Multi-Objective Validation of the Runoff Formation Model in the High-Mountain River Basin of the Central Caucasus
https://doi.org/10.24057/2071-9388-2025-3887
Abstract
This study demonstrates the effectiveness of a multi-objective validation approach for a distributed hydrological model in a high mountain river basin. Focusing on the Baksan River Basin in the Central Caucasus, where snow and glacier melt play a crucial role in runoff formation, we applied the ECOMAG model, which has proven its reliability in high-altitude hydrology. To enhance the validation accuracy, we integrated diverse data sources, including observed river discharge, MODISderived snow cover, stable isotope hydrograph separation, glacier mass balance observations, and glacial runoff simulations from the A-Melt model. The results confirm the high performance of the model across multiple hydrological components. The simulated and observed discharge values showed strong agreement, with the Nash-Sutcliffe efficiency exceeding 0.8 for both the calibration and validation periods. The model successfully captured seasonal snow cover variations, achieving an R² of 0.85 when compared with the MODIS data. Isotopic hydrograph separation further validated the accuracy of the simulated meltwater and rainfall contributions to runoff. Although glacier ablation simulations showed some deviations, particularly for the Djankuat Glacier, these findings highlight opportunities for refining glacial process representation. Overall, this study confirms the robustness and applicability of multi-objective validation for hydrological modeling in complex mountainous regions. The integration of multiple observational datasets significantly enhances the reliability of modeling results, providing valuable insights into water resource management, climate impact assessments, and sustainable development in glacier-fed river basins.
Keywords
mountain hydrology,
runoff formation modeling,
mountainous regions,
glacier modeling,
Central Caucasus,
A-melt,
ECOMAG
Supporting agencies: The study was carried out under the Governmental Order to Water Problems Institute, Russian Academy of Sciences, subject no. FMWZ-2025-0003 (ECOMAG model adaptation and calibration), under the state assignment of the Research Laboratory of Soil Erosion and Fluvial Processes, Faculty of Geography, Lomonosov Moscow State University (CITIS 121051100166-4 (results analysis), 121051400038-1 (snow cover data analysis)), and under the Russian Science Foundation Grant No. 23-17-00247 «Development of parameterization of mountain glaciers for Earth system models» (A-Melt modeling).
About the Authors
Ekaterina D. Pavlyukevich
Lomonosov Moscow State University ; Water Problems Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
119991, Moscow
119333, Moscow
Nelly E. Elagina
Institute of Geography of the Russian Academy of Sciences
Russian Federation
Russian Federation
119017, Moscow
Inna N. Krylenko
Lomonosov Moscow State University ; Water Problems Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
119991, Moscow
119333, Moscow
Ekaterina P. Rets
Water Problems Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
119333, Moscow
Abror A. Gafurov
German Research Centre for Geoscience,
Germany
Germany
Telegrafenberg, 14473, Potsdam
Yuri G. Motovilov
Water Problems Institute of the Russian Academy of Sciences
Russian Federation
Russian Federation
119333, Moscow
References
1. Addor N., Rössler O., Köplin N., Huss M., Weingartner R. and Seibert J. (2014). Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments. Water Resources Research, 50(10), 7541-7562, DOI: 10.1002/2014WR015549.
2. Ala-Aho P., Tetzlaff D., McNamara J.P., Laudon H. and Soulsby C. (2017). Using isotopes to constrain water flux and age estimates in snowinfluenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall-Runoff ) model. Hydrology and Earth System Sciences, 21(10), DOI: 10.5194/hess-21-5089-2017.
3. Bai P., Liu X. and Liu C. (2018). Improving hydrological simulations by incorporating GRACE data for model calibration. Journal of Hydrology, 557, DOI: 10.1016/j.jhydrol.2017.12.025.
4. Dozier J., Bair E.H. and Davis R.E. (2016). Estimating the spatial distribution of snow water equivalent in the world’s mountains. WIREs Water, 3(3), 461-474, DOI: 10.1002/wat2.1140.
5. Duethmann D., Peters J., Blume T., Vorogushyn S. and Güntner A. (2014). The value of satellite-derived snow cover images for calibrating a hydrological model in snow-dominated catchments in Central Asia. Water Resources Research, 50(3), 2002-2021, DOI: 10.1002/2013WR014382.
