Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3359-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-3359-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Jul 2017
Research article |
| 07 Jul 2017
Improving the Xin'anjiang hydrological model based on mass–energy balance
Yuan-Hao Fang
School of Earth Sciences and Engineering, Hohai University, Nanjing, China
National Cooperative Innovation Center for Water Safety & Hydro-Science, Hohai University, Nanjing, China
Department of Civil and Environmental Engineering (D.I.C.A.), Politecnico di Milano, Milan, Italy
National Cooperative Innovation Center for Water Safety & Hydro-Science, Hohai University, Nanjing, China
College of Hydrology and Water Resources, Hohai University, Nanjing, China
National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing, China
Chiara Corbari
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering (D.I.C.A.), Politecnico di Milano, Milan, Italy
Marco Mancini
Department of Civil and Environmental Engineering (D.I.C.A.), Politecnico di Milano, Milan, Italy
Guo-Yue Niu
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
Biosphere 2, University of Arizona, Oracle AZ, USA
Wenzhi Zeng
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China
Crop Science Group, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
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26 citations as recorded by crossref.
- Entropy-Based Research on Precipitation Variability in the Source Region of China’s Yellow River H. Gu et al. 10.3390/w12092486
- A Stacking Ensemble Model of Various Machine Learning Models for Daily Runoff Forecasting M. Lu et al. 10.3390/w15071265
- Error correction-based forecasting of reservoir water levels: Improving accuracy over multiple lead times X. Zhang et al. 10.1016/j.envsoft.2018.02.017
- A hydrologic similarity-based parameters dynamic matching framework: Application to enhance the real-time flood forecasting H. Wu et al. 10.1016/j.scitotenv.2023.167767
- Multi-Satellite Data of Land Surface Temperature, Lakes Area, and Water Level for Hydrological Model Calibration and Validation in the Yangtze River Basin C. Corbari et al. 10.3390/w11122621
- Scale Effects of Water Saving on Irrigation Efficiency: Case Study of a Rice-Based Groundwater Irrigation System on the Sanjiang Plain, Northeast China H. Chen et al. 10.3390/su10010047
- Enhancing streamflow estimation by integrating a data-driven evapotranspiration submodel into process-based hydrological models X. Lian et al. 10.1016/j.jhydrol.2023.129603
- Exploring an intelligent adaptation method of hydrological model parameters for flood simulations based on the light gradient-boosting machine K. Lin et al. 10.1016/j.jhydrol.2023.130340
- Estimating the Routing Parameter of the Xin’anjiang Hydrological Model Based on Remote Sensing Data and Machine Learning Y. Fang et al. 10.3390/rs14184609
- Inflow combination forecast of reservoir based on SWAT, XAJ model and Bayes model averaging method Z. Chang et al. 10.2166/ws.2022.405
- Integration of the generalized complementary relationship into a lumped hydrological model for improving water balance partitioning: A case study with the Xinanjiang model X. Lei et al. 10.1016/j.jhydrol.2023.129569
- Hydrological probabilistic forecasting based on deep learning and Bayesian optimization algorithm H. Bai et al. 10.2166/nh.2021.161
- Improved Dynamic System Response Curve Method for Real‐Time Flood Forecast Updating W. Si et al. 10.1029/2019WR025520
- Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin N. Paciolla et al. 10.1016/j.jaridenv.2021.104466
- An improved non-point source pollution model for catchment-scale hydrological processes and phosphorus loads X. Tong et al. 10.1016/j.jhydrol.2023.129588
- Computationally Efficient Multivariate Calibration and Validation of a Grid-Based Hydrologic Model in Sparsely Gauged West African River Basins T. Poméon et al. 10.3390/w10101418
- Mid- to Long-Term Runoff Prediction Based on Deep Learning at Different Time Scales in the Upper Yangtze River Basin Y. Ren et al. 10.3390/w14111692
- Spatial-Temporal Variations of Active Accumulated Temperature and Its Impact on Vegetation NDVI in the Source Region of China’s Yellow River H. Gu et al. 10.3390/w14213458
- Improving the interpretability and predictive power of hydrological models: Applications for daily streamflow in managed and unmanaged catchments P. Bhasme & U. Bhatia 10.1016/j.jhydrol.2023.130421
- Evaluation of the Impact of Multi-Source Uncertainties on Meteorological and Hydrological Ensemble Forecasting Z. Shu et al. 10.1016/j.eng.2022.06.007
- An ensemble CNN-LSTM and GRU adaptive weighting model based improved sparrow search algorithm for predicting runoff using historical meteorological and runoff data as input Z. Yao et al. 10.1016/j.jhydrol.2023.129977
- Objectivity verification experiment of the dynamic system response curve method for streamflow simulation J. Wang et al. 10.1016/j.jhydrol.2022.128969
- Value of long-term inflow forecast for hydropower operation: A case study in a low forecast precision region X. Shu et al. 10.1016/j.energy.2024.131218
- The rainfall threshold of forest cover for regulating extreme floods in mountainous catchments K. Li et al. 10.1016/j.catena.2023.107707
- A Combination Model for Quantifying Non-Point Source Pollution Based on Land Use Type in a Typical Urbanized Area S. Wang et al. 10.3390/w12030729
- Two-stage hybrid model for hydrological series prediction based on a new method of partitioning datasets H. Xu et al. 10.1016/j.jhydrol.2022.128122
Latest update: 13 Nov 2024
Short summary
Soil moisture and evapotranspiration (ET) are important to flood forecasting. An energy balance scheme based on the representative temperature (RET) was developed and coupled to the original mass balance scheme of the Xin'anjiang model. Validation against both runoff and land surface temperature confirmed the accuracy and applicability of the improved model (XAJ-EB). RET serves as a new constraint to the model and can be used for model calibration and validation.
Soil moisture and evapotranspiration (ET) are important to flood forecasting. An energy balance...
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