Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)

Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $....
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Autor*in:	Lupakov, S. Yu. [verfasserIn] Bugaets, A. N. Gonchukov, L. V. Sokolov, O. V. Bugaets, N. D.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Anmerkung:	© Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.

Übergeordnetes Werk:	Enthalten in: Water resources - Moscow : MAIK Nauka/Interperiodica Publ., 1974, 50(2023), 6 vom: 24. Nov., Seite 806-815
Übergeordnetes Werk:	volume:50 ; year:2023 ; number:6 ; day:24 ; month:11 ; pages:806-815

Links:	Volltext

DOI / URN:	10.1134/S0097807823700136

Katalog-ID:	SPR05385134X

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100	1		\|a Lupakov, S. Yu. \|e verfasserin \|4 aut
245	1	0	\|a Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
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500			\|a © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.
520			\|a Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models.
700	1		\|a Bugaets, A. N. \|4 aut
700	1		\|a Gonchukov, L. V. \|4 aut
700	1		\|a Sokolov, O. V. \|4 aut
700	1		\|a Bugaets, N. D. \|4 aut
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912			\|a GBV_USEFLAG_A
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912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4328
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
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allfields	10.1134/S0097807823700136 doi (DE-627)SPR05385134X (SPR)S0097807823700136-e DE-627 ger DE-627 rakwb eng Lupakov, S. Yu. verfasserin aut Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673. Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. Bugaets, A. N. aut Gonchukov, L. V. aut Sokolov, O. V. aut Bugaets, N. D. aut Enthalten in Water resources Moscow : MAIK Nauka/Interperiodica Publ., 1974 50(2023), 6 vom: 24. Nov., Seite 806-815 (DE-627)334716829 (DE-600)2058341-2 1608-344X nnns volume:50 year:2023 number:6 day:24 month:11 pages:806-815 https://dx.doi.org/10.1134/S0097807823700136 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 50 2023 6 24 11 806-815
spelling	10.1134/S0097807823700136 doi (DE-627)SPR05385134X (SPR)S0097807823700136-e DE-627 ger DE-627 rakwb eng Lupakov, S. Yu. verfasserin aut Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673. Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. Bugaets, A. N. aut Gonchukov, L. V. aut Sokolov, O. V. aut Bugaets, N. D. aut Enthalten in Water resources Moscow : MAIK Nauka/Interperiodica Publ., 1974 50(2023), 6 vom: 24. Nov., Seite 806-815 (DE-627)334716829 (DE-600)2058341-2 1608-344X nnns volume:50 year:2023 number:6 day:24 month:11 pages:806-815 https://dx.doi.org/10.1134/S0097807823700136 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 50 2023 6 24 11 806-815
allfields_unstemmed	10.1134/S0097807823700136 doi (DE-627)SPR05385134X (SPR)S0097807823700136-e DE-627 ger DE-627 rakwb eng Lupakov, S. Yu. verfasserin aut Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673. Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. Bugaets, A. N. aut Gonchukov, L. V. aut Sokolov, O. V. aut Bugaets, N. D. aut Enthalten in Water resources Moscow : MAIK Nauka/Interperiodica Publ., 1974 50(2023), 6 vom: 24. Nov., Seite 806-815 (DE-627)334716829 (DE-600)2058341-2 1608-344X nnns volume:50 year:2023 number:6 day:24 month:11 pages:806-815 https://dx.doi.org/10.1134/S0097807823700136 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 50 2023 6 24 11 806-815
allfieldsGer	10.1134/S0097807823700136 doi (DE-627)SPR05385134X (SPR)S0097807823700136-e DE-627 ger DE-627 rakwb eng Lupakov, S. Yu. verfasserin aut Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673. Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. Bugaets, A. N. aut Gonchukov, L. V. aut Sokolov, O. V. aut Bugaets, N. D. aut Enthalten in Water resources Moscow : MAIK Nauka/Interperiodica Publ., 1974 50(2023), 6 vom: 24. Nov., Seite 806-815 (DE-627)334716829 (DE-600)2058341-2 1608-344X nnns volume:50 year:2023 number:6 day:24 month:11 pages:806-815 https://dx.doi.org/10.1134/S0097807823700136 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 50 2023 6 24 11 806-815
allfieldsSound	10.1134/S0097807823700136 doi (DE-627)SPR05385134X (SPR)S0097807823700136-e DE-627 ger DE-627 rakwb eng Lupakov, S. Yu. verfasserin aut Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673. Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. Bugaets, A. N. aut Gonchukov, L. V. aut Sokolov, O. V. aut Bugaets, N. D. aut Enthalten in Water resources Moscow : MAIK Nauka/Interperiodica Publ., 1974 50(2023), 6 vom: 24. Nov., Seite 806-815 (DE-627)334716829 (DE-600)2058341-2 1608-344X nnns volume:50 year:2023 number:6 day:24 month:11 pages:806-815 https://dx.doi.org/10.1134/S0097807823700136 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 50 2023 6 24 11 806-815