6. Efstratiadis A. and Koutsoyiannis D. (2010). One decade of multi-objective calibration approaches in hydrological modelling: a review. Hydrological Sciences Journal, 55(1), DOI: 10.1080/02626660903526292.
7. Eis J., Van der Laan L., Maussion F. and Marzeion B. (2021). Reconstruction of Past Glacier Changes with an Ice-Flow Glacier Model: Proof of Concept and Validation. Frontiers in Earth Science, 9, DOI: 10.3389/feart.2021.595755.
8. Elagina N., Kutuzov S., Rets E., Smirnov A., Chernov R., Lavrentiev I. and Mavlyudov B. (2021). Mass Balance of Austre Grønfjordbreen, Svalbard, 2006–2020, Estimated by Glaciological, Geodetic and Modeling Aproaches. Geosciences, 11(2), 78, DOI: 10.3390/geosciences11020078.
9. Elagina N.E., Rets E.P., Korneva I.A. and Lavrentiev I.I. (2025). Simulation of mass balance and glacial runoff of Mount Elbrus from 1984 to 2022. Proceedings of the national open conference State of Mountain Glaciers in the Context of Modern Climate Change, 26-27 (in Russian).
10. Etter S., Addor N., Huss M. and Finger D. (2017). Climate change impacts on future snow, ice and rain runoff in a Swiss mountain catchment using multi-dataset calibration. Journal of Hydrology: Regional Studies, 13, 222-239, DOI: 10.1016/j.ejrh.2017.08.005.
11. Finger D., Vis M., Huss M. and Seibert J. (2015). The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments. Water Resources Research, 51(4), 1939-1958, DOI: 10.1002/2014WR015712.
12. Fyffe C.L., Potter E., Fugger S., Orr A., Fatichi S., Loarte E., Medina K., Hellström R., Bernat M., Aubry-Wake C., Gurgiser W., Perry L.B., Suarez W., Quincey D.J. and Pellicciotti F. (2021). The Energy and Mass Balance of Peruvian Glaciers. Journal of Geophysical Research: Atmospheres, 126(23), 1-22, DOI: 10.1029/2021JD034911.
13. Gabbi J., Carenzo M., Pellicciotti F., Bauder A. and Funk M. (2014). A comparison of empirical and physically based glacier surface melt models for long-term simulations of glacier response. Journal of Glaciology, 60(224), 1140-1154, DOI: 10.3189/2014JoG14J011.
14. Gelfan A., Gustafsson D., Motovilov Y., Arheimer B., Kalugin A., Krylenko I. and Lavrenov A. (2017). Climate change impact on the water regime of two great Arctic rivers: modeling and uncertainty issues. Climatic Change, 141(3), 499-515, DOI: 10.1007/s10584-016-1710-5.
15. Han P., Long D., Han Z., Du M., Dai L. and Hao X. (2019). Improved understanding of snowmelt runoff from the headwaters of China’s Yangtze River using remotely sensed snow products and hydrological modeling. Remote Sensing of Environment, 224, DOI: 10.1016/j.rse.2019.01.041.
16. Hersbach H., Bell B., Berrisford P., Hirahara S., Horányi A., Muñoz-Sabater J., Nicolas J., Peubey C., Radu R., Schepers D., Simmons A., Soci C., Abdalla S., Abellan X., Balsamo G., Bechtold P., Biavati G., Bidlot J., Bonavita M., Thépaut J. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049, DOI: 10.1002/qj.3803.
17. Hock R. (2003). Temperature index melt modelling in mountain areas. Journal of Hydrology, 282, 104-115, DOI: 10.1016/S0022-1694(03)00257-9.
18. Hoeg S., Uhlenbrook S. and Leibundgut C. (2000). Hydrograph separation in a mountainous catchment - combining hydrochemical and isotopic tracers. Hydrological Processes, 14(7), DOI: 10.1002/(SICI)1099-1085(200005)14:7<1199::AID-HYP35>3.0.CO;2-K.
19. Holmes T., Stadnyk T.A., Kim S.J. and Asadzadeh M. (2020). Regional Calibration With Isotope Tracers Using a Spatially Distributed Model: A Comparison of Methods. Water Resources Research, 56(9), DOI: 10.1029/2020WR027447.
20. Holmes T.L., Stadnyk T.A., Asadzadeh M. and Gibson J.J. (2023). Guidance on large scale hydrologic model calibration with isotope tracers. Journal of Hydrology, 621(12), 129604, DOI: 10.1016/j.jhydrol.2023.129604.
