Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in‐stream water quality and process interactions, soil health and land management, and (peri‐)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

[1]  M. Owens,et al.  SOME REAERATION STUDIES IN STREAMS. , 1964, Air and water pollution.

[2]  R. Thomann,et al.  Dynamic Water Quality Forecasting And Management , 1973 .

[3]  P. Oquist,et al.  The Epistemology of Action Research , 1978 .

[4]  G. Box.  Robustness in the Strategy of Scientific Model Building. , 1979 .

[5]  R. Thomann,et al.  Principles of surface water quality modeling and control , 1987 .

[6]  R. Ghanem,et al.  Stochastic Finite Elements: A Spectral Approach , 1990 .

[7]  J. B. Ellis,et al.  Urban Drainage: Impacts on Receiving Water Quality , 1993 .

[8]  W. Näther.  Optimum experimental designs , 1994 .

[9]  K. Chaloner,et al.  Bayesian Experimental Design: A Review , 1995 .

[10]  S. Chapra.  Surface Water-Quality Modeling , 1996 .

[11]  M. Anderson,et al.  Assessing hydrogeochemical heterogeneity in natural and constructed wetlands , 1997 .

[12]  James L. Martin,et al.  Hydrodynamics and Transport for Water Quality Modeling , 1998 .

[13]  J. Schindler,et al.  The hyporheic zone as a source of dissolved organic carbon and carbon gases to a temperate forested stream , 1998 .

[14]  A. Huete,et al.  MODIS VEGETATION INDEX ( MOD 13 ) ALGORITHM THEORETICAL BASIS DOCUMENT Version 3 . 1 Principal Investigators , 1999 .

[15]  Anthony J. Jakeman,et al.  An analytical model for stream sediment transport: application to Murray and Murrumbidgee river reaches, Australia , 1999 .

[16]  John C. Gille,et al.  Algorithm Theoretical Basis Document , 1999 .

[17]  Robert M. Argent,et al.  Integrated models for environmental management: issues of process and design , 1999 .

[18]  Hans Bock,et al.  Numerical methods for optimum experimental design in DAE systems , 2000 .

[19]  S. Pope.  Turbulent Flows: FUNDAMENTALS , 2000 .

[20]  D Borchardt,et al.  River Water Quality Model no. 1 (RWQM1): I. Modelling approach. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[21]  P Reichert,et al.  River Water Quality Model no. 1 (RWQM1): III. Biochemical submodel selection. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[22]  P. Reichert,et al.  Identifiability and uncertainty analysis of the river water quality model no. 1 (RWQM1). , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[23]  P Reichert,et al.  River Water Quality Model no. 1 (RWQM1): II. Biochemical process equations. , 2001, Water science and technology : a journal of the International Association on Water Pollution Research.

[24]  R. Gifford,et al.  Soil carbon stocks and land use change: a meta analysis , 2002 .

[25]  Wolfgang Rauch,et al.  REBEKA––a software tool for planning urban drainage on the basis of predicted impacts on receiving waters , 2002 .

[26]  Dongbin Xiu,et al.  The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations , 2002, SIAM J. Sci. Comput..

[27]  A. Franzluebbers.  Water infiltration and soil structure related to organic matter and its stratification with depth , 2002 .

[28]  A. Louise Heathwaite,et al.  Making process-based knowledge useable at the operational level: a framework for modelling diffuse pollution from agricultural land , 2003, Environ. Model. Softw..

[29]  A. J. Stern,et al.  Crop Yield Assessment from Remote Sensing , 2003 .

[30]  C. Lovelock,et al.  Using glomalin as an indicator for arbuscular mycorrhizal hyphal growth: an example from a tropical rain forest soil , 2004 .

[31]  Paul Quinn,et al.  Scale appropriate modelling: representing cause-and-effect relationships in nitrate pollution at the catchment scale for the purpose of catchment scale planning , 2004 .

[32]  Roger Moore,et al.  An overview of the open modelling interface and environment (the OpenMI) , 2005 .

