Joint assimilation of satellite soil moisture and vegetation conditions improves estimates of gross primary production and evapotranspiration over South Asia

Abstract

Soil moisture and vegetation critically influence the availability and distribution of water and carbon within terrestrial ecosystems. Therefore, realistic representations of soil moisture and vegetation dynamics in land surface models are essential to better understand land–atmospheric interactions. However, uncertainties in inputs and static vegetation parameterization restrict the model’s accuracy in capturing the variation in these fluxes across larger domains like South Asia. To overcome these limitations, this study implements a joint data assimilation framework within the Indian Land Data Assimilation System (ILDAS) using the Ensemble Kalman Filter method to assimilate Soil Moisture Active Passive (SMAP) and Global Land Surface Satellites (GLASS) leaf area index (LAI) data, to explore the influence on evapotranspiration (ET) and gross primary production (GPP) over South Asia. The Noah-MP land surface model simulates the land surface processes incorporating the meteorological forcings from MERRA2 and the Indian Meteorological Department (IMD) within ILDAS. Model estimates are statistically evaluated with in-situ and satellite datasets. The results demonstrate that data assimilation (DA) reduces variability in the estimates of soil moisture, LAI, GPP, and ET compared to the open-loop simulations. Seasonal differences between DA and open loop (OL) estimates of GPP, ET, and LAI vary predominantly in central and northern India during the pre-monsoon season, with standard deviations of 59.87 gC/m²/month, 29.33 mm/month and 0.706 m²/m², respectively. The improvements due to DA vary seasonally, with enhancements observed during certain months and across different land cover types due to seasonal variability in vegetation and soil moisture dynamics. Significant improvements in GPP and ET are observed over croplands and grasslands. This study is the first to explore the applicability of joint assimilation of soil moisture and leaf area index over South Asia and it provides valuable insights for future applications in eco-hydrological studies by assessing their combined impact on water and carbon fluxes.