scholarly journals Streamflow characteristics from modeled runoff time series – importance of calibration criteria selection

2017 ◽  
Vol 21 (11) ◽  
pp. 5443-5457 ◽  
Author(s):  
Sandra Pool ◽  
Marc J. P. Vis ◽  
Rodney R. Knight ◽  
Jan Seibert
Keyword(s):  
Time Series ◽  
Model Calibration ◽  
Performance Metrics ◽  
Low Flow ◽  
Flow Conditions ◽  
Ungauged Catchments ◽  
Calibration Process ◽  
Model Efficiency ◽  
Runoff Model ◽  
Calibration Approach

Abstract. Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

scholarly journals Streamflow characteristics from modelled runoff time series – importance of calibration criteria selection

2016 ◽  
Author(s):  
Sandra Pool ◽  
Marc J. P. Vis ◽  
Rodney R. Knight ◽  
Jan Seibert
Keyword(s):  
Model Calibration ◽  
Performance Metrics ◽  
Model Performance ◽  
Specific Model ◽  
Low Flow ◽  
Flow Conditions ◽  
Ungauged Catchments ◽  
Practical Applications ◽  
Runoff Model ◽  
Calibration Approach

Abstract. Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models. Estimated SFCs can be substantially uncertain when models are calibrated using traditional approaches based on minimization or maximization of statistical performance metrics (e.g. Nash–Sutcliffe efficiency). To evaluate model performance, we tested how well SFCs are simulated when the model objective function was calibrated using one or more SFCs. We calibrated a bucket-type runoff model for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 selected SFCs representing major flow regime components and different flow conditions. While the model tends to underestimate SFCs related to mean and high-flow conditions, SFCs related to low flow are overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional Nash–Sutcliffe efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration and modelled estimates need to be carefully interpreted.

scholarly journals Objective functions used as performance metrics for hydrological models: state-of-the-art and critical analysis

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Paloma Mara de Lima Ferreira ◽  
Adriano Rolim da Paz ◽  
Juan Martín Bravo
Keyword(s):  
Time Series ◽  
Model Calibration ◽  
Hydrological Model ◽  
Performance Metrics ◽  
Low Flow ◽  
Hydrological Models ◽  
Objective Functions ◽  
Flow Rates ◽  
Daily Streamflow ◽  
Synthetic Time Series

ABSTRACT Hydrological models (HMs) can be applied for different purposes, and a key step is model calibration using objective functions (OF) to quantify the agreement between observed and calculated discharges. Fully understanding the OF is important to properly take advantage of model calibration and interpret the results. This study evaluates 36 OF proposed in the literature, considering two watersheds of different hydrological regimes. Daily simulated streamflow time-series, using a distributed hydrological model (MGB-IPH), and ten daily streamflow synthetic time-series, generated from the observed and calculated streamflows, were used in the analysis of each watershed. These synthetic data were used to evaluate how does each metric evaluate hypothetical cases that present isolated very well known error behaviors. Despite of all NSE-derived (Nash-Sutcliffe efficiency) metrics that use the square of the residuals in their formulation have shown higher sensitivity to errors in high flows, the ones that use daily and monthly averages of flow rates in absolute terms were more stringent than the others to assess HMs performance. Low flow errors were better evaluated by metrics that use the flow logarithm. The constant presence of zero flow rates deteriorate them significantly, with the exception of the metrics TRMSE (Transformed root mean square error) did not demonstrate this problem. An observed limitation of the formulations of some metrics was that the errors of overestimation or underestimation are compensated. Our results reassert that each metric should be interpreted specifically thinking about the aspects it has been proposed for, and simultaneously taking into account a set of metrics would lead to a broader evaluation of HM ability (e.g. multiobjective model evaluation). We recommend that the use of synthetic time series as those proposed in this work could be useful as an auxiliary step towards better understanding the evaluation of a calibrated hydrological model for each study case, taking into account model capabilities and observed hydrologic regime characteristics.

