Evaluation of three semi-distributed hydrological models in simulating discharge from a small forest and arable dominated catchment

Biologia ◽  
2017 ◽  
Vol 72 (9) ◽  
Author(s):  
Ilona Kása ◽  
Györgyi Gelybó ◽  
Ágota Horel ◽  
Zsófia Bakacsi ◽  
Eszter Tóth ◽  
...  
Keyword(s):  
Model Performance ◽  
Coefficient Of Determination ◽  
Lake Balaton ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Discharge Data ◽  
Flow Duration Curves ◽  
Distributed Hydrological Models ◽  
Intercomparison Study ◽  
Light Precipitation

AbstractCatchment scale hydrological models are promising tools for simulating the effect of catchment-specific processes and management on soil and water resources. Here, we present a model intercomparison study of runoff simulations using three different semi-distributed rainfall-runoff catchment models. The objective of this study was to demonstrate the applicability of the Hydrologiska Byrans Vattenavdelning (HBV-Light); Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport (PERSiST); and INtegrated CAtchment (INCA) models on Somogybabod Catchment, near Lake Balaton, Hungary.The models were calibrated and validated against observed discharge data at the outlet of the catchment for the period of January 1, 2006 –July 12, 2015. Model performance was evaluated using graphical representations, e.g. daily and monthly hydrographs and Flow Duration Curves (FDC) and model evaluation statistic; Nash–Sutcliffe efficiency (NSE) and coefficient of determination (

scholarly journals Performance of HEC-HMS and SWAT to simulate streamflow in the sub-humid tropical Hemavathi catchment

2021 ◽  
Author(s):  
N. C. Sanjay Shekar ◽  
D. C. Vinay
Keyword(s):  
Model Calibration ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Curve Number ◽  
Coefficient Of Determination ◽  
Hydrological Models ◽  
Daily Streamflow ◽  
Compensation Factor ◽  
Elevation Model

Abstract The present study was conducted to examine the accuracy and applicability of the hydrological models Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center (HEC)- Hydrologic Modeling System (HMS) to simulate streamflows. Models combined with the ArcGIS interface have been used for hydrological study in the humid tropical Hemavathi catchment (5,427 square kilometer). The critical focus of the streamflow analysis was to determine the efficiency of the models when the models were calibrated and optimized using observed flows in the simulation of streamflows. Daily weather gauge stations data were used as inputs for the models from 2014–2020 period. Other data inputs required to run the models included land use/land cover (LU/LC) classes resulting from remote sensing satellite imagery, soil map and digital elevation model (DEM). For evaluating the model performance and calibration, daily stream discharge from the catchment outlet data were used. For the SWAT model calibration, available water holding capacity by soil (SOL_AWC), curve number (CN) and soil evaporation compensation factor (ESCO) are identified as the sensitive parameters. Initial abstraction (Ia) and lag time (Tlag) are the significant parameters identified for the HEC-HMS model calibration. The models were subsequently adjusted by autocalibration for 2014–2017 to minimize the variations in simulated and observed streamflow values at the catchment outlet (Akkihebbal). The hydrological models were validated for the 2018–2020 period by using the calibrated models. For evaluating the simulating daily streamflows during calibration and validation phases, performances of the models were conducted by using the Nash-Sutcliffe model efficiency (NSE) and coefficient of determination (R2). The SWAT model yielded high R2 and NSE values of 0.85 and 0.82 for daily streamflow comparisons for the catchment outlet at the validation time, suggesting that the SWAT model showed relatively good results than the HEC-HMS model. Also, under modified LU/LC and ungauged streamflow conditions, the calibrated models can be later used to simulate streamflows for future predictions. Overall, the SWAT model seems to have done well in streamflow analysis capably for hydrological studies.

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

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 On the evaluation of both spatial and temporal performance of distributed hydrological models

2021 ◽  
Author(s):  
Tam Nguyen ◽  
AN TRAN ◽  
Bhumika Uniyal ◽  
Thuc Phan
Keyword(s):  
Performance Evaluation ◽  
Spatial Model ◽  
Model Performance ◽  
Temporal Patterns ◽  
Hydrological Models ◽  
Spatiotemporal Model ◽  
Model Performance Evaluation ◽  
Distributed Approach ◽  
Temporal Model ◽  
Distributed Hydrological Models

