Statistical Methods for Source Apportionment of Riverine Loads of Pollutants

Grimvall, Anders; Stålnacke, Per

doi:10.1002/(sici)1099-095x(199603)7:2<201::aid-env205>3.0.co;2-r

Cited by 53 publications

(34 citation statements)

References 18 publications

(7 reference statements)

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“…Currently, relatively little information is available to assess data on retention (Grimvall and Stalnacke, 1996). Additional approaches include a comparison of retention values in both disturbed and relatively undisturbed rivers, taking into consideration differences in climate, geology and land use of the watersheds, or a historical evaluation of the development of retention values in time for a particular river.…”

Section: Indicators For Functional Ecosystem Characteristicsmentioning

confidence: 99%

Concepts in river ecology: implications for indicator development

Lorenz¹,

Dijk²,

Hattum³

et al. 1997

Regul. Rivers: Res. Mgmt.

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The present study aims to develop river ecosystem indicators, in particular for the River Rhine, on the basis of theoretical concepts describing natural rivers. The study includes river ecology concepts on zonation, stream hydraulics, river continuum, nutrient spiralling, serial discontinuity, flood pulse, riverine productivity and catchment hierarchy. The abiotic steering variables describing the hydrology, geomorphology and water quality, act as a template for ecosystem functioning. Functional processes are characterized by the flux of matter, which is affected by input, processing and retention of organic matter and nutrients. Spatial and temporal variation of input and retention of matter and the flow along the length of the river cause shifts in species distribution. These are reflected in gradients of macroinvertebrates and zonation of fish and benthic fauna, which form a dominant structural characteristic of the river ecosystem.Indicators proposed are retention of matter as an indicator for the functional characteristics and zonation of species as an indicator for the structural characteristics of the river ecosystem. Present river ecosystems are far from undisturbed. To allow efficient management of the river ecosystem, indicators and variables are required that reflect the cause-effect chain of human disturbance. River ecologists have developed a more spatially integrated and interdisciplinary view on rivers. Accordingly, the design, implementation and ecological assessment of monitoring programmes should reflect such an integrated spatial view. This means that a set of water quality, hydrological, geomorphological and ecological variables should be measured on a catchment scale, and that resulting data should be related to each other. Finally, this study presents some recommendations for monitoring, in particular for the Rhine monitoring programme.

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Section: Indicators For Functional Ecosystem Characteristicsmentioning

confidence: 99%

Concepts in river ecology: implications for indicator development

Lorenz¹,

Dijk²,

Hattum³

et al. 1997

Regul. Rivers: Res. Mgmt.

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“…We use the term ''loss'' to refer to the permanent removal of N from an ecosystem or flow path by denitrification, but may also include, in reference to certain of the models, the effects of longterm N storage in terrestrial or aquatic ecosystems. Note that this definition of ''loss'' differs from that used in the European literature (e.g., Grimvall and Stalnacke 1996) to refer to N flux in streams or from the terrestrial landscape. We use the term ''removal'' in this paper to refer to the collection of processes that are responsible for N removal from flow paths, including permanent N losses by denitrification, long-term N storage, and the temporary N removal by heterotrophic or autotrophic processes.…”

Section: Introductionmentioning

confidence: 99%

Modeling Denitrification in Terrestrial and Aquatic Ecosystems at Regional Scales

Boyer

Alexander

Parton

et al. 2006

Ecological Applications

228

258

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Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source-transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures.

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“…They allow forecasting and a better understanding of processes; however, calibration and data requirements are important in large-scale applications aimed at policy support. Other simplified models addressing the problem of water quality are proposed in the literature and based on the export-coefficient approach (Hetling et al, 1999;Johnes, 1996;Grimvall and Stålnacke, 1996), mass balance GIS-based method (Pieterse et al, 2003;Skop and Srensen, 1998;Adamus and Bergman, 1995) and statistical regression (Seitzinger et al, 2002;De Wit, 2000Behrendt and Optiz, 2000;Smith et al, 1997).…”

Section: Introductionmentioning

confidence: 99%