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Understanding the effects of agricultural land use transformations on weather dynamics in southern high plains

Team Members:

Person Name Person role on project Affiliation
Guofeng Cao Principal Investigator University of Colorado Boulder, Boulder , USA
Xiao-Peng Song Co-Investigator University of Maryland, College Park, , United States
Ronnie Abolafia-Rosenzweig Co-Investigator NSF NCAR, Boulder , USA
Abstract

The Southern High Plains (SHP), a critical region for agriculture and energy production in the U.S., is grappling with several climate-related challenges that pose significant risks to its sustainability and viability. These challenges are multifaceted, most prominently including the depletion of the primary agricultural water source (Ogallala aquifer), a warm and dry climate trend with an increasing frequency of extreme weather events (as exemplified by the recent Smokehouse Creek Fire in the Texas Panhandle), and the transition towards renewable energy. Various adaption strategies have been investigated to cope with these challenges while sustaining the productivity, including transitioning to less water-intensive crops and farming practices, and integrating wind energy infrastructure. All of the strategies require significant shifts in land use patterns that can further propagate in atmospheric dynamics. The discussions on these adaptation strategies have primarily centered on economic viability, often overlooking the potential effects on weather dynamics that in turn can have profound impact on sustainability. Understanding the nexus between agricultural land use, weather dynamics and economic productivity in the face of climate change and water scarcity is crucial for developing sustainable adaption strategies in the SHP region.

In this project, we aim to address the complex nexus in the SHP region through an Earth System Digital Twin (ESDT) approach by incorporating continuous agricultural land use and land cover (LULC) dynamics captured by time series of satellite imagery, geospatial artificial intelligence (GeoAI) and advanced land surface and weather models. Our goals are threefold: (1) to delineate the pathways through which agricultural LULC influences atmospheric dynamics and the subsequent outcome for extreme weather risks and agricultural and wind energy productivity; (2) to enhance the accuracy of regional weather forecasting through the integration of novel and high-resolution agricultural LULC datasets and refined parameterization for common and emerging crops in the area; and (3) to enable ESDT-based, uncertainty-aware, comprehensive assessments under various hypothetical land use scenarios, thereby contributing to the development of sustainable land use management and adaptation strategies.

To achieve the research goals, we first aim to create an agricultural land digital replica of the SHP region through an analysis integrating Landsat, MODIS, Sentinel and high-resolution satellite products, field observations and advanced GeoAI algorithms. The digital replica will characterize the long-term agricultural LULC dynamics, which will include annual 2000-2024 crop type maps, crop phenology maps, and crop-specific green vegetation cover within each growing season, altogether characterizing the life cycles of crops, from planting to harvesting. Second, we will inform the widely used Noah-MP land surface model with timely LULC dynamics to account for associated land-atmosphere interactions in high-resolution weather simulations (1-4 km) from the Weather and Researching and Forecasting modeling system (WRF), which relies on Noah-MP for the land component. WRF simulations will be calibrated using historical records and in-situ measurements. Third, we will integrate the land digital replica and the improved weather models with related datasets into an ESDT prototype. The prototype will enable a comprehensive diagnosis of the causal effects of agricultural LULC changes on weather dynamics. We will develop an uncertainty-aware GeoAI framework to integrate heterogeneous datasets to assess the implications on regional sustainability, with a focus on extreme weather risks, crop production and wind energy potential. With an interactive interface, the prototype will allow stakeholders to engage in an uncertainty-aware analysis of agricultural LULC scenarios to support sustainable land management and planning.
 

Project Research Area