Adjustment to the curve number (NRCS-CN) to account for the vegetation effect on hydrological processes
被引:19
作者:
Gonzalez, Alvaro
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机构:
CUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
CUNY City Coll, CUNY CREST Inst, New York, NY 10017 USACUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
Gonzalez, Alvaro
[1
,2
]
Temimi, Marouane
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机构:
CUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
CUNY City Coll, CUNY CREST Inst, New York, NY 10017 USA
Masdar Inst Sci & Technol, Inst Ctr Water & Environm iWater, Abu Dhabi, U Arab EmiratesCUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
Temimi, Marouane
[1
,2
,3
]
Khanbilvardi, Reza
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机构:
CUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
CUNY City Coll, CUNY CREST Inst, New York, NY 10017 USACUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
Khanbilvardi, Reza
[1
,2
]
机构:
[1] CUNY City Coll, Dept Civil Engn, New York, NY 10017 USA
[2] CUNY City Coll, CUNY CREST Inst, New York, NY 10017 USA
[3] Masdar Inst Sci & Technol, Inst Ctr Water & Environm iWater, Abu Dhabi, U Arab Emirates
This work proposes an approach to automatically adjust the curve number (CN) to account for changes in vegetation density. Precipitation-runoff pairs from the MOdel Parameter Estimation EXperiment (MOPEX) dataset were used to estimate monthly simulated CNs (CNsim). Remotely sensed greenness fraction (GF) was used as a proxy for vegetation density. A relationship was established between CNsim and GF values, and an adjustment factor was introduced. The coefficients of determination (R-2) between the simulated and observed runoff when using the unadjusted and adjusted CNs were 0.63 and 0.80, respectively. Likewise, Nash-Sutcliffe coefficients of -0.17 and 0.67, and root mean square error (RMSE) of 5.22 and 2.75 were also obtained for the unadjusted and adjusted CNs, respectively. The results demonstrate how the adjustments compensate for the runoff overestimation when the standard CN (CNstd) is used, and also imply that the adjustment is crucial for improved hydrological modelling, particularly, for flood and flash flood monitoring and forecasting. [GRAPHICS] Editor Z.W. Kundzewicz