21. Horton P., Schaefli B., Mezghani A., Hingray B. and Musy A. (2006). Assessment of climate-change impacts on alpine discharge regimes with climate model uncertainty. Hydrological Processes, 20(10), 2091-2109, DOI: 10.1002/hyp.6197.
22. Immerzeel W.W. and Droogers P. (2008). Calibration of a distributed hydrological model based on satellite evapotranspiration. Journal of Hydrology, 349(3-4), DOI: 10.1016/j.jhydrol.2007.11.017.
23. Justice C.O., Townshend J.R.G., Vermote E.F., Masuoka E., Wolfe R.E., Saleous N., Roy D.P. and Morisette J.T. (2002). An overview of MODIS Land data processing and product status. Remote Sensing of Environment, 83(1-2), DOI: 10.1016/S0034-4257(02)00084-6.
24. Kinnard C., Larouche O., Demuth M. and Menounos B. (2022). Mass balance modelling and climate sensitivity of Saskatchewan Glacier, western Canada. The Cryosphere Discussions, 16(8), 3071-3099, DOI: https://doi.org/10.5194/tc-16-3071-2022.
25. Kornilova E. D., Krylenko I.N., Rets E.P., Motovilov Y.G., Korneva I.A., Postnikova T.N. and Rybak O.O. (2024). Changes in water regime in the high-mountain region of the Terek River (North Caucasus) in connection with climate change and degradation of glaciation. Ice and Snow, 64(2), 173-188 (in Russian with English summary), DOI: 10.31857/S2076673424020014.
26. Kornilova E., Krylenko I., Rets E., Motovilov Y., Atabieva F. and Kuchmenova I. (2023). Simulating Runoff Regime in a Glaciated HighMountainous Basin: A Case Study of the Baksan River (Caucasus, Russia). Water Resources, 50, 569-576, DOI: 10.1134/S0097807823040140.
27. Kornilova E.D., Krylenko I.N., Rets E.P., Motovilov Y.G., Bogachenko E.M., Krylenko I.V. and Petrakov D.A. (2021). Modeling of Extreme Hydrological Events in the Baksan River Basin, the Central Caucasus, Russia. Hydrology, 8(1), DOI: 10.3390/hydrology8010024.
28. Kutuzov S., Lavrentiev I., Smirnov A., Nosenko G. and Petrakov D. (2019). Volume Changes of Elbrus Glaciers From 1997 to 2017. Frontiers in Earth Science, 7, 153, DOI: 10.3389/feart.2019.00153.
29. Lettenmaier D.P., Alsdorf D., Dozier J., Huffman G.J., Pan M. and Wood E.F. (2015). Inroads of remote sensing into hydrologic science during the WRR era. Water Resources Research, 51(9), 7309-7342, DOI: 10.1002/2015WR017616.
30. Li X., Wang N. and Wu Y. (2022). Automated Glacier Snow Line Altitude Calculation Method Using Landsat Series Images in the Google Earth Engine Platform. Remote Sensing, 14(10), 2377, DOI: 10.3390/rs14102377.
31. Li Y., Grimaldi S., Pauwels V.R.N. and Walker J.P. (2018). Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: The impact on predictions at gauged and ungauged locations. Journal of Hydrology, 557, DOI: 10.1016/j.jhydrol.2018.01.013.
32. Lisina A.A., Krylenko I.N., Kalugin A.S., Motovilov Y.G., Sazonov A.A. and Frolova N.L. (2023). Assessment of the Kolyma Runoff under Current Climate Changes. Water Resources, 50, 318-322, DOI: 10.1134/S0097807823700513.
33. Mikhalenko V.N., Kutuzov S.S., Lavrentiev I.I., Toropov P.A., Abramov A.A., Aleshina M.A., Gagarina L.V., Doroshina G.Y., Guinot P., Kozachek A.V., Legrand M., Lim S., Nagornov O.V., Nosenko G.A., Polukhov A.A., Potemkin A.D., Preunkert S., Rototaeva O.V., Smirnov A.M., Yarinich Y.. (2020). Glaciers and climate of Elbrus. 1st ed. St. Petersburg, Russia: Nestor-Istoriya Publisher. (in Russian)
34. Motovilov Y.G. (1999). Validation of a distributed hydrological model against spatial observations. Agricultural and Forest Meteorology, 96, 257–277.
