Parameter Extrapolation to Ungauged Basins with a Hydrological Distributed Model in a Regional Framework

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Parameter Extrapolation to Ungauged Basins with a Hydrological Distributed Model in a Regional Framework Hydrol. Earth Syst. Sci., 13, 229–246, 2009 www.hydrol-earth-syst-sci.net/13/229/2009/ Hydrology and © Author(s) 2009. This work is distributed under Earth System the Creative Commons Attribution 3.0 License. Sciences Parameter extrapolation to ungauged basins with a hydrological distributed model in a regional framework J. J. Velez´ 1,2, M. Puricelli1, F. Lopez´ Unzu3, and F. Frances´ 1 1Departamento de Ingenier´ıa Hidraulica´ y Medio Ambiente, Universidad Politecnica´ de Valencia, DIHMA-UPV, Camino de Vera s/n, 46022 Valencia, Spain 2Departmento de Ingenier´ıa Civil, Universidad Nacional de Colombia, sede Manizales, IDEA. Manizales, Colombia 3INTECSA-INARSA, c/ Santa Leonor 32, 28037 Madrid, Spain Received: 5 March 2007 – Published in Hydrol. Earth Syst. Sci. Discuss.: 27 April 2007 Revised: 8 January 2009 – Accepted: 12 February 2009 – Published: 23 February 2009 Abstract. A Regional Water Resources study was performed rameter maps (number of parameters times the number of at basins within and draining to the Basque Country Region cells). In this way, the calibration can be performed using (N of Spain), with a total area of approximately 8500 km2. automatic methodologies. In this work, the Shuffled Com- The objective was to obtain daily and monthly long-term dis- plex Evolution – University of Arizona, SCE-UA algorithm charges in 567 points, most of them ungauged, with basin was used. The available recent year’s data was used to cali- areas ranging from 0.25 to 1850 km2. In order to extrapo- brate the model in 20 of the most representative flow gauge late the calibrations at gauged points to the ungauged ones, stations in 18 basins with a Nash-Sutcliffe index higher than a distributed and conceptually based model called TETIS 0.6 (10 higher than 0.8). The calibrated correction factors at was used. In TETIS the runoff production is modelled us- each basin were similar but not equal. The validation process ing five linked tanks at the each cell with different outflow (in time and space) was performed using the remaining data relationships at each tank, which represents the main hy- in all flow gauge stations (62), with 42 basins with a Nash- drological processes as snowmelt, evapotranspiration, over- Sutcliffe index higher than 0.5 (25 higher than 0.7). De- land flow, interflow and base flow. The routing along the ficient calibration and validations were always related with channels’ network couples its geomorphologic characteris- flow gauge stations very close to the karstic springs. These tics with the kinematic wave approach. The parameter esti- results confirmed that it was feasible and efficient to use mation methodology tries to distinguish between the effec- the SCE-UA algorithm for the automatic calibration of dis- tive parameter used in the model at the cell scale, and the tributed conceptual models and the calibrated model could watershed characteristic estimated from the available infor- be used at ungauged basins. Finally, meteorological infor- mation, being the best estimation without losing its physical mation from the past 50 years at a daily scale was used to meaning. The relationship between them can be considered generate a daily discharges series at 567 selected points. as a correction function or, in its simple form, a correction factor. The correction factor can take into account the model input errors, the temporal and spatial scale effects and the 1 Introduction: problem framework watershed characteristics. Therefore, it is reasonable to as- sume the correction factor is the same for each parameter to During last decade hydrological institutions and research all cells within the watershed. This approach reduces drasti- groups have focused in the Prediction on Ungauged Basins cally the number of parameter to be calibrated, because only (PUB) as a research topic which must be studied, analyzed the common correction factors are calibrated instead of pa- and restructured if necessary in this decade (Sivapalan et al., 2003). McDonnell et al. (2007) mention that to make progress in watershed hydrology with coherence it is nec- Correspondence to: J. J. Velez´ essary to characterize the landscape heterogeneity explor- ([email protected]) ing the principles that might underlie the heterogeneity and Published by Copernicus Publications on behalf of the European Geosciences Union. 