Comparison of regionalization approaches based on regression and similarity for predictions in ungauged catchments under multiple hydro-climatic conditions

Bao, Zhenxin; Zhang, Jianyun; Liu, Jiufu; Fu, Guobin; Wang, Guoqing; He, Ronghai; Yan, Xiaolin; Jin, Jian; Liu, Hongwei

doi:10.1016/j.jhydrol.2012.07.048

Cited by 71 publications

(70 citation statements)

References 39 publications

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“…For example, the suitability of a regionalization approach is both location specific (Bao et al, 2012;Beven, 2000;Oudin et al, 2008;Wagener and Wheater, 2006) and rainfall-runoff model specific (Bárdossy, 2007;Beven, 2006;Kay et al, 2006). In response to the uncertainties introduced in model-dependent regionalization approaches, recent studies developed regionalization schemes that are model-independent (that is, they can be applied to any rainfall-runoff model).…”

Section: Predictions In Ungauged Basinsmentioning

confidence: 99%

Regionalization of hydrologic response in the Great Lakes basin: Considerations of temporal scales of analysis

Kult

Fry

Gronewold

et al. 2014

Journal of Hydrology

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Keywords:Runoff Regionalization Prediction in ungauged basins Hydrologic response Regression model Great Lakes basin s u m m a r y Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response commonly rely on regionalization techniques, where knowledge pertaining to gauged watersheds is transferred to ungauged watersheds. Hydrologic response indices have frequently been employed in contemporary regionalization research related to predictions in ungauged basins. In this study, we developed regionalization models using multiple linear regression and regression tree analysis to derive relationships between hydrologic response and watershed physical characteristics for 163 watersheds in the Great Lakes basin. These models provide an empirical means for simulating runoff in ungauged basins at a monthly time step without implementation of a rainfall-runoff model. For the dependent variable in these regression models, we used monthly runoff ratio as the indicator of hydrologic response and defined it at two temporal scales: (1) treating all monthly runoff ratios as individual observations, and (2) using the mean of these monthly runoff ratios for each watershed as a representative observation. Application of the models to 62 validation watersheds throughout the Great Lakes basin indicated that model simulations were far more sensitive to the temporal characterization of hydrologic response than to the type of regression technique employed, and that models conditioned on individual monthly runoff ratios (rather than long term mean values) performed better. This finding is important in light of the increased usage of hydrologic response indices in recent regionalization studies. Models using individual observations for the dependent variable generally simulated monthly runoff with reasonable skill in the validation watersheds (median Nash-Sutcliffe efficiency = 0.53, median R 2 = 0.66, median magnitude of the deviation of runoff volume = 13%). These results suggest the viability of empirical approaches to simulate runoff in ungauged basins. This finding is significant given the many regions of the world with sparse gauging networks and limited resources for gathering the field data required to calibrate rainfallrunoff models.

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Section: Predictions In Ungauged Basinsmentioning

confidence: 99%

Regionalization of hydrologic response in the Great Lakes basin: Considerations of temporal scales of analysis

Kult

Fry

Gronewold

et al. 2014

Journal of Hydrology

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“…Firstly we performed a principal component analysis (PCA, Legendre and Legendre, 1998) for catchment characteristics including topography, land cover and land use, soil, and catchment structure such as area and channel length, to select uncorrelated metrics representing the catchment responses. Then k-means clustering analysis and hierarchical clustering analysis were selected to group the catchments into a number of classes (homogenous regions).…”

Section: Methodsmentioning

confidence: 99%

“…Zhang and Francis (2009) analyse several approaches in 210 catchments in Australia and show that the spatial proximity-based approach is slightly better than the physical similarity approach. Bao et al (2012) investigate different regionalisation approaches for 55 catchments in China and find that the similarity based approaches are more accurate than the regression based approach, and become much more accurate from humid to arid regions. Parajka et al (2013) conducts an integrated analysis on 34 studies including 3874 catchments and conclude that the performances of different approaches largely depend on the selected rainfall runoff models and research sites.…”

Section: Introductionmentioning

confidence: 99%

Hydrological regionalisation based on available hydrological information for runoff prediction at catchment scale

Zhu

et al. 2018

Proc. IAHS

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Abstract. Regionalisation provides a way of transferring hydrological information from gauged to ungauged catchments. The past few decades has seen several kinds of regionalisation approaches for catchment classification and runoff predictions. The underlying assumption is that catchments having similar catchment properties are hydrological similar. This requires the appropriate selection of catchment properties, particularly the inclusion of observed hydrological information, to explain the similarity of hydrological behaviour. We selected observable catchments properties and flow duration curves to reflect the hydrological behaviour, and to regionalize rainfall-runoff response for runoff prediction. As a case study, we investigated 15 catchments located in the Yangtze and Yellow River under multiple hydro-climatic conditions. A clustering scheme was developed to separate the catchments into 4 homogeneous regions by employing catchment properties including hydro-climatic attributes, topographic attributes and land cover etc. We utilized daily flow duration curves as the indicator of hydrological response and interpreted hydrological similarity by root mean square errors. The combined analysis of similarity in catchment properties and hydrological response suggested that catchments in the same homogenous region were hydrological similar. A further validation was conducted by establishing a rainfall-runoff coaxial correlation diagram for each catchment. A common coaxial correlation diagram was generated for each homogenous region. The performances of most coaxial correlation diagrams met the national standard. The coaxial correlation diagram can be transferred within the homogeneous region for runoff prediction in ungauged catchments at an hourly time scale.

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“…A similar approach, the physical similarity method, uses the same logic except the donor basin is selected according to its physical similarity to the ungauged basin. The idea is that physically similar catchments should share hydrologic responses as well ( Bardossy 2007, Samuel et al 2011, Bao et al 2012. Oudin et al (2010) showed that the assumption of hydrologic and physical similarity being correlated is not always adequate and that our limited knowledge of hydrologic processes at the fundamental level limits the number of useful catchment attributes.…”

Section: Introductionmentioning

confidence: 99%

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

Arsenault

Poissant

Brissette

2015

Advances in Water Resources

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Comparison of regionalization approaches based on regression and similarity for predictions in ungauged catchments under multiple hydro-climatic conditions

Cited by 71 publications

References 39 publications

Regionalization of hydrologic response in the Great Lakes basin: Considerations of temporal scales of analysis

Regionalization of hydrologic response in the Great Lakes basin: Considerations of temporal scales of analysis

Hydrological regionalisation based on available hydrological information for runoff prediction at catchment scale

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

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