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Models for Describing Landscape Hydrochemical Discharge in Mountain Countries

  • Yuri KirstaEmail author
  • Alexander Puzanov
  • Tamara Rozhdestvenskaya
Chapter
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Part of the Innovations in Landscape Research book series (ILR)

Abstract

Using 34 river basins of the Altai-Sayan mountain country as an example, the universal mathematical models for seasonal and long-term dynamics of landscape water and hydrochemical discharges were developed. For this purpose, the system-analytical modelling and the solution of mathematical inverse problem were applied. The input factors of the models include monthly precipitation and mean monthly air temperature, spatially generalized for the country, as well as the cartographic information on the area and average altitude of individual landscapes in river basins, the altitude of the outlets, the length of river channels, and the area of arable land. The water and seven hydrochemical discharges (three nitrogen mineral forms \( {\text{NO}}_{2}^{ - } ,\,{\text{NO}}_{3}^{ - } ,\,{\text{NH}}_{4}^{ + } \), phosphates \( {\text{PO}}_{4}^{3 - } \), ions, total dissolved iron, suspended matter) are calculated for each of 13 specified landscape types in each river basin. The sensitivity of discharges to variations of environmental factors is evaluated. The Nash-Sutcliffe efficiency estimated as more than 0.65 for the models represent their good and very good performance. The models also make it possible to forecast the seasonal dynamics of discharges for any river basin in the country under study.

Keywords

Mountain rivers Landscapes System-analytical modelling Water discharge Hydrochemical discharge Forecast Altai-Sayan 

References

  1. Beven K, Hall J (2013) Applied uncertainty analysis for flood risk management. Imperial College Press, LondonGoogle Scholar
  2. Hauduc H, Neumann M, Muschalla D, Gamerith V, Gillot S, Vanrolleghem PA (2011) Towards quantitative quality criteria to evaluate simulation results in wastewater treatment — A critical review. In: Proceedings 8th international IWA symposium on systems analysis and integrated assessment in water management (WATERMATEX2011). San Sebastian, Spain, June 20–22, pp 36–46Google Scholar
  3. Iooss B, Lemaitre P (2015) A review on global sensitivity analysis methods. In: Meloni C, Dellino G (eds) Uncertainty management in simulation-optimization of complex systems: algorithms and applications. Springer, USCrossRefGoogle Scholar
  4. Kirsta YB (1986) Modelling of desert ecosystems, Ashgabat, Ylym (in Russian)Google Scholar
  5. Kirsta YB (2006) System-analytical modelling — Part I: General principles and theoretically best accuracies of ecological models. Soil-moisture exchange in agroecosystems. Ecol Model 191:315–330CrossRefGoogle Scholar
  6. Kirsta YB (2011) Spatial generalization of climatic characteristics in mountain areas. World Sci Cult Educ (Mir Nauki, Kul’tury, Obrazovaniya), 3(28):330–337 (in Russian)Google Scholar
  7. Kirsta YB (2016) Modeling of hydrochemical composition of mountain river runoff: 2. Assessment of model performance for the runoff of mineral nitrogen forms. News Samara Sci Cent RAS 18(2):408–412 (in Russian)Google Scholar
  8. Kirsta YB, Kirsta DY (2014) The information-physical principle of evolutionary systems formation, system-analytical modeling of ecosystems, 2nd edn, Barnaul, Altai State University Publishing House (in Russian)Google Scholar
  9. Kirsta YB, Lubenets LF, Chernykh DV (2011) Typological classification of landscapes for river flow estimation in Altai-Sayan mountainous country. Sustain Dev Mnt Territ 2(8):51–56 (in Russian)Google Scholar
  10. Kirsta YB, Puzanov AV, Lovtskaya OV, Lubenets LF, Kuznyak Ya E, Pakhotnova AY (2012) Simulation mathematical model of runoff for mid-size and small rivers in mountain territories. News Samara Sci Cent RAS 14(1):2334–2342.  https://doi.org/10.24412/Fd1kFw4CDjU (in Russian)Google Scholar
  11. Kirsta YB, Puzanov AV (2015) System-analytical modeling of mountain rivers runoff. In: Fundamental problems of water and water resources: Proceedings of IV Russian scientific conference. Moscow, Water Problems Institute RAS, pp 73–76 (in Russian)Google Scholar
  12. Kirsta YB, Puzanov AV (2016) Modeling of hydrochemical composition of mountain river runoff: 1. Runoff of nitrogen mineral forms. News Samara Sci Cent RAS 18(2):96–100 (in Russian)Google Scholar
  13. Koch·M, Cherie N (2013) SWAT-modeling of the impact of future climate change on the hydrology and the water resources in the upper blue Nile river basin, Ethiopia. In: Proceedings of the sixth international conference on water resources and environment research, ICWRER 2013. Germany, pp 428–523Google Scholar
  14. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulation. Trans ASABE 50(3):885–900CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yuri Kirsta
    • 1
    • 2
    Email author
  • Alexander Puzanov
    • 1
  • Tamara Rozhdestvenskaya
    • 1
  1. 1.Institute for Water and Environmental Problems of Siberian Branch, Russian Academy of SciencesBarnaulRussia
  2. 2.Altai State Technical UniversityBarnaulRussia

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