Estimating Crop Water Use via Remote Sensing Techniques vs. Conventional Methods in the South Platte River Basin,Colorado

We compared two methods of estimating crop water consumption to assess whether remote sensing techniques provide consumptive use (CU) estimates commensurate with conventional methods. Using available historical satellite and meteorological data, we applied Mapping EvapoTranspiration at high Resolution using Internalized Calibration (METRIC) to 317,455 ha in the South Platte basin, in northeastern Colorado, for the 2001 irrigation season. We then compared these derived CU estimates with values calculated by using the Colorado Water Conservation Board's South Platte Decision Support System StateCU model. Evaluating the data by irrigation ditch service area, we disaggregated the output to allow for comparison by service area size, crop type, irrigation method, water supply source, and water availability. We concluded that METRIC is a suitable alternative to StateCU in the South Platte basin and could help to identify areas with inhibited crop growth or deficit irrigation practices. In addition, METRIC could be used as a complement to StateCU to refine StateCU model parameters, allowing for more accurate estimates of crop water shortages and groundwater recharge associated with irrigation delivery and application.     

A tool for building community resilience? A case study of the Lewes Pound

In the last decade, “resilience” has gained increasing recognition as a theoretical framework for understanding and managing change in complex social–ecological systems. Resilience assessments are increasingly used to inform sustainability initiatives, strategies, and policies. The Lewes Pound represents a new complementary currency model in the UK, aiming to build community resilience. However, there have been no empirical studies to date assessing the socio-economic impacts of this model. This article addresses the need to understand how such currencies function by measuring whether the Lewes Pound is capable of building resilience. This is done by developing a novel framework for estimating economic, social, and environmental outcomes, which uses a mixed-methods approach. Findings suggest that complementary currencies can enhance social-ecological resilience through awareness-raising and changes in consumption. Although economic localisation – a key indicator – is lacking, there is evidence that the Lewes Pound has developed social interactions and changed consumption patterns of its users.     

Biodegradation of triclosan and formation of methyl-triclosan in activated sludge under aerobic conditions

Triclosan is an antimicrobial agent which is widely used in household and personal care products. Widespread use of this compound has led to the elevated concentrations of triclosan in wastewater, wastewater treatment plants (WWTPs) and receiving waters. Removal of triclosan and formation of triclosan-methyl was investigated in activated sludge from a standard activated sludge WWTP equipped with enhanced biological phosphorus removal. The removal was found to occur mainly under aerobic conditions while under anoxic (nitrate reducing) and anaerobic conditions rather low removal rates were determined. In a laboratory-scale activated sludge reactor 75% of the triclosan was removed under aerobic conditions within 150 h, while no removal was observed under anaerobic or anoxic conditions. One percent of the triclosan was converted to triclosan-methyl under aerobic conditions, less under anoxic (nitrate reducing) and none under anaerobic conditions.     

Characterization of a simple bacterial consortium for effective treatment of wastewaters with reactive dyes and Cr(VI)

A microbial consortia consisting of three bacteria isolated from tanning and textile wastewaters revealed high capacity to simultaneously bioaccumulate dye and Cr(VI). The identity of the bacteria were determined by 16S rRNA gene analysis to be closely related to Ochrobactrium sp., Salmonella enterica and Pseudomonas aeruginosa. Dependence of initial pH values and range of concentrations of the dye Reactive Black B (33.2-103.1 mg l(-1)) and Cr(VI) (19.9-127.6 mg l(-1)) were examined to find the effect of pH on the dye and Cr(VI) bioaccumulation. Optimal pH for growth of the consortia in media containing 35 mg l(-1) dye and 50 mg l(-1) Cr(VI) was determined to be around 8. The Cr(VI) bioaccumulation by the consortia was rapid in media containing molasses with or without reactive dye with a maximum Cr(VI) bioaccumulation yield ranging from 90% to 99% within a 2-4d period. A slightly lower yield for the dye bioaccumulation was measured with a maximum dye bioaccumulation of 80% at 59.3 mg l(-1) dye and 69.8 mg l(-1) Cr(VI). The highest specific Cr uptake value was obtained as 76.7 mg g(-1) at 117.1 mg l(-1) Cr(VI) and 50.8 mg l(-1) dye concentration. This ability to bioaccumulate dye and Cr(VI) was more efficient than the enriched sludge from which they were isolated.     

Automated Calibration of the METRIC‐Landsat Evapotranspiration Process

A remaining challenge to applying satellite‐based energy‐balance algorithms for operational estimation of evapotranspiration (ET) is the calibration of the energy‐balance model. Customized calibration for each image date is generally required to overcome biases associated with radiometric accuracy of the image, uncertainties in aerodynamic features of the landscape, background thermal conditions, and model assumptions. The CIMEC process (calibration using inverse modeling at extreme conditions) is an endpoint calibration procedure where near extreme conditions in the image are identified where the ET can be estimated and assigned. In the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC?) energy‐balance model, two endpoints represent the dry and wet ends of the ET spectrum. Generally, user‐intervention is required to select locations in the image to produce best accuracy. To bring the METRIC and similar processes into the domain of less experienced operators, a consistent, reproducible, and dependable statistics‐based procedure is introduced where relationships between vegetation amount and surface temperature are used to identify a subpopulation of locations (pixels) in an image that may best represent the calibration endpoints. This article describes the background and logic for the statistical approach, how the statistics were developed, area of interest requirements and assumptions, adjustment for dry conditions in desert climates, and implementation in a common image processing environment (ERDAS Imagine).