Characterizing Uncertainty in Daily Streamflow Estimates at Ungauged Locations for the Massachusetts Sustainable Yield Estimator

Hydrologic characterization at ungauged locations is one of the quintessential challenges of hydrology. Beyond simulation of historical streamflows, it is similarly important to characterize the level of uncertainty in hydrologic estimates. In tandem with updates to Massachusetts Sustainable Yield Estimator, this work explores the application of global uncertainty estimates to daily streamflow simulations. Expanding on a method developed for deterministic modeling, this approach produces confidence intervals on daily streamflow developed through nonlinear spatial interpolation of daily streamflow using flow duration curves; the 95% confidence is examined. Archived cross‐validations of daily streamflows from 66 watersheds in and around Massachusetts are used to evaluate an approach to uncertainty characterization. Neighboring sites are treated as ungauged, producing relative errors that can be resampled and applied to target sites. The method, with some modification, is found to provide appropriately narrow confidence intervals that contain 95% of the observed streamflows in cross‐validation. Further characterizing uncertainty, multiday means of daily streamflow are evaluated. Working through cross‐validation in Massachusetts, two‐ to three‐month averages of daily streamflow show the best performance. These two approaches to uncertainty characterization inform how streamflow simulation produced for prediction in ungauged basins can be used for water resources management.     

Determination of the compositional change (1999–2006) in the pine forests of British Columbia due to mountain pine beetle infestation

The current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia and Alberta is the largest recorded forest pest infestation in Canadian history. We integrate a spatial hierarchy of mountain pine beetle and forest health monitoring data, collected between 1999 and 2006, with provincial forest inventory data, and generate three information products representing 2006 forest conditions in British Columbia: cumulative percentage of pine infested by mountain pine beetle, percentage of pine uninfested, and the change in the percentage of pine on the landscape. All input data were formatted to a standardized spatial representation (1 ha minimum mapping unit), with preference given to the most detailed monitoring data available at a given location for characterizing mountain pine beetle infestation conditions. The presence or absence of mountain pine beetle attack was validated using field data (n?=?2054). The true positive rate for locations of red attack damage over all years was 92%. Classification of attack severity was validated using the Kruskal gamma statistic (γ?=?0.49). Error between the survey data and field data was explored using spatial autoregressive (SAR) models, which indicated that percentage pine and year of infestation were significant predictors of survey error at α?=?0.05. Through the integration of forest inventory and infestation survey data, the total area of pine infested is estimated to be between 2.89 and 4.14 million hectares. The generated outputs add value to existing monitoring data and provide information to support management and modeling applications.     

Mud,muddle and models in the knowledge value-chain to action on tropical peatland conservation

Tropical peatlands are known not only for their high, area-based, carbon emissions in response to land-use change but also as hot spots of debate about associated data uncertainties. Perspectives are still evolving on factors underlying the variability and uncertainty. Debate includes the ways of reducing emissions through rewetting, reforestation and agroforestry. A knowledge value-chain that is long and complex links (a) fundamental understanding of peat and peatland processes leading to sciencebased quantification and default values, (b) willingness and (c) ability to act towards emission reduction, and ultimately (d) to local, national and global actions that effectively provide rules, incentives and motivation to conserve peat and reduce emissions. We discuss this value chain, its stakeholders and issues that still remain partially unresolved. We conclude that, to shorten the denial and conspiracy-theory stages of debate that otherwise slow down steps B and C, networks of international and national scientists have to be involved at the early stage of identifying policysensitive environmental issues. Models span part of the knowledge value-chain but transition of analysis units requires specific attention, from soil volumes through area and commodity flows to opportunities for reductions. While drainage of peatlands triggers landscape-scale increases in emissions, factors beyond drainage depth, including nutrient supply, may have a major influence on decomposition rates. Attempts to disentangle the contributions of plant and peat-based respiration in surface flux measurements involve assumptions that cannot be easily verified in comparisons between land uses. With progress on A leading to new internationally accepted defaults and with resistance on step B reduced, the reality of C and lack of working solutions for D is currently constraining further progress.     

Sequential extraction combined with isotope analysis as a tool for the investigation of lead mobilisation in soils: application to organic-rich soils in an upland catchment in Scotland

Sequential extraction (modified BCR procedure) combined with isotope analysis has been investigated as a tool for assessing mobilisation of lead into streams at an upland catchment in NE Scotland. The maximum lead concentrations (up to 110 mg kg(-1) in air-dried soil) occurred not at the surface but at about 10 cm depth. The lowest (206)Pb/(207)Pb ratios in any profile occurred, with one exception, at 2.5-5 cm depth. In the one exception, closest to the only road in the area, significantly lower (206)Pb/(207)Pb ratios in the surface soil together with much increased chloride concentrations (in comparison to other surface waters) indicated the possible mobilisation of roadside lead and transfer to the stream. The (206)Pb/(207)Pb ratios in extractable fractions tended at depth towards the ratio measured in the residual phase but the ratios in the oxidizable fraction increased to a value higher than that of the residual phase.     

The Tropical Peatland Plantation-Carbon Assessment Tool: estimating CO2 emissions from tropical peat soils under plantations

Land use change on Indonesian peatlands contributes to global anthropogenic greenhouse gas (GHG) emissions. Accessible predictive tools are required to estimate likely soil carbon (C) losses and carbon dioxide (CO₂) emissions from peat soils under this land use change. Research and modelling efforts in tropical peatlands are limited, restricting the availability of data for complex soil model parameterisation and evaluation. The Tropical Peatland Plantation-Carbon Assessment Tool (TROPP-CAT) was developed to provide a user friendly tool to evaluate and predict soil C losses and CO₂ emissions from tropical peat soils. The tool requires simple input values to determine the rate of subsidence, of which the oxidising proportion results in CO₂ emissions. This paper describes the model structure and equations, and presents a number of evaluation and application runs. TROPP-CAT has been applied for both site specific and national level simulations, on existing oil palm and Acacia plantations, as well as on peat swamp forest sites to predict likely emissions from future land use change. Through an uncertainty and sensitivity analysis, literature reviews and comparison with other methods of estimating soil C losses, the paper identifies opportunities for future model development, bridging between different approaches to predicting CO₂ emissions from tropical peatlands under land use change. TROPP-CAT can be accessed online from www.redd-alert.eu in both English and Bahasa Indonesia.     

Becoming an undercover police officer: a note on fairness perceptions,behavior, and attitudes

Reactions to an undercover police officer selection system were analyzed for 271 officers. Officers given undercover assignments had higher procedural justice perceptions and outcome satisfaction than others awaiting assignment in a qualified applicant pool. Procedural and distributive justice perceptions were subsequently related to the undercover officer's job performance, job satisfaction, and organizational commitment. Copyright © 2003 John Wiley & Sons, Ltd.     

Ecosystem classifications based on summer and winter conditions

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.