scholarly journals Hydrologic similarity among catchments under variable flow conditions

2011 ◽  
Vol 15 (3) ◽  
pp. 989-997 ◽  
Author(s):  
S. Patil ◽  
M. Stieglitz
Keyword(s):  
Spatial Variability ◽  
Coefficient Of Variation ◽  
Low Flow ◽  
Flow Conditions ◽  
Ungauged Catchments ◽  
Evaporative Demand ◽  
Similar Reduction ◽  
Stream Response ◽  
Flow Duration Curves ◽  
Regional Similarity

Abstract. An assessment of regional similarity in catchment stream response is often needed for accurate predictions in ungauged catchments. However, it is not clear whether similarity among catchments is preserved at all flow conditions. We address this question through the analysis of flow duration curves for 25 gauged catchments located across four river basins in the northeast United States. The coefficient of variation of streamflow percentiles is used as a measure of variability among catchments across flow conditions. Results show that similarity in catchment stream response is dynamic and highly dependent on flow conditions. Specifically, within each of the four basins, the coefficient of variation is high at low flow percentiles and gradually reduces for higher flow percentiles. Analysis of the inter-annual variation in streamflow percentiles shows a similar reduction in variability from low flow to high flow percentiles. Greater similarity in streamflows is observed during the winter and spring (wet) seasons compared to the summer and fall (dry) seasons. Results suggest that the spatial variability in streamflow at low flows is primarily controlled by the dominance of high evaporative demand during the warm period. On the other hand, spatial variability at high flows during the cold period is controlled by the increased dominance of precipitation input over evapotranspiration. By evaluating variability over the entire range of streamflow percentiles, this work explores the nature of hydrologic similarity from a seasonal perspective.

scholarly journals Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

2006 ◽  
Vol 10 (3) ◽  
pp. 353-368 ◽  
Author(s):  
J. Parajka ◽  
V. Naeimi ◽  
G. Blöschl ◽  
W. Wagner ◽  
R. Merz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Regional Scale ◽  
Hydrologic Model ◽  
Hydrologic Models ◽  
Ungauged Catchments ◽  
Soil Moisture Dynamics ◽  
Model Efficiency ◽  
The Relationship ◽  
Runoff Model ◽  
Moisture Dynamics

Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

scholarly journals Hydrologic similarity among catchments under variable flow conditions

2010 ◽  
Vol 7 (5) ◽  
pp. 8607-8630 ◽  
Author(s):  
S. Patil ◽  
M. Stieglitz
Keyword(s):  
Spatial Variability ◽  
Coefficient Of Variation ◽  
Low Flow ◽  
Flow Conditions ◽  
Ungauged Catchments ◽  
Evaporative Demand ◽  
Similar Reduction ◽  
Stream Response ◽  
Flow Duration Curves ◽  
Regional Similarity

Abstract. An assessment of regional similarity in catchment stream response is often needed for accurate predictions in ungauged catchments. However, it is not clear whether similarity among catchments is preserved at all flow conditions. We address this question through the analysis of flow duration curves for 25 gauged catchments located across four river basins in the northeast United States. The coefficient of variation of streamflow percentiles is used as a measure of variability among catchments across flow conditions. Results show that similarity in catchment stream response is dynamic and highly dependent on flow conditions. Specifically, within each of the four basins, the coefficient of variation is high at low flow percentiles and gradually reduces for higher flow percentiles. Analysis of the inter-annual variation in streamflow percentiles shows a similar reduction in variability from low flow to high flow percentiles. Greater similarity in streamflows is observed during the winter and spring (wet) seasons compared to the summer and fall (dry) seasons. Results suggest that the spatial variability in streamflow at low flows is primarily controlled by the dominance of high evaporative demand during the warm period. On the other hand, spatial variability at high flows during the cold period is controlled mostly by the increased dominance of precipitation input over evapotranspiration. By evaluating variability over the entire range of streamflow percentiles, this work explores the nature of hydrologic similarity from an inter-seasonal perspective.

