Conceptual Background of Applied Geoinformatics



Present global climate modelling state-of-the-art and results have been published by the 4th Assessment Reports of the IPCC. They compile the results from 21 different atmosphere–ocean global circulation models (AOGCM) for the IPCC scenario A1B, evaluated as multimodel datasets (MMD-A1B) in the Program for Climate Model Diagnosis and Intercomparison (PCMDI). According to the 4th IPCC report, the temperature projections based on the MMD-A1B models indicate a significant warming over the 21st century. Temperature rise greater than the global mean is projected for South Asia (3.3 °C) and East Asia (3.3 °C), and is significantly higher than the global mean in the continental interior of Asia, for example, 3.7 °C in central Asia, 3.8 °C in Tibet, and 4.3 °C in northern Asia.


Integrate Water Resource Management Geographic Information System Analysis Geographic Information System Modelling River Basin Model Climate Change Impact Analysis 


  1. David O, Ascough II JC, Lloyd W, Green TR, Rojas KW, Leavesley GH, Ahuja LR (2013) A software engineering perspective on environmental modeling framework design: the object modeling system. Environ Model Softw 39:201–213CrossRefGoogle Scholar
  2. Dobler A, Yaoming M, Sharma N, Kienberger S, Ahrens B (2011) Regional climate projections in two Alpine River basins: Upper Danube and Upper Brahmaputra. Adv Sci Res 7:11–20. doi:10.5194/asr-7-11-2011. CrossRefGoogle Scholar
  3. Fink M, Krause P, Kralisch S, Bende-Michl U, Flügel W-A (2007) Development and application of the modelling system J2000-S for the EU-water framework directive. Adv Geosci 11:123–130CrossRefGoogle Scholar
  4. Flügel W-A (1995) Delineating Hydrological Response Units (HRU's) by GIS analysis for regional hydrological modelling using PRMS/MMS in the drainage basin of the River Bröl, Germany. Hydrol Process 9:423–436CrossRefGoogle Scholar
  5. Flügel W-A (1996) Hydrological Response Units (HRU) as modelling entities for hydrological river basin simulation and their methodological potential for modelling complex environmental process systems. Results from the Sieg catchment. DIE ERDE 127:42–62Google Scholar
  6. Flügel W-A (2000) Systembezogene Entwicklung regionaler hydrologischer Modellsysteme. Wasser Boden 52(3):14–17Google Scholar
  7. Flügel W-A (2009) Applied geoinformatics for sustainable IWRM and climate change impact analysis. Technol Resour Manage Dev 6:57–85Google Scholar
  8. Flügel W-A (2011a) Geoinformatics concepts, methods and toolsets for comprehensive impact assessment and analysis of climate change for IWRM. In: Joshi PK (ed) Geoinformatics for climate change studies, Chapter 6. Springer, TERI Press, 492 p. ISBN 9788179934098Google Scholar
  9. Flügel W-A, Busch C (2011) Development and implementation of an Integrated Water Resources Management System (IWRMS). Adv Sci Res 7:83–90. doi:10.5194/asr-7-83-2011. CrossRefGoogle Scholar
  10. Flügel W-A, Märker M (2003) The response units concept and its application for the assessment of hydrologically related erosion processes in Semiarid catchments of Southern Africa. ASTM-STP 1420:163–177Google Scholar
  11. Flügel W-A, Müschen B, Hochschild V, Steinocher K (2000) ARSGISIP, a European Project on the application of remote sensing techniques for the parameterization of hydrological. Erosion and solute transport models. IAHS-Publ 267:563–568Google Scholar
  12. Frauenfelder R, Kääb A (2009) Glacier mapping from multi-temporal optical remote sensing data within the Brahmaputra river basin. Conference: Remote Sensing of the Environment 2009, Stresa, ItalyGoogle Scholar
  13. Helmschrot J (2006a) An integrated, landscape-based approach to model the formation and hydrological functioning of wetlands in semiarid headwater catchments of the Umzimvubu River, South Africa. Sierke Verlag, Göttingen, 314 p. ISBN: 3-933893-75–5Google Scholar
  14. Helmschrot J (2006b) Assessment of temporal and spatial effects of landuse changes on wetland hydrology: a case study from South Africa. In: Kotowski W, Maltby E, Miroslaw–Swiatek D, Okruszko T, Szatylowicz J (eds) Wetlands: modelling, monitoring, management, Taylor & Francis, The Netherlands/A. A. Balkema Publisher, pp 197–204Google Scholar
  15. Helmschrot J, Flügel W-A (2002) Land use characterization and change detection analysis for hydrological model parameterisation of large scale afforested areas using remote sensing. Phys Chem Earth 27:711–718CrossRefGoogle Scholar
  16. Hutton CW, Kienberger S, Amoako Johnson F, Allan A, Giannini V, Allen R (2011) Vulnerability to climate change: people, place and exposure to hazard. Adv Sci Res 7:37–45. doi:10.5194/asr-7-37-2011. CrossRefGoogle Scholar
  17. IPCC (2000) Special report on emissions scenarios. A special report of working group III of the Intergovernmental Panel on Climate Change, 27 p. In: Nakicenovic N, Swart R (eds) Cambridge University Press, UK.
