31 citations as recorded by crossref.

1. The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection X. Ji & C. Shen https://doi.org/10.1016/j.cageo.2017.09.014
2. Estimating soil moisture using Sentinel-1 and Sentinel-2 sensors for dryland and palustrine wetland areas R. Gangat et al. https://doi.org/10.17159/sajs.2020/6535
3. Multi-depth soil moisture estimation via 1D convolutional neural networks from drone-mounted ground penetrating Radar data M. Vahidi et al. https://doi.org/10.1016/j.compag.2025.110104
4. A fused soil moisture product integrating linear fusion method and error characteristics approach A. Singh et al. https://doi.org/10.1080/01431161.2026.2653239
5. Quantifying the space – time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework H. Qiu et al. https://doi.org/10.1016/j.scitotenv.2019.04.147
6. A Multiscale Deep Learning Model for Soil Moisture Integrating Satellite and In Situ Data J. Liu et al. https://doi.org/10.1029/2021GL096847
7. Development of a computationally efficient semi-distributed hydrologic modeling application for soil moisture, lateral flow and runoff simulation H. Ajami et al. https://doi.org/10.1016/j.envsoft.2016.09.002
8. Improving the representation of hydrologic processes in Earth System Models M. Clark et al. https://doi.org/10.1002/2015WR017096
9. Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0) G. Bisht et al. https://doi.org/10.5194/gmd-10-4539-2017
10. Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter Y. Li et al. https://doi.org/10.3390/rs15071852
11. Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks U. Mishra & W. Riley https://doi.org/10.5194/bg-12-3993-2015
12. Seasonal and Interannual Patterns and Controls of Hydrological Fluxes in an Amazon Floodplain Lake With a Surface‐Subsurface Process Model X. Ji et al. https://doi.org/10.1029/2018WR023897
13. Quantifying the integrated water and carbon cycle in a data-limited karst basin using a process-based hydrologic model H. Qiu et al. https://doi.org/10.1007/s12665-019-8324-y
14. Interannual Variation in Hydrologic Budgets in an Amazonian Watershed with a Coupled Subsurface–Land Surface Process Model J. Niu et al. https://doi.org/10.1175/JHM-D-17-0108.1
15. A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape G. Pau et al. https://doi.org/10.5194/gmd-7-2091-2014
16. The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics C. Shen et al. https://doi.org/10.1002/2015WR018086
17. Combining a land surface model with groundwater model calibration to assess the impacts of groundwater pumping in a mountainous desert basin K. Fang et al. https://doi.org/10.1016/j.advwatres.2019.05.008
18. A Hybrid Reduced‐Order Model of Fine‐Resolution Hydrologic Simulations at a Polygonal Tundra Site Y. Liu et al. https://doi.org/10.2136/vzj2015.05.0068
19. Soil Moisture for Hydrological Applications: Open Questions and New Opportunities L. Brocca et al. https://doi.org/10.3390/w9020140
20. Importance and strength of environmental controllers of soil organic carbon changes with scale K. Adhikari et al. https://doi.org/10.1016/j.geoderma.2020.114472
21. Streamflow, stomata, and soil pits: Sources of inference for complex models with fast, robust uncertainty quantification M. Dwelle et al. https://doi.org/10.1016/j.advwatres.2019.01.002
22. A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability C. Montzka et al. https://doi.org/10.3390/rs10030427
23. Virtual laboratory for understanding impact of heterogeneity on ecohydrologic processes across scales K. Wang & P. Kumar https://doi.org/10.1016/j.envsoft.2021.105283
24. Hierarchical sensitivity analysis for a large-scale process-based hydrological model applied to an Amazonian watershed H. Liu et al. https://doi.org/10.5194/hess-24-4971-2020
25. Variability of flow discharge in lateral inflow-dominated stream channels C. Chang & H. Yeh https://doi.org/10.5194/hess-19-2505-2015
26. Size Distributions of Arctic Waterbodies Reveal Consistent Relations in Their Statistical Moments in Space and Time S. Muster et al. https://doi.org/10.3389/feart.2019.00005
27. Modeling the Arctic freshwater system and its integration in the global system: Lessons learned and future challenges C. Lique et al. https://doi.org/10.1002/2015JG003120
28. A hybrid‐3D hillslope hydrological model for use in Earth system models P. Hazenberg et al. https://doi.org/10.1002/2014WR016842
29. Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow X. Ji et al. https://doi.org/10.1016/j.advwatres.2015.09.027
30. Effects of meteorological forcings and land surface model on soil moisture simulation over China J. Zeng et al. https://doi.org/10.1016/j.jhydrol.2021.126978
31. Mineral properties, microbes, transport, and plant-input profiles control vertical distribution and age of soil carbon stocks D. Dwivedi et al. https://doi.org/10.1016/j.soilbio.2016.12.019