmers to government regulations. However, these strategies have different economic and political costs, and their relative effectiveness in decreasing N leaching has not been evaluated at scale, particularly concerning potential trade-offs in crop yield and profitability. To inform policy efforts in the US Midwest, we quantified the effects of four policy scenarios designed to reduce fertilizer N inputs without sacrificing maize yields below 95%. A simulated dataset for economically optimum N rates and corresponding leaching losses was developed using a process-based crop model across 4,030 fields over 30 years. Policy scenarios were (1) higher N prices, (2) N leaching fee, (3) N balance fee, and (4) voluntary reduction of N use by farmers, each implemented under a range of sub-levels (low to high severity). Aggregated results show that all policies decreased N rates and N leaching, but this was associated with an exponential increase in economic costs. Achieving an N leaching reduction target of 20% has an estimated pollution control cost of 30-37 US$/ha, representing 147 million US$/year when scaled up to the state level, which is in the range of current government payments for existing conservation programs. Notably, such control of N losses would reduce the environmental impact of agriculture on water quality (externalities) by an estimated 524 million US$/year, representing an increase in society welfare of 377 million US$/year. Among the four policies, directly charging a fee on N leaching helped mitigate economic losses while improving the point source reduction effect (i.e., targeting fields that were leaching hotspots) and better internalization effect (i.e., targeting fields with higher environmental impact costs). This study provides actionable data to inform the development of cost-effective N fertilizer regulations by integrating changes in crop productivity and N losses in economic terms at the field level.

Socio-psychological factors influencing intent to adopt conservation practices in the Minnesota River Basin

In the upper Midwestern United States, one of the central goals of agri-environmental policy is to reduce environmental and water quality degradation resulting from agriculture without sacrificing production. The primary tool available to policymakers is offering farmers incentives to voluntarily adopt more conservation practices, often known as Best Management Practices (BMPs). Using the Theory of Planned Behavior (TPB) and Diffusion of Innovation (DoI) frameworks, we surveyed 2000 agricultural landowners in the Minnesota River Basin to explore the socio-psychological drivers of the adoption decisions for specific BMPs such as wetlands, cover crops, and nutrient management. We found that attitude (both favorable and unfavorable), awareness of environmental problems, and appreciation of ecosystem services significantly affected landowners' adoption intentions for the three BMPs. We applied landowner segmentation analysis and compared both the socio-psychological and socio-demographic features among different landowner segments (i.e. environmentally-conscious landowners, engaging-absentee landowners, and adoption-averse landowners). Our study can inform the development of targeted conservation policies for various landowner types to motivate BMPs adoption.

Drinking water, fracking, and infant health

This study assesses the health risks associated with drinking water contamination using variation in the timing and location of shale gas development (SGD). Our novel dataset, linking health and drinking water outcomes to shale gas activity through water sources, enables us to provide new estimates of the causal effects of water pollution on health and to isolate drinking water as a specific mechanism of exposure for SGD. We find consistent and robust evidence that drilling shale gas wells negatively impacts both drinking water quality and infant health. These results indicate large social costs of water pollution and provide impetus for re-visiting the regulation of public drinking water.

Transferring and extrapolating estimates of cost-effectiveness for water quality outcomes: Challenges and lessons from the Great Barrier Reef

In recent decades the declining health of the Great Barrier Reef has led to a number of government policies being implemented to reduce pollutant loads from the adjacent agricultural-based catchments. There is increasing use of cost-effectiveness measures to help prioritise between different programs and actions to reduce pollutants, given limited resources and the scale of the issues. However there are a small number of primary studies available, and the consistency of cost-effectiveness measures and their application is limited, particularly given the various uncertainties that underlie the measures. Unlike Europe and the United States of America water policy or benefit transfer approaches, there are no procedural guidance studies that must be followed in the context of the Great Barrier Reef catchments. In this study we review the use of cost effectiveness estimates for pollutant reduction into the Great Barrier Reef in the context of a benefit transfer framework, where estimates of costs from a particular case study are transferred to various scenarios within different catchments. The conclusions suggest a framework be developed for the Great Barrier Reef, which is consistent, transparent, and rigorous.

Quantifying the social benefits and costs of reducing phosphorus pollution under climate change

Excess phosphorus loading to waterbodies has led to increasing frequency and severity of harmful algal blooms, negatively impacting economic activity and human health. While interventions to improve water quality can create large societal benefits, these investments are costly and the value of benefits is often unknown. Understanding the social and economic impacts of reduced phosphorus loading is critical for developing effective land use policies and for generating public and political support for these initiatives. Here, we quantify the social benefits and costs of improving water quality in Lake Champlain under a range of phosphorus reduction and climate change scenarios between 2016 and 2050. We use statistical models to link water quality outputs from an established integrated assessment model with three categories of benefits: tourism expenditures, property sales, and avoided human health impacts. We estimate the costs of reducing phosphorus loading using data reported by the State of Vermont. We find that under the most aggressive phosphorus reduction scenario, the total benefits of improved water quality are $55 to $60 million between 2016 and 2050. Over this 35 year time horizon, the combined benefits do not outweigh the costs under any scenario. If the time horizon is extended to 2100 or beyond, however, the benefits may exceed the costs if the applied discount rate is less than 3%. Importantly, we almost certainly underestimate the value of clean water, due to the omission of other types of benefits. Despite this uncertainty, our study provides a tractable framework for disentangling the complex relationships between water quality and human well-being, and illuminates the value of reductions in phosphorus loading to society.

