Articles | Volume 20, issue 2
https://doi.org/10.5194/hess-20-669-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-669-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Feb 2016
Research article |
| 11 Feb 2016
Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes
M. F. Müller
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Davis Hall,
University of California, Berkeley CA, USA
S. E. Thompson
Department of Civil and Environmental Engineering, Davis Hall,
University of California, Berkeley CA, USA
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- A Value‐Based Model Selection Approach for Environmental Random Variables M. Müller & S. Thompson 10.1029/2018WR023000
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- Potential of the Molawin creek for micro hydro power generation: An assessment J. Casila et al. 10.1016/j.seta.2019.02.005
- Characterizing the spatial correlation of daily streamflows A. Betterle et al. 10.1002/2016WR019195
- Probabilistic Description of Streamflow and Active Length Regimes in Rivers N. Durighetto et al. 10.1029/2021WR031344
48 citations as recorded by crossref.
- The construction of the flow duration curve and the regionalization parameters analysis in the northwest of China J. Luan et al. 10.2166/wcc.2021.324
- GEO-CWB: GIS-Based Algorithms for Parametrising the Responses of Catchment Dynamic Water Balance Regarding Climate and Land Use Changes S. Gharbia et al. 10.3390/hydrology7030039
- An assessment of small island hydrological research activity conducted in the Oceania Region C. Leong et al. 10.1080/02626667.2023.2252406
- A step toward global-scale applicability and transferability of flow duration curve studies: A flow duration curve review (2000–2020) C. Leong & Y. Yokoo 10.1016/j.jhydrol.2021.126984
- Bridging the information gap: A webGIS tool for rural electrification in data-scarce regions M. Müller et al. 10.1016/j.apenergy.2016.03.052
- On the probability distribution of daily streamflow in the United States A. Blum et al. 10.5194/hess-21-3093-2017
- Strategies to enhance the reliability of flow quantile prediction in the gauged and ungauged basins G. Tegegne & Y. Kim 10.1002/rra.3603
- A Value‐Based Model Selection Approach for Environmental Random Variables M. Müller & S. Thompson 10.1029/2018WR023000
- Impact assessment of land use/land cover and climate change on streamflow regionalization in an ungauged catchment J. Swain & K. Patra 10.2166/wcc.2018.161
- Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity A. Betterle et al. 10.1002/hyp.13350
- Streamflow Estimation in Ungauged Catchments Using Regional Flow Duration Curve: Comparative Study J. Swain & K. Patra 10.1061/(ASCE)HE.1943-5584.0001509
- Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India A. Nag & B. Biswal 10.3390/hydrology6020032
- Flow duration curve prediction: A framework integrating regionalization and copula model T. Lan et al. 10.1016/j.jhydrol.2024.132364
- TheF-family of covariance functions: A Matérn analogue for modeling random fields on spheres A. Alegría et al. 10.1016/j.spasta.2021.100512
- A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves C. Leong & Y. Yokoo 10.1002/hyp.14569
- Noise-Driven Return Statistics: Scaling and Truncation in Stochastic Storage Processes T. Aquino et al. 10.1038/s41598-017-00451-x
- Using national hydrologic models to obtain regional climate change impacts on streamflow basins with unrepresented processes P. Bosompemaa et al. 10.1016/j.envsoft.2024.106234
- On the Effect of Nonlinear Recessions on Low Flow Variability: Diagnostic of an Analytical Model for Annual Flow Duration Curves N. Karst et al. 10.1029/2019WR024912
- On the regional-scale variability in flow duration curves in Peninsular India P. Dey et al. 10.5194/hess-28-1493-2024
- Estimation of dependable flow in river baspa at kuppa barrage using flow duration curve N. Vivekanandan 10.26634/jce.13.1.19146
- Managing diversions in unregulated streams using a modified percent‐of‐flow approach D. Mierau et al. 10.1111/fwb.12985
- Impact of catchment classification on streamflow regionalization in ungauged catchments J. Swain & K. Patra 10.1007/s42452-019-0476-6
