New Standardized Base Flow Index for Identification of Hydrologic Drought in the Red River of the North Basin

Bazrkar, Mohammad Hadi; Chu, Xuefeng

doi:10.1061/(asce)nh.1527-6996.0000414

Cited by 6 publications

(8 citation statements)

References 16 publications

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“…Application of the WETSPRO flow filtering tool (Willems, 2009) to the recorded streamflow of the Red River at Emerson station shows that the contribution of groundwater to the streamflow is around 40% (flow filtering result provided in Text S4 and Figure S7 in Supporting Information ). This is close to the results of Bazrkar and Chu (2020).…”

Section: Resultssupporting

confidence: 92%

“…The posterior simulations of IE‐H‐HYPE—applied to the RARB—provide a groundwater contribution with an interquartile range of 61.4%–71.5% (Table 4). This shows that IE‐H‐HYPE also overestimates the groundwater contribution as compared to the literature value (Bazrkar & Chu, 2020) and the data‐driven groundwater contribution obtained for the Emerson station. But the advantage of IE‐H‐HYPE over H‐HYPE is apparent given that IE‐H‐HYPE simulates groundwater contribution that provide a much better agreement with the literature value (Bazrkar & Chu, 2020) and the data‐driven groundwater contribution obtained for the Emerson station as compared to that simulated by H‐HYPE.…”

Section: Resultssupporting

confidence: 61%

“…We compared the groundwater contributions simulated by the HYPE, SQ‐HYPE, and IE‐HYPE models with literature estimates of the Beaver watershed (Buttle et al., 2015; Neff et al., 2005) and by constructing empirical distributions of base flow indices of each model using the posterior parameter sets. The groundwater contribution of the RARB simulated by the three models (H‐HYPE, SQ‐H‐HYPE, and IE‐H‐HYPE) was compared with the baseflow fraction of the basin estimated by Bazrkar and Chu (2020). In addition, we used the WETSPRO baseflow separation tool (Willems, 2009) to filter the baseflow of the Beaver watershed at Beaverton and the RARB at Emerson.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Impacts of Uncontrolled Operator Splitting Methods on Parameter Identification, Prediction Uncertainty, and Subsurface Flux Representation in Conceptual Hydrological Models

Woldegiorgis

Baulch

Wheater

et al. 2023

Water Resources Research

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The proper numerical representation of physical processes in mechanistic hydrological models is essential to produce robust predictions. A common problem with numerical schemes in hydrological models is that multiple concurrent fluxes are calculated sequentially. Although the importance of errors introduced by inappropriate numerical schemes is well recognized in the literature, many hydrological models calculate concurrent fluxes sequentially. Here, two versions of the HYPE model are used to investigate the limitations of sequential calculations. A fourth order Gear‐Nordsieck solution of the continuous state‐space formulation of HYPE (I‐HYPE) is developed to provide a robust solution, and a fixed‐step implicit Euler scheme (IE‐HYPE) is implemented to provide a computationally efficient and robust approximation of the I‐HYPE simulations. In contrast to I‐HYPE, results show that the original HYPE and the sequential calculation implemented in the continuous state‐space formulation of HYPE (SQ‐HYPE) typically simulate no interflow when soil moisture levels exceed the field capacity. The discrepancy between SQ‐HYPE and I‐HYPE grows with the size of the computation time step, and this implies a compromised representation of flow paths by sequential schemes. IE‐HYPE provides responses comparable with I‐HYPE for both daily and hourly time steps. IE‐HYPE and SQ‐HYPE are compared in terms of their groundwater representation, parameter identifiability, and predictive skills for two catchments. The sequential models have larger groundwater contributions to flow than IE‐HYPE because the splitting errors in SQ‐HYPE limit the interflow flux. IE‐HYPE estimates of the groundwater flux are more consistent with literature values of groundwater contributions to flow for the basins studied.

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Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 61%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Impacts of Uncontrolled Operator Splitting Methods on Parameter Identification, Prediction Uncertainty, and Subsurface Flux Representation in Conceptual Hydrological Models

Woldegiorgis

Baulch

Wheater

et al. 2023

Water Resources Research

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show abstract

“…The essential baseflow characteristics to replenish river flow during dry periods, SBI instead of SSI, can better respond to hydrologic drought characteristics. Bazrkar and Chu [20] improved hydrological drought identification by developing a new standardized base flow index. Meresa et al [21] explored the relationship between hydrological and meteorological drought and watershed characteristics.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Hydrological and Meteorological Composite Drought Characteristics Based on Baseflow and Precipitation

Huang,

Zhang,

Liu

et al. 2024

Water

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Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the standardized precipitation index (SPI) and the standardized baseflow index (SBI) for the Jiaojiang River Basin (JRB) using the copula function. The prediction model was established by training random forests on past data, and the driving force behind the combined drought index was explored through the LIME algorithm. The results show that the established composite drought index combines the advantages of SPI and SBI in drought forecasting. The monthly and annual droughts in the JRB showed an increasing trend from 1991 to 2020, but the temporal characteristics of the changes in each subregion were different. The accuracies of the trained random forest model for heavy drought in Baizhiao (BZA) and Shaduan (SD) stations were 83% and 88%, respectively. Furthermore, the Local Interpretable Model-Agnostic Explanations (LIME) interpretation identified the essential precipitation, baseflow, and evapotranspiration features that affect drought. This study provides reliable and valid multivariate indicators for drought monitoring and can be applied to drought prediction in other regions.

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“…For instance, Wu et al (2019) and Rangecroft et al (2019) have used total runoff to determine HD, while other studies consider HD by looking separately at the components of the hydrological process, particularly baseflow drought (e.g. Bazrkar and Chu, 2020). Our study, therefore, focuses on assessing the impact of human factors on HD characteristics considering (sub)surface runoff separately.…”

Section: Introductionmentioning

confidence: 99%

Modelling human impacts on surface and subsurface hydrological drought

Senbeta,

Kochanek,

Karamuz

et al. 2024

Proc. IAHS

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Abstract. The scientists tend to assume that climatic factors are the only drivers in the development of drought. However, this classical assumption is no longer valid in the Anthropocene, as most catchments have been significantly modified by human factors. Recent theoretical developments have shown that there are mutual interactions and feedback mechanisms – drought shapes humans and vice versa. Therefore, this study aims to assess the role of human impacts on hydrological drought (HD) characteristics by considering runoff and baseflow separately. For this purpose, the two rainfall-runoff models: SWAT (Soil and Water Assessment Tool) and HBV (Hydrologiska Byrans Vattenbalansavdelning) models are compared. The results show significant differences in the magnitude of change between the two models, suggesting that the ensemble method of multiple models need to be considered for modelling human impact. However, the results confirm that despite significant differences in the magnitude of change, both hydrological models indicate similar impacts, i.e. positive and negative.

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New Standardized Base Flow Index for Identification of Hydrologic Drought in the Red River of the North Basin

Cited by 6 publications

References 16 publications

Impacts of Uncontrolled Operator Splitting Methods on Parameter Identification, Prediction Uncertainty, and Subsurface Flux Representation in Conceptual Hydrological Models

Impacts of Uncontrolled Operator Splitting Methods on Parameter Identification, Prediction Uncertainty, and Subsurface Flux Representation in Conceptual Hydrological Models

Assessment of Hydrological and Meteorological Composite Drought Characteristics Based on Baseflow and Precipitation

Modelling human impacts on surface and subsurface hydrological drought

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