  18. IPCC, Intergovernmental Panel on Climate Change (2007a) Climate Change 2007, The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. http,//
  19. IPCC, Intergovernmental Panel on Climate Change (2007b) Climate change 2007, impacts, adaption and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the IPCC. http,//
  20. IPCC, Intergovernmental Panel on Climate Change (2007c) Climate change 2007, mitigation of climate change. Contribution of Working Group III to the Fourth Assessment Report of the IPCC. http,//
  21. IUCN (2003) Change. Adaptation of water management to climate change. IUCN, Gland, Switzerland and Cambridge, UK. ix+53 pGoogle Scholar
  22. Kääb A, Reynolds JM, Haeberli W (2005) Glacier and permafrost hazards in high mountains. In: Huber UM, Bugmann HKM, Reasoner MA (eds) Global change and mountain regions (A state of knowledge overview). Advances in global change research. Springer, Dordrecht, pp 225–234Google Scholar
  23. Karma AY, Naito N, Iwata S, Yabuki H (2003) Glacier distribution in the Himalayas and glacier shrinkage from 1963 to 1993 in the Bhutan Himalayas. Bull Glaciol Res 20:29–40Google Scholar
  24. Kralisch S, Krause P (2007) JAMS—a framework for natural resource model development and application. In: Voinov A, Jakeman A, Rizzoli AE (eds) Proceedings of the iEMSs Third Biannual Meeting “Summit on Environmental Modelling and Software”. Burlington, USA, July 2006. Int. Env. Modelling and Software SocietyGoogle Scholar
  25. Kralisch S, Fink M, Flügel W-A, Beckstein C (2003) A neural network approach for the optimization of watershed management. Environ Model Softw 18(8–9):815–823CrossRefGoogle Scholar
  26. Kralisch S, Fink M, Beckstein C (2005a) Neural network based sensitivity analysis of natural resource models. In: Zerger A, Argent RM (eds) Proc. MODSIM 2005, December 2005, 2498–2504Google Scholar
  27. Kralisch S, Krause P, David O (2005b) Using the object modeling system for hydrological model development and application. Adv Geosci 4:75–81CrossRefGoogle Scholar
  28. Kralisch S, Krause P, Fink M, Fischer C, Flügel W-A (2007) Component based environmental modelling using the JAMS framework. In: Kulasiri D, Oxley L (eds) MODSIM 2007 International congress on modelling and simulation. Modelling and Simulation Society of Australia and New Zealand, December 2007Google Scholar
  29. Kralisch S, Zander F, Krause P (2009) Coupling the RBIS Environmental Information System and the JAMS Modelling Framework. In: Anderssen R, Braddock R, Newham L (eds) Proc. 18th World IMACS/and MODSIM09 International Congress on Modelling and Simulation, Cairns, Australia, 902–908Google Scholar
  30. Kralisch S, Böhm B, Böhm C, Busch C, Fink M, Fischer C, Schwartze C, Selsam P, Zander F, Flügel W-A (2012) ILMS—a software platform for integrated environmental management. In: Seppelt R, Voinov AA, Lange S, Bankamp D (eds) iEMSs Proceedings, 2012 International Congress on Environmental Modelling and Software Managing Resources of a Limited Planet, Sixth Biennial Meeting, Leipzig, Germany.
