Articles | Volume 19, issue 6
https://doi.org/10.5194/hess-19-2925-2015
© Author(s) 2015. 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-19-2925-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Jun 2015
Research article |
| 24 Jun 2015
TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks
M. F. Müller
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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Cited
19 citations as recorded by crossref.
- Urban Flood Mitigation Strategies with Coupled Gray–Green Measures: A Case Study in Guangzhou City, China J. Li et al.
- What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations A. Betterle et al.
- Bridging the information gap: A webGIS tool for rural electrification in data-scarce regions M. Müller et al.
- Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots L. Rizo-Decelis et al.
- Bayesian regional flood frequency analysis with GEV hierarchical models under spatial dependency structures J. Sampaio & V. Costa
- Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes M. Müller & S. Thompson
- Forest cover lessens the impact of drought on streamflow in Puerto Rico J. Hall et al.
- 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
- Flow alterations in rivers due to unconventional oil and gas development in the Ohio River basin B. Harmon et al.
- Transferring measured discharge time series: Large‐scale comparison of Top‐kriging to geomorphology‐based inverse modeling A. de Lavenne et al.
- Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity A. Betterle et al.
- Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al.
- Does Catchment Nestedness Enhance Hydrological Similarity? A. Betterle & G. Botter
- atakrig: An R package for multivariate area-to-area and area-to-point kriging predictions M. Hu & Y. Huang
- Toward geostatistical unbiased predictions of flow duration curves at ungauged basins W. Wolff & S. Duarte
- Regional Modeling of Long-Term and Annual Flow Duration Curves: Reliability for Information Transfer with Evolutionary Polynomial Regression V. Costa & W. Fernandes
- Patterns of streamflow regimes along the river network: The case of the Thur river B. Doulatyari et al.
- Catchment processes can amplify the effect of increasing rainfall variability M. Müller et al.
- The transfR toolbox for transferring observed streamflow series to ungauged basins based on their hydrogeomorphology A. de Lavenne et al.
19 citations as recorded by crossref.
- Urban Flood Mitigation Strategies with Coupled Gray–Green Measures: A Case Study in Guangzhou City, China J. Li et al.
- What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations A. Betterle et al.
- Bridging the information gap: A webGIS tool for rural electrification in data-scarce regions M. Müller et al.
- Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots L. Rizo-Decelis et al.
- Bayesian regional flood frequency analysis with GEV hierarchical models under spatial dependency structures J. Sampaio & V. Costa
- Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes M. Müller & S. Thompson
- Forest cover lessens the impact of drought on streamflow in Puerto Rico J. Hall et al.
- 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
- Flow alterations in rivers due to unconventional oil and gas development in the Ohio River basin B. Harmon et al.
- Transferring measured discharge time series: Large‐scale comparison of Top‐kriging to geomorphology‐based inverse modeling A. de Lavenne et al.
- Flow dynamics at the continental scale: Streamflow correlation and hydrological similarity A. Betterle et al.
- Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al.
- Does Catchment Nestedness Enhance Hydrological Similarity? A. Betterle & G. Botter
- atakrig: An R package for multivariate area-to-area and area-to-point kriging predictions M. Hu & Y. Huang
- Toward geostatistical unbiased predictions of flow duration curves at ungauged basins W. Wolff & S. Duarte
- Regional Modeling of Long-Term and Annual Flow Duration Curves: Reliability for Information Transfer with Evolutionary Polynomial Regression V. Costa & W. Fernandes
- Patterns of streamflow regimes along the river network: The case of the Thur river B. Doulatyari et al.
- Catchment processes can amplify the effect of increasing rainfall variability M. Müller et al.
- The transfR toolbox for transferring observed streamflow series to ungauged basins based on their hydrogeomorphology A. de Lavenne et al.
Saved (final revised paper)
Latest update: 11 May 2026
Short summary
We introduce TopREML as a method to predict runoff signatures in ungauged basins using linear mixed models with spatially correlated random effects. The nested nature of streamflow networks is accounted for by allowing for stronger correlations between flow-connected basins. The restricted maximum likelihood framework provides best linear unbiased predictions of both the predicted flow variable and its uncertainty as shown in Monte Carlo and cross-validation analyses in Nepal and Austria.
We introduce TopREML as a method to predict runoff signatures in ungauged basins using linear...
