Welcome to the ALICE laboratory, dedicated to pioneering scientific research in climate, hydrology, environment, and agriculture in Asian regions, which historically deprived of crucial data. Our team prioritize the integration of advanced methodologies such as hydrology and land surface modeling, remote sensing, artificial intelligence (AI), data assimilation, and computational hydrology (via high-performance computing; HPC) to overcome data scarcity challenges. Our mission is to not only collect and analyze high-quality data but also to develop innovative techniques that enhance our understanding of the intricate relationships between climate, hydrological processes, and agricultural systems. By harnessing the power of cutting-edge technologies and fostering interdisciplinary collaboration, we aim to fill knowledge gaps, empower decision-makers, and drive sustainable development in data-sparse areas worldwide. Join us as we embark on a journey to revolutionize scientific research and create positive impact in communities facing data scarcity challenges.
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Enhancing Satellite Gravimetry for Sustainable Water Resource and Disaster Management
The project, “Enhancing Satellite Gravimetry for Sustainable Water Resource and Disaster Management,” seeks to revolutionize how Thailand and Southeast Asia monitor environmental changes by leveraging frontier Earth and Space Technology. Funded by the Program Management Unit for Frontier Brainpower and Future Industries (PMU-B), this initiative addresses a critical gap where global gravity data from the GRACE and GRACE-FO missions is currently provided at a spatial resolution (~300 km) too low for localized basin management. To resolve this, the project implements advanced regional processing and data integration techniques to sharpen these signals into high-resolution datasets. By accurately separating groundwater components from total water storage, the project provides a vital tool for monitoring depletion and preventing land subsidence. Ultimately, by establishing an Open Data platform and fostering a network of regional experts, this PMU-B supported initiative empowers government agencies to make science-based decisions, reducing economic losses from droughts and floods while positioning Thailand as a leader in international space technology.
Our laboratory is developing cutting-edge scientific methodologies to enhance satellite gravimetry products and expand their applicability for water resources, climate variability, and natural hazard assessments in Thailand and Southeast Asia. To support this effort, we are pleased to invite applications from motivated scientists to join our growing research team.
The workshop of “Nature-based Solutions for Enhancing Water Security in Chiang Rai” was attended by 25 participants from a variety of organizations, including the Chiang Rai Provincial Irrigation Office (RID), the International Union for Conservation of Nature (IUCN), the Chiang Rai Provincial Office of Natural Resources and Environment, the Chiang Rai Provincial Department of Disaster Prevention and Mitigation (DDPM), and the Chiang Rai Municipality. The primary objectives were to explore current water security scenarios and to co-develop ideal community adaptation strategies to address water-related hazards.
This workshop is a vital part of a larger project tackling Chiang Rai’s growing water security issues, which are worsened by climate change and rapid urbanization. Moving beyond traditional infrastructure, we are promoting Nature-based Solutions (NbS) as a more sustainable approach. This event is designed to bring key people together, so we can collectively understand the challenges and co-develop effective, local strategies to build a more resilient community.
A critical new era for Thailand’s climate resilience began today as our lab officially joined forces with the Asian Disaster Preparedness Center (ADPC) and key Thai government partners. At a high-profile kick-off event, our team solidified its pivotal role in a groundbreaking initiative to develop state-of-the-art flood risk assessments for two of Thailand’s most vulnerable river basins.
The training focused on transferring practical knowledge of THSF big data applications to multi-stakeholders for improved water and agricultural management under climate variability. The workshop also facilitated valuable networking among experts from government agencies, research institutions, and agricultural organizations, promoting collaborative approaches to climate-smart decision-making.
The Asian Institute of Technology (AIT) and ARDA will host a seminar on December 16, 2024, at Rama Gardens Hotel Bangkok, focusing on Thailand’s 1km high-resolution seasonal hydro-meteorological forecasting system. The event will explore using Big Data and geospatial insights to enhance smart agriculture and water management in the face of climate variability.
Analysis of soil moisture variations in South Rangsit, comparing Land Surface Model (LSM) data with Sentinel-1 satellite estimates. The study highlights how irrigation practices influence soil moisture patterns, particularly through sudden increases in the satellite data during the dry season.
Triple Collocation (TC) is a statistical method for assessing error variances among three independent datasets measuring the same variable, without requiring true values. It is widely used in remote sensing, hydrology, and meteorology to enhance data accuracy and reliability.
RECENTLY PUBLISHED
Our recent publications showcase our team’s ongoing research on satellite geodesy, terrestrial water storage variability, groundwater depletion, cryosphere dynamics, and hydrological modeling. These studies contribute to improving our understanding of global water cycle processes and large-scale mass change monitoring using advanced Earth observation and data analysis approaches.
Weight-Supported Random Forest Downscaled GRACE(-FO) Data
This study investigates groundwater depletion in the Lower Indus Basin (LIB), where intensive irrigation has led to unsustainable groundwater extraction. To address the coarse spatial resolution of satellite-derived water storage data, a Weight-Supported Random Forest (WSRF) model was developed to downscale data to a finer 0.1° resolution using precipitation, evapotranspiration, vegetation index, and soil moisture as predictors. The results showed high agreement with groundwater well observations (R² > 0.85) and revealed detailed spatial patterns of groundwater depletion from 2003–2023, highlighting the combined influence of climate variability and irrigation practices.
Dive into our comprehensive research themes at the Asian Land Information for Climate and Environmental Research Laboratory (ALICE-LAB). Our focus areas include:
Explore the cutting-edge technology that enables us to observe and understand our planet from space. Satellite remote sensing is a powerful tool that leverages advanced sensors and sophisticated algorithms to collect valuable data about the Earth’s surface, atmosphere, and oceans.
Understanding and simulating the dynamic processes that govern the Earth’s land surfaces and water systems. Our advanced modeling techniques integrate satellite remote sensing data, field observations, and computational algorithms to provide comprehensive insights into land and water resource management, environmental monitoring, and climate change impacts.
Discover how AI and big data are transforming water management and satellite technologies. Advanced algorithms and extensive datasets enhance real-time monitoring, predictive analytics, and decision-making across water resources and satellite applications.
Explore our extensive datasets and advanced tools essential for water engineering and management research. Access detailed research records, information, land use data, and more to support your studies and drive sustainable solutions.