[33]  V. Brady,et al.  Relationship of stream flow regime in the western Lake Superior basin to watershed type characteristics , 2005 .

[34]  G Weiss,et al.  A new database on urban runoff pollution: comparison of separate and combined sewer systems. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[35]  Fotis Sotiropoulos,et al.  Introduction to Statistical Turbulence Modelling for Hydraulic Engineering Flows , 2005 .

[36]  M Schütze,et al.  An integrated modelling concept for immission-based management of sewer system, wastewater treatment plant and river. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[37]  P. Kareiva,et al.  Ecosystem services , 2005, Current Biology.

[38]  Nanée Chahinian,et al.  Large Sample Basin Experiments for Hydrological Model Parameterization: Results of the Model Parameter Experiment — MOPEX , 2006 .

[39]  John C. Schaake,et al.  The US MOPEX data set. , 2006 .

[40]  Jery R. Stedinger,et al.  Water Resources Systems Planning And Management , 2006 .

[41]  Jean-Luc Bertrand-Krajewski,et al.  Stormwater pollutant loads modelling: epistemological aspects and case studies on the influence of field data sets on calibration and verification. , 2007, Water science and technology : a journal of the International Association on Water Pollution Research.

[42]  N. Jarvis.  A review of non‐equilibrium water flow and solute transport in soil macropores: principles, controlling factors and consequences for water quality , 2007 .

[43]  Y. Rao,et al.  Off flavours in large waterbodies: physics, chemistry and biology in synchrony. , 2007, Water science and technology : a journal of the International Association on Water Pollution Research.

[44]  David K. Stevens,et al.  Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations 1 , 2011 .

[45]  K. C. Abbaspour,et al.  SWAT-CUP Calibration and Uncertainty Programs for SWAT , 2007 .

[46]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[47]  Stefan Achleitner,et al.  CITY DRAIN copyright - An open source approach for simulation of integrated urban drainage systems , 2007, Environ. Model. Softw..

[48]  G. S. Zhang,et al.  Relationship between soil structure and runoff/soil loss after 24 years of conservation tillage , 2007 .

[49]  Heikki Haario,et al.  Bayesian modelling of algal mass occurrences - using adaptive MCMC methods with a lake water quality model , 2007, Environ. Model. Softw..

[50]  K. Beven,et al.  SHE : towards a methodology for physically-based distributed forecasting in hydrology , 2007 .

[51]  D. Opdyke,et al.  Hydrodynamics and Water Quality: Modeling Rivers, Lakes, and Estuaries , 2008 .

[52]  Huaicheng Guo,et al.  Water quality modeling for load reduction under uncertainty: a Bayesian approach. , 2008, Water research.

[53]  E. Gaddis,et al.  Lessons for successful participatory watershed modeling: A perspective from modeling practitioners , 2008 .

[54]  Martin Volk,et al.  Integrated ecological-economic modelling of water pollution abatement management options in the Upper Ems River Basin , 2008 .

[55]  Benoit Cushman-Roisin,et al.  Environmental fluid mechanics: Current issues and future outlook , 2008 .

[56]  Martin Volk,et al.  Towards the implementation of the European Water Framework Directive?: Lessons learned from water quality simulations in an agricultural watershed , 2009 .

[57]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[58]  R. Wilby,et al.  A review of the potential impacts of climate change on surface water quality , 2009 .

[59]  J. Baar.  Development of soil quality metrics using mycorrhizal fungi. , 2010 .

[60]  E. Haber,et al.  Optimal Experimental Design for the Large‐Scale Nonlinear Ill‐Posed Problem of Impedance Imaging , 2010 .

[61]  Gabriele Freni,et al.  Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution , 2010 .

[62]  Jixian Zhang.  Multi-source remote sensing data fusion: status and trends , 2010 .

[63]  D. Wipf,et al.  Agroecology: the key role of arbuscular mycorrhizas in ecosystem services , 2010, Mycorrhiza.

