Hydrological modeling in alpine catchments: sensing the critical parameters towards an efficient model calibration

2009 ◽  
Vol 60 (6) ◽  
pp. 1507-1514 ◽  
Author(s):  
S. Achleitner ◽  
M. Rinderer ◽  
R. Kirnbauer
Keyword(s):  
Model Calibration ◽  
Hydrological Modeling ◽  
Calibration Procedure ◽  
Critical Parameters ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Ice Melt ◽  
Alpine Catchments ◽  
Set Up ◽  
Two Parameters

For the Tyrolean part of the river Inn, a hybrid model for flood forecast has been set up and is currently in its test phase. The system is a hybrid system which comprises of a hydraulic 1D model for the river Inn, and the hydrological models HQsim (Rainfall-runoff-discharge model) and the snow and ice melt model SES for modeling the rainfall runoff form non-glaciated and glaciated tributary catchment respectively. Within this paper the focus is put on the hydrological modeling of the totally 49 connected non-glaciated catchments realized with the software HQsim. In the course of model calibration, the identification of the most sensitive parameters is important aiming at an efficient calibration procedure. The indicators used for explaining the parameter sensitivities were chosen specifically for the purpose of flood forecasting. Finally five model parameters could be identified as being sensitive for model calibration when aiming for a well calibrated model for flood conditions. In addition two parameters were identified which are sensitive in situations where the snow line plays an important role.

scholarly journals The GEOframe-NewAge Modelling System Applied in a Data Scarce Environment

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 86
Author(s):  
Marialaura Bancheri ◽  
Riccardo Rigon ◽  
Salvatore Manfreda
Keyword(s):  
Hydrological Modeling ◽  
Model Parameters ◽  
Control Points ◽  
Rainfall Runoff ◽  
Entire Region ◽  
Web Based ◽  
Basilicata Region ◽  
Distributed Hydrological Modeling ◽  
Reliable Parameter ◽  
Good Agreement

In this work, the semi-distributed hydrological modeling system GEOframe-NewAge was integrated with a web-based decision support system implemented for the Civil Protection Agency of the Basilicata region, Italy. The aim of this research was to forecast in near real-time the most important hydrological variables at 160 control points distributed over the entire region. The major challenge was to make the system operational in a data-scarce region characterized by a high hydraulic complexity, with several dams and infrastructures. In fact, only six streamflow gauges were available for the calibration of the model parameters. Reliable parameter sets were obtained by simulating the hydrological budget and then calibrating the rainfall-runoff parameters. After the extraction of the flow-rating curves, six sets of parameters were obtained considering the different streamflow components (i.e., the baseflow and surface runoff) and using a multi-site calibration approach. The results show a good agreement between the measured and modeled discharges, with a better agreement in the sections located upstream of the dams. Moreover, the results were validated using the inflows measured at the most important dams (Pertusillo, San Giuliano and Monte Cotugno). For rivers without monitoring points, parameters were assigned using a principle of hydrological similarity in terms of their geology, lithology, and climate.

Inverse Methodologies for Actual Status Recognition of Gas Turbine Components

2005 ◽  
Author(s):  
Giovanni Cerri ◽  
Sandra Borghetti ◽  
Coriolano Salvini
Keyword(s):  
Inverse Problems ◽  
Gas Turbine ◽  
Monitoring System ◽  
Model Calibration ◽  
Model Parameters ◽  
Deterministic Algorithms ◽  
Plant Monitoring ◽  
Set Up ◽  
Status Recognition ◽  
Real Plant

A general methodology has been established to set up GT based plant simulators to perform analysis and to identify inverse model parameters. The attention is focused on three categories of inverse problems faced in setting up the plant simulator: i) sizing of components; ii) calibration on the basis of test acceptance data; iii) actual status recognition from data collected by the plant monitoring system. Due to the different nature and requirements of the above problems different solution approaches have been adopted: hybrid stochastic-deterministic algorithms for model calibration and neural techniques for status recognition. An application to a real plant shows the capabilities of the proposed methodology.

