Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-41-2021
https://doi.org/10.5194/hess-25-41-2021
Research article
 | 
04 Jan 2021
Research article |  | 04 Jan 2021

Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins

Yifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, and Kiran Shakya

Related authors

Benchmarking and evaluating the NASA Land Information System (version 7.5.2) coupled with the refactored Noah-MP land surface model (version 5.0)
Cenlin He, Tzu-Shun Lin, David M. Mocko, Ronnie Abolafia-Rosenzweig, Jerry W. Wegiel, and Sujay V. Kumar
EGUsphere, https://doi.org/10.5194/egusphere-2024-4176,https://doi.org/10.5194/egusphere-2024-4176, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Reactive nitrogen in and around the northeastern and mid-Atlantic US: sources, sinks, and connections with ozone
Min Huang, Gregory R. Carmichael, Kevin W. Bowman, Isabelle De Smedt, Andreas Colliander, Michael H. Cosh, Sujay V. Kumar, Alex B. Guenther, Scott J. Janz, Ryan M. Stauffer, Anne M. Thompson, Niko M. Fedkin, Robert J. Swap, John D. Bolten, and Alicia T. Joseph
Atmos. Chem. Phys., 25, 1449–1476, https://doi.org/10.5194/acp-25-1449-2025,https://doi.org/10.5194/acp-25-1449-2025, 2025
Short summary
Coupling the ParFlow Integrated Hydrology Model within the NASA Land Information System: A case study over the Upper Colorado River Basin
Peyman Abbaszadeh, Fadji Zaouna Maina, Chen Yang, Dan Rosen, Sujay Kumar, Matthew Rodell, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-280,https://doi.org/10.5194/hess-2024-280, 2024
Preprint under review for HESS
Short summary
Modeling irrigation and land surface dynamics: comparing AquaCrop and Noah-MP over the Po Valley
Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabrielle J. M. De Lannoy
EGUsphere, https://doi.org/10.2139/ssrn.4974019,https://doi.org/10.2139/ssrn.4974019, 2024
Short summary
Extending the utility of space-borne snow water equivalent observations over vegetated areas with data assimilation
Justin M. Pflug, Melissa L. Wrzesien, Sujay V. Kumar, Eunsang Cho, Kristi R. Arsenault, Paul R. Houser, and Carrie M. Vuyovich
Hydrol. Earth Syst. Sci., 28, 631–648, https://doi.org/10.5194/hess-28-631-2024,https://doi.org/10.5194/hess-28-631-2024, 2024
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025,https://doi.org/10.5194/hess-29-1659-2025, 2025
Short summary
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025,https://doi.org/10.5194/hess-29-1637-2025, 2025
Short summary
Distribution, trends, and drivers of flash droughts in the United Kingdom
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025,https://doi.org/10.5194/hess-29-1295-2025, 2025
Short summary
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025,https://doi.org/10.5194/hess-29-1201-2025, 2025
Short summary
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025,https://doi.org/10.5194/hess-29-1135-2025, 2025
Short summary

Cited articles

Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. 
Arsenault, K. R., Kumar, S. V., Geiger, J. V., Wang, S., Kemp, E., Mocko, D. M., Beaudoing, H. K., Getirana, A., Navari, M., Li, B., Jacob, J., Wegiel, J., and Peters-Lidard, C. D.: The Land surface Data Toolkit (LDT v7.2) – a data fusion environment for land data assimilation systems, Geosci. Model Dev., 11, 3605–3621, https://doi.org/10.5194/gmd-11-3605-2018, 2018. 
Barros, V. R. and Field, C. B.: Climate change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects, Cambridge University Press, Cambridge, UK, 2014. 
Bell, V. A., Davies, H. N., Kay, A. L., Brookshaw, A., and Scaife, A. A.: A national-scale seasonal hydrological forecast system: development and evaluation over Britain, Hydrol. Earth Syst. Sci., 21, 4681–4691, https://doi.org/10.5194/hess-21-4681-2017, 2017. 
Borovikov, A., Cullather, R., Kovach, R., Marshak, J., Vernieres, G., Vikhliaev, Y., Zhao, B., and Li, Z.: GEOS-5 seasonal forecast system, Clim. Dynam., 53, 7335–7361, 2019. 
Download
Short summary
South and Southeast Asia face significant food insecurity and hydrological hazards. Here we introduce a South and Southeast Asia hydrological monitoring and sub-seasonal to seasonal forecasting system (SAHFS-S2S) to help local governments and decision-makers prepare for extreme hydroclimatic events. The monitoring system captures soil moisture variability well in most regions, and the forecasting system offers skillful prediction of soil moisture variability 2–3 months in advance, on average.
Share