The impact of interpolation method on the accuracy of meteorological variables in distributed hydrological model

2020 ◽  
Author(s):  
Jiajia Liu ◽  
Zuhao Zhou ◽  
Ziqi Yan ◽  
Yangwen Jia ◽  
Hao Wang
Keyword(s):  
Input Data ◽  
Hydrological Model ◽  
Interpolation Method ◽  
Stable State ◽  
Meteorological Station ◽  
Data Uncertainty ◽  
Meteorological Variables ◽  
Distributed Hydrological Model ◽  
Centroid Point ◽  
The Impact

<p>Precipitation and other meteorological variables are very important input data for distributed hydrological models, which determine the simulation accuracy of the models. It is a normal way to subdivide the large area watershed into numerous subbasins to reflect the spatial variation, and the value is usually unique within each subbasin. In most model application, the values of meteorological variables are interpolated from meteorological station observed data to the centroid point of the subbasin with interpolation method (called one-cell interpolation). Because the centroid point could not represent the whole subbasin, the one-cell interpolation will bring input data uncertainty to the model. In this study, a new method is introduced to analysis this uncertainty, which firstly interpolate the values into numerous cells smaller than the subbasin then sum up to the subbasin (called multi-cells interpolation). The results show that one-cell interpolation way is not always consistent with the results of multi-cells interpolation, and the variance is greater in summer than in winter. The consistency grows with the increase of the number of the cells, which indicates that dozens of the cells could got the stable state. The variance is also influenced by the density of meteorological station, but the minimal cell number is almost the same. Thus, in the interpolation of the meteorological variables in distributed hydrological model, it recommends to interpolate the values to numerous smaller cells then sum up to the subbasins, rather than only interpolate to the centroid point.</p>

scholarly journals Application of deterministic distributed hydrological model for large catchment: a case study at Vu Gia Thu Bon catchment, Vietnam

2016 ◽  
Vol 18 (5) ◽  
pp. 885-904 ◽  
Author(s):  
Ngoc Duong Vo ◽  
Philippe Gourbesville
Keyword(s):  
Overland Flow ◽  
Hydrological Model ◽  
Unsaturated Flow ◽  
Correlation Coefficients ◽  
Water Levels ◽  
Distributed Hydrological Model ◽  
Ungauged Catchments ◽  
Quality Of Results ◽  
The Impact

In order to create a tool to help hydrologists and authorities to have good understanding about occurrences in stream flow regime together with its variation in the future under the impact of climate change in the Vu Gia Thu Bon catchment, a deterministic distributed hydrological model has been developed and constructed. This model covers the major processes in the hydrologic cycle including rainfall, evapotranspiration, overland flow, unsaturated flow, groundwater flow, channel flow, and their interactions. The model is calibrated and validated against the daily data recorded at seven stations during 1991–2000 and 2001–2010, respectively. The quality of results is demonstrated by Nash–Sutcliffe and correlation coefficients that reach 0.82 and 0.92, respectively, in discharge comparison. With water levels, the obtained coefficients are lower but the quality of results still remains high; Nash–Sutcliffe and correlation coefficients reach 0.77 and 0.89, respectively, in the upstream part of the catchment. This analysis demonstrates the performance of the deterministic distributed modeling approach in simulating hydrological processes one more time; it also confirms the usefulness of this model with ungauged catchments or large catchments. Additionally, this analysis proves the role of multi-calibration in increasing the accuracy of hydrological models for large catchments.

scholarly journals Impacts of Introducing Remote Sensing Soil Moisture in Calibrating a Distributed Hydrological Model for Streamflow Simulation

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 666 ◽  
Author(s):  
Lihua Xiong ◽  
Ling Zeng
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Objective Function ◽  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Soil Moisture Data ◽  
Streamflow Data ◽  
The Impact ◽  
Hydrological Variables ◽  
Streamflow Simulation

With the increased availability of remote sensing products, more hydrological variables (e.g., soil moisture and evapotranspiration) other than streamflow data are introduced into the calibration procedure of a hydrological model. However, how the incorporation of these hydrological variables influences the calibration results remains unclear. This study aims to analyze the impact of remote sensing soil moisture data in the joint calibration of a distributed hydrological model. The investigation was carried out in Qujiang and Ganjiang catchments in southern China, where the Dem-based Distributed Rainfall-runoff Model (DDRM) was calibrated under different calibration schemes where the streamflow data and the remote sensing soil moisture are assigned to different weights in the objective function. The remote sensing soil moisture data are from the SMAP L3 soil moisture product. The results show that different weights of soil moisture in the objective function can lead to very slight differences in simulation performance of soil moisture and streamflow. Besides, the joint calibration shows no apparent advantages in terms of streamflow simulation over the traditional calibration using streamflow data only. More studies including various remote sensing soil moisture products are necessary to access their effect on the joint calibration.

