Performance Evaluation of Physically Based Distributed Hydrologic Models and Lumped Hydrologic Models

2004 ◽  
Author(s):  
E. A. Meselhe ◽  
E. Habib ◽  
O. C. Oche ◽  
S. Gautam
Keyword(s):  
Performance Evaluation ◽  
Hydrologic Models ◽  
Physically Based

Sensitivity of Conceptual and Physically Based Hydrologic Models to Temporal and Spatial Rainfall Sampling

2009 ◽  
Vol 14 (7) ◽  
pp. 711-720 ◽  
Author(s):  
E. A. Meselhe ◽  
E. H. Habib ◽  
O. C. Oche ◽  
S. Gautam
Keyword(s):  
Hydrologic Models ◽  
Physically Based ◽  
Temporal And Spatial

A New Physically Based Self-Calibrating Palmer Drought Severity Index and its Performance Evaluation

2015 ◽  
Vol 29 (13) ◽  
pp. 4833-4847 ◽  
Author(s):  
Yi Liu ◽  
Xiaoli Yang ◽  
Liliang Ren ◽  
Fei Yuan ◽  
Shanhu Jiang ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Severity ◽  
Physically Based ◽  
Drought Severity Index

scholarly journals Modeling Hydrologic Phenomena [Free opinion]

2005 ◽  
Vol 9 (4) ◽  
pp. 421-434 ◽  
Author(s):  
J. Ganoulis
Keyword(s):  
Large Scale ◽  
Stokes Equations ◽  
Proper Time ◽  
Black Box ◽  
Fickian Diffusion ◽  
Hydrologic Models ◽  
Time And Space ◽  
Expert Opinions ◽  
Physically Based ◽  
Empirical Coefficients

With the aim of suggesting some practical rules for the use of hydrological models, G. De MARSILY in his "free opinion" (Rev. Sci. Eau 1994, 7(3): 219-234) proposes a classification of hydrologic models into two categories: - models built on data (observable phenomena) and ; - models without any available observations (unobservable phenomena). He claims that for the former group of observable phenomena, models developed through a learning process as well as those based on the underlying physical laws are of the black box type. For the latter group of unobservable phenomena, he suggests that physically-based hydrologic models be developed. Physically-based hydrologic models should introduce to the phenomenological laws the correct empirical coefficients, which correspond to the proper time and space scales (GANOULIS, 1986). Well-known examples are Darcy's permeability coefficient on the macroscopic scale as derived from the Navier-Stokes equations on the local scale and the macroscopic dispersion coefficients in comparison with the local Fickian diffusion coefficients. Misuse of these models by confusing the proper time and space scales and determining the coefficients by calibration is not a sufficient reason to consider them as belonging to the black box type. Black box type hydrologic models, although very useful when data are available, remain formally empirical. They fail to give correct answers when serious constraints of unity in place, time and action are not fulfilled. Concerning the second class of models, we may notice that purely unobservable phenomena without any available data do not really exist in hydrology. In the case of very rare events and complex systems, such as radioactivity impacts and forecasting of changes on a large scale, physically-based models with adequate parameters may be used to integrate scarce information from experiments and expert opinions in a Bayesian probabilistic framework (APOSTOLAKIS, 1990). The most important feature of hydrologic models capable of describing real hydrologic phenomena, is the possibility of handling imprecision and natural variabilities. Uncertainties may be seen in two categories: aleatory or noncognitive, and epistemic or cognitive. Probabilistic hydrologic models are more suitable for dealing with aleatory uncertainties. Fuzzy logic-based models may quantify epistemic uncertainties (GANOULIS et al., 1996). The stochastic and fuzzy modeling approaches are briefly explained in this free opinion as compared to the deterministic physically-based hydrologic modeling.

scholarly journals Regionalization of subsurface stormflow parameters of hydrologic models: Up-scaling from physically based numerical simulations at hillslope scale

2014 ◽  
Vol 519 ◽  
pp. 683-698 ◽  
Author(s):  
Melkamu Ali ◽  
Sheng Ye ◽  
Hong-yi Li ◽  
Maoyi Huang ◽  
L. Ruby Leung ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Hydrologic Models ◽  
Physically Based ◽  
Hillslope Scale ◽  
Up Scaling

scholarly journals Verification of Regional Deterministic Precipitation Analysis products using snow data assimilation for application in meteorological network assessment in sparsely gauged Nordic basins

2021 ◽  
Author(s):  
Kian Abbasnezhadi ◽  
Alain N. Rousseau ◽  
Étienne Foulon ◽  
Stéphane Savary
Keyword(s):  
Flow Simulation ◽  
State Variables ◽  
Hydrologic Models ◽  
Flow Estimation ◽  
Estimation Uncertainty ◽  
Observation Network ◽  
Physically Based ◽  
Precipitation Analysis ◽  
The Impact ◽  
Observation Networks

