scholarly journals Exploring the Use of the Three Rainfall Remote Sensing Products for Flood Prediction in the Brahmaputra Basin

10.29007/h6z1 ◽  
2018 ◽  
Author(s):  
Maurizio Mazzoleni ◽  
Biswa Bhattacharya ◽  
Miguel Angel Laverde Barajas ◽  
Dimitri Solomatine
Keyword(s):  
The Other ◽  
Hydrological Models ◽  
Flood Prediction ◽  
Satisfactory Model ◽  
Fusion Methods ◽  
Brahmaputra Basin ◽  
Distributed Hydrological Models ◽  
Gauged Basins ◽  
Rainfall Estimates ◽  
Accurate Quantification

An important aspect in hydrological modelling is the accurate quantification and prediction of rainfall. In ungauged or poorly gauged basins ground data is sparse and often is complemented by rainfall satellite products, which brings additional uncertainties. The main objective of this research is to assess performance of distributed hydrological models using the remotely sensed rainfall estimates as forcings for the model. The model, based is based on the conceptual HBV-96 model and the PCRaster framework, is implemented for the Brahmaputra basin. Three different remote sensed datasets of precipitation (MSWEP, TMPA and PERSIANN-CDR) are used. Simple fusion methods are used to combine models results generate by the dataset of precipitation. The preliminary results of this study show that better model results are achieved merging the output results. Using MSWEP and TMPA as the forcing data provides satisfactory model results. On the other hand, use of PERSIANN-CDR leads to better prediction of flow peaks but overestimations of the hydrographs’ falling limbs.

scholarly journals A comparison between lumped and distributed hydrological models for daily rainfall-runoff simulation

2021 ◽  
Vol 958 (1) ◽  
pp. 012016
Author(s):  
F Vilaseca ◽  
S Narbondo ◽  
C Chreties ◽  
A Castro ◽  
A Gorgoglione
Keyword(s):  
Computational Cost ◽  
Model Performance ◽  
Daily Rainfall ◽  
Complex Model ◽  
The Other ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Distributed Hydrological Models ◽  
Social Importance

Abstract In Uruguay, the Santa Lucía Chico watershed has been studied in several hydrologic/hydraulic works due to its economic and social importance. However, few studies have been focused on water balance computation in this watershed. In this work, two daily rainfall-runoff models, a distributed (SWAT) and a lumped one (GR4J), were implemented at two subbasins of the Santa Lucía Chico watershed, with the aim of providing a thorough comparison for simulating daily hydrographs and identify possible scenarios in which each approach is more suitable than the other. Results showed that a distributed and complex model like SWAT performs better in watersheds characterized by anthropic interventions such as dams, which can be explicitly represented. On the other hand, for watersheds with no significant reservoirs, the use of a complex model may not be justified due to the higher effort required in modeling design, implementation, and computational cost, which is not reflected in a significant improvement of model performance.

scholarly journals An Evaluation Matrix to Compare Computer Hydrological Models for Flood Predictions

Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 42 ◽  
Author(s):  
Pasquale Filianoti ◽  
Luana Gurnari ◽  
Demetrio Antonio Zema ◽  
Giuseppe Bombino ◽  
Marco Sinagra ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Early Stage ◽  
Optimal Choice ◽  
Evaluation Framework ◽  
The Other ◽  
Hydrological Models ◽  
Complete Evaluation ◽  
Flood Prediction ◽  
Stage Of Development ◽  
Performance Matrix

In order to predict and control the impacts of floods in torrents, it is important to verify the simulation accuracy of the most used hydrological models. The performance verification is particularly needed for applications in watersheds with peculiar climatic and geomorphological characteristics, such as the Mediterranean torrents. Moreover, in addition to the accuracy, other factors affect the choice of software by stakeholders (users, modellers, researchers, etc.). This study introduces a “performance matrix”, consisting of several evaluation parameters weighted by stakeholders’ opinions. The aim is to evaluate the accuracy of the flood prediction which is achieved by different models, as well as the pros and cons of software user experience. To this aim, the performances and requisites of four physical-based and conceptual models (HEC-HMS, SWMM, MIKE11 NAM and WEC-FLOOD) have been evaluated, by predicting floods in a midsized Mediterranean watershed (Mèsima torrent, Calabria, Southern Italy). In the case study, HEC-HMS and MIKE 11 NAM were the best computer models (with a weighted score of 4.45 and 4.43, respectively), thanks to their low complexity and computation effort, as well as good user interface and prediction accuracy. However, MIKE11 NAM is not free of charge. SWMM showed a lower prediction accuracy, which put the model in third place of the four models. The performance of WEC-FLOOD, although not being as good as for the other tested models, can be considered overall acceptable in comparison to the other well-consolidated models, considering that WEC-FLOOD is in the early stage of development. Overall, the proposal of the performance matrix for hydrological models may represent a first step in building a more complete evaluation framework of the hydrological and hydraulic commercial models, in order to give indications to allow potential users to make an optimal choice.