scholarly journals Modelling a river catchment using an electrical circuit analogue

1998 ◽  
Vol 2 (1) ◽  
pp. 9-18 ◽  
Author(s):  
C. G. Collier
Keyword(s):  
Input Data ◽  
River Flow ◽  
Hydrological Model ◽  
Analytic Solution ◽  
Electrical Circuit ◽  
Physical Processes ◽  
River Catchment ◽  
Analogue Research ◽  
The Impact ◽  
Modelling Approach

Abstract. An electrical circuit analogue of a river catchment is described from which is derived an hydrological model of river flow called the River Electrical Water Analogue Research and Development (REWARD) model. The model is based upon an analytic solution to the equation governing the flow of electricity in an inductance-capacitance-resistance (LCR) circuit. An interpretation of L, C and R in terms of catchment parameters and physical processes is proposed, and tested for the River Irwell catchment in northwest England. Hydrograph characteristics evaluated using the model are compared with observed hydrographs, confirming that the modelling approach does provide a reliable framework within which to investigate the impact of variations in model input data.

scholarly journals Multi-hazard risk assessment for roads: probabilistic versus deterministic approaches

2020 ◽  
Vol 20 (11) ◽  
pp. 3135-3160
Author(s):  
Stefan Oberndorfer ◽  
Philip Sander ◽  
Sven Fuchs
Keyword(s):  
Risk Assessment ◽  
Road Safety ◽  
Input Data ◽  
Probabilistic Approach ◽  
Transport Infrastructure ◽  
Data Uncertainty ◽  
European Alps ◽  
Hazard Risk ◽  
The Impact

Abstract. Mountain hazard risk analysis for transport infrastructure is regularly based on deterministic approaches. Standard risk assessment approaches for roads need a variety of variables and data for risk computation, however without considering potential uncertainty in the input data. Consequently, input data needed for risk assessment are normally processed as discrete mean values without scatter or as an individual deterministic value from expert judgement if no statistical data are available. To overcome this gap, we used a probabilistic approach to analyse the effect of input data uncertainty on the results, taking a mountain road in the Eastern European Alps as a case study. The uncertainty of the input data are expressed with potential bandwidths using two different distribution functions. The risk assessment included risk for persons, property risk and risk for non-operational availability exposed to a multi-hazard environment (torrent processes, snow avalanches and rockfall). The study focuses on the epistemic uncertainty of the risk terms (exposure situations, vulnerability factors and monetary values), ignoring potential sources of variation in the hazard analysis. As a result, reliable quantiles of the calculated probability density distributions attributed to the aggregated road risk due to the impact of multiple mountain hazards were compared to the deterministic outcome from the standard guidelines on road safety. The results based on our case study demonstrate that with common deterministic approaches risk might be underestimated in comparison to a probabilistic risk modelling setup, mainly due to epistemic uncertainties of the input data. The study provides added value to further develop standardized road safety guidelines and may therefore be of particular importance for road authorities and political decision-makers.

scholarly journals Reconstructing Flood Events in Mediterranean Coastal Areas Using Different Reanalyses and High-Resolution Meteorological Models

2020 ◽  
Vol 21 (8) ◽  
pp. 1865-1887
Author(s):  
A. Senatore ◽  
S. Davolio ◽  
L. Furnari ◽  
G. Mendicino
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Hydrological Model ◽  
Numerical Models ◽  
Heavy Precipitation ◽  
High Impact ◽  
Added Value ◽  
Distributed Hydrological Model ◽  
The Impact ◽  
Small Catchments

AbstractReliable reanalysis products can be exploited to drive mesoscale numerical models and generate high-resolution reconstructions of high-impact weather events. Within this framework, regional weather and climate models may greatly benefit from the recent release of the ERA5 product, an improvement to the ERA-Interim dataset. In this study, two different convection-permitting models driven by these two reanalysis datasets are used to reproduce three heavy precipitation events affecting a Mediterranean region. Moreover, different sea surface temperature (SST) initializations are tested to assess how higher-resolution SST fields improve the simulation of high-impact events characterized by strong air–sea interactions. Finally, the coupling with a distributed hydrological model allows evaluating the impact at the ground, specifically assessing the possible added value of the ERA5 dataset for the high-resolution simulation of extreme hydrometeorological events over the Calabria region (southern Italy). Results, based on the comparison against multiple-source precipitation observations, show no clear systematic benefit to using the ERA5 dataset; moreover, intense convective activity can introduce uncertainties masking the signal provided by the boundary conditions of the different reanalyses. The effect of the high-resolution SST fields is even more difficult to detect. The uncertainties propagate and amplify along the modeling chain, where the spatial resolution increases up to the hydrological model. Nevertheless, even in very small catchments, some of the experiments provide reasonably accurate results, suggesting that an ensemble approach could be suitable to cope with uncertainties affecting the overall meteo-hydrological chain, especially for small catchments.