[64]  David K. Stevens,et al.  A sensor network for high frequency estimation of water quality constituent fluxes using surrogates , 2010, Environ. Model. Softw..

[65]  M. Rumor.  Environmental Monitoring and Assessment , 2011 .

[66]  H. Blanco‐Canqui.  Does no‐till farming induce water repellency to soils? , 2011 .

[67]  N. McIntyre,et al.  Catchment scale hydrological modelling: a review of model types, calibration approaches and uncertainty analysis methods in the context of recent developments in technology and applications , 2011 .

[68]  R. Dalal,et al.  Soil Health Indicators Under Climate Change: A Review of Current Knowledge , 2011 .

[69]  H. Nepf.  Flow and Transport in Regions with Aquatic Vegetation , 2012 .

[70]  Sankaran Mahadevan,et al.  Likelihood-Based Approach to Multidisciplinary Analysis Under Uncertainty , 2012 .

[71]  Laurence Smith,et al.  The role of expert opinion in environmental modelling , 2012, Environ. Model. Softw..

[72]  Kyle R. Douglas-Mankin,et al.  Hydrologic and Water Quality Models: Use, Calibration, and Validation , 2012 .

[73]  S. Basu.  Turbulent Flow Modeling , 2012 .

[74]  D. Tonina.  Surface water and streambed sediment interaction: The hyporheic exchange , 2012 .

[75]  G. Doria.  Gas-transfer at unsheared free-surfaces , 2012 .

[76]  Ben R. Hodges,et al.  Challenges in Continental River Dynamics , 2013, Environ. Model. Softw..

[77]  I. Nopens,et al.  Cost-effective solutions for water quality improvement in the Dommel River supported by sewer-WWTP-river integrated modelling. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[78]  Joseph H. A. Guillaume,et al.  Characterising performance of environmental models , 2013, Environ. Model. Softw..

[79]  Keith Beven,et al.  Macropores and water flow in soils revisited , 2013 .

[80]  D. Tonina,et al.  Hydraulic Modelling Approaches for Ecohydraulic Studies: 3D, 2D, 1D and Non‐Numerical Models , 2013 .

[81]  Mary C. Hill,et al.  Integrated environmental modeling: A vision and roadmap for the future , 2013, Environ. Model. Softw..

[82]  W. Rodi,et al.  Large-Eddy Simulation in Hydraulics , 2013 .

[83]  Scott D. Peckham,et al.  A component-based approach to integrated modeling in the geosciences: The design of CSDMS , 2013, Comput. Geosci..

[84]  Thorsten R. Arnold,et al.  Procedural knowledge for integrated modelling: Towards the Modelling Playground , 2013, Environ. Model. Softw..

[85]  Rolf Rannacher,et al.  Model Based Parameter Estimation , 2013 .

[86]  H. Bock,et al.  Parameter Estimation and Optimum Experimental Design for Differential Equation Models , 2013 .

[87]  K. R. Douglas-Mankin,et al.  Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations , 2014, Environ. Model. Softw..

[88]  Piet Seuntjens,et al.  Use of online water quality monitoring for assessing the effects of WWTP overflows in rivers. , 2014, Environmental science. Processes & impacts.

[89]  Jochen F. Mueller,et al.  Quality Assurance & Quality Control of Environmental Field Sampling , 2014 .

[90]  T. Stoesser.  Large-eddy simulation in hydraulics: Quo Vadis? , 2014 .

[91]  D. Mccarthy,et al.  Quality assurance/quality control in stormwater sampling , 2014 .

[92]  Karen Willcox,et al.  A decomposition‐based approach to uncertainty analysis of feed‐forward multicomponent systems , 2014 .

[93]  Olaf David,et al.  Model-As-A-Service (MaaS) Using the Cloud Services Innovation Platform (CSIP) , 2014 .

[94]  Peng Wang,et al.  A Bayesian method for multi-pollution source water quality model and seasonal water quality management in river segments , 2014, Environ. Model. Softw..

[95]  Jochen F. Mueller,et al.  An introduction to quality assurance/quality control in environmental field sampling , 2014 .

