Streamflow estimation in ungauged catchments using regionalization techniques

Swain, Janaki Ballav; Patra, Kanhu Charan

doi:10.1016/j.jhydrol.2017.08.054

Cited by 99 publications

(58 citation statements)

References 58 publications

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“…The regression technique considers watershed attributes as independent variables and model parameters as dependent variables [17]. Several studies have compared the performance of the three-regionalization approaches in different watersheds [18][19][20]. Parajka et al used the semi-distributed Hydrologiska Byråns Vattenbalansavdelning (HBV) model in Austria and showed that the physical similarity method performs better than the regression and spatial proximity ones [8].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Narbondo

Gorgoglione

Crisci

et al. 2020

Water

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Regionalization techniques have been comprehensively discussed as the solution for runoff predictions in ungauged basins (PUB). Several types of regionalization approach have been proposed during the years. Among these, the physical similarity one was demonstrated to be one of the most robust. However, this method cannot be applied in large regions characterized by highly variable climatic conditions, such as sub-tropical areas. Therefore, this study aims to develop a new regionalization approach based on an enhanced concept of physical similarity to improve the runoff prediction of ungauged basins at country scale, under highly variable-weather conditions. A clustering method assured that watersheds with different hydrologic and physical characteristics were considered. The novelty of the proposed approach is based on the relationships found between rainfall-runoff model parameters and watershed-physiographic factors. These relationships were successively exported and validated at the ungauged basins. From the overall results, it can be concluded that the runoff prediction in the ungauged basins was very satisfactory. Therefore, the proposed approach can be adopted as an alternative method for runoff prediction in ungauged basins characterized by highly variable-climatic conditions.

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Section: Introductionmentioning

confidence: 99%

Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Narbondo

Gorgoglione

Crisci

et al. 2020

Water

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“…Swain et al [16] used inverse distance weighted (IDW), kriging, global mean, regression and physical similarity to simulate streamflow in 32 catchments in Eastern and Southern India. Prior to using the regionalization approaches, they calibrated and validated each watershed with NSE values between 0.59 and 0.81 for the calibration period and 0.48 to 0.77 for the validation period.…”

Section: Introductionmentioning

confidence: 99%

Comparison of three regionalization techniques for predicting streamflow in ungaged watersheds in Nebraska, USA using SWAT model

Liew

Mittelstet

2018

International Journal of Agricultural and Biological Engineering

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This study compared three approaches, regional averaging, nearest neighbor, and donor techniques, to regionalize parameters in the Soil and Water Assessment Tool (SWAT) on eleven watersheds located in the Dissected Plains, Plains, and Rolling Hills Landforms in the eastern portion of the State of Nebraska, USA. Within the Rolling Hills Landform, three watersheds were randomly selected as calibration watersheds while two were randomly selected as validation watersheds. Two watersheds were randomly selected as calibration watersheds while one was randomly selected as a validation watershed within each of the Dissected Plains and Plains Landforms. The seven calibration watersheds were used to provide the necessary calibrated parameter sets to execute each of the regional approaches, while the four validation watersheds were used to assess the impact of applying each of these approaches to an uncalibrated watershed. Percent Bias (PBIAS) and the Nash Sutcliffe Coefficient of Efficiency (NSE) were used to assess model performance. Test results of this study show that all three methods performed poorly, since the majority of watersheds among each method tested exhibited PBIAS values greater than ±25% and/or NSE values less than 0.50, which were considered to be unsatisfactory in terms of model performance. The average regionalization, nearest neighbor and donor methods resulted in only four (two calibration and two validation), zero and one satisfactory set of simulated watershed results, respectively.The findings from this study indicate that although each watershed was successfully calibrated with NSE values ranging from 0.51 to 0.84, none of the three regionalization methods provided suitable calibration data sets to define parameter values for performing satisfactory simulations on ungaged watersheds across the eastern Nebraska landscape.

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“…The calibrated parameters of the donor catchments are then transferred to the ungauged (receiver) catchments. The application of these methods in UK, Australia, and Indian, as well as other countries, has demonstrated that the former two approaches yield better results than the latter [22][23][24][25][26]. A combination of spatial proximity (distance) and physical similarity indices could therefore improve the accuracy of simulations [25].…”

Section: Introductionmentioning

confidence: 99%

“…A combination of spatial proximity (distance) and physical similarity indices could therefore improve the accuracy of simulations [25]. For the stream flow prediction of ungauged catchments, the presence of well-gauged catchments in proximity is more beneficial than having physically similar catchments [24]. Norbiato et al found that the model parameters, which transferred directly from gauged to ungauged catchments of the same river system had limitations when computed via FFG [27].…”

Section: Introductionmentioning

confidence: 99%

Forecasting and Providing Warnings of Flash Floods for Ungauged Mountainous Areas Based on a Distributed Hydrological Model

Wang

Liu

Guo

et al. 2017

Water

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Flash floods occur in mountainous catchments with short response times, which are among the most devastating natural hazards in China. This paper intends to forecast and provide warnings of flash floods timely and precisely using the flash flood warning system, which is established by a new distributed hydrological model (the China flash flood hydrological model, CNFF-HM). Two ungauged mountainous regions, Shunchang and Zherong, are chosen as the study areas. The CNFF-HM is calibrated in five well-monitored catchments. The parameters for the ungauged regions are estimated by regionalization. River water stage data and reservoir water stage data from Shunchang, and reservoir water stage data from Zherong are used to validate the model. The model performs well and the average Nash-Sutcliffe efficiency (NSE) is above 0.8 for the five catchments. The validation shows the difference in the timing of flood peaks using the two types of water stage data is less than 1 h. The rising and declining trends of the floods correspond to the observed trends over the entire validation process. Furthermore, the flash flood warning system was effectively applied in flash flood event on 28 September 2016 in Zherong. Thus, the CNFF-HM with regionalization is effective in forecasting flash floods for ungauged mountainous regions.

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Streamflow estimation in ungauged catchments using regionalization techniques

Cited by 99 publications

References 58 publications

Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Enhancing Physical Similarity Approach to Predict Runoff in Ungauged Watersheds in Sub-Tropical Regions

Comparison of three regionalization techniques for predicting streamflow in ungaged watersheds in Nebraska, USA using SWAT model

Forecasting and Providing Warnings of Flash Floods for Ungauged Mountainous Areas Based on a Distributed Hydrological Model

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