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Yong Feng, Nijia Qian*, Qingqing Tong, et al. (2025). Enhanced Detection of Drought Events in California’s Central Valley Basin Using Rauch–Tung–Striebel Smoothed GRACE Level-2 Data: Mechanistic Insights from Climate–Hydrology Interactions

  • Release time:2026-05-23
  • Hits:

  • Journal: 

    Remote Sensing

  • Key Words: 

    GRACE; state space model; generalized three-cornered hat; GRACE groundwater drought index; El Niño–Southern Oscillation

  • Abstract: 

    To mitigate the impact of north–south strip errors inherent in Gravity Recovery and Climate Experiment (GRACE) spherical harmonic coefficient solutions, this research develops a state-space model to generate a more robust solution. The efficacy of the state-space model is demonstrated by comparing its performance with that of conventional filtering methods and hydrological modeling schemes. The method is subsequently applied to estimate the GRACE Groundwater Drought Index in the California Central Valley basin, a region significantly affected by drought during the GRACE observation period. This analysis quantifies the severity of droughts and floods while investigating the direct influences of precipitation, runoff, evaporation, and anthropogenic activities. By incorporating the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation, the study offers a detailed causal analysis and proposes a novel methodology for water resource management and disaster early warning. The results indicate that a moderate-duration flood event in 2006 resulted in a recharge of 19.81 km3 of water resources in the California Central Valley basin, whereas prolonged droughts in 2008 and 2013, lasting over 15 months, led to groundwater depletion of 41.53 km3 and 91.45 km3, respectively. Precipitation and runoff are identified as the primary determinants of local drought and flood conditions. The occurrence of ENSO events correlates with sustained precipitation variations over the subsequent 2–3 months, resulting in corresponding changes in groundwater storage.

  • Indexed by: 

    Journal paper

  • Discipline: 

    Engineering

  • First-Level Discipline: 

    Surveying and Mapping

  • Document Type: 

    J

  • Translation or Not: 

    no

  • Included Journals: 

    SCI
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