Evaluating the spatial and temporal model performance of distributed hydrological models is necessary to ensure that the simulated spatial and temporal patterns are meaningful. In recent years, spatial and temporal remote sensing data have been increasingly used for model performance evaluation. Previous studies, however, have focused on either the temporal or spatial model performance evaluation. In addition, temporal (or spatial) model performance evaluation is often done in a spatially (or temporally) lumped approach. Here, we evaluated (1) the temporal model performance evaluation in a spatially distributed approach (spatiotemporal) and (2) the spatial model performance in a temporally distributed approach (temporospatial) model performance evaluation. This study demonstrated that both spatiotemporal and temporospatial model performance evaluations are necessary since they provide different aspects of the model performance. For example, spatiotemporal model performance evaluation helps in detecting the areas with an issue in the simulated temporal patterns. However, temporospatial model performance evaluation helps in detecting the time with an issue in the simulated spatial patterns. The results also show that an increase in the spatiotemporal model performance will not necessarily lead to an increase in the temporospatial model performance and vice versa, depending on the evaluation statistics. Overall, this study has highlighted the necessity of a joint spatiotemporal and temporospatial model performance evaluation to understand/improve spatial and temporal model behavior/performance.

scholarly journals The importance of topography controlled sub-grid process heterogeneity in distributed hydrological models

2015 ◽  
Vol 12 (12) ◽  
pp. 13301-13358 ◽  
Author(s):  
R. C. Nijzink ◽  
L. Samaniego ◽  
J. Mai ◽  
R. Kumar ◽  
S. Thober ◽  
...  
Keyword(s):  
Expert Knowledge ◽  
Model Performance ◽  
Hydrologic Model ◽  
Low Flow ◽  
Evaluation Procedure ◽  
Base Case ◽  
Hydrological Process ◽  
Hydrological Models ◽  
Knowledge Based ◽  
Distributed Hydrological Models

Abstract. Heterogeneity of landscape features like terrain, soil, and vegetation properties affect the partitioning of water and energy. However, it remains unclear to which extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated in the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge based model constraints reduces model uncertainty; and (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both, the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as overall measure for model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 % respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. Besides, it was shown that suitable semi-quantitative prior constraints in combination with the transfer function based regularization approach of mHM, can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

Investigating the reasons for poor model performance in a changing climate

2020 ◽  
Author(s):  
Doris Duethmann ◽  
Günter Blöschl ◽  
Juraj Parajka
Keyword(s):  
Climate Change ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Model Performance ◽  
Model Structure ◽  
Precipitation Data ◽  
Hydrological Models ◽  
Discharge Data ◽  
Climate Conditions ◽  
Changing Climate

<p>Hydrological models are often applied to estimate climate change impacts on hydrology. However, several studies demonstrated that hydrological models do not perform well when applied under changing climate conditions. In order to decide on the way forward for improving hydrological modelling in climate change contexts, it is important to understand the reasons for poor performance in a changing climate, but there are only a few studies on this topic.</p><p>Here we revisit a study in Austria that demonstrated the inability of a conceptual model to simulate the discharge response to increases in precipitation and air temperature. We set up hypotheses for the differences between the observed and simulated changes in discharge and test these using simulations with various modifications of the model (including modifications of the input data, model calibration, and model structure).</p><p>The baseline model overestimates discharge trends over 1978−2013, on average over all 156 catchments, by 93 ± 50 mm yr<sup>−1</sup> per 35 years. Accounting for vegetation dynamics in the calculation of reference evaporation based on a satellite-derived vegetation index, reduces the difference between simulated and observed discharge by 35 ± 9 mm yr<sup>−1</sup> per 35 years. Inhomogeneities in the precipitation data, caused by a variable number of stations and, to a lesser degree, climate variability effects on the undercatch error, can explain 44 ± 28 mm yr<sup>−1</sup> per 35 years of this difference. Extending the calibration period from 5 to 25 years, varying the objective function by including annually aggregated discharge data, or estimating evaporation with the Penman-Monteith instead of the Blaney-Criddle approach has little influence on the simulated discharge trends. The model structure problem with respect to vegetation dynamics has important implications for studies in a climate change context. Our results furthermore highlight the importance of using precipitation data based on a stationary input station network for studying observed hydrologic changes.</p>

Behind the scenes of runoff performance

2020 ◽  
Author(s):  
Tanja de Boer-Euser ◽  
Laurène Bouaziz ◽  
Guillaume Thirel ◽  
Lieke Melsen ◽  
Joost Buitink ◽  
...  
Keyword(s):  
Model Comparison ◽  
Remotely Sensed ◽  
Hydrological Models ◽  
Catchment Scale ◽  
Process Representation ◽  
Complex Interactions ◽  
International Model ◽  
Internal States ◽  
Short Term Forecasting ◽  
Intercomparison Study