scholarly journals Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

2005 ◽  
Vol 2 (6) ◽  
pp. 2739-2786 ◽  
Author(s):  
J. Parajka ◽  
V. Naeimi ◽  
G. Blöschl ◽  
W. Wagner ◽  
R. Merz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Regional Scale ◽  
Hydrologic Model ◽  
Hydrologic Models ◽  
Ungauged Catchments ◽  
Soil Moisture Dynamics ◽  
Model Efficiency ◽  
The Relationship ◽  
Runoff Model ◽  
Moisture Dynamics

Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

scholarly journals Value of uncertain streamflow observations for hydrological modelling

2018 ◽  
Vol 22 (10) ◽  
pp. 5243-5257 ◽  
Author(s):  
Simon Etter ◽  
Barbara Strobl ◽  
Jan Seibert ◽  
H. J. Ilja van Meerveld
Keyword(s):  
Time Series ◽  
Model Calibration ◽  
Model Performance ◽  
Error Distribution ◽  
Random Errors ◽  
Ungauged Catchments ◽  
Error Distributions ◽  
Data Points ◽  
Log Normal ◽  
Synthetic Time Series

Abstract. Previous studies have shown that hydrological models can be parameterised using a limited number of streamflow measurements. Citizen science projects can collect such data for otherwise ungauged catchments but an important question is whether these observations are informative given that these streamflow estimates will be uncertain. We assess the value of inaccurate streamflow estimates for calibration of a simple bucket-type runoff model for six Swiss catchments. We pretended that only a few observations were available and that these were affected by different levels of inaccuracy. The level of inaccuracy was based on a log-normal error distribution that was fitted to streamflow estimates of 136 citizens for medium-sized streams. Two additional levels of inaccuracy, for which the standard deviation of the error distribution was divided by 2 and 4, were used as well. Based on these error distributions, random errors were added to the measured hourly streamflow data. New time series with different temporal resolutions were created from these synthetic streamflow time series. These included scenarios with one observation each week or month, as well as scenarios that are more realistic for crowdsourced data that generally have an irregular distribution of data points throughout the year, or focus on a particular season. The model was then calibrated for the six catchments using the synthetic time series for a dry, an average and a wet year. The performance of the calibrated models was evaluated based on the measured hourly streamflow time series. The results indicate that streamflow estimates from untrained citizens are not informative for model calibration. However, if the errors can be reduced, the estimates are informative and useful for model calibration. As expected, the model performance increased when the number of observations used for calibration increased. The model performance was also better when the observations were more evenly distributed throughout the year. This study indicates that uncertain streamflow estimates can be useful for model calibration but that the estimates by citizen scientists need to be improved by training or more advanced data filtering before they are useful for model calibration.

scholarly journals Flood Estimation in Ungauged Catchment Using ENKI Simulation: A Case Study in Norway

10.29007/hrpj ◽  
2018 ◽  
Author(s):  
Yueyang Chen ◽  
Oddbjørn Bruland ◽  
Tiejian Li
Keyword(s):  
Efficiency Index ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Ungauged Catchment ◽  
Flood Estimation ◽  
Model Efficiency ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

This paper deals with flood estimation in ungauged catchment using continuous rainfall-runoff model. The rainfall-runoff model used in this study is developed based on the ENKI hydrological framework. In this study, flood estimation in ungauged catchment is based on transfer of parameter values from nearby station. The catchment used in this study to test the suitability of the ENKI system in flood estimation of ungauged catchment is the Gaula catchment located in Norway. This catchment has three main sub-catchments where flow records are available. The ENKI system is calibrated for each sub-catchment. In order to test its suitability in flood estimation, the average of the parameter set obtained from any of the two sub-catchments is used in the remaining sub-catchments. The performance of the ENKI system in flood estimation is evaluated in terms of the Nash–Sutcliffe (NSE) model efficiency index and the model ability to simulate the daily observed Annual Maximum Series (AMS). The result of this study shows that the ENKI framework has considerable potential in flood estimation in ungauged catchments.

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