AbstractSparse precipitation information can result in uncertainties in hydrological modelling practices. Precipitation observation network augmentation is one way to reduce the uncertainty. Meanwhile, in basins with snowpack-dominated hydrology, in the absence of a high-density precipitation observation network, assimilation of in situ and remotely sensed measurements of snowpack state variables can also provide the possibility to reduce flow estimation uncertainty. Similarly, assimilation of existing precipitation observations into gridded numerical precipitation products can alleviate the adverse effects of missing information in poorly instrumented basins. In Canada, the Regional Deterministic Precipitation Analysis (RDPA) data from the Canadian Precipitation Analysis (CaPA) system have been increasingly applied for flow estimation in sparsely gauged Nordic basins. Moreover, CaPA-RDPA data have also been applied to establish observational priorities for augmenting precipitation observation networks. However, the accuracy of the assimilated data should be validated before being applicable in observation network assessment. The assimilation of snowpack state variables has proven to significantly improve streamflow estimates, and therefore, it can provide the benchmark against which the impact of assimilated precipitation data on streamflow simulation can be compared. Therefore, this study introduces a parsimonious framework for performing a proxy-validation of the precipitation assimilated products through the application of snow assimilation in physically-based hydrologic models. This framework is demonstrated to assess the observation networks in three boreal basins in Yukon, Canada. The results indicate that in most basins, the gridded analysis products generally enjoyed the level of accuracy required for accurate flow simulation and therefore were applied in the meteorological network assessment in those cases.

scholarly journals Investigating Parameter Transferability across Models and Events for a Semiarid Mediterranean Catchment

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2261 ◽  
Author(s):  
Enrica Perra ◽  
Monica Piras ◽  
Roberto Deidda ◽  
Giuseppe Mascaro ◽  
Claudio Paniconi
Keyword(s):  
Soil Layer ◽  
Model Performance ◽  
Hydrologic Models ◽  
Integration Model ◽  
Soil Crusting ◽  
Kinematic Approximation ◽  
Top Soil ◽  
Physically Based ◽  
Simplifying Assumptions ◽  
One Year

Physically based distributed hydrologic models (DHMs) simulate watershed processes by applying physical equations with a variety of simplifying assumptions and discretization approaches. These equations depend on parameters that, in most cases, can be measured and, theoretically, transferred across different types of DHMs. The aim of this study is to test the potential of parameter transferability in a real catchment for two contrasting periods among three DHMs of varying complexity. The case study chosen is a small Mediterranean catchment where the TIN-based Real-time Integrated Basin Simulator (tRIBS) model was previously calibrated and tested. The same datasets and parameters are used here to apply two other DHMs—the TOPographic Kinematic Approximation and Integration model (TOPKAPI) and CATchment HYdrology (CATHY) models. Model performance was measured against observed discharge at the basin outlet for a one-year period (1930) corresponding to average wetness conditions for the region, and for a much drier two-year period (1931–1932). The three DHMs performed comparably for the 1930 period but showed more significant differences (the CATHY model in particular for the dry period. In order to improve the performance of CATHY for this latter period, an hypothesis of soil crusting was introduced, assigning a lower saturated hydraulic conductivity to the top soil layer. It is concluded that, while the physical basis for the three models allowed transfer of parameters in a broad sense, transferability can break down when simulation conditions are greatly altered.

scholarly journals Effect of time scale on flood simulation: maximum rainfall intensity and fractal theory based time disaggregation method for rainfall

2020 ◽  
Vol 20 (8) ◽  
pp. 3585-3596
Author(s):  
Hanchen Zhang ◽  
Weijiang Zhang
Keyword(s):  
Time Scale ◽  
Rainfall Intensity ◽  
Fractal Theory ◽  
Rainfall Data ◽  
Distributed Hydrological Model ◽  
Hydrologic Models ◽  
Self Similarity ◽  
Flood Simulation ◽  
Maximum Rainfall ◽  
Physically Based

Abstract The time scale of rainfall data limits the accuracy and application scope of hydrologic models, especially when low-accuracy observed rainfall data are used in physically based distributed hydrologic models. In this study, an optimized rainfall method based on maximum rainfall intensity and self-similarity was established to provide different rainfall data for the physically based distributed hydrological model. The results showed the following: (1) the increase of time scale resulted in decreased rainfall intensity and an evenly distributed rainfall pattern; (2) the established disaggregation method for rainfall well described the uneven distribution in time; (3) the influence of time scale could be divided into 1–20, 20–120, and 120–360 min; (4) the conversion method between rainfall intensity and saturated hydraulic conductivity was effective at ensuring the physical meaning of the parameters on a time scale of 20–90 min. Furthermore, results showed that the reasonable time scale of application of the CASC2D model is less than 120 min. For longer time scales, the model was able to simulate peak discharge but unable to describe the flood process.

Performance evaluation of a physically based model for shallow landslide prediction

Landslides ◽  
2016 ◽  
Vol 14 (3) ◽  
pp. 961-980 ◽  
Author(s):  
Jui-Yi Ho ◽  
Kwan Tun Lee
Keyword(s):  
Performance Evaluation ◽  
Shallow Landslide ◽  
Landslide Prediction ◽  
Physically Based Model ◽  
Physically Based

scholarly journals Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1214 ◽  
Author(s):  
Simon Ricard ◽  
François Anctil
Keyword(s):  
Wind Speed ◽  
Water Availability ◽  
Reference Evapotranspiration ◽  
Low Flow ◽  
Hydrologic Response ◽  
Hydrologic Models ◽  
Suggested Approach ◽  
Hydrologic Processes ◽  
Calibration And Validation ◽  
Physically Based

The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

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