Values for protecting the Great Barrier Reef: A review and synthesis of studies over the past 35 years

Assessing the economic value of improved protection of the Great Barrier Reef (GBR) is important to demonstrate the consequences of loss and to evaluate the public benefits of programs to reduce pressures and address degradation. However, those values are not easy to measure, in part because of the diversity and complexity of the GBR, and because there are very different types of benefits involved. Since 1985, there have been over 40 major studies that have assessed values for these components at the whole GBR level, and many more for components at smaller scales. This study synthesises estimates from the major valuation studies in the GBR since 1985, generating estimates of average values across different benefit categories. We observe mixed results. While values are often reasonably consistent within sub-categories, there is mixed evidence about temporal trends and the small number of available studies makes it difficult to draw definitive outcomes.

Protecting local water quality has global benefits

Surface water is among Earth's most important resources. Yet, benefit-cost studies often report that the costs of water quality protection exceed its benefits. One possible reason for this seeming paradox is that often only a narrow range of local water quality benefits are considered. In particular, the climate damages from water pollution have rarely been quantified. Recent advances in global water science allow the computation of the global methane emission from lakes caused by human nutrient enrichment (eutrophication). Here, we estimate the present value of the global social cost of eutrophication-driven methane emissions from lakes between 2015 and 2050 to be $7.5-$81 trillion (2015 $US), and in a case-study for one well-studied lake (Lake Erie) we find the global value of avoiding eutrophication exceeds local values of either beach use or sport fishing by 10-fold.

Water quality sampling methods may bias evaluations of watershed management practices

Accurate measurement of the discharge of total suspended solids (TSS) from watersheds is complicated by the extreme temporal variability of suspended solid concentrations during periods of high stream flow. Consequently, TSS loads estimated from data collected at different temporal frequencies may differ in accuracy and precision. Moreover, there remains a need for optimal sampling methods which yield the highest possible accuracy for the least effort. We investigated the effect of sampling frequency on estimations of TSS loads and retention within a restored stream in Maryland, USA. We found that coarser temporal sampling methods can lead to erroneous conclusions of restoration efficacy with poor accuracy and precision in estimates of sediment retention. Additionally, we synthesized 28 years of continuous turbidity-based TSS data from Europe and North America to assess the effect of sampling frequency. Our synthesis suggests that flow-paced composite sampling may be the most accurate and precise sampling method. This method is also economical, requiring analysis of only one sample per week. Thus, the flow-paced method may be a potential solution to economize and standardize water quality monitoring.

Phosphorus Inventory for the Conterminous United States (2002-2012)

Published reports suggest efforts designed to prevent the occurrence of harmful algal blooms and hypoxia by reducing non-point and point source phosphorus (P) pollution are not delivering water quality improvements in many areas. Part of the uncertainty in evaluating watershed responses to management practices is the lack of standardized estimates of phosphorus inputs and outputs. To assess P trends across the conterminous United States, we compiled an inventory using publicly available datasets of agricultural P fluxes, atmospheric P deposition, human P demand and waste, and point source discharges for 2002, 2007, and 2012 at the scale of the 8-digit Hydrologic Unit Code subbasin (~1,800 km²). Estimates of agricultural legacy P surplus accumulated from 1945 to 2001 were also developed. Fertilizer and manure inputs were found to exceed crop removal rates by up to 50% in many agricultural regions. This excess in inputs has led to the continued accumulation of legacy P in agricultural lands. Atmospheric P deposition increased throughout the Rockies, potentially contributing to reported increases in surface water P concentrations in undisturbed watersheds. In some urban areas, P fluxes associated with human waste and non-farm fertilizer use has declined despite population growth, likely due, in part, to various sales bans on P-containing detergents and fertilizers. Although regions and individual subbasins have different contemporary and legacy P sources, a standardized method of accounting for large and small fluxes and ready to use inventory numbers provide essential infromation to coordinate targeted interventions to reduce P concentrations in the nation's waters.

The effects of heterogeneous environmental regulations on water pollution control: Quasi-natural experimental evidence from China

The policy effect of environmental regulations on water pollution has been widely discussed, but few studies have empirically tested the relative effectiveness of heterogeneous environmental regulations-command-and-control environmental regulations and market-based environmental regulations-on water pollution control. Using the difference-in-difference method, this paper takes advantage of two Chinese policies-the National Key Ecological Functional Areas Policy (NKEFAP), which can be regarded as a command-and-control environmental regulation, and the Transfer Payment of Ecological Functional Areas Policy (TPEFAP), which can be regarded as a market-based environmental regulation-as quasi-natural experiments to examine the relative effectiveness of different environmental regulations on water pollution control. The results show that both the NKEFAP and TPEFAP can reduce water pollution, but the reduction effect is higher for the TPEFAP than for the NKEFAP. For underlying mechanisms, the NKEFAP and TPEFAP reduce water pollution mainly by controlling industrial waste discharge, rather than by controlling agricultural and domestic pollution. Heterogeneity analysis reveals that counties with higher initial pollution levels and higher economic levels have a greater water pollution reduction effect. Our findings contribute to the understanding of the effect of heterogeneous environmental regulations on pollution control and are conducive to future policymaking.

