Commit 41a5e464 authored by Delaigue Olivier's avatar Delaigue Olivier
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refactor(Publications): update a reference in the 'Articles' section

Refs: #2
parent bc084b9e
......@@ -119,7 +119,6 @@ output:
- Mercado-Bettín D., Clayer F., Shikhani M., Moore T.N., Frías M.D., Jackson-Blake L., et al. (2021). Forecasting water temperature in lakes and reservoirs using seasonal climate prediction. Water Research, 117286. doi: [10.1016/j.watres.2021.117286](https://doi.org/10.1016/j.watres.2021.117286)
- Nguyen H., Mehrotra R. & Sharma A. (2020). Assessment of Climate Change Impacts on Reservoir Storage Reliability, Resilience, and Vulnerability Using a Multivariate Frequency Bias Correction Approach. Water Resources Research 56. doi: [10.1029/2019WR026022](https://doi.org/10.1029/2019WR026022)
- Pelletier A. & Andréassian V. (2021). On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation. Hydrology and Earth System Sciences Discussions 2021, 1–37. doi: [10.5194/hess-2021-413](https://doi.org/10.5194/hess-2021-413)
- Peredo D., Ramos M.-H., Andréassian V. & Oudin L. (2022). Investigating hydrological model versatility to simulate extreme flood events. Hydrological Sciences Journal 0, 1–18. doi: [10.1080/02626667.2022.2030864](https://doi.org/10.1080/02626667.2022.2030864)
- Piazzi G., Thirel G., Perrin C. & Delaigue O. (2021). Sequential Data Assimilation for Streamflow Forecasting: Assessing the Sensitivity to Uncertainties and Updated Variables of a Conceptual Hydrological Model at Basin Scale. Water Resources Research 57. doi: [10.1029/2020WR028390](https://doi.org/10.1029/2020WR028390)
- Saadi M., Oudin L. & Ribstein P. (2021). Physically consistent conceptual rainfall–runoff model for urbanized catchments. Journal of Hydrology 599, 126394. doi: [10.1016/j.jhydrol.2021.126394](https://doi.org/10.1016/j.jhydrol.2021.126394)
- Schmidt-Walter P., Trotsiuk V., Meusburger K., Zacios M. & Meesenburg H. (2020). Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R. Agricultural and Forest Meteorology, 108023. doi: [10.1016/j.agrformet.2020.108023](https://doi.org/10.1016/j.agrformet.2020.108023)
......@@ -135,6 +134,7 @@ output:
- Jackson-Blake L.A., Clayer F., de Eyto E., French A.S., Frías M.D., Mercado-Bettín D., et al. (2022). Opportunities for seasonal forecasting to support water management outside the tropics. Hydrology and Earth System Sciences 26, 1389–1406. doi: [10.5194/hess-26-1389-2022](https://doi.org/10.5194/hess-26-1389-2022)
- Jougla R. & Leconte R. (2022). Short-Term Hydrological Forecast Using Artificial Neural Network Models with Different Combinations and Spatial Representations of Hydrometeorological Inputs. Water 14. doi: [10.3390/w14040552](https://doi.org/10.3390/w14040552)
- Peredo D., Ramos M.-H., Andréassian V. & Oudin L. (2022). Investigating hydrological model versatility to simulate extreme flood events. Hydrological Sciences Journal 67, 628–645. doi: [10.1080/02626667.2022.2030864](https://doi.org/10.1080/02626667.2022.2030864)
- Trinugroho M.W. & Prima Nugroho A. (2022). Pemodelan limpasan air hujan menggunakan GR2M berbasis R di hilir daerah aliran sungai Cimanuk. Buletin Hasil Penelitian Agroklimat dan Hidrologi 18, 14–21. ISSN: [0216-3934](http://repository.pertanian.go.id/bitstream/handle/123456789/15283/buletin-2021_.pdf?sequence=1&isAllowed=y)
### 2021
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