PCDDs, PCDFs, PCBs and HCB in marine and estuarine sediments from Queensland, Australia.

Concentrations of 2,3,7,8-chlorine substituted PCDDs, PCDFs, selected PCB congeners and HCB were determined in sediment samples collected from sites along the east coast of Queensland in northern Australia. PCDDs were detectable in all sediment samples while PCDFs, PCBs and HCB were mainly found in sediment samples collected from sites in the Brisbane metropolitan area. The results provide evidence that an unidentified source for higher chlorinated PCDDs exists along the Queensland coast.     

Climate and Land Use Effects on Hydrologic Processes in a Primarily Rain‐Fed,Agricultural Watershed

Anticipating changes in hydrologic variables is essential for making socioeconomic water resource decisions. This study aims to assess the potential impact of land use and climate change on the hydrologic processes of a primarily rain‐fed, agriculturally based watershed in Missouri. A detailed evaluation was performed using the Soil and Water Assessment Tool for the near future (2020–2039) and mid‐century (2040–2059). Land use scenarios were mapped using the Conversion of Land Use and its Effects model. Ensemble results, based on 19 climate models, indicated a temperature increase of about 1.0°C in near future and 2.0°C in mid‐century. Combined climate and land use change scenarios showed distinct annual and seasonal hydrologic variations. Annual precipitation was projected to increase from 6% to 7%, which resulted in 14% more spring days with soil water content equal to or exceeding field capacity in mid‐century. However, summer precipitation was projected to decrease, a critical factor for crop growth. Higher temperatures led to increased potential evapotranspiration during the growing season. Combined with changes in precipitation patterns, this resulted in an increased need for irrigation by 38 mm representing a 10% increase in total irrigation water use. Analysis from multiple land use scenarios indicated converting agriculture to forest land can potentially mitigate the effects of climate change on streamflow, thus ensuring future water availability.     

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Herbicide Transport in Goodwater Creek ExperimentalWatershed: I. Long‐Term Research on Atrazine1

Lerch, R.N., E.J. Sadler, K.A. Sudduth, C. Baffaut, and N.R. Kitchen, 2010. Herbicide Transport in Goodwater Creek Experimental Watershed: I. Long‐Term Research on Atrazine. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00503.x Abstract: Atrazine continues to be the herbicide of greatest concern relative to contamination of surface waters in the United States (U.S.). The objectives of this study were to analyze trends in atrazine concentration and load in Goodwater Creek Experimental Watershed (GCEW) from 1992 to 2006, and to conduct a retrospective assessment of the potential aquatic ecosystem impacts caused by atrazine contamination. Located within the Central Claypan Region of northeastern Missouri, GCEW encompasses 72.5 km² of predominantly agricultural land uses, with an average of 21% of the watershed in corn and sorghum. Flow‐weighted runoff and weekly base‐flow grab samples were collected at the outlet to GCEW and analyzed for atrazine. Cumulative frequency diagrams and linear regression analyses generally showed no significant time trends for atrazine concentration or load. Relative annual loads varied from 0.56 to 14% of the applied atrazine, with a median of 5.9%. A cumulative vulnerability index, which takes into account the interactions between herbicide application, surface runoff events, and atrazine dissipation kinetics, explained 63% of the variation in annual atrazine loads. Based on criteria established by the U.S. Environmental Protection Agency, atrazine reached concentrations considered harmful to aquatic ecosystems in 10 of 15 years. Because of its vulnerability, atrazine registrants will be required to work with farmers in GCEW to implement practices that reduce atrazine transport.     