[96]  Peter Steen Mikkelsen,et al.  A critical review of integrated urban water modelling - Urban drainage and beyond , 2014, Environ. Model. Softw..

[97]  Valerie O. Snow,et al.  Agricultural production systems modelling and software: Current status and future prospects , 2015, Environ. Model. Softw..

[98]  K. Abbaspour,et al.  A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model , 2015 .

[99]  Youssef,et al.  Hydrological Processes and Model Representation: Impact of Soft Data on Calibration , 2015 .

[100]  Juha Hyyppä,et al.  Two‐dimensional and three‐dimensional computational models in hydrodynamic and morphodynamic reconstructions of a river bend: sensitivity and functionality , 2015 .

[101]  Paul Quinn,et al.  Digital catchment observatories: A platform for engagement and knowledge exchange between catchment scientists, policy makers, and local communities , 2015 .

[102]  Richard A. Skeffington,et al.  High‐frequency water quality monitoring in an urban catchment: hydrochemical dynamics, primary production and implications for the Water Framework Directive , 2015 .

[103]  David P. Hamilton,et al.  Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories , 2015 .

[104]  Dharmendra Saraswat,et al.  Hydrologic and Water Quality Models: Key Calibration and Validation Topics , 2015 .

[105]  Jeffery S. Horsburgh,et al.  Evaluating the simulation times and mass balance errors of component-based models: An application of OpenMI 2.0 to an urban stormwater system , 2015, Environ. Model. Softw..

[106]  Joseph H. A. Guillaume,et al.  Integrated assessment and modelling: Overview and synthesis of salient dimensions , 2015, Environ. Model. Softw..

[107]  Andrew J. Wade,et al.  Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive , 2015 .

[108]  Jon E. Schoonover,et al.  An Introduction to Soil Concepts and the Role of Soils in Watershed Management , 2015 .

[109]  Naresh Pai,et al.  A Recommended Calibration and Validation Strategy for Hydrologic and Water Quality Models , 2015 .

[110]  Wim S. J. Uijttewaal,et al.  Effects of vegetation on flow and sediment transport: comparative analyses and validation of predicting models , 2015 .

[111]  Oei,et al.  Guidance on Systematic Planning Using the Data Quality Objectives Process, EPA QA/G-4 , 2015 .

[112]  Tim R. McVicar,et al.  Global‐scale regionalization of hydrologic model parameters , 2016 .

[113]  Suzanne A. Pierce,et al.  Modelling with stakeholders e Next generation , 2015 .

[114]  Michael Rode,et al.  Sensors in the Stream: The High-Frequency Wave of the Present. , 2016, Environmental science & technology.

[115]  Beck Hylke,et al.  Global-scale regionalization of hydrologic model parameters , 2016 .

[116]  Holger R. Maier,et al.  Best practices for conceptual modelling in environmental planning and management , 2016, Environ. Model. Softw..

[117]  A. J. Jakeman,et al.  An Overview of Methods to Identify and Manage Uncertainty for Modelling Problems in the Water–Environment–Agriculture Cross-Sector , 2016 .

[118]  Budiman Minasny,et al.  Digital soil mapping: A brief history and some lessons , 2016 .

[119]  David Hannah,et al.  Real-time monitoring of nutrients and dissolved organic matter in rivers: Capturing event dynamics, technological opportunities and future directions. , 2016, The Science of the total environment.

[120]  A. Ward.  The evolution and state of interdisciplinary hyporheic research , 2016 .

[121]  Brandon P. Wong,et al.  Real-time environmental sensor data: An application to water quality using web services , 2016, Environ. Model. Softw..

[122]  David T. Limmer,et al.  Water at Interfaces. , 2016, Chemical reviews.

[123]  J. Vader,et al.  A checklist for model credibility, salience, and legitimacy to improve information transfer in environmental policy assessments , 2016, Environ. Model. Softw..

[124]  A. Wade,et al.  Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA‐P , 2017 .

