Error analysis for the evaluation of model performance: rainfall–runoff event summary variables

2007 ◽  
Vol 21 (22) ◽  
pp. 3009-3024 ◽  
Author(s):  
Edzer J. Pebesma ◽  
Paul Switzer ◽  
Keith Loague
Keyword(s):  
Error Analysis ◽  
Model Performance ◽  
Rainfall Runoff ◽  
Runoff Event

Error analysis for the evaluation of model performance: rainfall-runoff event time series data

2005 ◽  
Vol 19 (8) ◽  
pp. 1529-1548 ◽  
Author(s):  
Edzer J. Pebesma ◽  
Paul Switzer ◽  
Keith Loague
Keyword(s):  
Time Series ◽  
Error Analysis ◽  
Time Series Data ◽  
Model Performance ◽  
Series Data ◽  
Rainfall Runoff ◽  
Event Time ◽  
Runoff Event

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

scholarly journals Derivation of S-Curve from Oscillatory Hydrograph Using Digital Filter

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1456
Author(s):  
Kee-Won Seong ◽  
Jang Hyun Sung
Keyword(s):  
Digital Filter ◽  
Model Performance ◽  
Performance Criteria ◽  
Rainfall Runoff ◽  
Small Watershed ◽  
Unit Hydrograph ◽  
Time To Peak ◽  
S Curve ◽  
And Performance ◽  
Smooth Data

An oscillatory S-curve causes unexpected fluctuations in a unit hydrograph (UH) of desired duration or an instantaneous UH (IUH) that may affect the constraints for hydrologic stability. On the other hand, the Savitzky–Golay smoothing and differentiation filter (SG filter) is a digital filter known to smooth data without distorting the signal tendency. The present study proposes a method based on the SG filter to cope with oscillatory S-curves. Compared to previous conventional methods, the application of the SG filter to an S-curve was shown to drastically reduce the oscillation problems on the UH and IUH. In this method, the SG filter parameters are selected to give the minimum influence on smoothing and differentiation. Based on runoff reproduction results and performance criteria, it appears that the SG filter performed both smoothing and differentiation without the remarkable variation of hydrograph properties such as peak or time-to peak. The IUH, UH, and S-curve were estimated using storm data from two watersheds. The reproduced runoffs showed high levels of model performance criteria. In addition, the analyses of two other watersheds revealed that small watershed areas may experience scale problems. The proposed method is believed to be valuable when error-prone data are involved in analyzing the linear rainfall–runoff relationship.

scholarly journals Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach

2005 ◽  
Vol 2 (3) ◽  
pp. 639-690 ◽  
Author(s):  
G. P. Zhang ◽  
H. H. G. Savenije
Keyword(s):  
River Basin ◽  
Overland Flow ◽  
Model Performance ◽  
Source Area ◽  
Subsurface Water ◽  
Watershed Hydrology ◽  
Rainfall Runoff ◽  
Data Set ◽  
Physically Based ◽  
Infiltration Excess

Abstract. Based on the Representative Elementary Watershed (REW) approach, the modelling tool REWASH (Representative Elementary WAterShed Hydrology) has been developed and applied to the Geer river basin. REWASH is deterministic, semi-distributed, physically based and can be directly applied to the watershed scale. In applying REWASH, the river basin is divided into a number of sub-watersheds, so called REWs, according to the Strahler order of the river network. REWASH describes the dominant hydrological processes, i.e. subsurface flow in the unsaturated and saturated domains, and overland flow by the saturation-excess and infiltration-excess mechanisms. Through flux exchanges among the different spatial domains of the REW, surface and subsurface water interactions are fully coupled. REWASH is a parsimonious tool for modelling watershed hydrological response. However, it can be modified to include more components to simulate specific processes when applied to a specific river basin where such processes are observed or considered to be dominant. In this study, we have added a new component to simulate interception using a simple parametric approach. Interception plays an important role in the water balance of a watershed although it is often disregarded. In addition, a refinement for the transpiration in the unsaturated zone has been made. Finally, an improved approach for simulating saturation overland flow by relating the variable source area to both the topography and the groundwater level is presented. The model has been calibrated and verified using a 4-year data set, which has been split into two for calibration and validation. The model performance has been assessed by multi-criteria evaluation. This work is the first full application of the REW approach to watershed rainfall-runoff modelling in a real watershed. The results demonstrate that the REW approach provides an alternative blueprint for physically based hydrological modelling.

A case study of heavy PM2.5 secondary formation by N2O5 nocturnal chemistry in Seoul, Korea in January 2018: Model performance and error analysis

2021 ◽  
pp. 105951
Author(s):  
Hyun-Young Jo ◽  
Hyo-Jung Lee ◽  
Yu-Jin Jo ◽  
Gookyoung Heo ◽  
Meehye Lee ◽  
...  
Keyword(s):  
Error Analysis ◽  
Model Performance ◽  
Secondary Formation

scholarly journals Landscape Controls on Nutrient Export during Snowmelt and an Extreme Rainfall Runoff Event in Northern Agricultural Watersheds

2019 ◽  
Vol 48 (4) ◽  
pp. 841-849 ◽  
Author(s):  
Henry F. Wilson ◽  
Nora J. Casson ◽  
Aaron J. Glenn ◽  
Pascal Badiou ◽  
Lyle Boychuk
Keyword(s):  
Extreme Rainfall ◽  
Agricultural Watersheds ◽  
Nutrient Export ◽  
Rainfall Runoff ◽  
Runoff Event

scholarly journals The HYDROMED model and its application to semi-arid Mediterranean catchments with hill reservoirs 2: Rainfall-runoff model applications to three Mediterranean hill reservoirs

