Development of a rule-based fuzzy set classification model to determine process-based chemical hydrological response units (CHRUs) within the ArcView GIS ®

MODSIM05 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings

Volumn , Issue , 2005, Pages 1346-1353

  Bende Michl, U ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

Fuzzy Set classification; GIS; Modeling assessment of nutrients dynamics; Response units

Indexed keywords

ARCVIEW; CATCHMENT PROPERTIES; CLASSIFICATION MODELS; DOMINANT PROCESS; FUZZY CLASSIFICATION; FUZZY-SET CLASSIFICATION; GERMANY; HYDROCHEMICAL MODELS; HYDROCHEMICAL PROCESS; HYDROCHEMICALS; HYDROLOGICAL RESPONSE UNIT; LATERAL FLOW; MIDDLE MOUNTAINS; MULTI SCALE ANALYSIS; NITROGEN TURNOVER; NON-POINT SOURCE; OVERLAY ANALYSIS; PRE-PROCESSING; PROCESS BEHAVIOR; PROCESS DYNAMICS; PROCESS INFORMATION; RESPONSE UNITS; RIVER SYSTEMS; RULE BASED; SPATIAL HETEROGENEITY; SPATIAL INFORMATIONS; SPATIAL PATTERNS; SPATIAL REASONING; SPATIAL RELATIONS; TRANSLOCATION DYNAMICS; TRANSLOCATION PROCESS; HYDROCHEMICAL MODELING;

COMPUTER SIMULATION; DECISION MAKING; DYNAMICS; FUZZY SETS; GEOLOGIC MODELS; HYDROCHEMISTRY; LANDFORMS; NUTRIENTS; RATING; RIVERS; RUNOFF; CATCHMENTS; GEOGRAPHIC INFORMATION SYSTEMS; NITROGEN; TOPOGRAPHY;

CATCHMENTS; DECISION MAKING;

EID: 80053120163     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Bende, U. (1997), Regional hydrochemical modelling by delineation of chemical hydrological response units ( CHRUs) within a GIS: An approach of observing man-made impacts in the Bröl River catchment (Germany). Mathematics and Computers in Simulation, 43: 305-312.
2. Bende-Michl, U. (2004), Entwicklung eines multiskaligen hydrochemischen Regionalisierungskonzepts im Mittelgebirsgraum, Typisierung, Modellierung und Fuzzy-Setbasierte Flächenklassifikation nach einheitlichen Prozesseigenschaften, Dissertation, Jena.
3. Burrough, P. (1996); Natural Objects with indeterminated boundaries. P. Burrough and A. Frank (Eds.) Geographic Objects with indeterminated boundaries, London.
4. Cheng, T. and M. Molenaar (1999), Objects with fuzzy extend. Photoframmetric Engineering &Remote Sensing 65: 135-154.
5. Diekkrüger, B. (1999), Regionalisierung der Wasserquantität und -qualität - Konezpte und Methoden. U. Steinhardt and M. Volk (Eds.) Regionalisierung in der Landschaftsökologie, Stuttgart, Leipzig.
6. Fink, M. (2004), Regionale Modellierung der Wasser- und Stickstoffdynamik als Entscheidungsunterstützung für die Reduktion des N-Eintrags: am Beispiel des Trinkwassertalsperrensystems Weida-Zeulenroda, Thüringen, Dissertation, Jena.
7. Flügel, W. A. (1995), Delineating hydrological response units by geographical information system for regional hydrological modelling using MMS/PRMS in the drainage basin of the Bröl. Hydrologic Processes 9: 423-436.
8. Fonte, C. C. and Lowdwick, W. A. (2004), Modelling the Fuzzy Spatial Extend of Geographical Entities. E. Petry, V.B. Robinson, M. A. Cobb (eds.): Fuzzy Modeling with Spatial Information for Geographic Problems. Berlin, Heidelberg, New York, pp. 121-142.
9. Guesgen, H.W. (2004), Fuzzy Reasoning about Geographic Regions, E. Petry, V.B. Robinson, M. A. Cobb (eds.): Fuzzy Modeling with Spatial Information for Geographic Problems. Berlin, Heidelberg, New York, pp. 1-14.
10. Kern, T.J. and J. D. Stednick (1993), Identification of heavy metal concentrations in surface waters through coupling GIS and hydrochemical models. Kovar & Nachtnebel (Eds.) HydroGIS: Application of Geographic Information Systems in Hydrology and Water Resources. Proceedings of the Vienna Conference. IAHS Publ. 211: 559-567.
11. th NHRI Symposium, Applications of Remote Sensing in Hydrology.
12. Müller, G. (1998), Zur räumlichen Klassifikation der Abflussbildung im Mittelgebirge - Prozessstudien für eine Flächenklassifikation nach typischen Abflussbeiträgen, Dissertation, Dresden.
13. Nauck, U. (1999), Konzeption und Implementierung eines Neuro-Fuzzy-Datenanalysetools in Java. http://fuzzy.cs.unimagdeburg.de/nefclass.
14. Petry F.E., V.B. Robinson and M. A. Cobb (2004), Fuzzy Modeling with Spatial Information for Geographic Problems. Berlin, Heidelberg, New York.
15. Peuquet, D.J. (2002), Representations of Space and Time, The Guilford Press, New York.
16. Randell, D., Cui, Z. and A. Cohn (1992), A spatial logic based on regions and connection. Proceeding KR-92: 165-176, Cambridge, Massachusetts.
17. Reiche, E.-W. (1994), Modelling water and nitrogen dynamics on a catchment scale. Ecological Modelling 75/76:371-384.
18. Schmidt, D. (1996), Kopplung des Raster-GIS IDRISI mit einem Fuzzy-Klassifikationsmodell zur Modellierung eines unscharfen räumlichen Entscheidungsprozesses. Salzburger Geographische Schriften 25: 40-51.
19. Waldenmeyer, G. (2003), Abflussbildung und Regionalisierung in einem forstlich genutzten Einzugsgebiet (Dürreychtal, Nordschwarzwald), Karlsruher Schriften zur Geographie und Geoökologie 20: 1-277.
20. Zadeh, L. A. (1965), Fuzzy Sets. Information and Control 8: 338-353.