Do land models miss key soil hydrological processes controlling soil moisture memory? MA Farmani, A Behrangi, A Gupta, A Tavakoly, M Geheran, GY Niu. Hydrology and Earth System Sciences 29 (2), 547-566.
Mohammad A. Farmani, Ahmad A. Tavakoly, Ali Behrangi, et al. Improving Streamflow Predictions in the Arid Southwestern United States Through Understanding of Baseflow Generation Mechanisms. ESS Open Archive, 2024. DOI: 10.22541/essoar.173272456.69006273/v1.
Hossein Yousefi Sohi, Mohammad A. Farmani, Ali Behrangi. How do IMERG V07, IMERG V06, and ERA5 Precipitation Products Perform Over Snow-ice-free and Snow-ice-covered Surfaces at a Range of Near Surface Temperatures? ESS Open Archive, 2024. DOI: 10.22541/essoar.172675931.16404474/v1.
Niu, G.-Y., Fang, Y., Alves Meira Neto, A., Guo, B.,Zhang, X-Y, Farmani, M., Behrangi, A., and Zeng, X. Representing Preferential Flow through Variably-Saturated Soils with Surface Ponding in a Large-Scale Land Surface Model over the Conterminous US. ESS Open Archive, 2024. DOI: 10.22541/essoar.172286649.90332939/v1.
Farmani, M. A., Behrangi, A., Gupta, A., Tavakoly, A., Geheran, M., and Niu, G.-Y.: What Are the Key Soil Hydrological Processes to Control Soil Moisture Memory?, EGUsphere [preprint], 10.5194/egusphere-2024-1256, 2024.
Jawad, Muhammad, Behrangi, Ali, Farmani, Mohammad, Qiu, Yuan, Yousefi, Hossein, Gupta, Aniket, and Niu, Guo-Yue. Improved Evapotranspiration Estimation Using the Penman-Monteith Equation with a Deep Learning (Dnn) Model Over the Dry Southwestern US: Comparison with Ecostress, Modis, and Openet. Available at SSRN or DOI: 10.2139/ssrn.5026281.
Agnihotri, J., Behrangi, A., Tavakoly, A., Geheran, M., Farmani, M. A., & Niu, G. Y. (2023). Higher frozen soil permeability represented in a hydrological model improves spring streamflow prediction from river basin to continental scales. Water Resources Research, 59(4), e2022WR033075.
Mohammad A. Farmani, Ahmad A. Tavakoly, Ali Behrangi, et al. Improving Streamflow Predictions in the Dry Southwestern United States Through Understanding of Baseflow Generation Mechanisms. AGU24.
Hossein Yousefi Sohi, Mohammad A. Farmani, Ali Behrangi. How do IMERG V07, IMERG V06, and ERA5 Precipitation Products Perform Over Snow-ice-free and Snow-ice-covered Surfaces? AGU24.
Qiu, Y., Niu, G. Y., Behrangi, A., Famiglietti, J. S., Farmani, M., Gupta, A., et al. The Significant Impact of Precipitation Intensity on Natural Groundwater Recharge and Terrestrial Water Storage Change in Arid Regions. AGU24.
Gupta, A., Behrangi, A., Farmani, M. A., Niu, G.-Y. Implementing the machine learning based Van-Genuchten parametrization in the NextGen Framework for improved streamflow prediction. AGU24.
Farmani, M. A., Behrangi, A., Gupta, A., Tavakoly, A., Geheran, M., and Niu, G.-Y. What Are the Key Soil Hydrological Processes to Control Soil Moisture Memory? CMWR 2024.
Niu, G.-Y., Fang, Y., Alves Meira Neto, A., Guo, B., Farmani, M., and Behrangi, A. Representing Preferential Flow through Variably Saturated Soils with Surface Ponding in Noah-MP. AGU 2023, H11G-1343.
Gupta, A., Behrangi, A., Farmani, M., and Niu, G.-Y., “Impact of Vegetation Dynamics on Hydrological Fluxes using Noah-MP Coupled to NextGen Modeling Framework: A Case Study of High-resolution Hydrological Simulations over California. AGU 2023, H31V-1798.