Articles | Volume 30, issue 13
https://doi.org/10.5194/hess-30-4271-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Disentangling the key drivers of water balance in Central Asia's Lake Balkhash: A relative contribution assessment
Related authors
Cited articles
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., and Hegewisch, K. C.: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015, Sci. Data, 5, 170191, https://doi.org/10.1038/sdata.2017.191, 2018.
Alimkulov, S., Makhmudova, L., Talipova, E., Baspakova, G., Myrzakhmetov, A., Smagulov, Z., and Zagidullina, A.: Long-term water level projections for Lake Balkhash using scenario-based water balance modeling under climate and socioeconomic uncertainties, Water, 17, 2021, https://doi.org/10.3390/w17132021, 2025.
Altenau, E. H., Pavelsky, T. M., Durand, M. T., Yang, X., Frasson, R. P. de M., and Bendezu, L.: The surface water and ocean topography (SWOT) mission river database (SWORD): A global river network for satellite data products, Water Resour. Res., 57, e2021WR030054, https://doi.org/10.1029/2021WR030054, 2021.
Behrouz, M. S., Yazdi, M. N., and Sample, D. J.: Using random forest, a machine learning approach to predict nitrogen, phosphorus, and sediment event mean concentrations in urban runoff, J. Environ. Manage., 317, 115412, https://doi.org/10.1016/j.jenvman.2022.115412, 2022.
Budyko, M. I.: Climate and Life, International Geophysics Series, Vol. 18, Academic Press, New York, 508 pp., 1974.