Title: Land Agriculture Information System (LAIS): A Coupled Hydrology and Agriculture Modeling Platform for Estimating Hydrological and Agricultural Growth Variables
Presenting Author: Rajat Bindlish
Organization: NASA Goddard Space Flight Center
Co-Author(s): Pang-Wei Liu, Sujay V Kumar, Jessica Erlingis, Shahryar Khalique Ahmad, Alexander C Ruane, Meijian Yang, Luke Monhollon, Zhengwei Yang, Gary Feng and Yanbo Huang

Abstract:
Agricultural models require inputs of precipitation, temperature, and moisture conditions along with historical data as key weather parameters to develop estimates of field operations schedules, from seeding to harvesting, with fertilizer and herbicide treatments in-between. Unexpected extreme weather and climate change has a major socioeconomic impact on agriculture and food security. Crop growth, yield, and agricultural production information is critical for commodity market, food security, economic stability, and government policy formulation. Although current crop growth models provide rigorous modules to simulate crop development, they lack rigorous water balance and hydrologic processes. On the other hand, hydrology models lack more in-depth simulation of crop development stages and farm management. Coupling hydrology and crop growth models with interdependent constraints will leverage their complementary strengths to improve the estimates of hydro-agricultural variables. Land Information System (LIS) was coupled with Decision Support System for Agrotechnology Transfer (DSSAT) model to estimate crop growth stages, biomass, and crop yield for different conditions. The coupled model framework is capable of directly utilizing the LIS’s built-in modules to assimilate remotely sensed data such as soil moisture and LAI to update and improve the model simulations. In the presentation, we will demonstrate the capability of the developed digital twin framework and explore the impact of weather (precipitation, soil moisture, temperature) and climate on crop yield. The framework will provide an unprecedented useful tool to support the best management practices for farming systems and productivity outlooks for agricultural decision makers.