[125]  J. Herr,et al.  WARMF-Online – A Web-Based Portal Supporting Real-time Salinity Management in the San Joaquin River Basin , 2017 .

[126]  Peng Yue,et al.  GeoJModelBuilder: an open source geoprocessing workflow tool , 2017, Open Geospatial Data, Software and Standards.

[127]  T. Krueger.  Bayesian inference of uncertainty in freshwater quality caused by low-resolution monitoring. , 2017, Water research.

[128]  A Deletic,et al.  Modelling transitions in urban water systems. , 2017, Water research.

[129]  U. Jeppsson,et al.  A model library for simulation and benchmarking of integrated urban wastewater systems , 2017, Environ. Model. Softw..

[130]  Jeffery S. Horsburgh,et al.  Design of a metadata framework for environmental models with an example hydrologic application in HydroShare , 2017, Environ. Model. Softw..

[131]  John D. Jakeman,et al.  Optimal Experimental Design Using A Consistent Bayesian Approach , 2017, 1705.09395.

[132]  J. Horsburgh,et al.  An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances , 2017, Environmental Monitoring and Assessment.

[133]  Jun Wang,et al.  Real-Time Web-Based Decision Support for Stakeholder Implementation of Basin-Scale Salinity Management , 2017, ISESS.

[134]  Anders Nielsen,et al.  An open source QGIS-based workflow for model application and experimentation with aquatic ecosystems , 2017, Environ. Model. Softw..

[135]  Ward N. Smith,et al.  Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes. , 2017, The Science of the total environment.

[136]  G. Katul,et al.  Multiple mechanisms generate a universal scaling with dissipation for the air‐water gas transfer velocity , 2017 .

[137]  M. Follum,et al.  Large-Scale Flood Inundation Modeling in Data Sparse Environments using TanDEM-X Terrain Data , 2017 .

[138]  V. Snow,et al.  Nitrogen Cycling from Increased Soil Organic Carbon Contributes Both Positively and Negatively to Ecosystem Services in Wheat Agro-Ecosystems , 2017, Front. Plant Sci..

[139]  C. Gualtieri,et al.  A field study of the confluence between Negro and Solimões Rivers. Part 1: Hydrodynamics and sediment transport , 2017 .

[140]  Feng Liu,et al.  Recent progress and future prospect of digital soil mapping: A review , 2017 .

[141]  G. Harvey,et al.  Life in turbulent flows: interactions between hydrodynamics and aquatic organisms in rivers , 2017 .

[142]  Z. Ji.  Hydrodynamics and water quality : modeling rivers, lakes, and estuaries , 2017 .

[143]  Anthony J. Jakeman,et al.  Uncertainty in Environmental Water Quality Modelling: Where Do We Stand? , 2018 .

[144]  Jeffery S. Horsburgh,et al.  Advancing the Open Modeling Interface (OpenMI) for integrated water resources modeling , 2018, Environ. Model. Softw..

[145]  Xi Chen,et al.  Uncertainty analysis of a semi-distributed hydrologic model based on a Gaussian Process emulator , 2018, Environ. Model. Softw..

[146]  Advances in River Water Quality Modelling and Management: Where We Come from, Where We Are, and Where We’re Going? , 2018, New Trends in Urban Drainage Modelling.

[147]  Peter J. Thorburn,et al.  Modelling crops and cropping systems—Evolving purpose, practice and prospects , 2018, European Journal of Agronomy.

[148]  C. Gascuel-Odoux,et al.  Challenges of Reducing Phosphorus Based Water Eutrophication in the Agricultural Landscapes of Northwest Europe , 2018, Front. Mar. Sci..

[149]  Derek B. Ingham,et al.  Optimisation of flow resistance and turbulent mixing over bed forms , 2018, Environ. Model. Softw..

[150]  Ricardo Vieira,et al.  ScoRE—A Simple Approach to Select a Water Quality Model , 2018, Water.

[151]  Benjamin Peherstorfer,et al.  Survey of multifidelity methods in uncertainty propagation, inference, and optimization , 2018, SIAM Rev..

