A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions

Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is oft...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Zeng, Lan [verfasserIn] Chu, Xuefeng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Hydrologic model Depressions Variable contributing area Overland flow Probability distribution

Übergeordnetes Werk:	Enthalten in: Journal of hydrology - Amsterdam [u.a.] : Elsevier, 1963, 602
Übergeordnetes Werk:	volume:602

DOI / URN:	10.1016/j.jhydrol.2021.126762

Katalog-ID:	ELV006787789

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520			\|a Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes.
650		4	\|a Hydrologic model
650		4	\|a Depressions
650		4	\|a Variable contributing area
650		4	\|a Overland flow
650		4	\|a Probability distribution
700	1		\|a Chu, Xuefeng \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Journal of hydrology \|d Amsterdam [u.a.] : Elsevier, 1963 \|g 602 \|h Online-Ressource \|w (DE-627)268761817 \|w (DE-600)1473173-3 \|w (DE-576)077610628 \|x 1879-2707 \|7 nnns
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912			\|a GBV_ILN_69
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912			\|a GBV_ILN_74
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936	b	k	\|a 38.85 \|j Hydrologie: Allgemeines \|q VZ
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Indexfelder

author_variant	l z lz x c xc
matchkey_str	article:18792707:2021----::nwrbbltebdemdlosmltnvralcnrbtnaesnhdooipoes
hierarchy_sort_str	2021
bklnumber	38.85
publishDate	2021
allfields	10.1016/j.jhydrol.2021.126762 doi (DE-627)ELV006787789 (ELSEVIER)S0022-1694(21)00812-X DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Zeng, Lan verfasserin aut A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes. Hydrologic model Depressions Variable contributing area Overland flow Probability distribution Chu, Xuefeng verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 602 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:602 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines VZ AR 602
spelling	10.1016/j.jhydrol.2021.126762 doi (DE-627)ELV006787789 (ELSEVIER)S0022-1694(21)00812-X DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Zeng, Lan verfasserin aut A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes. Hydrologic model Depressions Variable contributing area Overland flow Probability distribution Chu, Xuefeng verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 602 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:602 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines VZ AR 602
allfields_unstemmed	10.1016/j.jhydrol.2021.126762 doi (DE-627)ELV006787789 (ELSEVIER)S0022-1694(21)00812-X DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Zeng, Lan verfasserin aut A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes. Hydrologic model Depressions Variable contributing area Overland flow Probability distribution Chu, Xuefeng verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 602 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:602 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines VZ AR 602
allfieldsGer	10.1016/j.jhydrol.2021.126762 doi (DE-627)ELV006787789 (ELSEVIER)S0022-1694(21)00812-X DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Zeng, Lan verfasserin aut A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes. Hydrologic model Depressions Variable contributing area Overland flow Probability distribution Chu, Xuefeng verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 602 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:602 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines VZ AR 602
allfieldsSound	10.1016/j.jhydrol.2021.126762 doi (DE-627)ELV006787789 (ELSEVIER)S0022-1694(21)00812-X DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Zeng, Lan verfasserin aut A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes. Hydrologic model Depressions Variable contributing area Overland flow Probability distribution Chu, Xuefeng verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 602 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:602 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines VZ AR 602
language	English
source	Enthalten in Journal of hydrology 602 volume:602
sourceStr	Enthalten in Journal of hydrology 602 volume:602
format_phy_str_mv	Article
bklname	Hydrologie: Allgemeines
institution	findex.gbv.de
topic_facet	Hydrologic model Depressions Variable contributing area Overland flow Probability distribution
dewey-raw	690
isfreeaccess_bool	false
container_title	Journal of hydrology
authorswithroles_txt_mv	Zeng, Lan @@aut@@ Chu, Xuefeng @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	268761817
dewey-sort	3690
id	ELV006787789
language_de	englisch
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author	Zeng, Lan
spellingShingle	Zeng, Lan ddc 690 bkl 38.85 misc Hydrologic model misc Depressions misc Variable contributing area misc Overland flow misc Probability distribution A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
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topic_title	690 VZ 38.85 bkl A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions Hydrologic model Depressions Variable contributing area Overland flow Probability distribution
topic	ddc 690 bkl 38.85 misc Hydrologic model misc Depressions misc Variable contributing area misc Overland flow misc Probability distribution
topic_unstemmed	ddc 690 bkl 38.85 misc Hydrologic model misc Depressions misc Variable contributing area misc Overland flow misc Probability distribution
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title	A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
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title_full	A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
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title_sort	a new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
title_auth	A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
abstract	Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes.
abstractGer	Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes.
abstract_unstemmed	Surface depressions play an important role in overland flow generation, infiltration, and other hydrologic processes. They undergo filling, spilling, and merging during rainfall/snowmelt events, affecting hydrologic connectivity and the size of the contributing area. However, such variability is often ignored or oversimplified in traditional hydrologic models. Consequently, they fail to simulate the threshold-controlled overland flow dynamics. The goal of this study is to improve hydrologic modeling, especially for depression-dominated areas, by capturing the variable contributing area and the threshold behavior of overland flow. To achieve this goal, a new depression-oriented variable contributing area (D-VCA) model is developed to simulate the contributing area, runoff dynamics, and their likelihood of occurrence. Specifically, the D-VCA model integrates the simulation of hydrologic processes with a surface topographic analysis procedure, which is able to (1) determine the probability distribution functions of depression storage and the corresponding contributing area and (2) examine the intrinsic changing patterns of depression storage and contributing area. The model was applied to a depression-dominated watershed in North Dakota and its performance was evaluated by comparing the simulated and observed discharges at two USGS gaging stations. The improved performance of the D-VCA model was demonstrated by comparing different modeling methods including the widely-used lumped depression approach. Modeling results demonstrated the unique capabilities of the D-VCA model in simulating depression-influenced overland flow dynamics and the associated threshold behavior. The new model also provides an improved understanding of the evolution of contributing areas and their influence on overland flow generation across different topographic landscapes.
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title_short	A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions
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doi_str	10.1016/j.jhydrol.2021.126762
up_date	2024-07-06T22:33:52.553Z
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A new probability-embodied model for simulating variable contributing areas and hydrologic processes dominated by surface depressions

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