scholarly journals Application of a developed distributed hydrological model based on the mixed runoff generation model and 2D kinematic wave flow routing model for better flood forecasting

2017 ◽  
Vol 18 (7) ◽  
pp. 284-293 ◽  
Author(s):  
Hongjun Bao ◽  
Lili Wang ◽  
Ke Zhang ◽  
Zhijia Li
Keyword(s):  
Hydrological Model ◽  
Flood Forecasting ◽  
Wave Flow ◽  
Generation Model ◽  
Distributed Hydrological Model ◽  
Kinematic Wave ◽  
Runoff Generation ◽  
Flow Routing ◽  
Model Based

scholarly journals Ensemble flood forecasting based on ensemble NWP and the GMKHM distributed hydrological model

2018 ◽  
Vol 246 ◽  
pp. 01108
Author(s):  
Lili Wang ◽  
Hongjun Bao
Keyword(s):  
Overland Flow ◽  
Hydrological Model ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
False Alarms ◽  
Generation Model ◽  
Flood Forecast ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Numerical Weather

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for flood forecast. The GMKHM distributed hydrological model, which is based on a mixed runoff generation model and overland flow routing model based on kinematic wave theory, and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the GMKHM model and the TIGGE database gives a promising tool for the anticipation of flood events several days ahead,, comparable with that driven by raingauge observation.

scholarly journals Diagnostic calibration of a hydrological model in an alpine area

2014 ◽  
Vol 11 (1) ◽  
pp. 1253-1300 ◽  
Author(s):  
Z. He ◽  
F. Tian ◽  
H. C. Hu ◽  
H. V. Gupta ◽  
H. P. Hu
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Generation Mechanism ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Area ◽  
Long Time ◽  
Tailan River Basin

Abstract. Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

scholarly journals Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

2010 ◽  
Vol 14 (12) ◽  
pp. 2577-2594 ◽  
Author(s):  
M. Shrestha ◽  
L. Wang ◽  
T. Koike ◽  
Y. Xue ◽  
Y. Hirabayashi
Keyword(s):  
Snow Depth ◽  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Phase 1 ◽  
Forest Site ◽  
Distributed Hydrological Model ◽  
Snowmelt Runoff ◽  
Runoff Generation ◽  
Basin Scale ◽  
Snow Physics

Abstract. In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S) is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP) phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA) and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan). The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes) are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff), since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff generation with a grid-hillslope scheme, and the flow routing in the river network).

scholarly journals Operational flood-forecasting in the Piemonte region – development and verification of a fully distributed physically-oriented hydrological model

2009 ◽  
Vol 17 ◽  
pp. 111-117 ◽  
Author(s):  
D. Rabuffetti ◽  
G. Ravazzani ◽  
S. Barbero ◽  
M. Mancini
Keyword(s):  
Cross Sections ◽  
System Reliability ◽  
Hydrological Model ◽  
Warning System ◽  
Flood Forecasting ◽  
Large River ◽  
Distributed Hydrological Model ◽  
Flood Events ◽  
Discharge Time ◽  
Po River

Abstract. A hydrological model for real time flood forecasting to Civil Protection services requires reliability and rapidity. At present, computational capabilities overcome the rapidity needs even when a fully distributed hydrological model is adopted for a large river catchment as the Upper Po river basin closed at Ponte Becca (nearly 40 000 km2). This approach allows simulating the whole domain and obtaining the responses of large as well as of medium and little sized sub-catchments. The FEST-WB hydrological model (Mancini, 1990; Montaldo et al., 2007; Rabuffetti et al., 2008) is implemented. The calibration and verification activities are based on more than 100 flood events, occurred along the main tributaries of the Po river in the period 2000–2003. More than 300 meteorological stations are used to obtain the forcing fields, 10 cross sections with continuous and reliable discharge time series are used for calibration while verification is performed on about 40 monitored cross sections. Furthermore meteorological forecasting models are used to force the hydrological model with Quantitative Precipitation Forecasts (QPFs) for 36 h horizon in "operational setting" experiments. Particular care is devoted to understanding how QPF affects the accuracy of the Quantitative Discharge Forecasts (QDFs) and to assessing the QDF uncertainty impact on the warning system reliability. Results are presented either in terms of QDF and of warning issues highlighting the importance of an "operational based" verification approach.

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