Prediction of Subcooled Boiling With Uncertainties From Boundary Conditions and Interaction Models

2018 ◽  
Author(s):  
Tenglong Cong ◽  
Minjun Peng ◽  
Xiang Zhang
Keyword(s):  
Boundary Conditions ◽  
Model Calibration ◽  
Correlation Coefficients ◽  
Latin Hypercube Sampling ◽  
Monte Carlo Sampling ◽  
Critical Parameters ◽  
Model Parameters ◽  
Subcooled Boiling ◽  
Experiment Data ◽  
Hierarchy Analysis

Subcooled boiling has been investigated by using the RPI wall boiling models in the last two decades. High accuracy of such models has been achieved by improving the submodels for interphase actions or tuning the model parameters. However, the reliabilities of the models are still suspicious due to the limited model validation and the experimental data based model calibration. The applicability of calibrated model parameters in the new experiment data can not be assured. The effects of model parameters need to be calibrated were treated as the uncertainties of these parameters. The critical parameters that dominate the prediction of subcooled boiling were selected by using the hierarchy analysis. After that, the input samples for uncertainty analysis were obtained by an efficient Monte-Carlo sampling technology — Latin Hypercube Sampling based on the hypothetic normal distribution. Then, the samples were transferred into the FLUENT code for CFD calculations. Results from CFD code were extracted for statistical analysis. Besides, the uncertainties from boundary conditions were also analyzed to quantify the effects of experimental uncertainties. The dependency of the predicted subcooling parameters and the input parameters can be obtained. A PIRT table can be drawn from the generated correlation coefficients between inputs and outputs to quantify the importance of model parameters on subcooled boiling.

scholarly journals A Review on Rainfall Runoff Simulation at Ungauged Catchment

2018 ◽  
Vol 7 (4.35) ◽  
pp. 162
Author(s):  
W.N.C.W. Zanial ◽  
M.A. Malek ◽  
M.N.M. Reba
Keyword(s):  
Alternative Methods ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Ungauged Catchments ◽  
Ungauged Catchment ◽  
Rain Gauges ◽  
Other Information ◽  
Physically Based ◽  
Set Up

Ungauged catchment occurs when no runoff data are available or when very few ground rain gauges are located in a huge catchment.  For these catchments, the parameters to be used in rainfall‐runoff models cannot be attained just by adjusting runoff information and thus should be procured by different techniques. Show parameters that require orientation are normally transposed from comparable measured catchments. The rainfall runoff simulation is very important to estimate and predict the flow in ungauged catchment. This investigation reviews ideas to differentiate hydrological comparability for transposing parameters from a gauged to an ungauged catchment. Model parameters that are physically based are generally derived from other information close to the ungauged catchment of intrigue. The primary challenge with rainfall‐runoff demonstrating in ungauged catchments is the absence of neighborhood ground precipitation and streamflow information to be utilized in aligning the proposed show parameters. Parameter alignment is useful since adjustment can represent the impacts of hydrological set up in a specific catchment. Since hydrological models are especially reliant on their limit conditions, the alignment practice directed can modify the predispositions of info information utilized. Parameters' adjustment can fundamentally improve the execution of rainfall‐runoff models since it included media properties of soil and vegetation which are exceptionally heterogeneous and basically are in every case inadequately known. Alternative methods for ungauged catchments are required which are the subject of this study. This study summarizes the important methods used in an ungauged catchments, discusses the issues of using satellite data as a substitute input to rainfall‐runoff models and its comparison with point scale ground data.

scholarly journals Moving beyond traditional model calibration or how to better identify realistic model parameters: sub-period calibration

2012 ◽  
Vol 9 (2) ◽  
pp. 1885-1918
Author(s):  
S. Gharari ◽  
M. Hrachowitz ◽  
F. Fenicia ◽  
H. H. G. Savenije
Keyword(s):  
Model Calibration ◽  
Model Performance ◽  
Realistic Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
New Approach ◽  
Consistent Model ◽  
Set Up

Abstract. Conceptual hydrological models often rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of confronting model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time consistent parameter sets. The approach is demonstrated in a case study where we illustrate the multi-objective calibration of the HyMod hydrological model to a Luxembourgish catchment.

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2006 ◽  
Vol 3 (3) ◽  
pp. 1105-1124 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Regional Function ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model

Abstract. The parameters of hydrological models for catchments with few or no discharge records can only be estimated using regional information. One can assume that catchments with similar characteristics show a similar hydrological behaviour and thus can be modeled using similar model parameters. Therefore a regionalisation of the hydrological model parameters on the basis of catchment characteristics is plausible. However, due to the non-uniqueness of the rainfall-runoff model parameters (equifinality), a workflow of regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper a different approach for the transfer of entire parameter sets from one catchment to another is discussed. Transferable parameter sets are identified using regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics.

