A5022867384- Geophysics and Gravity Measurements
- GNSS positioning and interference
- Soil Moisture and Remote Sensing
- Meteorological Phenomena and Simulations
- Solar and Space Plasma Dynamics
- Geomagnetism and Paleomagnetism Studies
- Remote Sensing and LiDAR Applications
- Flood Risk Assessment and Management
- Geophysical and Geoelectrical Methods
- Hydrology and Watershed Management Studies
- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Climate change and permafrost
- Computational Physics and Python Applications
- Remote Sensing in Agriculture
- Reservoir Engineering and Simulation Methods
- Cryospheric studies and observations
- Geology and Paleoclimatology Research
- Precipitation Measurement and Analysis
- Landslides and related hazards
- Geological Modeling and Analysis
- Groundwater and Isotope Geochemistry
- Remote Sensing and Land Use
- Agriculture Sustainability and Environmental Impact
- Climate change impacts on agriculture
Asian Institute of Technology
2023-2025
Earth System Science Interdisciplinary Center
2019-2023
University of Maryland, College Park
2019-2023
Goddard Space Flight Center
2019-2023
University of Newcastle Australia
2016-2020
Delft University of Technology
2014-2018
National Yang Ming Chiao Tung University
2011-2016
Abstract The scarcity of groundwater storage change data at the global scale hinders our ability to monitor resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) scale, with goal generating time series that are useful for drought monitoring other applications. Evaluation using in situ nearly 4,000 wells shows GRACE...
Abstract. The ability to estimate terrestrial water storage (TWS) realistically is essential for understanding past hydrological events and predicting future changes in the cycle. Inadequacies model physics, uncertainty land parameters, uncertainties meteorological data commonly limit accuracy of models simulating TWS. In an effort improve performance, this study investigated benefits assimilating TWS estimates derived from Gravity Recovery Climate Experiment (GRACE) into OpenStreams...
In this study, satellite observations including gravity (GRACE), terrestrial reflectance (MODIS), and global precipitation (TRMM) data, along with the output from PCR-GLOBWB hydrological model, are used to generate monthly sub-monthly water storage (TWS) estimates quantify flood events over Tonlé Sap basin between 2002 2014. This study is first time GRACE data have been investigate processes basin. To improve accuracy of TWS GRACE, a signal restoration method was applied in an effort recover...
Abstract. An accurate estimation of water resources dynamics is crucial for proper management both agriculture and the local ecology, particularly in semi-arid regions. Imperfections model physics, uncertainties land parameters meteorological data, as well human impact on changes often limit accuracy hydrological models estimating storages. To mitigate this problem, study investigated assimilation terrestrial storage variation (TWSV) estimates derived from Gravity Recovery And Climate...
The accurate knowledge of the groundwater storage variation (ΔGWS) is essential for reliable water resource assessment, particularly in arid and semi-arid environments (e.g., Australia, North China Plain (NCP)) where significantly affected by human activities spatiotemporal climate variations. large-scale ΔGWS can be simulated from a land surface model (LSM), but high uncertainty major drawback that reduces reliability estimates. evaluation estimate then very important to assess its...
The construction of hydropower dams is a common strategy to support country's increasing need for electricity and river water management industry agriculture. Although the hydrological geophysical impacts relocation are usually assessed prior impoundment, their accuracy generally limited due lack in situ observations, especially remote area. This study presents workflow quantify terrestrial storage change (∆TWS) land subsidence induced by reservoir's impoundment using multiple satellite...
Accurate terrestrial water storage (TWS) estimation is important to evaluate the situation of resources over Yangtze River Basin (YRB). This study exploits TWS observation from new temporal gravity field model, HUST-Grace2016 (Huazhong University Science and Technology), which developed by a low-frequency noise processing strategy. A novel GRACE (Gravity Recovery Climate Experiment) post-processing approach proposed enhance quality estimate, improved used characterize drought flood events...
Abstract. An accurate estimation of soil moisture and groundwater is essential for monitoring the availability water supply in domestic agricultural sectors. In order to improve storage estimates, previous studies assimilated terrestrial variation (ΔTWS) derived from Gravity Recovery Climate Experiment (GRACE) into land surface models (LSMs). However, GRACE-derived ΔTWS was generally computed high-level products (e.g. time-variable gravity fields, i.e. level 2, grid 3 product). The gridded...
Hydrology and land surface models (HM LSM) are essential tools for estimating global terrestrial water storage (TWS), an important component of the budget assessing accessibility long-term variability supplies. With expansion open-source open-data policies, community can now perform model TWS simulation from source codes as well directly exploit end-user hydrologic products resource applications. Regardless effectiveness usability, accuracy assessment is necessary to quantify model’s...
 Hydrological modeling is essential for understanding water balance dynamics, yet physical models often face limitations such as computational inefficiency, insufficient representation of complex processes, and challenges in integrating diverse data sources. To address these limitations, data-driven offer enhanced predictive capabilities, scalability, real-time analysis potential. In this study, a Long Short-Term Memory (LSTM) model was developed to simulate the using open-source...
Terrestrial hydrologic trends over the conterminous United States are estimated for 1980-2015 using National Climate Assessment Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs uncoupled Noah version 3.3 land surface model at 0.125°× 1258° forced with NLDAS-2 meteorology, rescaled Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth, irrigation products. Mean annual reported nonparametric Mann-Kendall test
Abstract The mass loss of the Greenland Ice Sheet (GrIS) has profound impacts on sea levels, water cycle, and global climate variability. Gravity Recovery Climate Experiment (GRACE) its follow‐on mission (GRACE‐FO) provide accurate but limited spatial resolution observations GrIS changes. Therefore, we developed a novel multi‐time scale weighted forward modeling (WFM) approach that combines GRACE(‐FO) with satellite altimetry data to improve change estimations in at high‐resolution (25 km ×...
Abstract Hydroclimatic stresses can negatively impact crop production via water deficits (low soil supply and high atmospheric demand) or surpluses (high low demand). However, the of both on yields at regional scales is not well understood. Here we quantified yield sensitivities corresponding spatio-temporal losses US rainfed maize, soybeans, sorghum, spring wheat to hydroclimatic by considering joint impacts root-zone moisture evaporative demand from 1981 2020. We show that be reduced...
Lakes Baikal and Balkhash are two of the world's major lakes affecting fresh water supplies in their catchments.Measurements from satellite altimetry (TOPEX/Poseidon, Jason-1 -2), gravimetry (GRACE) a hydrological model (LDAS) used to see relationship between lake level change (LLC) storage these lakes.At Lake Baikal, average rate LLC is negative for 1992 -1998 positive 1998 -2007, reversal trend concurs with that temperature during 1997 El Niño.The gravity ranges -0.5 0.5 μgal yr -1 low...