230 J. J. Velez´ et al.: Regional water resources study using distributed modelling Distributed models divide the catchment into a number of Butroe Bidasoa Oka smaller areas (grid elements or subcatchments), which are as- Aguera Lea Oiartzun sumed to be uniform with respect to their hydrologic parame- Barbadun Artibai Karrantza Urumea ters. There has been an “exponentially growing” recent inter- Urola Oria Ibaizabal Deba est in distributed hydrologic modelling that has been fuelled by growing availability of GIS-related information (Schaake, 2003). NORTH Arakil Omecillo Baia Zadorra Temporal and spatial heterogeneity can be important in many hydrologic applications. The main processes of the Bay of Biscay hydrological cycle are variable in time and space. The tem- Ega France poral variation is observed in input temporal data as precip- Inglares Ebro River itation, potential evapotranspiration, temperature, etc. The Ebro Spain spatial variation is mainly detected in soil properties, soil 250 km Portugal Ebro River moisture, land use, etc., which are represented as maps. In some cases, simple aggregation of temporal variability can Fig. 1. Division of the study area in 21 systems (different colours) misrepresent important physical processes. Different hydro- and 41 basins. Thick red line divides the study area into northern logical processes as runoff production and channel network and southern basins. Circles and triangles correspond to calibration routing are affected by this temporal and spatial variability and validation points, respectively. which must be considered in the selected model (Wood et al., 1988; Gan and Biftu, 1996). Heuvelmans et al. (2004) studied the spatial variability of complexity. Nevertheless, the ability to generalize these find- soil parameters using regionalisation schemes and concluded ings to ungauged regions remains unsolved. However, in that clustering of parameter sets gives a more accurate re- this paper the extrapolation of the parameters to ungauged sult than the single parameter approach and is, therefore, the basins with a hydrological distributed model is successfully preferred technique for use in the parameterisation of un- exposed. gauged sub-catchments as part of the simulation of a large Knowing water budgets for the basin and its subbasins river basin. allows water-resource managers to identify areas of great- The scale effect by spatial and temporal aggregation of est concern in the basin and make more informed decisions nonlinear processes is complex because the mean process re- about conservation and remediation. A Regional Water Re- sponse is not the result of the true mean parameter; therefore sources study was performed at basins within and draining to it is necessary to introduce effective parameters in the model the Basque Country Region (N of Spain), with a total area of 2 in order to overcome this problem. The effective parameters approximately 8500 km . The objective was to obtain daily usually are: physically senseless, non-stationary (they are not and monthly long-term discharges in 567 points (initially 123 valid if used at different ranges obtained during calibration), points, but at the end of the project more simulation points and highly uncertain. The proposed solution is to use dis- were demanded), obviously most of them ungauged, with 2 tributed modelling with a small temporal discretization. basin areas ranging from 0.25 to 1850 km . The study area The TETIS model is a freeware which has been devel- is officially divided into 21 hydrological systems with a to- oped at DIHMA-UPV as a continuous and event model and tal of 41 basins (Fig. 1), only 17 of them with at least one corresponds to a distributed hydrological conceptual model, flow gauge station. Northern basins drain to the Bay of Bis- which has been chosen because of their very good perfor- cay in the Atlantic Ocean with a humid climate, and southern mance in different basins and climates; Velez´ (2001), Velez´ basins drain to the Ebro River (which flows to the Mediter- et al. (2002a, b, 2007) and Frances´ et al. (2007). The TETIS ranean Sea) with a dry continental climate. model uses the kinematic wave methodology coupled to the In this study, distributed modelling was proposed mainly: basin geomorphologic characteristics in order to route the flow along the channel network. This procedure is known, – Due to the high number of simulation points and its according to Velez´ (2001), as the “Geomorphologic Kine- vague definition at the beginning of the project. matic Wave” or GKW. It is well known in hydrology that the quality in the out- – In order to extrapolate the calibrations at gauged points put data of conceptual rainfall-runoff models depends on: the to the ungauged ones, without parameters regionaliza- quality of input data, the model structure and the calibration tion but reproducing the natural spatial variability of the process (Sorooshian et al., 1993; Liden´ and Harlin, 2000 and Hydrological Cycle. Madsen, 2000). According to Grayson et al. (1992), con- ceptual models are better than physically based models since – Because spatial information is available to be used in they are faster computationally and have less number of pa- this type of models. rameters when the suitable scale is adopted. Likewise, the Hydrol. Earth Syst. Sci., 13, 229–246, 2009 www.hydrol-earth-syst-sci.net/13/229/2009/ J. J. Velez´ et al.: Regional water resources study using distributed modelling 231 conceptual models have a great capacity to compensate for Efficiency indexes must be treated with care in the mod- errors and they are difficult to calibrate because they have els, since reliability and validity are not equivalent and the been created for specific conditions.
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