Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis

Trend analysis of stream constituent concentrations requires adjustment for exogenous variables like discharge because concentrations often have variable relations with flow. To remove the influence of flow on stream water quality data, an accurate characterization of the relationship between the constituent and streamflow is needed. One popular method, locally weighted regression (LOESS), provides an effective means for flow-adjusting concentrations. The LOESS fit can be tailored to the data via the smoothing parameter (f), so that the user can avoid overfitting or oversmoothing the data. However, it is a common practice to use a single f value when flow-adjusting water quality data for trend analysis. This study provides a robust, automated method for determining the optimal f value (f_opt) for each dataset via an iterative K-fold cross-validation procedure that minimizes prediction error in LOESS. The method is developed by analyzing datasets of seven different constituents across 17 sites (119 datasets total) from a stream monitoring program in northwest Arkansas (USA). We recommend using 10 iterations of 10-fold cross-validation (10?×?10 CV) in order to select f_opt when flow-adjusting water quality data with LOESS. The use of a default f value did not produce different trend interpretations for the data used here; however, the proposed approach may be helpful in other water quality studies which employ similar statistical fitting methods. Additionally, we provide an implementation of the method in the R statistical computing environment.     

Erratum to: Estimating urban water demand under conditions of rapid growth: the case of Shanghai

Regional Environmental Change - Many of the world’s major cities are expected to face significant water shortages in coming decades, largely due to increased demand arising from economic and...     

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Protected areas and deforestation: new results from high‐resolution panel data

This paper investigates the effectiveness of protected areas in slowing tropical forest clearing in 64 countries in Asia/Pacific, Africa and Latin America during the period of 2001–2012 by comparing deforestation rates inside and within 10 km outside of the boundaries of protected areas. Annual time series of these deforestation rates were constructed from recently published high‐resolution data on forest clearing from Hansen et al. (2013). For 4,028 parks, panel estimation based on a variety of park characteristics was conducted to test if deforestation was lower in protected areas because of their protected status, or if other factors explained the difference. From a sample of 726 parks established since 2002, a test was also conducted to investigate the effect of park establishment on protection. Findings suggest park size, national park status and management by indigenous people all are significantly associated with effective protection across regions. For the Asia/Pacific region, the test offers compelling evidence that park establishment has a near‐immediate and powerful effect.     

Effects of Urbanization on Flow Duration and Stream Flashiness: A Case Study of Puget Sound Streams,Western Washington,USA

The overall influence of urbanization on how flows of different frequency might change over time, while important in hydrologic design, remains imprecisely known. In this study, we investigate the effects of urbanization on flow duration curves (FDCs) and flow variability through a case study of eight watersheds that underwent different amounts of growth, in the Puget Sound region in Western Washington State, United States. We computed annual FDCs from flow records spanning 1960‐2010 and, after accounting for the effects of precipitation, we conducted statistical trend analyses on flow metrics to quantify how key FDC percentiles changed with time in response to urbanization. In the urban watersheds, the entire FDC tended to increase in magnitude of flow, especially the 95th‐99th percentile of the daily mean flow series, which increased by an average of 43%. Stream flashiness in urban watersheds was found to increase by an average of 70%. The increases in FDC magnitude and flashiness in urbanizing watersheds are most likely a result of increasing watershed imperviousness and altered hydrologic routing. Rural watersheds were found to have decreasing FDC magnitude over the same time period, which is possibly due to anthropogenic extractions of groundwater, and increasing stream flashiness, which is likely a result of reductions in base flow and increasing precipitation intensity and variability.     

Analysis of macroinvertebrate assemblages in relation to environmental gradients among lotic habitats of California's Central Valley

We assessed relationships between environmental characteristicsand macroinvertebrate assemblages in lotic habitats of California's Central Valley with community metric and multivariate statistical approaches. Using canonical ordinationanalyses, we contrasted results when assemblage structure was assessed with macroinvertebrate metrics, as suggested for use inindices of biotic integrity, or with genera abundances. Our objectives were to identify metrics or taxa diagnostic of loticenvironmental stressors and compare the capacity of theseapproaches to detect stressors in order to suggest how they mightbe used to diagnose stressors. For macroinvertebrate metrics,redundancy analysis (RDA) extracted three axes correlated withchannel morphology and substrates. For genera abundances, canonical correspondence analysis (CCA) extracted two axescorrelated with soluble salts and with channel morphology andsubstrates but did not separate these gradients onto differentaxes. Cluster analyses identified five RDA and five CCA sitegroups, which exhibited differences for environmental variables,metrics, or genera abundances, and agreement between the analysesin partitioning of sites was greater than if sites were partitioned randomly. These approaches differ in their abilityto detect environmental stressors, because they measure differentaspects of assemblages and would be complementary in design ofnew metrics diagnostic of stressors.     

Development of a New Approach to Cumulative Effects Assessment: A Northern River Ecosystem Example

If sustainable development of Canadian waters is to be achieved, a realistic and manageable framework is required for assessing cumulative effects. The objective of this paper is to describe an approach for aquatic cumulative effects assessment that was developed under the Northern Rivers Ecosystem Initiative. The approach is based on a review of existing monitoring practices in Canada and the presence of existing thresholds for aquatic ecosystem health assessments. It suggests that a sustainable framework is possible for cumulative effects assessment of Canadian waters that would result in integration of national indicators of aquatic health, integration of national initiatives (e.g., water quality index, environmental effects monitoring), and provide an avenue where long-term monitoring programs could be integrated with baseline and follow-up monitoring conducted under the environmental assessment process.     

Application of encapsulation (pH-sensitive polymer and phosphate buffer macrocapsules): a novel approach to remediation of acidic ground water

Macrocapsules, composed of a pH-sensitive polymer and phosphate buffer, offer a novel remediation alternative for acidic ground waters. To test their potential effectiveness, laboratory experiments were carried out followed by a field trial within a coal pile runoff (CPR) acidic contaminant plume. Results of traditional limestone and macrocapsule treatments were compared in both laboratory and field experiments. Macrocapsules were more effective than limestone as a passive treatment for raising pH in well water from 2.5 to 6 in both laboratory and field experiments. The limestone treatments had limited impact on pH, only increasing pH as high as 3.3, and armoring by iron was evident in the field trial. Aluminum, iron and sulfate concentrations remained relatively constant throughout the experiments, but phosphate increased (0.15-32 mg/L), indicating macrocapsule release. This research confirmed that macrocapsules may be an effective alternative to limestone to treat highly acidic ground water.     

Biodynamic modelling and the prediction of accumulated trace metal concentrations in the polychaete Arenicola marina

The use of biodynamic models to understand metal uptake directly from sediments by deposit-feeding organisms still represents a special challenge. In this study, accumulated concentrations of Cd, Zn and Ag predicted by biodynamic modelling in the lugworm Arenicola marina have been compared to measured concentrations in field populations in several UK estuaries. The biodynamic model predicted accumulated field Cd concentrations remarkably accurately, and predicted bioaccumulated Ag concentrations were in the range of those measured in lugworms collected from the field. For Zn the model showed less but still good comparability, accurately predicting Zn bioaccumulation in A. marina at high sediment concentrations but underestimating accumulated Zn in the worms from sites with low and intermediate levels of Zn sediment contamination. Therefore, it appears that the physiological parameters experimentally derived for A. marina are applicable to the conditions encountered in these environments and that the assumptions made in the model are plausible.