[152]  A. V. Vecchia.  Model methodology for estimating pesticide concentration extremes based on sparse monitoring data , 2018 .

[153]  Joseph R. Kasprzyk,et al.  Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: Successes and challenges , 2018, Environ. Model. Softw..

[154]  Matthias Zessner,et al.  Modelled impacts of policies and climate change on land use and water quality in Austria , 2018, Land Use Policy.

[155]  T. Quine,et al.  Tracing of particulate organic C sources across the terrestrial-aquatic continuum, a case study at the catchment scale (Carminowe Creek, southwest England). , 2018, The Science of the total environment.

[156]  J. Bouma,et al.  Refining physical aspects of soil quality and soil health when exploring the effects of soil degradation and climate change on biomass production: an Italian case study , 2018 .

[157]  Cengiz Koparan,et al.  In Situ Water Quality Measurements Using an Unmanned Aerial Vehicle (UAV) System , 2018 .

[158]  M. P. González-Dugo,et al.  Twenty-three unsolved problems in hydrology (UPH) – a community perspective , 2019, Hydrological Sciences Journal.

[159]  N. Kitchen,et al.  Long-term simulated runoff and water quality from grain cropping systems on restrictive layer soils , 2019, Agricultural Water Management.

[160]  Ugur Avdan,et al.  Monitoring the Water Quality of Small Water Bodies Using High-Resolution Remote Sensing Data , 2019, ISPRS Int. J. Geo Inf..

[161]  Ashish Sharma,et al.  The influence of data transformations in simulating Total Suspended Solids using Bayesian inference , 2019, Environ. Model. Softw..

[162]  Anthony J. Jakeman,et al.  A review of catchment-scale water quality and erosion models and a synthesis of future prospects , 2019, Environ. Model. Softw..

[163]  Jeffery S. Horsburgh,et al.  Parallel multi-objective calibration of a component-based river temperature model , 2019, Environ. Model. Softw..

[164]  A. Western,et al.  Key Factors Affecting Temporal Variability in Stream Water Quality , 2019, Water Resources Research.

[165]  W. McDonald.  Drones in urban stormwater management: a review and future perspectives , 2019, Urban Water Journal.

[166]  Joseph H. A. Guillaume,et al.  A framework for characterising and evaluating the effectiveness of environmental modelling , 2019, Environ. Model. Softw..

[167]  Nadejda A. Soudzilovskaia,et al.  Global mycorrhizal plant distribution linked to terrestrial carbon stocks , 2019, Nature Communications.

[168]  Joseph H. A. Guillaume,et al.  Introductory overview of identifiability analysis: A guide to evaluating whether you have the right type of data for your modeling purpose , 2019, Environ. Model. Softw..

[169]  M. Stutter,et al.  Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors. , 2019, Journal of environmental quality.

[170]  M. Futter,et al.  An evaluation of high frequency turbidity as a proxy for riverine total phosphorus concentrations. , 2019, The Science of the total environment.

[171]  M. Flindt,et al.  Impact of Land Use and Runoff on Stream Quality , 2019, Sustainability.

[172]  F. Krajinski,et al.  Trading on the arbuscular mycorrhiza market: from arbuscules to common mycorrhizal networks. , 2019, The New phytologist.

[173]  G. Katul,et al.  Friction factor for turbulent open channel flow covered by vegetation , 2019, Scientific Reports.

[174]  D. Lobell,et al.  Satellites reveal a small positive yield effect from conservation tillage across the US Corn Belt , 2019, Environmental Research Letters.

[175]  Alison P. Appling,et al.  AquaSat: A Data Set to Enable Remote Sensing of Water Quality for Inland Waters , 2019, Water Resources Research.

[176]  Johan Bouma,et al.  Refining physical aspects of soil quality and soil health when exploring the effects of soil degradation and climate change on biomass production: an Italian case study , 2019, SOIL.

[177]  Lee-Fong Yau,et al.  Alterations of Sphingolipid Metabolism in Different Types of Polycystic Ovary Syndrome , 2019, Scientific Reports.

