Authors: Joseph Quansah – Tuskegee University
Title: The Development of An Agricultural Water Risk Assessment and Management System Utilizing National Water Model (NWM) Forecast and Soil Moisture Products
Presentation Type: Poster
Abstract: Agricultural production is highly vulnerable to water-related risks such as drought, flooding, and irregular water supply. Despite advancements in hydrological modeling and soil moisture assessment, a significant gap remains in integrating accessible, data-driven tools for effective agricultural water management. This research aims to develop a comprehensive risk assessment framework that integrates the Agricultural Water Risk Indicator (AWRI) with soil moisture variability products to support informed water management decisions across the Alabama Black Belt Region (ABBR). The AWRI framework utilizes National Water Model (NWM) streamflow forecasts to classify hydrological threats (water scarcity and excess) based on crop sensitivity and farmer adaptive capacity. To strengthen regional soil moisture assessment, the system incorporates Global Ensemble Forecast System (GEFS) soil moisture forecasts, Crop Water Requirement thresholds, remote sensing-derived indices, and in-situ soil moisture sensor validation at five ABBR farms. Validation results established high reliability of NWM streamflow forecasts, with Nash-Sutcliffe Efficiency values ranging from 0.70 to 0.86. GEFS forecasts strongly correlated with in-situ sensor readings, particularly at shallow depths, yielding average Pearson correlation values of 0.85 for 10cm GEFS vs. 15 – 20cm sensor depths. A machine learning model trained for one pilot site achieved an R² of 0.61 at shallow depths. Additionally, soil moisture indices showed improved predictive accuracy with depth, with the best performance observed at 30cm. Using streamflow, the resulting AWRI tool successfully simulated the hydrological threat conditions and risk for different crops within the ABBR. By integrating hydrological forecasts with soil moisture products and agricultural variables, farmers can take proactive actions in advance for irrigation planning and sustainable water management.