Journal articles

Li, P., Shen, C., Liu, J., Rahmani, F., Pan, M., & Lawson, K. (accepted for publication). Systematic discrepancies should be addressed before effective parameter learning: Insights from soil moisture simulations using differentiable process-based models. Water Resources Research.
Li, P., Song, Y., Pan, M., Lawson, K., & Shen, C. (2025). Ensembling differentiable process-based and data-driven models with diverse meteorological forcing datasets to advance streamflow simulation. Hydrology and Earth System Sciences, 29(23), 6829–6861. DOI
Li, P., Zha, Y., Zhang, Y., et al. (2024). Deep learning integrating scale conversion and pedo-transfer function to avoid potential errors in cross-scale transfer. Water Resources Research, 60(3), e2023WR035543. DOI
Li, P., Zha, Y., Zuo, B., & Zhang, Y. (2023). A family of soil water retention models based on sigmoid functions. Water Resources Research, 59, e2022WR033160. DOI
Li, P., Zha, Y., & Tso, C.-H. M. (2023). Reconstructing GRACE-derived terrestrial water storage anomalies with in-situ groundwater level measurements and meteorological forcing data. Journal of Hydrology: Regional Studies, 50, 101528. DOI
Li, P., Zha, Y., Shi, L., & Zhong, H. (2022). Assessing the global relationships between teleconnection factors and terrestrial water storage components. Water Resources Management, 36, 119–133. DOI
Li, P., Zha, Y., Shi, L., & Zhong, H. (2021). Identification of the terrestrial water storage change features in the North China Plain via independent component analysis. Journal of Hydrology: Regional Studies, 38, 100955. DOI
Li, P., Zha, Y., Shi, L., Tso, C. H. M., Zhang, Y., & Zeng, W. (2020). Comparison of the use of a physical-based model with data assimilation and machine learning methods for simulating soil water dynamics. Journal of Hydrology, 584, 124692. DOI
Li, P., Zha, Y., Tso, C. H. M., Shi, L., Yu, D., Zhang, Y., & Zeng, W. (2020). Data assimilation of uncalibrated soil moisture measurements from frequency-domain reflectometry. Geoderma, 374, 114432. DOI

Conferences

Li, P., Zha, Y., Tso, C. H. M., Shi, L., Yu, D., Zhang, Y., Zeng, W., & Peng, J. (2023). Bias detection of ISMN soil moisture measurements through soil water balance model and data assimilation. EGU General Assembly 2023, Vienna, Austria.