  31. Krause P (2002) Quantifying the impact of land use changes on the water balance of large catchments using the J2000 model. Phys Chem Earth 27:663–673CrossRefGoogle Scholar
  32. Krause P, Flügel W-A (2005) Model integration and development of modular modelling systems. Adv Geosci 4:1–2CrossRefGoogle Scholar
  33. Krause P, Hanisch S (2009) Simulation and analysis of the impact of projected climate change on the spatially distributed water balance in Thuringia, Germany. Adv Geosci 7:1–16Google Scholar
  34. Krause P, Bende-Michl U, Bäse F, Fink M, Flügel W-A, Pfennig B (2006) Investigations in a mesoscale catchment—hydrological modelling in the gera catchment. Adv Geosci 9:53–61CrossRefGoogle Scholar
  35. Lang S, Kääb A, Pechstädt J, Flügel W-A, Zeil P, Lanz E, Kahuda D, Frauenfelder R, Casey K, Füreder P, Sossna I, Wagner I, Janauer G, Exler N, Boukalova Z, Thapa R, Lui J, Sharma N (2011) Assessing components of the natural environment of the Upper Danube and Upper Brahmaputra river basins. Adv Sci Res 7:21–36. doi:10.5194/asr-7-21-2011. CrossRefGoogle Scholar
  36. Mauser W, Bach H (2009) PROMET—Large scale distributed hydrological modelling to study the impact of climate change on the water flows of mountain watersheds. J Hydrol 376:362–377CrossRefGoogle Scholar
  37. Mauser W, Ludwig R (2002) GLOWA-DANUBE—a research concept to develop integrative techniques, scenarios and strategies regarding the global change of the water cycle. In: Beniston M (ed) Climatic change: implications for the hydrological cycle and for water management. Kluwer Academic Publishers, Boston. (Adv Global Change Research 10:171–188)Google Scholar
  38. Morrison J, Gleick P (2004) Freshwater resources: managing the risks facing the private sector. Research Paper, Pacific Institute ( August 2004, 16 p
  39. Nepal S (2012) Evaluating Upstream-Downstream Linkages of Hydrological Dynamics in the Himalayan Region. PhD. Thesis. Friedrich Schiller University of Jena, Germany.
  40. Nepal S, Krause P, Flügel W-A, Fink M, Fischer C (2013) Understanding the hydrological system dynamics of a glaciated alpine catchment in the Himalayan region using the J2000 hydrological model. Hydrol Process 28:1329–1344. doi:10.1002/hyp.9627CrossRefGoogle Scholar
  41. Paul F, Kääb A, Maisch M, Kellenberger T, Haeberli W (2004) Rapid disintegration of Alpine glaciers observed with satellite data. Geophys Res Lett 31:L21402. doi:10.1029/2004GL020816CrossRefGoogle Scholar
  42. Pfennig B, Kipka H, Wolf M, Fink M, Krause P, Flügel W-A (2009) Development of an extended spatially distributed routing scheme and its impact on process oriented hydrological modelling results. IAHS Publ 333:37–43Google Scholar
  43. Prasch M, Marke T, Strasser U, Mauser W (2011) Large scale integrated hydrological modelling of the impact of climate change on the water balance with DANUBIA. Adv Sci Res 7:61–70. doi:10.5194/asr-7-61-2011. CrossRefGoogle Scholar
  44. Querner EP (2002) Analysis of basin response resulting from climate change and mitigation measures. In: Van Lanen HAJ, Demuth S (eds) Regional hydrology, bridging the gap between research and practice. IAHS Publ, 274, pp 77–84 (Friend)Google Scholar
  45. Ren J, Qin D, Kang S, Hou S, Pu J, Jing Z (2004) Glacier variations and climate warming and drying in the central Himalayas. Chinese Sci Bull 49(1):65–69CrossRefGoogle Scholar
  46. Subba B (2001) Himalayan waters. The Panos Institute, South Asia, 286 pGoogle Scholar
  47. Wolf M, Pfennig B, Krause P, Flügel W-A (2009) Landscape dependent derivation of J2000 model parameters for hydrological modelling in Ungauged Basins. IAHS Publ 333:1–14Google Scholar
  48. Zander F, Kralisch S, Busch C, Flügel W-A (2012) Data management in multidisciplinary research projects with the River Basin information system. In: Pillmann W, Arndt H-K, Knetsch G (eds) Shaker Verlag, Dessau, pp 137–143Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Geoinformatics, Hydrology and ModellingFriedrich Schiller University, Jena (FSU-Jena)JenaGermany

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