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 Development of dynamic system response curve method for estimating initial conditions of conceptual hydrological models

2018 ◽  
Vol 20 (6) ◽  
pp. 1387-1400
Author(s):  
Yiqun Sun ◽  
Weimin Bao ◽  
Peng Jiang ◽  
Xuying Wang ◽  
Chengmin He ◽  
...  
Keyword(s):  
Dynamic System ◽  
Response Curve ◽  
Initial Conditions ◽  
Model Performance ◽  
System Response ◽  
Hydrological Models ◽  
Flood Prediction ◽  
Ill Posed ◽  
Value Decomposition

Abstract The dynamic system response curve (DSRC) has its origin in correcting model variables of hydrologic models to improve the accuracy of flood prediction. The DSRC method can lead to unstable performance since the least squares (LS) method, employed by DSRC to estimate the errors, often breaks down for ill-posed problems. A previous study has shown that under certain assumptions the DSRC method can be regarded as a specific form of the numerical solution of the Fredholm equation of the first kind, which is a typical ill-posed problem. This paper introduces the truncated singular value decomposition (TSVD) to propose an improved version of the DSRC method (TSVD-DSRC). The proposed method is extended to correct the initial conditions of a conceptual hydrological model. The usefulness of the proposed method is first demonstrated via a synthetic case study where both the perturbed initial conditions, the true initial conditions, and the corrected initial conditions are precisely known. Then the proposed method is used in two real basins. The results measured by two different criteria clearly demonstrate that correcting the initial conditions of hydrological models has significantly improved the model performance. Similar good results are obtained for the real case study.

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 Flood Inundation Mapping of the Sparsely Gauged Large-Scale Brahmaputra Basin Using Remote Sensing Products

2019 ◽  
Vol 11 (5) ◽  
pp. 501 ◽  
Author(s):  
Biswa Bhattacharya ◽  
Maurizio Mazzoleni ◽  
Reyne Ugay
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Large Scale ◽  
Hydrological Model ◽  
Rainfall Data ◽  
Flood Inundation ◽  
Hydraulic Modelling ◽  
Brahmaputra Basin ◽  
Gauged Basins ◽  
Global Datasets

Sustainable water management is one of the important priorities set out in the Sustainable Development Goals (SDGs) of the United Nations, which calls for efficient use of natural resources. Efficient water management nowadays depends a lot upon simulation models. However, the availability of limited hydro-meteorological data together with limited data sharing practices prohibits simulation modelling and consequently efficient flood risk management of sparsely gauged basins. Advances in remote sensing has significantly contributed to carrying out hydrological studies in ungauged or sparsely gauged basins. In particular, the global datasets of remote sensing observations (e.g., rainfall, evaporation, temperature, land use, terrain, etc.) allow to develop hydrological and hydraulic models of sparsely gauged catchments. In this research, we have considered large scale hydrological and hydraulic modelling, using freely available global datasets, of the sparsely gauged trans-boundary Brahmaputra basin, which has an enormous potential in terms of agriculture, hydropower, water supplies and other utilities. A semi-distributed conceptual hydrological model was developed using HEC-HMS (Hydrologic Modelling System from Hydrologic Engineering Centre). Rainfall estimates from Tropical Rainfall Measuring Mission (TRMM) was compared with limited gauge data and used in the simulation. The Nash Sutcliffe coefficient of the model with the uncorrected rainfall data in calibration and validation were 0.75 and 0.61 respectively whereas the similar values with the corrected rainfall data were 0.81 and 0.74. The output of the hydrological model was used as a boundary condition and lateral inflow to the hydraulic model. Modelling results obtained using uncorrected and corrected remotely sensed products of rainfall were compared with the discharge values at the basin outlet (Bahadurabad) and with altimetry data from Jason-2 satellite. The simulated flood inundation maps of the lower part of the Brahmaputra basin showed reasonably good match in terms of the probability of detection, success ratio and critical success index. Overall, this study demonstrated that reliable and robust results can be obtained in both hydrological and hydraulic modelling using remote sensing data as the only input to large scale and sparsely gauged basins.

A preliminary appraisal of Thurnham dual polarisation radar in the context of hydrological modelling structure

2012 ◽  
Vol 43 (5) ◽  
pp. 736-752 ◽  
Author(s):  
D. Zhu ◽  
I. D. Cluckie
Keyword(s):  
Direct Consequence ◽  
Hydrological Models ◽  
Short Term ◽  
Radar Rainfall ◽  
Mathematical Structures ◽  
Extreme Flood ◽  
Clutter Removal ◽  
The Impact ◽  
Further Development ◽  
Rainfall Estimates

The Thurnham radar is a prototype of a potential operational C-Band dual-polarisation weather radar designed specifically for the measurement of rainfall. It is also designed to increase the radar coverage over London when operating as a conventional C-Band radar as a direct consequence of the Lewes floods of October 2000. Dual-polarisation processing is expected to provide improved estimation of rainfall rates, especially at higher intensities, in terms of clutter removal, attenuation correction and rainfall estimation. In this study, three hydrological models with different mathematical structures were selected to evaluate the impact that dual-polarisation technology could have on operational hydrology and recommendations provided on the further development of the dual-polarisation algorithms in the short term. The preliminary appraisal was focused on the Upper Medway Catchment (south of London, UK) using different precipitation inputs, including raingauge measurements, radar rainfall estimates from single-polarised algorithms (cartesian format) and five different dual-polarisation algorithms (polar format). The influence of the different rainfall inputs on the various hydrological models were compared using a extreme flood event to provide an initial evaluation of the performance of the Thurnham radar. Recommendations for applying dual-polarisation radar to real-time flood forecasting are discussed in detail.

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