Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Muskox status,recent variation,and uncertain future

Ambio - Muskoxen (Ovibos moschatus) are an integral component of Arctic biodiversity. Given low genetic diversity, their ability to respond to future and rapid Arctic change is unknown, although...     

Outsourcing,trade, technology,and greenhouse gas emissions

Environmental Economics and Policy Studies - U.S. output has steadily outpaced the rise in greenhouse gas (GHG) emissions over the past several decades. The decoupling of these two trends...     

Determinants of CO2 emissions in upper middle-income group countries: an empirical investigation

Environmental Science and Pollution Research - This study investigates the kinked exponential growth, degree of association, and causation between economic growth, energy consumption, population,...     

Can we gain precision by sampling with probabilities proportional to size in surveying recent landscape changes in the Netherlands?

Seventy-two squares of 100 ha were selected by stratified random sampling with probabilities proportional to size (pps) to survey landscape changes in the period 1996–2003. The area of the plots times the urbanization pressure was used as a size measure. The central question of this study is whether the sampling with probabilities proportional to size leads to gain in precision compared to equal probability sampling. On average 1.03 isolated buildings per 100 ha have been built, while 0.90 buildings per 100 ha have been removed, leading to a net change of 0.13 building per 100 ha. The area with unspoiled natural relief has been reduced by 2.3 ha per 100 ha, and the length of linear relicts by 137 m per 100 ha. On average 74 m of linear green elements have been planted per 100 ha, while 106 m have been removed, leading to a net change of −31 m per 100 ha. For the state variables ‘unspoiled natural relief', ‘ linear relicts', ‘removed linear green elements', and ‘new – removed linear green elements' there is a gain in precision due to the pps-sampling. For the remaining state variables there is no gain or even a loss of precision (`new buildings', ‘removed buildings', ‘new – removed buildings', ‘new linear green elements'). Therefore, if many state variables must be monitored or when interest is not only in the change but also in the current totals, we recommend to keep things simple, and to select plots with equal probability.     

Spatial and Temporal Variations in Trace Metal Concentrations in the Cockle, Austrovenus Stutchburyi from Otago, New Zealand

This is the first comprehensive study of sources of variation in metal concentrations within the whole tissues of a shallow burrowing, filter-feeding intertidal clam, Austrovenus stutchburyi. Samples were collected from 12 sites in April, August, November and February in 1993–1994 in the vicinity of Otago Harbour and Peninsula, New Zealand. Total tissue trace metal concentrations (μg g⁻¹ dry weight) were measured in individual animals for the essential metals : Mn, Cu, Zn, Ni and the non-essential Cr using trace-metal clean acid-digestion and ICP-OAES techniques. Average metal concentrations were 3–60 μg g⁻¹ for Cu, 40–118 μg g⁻¹ for Zn, 2–12 μg g⁻¹ for Mn, 5–35 μg g⁻¹ for Ni and 1–44 μg g⁻¹ for Cr. These levels decreased with body weight and differed amongst sites except for Cr in February (mid-summer). Highest concentrations occurred at sites close to a city (Dunedin) and within the central harbour region although the Cu, Zn, Ni and Cr concentrations did not correlate with the environmental gradient or season. At one coastal site, samples of both the blue mussel Mytilus galloprovincialis and cockles gave similar trends in trace metal levels. These results suggest that the cockle could be a useful trace metal biomonitor within NZ estuaries.     

Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.     

Characterization of Benthic Communities and Physical Habitat in the Stanislaus, Tuolumne, and Merced Rivers, California

The primary goal of this study was to characterize physical habitat and benthic communities (macroinvertebrates) in the Stanislaus, Tuolumne and Merced Rivers in California’s San Joaquin Valley in 2003. These rivers have been listed as impaired water bodies (303 (d) list) by the State of California due to the presence of organophosphate (OP) insecticides chlorpyrifos and diazinon, Group A pesticides (i.e., organochlorine pesticides), mercury, or unknown toxicity. Based on 10 instream and riparian physical habitat metrics, total physical habitat scores in the Stanislaus River ranged from 124 to 188 (maximum possible total score is 200). The highest total habitat score was reported at the upstream site. Tuolumne River physical habitat scores ranged from 86 to 167. Various Tuolumne River physical habitat metrics, including total habitat score, increased from downstream to upstream in this river. Merced River physical habitat scores ranged from 121 to 170 with a significant increase in various physical habitat metrics, including total habitat score, reported from downstream to upstream. Channel flow (an instream metric) and bank stability (a riparian metric) were the most important physical habitat metrics influencing the various benthic metrics for all three rivers. Abundance measures of benthic macroinvertebrates (5,100 to 5,400 individuals) were similar among the three rivers in the San Joaquin watershed. Benthic communities in all three rivers were generally dominated by: (1) Baetidae species (mayflies) which are a component of EPT taxa generally considered sensitive to environmental degradation; (2) Chironomidae (midges) which can be either tolerant or sensitive to environmental stressors depending on the species; (3) Ephemerellidae (mayflies) which are considered sensitive to pollution stress; and (4) Naididae (aquatic worms) which are generally considered tolerant to environmental stressors. The presence of 117 taxa in the Stanislaus River, 114 taxa in the Tuolumne River and 96 taxa in the Merced River implies that the benthic communities in these streams are fairly diverse but without a clear definition of benthic community expectations it is unknown if these water bodies are actually impaired.     

Trace Element Concentrations and Bioindicator Responses in Tree Swallows from Northwestern Minnesota

Extremely high concentrations of cadmium (3.5 μg/g dry wgt.) and elevated concentrations of chromium (>10 μg/g dry wgt.) and mercury (1.6 μg/g dry wgt.) were reported in waterbird tissues at Agassiz National Wildlife Refuge in northwestern Minnesota in 1994. Tree swallows (Tachycineta bicolor) were studied during 1998–2001 at three drainages into the Refuge, two pools on the Refuge, and at a nearby reference location to document whether high levels of contaminants were still present, and if so to quantify the source and severity of the contamination. Trace elements were measured in tree swallow eggs, livers, and diet. Reproductive success and bioindicator responses were monitored. In 2000, water was drawn down on Agassiz Pool, one of the main pools on the Refuge. This presented an opportunity to evaluate the response of trace element concentrations in the diet and tissues of tree swallows after reflooding. High concentrations of trace elements were not detected in swallow tissues, nor were there differences among locations. Less than 20% of swallow samples had detectable concentrations of cadmium or chromium. Mercury concentrations were low and averaged <0.25 μg/g dry wgt. in swallow tissues. Trace elements, including mercury, did not increase in tree swallows following the 2000 drawdown at Agassiz Pool. Hatching success and survival of nestlings to 12 days-of-age for tree swallows on the Refuge were similar to the national average and consistent with background trace element concentrations. Bioindicator measurements were within the normal ranges as well.     

A Rapid Method for Assessing the Environmental Performance of Commercial Farms in the Pampas of Argentina

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.