Validation of the GeoWATCH soil moisture model and proposed bias correction method

Abstract

The US Army is required to be a good steward of the land per US Army regulation AR 200-1. Based on this regulation, Army installations need to manage lands, to reduce potential damage and impacts to water quality and habitat that may occur from training. Maneuver training does impact the vegetation and soil and this damage is directly related to soil moisture. Soil moisture is an important factor for understanding the potential for soil surface disturbance due to vehicle impacts and predicting soil resilience to vehicle traffic, however, producing accurate estimates of the spatial and temporal variation of soil moisture has historically been elusive. GeoWATCH, which stands for Geospatial Weather-Affected Terrain Conditions and Hazards (formerly DASSP), simulates soil moisture world-wide, at relatively small spatial and temporal scales. GeoWATCH uses a physics-based downscaling approach that uses weather-scale land surface model estimates of soil moisture and land surface water and energy fluxes, with high resolution geospatial data. GeoWATCH soil moisture outputs coupled with vehicle impact models, are anticipated to be useful for near-real-time estimation of ground disturbance, but will require ground validation. To validate GeoWATCH soil moisture estimates, we utilized Soil Climate Analysis Network (SCAN) gauge network soil moisture data from 127 sites across 34 states. Statistical analysis of the raw GeoWATCH output indicated the model performs statistically better in certain soil textures. Model bias is largest for sandy soils, whereas clayey soils were least biased. As a result, bias correction models were applied to the raw GeoWATCH simulated values using linear regression to predict correction factor (CF) values based on physical site characteristics. The bias correction models significantly improved the performance of the GeoWATCH soil moisture model in terms of average performance statistics and number of statistically cally unbiased sites. This process could easily be incorporated into GeoWATCH, allowing for a capability to rapidly estimate vehicle impacts and determine rehabilitation requirements by installation land managers.