<p>Hydrological models are valuable tools for short-term forecasting of river flows, long-term predictions for water resources management and to increase our understanding of the complex interactions of water storage and release processes at the catchment scale. Hydrological models provide relatively robust estimates of streamflow dynamics, as shown by the countless applications in many regions across the world. However, various model structures can lead to similar aggregated outputs, i.e. model equifinality. To provide reliable estimates, it is of critical importance that not only the aggregated response but also the internal behaviors are consistent with their real-world equivalents. In a previous international comparison study (de Boer-Euser et al., 2017), eight research groups followed the same protocol to calibrate their twelve models on streamflow for several catchments within the Meuse basin. In the current study, we hypothesize that these twelve process-based models with similar runoff performance have similar representations of internal states and fluxes. We test our hypothesis by comparing internal states and fluxes between models and we assess their plausibility using remotely-sensed products of actual evaporation, snow cover, soil moisture and total storage anomalies. Our results indicate that models with similar runoff performance represent internal states and fluxes differently. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Using remotely-sensed products, the plausibility of process representation could only be evaluated to some extent as many variables remain unknown, highlighting the need for more experimental research. The study further emphasizes the value of multi-model, multi-parameter studies to reveal to decision-makers the uncertainty inherent to the lack of evaluation data and the heterogeneous hydrological landscape.</p><p>References:<br>de Boer-Euser, T., Bouaziz, L., De Niel, J., Brauer, C., Dewals, B., Drogue, G., Fenicia, F., Grelier, B., Nossent, J., Pereira, F., Savenije, H., Thirel, G., and Willems, P.: Looking beyond general metrics for model comparison – lessons from an international model intercomparison study, Hydrol. Earth Syst. Sci., 21, 423–440, https://doi.org/10.5194/hess-21-423-2017, 2017.</p>

scholarly journals Theoretical Hydrokinetic Power Potential Assessment of the U-Tapao River Basin Using GIS

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1749
Author(s):  
Fida Ali ◽  
Chatchawin Srisuwan ◽  
Kuaanan Techato ◽  
Adul Bennui ◽  
Tanita Suepa ◽  
...  
Keyword(s):  
River Basin ◽  
New Technologies ◽  
Assessment Tool ◽  
Model Performance ◽  
Coefficient Of Determination ◽  
Lake Basin ◽  
Discharge Data ◽  
Flow Estimation ◽  
Southern Thailand ◽  
Water Assessment

Conventional hydropower technologies such as dams have been criticized due to their negative environmental effects which have necessitated the development of new technologies for sustainable development of hydropower energy. Hydrokinetic (HK) energy is one such emerging renewable energy technology and, in this study, a theoretical potential assessment was done using a Geographic Information System (GIS) and Soil and Water Assessment Tool (SWAT) hydrological model, for the U-Tapao river basin (URB), a major tributary of the Songkhla lake basin (SLB) in southern Thailand. The SWAT was calibrated and validated with SWAT calibration and uncertainty (SWAT-CUP)-SUFI 2 programs using the observed discharge data from the gauging stations within the watershed. The model performance was evaluated based on the Nash–Sutcliffe efficiency (NSE) and the coefficient of determination (R2) values, achieving 0.62 and 0.60, respectively, for calibration, and 0.65 and 0.68 for validation which is considered acceptable and can be used to represent flow estimation. The theoretical HK potential was estimated to be 71.9 MW along the 77.18 km U-Tapao river, which could be developed as a renewable and reliable energy source for the communities living around the river. The method developed could also be applied to river systems around the world for resource and time efficient HK potential assessments.

scholarly journals The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models

2016 ◽  
Vol 20 (3) ◽  
pp. 1151-1176 ◽  
Author(s):  
Remko C. Nijzink ◽  
Luis Samaniego ◽  
Juliane Mai ◽  
Rohini Kumar ◽  
Stephan Thober ◽  
...  
Keyword(s):  
Expert Knowledge ◽  
Model Performance ◽  
Hydrologic Model ◽  
Low Flow ◽  
Evaluation Procedure ◽  
Base Case ◽  
Hydrological Process ◽  
Hydrological Models ◽  
Knowledge Based ◽  
Distributed Hydrological Models

Abstract. Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

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