System-analytical simulation of the hydrochemical runoff of mountain rivers: case study of dissolved iron

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Abstract

A water balance simulation model of seasonal and long-term flow dynamics of total dissolved iron has been developed using the example of the middle-size and smaller rivers of the Altai–Sayan highland. Model input factors and input variables included monthly precipitation and average monthly air temperatures (normalized and spatially generalized according to the regional climate model), water flows calculated for individual river basins (according to a discharge model for mountain rivers), and cartographic information on river basins and arable land area. The sensitivity of the model to natural variations of input factors was determined as the contribution of a specific factor to the variance of the observed values of hydrochemical runoff. The calculated criteria RSR = 0.57 and Nash–Sutcliffe Efficiency NSE = 0.67 indicate the good quality of the model.

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About the authors

Yu. B. Kirsta

Institute for Water and Environmental Problems, Siberian Branch of the Russian Akademy of Sciences; Polzunov Altai State Technical University

Author for correspondence.
Email: kirsta@iwep.ru
Russian Federation, 1, Molodezhnaya street, Barnaul, 656038; 46, Lenin prospect, Barnaul, 656038

A. V. Puzanov

Institute for Water and Environmental Problems, Siberian Branch of the Russian Akademy of Sciences

Email: kirsta@iwep.ru
Russian Federation, 1, Molodezhnaya street, Barnaul, 656038

References

  1. Беручашвили Н.Л., Жучкова В.К. Методы комплексных физико-географических исследований. Учебник для вузов. М.: Изд-во Московского ун-та, 1997. 320 с.
  2. Кирста Ю.Б. Пространственное обобщение климатических характеристик для горных территорий // Мир науки, культуры, образования. 2011. № 3(28). С. 330–337.
  3. Кирста Ю.Б. Чувствительность моделей речного стока к факторам среды и ее количественная оценка // Изв. СамНЦ РАН. 2015. Т. 17. № 6. С. 97–103.
  4. Кирста Ю.Б., Кирста Б.Ю. Информационно-физический закон построения эволюционных систем. Системно-аналитическое моделирование экосистем. Барнаул: Изд-во АлтГТУ, 2014. 283 с.
  5. Кирста Ю.Б., Лубенец Л.Ф., Черных Д.В. Типизация ландшафтов для оценки речного стока в Алтае-Саянской горной стране // Устойчивое развитие горных территорий. 2011. № 2(8). С. 51–56.
  6. Кирста Ю.Б., Пузанов А.В., Ловцкая О.В., Лубенец Л.Ф. Универсальная математическая модель стока взвешенных веществ для бассейнов горных рек // Устойчивое развитие горных территорий. 2012. № 3–4 (13–14). С. 46–53.
  7. Кирста Ю.Б., Пузанов А.В., Ловцкая О.В., Лубенец Л.Ф., Кузняк Я.Э., Пахотнова А.Ю. Имитационная математическая модель стока средних и малых рек для горных территорий // Изв. СамНЦ РАН. 2012. Т. 14. № 1(9). С. 2334–2342.
  8. Перельман А.И., Касимов Н.С. Геохимия ландшафта: Учеб. пособие. М.: Астрея-2000, 1999. 764 с.
  9. РД 52.24.358-95. Руководящий документ. Методические указания. Методика выполнения измерений массовой концентрации железа общего в водах фотометрическим методом с 1,10-фенантролином. М.: Росгидромет, 1994.
  10. Савичев О.Г., Иванов А.О. Атмосферные выпадения в бассейне Средней Оби и их влияние на гидрохимический сток рек // Изв. РАН. Сер. геогр. 2010. № 1. С. 63–70.
  11. Черных Д.В. Пространственно-временная организация внутриконтинентальных горных ландшафтов (на примере Русского Алтая). Дис. … докт. географ. наук. Томск: ТГУ, 2012. 312 с.
  12. Beven K., Hall J. Applied Uncertainty Analysis for Flood Risk Management. London:I mperial College Press, 2013. 500 p.
  13. Iooss B., Lemaitre P. A review on global sensitivity analysis methods // Uncertainty management in Simulation-Optimization of Complex Systems: Algorithms and Applications / Eds. Meloni C., Dellino G. New York: Springer, 2015. 264 p.
  14. Kirsta Yu.B. System-analytical modelling – Pt. I: General principles and theoretically best accuracies of ecological models. Soil-moisture exchange in agroecosystems // Ecol. Modelling. 2006. V. 191. P. 315–330.
  15. Koch M., Cherie N. SWAT-modeling of the impact of future climate change on the hydrology and the water resources in the upper blue Nile river basin, Ethiopia // Proc. 6th Int. Conf. Water Resour. Environ. Res. ICWRER 2013. Koblenz, Germany, 2013. P. 428–523.
  16. Moriasi D.N., Arnold J.G., Van Liew M.W., Bingner R.L., Harmel R.D., Veith T.L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulation // Transactions of the ASABE. 2007. V. 50(3). P. 885–900.
  17. Neitsch S.L., Arnold J.G., Kiniry J.R., Williams J.R. Soil and Water Assessment Tool. Theoretical Documentation. Version 2009. Texas: Texas Water Resour. Inst., 2011. http://swat.tamu.edu/media/99192/swat2009-theory.pdf
  18. Renard B., Kavetski D., Kuczera G., Thyer M., Franks S.W. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors // Water Resour. Res. 2010. 46. W05521.doi: 10.1029/2009WR008328
  19. Skahill B.E. Practice driven and state-of-the-art methods to quantify hydrologic model uncertainty. ERDC/CHL CHETN-IV-87. Vicksburg, MS, U.S.: Army Engineer Res. Development Center, 2013. 19 p.
  20. Song X., Zhang J., Zhan C., Xuan Y., Ye M., Xu C. Global sensitivity analysis in hydrological modeling. Review of concepts, methods, theoretical framework, and applications // J. Hydrol. 2015. V. 523. P. 739–757.

Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. Map of the location of the 34 model river basins of the Altai-Sayan mountainous country.

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3. Fig. 2. Continuous piecewise linear function H (X1, X2, Y1, Y2, Z1, Z2, X) of three linear fragments with arbitrarily variable parameters (equation (1)).

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4. Fig. 3. A cross-section of the river basin and a scheme for determining its average transverse slope K i by the average height (h) and width (L).

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5. Fig. 4. Dependence of total dissolved iron runoff (g / s) on a hypothetically different transverse slope of the river basin and normalized to its mean multiyear value of precipitation for the upper reaches. Katun (section of Tungur): a - winter low water (precipitation in the months of the IX – XI of the previous year), b - spring-summer flood (precipitation in the months of the IV – VI current year), in - summer low water (precipitation in the months of VII – VIII ), d - autumnal low flow (precipitation for the months of IX – XI).

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