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Reduced Models of the Retention of Nitrogen in Catchments
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
Aquatic Environments Research Centre, School of Human and Environmental Sciences, The University of Reading, UK.
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2004 (English)In: Proceedings of the International Environmental Modelling and Software Society Conference (iEMSs), 14-17 June, Osnabrück, Germany, 2004, 1081-1086 p.Conference paper, Published paper (Refereed)
Abstract [en]

Process-oriented models of the retention of nitrogen in catchments are by necessity rather complex. We introduced several types of ensemble runs that can provide informative summaries of meteorologically normalised model outputs and also clarify the extent to which such outputs are related to various model parameters. Thereafter we employed this technique to examine policy-relevant outputs of the catchment model INCA-N. In particular, we examined how long it will take for changes in the application of fertilisers on cultivated land to affect the predicted riverine loads of nitrogen. The results showed that the magnitude of the total intervention effect was influenced mainly by the parameters governing the turnover of nitrogen in soil, whereas the temporal distribution of the water quality response was determined primarily by the hydromechanical model parameters. This raises the question of whether the soil nitrogen processes included in the model are elaborate enough to correctly explain the widespread observations of slow water quality responses to changes in agricultural practices.

Place, publisher, year, edition, pages
2004. 1081-1086 p.
Keyword [en]
Model reduction; Ensemble runs; Catchment; Nitrogen; Retention
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-17110OAI: oai:DiVA.org:liu-17110DiVA: diva2:201970
Available from: 2009-03-06 Created: 2009-03-06 Last updated: 2009-12-11Bibliographically approved
In thesis
1. Computer Experiments Designed to Explore and Approximate Complex Deterministic Models
Open this publication in new window or tab >>Computer Experiments Designed to Explore and Approximate Complex Deterministic Models
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Computer experiments are widely used to investigate how technical, economic, and ecological systems respond to changes in inputs or driving forces. This thesis is focused on design of computer experiments that can help us better understand the output from complex computer code models. The major part of our work was devoted to experiments involving derivation and application of computationally cheaper surrogate models of a given computer code model. We developed an adaptive sequential design algorithm that efficiently reveals nonlinearities in the model output, and we integrated this algorithm with methods for predicting model outputs at untried inputs. Compared to the methods currently in use, our sequential design has the advantage of not requiring any prior information about the response of the investigated model output to changes in the inputs. Of special interest, we found that our algorithm works satisfactorily even if the curvature of the response surface varies strongly over the input domain. Variance-based sensitivity analysis is a well-established technique to elucidate model outputs, but it can become prohibitively expensive to implement because it requires numerous model runs. Surrogate models can facilitate such analysis, and if our sequential design algorithm is utilized, it can supply useful information about both linear and nonlinear responses to model inputs. Experiments involving repeated runs of a model of the flow of water and nitrogen through a river basin showed that our approach can be applied to extract the essence of complex deterministic models. In addition, our research showed that computationally inexpensive surrogate models offer an ideal basis for interactive decision support tools and learning processes, because they can provide almost immediate responses to user-defined model inputs.

Abstract [sv]

Datorexperiment används allmänt för att undersöka hur tekniska, ekonomiska och ekologiska system reagerar på förändringar i tillförsel eller drivkrafter. Denna avhandling är inriktad på datorexperiment som kan hjälpa oss att bättre förstå beräkningar baserade på komplicerade numeriska modeller som bara är definierade av en datorkod. Huvuddelen av vårt arbete ägnades åt experiment som innefattar härledning och tillämpning av beräkningsmässigt billiga s.k. surrogatmodeller som ger nästan samma resultat som ursprungsmodellen. Vi utvecklade en adaptiv sekventiell designalgoritm som effektivt avslöjar icke-linjära reaktioner på ändrad input till modellen, och vi integrerade denna algoritm med metoder för att prediktera modellens output för nya indata. Jämfört med de metoder som nu används har vår algoritm fördelen att den inte ställer några krav på förhandsinformation om modellens struktur. Speciellt noterade vi att den fungerar tillfredsställande även om olika delar av modellens responsyta har helt olika statistiska egenskaper. Varians-baserad känslighetsanalys är en väl etablerad teknik för att belysa modellers output, men den kan leda till höga datorkostnader eftersom den kräver många modellkörningar. Surrogatmodeller kan i sådana fall underlätta analysen. Om vår sekventiella designalgoritm utnyttjas, kan man desutom få viktig information om både linjära och icke-linjära effekter av förändringar i modellens indata. Experiment som innefattade upprepade körningar av en model för flödet av vatten och kväve genom ett avrinningsområde visade att man kan klarlägga det centrala i stora komplexa modeller. Dessutom visade vår forskning att beräkningsmässigt billiga surrogatmodeller erbjuder en idealisk grund för beslutstöd och lärandeprocesser, eftersom de kan ge en nästan omedelbar respons på de data som användaren matar in i modellen.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2008. 58 + papers 1-4 p.
Series
Linköping Studies in Arts and Science, ISSN 0282-9800 ; 423Linköping Studies in Statistics, ISSN 1651-1700 ; 9
National Category
Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-17115 (URN)978-91-7393-976-8 (ISBN)
Public defence
2008-02-29, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:00 (English)
Opponent
Supervisors
Available from: 2009-03-06 Created: 2009-03-06 Last updated: 2014-09-23Bibliographically approved
2. Roadmap for trend detection and assessment of data quality
Open this publication in new window or tab >>Roadmap for trend detection and assessment of data quality
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Regular measurements of the state of the environment constitute a cornerstone of environmental management. Without the support of long time series of reliable data, we would know much less about changes that occur in the environment and their causes. The present research aimed to explore how improved techniques for data analysis can help reveal flawed data and extract more information from environmental monitoring programmes. Based on our results, we propose that the organization of such monitoring should be transformed from a system for measuring and collecting data to an information system where resources have been reallocated to data analysis. More specifically, this thesis reports improved methods for joint analysis of trends in multiple time series and detection of artificial level shifts in the presence of smooth trends. Furthermore, special consideration is given to methods that automatically detect and adapt to the interdependence of the collected data. The current work resulted in a roadmap describing the process of proceeding from a set of observed concentrations to arrive at conclusions about the quality of the data and existence of trends therein. Improvements in existing software accompanied the development of new statistical procedures.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2008. 81 + papers 1-5 p.
Series
Linköping Studies in Statistics, ISSN 1651-1700 ; 10Linköping Studies in Arts and Science, ISSN 0282-9800 ; 454
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-43109 (URN)71719 (Local ID)978-91-7393-792-4 (ISBN)71719 (Archive number)71719 (OAI)
Public defence
2008-10-10, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Supervisors
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-09-25Bibliographically approved

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Wahlin, KarlShahsavani, DavoodGrimvall, Anders

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