Assessment of water resource change over Central Asian aridzone using remote sensing, global hydrological models and machine learning approach

Project: Research project

Project Details


This project is to seek the solution for better estimating the change of water resources in Central Asian aridzone. The aim of this project is two-folds: (1) to develop a new methodology to assess and simulate regional terrestrial water storage anomalies (TWSA), and (2) to reveal the spatiotemporal pattern of water resources for the evaluation of the impacts by climate change and human activities on the water cycle over Central Asian aridzone. Two scientific questions/issues will be addressed. First, can the change of TWSA, hence the components of the regional water resource, be monitored more efficiently and practically by integrating remote sensing technology and global hydrological models (GHMs)? Second, what is the eco-hydrological response of the regional water cycle, which is revealed by the application of above integrated approach, to climate change and human activity in Central Asian aridzone? A new and innovative approach is proposed to derive TWSA by the assimilation and integration of Gravity Recovery and Climate Experiment (GRACE) data and the global hydrological models (GHMs). The proposed TWSA estimation methodology overcomes the drawbacks of GHMs due to their uncertainties caused by the limited availability of in situ observations as the model inputs, and the restricted applicability due to structural limits of the model. On the other hand, the proposed approach also seek the solution to improve the TWSA assessment by the GRACE alone, which the short time series and coarse spatial resolution are widely identified as major limits in application.

Three research outcomes are expected, including (1) a TWSA estimation method by the assimilation and integration of GRACE and GHM, which, with the proper calibration and validation, can be applied to water resource applications in an arid environment at a regional scale; (2) an improved TWSA dataset covering Central Asian aridzone with a better spatial resolution and longer time series, and derived hydrological components of water cycle such as soil moisture, groundwater, snow water equivalent and ice; and (3) a better understanding about the relationships between the regional water resources and climate change and human activity in Central Asian aridzone. Scientific evidences and advices can therefore be provided to the local policy maker in sustainable water resource management, which is a core element to achieve for solving the international water resource disputes between Central Asian states.
Effective start/end date1/01/2131/12/23


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