Terrestrial Water Storage (TWS) is a key indicator in water resource management and climate research, as it represents the total amount of water stored in land components like soil moisture, groundwater, snow, and surface water. Accurate TWS estimates are essential for assessing water availability, drought conditions, and flood risks. In climate research, long-term TWS records help monitor reliable climate variations, such as trends in water storage due to climate change or anthropogenic influences. High-resolution TWS data is particularly valuable for regional studies because it allows for more detailed insights into localized water storage dynamics. However, obtaining high-resolution TWS data over long periods is challenging, as such data are often scarce in the public domain.
Simulating high-resolution TWS data, especially over long time records, requires advanced computational techniques, including parallel computing. This level of modeling demands significant resources and expertise. In ALICE-Lab, we have the capability to simulate high-resolution TWS data using supercomputing facilities, which enables us to conduct detailed regional studies and better capture climate variations. This computational power is critical for producing reliable simulations and analyses that can inform water resource management and contribute to climate science.
Figure 1: High-resolution map of Terrestrial Water Storage (TWS) anomalies for September 2024 across California. TWS reflects the total water stored in land components, including soil moisture, groundwater, and snow. The map shows regions with above-average water storage (cool tones) and below-average storage (warm tones), in comparison to the baseline period from 2004 to 2009. This information is vital for analyzing water resource availability, monitoring drought conditions, and studying the impacts of climate variability, revealing how regional water storage fluctuations affect ecosystems and resource management.
The Regional TWS Simulation at 5 km (RTWS5) is generated using the land surface model (LSM) at a high spatial resolution of 5 km, spanning from 1940 to the present. The LSM is designed to simulate land-atmosphere interactions, including key processes such as soil moisture, snow dynamics, vegetation, and energy exchanges and simulates Terrestrial Water Storage (TWS) by accounting for major water storage components, including soil moisture across four layers, snow water equivalent, canopy storage, and groundwater. The model is run at a sub-daily timestep and producing monthly TWS outputs to align with the temporal resolution of remote sensing such as GRACE observations.
More details on the LSM can be found here.
Spatial Resolution: 0.05 equal-area grid (~5 km)
Temporal Resolution: 1 month
Time span: 1940 – Present
File format: NetCDF
Latency: 1 month
Variables
| Variables | Name | Unit |
|---|---|---|
| TWS | Terrestrial Water Storage | mm |
| CanopInt | Total Canopy Water Storage | kg/m2 |
| SWE | Snow Water Equivalent | kg/m2 |
| SoilMoist1 | Average layer 1 soil moisture (10 cm) | m3/m3 |
| SoilMoist2 | Average layer 2 soil moisture (30 cm) | m3/m3 |
| SoilMoist3 | Average layer 3 soil moisture (60 cm) | m3/m3 |
| SoilMoist4 | Average layer 4 soil moisture (100 cm) | m3/m3 |
| GWS | Ground Water Storage | mm |
This map displays Terrestrial Water Storage (TWS) anomalies in California, relative to the mean water storage during the period from 2004 to 2009. It highlights areas where water storage is above (cool tones) or below (warm tones) the average levels observed during those years. This data is essential for understanding fluctuations in water availability, assessing drought conditions, and studying the impacts of climate variability on regional water resources. By comparing current anomalies to this baseline, the map helps illustrate shifts in water storage and supports efforts in water resource management and climate impact analysis.
This map shows Terrestrial Water Storage (TWS) anomalies in High-Plains Aquifer, relative to the average water storage from 2004 to 2009. Regions with higher than average water storage are represented in cool tones, while areas with lower than average storage are shown in warm tones. This visualization is vital for monitoring changes in water availability, analyzing drought impacts, and evaluating climate effects on water resources. By comparing current TWS values to this baseline period, the map provides valuable insights into regional water storage dynamics and helps inform resource management and climate adaptation strategies.
