A comparative study of heavy metal concentration and distribution in deposited street dusts in a large and a small urban area: Birmingham and Coventry, West Midlands, UK

Environment International, Journal Year: 2003, Volume and Issue: 29(5), P. 563 - 573

Published: May 12, 2003

Language: Английский

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Evaluation of the current state of mechanistic aquatic biogeochemical modeling

Marine Ecology Progress Series, Journal Year: 2004, Volume and Issue: 271, P. 13 - 26

Published: Jan. 1, 2004

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout JournalEditorsTheme Sections 271:13-26 (2004) - doi:10.3354/meps271013 Evaluation of current state mechanistic aquatic biogeochemical modeling George B. Arhonditsis1,2,*, Michael T. Brett1 1Department Civil & Environmental Engineering, More Hall, Box 352700, University Washington, Seattle, Washington 98195, USA 2Present address: Nicholas School Environment and Earth Sciences, Duke University, Durham, North Carolina 27708, *Email: [email protected] ABSTRACT: The need for predictive process-oriented planktonic ecosystem models is widely recognized by science community. We conducted a meta-analysis recent (153 studies published from 1990 2002), assess their ability predict spatial temporal patterns in physical, chemical biological dynamics systems. selected covered wide range model complexity, ecosystem-types, spatio-temporal scales purposes development. Despite heterogeneous nature this data set, we were able identify behavior trends illuminate aspects practice that be reevaluated. Temperature dissolved oxygen had highest coefficients determination (respective median r2 values 0.93 0.70) lowest relative error (median RE < 10%), nutrients phytoplankton intermediate predictability ranging 0.40 0.60 ~ 40%), whereas bacteria = 0.06) zooplankton 70%) poorly predicted. Longer simulation periods (i.e. months decades) reduced predictability, increased complexity did not improve fit. Aquatic modelers more consistent how they apply conventional methodological steps during development sensitivity analysis, validation), community should adopt generally accepted standards performance. Recent advancements assimilation techniques, combination present family with goal functions (derived non-equilibrium thermodynamics) stronger physiological basis are promising frameworks obtaining accurate simulations processes. KEY WORDS: Ecological · Model Eutrophication cycles Plankton systems Full text pdf format PreviousNextExport citation Tweet linkedIn Cited Published Vol. 271. Online publication date: April 28, 2004 Print ISSN: 0171-8630; 1616-1599 Copyright © Inter-Research.

Language: Английский

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Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs

Ecological Modelling, Journal Year: 2004, Volume and Issue: 181(4), P. 581 - 589

Published: Sept. 21, 2004

Language: Английский

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Implementation of ecological modeling as an effective management and investigation tool: Lake Kinneret as a case study

Ecological Modelling, Journal Year: 2009, Volume and Issue: 220(13-14), P. 1697 - 1718

Published: May 15, 2009

Language: Английский

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A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry

Remote Sensing of Environment, Journal Year: 2020, Volume and Issue: 244, P. 111831 - 111831

Published: May 6, 2020

Language: Английский

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Assessment of river quality models: a review

Reviews in Environmental Science and Bio/Technology, Journal Year: 2012, Volume and Issue: 12(3), P. 285 - 311

Published: June 27, 2012

Language: Английский

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Quantitative microbial risk assessment combined with hydrodynamic modelling to estimate the public health risk associated with bathing after rainfall events

The Science of The Total Environment, Journal Year: 2016, Volume and Issue: 548-549, P. 270 - 279

Published: Jan. 21, 2016

Language: Английский

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Impacts of Climate Change on the Water Quality of a Regulated Prairie River

Water, Journal Year: 2017, Volume and Issue: 9(3), P. 199 - 199

Published: March 10, 2017

Flows along the upper Qu’Appelle River are expected to increase in future via increased discharge from Lake Diefenbaker meet demands of agricultural and industrial activity population growth southern Saskatchewan. This air temperature due climate change both have an impact on water quality river. The Water Quality Analysis Simulation Program (WASP7) was used model current River. calibrated validated characterize state then predict [nutrient (nitrogen phosphorus) concentrations oxygen dynamics] for years 2050–2055 2080–2085. modelling results indicate that global warming will result a decrease ice thickness, shorter cover period, decreased nutrient 2050 or 2080 relative 2010, with greater open water. In contrast effect warmer temperatures, flow through management may cause increases ammonium, nitrate, dissolved decreases orthophosphate summer.

Language: Английский

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Spatiotemporal variation in nitrogen loads and their impacts on river water quality in the upper Yangtze River basin

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 590, P. 125487 - 125487

Published: Sept. 3, 2020

Language: Английский

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Forecast of chlorophyll-a concentration as an indicator of phytoplankton biomass in El Val reservoir by utilizing various machine learning techniques: A case study in Ebro river basin, Spain

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 639, P. 131639 - 131639

Published: July 5, 2024

The trophic condition of bodies water, such as oceans, lakes, and reservoirs, can be accurately assessed thanks to the use chlorophyll-a, or Chl-a, an indicator phytoplankton biomass abundance. In fact, main molecule in charge photosynthesis is Chl-a. This work presents a powerful reliable nonparametric method for predicting concentration Chl-a El Val reservoir using dataset containing 240,765 samples: Support Vector Regression (SVR) with different kinds kernels. mathematical SVR-relied model was constructed five years (2018–2022) water quality variable monitoring (physico-chemical independent variables) (located northeast Spain). For comparison, M5 trees, Multilayer Perceptron (MLP), that particular type artificial neural network (ANN), multivariate linear regression (MLR) were also used same observed data. Grid Search (GS) algorithm employed optimizer; this approach greatly improves precision by allowing optimal kernel parameters chosen during SVR training phase. There are two ways sum up findings investigation. First, it determined how relevant each input reservoir. Second, hybrid GS/SVR-relied PUK predict (R2 r values 0.8989 0.9499, respectively). model's agreement data amply proves remarkable efficacy creative strategy.

Language: Английский

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