2001 ◽  
Vol 5 (4) ◽  
pp. 554-562 ◽  
Author(s):  
R. Ragab ◽  
D. Moidinis ◽  
J. Albergel ◽  
J. Khouri ◽  
A. Drubi ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Performance ◽  
Limited Information ◽  
Rainfall Runoff ◽  
Significant Events ◽  
Reliable Parameter ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

Abstract. The objective of this work was to assess the performance of the newly developed HYDROMED model. Three catchments with hill reservoirs were selected. They are El-Gouazine and Kamech in Tunisia and Es Sindiany in Syria. The rainfall, the spillway flow and volume of water in the reservoirs were used as input to the model. Events that generated spillway flow were preferred for calibration. The results confirmed that the HYDROMED model is capable of reproducing the runoff volume at all the three sites. In calibrating single events, the model performance was high as measured by the Nash-Sutcliffe criterion for goodness of fit. In some events this value was as high as 98%. In simulation mode, the highest Nash-Sutcliffe criterion value was close to 70% in the El-Gouazine and Kamech catchments and close to 50% in the Es Sindiany catchment. Given the limited information available, especially on the unrecorded releases in the three catchments, the hydrological impact of site geology (e.g. Kamech), the unrecorded operator intervention during the spillway flow (e.g. Es Sindiany) and other unaccounted factors (e.g siltation, evaporation, etc.), these results are by and large very encouraging. However, they could be further improved as and when more information on the unrecorded parameters becomes available. Additionally, the results of this work highlighted the need for long term records with a large number of significant events that are able to generate spillway flow to obtain more consistent and reliable parameter values. It also highlights the need for more accurately recorded releases for irrigation and other uses. As these results are encouraging, more tests on those three and other sites are planned. Keywords: HYDROMED, rainfall-runoff model, Mediterranean, conceptual model

scholarly journals Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India

Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 32 ◽  
Author(s):  
Nag ◽  
Biswal
Keyword(s):  
Model Performance ◽  
Data Availability ◽  
Ungauged Basins ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Study Region ◽  
Calibration Free ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Free Dynamic

Construction of flow duration curves (FDCs) is a challenge for hydrologists as most streams and rivers worldwide are ungauged. Regionalization methods are commonly followed to solve the problem of discharge data scarcity by transforming hydrological information from gauged basins to ungauged basins. As a consequence, regionalization-based FDC predictions are not very reliable where discharge data are scarce quantitatively and/or qualitatively. In such a scenario, it is perhaps more meaningful to use a calibration-free rainfall‒runoff model that can exploit easily available meteorological information to predict FDCs in ungauged basins. This hypothesis is tested in this study by comparing a well-known regionalization-based model, the inverse distance weighting (IDW) model, with the recently proposed calibration-free dynamic Budyko model (DB) in a region where discharge observations are not only insufficient quantitatively but also show apparent signs of observational errors. The DB model markedly outperformed the IDW model in the study region. Furthermore, the IDW model’s performance sharply declined when we randomly removed discharge gauging stations to test the model in a variety of data availability scenarios. The analysis here also throws some light on how errors in observational datasets and drainage area influence model performance and thus provides a better picture of the relative strengths of the two models. Overall, the results of this study support the notion that a calibration-free rainfall‒runoff model can be chosen to predict FDCs in discharge data-scarce regions. On a philosophical note, our study highlights the importance of process understanding for the development of meaningful hydrological models.

An experimental approach to reduce the parametric dimensionality for rainfall–runoff models

2016 ◽  
Vol 48 (1) ◽  
pp. 48-65 ◽  
Author(s):  
Jie Chen ◽  
Richard Arsenault ◽  
François P. Brissette
Keyword(s):  
Experimental Approach ◽  
Model Performance ◽  
Optimal Number ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Efficiency Criterion ◽  
Performance Loss ◽  
The Past ◽  
Multi Objective Genetic Algorithm

Sobol’ sensitivity analysis has been used successfully in the past to reduce the parametric dimensionality for hydrological models. However, the effects of its limitation, in that it assumes an independence of parameters, need to be investigated. This study proposes an experimental approach to assess the commonly used Sobol’ analysis for reducing the parameter dimensionality of hydrological models. In this approach, the number of model parameters is directly pitted against an efficiency criterion within a multi-objective genetic algorithm (MOGA), thus allowing both the identification of key model parameters and the optimal number of parameters to be used within the same analysis. The proposed approach was tested and compared with the Sobol’ method based on a conceptual lumped hydrological model (HSAMI) with 23 free parameters. The results show that both methods performed very similarly, and allowed 11 out of 23 HSAMI parameters to be reduced with little loss in model performance. Based on this comparison, Sobol’ appears to be an effective and robust method despite its limitations. On the other hand, the MOGA algorithm outperformed Sobol’ analysis for further reduction of the parametric space and found optimal solutions with as few as eight parameters with minimal performance loss in validation.

scholarly journals Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs

2011 ◽  
Vol 12 (5) ◽  
pp. 1100-1112 ◽  
Author(s):  
J. Vaze ◽  
D. A. Post ◽  
F. H. S. Chiew ◽  
J.-M. Perraud ◽  
J. Teng ◽  
...  
Keyword(s):  
Model Simulation ◽  
Model Performance ◽  
Daily Rainfall ◽  
Grid Cell ◽  
Rainfall Series ◽  
Data Availability ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.

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