Articles | Volume 27, issue 11
https://doi.org/10.5194/hess-27-2149-2023
https://doi.org/10.5194/hess-27-2149-2023
Research article
 | 
07 Jun 2023
Research article |  | 07 Jun 2023

Using normalised difference infrared index patterns to constrain semi-distributed rainfall–runoff models in tropical nested catchments

Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije

Related authors

Using NDII pattern for a semi-distributed rainfall-runoff model in tropical nested catchments
Nutchanart Sriwongsitanon, Wasana Jandang, Thienchart Suwawong, and Hubert H.~G. Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-82,https://doi.org/10.5194/hess-2020-82, 2020
Manuscript not accepted for further review
Short summary
Comparing the Normalized Difference Infrared Index (NDII) with root zone storage in a lumped conceptual model
Nutchanart Sriwongsitanon, Hongkai Gao, Hubert H. G. Savenije, Ekkarin Maekan, Sirikanya Saengsawang, and Sansarith Thianpopirug
Hydrol. Earth Syst. Sci., 20, 3361–3377, https://doi.org/10.5194/hess-20-3361-2016,https://doi.org/10.5194/hess-20-3361-2016, 2016
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025,https://doi.org/10.5194/hess-29-1703-2025, 2025
Short summary
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025,https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary
Extended-range forecasting of stream water temperature with deep-learning models
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025,https://doi.org/10.5194/hess-29-1685-2025, 2025
Short summary
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025,https://doi.org/10.5194/hess-29-1749-2025, 2025
Short summary
Projections of streamflow intermittence under climate change in European drying river networks
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025,https://doi.org/10.5194/hess-29-1615-2025, 2025
Short summary

Cited articles

Bao, A. M., Liu, H. L., Chen, X., and Pan, X. l.: The effect of estimating areal rainfall using self-similarity topography method on the simulation accuracy of runoff prediction, Hydrol. Process., 25, 3506–3512, https://doi.org/10.1002/hyp.8078, 2011. 
Bouaziz, L. J. E., Steele-Dunne, S. C., Schellekens, J., Weerts, A. H., Stam, J., Sprokkereef, E., Winsemius, H. H. C., Savenije, H. H. G., and Hrachowitz, M.: Improved understanding of the linkbetween catchment-scale vegetation accessible storage and satellite-derivedSoil Water Index, Water Resour. Res., 56, e2019WR026365, https://doi.org/10.1029/2019WR026365, 2020. 
Boyd, M. J., Bates, B. C., Pilgrim, D. H., and Cordery, I.: WBNM: A General Runoff Routing Model Computer Programs and User Guide, Water Research Laboratory, The University of New South Wales, https://doi.org/10.4225/53/57996b382f17b, 1987. 
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martínez-Fernandez, J., and Llorens, P.: Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe, Remote Sens. Environ., 115, 3390–3408, https://doi.org/10.1016/j.rse.2011.08.003, 2011. 
Carroll, D.: URBS a Rainfall Runoff Routing Model for flood forecasting and design version 4.00, https://www.scribd.com/document/93746264/URBSManualV440 (last access: 15 January 2020), 2004. 
Download
Short summary
We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Share