23 citations as recorded by crossref.

1. Multisite seasonal forecast of arid river flows using a dynamic model combination approach S. Chowdhury & A. Sharma https://doi.org/10.1029/2008WR007510
2. Water level as the main driver of the alternation between a free-floating plant and a phytoplankton dominated state: a long-term study in a floodplain lake I. O’Farrell et al. https://doi.org/10.1007/s00027-010-0175-2
3. Seasonal and inter-annual variability of water quality in the Uruguay River, Argentina J. Colombo et al. https://doi.org/10.1080/02626667.2014.905690
4. Possible influence of ENSO on annual maximum streamflow of the Yangtze River, China Q. Zhang et al. https://doi.org/10.1016/j.jhydrol.2006.08.010
5. Effects of El-Niño and La-Niña Sea Surface Temperature Anomalies on Annual Precipitations and Streamflow Discharges in Southeastern United States C. Clark et al. https://doi.org/10.2112/SI68-015.1
6. Previsão Sazonal de Vazões para a Bacia do Orós (Ceará, Brasil) Utilizando Redes Neurais e a Técnica De Reamostragem dos K-vizinhos C. Araújo et al. https://doi.org/10.1590/0102-7786351015
7. American cutaneous leishmaniasis associated with degradation of native forest, regardless of economic, social and infrastructure vulnerability E. Caldart et al. https://doi.org/10.1111/zph.12793
8. Padrões de Variabilidade de Vazão de Rios nas Principais Bacias Brasileiras e Associação com Índices Climáticos C. Capozzoli et al. https://doi.org/10.1590/0102-77863220006
9. Streamflow changes of the Changjiang (Yangtze) River in the recent 60 years: Impacts of the East Asian summer monsoon, ENSO, and human activities W. Wei et al. https://doi.org/10.1016/j.quaint.2013.10.064
10. Spectral‐temporal characterization of riverflow variability in England and Wales for the period 1865–2002 A. Sen https://doi.org/10.1002/hyp.7224
11. River effects on sea-level rise in the Río de la Plata estuary during the past century C. Piecuch https://doi.org/10.5194/os-19-57-2023
12. Large scale meteorological phenomena, ENSO and ITCZ, define the Paraná River isotope composition H. Panarello & C. Dapeña https://doi.org/10.1016/j.jhydrol.2008.11.026
13. Previsões multiescala de vazões para o sistema hidrelétrico brasileiro utilizando ponderação bayesiana de modelos (BMA) V. Oliveira & C. Lima https://doi.org/10.1590/2318-0331.011616032
14. Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil C. Lima et al. https://doi.org/10.5194/esd-8-1071-2017
15. Effect of large-scale oceanic and atmospheric processes on the Indian summer monsoon S. Lenka et al. https://doi.org/10.1007/s00704-021-03896-3
16. Climatic variability of river outflow in the Pantanal region and the influence of sea surface temperature C. Silva et al. https://doi.org/10.1007/s00704-016-1760-7
17. Multivariate analysis for medium- and long-range forecasting of Nile River flow to mitigate drought and flood risks H. Ahmed et al. https://doi.org/10.1007/s11069-021-04968-3
18. Spatiotemporal Analysis on the Teleconnection of ENSO and IOD to the Stream Flow Regimes in Java, Indonesia A. Nugroho et al. https://doi.org/10.3390/w14020168
19. Climate informed monthly streamflow forecasts for the Brazilian hydropower network using a periodic ridge regression model C. Lima & U. Lall https://doi.org/10.1016/j.jhydrol.2009.11.016
20. Hierarchical Bayesian modeling of multisite daily rainfall occurrence: Rainy season onset, peak, and end C. Lima & U. Lall https://doi.org/10.1029/2008WR007485
21. Monthly streamflow forecast for National Interconnected System (NIS) using Periodic Auto-regressive Endogenous Models (PAR) and Exogenous (PARX) with climate information C. Silveira et al. https://doi.org/10.1590/2318-0331.011715186
22. Hydrological natural inflow and climate variables: Time and frequency causality analysis X. Huang et al. https://doi.org/10.1016/j.physa.2018.09.079
23. The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia A. Nugroho et al. https://doi.org/10.3390/w13101375