Spatial variation in the landscape factors climate, geomorphology, and lithology cause significant differences in water quality issues even when land use pressures are similar. The Physiographic Environment Classification (PEC) classifies landscapes based on their susceptibility to the loss of water quality contaminants. The classification is informed by a conceptual model of the landscape factors that control the hydrochemical maturity of water discharged to streams.
View Article and Find Full Text PDFElevated contaminant levels and hydrological alterations resulting from land use are degrading aquatic ecosystems on a global scale. A range of land management actions may be used to reduce or prevent this degradation. To select among alternative management actions, decision makers require predictions of their effectiveness, their economic impacts, estimated uncertainty in the predictions, and estimated time lags between management actions and environmental responses.
View Article and Find Full Text PDFA method for objectively estimating reference states for suspended fine sediment (turbidity) is presented. To be fit for water policy development and implementation the method had to satisfy four requirements: (1) the method must not be dependent on data from minimally-disturbed reference sites; (2) the method must facilitate characterization of reference states throughout heterogeneous river networks, given patchy data; (3) the classification of reference states must be relevant and legitimate to end-users; (4) the method should provide several classifications of reference states at different spatial resolutions allowing selection of the resolution yielding the most parsimonious classification of reference states throughout the network. Implementing the method involves two stages: (1) Development of a river classification based on sediment supply and retention regimes (defining 'turbidity classes') at multiple spatial resolutions.
View Article and Find Full Text PDFA common land and water management task is to determine where and by how much source loadings need to change to meet water quality limits in receiving environments. This paper addresses the problem of quantifying changes in loading when limits are specified in many locations in a large and spatially heterogeneous catchment, accounting for cumulative downstream impacts. Current approaches to this problem tend to use either scenario analysis or optimization, which suffer from difficulties of generating scenarios that meet the limits, or high complexity of optimization approaches.
View Article and Find Full Text PDFThe Opuha Dam was designed for water storage, hydropower, and to augment summer low flows. Following its commissioning in 1999, algal blooms (dominated first by Phormidium and later Didymosphenia geminata) downstream of the dam were attributed to the reduced frequency and magnitude of high-flow events. In this study, we used a 20-year monitoring dataset to quantify changes associated with the dam.
View Article and Find Full Text PDFMapped environmental classifications are defined using various procedures, but there has been little evaluation of the differences in their ability to discriminate variation in independent ecological characteristics. We tested the performance of environmental classifications of the streams and rivers of France that had been defined from the same environmental data using geographic regionalization and numerical classification of individual river valley segments. Test data comprised invertebrate assemblages, water chemistry, and hydrological indexes obtained from sites throughout France.
View Article and Find Full Text PDFMultivariate classifications of environmental factors are used as frameworks for conservation management. Although classification performance is likely to be sensitive to choice of input variables, these choices have been subjective in most previous studies. We used the Mantel test on a limited set of sites for which biological data were available to iteratively seek a definition of environmental space (i.
View Article and Find Full Text PDFWe describe here the development of an ecosystem classification designed to underpin the conservation management of marine environments in the New Zealand region. The classification was defined using multivariate classification using explicit environmental layers chosen for their role in driving spatial variation in biologic patterns: depth, mean annual solar radiation, winter sea surface temperature, annual amplitude of sea surface temperature, spatial gradient of sea surface temperature, summer sea surface temperature anomaly, mean wave-induced orbital velocity at the seabed, tidal current velocity, and seabed slope. All variables were derived as gridded data layers at a resolution of 1 km.
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