Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR022555 |
Development of Multivariable Dynamic System Response Curve Method for Real-Time Flood Forecasting Correction | |
Sun, Y.1; Bao, W.1; Jiang, P.2; Ji, X.3; Gao, S.3; Xu, Y.4; Zhang, Q.5; Si, W.1 | |
2018-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:7页码:4730-4749 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA |
英文摘要 | Error correction method is widely used to improve the performance of flood forecasting. The Dynamic System Response Curve method (DSRC) has been proposed as an error correction method to improve the performance of hydrological modeling. One of the critical problems is the unstable performance caused by the ill-posed property of the model structure and the inability of estimating multiple variables. To address this problem, the original structure of DSRC was modified to enable the capability of estimating multiple variables. Using the variable forgetting factor recursive least squares algorithm (VFF-RLS), we proposed an improved version of DSRC (VFF-RLS-MDSRC). The proposed method was tested in a synthetic case to examine the ability to correct state variables of a hydrological model. In addition, it was compared with the autoregressive technique in a real case study to evaluate the effects on the improvement of model performance. The results of the synthetic study indicate that the proposed method can significantly improve the performance of both the model output and the state variables. The results of the real case study indicate that the performance obtained by the proposed method tends to have a slower decline trend when increasing the lead time compared with autoregressive technique. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000442502100031 |
WOS关键词 | VARIABLE FORGETTING FACTOR ; RECURSIVE LEAST-SQUARES ; RAINFALL-RUNOFF MODELS ; ILL-POSED PROBLEMS ; XINANJIANG MODEL ; HYDROLOGIC MODEL ; NEURAL-NETWORK ; UNCERTAINTY ASSESSMENT ; GENETIC ALGORITHM ; RLS ALGORITHM |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/22018 |
专题 | 资源环境科学 |
作者单位 | 1.Hohai Univ, Coll Hydrol & Water Resources, Nanjing, Jiangsu, Peoples R China; 2.Desert Res Inst, Div Hydrol Sci, Las Vegas, NV 89119 USA; 3.Liaoning Adm Hydrol & Water Resources Invest, Shenyang, Liaoning, Peoples R China; 4.Liaoning Adm Chaihe Reservoir, Tieling, Peoples R China; 5.Bei Fang Invest Design & Res Co LTD, Tianjin, Peoples R China |
推荐引用方式 GB/T 7714 | Sun, Y.,Bao, W.,Jiang, P.,et al. Development of Multivariable Dynamic System Response Curve Method for Real-Time Flood Forecasting Correction[J]. WATER RESOURCES RESEARCH,2018,54(7):4730-4749. |
APA | Sun, Y..,Bao, W..,Jiang, P..,Ji, X..,Gao, S..,...&Si, W..(2018).Development of Multivariable Dynamic System Response Curve Method for Real-Time Flood Forecasting Correction.WATER RESOURCES RESEARCH,54(7),4730-4749. |
MLA | Sun, Y.,et al."Development of Multivariable Dynamic System Response Curve Method for Real-Time Flood Forecasting Correction".WATER RESOURCES RESEARCH 54.7(2018):4730-4749. |
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