- Complementary Vantage Points: Integrating Hydrology and Economics for Sociohydrologic Knowledge Generation M. Müller & M. Levy 10.1029/2019WR024786
- Physical controls and regional pattern similarities of precipitation and flow duration curves using the three‐parameter gamma distribution Y. Zhou & Y. Zhang 10.1002/hyp.15082
- Reliable estimation of high floods: A method to select the most suitable ordinary distribution in the Metastatistical extreme value framework S. Mushtaq et al. 10.1016/j.advwatres.2022.104127
- Annual flow duration curve model for ungauged basins H. Burgan & H. Aksoy 10.2166/nh.2018.109
- Analytical flow duration curves for summer streamflow in Switzerland A. Santos et al. 10.5194/hess-22-2377-2018
- Climate and Landscape Controls of Regional Patterns of Flow Duration Curves Across the Continental United States: Statistical Approach S. Ghotbi et al. 10.1029/2020WR028041
- A web-based urban hydrology model for municipal scale applications M. Mohammad Zadeh et al. 10.1016/j.envsoft.2024.106096
- Patterns of streamflow regimes along the river network: The case of the Thur river B. Doulatyari et al. 10.1016/j.envsoft.2017.03.002
- Monthly Flow Duration Curve Model for Ungauged River Basins H. Burgan & H. Aksoy 10.3390/w12020338
- Recession flow prediction in gauged and ungauged basins by just considering past discharge information C. Reddyvaraprasad et al. 10.1080/02626667.2019.1643465
- A conceptual stochastic rainfall-runoff model of an order-one catchment under a stationary precipitation regime S. Vallejo-Bernal et al. 10.1007/s00477-021-02041-w
- Validation and Characterization of Stochastic Flow Regime Predicting Method R. ARAI et al. 10.3178/jjshwr.32.301
- Alternative for the regionalization of flow duration curves R. Silva et al. 10.1080/23249676.2019.1611493
- Estimating the price (in)elasticity of off-grid electricity demand M. Müller et al. 10.1016/j.deveng.2017.12.001
- Regional Modeling of Long-Term and Annual Flow Duration Curves: Reliability for Information Transfer with Evolutionary Polynomial Regression V. Costa & W. Fernandes 10.1061/(ASCE)HE.1943-5584.0002051
- Comparative performance of regionalization methods for model parameterization in ungauged Himalayan watersheds N. Karki et al. 10.1016/j.ejrh.2023.101359
- Identification of run-of-river hydropower investments in data scarce regions using global data D. Magaju et al. 10.1016/j.esd.2020.07.001
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- Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio W. Farmer & G. Koltun 10.1016/j.ejrh.2017.08.006
- Streamflow Forecasting without Models W. Krajewski et al. 10.1175/JHM-D-19-0292.1
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- Application of fiducial method for streamflow prediction under small sample cases in Xiangxihe watershed, China J. Zhang et al. 10.1016/j.jhydrol.2020.124866
- Modelling river flow in cold and ungauged regions: a review of the purposes, methods, and challenges C. Belvederesi et al. 10.1139/er-2021-0043
- Anlık Maksimum Debilerin 2025-2055 Dönemindeki Yağış ve Sıcaklık Farklılıklarına Göre Değişimi, Doğu Karadeniz Havzası İncelemesi H. Babacan 10.21324/dacd.1447159
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- Potential of the Molawin creek for micro hydro power generation: An assessment J. Casila et al. 10.1016/j.seta.2019.02.005
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Latest update: 13 Dec 2024
Short summary
We compare a stochastic (process-based) and statistical (data-based) method to predict flow duration curves in ungauged basins, under stationary and non-stationary conditions, and using Nepal as a case study. Both methods worked well in stationary conditions, with performances driven by the main source of runoff heterogeneity (climate vs. recession). The stochastic model worked better under change, and the performance of the statistical model was determined by the resilience of the flow regime.
We compare a stochastic (process-based) and statistical (data-based) method to predict flow...
