Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

Dakhlaoui, Hamouda; Ruelland, Denis; Tramblay, Yves; Bargaoui, Zoubeïda

doi:10.1016/j.jhydrol.2017.04.032

Cited by 101 publications

(97 citation statements)

References 67 publications

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“…The results reported that the model with the multiperiod calibration approach exhibits considerable advantages over the conventional single‐period model under variational climatic conditions. Dakhlaoui et al () assessed the robustness of three conceptual rainfall‐runoff models in five basins under long‐term climate variability. The robustness of the models was evaluated using a differential split sample to cluster the calibration period into the climate‐contrasted subperiods.…”

Section: Introductionmentioning

confidence: 99%

A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations

Lan

Lin

Liu

et al. 2018

Water Resources Research

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One model structural deficiency is that some dynamic characteristics (such as seasonal dynamics) in catchment conditions are not explicitly represented by hydrological models. This study integrates data mining techniques to develop a clustering preprocessing framework for the subannual calibration of hydrological models to simulate seasonal dynamic behaviors. The proposed framework aims to solve the problems caused by missing processes and deficiencies of hydrological models, providing guidance for future model development. A set of climatic‐land surface indices is provided and preprocessed using the maximal information coefficient and the principal component analysis. Two clustering operations are performed based on the preprocessed climatic index and land‐surface index systems. Hydrological data are clustered into subannual periods for calibration. The parameters are independently optimized for each subperiod using a modified parallel calibration scheme and are then combined to generate a continuous simulation. The framework is applied in calibrating the TOPMODEL. The results show that the performance of the model with a clustering preprocessing framework in the middle‐ and low‐flow conditions is significantly improved without reducing the simulation accuracy for high flows. The transposability of the model parameters from the calibration to validation period has been improved significantly as well. The anomalous parameter values may be attributed in part to the convergence problem when using an optimization algorithm. Though well applied in the TOPMODEL, the framework has the potential to be used in other hydrological models.

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Section: Introductionmentioning

confidence: 99%

A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations

Lan

Lin

Liu

et al. 2018

Water Resources Research

View full text Add to dashboard Cite

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“…Calibration is the procedure adopted to obtain a set of optimal parameters and initial values that are adjusted to the particular characteristics of each basin (Dakhlaoui et al, 2017). The Nash Sutcliffe objective function -NSE [8] 130 (Wu et al, 2017) is considered a test for the goodness of fit of the hydrological prediction model, got by comparing between observed and simulated discharges (Dakhlaoui et al, 2017). Measured discharge was used as indicative variable, to be compared with model predictions of discharge, through the studied period.…”

Section: Calibration and Validationmentioning

confidence: 99%

Hydrological Modeling in Tropical Regions via TopModel. Study Case: Central Sector of the Middle Magdalena Valley - Colombia

Arenas-Bautista¹,

Arboleda-Obando²,

Duque-Gardeazabal³

et al. 2018

Preprint

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Hydrological modeling allows us to make a comprehensive assessment of the interaction between dynamics of the hydrological cycle, climate conditions, and land use. These modeling results are relevant in water resources management field. We use TopModel (TOPography based hydrological MODEL for the hydrological 15 modeling of an area of 17 000 km 2 in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia.This study is located in the intertropical convergence zone (ITCZ) which is characterized by special meteorological conditions and fast water fluxes over the year. This area has been subjected to significant land use changes, as a result of intense economic activities, e.g., agriculture, hydropower energy and oil & gas production (Avellaneda, 2003). The proposed model is based on a record of 12 years of: i.) daily precipitation data from observed gauges, ii.) 20 daily evapotranspiration data from temperature data and iii.) daily streamflow data as observed data. A calibration process was performed using data from 2000 to 2008, and a validation was performed with data from 2009 to 2012.The Nash-Sutcliffe coefficient was used as an objective function to assess the quality of these processes (values of this metric are between 0.74 and 0.73 respectively, for model calibration and validation). The results show us an adequate performance of the model in areas of the tropical region and allow us to analyze the relationship between 25 water storage capacity in the soils of the area with subsurface runoff. This conclusion is consistent with the characteristics of the region. The calibrated model provides an idea about the hydrological functioning of the basin and estimates an approximation of the groundwater recharge in the region. The estimation of the recharge is important to quantify the interaction of surface water and groundwater, especially during the dry season, due to its importance in the analysis of scenarios with climate variability. 30

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“…It is widely used for various hydrological applications in France (Grouillet et al, 2016;van Esse et al, 2013) and in other countries (Dakhlaoui et al, 2017;Seiller et al, 2017). It has shown good performances on a wide range of catchments (Coron et al, 2012).…”

Section: Discrete Gr4 Modelmentioning

confidence: 99%

State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

Santos¹,

Thirel²,

Perrin³

2017

Preprint

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Abstract. In many conceptual rainfall-runoff models, the water balance differential equations are not explicitly formulated.These differential equations are solved sequentially by splitting the equations into terms that can be solved analytically with a technique called "operator splitting". As a result, only the resolutions of the split equations are used to present the different models. This article provides a methodology to make the governing water balance equations of a bucket-type rainfall-runoff model explicit. This is done by setting up a comprehensive state-space representation of the model. By representing it in this 5 way, the operator splitting, which complexifies the structural analysis of the model, is removed. In this state-space representation, the lag functions (unit hydrographs), which are frequent in this type of model and make the resolution of the representation difficult, are replaced by a so-called "Nash cascade". This substitution also improves the lag parameter consistency across time

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Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

Cited by 101 publications

References 67 publications

A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations

A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations

Hydrological Modeling in Tropical Regions via TopModel. Study Case: Central Sector of the Middle Magdalena Valley - Colombia

State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

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