language	English
source	Enthalten in Water resources 50(2023), 6 vom: 24. Nov., Seite 806-815 volume:50 year:2023 number:6 day:24 month:11 pages:806-815
sourceStr	Enthalten in Water resources 50(2023), 6 vom: 24. Nov., Seite 806-815 volume:50 year:2023 number:6 day:24 month:11 pages:806-815
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container_title	Water resources
authorswithroles_txt_mv	Lupakov, S. Yu. @@aut@@ Bugaets, A. N. @@aut@@ Gonchukov, L. V. @@aut@@ Sokolov, O. V. @@aut@@ Bugaets, N. D. @@aut@@
publishDateDaySort_date	2023-11-24T00:00:00Z
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author	Lupakov, S. Yu.
spellingShingle	Lupakov, S. Yu. Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
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topic_title	Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
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title	Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
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title_full	Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
author_sort	Lupakov, S. Yu.
journal	Water resources
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author_browse	Lupakov, S. Yu. Bugaets, A. N. Gonchukov, L. V. Sokolov, O. V. Bugaets, N. D.
container_volume	50
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author-letter	Lupakov, S. Yu.
doi_str_mv	10.1134/S0097807823700136
title_sort	comparison of runoff components, water balance, and the parameters of conceptual models hbv and gr4j: case study of the upper ussuri basin (south of primorsky region, pacific russia)
title_auth	Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
abstract	Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.
abstractGer	Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.
abstract_unstemmed	Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models. © Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.
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container_issue	6
title_short	Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)
url	https://dx.doi.org/10.1134/S0097807823700136
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up_date	2024-07-03T22:28:10.093Z
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Yu.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Pleiades Publishing, Ltd. 2023. ISSN 0097-8078, Water Resources, 2023, Vol. 50, No. 6, pp. 806–815. © Pleiades Publishing, Ltd., 2023. Russian Text © The Author(s), 2023, published in Vodnye Resursy, 2023, Vol. 50, No. 6, pp. 664–673.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The efficiency of runoff simulation, the values of parameters, and the dynamics of the estimated runoff components were analyzed for two conceptual hydrological models GR4J and HBV for 17 watersheds in the Upper Ussuri River (Primorsky Krai, Russia) with areas from 138 to 24 400 $ km^{2} $. Both models demonstrate an increase in the simulation efficiency (based on NSE criterion) with an increase in the catchment area up to 1–2 thousand $ km^{2} $, after which they stabilize within the interval of 0.75–0.85 for the calibration period and 0.70–0.80 for the verification period. The estimates obtained for the HBV model were 5–10% higher than those for the GR4J model. Analysis of the measured and calculated annual runoff maximums over the warm season suggests the conclusion that GR4J model is on the average 5–6% more efficient than the HBV model in calculating the maximal values of rain flood discharges. At the same time, the obtained values of the relative error BIAS demonstrate a more accurate reproduction of the annual average runoff by the HBV model. The main distinctions determining the efficiency of simulation in the study region are as follows: the method of considering the precipitation height increments within altitude belts, the specific features of the calculation of model evapotranspiration, the method for calculating the outflow from conceptual runoff-forming storages in the GR4J and HBV models.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bugaets, A. N.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gonchukov, L. 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Comparison of Runoff Components, Water Balance, and the Parameters of Conceptual Models HBV and GR4J: Case Study of the Upper Ussuri Basin (South of Primorsky Region, Pacific Russia)

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