Sewer flow quality modelling

1997 ◽  
Vol 36 (5) ◽  
pp. 177-184
Author(s):  
Lennart Heip ◽  
Johan Van Assel ◽  
Patrick Swartenbroekx
Keyword(s):  
Model Calibration ◽  
Model Building ◽  
Quality Model ◽  
Hydraulic Behaviour ◽  
Measuring Campaign ◽  
Flow Quality ◽  
Wet Weather ◽  
Calibration And Verification ◽  
Set Up ◽  
Dry Weather Flow

Within the framework of an EC-funded SPRINT-project, a sewer flow quality model of a typical rural Flemish catchment was set up. The applicability of such a model is demonstrated. Furthermore a methodology for model building, data collection and model calibration and verification is proposed. To this end an intensive 9 month measuring campaign was undertaken. The hydraulic behaviour of the sewer network was continuously monitored during those 9 months. During both dry weather flow (DWF) and wet weather flow (WWF) a number of sewage samples were taken and analysed for BOD, COD, TKN, TP and TSS. This resulted in 286 WWF and 269 DWF samples. The model was calibrated and verified with these data. Finally a software independent methodology for interpretation of the model results is proposed.

scholarly journals Mining Camera Traces to Estimate Interactions Between Healthcare Workers and Patients

2020 ◽  
Vol 41 (S1) ◽  
pp. s12-s12
Author(s):  
D. M. Hasibul Hasan ◽  
Philip Polgreen ◽  
Alberto Segre ◽  
Jacob Simmering ◽  
Sriram Pemmaraju
Keyword(s):  
Time Of Day ◽  
Microsoft Kinect ◽  
Critical Parameters ◽  
Model Parameters ◽  
Patient Room ◽  
University Of Iowa ◽  
Velocity Change ◽  
Fine Grained ◽  
Visit Frequency ◽  
Contact Patterns

Background: Simulations based on models of healthcare worker (HCW) mobility and contact patterns with patients provide a key tool for understanding spread of healthcare-acquired infections (HAIs). However, simulations suffer from lack of accurate model parameters. This research uses Microsoft Kinect cameras placed in a patient room in the medical intensive care unit (MICU) at the University of Iowa Hospitals and Clinics (UIHC) to obtain reliable distributions of HCW visit length and time spent by HCWs near a patient. These data can inform modeling efforts for understanding HAI spread. Methods: Three Kinect cameras (left, right, and door cameras) were placed in a patient room to track the human body (ie, left/right hands and head) at 30 frames per second. The results reported here are based on 7 randomly selected days from a total of 308 observation days. Each tracked body may have multiple raw segments over the 2 camera regions, which we “stitch” up by matching features (eg, direction, velocity, etc), to obtain complete trajectories. Due to camera noise, in a substantial fraction of the frames bodies display unnatural characteristics including frequent and rapid directional and velocity change. We use unsupervised learning techniques to identify such “ghost” frames and we remove from our analysis bodies that have 20% or more “ghost” frames. Results: The heat map of hand positions (Fig. 1) shows that high-frequency locations are clustered around the bed and more to the patient’s right in accordance with the general medical practice of performing patient exams from their right. HCW visit frequency per hour (mean, 6.952; SD, 2.855) has 2 peaks, 1 during morning shift and 1 during the afternoon shift, with a distinct decrease after midnight. Figure 2 shows visit length (in minutes) distribution (mean, 1.570; SD, 2.679) being dominated by “check in visits” of <30 seconds. HCWs do not spend much time at touching distance from patients during short-length visits, and the fraction of time spent near the patient’s bed seems to increase with visit length up to a point. Conclusions: Using fine-grained data, this research extracts distributions of these critical parameters of HCW–patient interactions: (1) HCW visit length, (2) HCW visit frequency as a function of time of day, and (3) time spent by HCW within touching distance of patient as a function of visit length. To the best of our knowledge, we provide the first reliable estimates of these parameters.Funding: NoneDisclosures: None

scholarly journals Spatio-Temporal Hydrological Model Structure and Parametrization Analysis

2021 ◽  
Vol 9 (5) ◽  
pp. 467
Author(s):  
Mostafa Farrag ◽  
Gerald Corzo Perez ◽  
Dimitri Solomatine
Keyword(s):  
Hydrological Modeling ◽  
Model Building ◽  
Model Performance ◽  
Model Description ◽  
Generation Model ◽  
Model Structure ◽  
Runoff Generation ◽  
Spatial Sensitivity ◽  
Spatio Temporal ◽  
Set Up

Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters’ values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.

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