scholarly journals Scaling Precipitation Input to Spatially Distributed Hydrological Models by Measured Snow Distribution

2016 ◽  
Vol 4 ◽  
Author(s):  
Christian Vögeli ◽  
Michael Lehning ◽  
Nander Wever ◽  
Mathias Bavay
Keyword(s):  
Hydrological Models ◽  
Spatially Distributed ◽  
Snow Distribution ◽  
Distributed Hydrological Models

Split-parameter structure for the automatic calibration of distributed hydrological models

2007 ◽  
Vol 332 (1-2) ◽  
pp. 226-240 ◽  
Author(s):  
Félix Francés ◽  
Jaime Ignacio Vélez ◽  
Jorge Julián Vélez
Keyword(s):  
Automatic Calibration ◽  
Hydrological Models ◽  
Split Parameter ◽  
Distributed Hydrological Models

scholarly journals Model Uncertainty Analysis Methods for Semi-Arid Watersheds with Different Characteristics: A Comparative SWAT Case Study

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1177 ◽  
Author(s):  
Lufang Zhang ◽  
Baolin Xue ◽  
Yuhui Yan ◽  
Guoqiang Wang ◽  
Wenchao Sun ◽  
...  
Keyword(s):  
Uncertainty Analysis ◽  
River Basin ◽  
Model Uncertainty ◽  
Assessment Tool ◽  
Rapid Development ◽  
Swat Model ◽  
Observation Data ◽  
Hydrological Models ◽  
Distributed Hydrological Models ◽  
Different Characteristics

Distributed hydrological models play a vital role in water resources management. With the rapid development of distributed hydrological models, research into model uncertainty has become a very important field. When studying traditional hydrological model uncertainty, it is very common to use multisite observation data to evaluate the performance of the model in the same watershed, but there are few studies on uncertainty in watersheds with different characteristics. This study is based on the Soil and Water Assessment Tool (SWAT) model, and uses two common methods: Sequential Uncertainty Fitting Version 2 (SUFI-2) and Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis. We compared these methods in terms of parameter uncertainty, model prediction uncertainty, and simulation effects. The Xiaoqing River basin and the Xinxue River basin, which have different characteristics, including watershed geography and scale, were used for the study areas. The results show that the GLUE method had better applicability in the Xiaoqing River basin, and that the SUFI-2 method provided more reasonable and accurate analysis results in the Xinxue River basin; thus, the applicability was higher. The uncertainty analysis method is affected to some extent by the characteristics of the watershed.

scholarly journals Spatial Interpolation for Real-Time Rainfall Field Estimation in Areas with Complex Topography

2013 ◽  
Vol 14 (1) ◽  
pp. 85-104 ◽  
Author(s):  
M. C. Rogelis ◽  
M. G. F. Werner
Keyword(s):  
Real Time ◽  
Ordinary Kriging ◽  
Kriging With External Drift ◽  
Time Operation ◽  
Spatially Distributed ◽  
Interpolation Procedure ◽  
Real Time Operation ◽  
Distributed Hydrological Models ◽  
Gaussian Simulation ◽  
External Drift

Abstract For many hydrological applications interpolation of point rainfall measurements is needed. One such application is flood early warning, particularly where spatially distributed hydrological models are used. Operation in real time poses challenges to the interpolation procedure, as this should then both be automatic and efficiently provide robust interpolation of gauged data. The differences in performance of ordinary kriging, universal kriging, and kriging with external drift with individual and pooled variograms were assessed for 139 daily datasets with significant precipitation in a study area in Bogotá, Colombia. Interpolators were compared using the percentage of variability explained and the root-mean-square error found in cross validation, aiming at identifying a procedure for real-time interpolation. The results showed that interpolators using pooled variograms provide a performance comparable to when the interpolators were applied to the storms individually, showing that they can be used successfully for interpolation in real-time operation in the study area. The analysis identified limitations in the use of kriging with external drift. Only when the adjusted R2 between the secondary variables and precipitation is higher than the percentage of variability explained found in ordinary kriging, then kriging with external drift provided a consistent improvement. This interpolator was found to give a lower performance in all other cases. The distribution of precipitation over basins of interest for each of the storms, derived through sampling rainfall fields generated through conditional Gaussian simulation, shows that, while differences between the interpolators may appear to be significant, the variability of the precipitation volume is less significant.

Integration of earth observation data in distributed hydrological models: the Senegal River basin

2003 ◽  
Vol 29 (6) ◽  
pp. 701-710 ◽  
Author(s):  
Inge Sandholt ◽  
Jens Andersen ◽  
Gorm Dybkjær ◽  
Lotte Nyborg ◽  
Medou Lô ◽  
...  
Keyword(s):  
River Basin ◽  
Earth Observation ◽  
Observation Data ◽  
Hydrological Models ◽  
Senegal River ◽  
Earth Observation Data ◽  
Distributed Hydrological Models ◽  
Senegal River Basin

A watershed rainfall data recovery approach with application to distributed hydrological models

2011 ◽  
Vol 26 (13) ◽  
pp. 1937-1948 ◽  
Author(s):  
Jinggang Chu ◽  
Chi Zhang ◽  
Yilun Wang ◽  
Huicheng Zhou ◽  
Christine A. Shoemaker
Keyword(s):  
Rainfall Data ◽  
Data Recovery ◽  
Hydrological Models ◽  
Distributed Hydrological Models ◽  
Recovery Approach
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