Assessment of Soil Moisture Anomalies in Irrigated and Nonirrigated Soils Combining SMAP Anomaly Data and NASS Crop Soil Moisture Conditions

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Abstract The U.S. Department of Agriculture National Agricultural Statistics Service (NASS) collects crop soil (topsoil and subsoil) moisture conditions in U.S. agricultural regions. NASS dynamically assesses crop soil moisture conditions in four categories—Very Short, Short, Adequate, and Surplus—and publishes weekly statistics for states. Previous studies mapped NASS crop soil moisture (SM) condition categories to NASA’s SM Active Passive (SMAP) level-4 (L4) weekly surface and root-zone soil moisture by using NASS survey-reported category percentages to determine corresponding threshold values from the cumulative distributions of SMAP soil moisture. However, a notable challenge arose in croplands with coarse-textured soils, where frequent irrigation is necessary due to rapid drainage. Yet, the SMAP product often inaccurately indicates dry conditions in these soils, failing to capture the effects of irrigation due to coarse resolution and mixed pixels. To address this issue, this study utilizes soil moisture anomalies to better reflect crop soil moisture conditions in irrigated lands. Soil moisture anomalies were categorized into the same four classes, with classification thresholds determined by mapping cumulative distributions of SMAP surface and root-zone anomalies to NASS categories. We compared SMAP SM-based estimates with SMAP anomaly-based estimates for the soil moisture conditions in two case study regions: the Columbia basin in Washington (which includes irrigated and nonirrigated croplands) and Iowa (primarily nonirrigated), followed by an uncertainty analysis of the anomaly-based results. The key finding is that anomaly-based mapping yields a different and more distinct representation of soil moisture conditions for irrigated versus nonirrigated croplands in Washington’s Columbia basin during a drought year. Significance Statement This study advances national-scale soil moisture monitoring by using soil moisture anomalies from NASA’s Soil Moisture Active Passive (SMAP) data to improve the mapping of crop soil moisture conditions reported by USDA National Agricultural Statistics Service (NASS). Previous soil moisture condition mapping often underestimates wetness in irrigated coarse-textured soils due to mixed-pixel and resolution limitations. The anomaly-based mapping aligns more closely with survey feedback and provides a more realistic depiction of soil moisture adequacy for irrigated croplands than soil moisture (SM)-based mapping, particularly in Washington’s Columbia basin. Built entirely on publicly available datasets, the framework is transparent, reproducible, and cost effective. Designed for operational integration with USDA’s Crop Condition and Soil Moisture Analytics (Crop-CASMA) platform, it supports near-real-time agricultural drought monitoring and improved irrigation management.

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