scholarly journals Integration of Forest Growth Component in the FEST-WB Distributed Hydrological Model: The Bonis Catchment Case Study

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1794
Author(s):  
Mouna Feki ◽  
Giovanni Ravazzani ◽  
Alessandro Ceppi ◽  
Gaetano Pellicone ◽  
Tommaso Caloiero
Keyword(s):  
Primary Production ◽  
Hydrological Model ◽  
Carbon Allocation ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Forest Growth ◽  
Distributed Hydrological Model ◽  
Homogeneous Population ◽  
Forest Model ◽  
The Impact

In this paper, the FEST-FOREST model is presented. A FOREST module is written in the FORTRAN-90 programming language, and was included in the FEST-WB distributed hydrological model delivering the FEST-FOREST model. FEST-FOREST is a process-based dynamic model allowing the simulation at daily basis of gross primary production (GPP) and net primary production (NPP) together with the carbon allocation of a homogeneous population of trees (same age, same species). The model was implemented based on different equations from literature, commonly used in Eco-hydrological models. This model was developed within the framework of the INNOMED project co-funded under the ERA-NET WaterWorks2015 Call of the European Commission. The aim behind the implementation of the model was to simulate in a simplified mode the forest growth under different climate change and management scenarios, together with the impact on the water balance at the catchment. On a first application of the model, the results are considered very promising when compared to field measured data.

Research the Effect of Roughness on the Distribution Overland Runoff Simulation

2012 ◽  
Vol 518-523 ◽  
pp. 3668-3671 ◽  
Author(s):  
Sheng Tang Zhang ◽  
Miao Miao Li ◽  
Peng Chi
Keyword(s):  
Spatial Variation ◽  
Human Activities ◽  
Overland Flow ◽  
Hydrological Model ◽  
Flow Direction ◽  
Distributed Hydrological Model ◽  
Runoff Simulation ◽  
Flow Convergence ◽  
Overland Runoff ◽  
The Impact

The slope roughness is a character parameter which shows the blocking effects of earth surface on the overland flow. As a result of the impact of human activities, the land utilization types spatially change rapidly. Consequently, the catchment surface appears as broken patches pattern so that the spatial variation of surface roughness increased. And this leads to change on the runoff flow convergence velocity, the flow direction and the flow assignment in each direction. The accurately runoff simulation is not available when the roughness effect is neglected. Therefore, study on slope roughness effects become important in human activities impacted hydrological research. Based on former researches, we divided the slope roughness research into three levels, and discussed the inappropriate points of the slope runoff flow convergence algorithm, which adopted by the current distributed hydrological model, when dealing with the slope roughness on the human activities impacted catchment. Moreover, we presented that in order to obtain an effective result of simulating overland runoff. The distributed hydrological model should take the spatial variation effect of the slope roughness factor into consideration and formulation.

scholarly journals State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

2012 ◽  
Vol 9 (3) ◽  
pp. 3961-3999 ◽  
Author(s):  
O. Rakovec ◽  
A. H. Weerts ◽  
P. Hazenberg ◽  
P. J. J. F. Torfs ◽  
R. Uijlenhoet
Keyword(s):  
Ensemble Kalman Filter ◽  
Hydrological Model ◽  
Forecast Accuracy ◽  
Distributed Hydrological Model ◽  
Observation Network ◽  
Spatially Distributed ◽  
Observation Uncertainty ◽  
The Impact ◽  
Observation Vector ◽  
Ensemble Kalman Filtering

Abstract. This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of the hourly HBV-96 model. Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF scheme is mainly changing the pdf's of the two routing model storages. This also holds for situations, where the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

scholarly journals State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

2012 ◽  
Vol 16 (9) ◽  
pp. 3435-3449 ◽  
Author(s):  
O. Rakovec ◽  
A. H. Weerts ◽  
P. Hazenberg ◽  
P. J. J. F. Torfs ◽  
R. Uijlenhoet
Keyword(s):  
Hydrological Model ◽  
Forecast Accuracy ◽  
Markov Property ◽  
Distributed Hydrological Model ◽  
Time Step ◽  
Observation Network ◽  
Physically Based ◽  
Spatially Distributed ◽  
Observation Uncertainty ◽  
The Impact

Abstract. This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

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