35. Motovilov Y.G. and Gelfan A.N. (2018). Models of flow formation in river basin hydrology. Moscow, Russia: Publisher of the Russian Academy of Sciences (in Russian), DOI: 10.31857/S9785907036222000001.
36. Motovilov Y. G., Kalugin A.S. and Gelfan A.N. (2017). An ECOMAG-based Regional Hydrological Model for the Mackenzie River basin. EGU General Assembly Conference Abstracts, 8064.
37. Motovilov Yury G. and Fashchevskaya T.B. (2019). Simulation of spatially-distributed copper pollution in a large river basin using the ECOMAG-HM model. Hydrological Sciences Journal, 64(6), 739-756, DOI: 10.1080/02626667.2019.1596273.
38. Oshun J., Dietrich W.E., Dawson T.E. and Fung I. (2016). Dynamic, structured heterogeneity of water isotopes inside hillslopes. Water Resources Research, 52(1), 164-189, DOI: 10.1002/2015WR017485.
39. Parajka J., Naeimi V., Blöschl G. and Komma J. (2009). Matching ERS scatterometer based soil moisture patterns with simulations of a conceptual dual layer hydrologic model over Austria. Hydrology and Earth System Sciences, 13(2), DOI: 10.5194/hess-13-259-2009.
40. Poméon T., Diekkrüger B., Springer A., Kusche J. and Eicker A. (2018). Multi-Objective Validation of SWAT for Sparsely-Gauged West African River Basins—A Remote Sensing Approach. Water, 10(4), 451, DOI: 10.3390/w10040451.
41. Popovnin V., Gubanov A., Lisak V. and Toropov P. (2024). Recent Mass Balance Anomalies on the Djankuat Glacier, Northern Caucasus. Atmosphere, 15, 107, DOI: 10.3390/atmos15010107.
42. Rets E., Khomiakova V., Kornilova E., Ekaykin A., Kozachek A. and Mikhalenko V. (2024). How and when glacial runoff is important: Tracing dynamics of meltwater and rainfall contribution to river runoff from headwaters to lowland in the Caucasus Mountains. Science of The Total Environment, 927, 172201, DOI: 10.1016/j.scitotenv.2024.172201.
43. Rets E.P., Frolova N.L. and Popovnin V. V. (2011). Simulation of melting of a mountain glacier surface. Ice and Snow, 4, 24–31. (in Russian)
44. Rets E.P., Petrakov D.A., Belozerov E. V. and Shpuntova A.M. (2021). Mass balance modelling for the sary-tor glacier (The Ak-Shyirak massif, Inner Tien Shan). Earth’s Cryosphere, 25(5), DOI: 10.15372/KZ20210504.
45. Reveillet M., Six D., Vincent C., Rabatel A., Dumont M., Lafaysse M., Morin S., Vionnet V. and Litt M. (2018). Relative performance of empirical and physical models in assessing seasonal and annual glacier surface mass balance of Saint-Sorlin Glacier (French Alps). The Cryosphere, 12, 1367-1386, DOI: 10.5194/tc-12-1367-2018.
46. RGI Consortium. (2017). Randolph Glacier Inventory - A Dataset of Global Glacier Outlines. (NSIDC-0770, Version 6). National Snow and Ice Data Center. Available at: https://nsidc.org/data/nsidc-0770/versions/6 [Accessed 20 July 2024], DOI: 10.7265/4m1f-gd79.
47. Rototaeva O.V., Nosenko G.A., Kerimov A.M., Kutuzov S.S., Lavrentiev I.I., Kerimov A.A., Nikitin S.A. and Tarasova L.N. (2019). Changes in the mass balance of the Garabashi glacier (Mt. Elbrus) at the turn of the XX-XXI centuries. Ice and Snow, 59(1), 5-22 (in Russian with English summary), DOI: 10.15356/2076-6734-2019-1-5-22.
48. Sakai A. and Fujita K. (2017). Contrasting glacier responses to recent climate change in high-mountain Asia. Scientific Reports, 7(1), 1-8, DOI: 10.1038/s41598-017-14256-5.
49. Schaefli B., Hingray B., Niggli M. and Musy A. (2005). Hydrology and Earth System Sciences A conceptual glacio-hydrological model for high mountainous catchments. Hydrology and Earth System Sciences, 9, 95-109.
