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Article

515 Views

26 Pages

Privacy-Preserving Federated Learning for Hydrological Forecasting in the Chu–Talas Basin

Raushan Amanzholova,
Azamat Serek,
Adil Akhmetov,
Zhuldyzbek Onglassynov,
Sholpan Kulbekova,
Issa Rakhmetov and
Janay Sagin

Water2026, 18(11), 1361;https://doi.org/10.3390/w18111361

3 June 2026

The hydrological prediction in transboundary river basins is difficult because of their heterogeneous data distribution, restrictions of data sovereignty, and the irregular nature of the discharge pattern. In this paper, Federated Learning (FL) with...

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17 Citations

3,618 Views

16 Pages

Evaluation and Application of MSWEP in Drought Monitoring in Central Asia

Min Li,
Xiaoyu Lv,
Li Zhu,
Friday Uchenna Ochege and
Hao Guo

Atmosphere2022, 13(7), 1053;https://doi.org/10.3390/atmos13071053

1 July 2022

Thanks to the large scope, high spatial resolution, and increasing data records, satellite-based precipitation products are playing an increasingly important role in drought monitoring. First, based on the data from ground sites, the long-term Multi-...

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28 Citations

9,073 Views

23 Pages

An Unsupervised Classification Algorithm for Multi-Temporal Irrigated Area Mapping in Central Asia

Silvan Ragettli,
Timo Herberz and
Tobias Siegfried

Remote Sens.2018, 10(11), 1823;https://doi.org/10.3390/rs10111823

17 November 2018

Sound water resources planning and management requires adequate data with sufficient spatial and temporal resolution. This is especially true in the context of irrigated agriculture, which is one of the main consumptive users of the world’s fre...

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