[178]  Joachim Denzler,et al.  Deep learning and process understanding for data-driven Earth system science , 2019, Nature.

[179]  I. Cozzarelli,et al.  Urban Stormwater: An Overlooked Pathway of Extensive Mixed Contaminants to Surface and Groundwaters in the United States , 2019, Environmental science & technology.

[180]  T. Endreny,et al.  A 3D analysis of spatial habitat metrics about the confluence of Negro and Solimões rivers, Brazil , 2019, Ecohydrology.

[181]  A. Don,et al.  Factors controlling the variation in organic carbon stocks in agricultural soils of Germany , 2019, European Journal of Soil Science.

[182]  N. Gill,et al.  Transformational adaptation on the farm: Processes of change and persistence in transitions to ‘climate-smart’ regenerative agriculture , 2019, Global Environmental Change.

[183]  I. Moudrakovski,et al.  Sub-stoichiometric 2D covalent organic frameworks from tri- and tetratopic linkers , 2019, Nature Communications.

[184]  Horst P. Beck,et al.  Real-time monitoring of water quality to identify pollution pathways in small and middle scale rivers. , 2019, The Science of the total environment.

[185]  Jennifer Badham,et al.  Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities , 2019, Environ. Model. Softw..

[186]  Gianluca Geraci,et al.  Adaptive Multi-index Collocation for Uncertainty Quantification and Sensitivity Analysis , 2019, International Journal for Numerical Methods in Engineering.

[187]  D. Lawrence,et al.  Infiltration from the Pedon to Global Grid Scales: An Overview and Outlook for Land Surface Modeling , 2019, Vadose Zone Journal.

[188]  Anthony J. Jakeman,et al.  Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources , 2020, Environ. Model. Softw..

[189]  Baihua Fu,et al.  A bricolage-style exploratory scenario analysis to manage uncertainty in socio-environmental systems modeling: investigating integrated water management options , 2020 .

[190]  Cornelius Senf,et al.  Benchmarking inference methods for water quality monitoring and status classification , 2020, Environmental Monitoring and Assessment.

[191]  Min Chen,et al.  A global sensitivity analysis approach for identifying critical sources of uncertainty in non-identifiable, spatially distributed environmental models: A holistic analysis applied to SWAT for input datasets and model parameters , 2020, Environ. Model. Softw..

[192]  Gianluca Geraci,et al.  A generalized approximate control variate framework for multifidelity uncertainty quantification , 2018, J. Comput. Phys..

[193]  K. Carlson,et al.  Turbulent Flows , 2020, Finite Analytic Method in Flows and Heat Transfer.

[194]  Alessandro Veneziani,et al.  Propagating uncertainties in large-scale hemodynamics models via network uncertainty quantification and reduced-order modeling , 2020 .

[195]  R. Tinoco,et al.  Simplification bias: lessons from laboratory and field experiments on flow through aquatic vegetation , 2020, Earth Surface Processes and Landforms.

[196]  Magnus Dahler Norling,et al.  Rapid development of fast and flexible environmental models: the Mobius framework v1.0 , 2020, Geoscientific Model Development.

[197]  H. McMillan.  Linking hydrologic signatures to hydrologic processes: A review , 2020, Hydrological Processes.

[198]  Joseph H. A. Guillaume,et al.  From ad-hoc modelling to strategic infrastructure: A manifesto for model management , 2020, Environ. Model. Softw..

[199]  U. Dittmer,et al.  Impact of Combined Sewer Systems on the Quality of Urban Streams: Frequency and Duration of Elevated Micropollutant Concentrations , 2020, Water.

[200]  Xie-kang Wang,et al.  Morphological environment survey and hydrodynamic modeling of a large bifurcation-confluence complex in Yangtze River, China. , 2020, The Science of the total environment.

[201]  Magnus Dahler Norling,et al.  Rapid development of fast and flexible environmental models: the Mobius framework v1.0 , 2021 .