50. Shannon S., Smith R., Wiltshire A., Payne T., Huss M., Betts R., Caesar J., Koutroulis A., Jones D. and Harrison S. (2019). Global glacier volume projections under high-end climate change scenarios. Cryosphere, 13(1), 325-350, DOI: 10.5194/tc-13-325-2019.
51. Tong R., Parajka J., Salentinig A., Pfeil I., Komma J., Széles B., Kubáň M., Valent P., Vreugdenhil M., Wagner W. and Blöschl G. (2021). The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model. Hydrology and Earth System Sciences, 25(3), 1389-1410, DOI: 10.5194/hess-25-1389-2021.
52. Toropov P.A., Shestakova A.A., Yarinich Y.I. and Kutuzov S.S. (2023). Modeling Orographic Precipitation Using the Example of Elbrus. Izvestiya, Atmospheric and Oceanic Physics, 59(S1), S8-S22, DOI: 10.1134/S0001433823130108.
53. Trautmann T., Koirala S., Carvalhais N., Eicker A., Fink M., Niemann C. and Jung M. (2018). Understanding terrestrial water storage variations in northern latitudes across scales. Hydrology and Earth System Sciences, 22(7), DOI: 10.5194/hess-22-4061-2018.
54. Treichler D. and Kääb A. (2017). Snow depth from ICESat laser altimetry — A test study in southern Norway. Remote Sensing of Environment, 191, 389-401, DOI: 10.1016/j.rse.2017.01.022.
55. Udnæs H.-C., Alfnes E. and Andreassen L.M. (2007). Improving runoff modelling using satellite-derived snow covered area? Hydrology Research, 38(1), 21-32, DOI: 10.2166/nh.2007.032.
56. Van Pelt W., Pohjola V., Pettersson R., Marchenko S., Kohler J., Luks B., Hagen J.O., Schuler T. V., Dunse T., Noël B. and Reijmer C. (2019). A long-term dataset of climatic mass balance, snow conditions and runoff in Svalbard (1957-2018). The Cryosphere Discussions, 13(9), 2259- 2280, DOI: 10.5194/tc-2019-53.
57. Vasil’chuk Y.K., Rets E.P., Chizhova J.N., Tokarev I. V., Frolova N.L., Budantseva N.A., Kireeva M.B. and Loshakova N.A. (2016). Hydrograph separation of the Dzhankuat River, North Caucasus, with the use of isotope methods. Water Resources, 43(6), 847-861, DOI: 10.1134/S0097807816060087.
58. Wanders N., Bierkens M.F.P., de Jong S.M., de Roo A. and Karssenberg D. (2014). The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models. Water Resources Research, 50(8), 6874-6891, DOI: 10.1002/2013WR014639.
59. Zemp M., Frey H., Gärtner-Roer I., Nussbaumer S.U., Hoelzle M., Paul F., Haeberli W., Denzinger F., Ahlstrøm A.P., Anderson B., Bajracharya S., Baroni C., Braun L.N., Càceres B.E., Casassa G., Cobos G., Dàvila L.R., Delgado Granados H., Demuth M.N., Vincent C. (2015). Historically unprecedented global glacier decline in the early 21st century. Journal of Glaciology, 61(228), 745-762, DOI: 10.3189/2015JoG15J017.
60. Zhang Y., Chiew F.H.S., Zhang L. and Li H. (2009). Use of remotely sensed actual evapotranspiration to improve rainfall-runoff modeling in Southeast Australia. Journal of Hydrometeorology, 10(4), DOI: 10.1175/2009JHM1061.1.
61. Zolotarev E.A. and Kharkovets E.G. (2000). Glaciation of Elbrus in the end of XX century (digital orthophoto map of Elbrus for 1997). Materialy Glyatsiologicheskikh Issledovaniy. Data of Glaciological Studies, 89, 175-181.
Review
For citations:
Pavlyukevich E.D., Elagina N.E., Krylenko I.N., Rets E.P., Gafurov A.A., Motovilov Yu.G. Multi-Objective Validation of the Runoff Formation Model in the High-Mountain River Basin of the Central Caucasus. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2025;18(2):189-200. https://doi.org/10.24057/2071-9388-2025-3887
Views:
7
Email this article 