Ammonia volatilization from marsh-pond-marsh constructed wetlands treating swine wastewater

Ammonia (NH3) volatilization is an undesirable mechanism for the removal of nitrogen (N) from wastewater treatment wetlands. To minimize the potential for NH3 volatilization, it is important to determine how wetland design affects NH3 volatilization. The objective of this research was to determine how the presence of a pond section affects NH3 volatilization from constructed wetlands treating wastewater from a confined swine operation. Wastewater was added at different N loads to six constructed wetlands of the marsh-pond-marsh design that were located in Greensboro, North Carolina, USA. A large enclosure was used to measure NH3 volatilization from the marsh and pond sections of each wetland in July and August of 2001. Ammonia volatilized from marsh and pond sections at rates ranging from 5 to 102 mg NH3-N m(-2) h(-1). Pond sections exhibited a significantly greater increase in the rate of NH3 volatilization (p < 0.0001) than did either marsh section as N load increased. At N loads greater than 15 kg ha(-1) d(-1), NH3 volatilization accounted for 23 to 36% of the N load. Furthermore, NH3 volatilization was the dominant (54-79%) N removal mechanism at N loads greater than 15 kg ha(-1) d(-1). Without the pond sections, NH3 volatilization would have been a minor contributor (less than 12%) to the N balance of these wetlands. To minimize NH3 volatilization, continuous marsh systems should be preferred over marsh-pond-marsh systems for the treatment of wastewater from confined animal operations.     

Local food networks as catalysts for food policy change to improve health and build the economy

Local food networks (LFNs) are growing in popularity, in part as a response to broader criticisms of conventional food production. Municipal policy-makers have the opportunity to work with stakeholders to build LFNs to increase access to healthy foods in cities and ultimately improve population health and well-being. Building opportunities for healthy eating is particularly important in our study area. Flint, Michigan, is a post-industrial shrinking city suffering from the economic and health effects of deindustrialisation. Various stakeholders in Flint have responded to a significant issue with access to food by strengthening collaborations through a food policy council (FPC). Growth in the local food system has been supported by administrators and community advocates alike, through supporting community gardens, farmers' markets, and urban agriculture in a manner similar to nearby Detroit. Participant observation was conducted with stakeholders involved in the development of the LFN and the FPC in Flint. Stakeholders were exposed to existing research on the food system to help inform their policy direction. The group expressed several core concerns and prospects for future work, including a strong emphasis on consensus-based decision-making. Based on the synthesis of stakeholder opinions, policy recommendations are made to aid in continued planning of the LFN. Planning for food is an important first step in improving public health and strengthening local economic development in post-industrial cities. This research highlights the issue by making explicit the challenges and opportunities for policy advocacy in LFNs.     

Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor,Alachlor, Metolachlor,and Metribuzin1

Lerch, R.N., E.J. Sadler, C. Baffaut, N.R. Kitchen, and K.A. Sudduth, 2010. Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor, Alachlor, Metolachlor, and Metribuzin. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00504.x Abstract: Farmers in the Midwestern United States continue to be reliant on soil‐applied herbicides for weed control in crop production, and herbicide contamination of streams remains an environmental problem. The main objective of this study was to analyze trends in concentration and load of acetochlor, alachlor, metolachlor, and metribuzin in Goodwater Creek Experimental Watershed (GCEW) from 1992 to 2006. A secondary objective was to document the effects of best management practices (BMPs) implemented within GCEW on herbicide transport trends. Median relative herbicide loads, as a percent of applied, were 3.7% for metolachlor, 1.3% for metribuzin, 0.36% for acetochlor, and 0.18% for alachlor. The major decrease in alachlor use and increase in acetochlor use caused shifts in flow‐weighted concentrations that were observed over the entire concentration range. The smaller decrease in metolachlor use led to a consistent decreasing time trend only for the upper end of the concentration distribution. Metribuzin also showed moderate decreases in concentration with time since 1998. Annual loads were generally correlated to second quarter discharge. Despite extensive education efforts in the watershed, conservation BMPs within GCEW were mainly implemented to control erosion, and therefore had no discernable impact on reducing herbicide transport. Overall, changes in herbicide use and second quarter discharge had the greatest effect on trends in flow‐weighted concentration and annual load.