Total terrestrial water storage modeling at sub-monthly and monthly timescales over Iran using line-of-sight gravity differences data and a spherical cap harmonic basis function

<p>Every year, 4 billion cubic meters of irreversible underground water from Iran is pumped to the earth's surface, exposing Iran's freshwater supplies to indiscriminate and poorly managed withdrawals. The future basins water supply in central and northern Iran is projected to face significant challenges due to the rising demand for groundwater on the one hand, and the high rate of irrigation and overexploitation of water resources in some places, on the other. So investigating, monitoring and prediction of total terrestrial water storage modelling always plays crucial role to obtain more information about climate changes of the Iran.</p> <p>The GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On (FO) satellite gravity missions enable global monitoring of the mass transport within the Earth’s system, leading to our understanding of the global water cycle in the climate changes of the Earth. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations at different timescales. While the parametrization using GRACE gravity data has been extensively used to assess spatial-temporal changes in TWS, little effort has been made to exhibit mass variation based on regional harmonic basis function.</p> <p>This study focuses on the parametrization (especially in the higher frequency domain) for TWS variations at sub monthly and monthly time scales over Iran using LGD (Line of sight Gravity Differences) data obtained by GRACE-FO missions based on a regional harmonic basis function. We will apply regional harmonic basis functions. i.e. spherical cap harmonic (SCH) functions to provide nearly full extracting of gravitational signal over a spherical cap region that are generally underestimated by GRACE Level2 product. In particular, we analyzed whether the estimated storage component represented the TWS variations at monthly and sub-monthly temporal scales, and whether the estimated component is consistent across small to large spatial scales.</p> <p> </p>