Contiguous U.S. surface water availability and short-term trends of wastewater effluent flows in San Antonio, TX

Surface water is a vital and sometimes stressed resource in the U.S. The quantity of this resource is threatened by population shifts and growth concurrently with climate change intensification. Additionally, growing population centers can impact water quality by discharging treated wastewater effluent, which is typically of lower quality than its receiving surface waters. Depending on baseflow and environmental factors, this could decrease water quality. From a previous model prepared in our lab, this study can improve the understanding of water resource quality and quantity, surface water availability for the contiguous U.S. was estimated for each USGS Hydrologic Unit Code (HUC) during 2015. The Mississippi River generally served as a dividing line for surface water availability, with five of the six regions with very low water availability (<24,000 LD^-1Km^-2) residing in the west. These same areas also experience more drought as well as more severe droughts than regions in the east. In regions with lower surface water flows, their water quality is more susceptible to the influence of wastewater effluent discharges, especially near large and growing population centers like San Antonio, Texas. A prediction model was established for this city, which found that from 2009 to 2017 wastewater effluent increased by 1.8%. As cities grow, especially in the Southwest and Western U.S. together with intensified climate change, surface water quantity and quality become more crucial to sustainability. This study shows where surface water availability is already an issue and provides a model to estimate, as well as project, wastewater effluent flows into surface water bodies.

Trends in nutrient-related pollution as a source of potential water quality damages: A case study of Texas, USA

We examine long-run trends in surface water quality in Texas, USA, with a focus on nutrient pollution and its potential economic impacts. Using >2 million observations of total nitrogen, total phosphorous, dissolved oxygen, and chlorophyll a concentrations from water quality monitors in the state's 23 river sub-basins, we find that nutrient pollution may be a growing problem that is essentially statewide in scope. In addition, because economic impacts of nutrient pollution depend not just on observed water quality, but also on the typical uses of surface water resources that people value, we quantify the share of the state's surface water resources that does not meet common definitions of quality suitable for boating, fishing, swimming, and drinking, as well as the share that does not meet state regulatory standards for their designated uses. This analysis indicates that water quality improvements relative to human uses have stagnated over the last three decades and that nutrient pollution represents a much greater relative threat to attainment of designated uses than it did in the 1970s. We conclude that nutrient pollution is likely taking a toll on the economic value of Texas' water resources.

Did changes in western federal land management policies improve salmonid habitat in streams on public lands within the Interior Columbia River Basin?

Historic management actions authorized or allowed by federal land management agencies have had a profound negative effect on salmon, trout, and char populations and their habitats. To rectify past failings, in the 1990s, federal agencies in the Interior Columbia River Basin modified how they conducted land management activities to foster the conservation of aquatic species. The primary policy changes were to provide additional protection and restoration of lands near streams, lakes, and wetlands. What remains uncertain was whether these changes have altered the trajectory of stream habitat conditions. To address this question, we evaluate the status and trends of ten stream habitat attributes; wood frequency, wood volume, residual pool depth, percent pool, pool frequency, pool tail fines (< 6 mm), median particle size, percent undercut banks, bank angle, and streambank stability in managed and reference catchments following changes in management policies. Our review of these data support the hypothesis that changes made in management standards and guidelines in the 1990s are related to improved stream conditions. Determining the precise magnitude of changes in stream conditions that resulted from the modification of land management policies is difficult due to the shifting environmental baseline. By understanding and accounting for how changes in stream conditions reflect improved land management policies and broader environmental trends, federal agencies will be better situated to make project level decisions that benefit aquatic resources.

Regenerating Agricultural Landscapes with Perennial Groundcover for Intensive Crop Production

The Midwestern U.S. landscape is one of the most highly altered and intensively managed ecosystems in the country. The predominant crops grown are maize (Zea mays L.) and soybean [Glycine max (L.) Merr]. They are typically grown as monocrops in a simple yearly rotation or with multiple years of maize (2 to 3) followed by a single year of soybean. This system is highly productive because the crops and management systems have been well adapted to the regional growing conditions through substantial public and private investment. Furthermore, markets and supporting infrastructure are highly developed for both crops. As maize and soybean production have intensified, a number of concerns have arisen due to the unintended environmental impacts on the ecosystem. Many areas across the Midwest are experiencing negative impacts on water quality, soil degradation, and increased flood risk due to changes in regional hydrology. The water quality impacts extend even further downstream. We propose the development of an innovative system for growing maize and soybean with perennial groundcover to recover ecosystem services historically provided naturally by predominantly perennial native plant communities. Reincorporating perennial plants into annual cropping systems has the potential of restoring ecosystem services without negatively impacting grain crop production and offers the prospect of increasing grain crop productivity through improving the biological functioning of the system.