Publications

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Published Peer-Reviewed Journal Articles

(Chronologically) Update: April 01, 2026

2026 [7] Saeedi, Mohammad., Kim, H., Bolten, J., Eylander, J., & Lakshmi, V. Beyond Satellite-based Precipitation Data: A Novel Soil Moisture Physics Framework with Green-Ampt and Bayesian Optimization for Rainfall Estimation.
npj Climate and Atmospheric Science. (Link)

2026 [6] Saeedi, Mohammad., Kim, H., Kim, S., Choi., & Lakshmi, V. Depth-Aware Global Calibration of SM2RAIN-NWF Using Growing Neural Gas-Derived Hydroclimatic Clusters Across Heterogeneous Soils.
Water Resources Research. (Link)

2025 [5] Saeedi, Mohammad., Kim, H., & Lakshmi, V. Introducing a new clustering-based method for regionalization framework for continental-scale rainfall estimates from soil moisture dynamics using machine learning methods.
Agricultural and Forest Meteorology. (Link)

2023 [4] Saeedi, Mohammad., Nabaei, S., Kim, H., Tavakol, A., & Lakshmi, V. Performance assessment of SM2RAIN-NWF using ASCAT soil moisture via supervised land cover-soil-climate classification.
Remote Sensing of Environment. (Link)

2022 [3] Saeedi, Mohammad., Kim, H., Nabaei, S., Brocca, L., Lakshmi, V., & Mosaffa, H. A comprehensive assessment of SM2RAIN-NWF using ASCAT and a combination of ASCAT and SMAP soil moisture products for rainfall estimation.
Science of the Total Environment. (Link)

2022 [2] Saeedi, Mohammad., Sharafati, A., Brocca, L., & Tavakol, A. Estimating rainfall depth from satellite-based soil moisture data: A new algorithm by integrating SM2RAIN and the analytical net water flux modelse.
Journal of Hydrology. (Link)

2021 [1] Saeedi, Mohammad., Sharafati, A., & Tavakol, A. Evaluation of gridded soil moisture products over varied land covers, climates, and soil textures using in situ measurements: A case study of Lake Urmia Basin.
Theoretical and Applied Climatology. (Link)

Conference Papers

(Chronologically) Update: 2025

2025 [6] Ziyue Zhu, Saeedi, Mohammad., Kim, H., & Lakshmi, V. Interpreting Upstream Influence on Downstream River Discharge Forecasting: Insights from ConvLSTM and SHAP Analyses Across Spatial Scales and Temporal Horizons.
AGU Fall Meeting.

2025 [5] Saeedi, Mohammad., Saeedi, M., Kim, H.,…, & Lakshmi, V. A Novel Hybrid CNN-LSTM Approach to Dynamically Parameterize the Soil Water Balance for Improved and Self-Calibration of Global Rainfall Estimation..
AGU Fall Meeting.

2025 [4] Saeedi, Mohammad., Kim, H.,…, & Lakshmi, V. Turning Streams into Rain Gauges: Leveraging Long-Term Streamflow Data to Recover Historical Precipitation.
AGU Fall Meeting.

2024 [3] Saeedi, Mohammad., & Lakshmi, V. Leveraging Satellite Soil Moisture Data for Global Rainfall Estimation Using a Bottom-Up Approach: Exploring the Global Potential of SM2RAIN-NWF.
AGU Fall Meeting.

2024 [2] Saeedi, Mohammad., Kim, H.,…, & Lakshmi, V. Leveraging Machine Learning to Improve Rainfall Estimation: A Study on Noise Reduction in Soil Moisture Time Series in Areas with In-Situ Data Limitation.
AGU Fall Meeting.

2023 [1] Saeedi, Mohammad., Kim, H., & Lakshmi, V. Beyond the Conventional: Advancements in Rainfall Estimation through a Bottom-Up Approach and Net Water Flux.
AGU Fall Meeting.