The North American Land Data Assimilation System (NLDAS) has a long successful history of producing products that are used for drought monitoring and numerous other water applications. Recent MAPP-funded efforts led by the PI Peters-Lidard, co-PI Mocko, Co-I Kumar (NASA) and co-I Xia (NCEP/EMC) have demonstrated the utility of remotely-sensed soil moisture, snow, and terrestrial water storage estimates on improving estimates of land- surface conditions and drought characterization within NLDAS. Related work by MSFC Institutional-PI Hain and Collaborator Anderson has shown utility of thermal and vegetation remote sensing products in capturing processes related to human activities, including irrigation water sources/sinks and the effect of burned areas. In the proposed work, we will enable the use of daily vegetation products and the assimilation of thermal remote sensing products in NLDAS. We believe that incorporation of these products into NLDAS LSMs will also produce improved data products for drought monitoring and water resource management that better represent evolving conditions under human-caused and natural changes.
The proposed work will include the following three elements: 1) Using retrospective and operational LAI/GVF products to improve the representation of vegetation within NLDAS. This element will demonstrate the impact of these daily products relative to existing monthly climatologies; 2) Using retrospective and operational thermal-based products to better represent impacts of human-managed agricultural water use and other human-managed influences. All simulations will be performed using the NASA-developed Land Information System (LIS) software framework. Elements #1 and #2 will both also include examination of changes to drought severity/extent through the exploitation of these products; and 3) Performing a thorough evaluation of the current and upgraded NLDAS systems using the NASA-developed Land Verification Toolkit (LVT) for comparison to observations and benchmarking. This element will quantify the improvements to simulated soil moisture, streamflow, and other hydrological fields towards a more realistic and representative drought monitoring system.
The proposed work is highly relevant to objective #3 – Advancing operational drought monitoring systems, with a focus on improving snowpack, streamflow, groundwater, and soil moisture representation; integrating new data sources including remotely-sensed products; accounting for human forcing of droughts; and improving vegetation representation. The capability to retrospectively and operationally use and assimilate thermal and vegetation products using the existing capabilities of LIS for NLDAS will represent a significant advance over the current state-of-the-art in land data assimilation and will directly benefit drought monitoring and assessment, including an expected improvement in the representation of human- managed influences (such as irrigation and drainage). These proposed efforts will also contribute to the MAPP Drought Task Force (DTF) by: 1) providing scientific leadership of the Task Force; 2) linking international efforts on advancing global drought monitoring and prediction; 3) facilitating a drought database and visualization capabilities for drought inter-comparison and benchmarking, and 4) leading narrative reports to connect DTF research to relevant drought events to advance drought understanding through project integration.
Climate Risk Area: Water Resources