Analysis of the intra-annual variations in soil moisture throughout the Missouri and Arkansas-White-Red River basins

Abstract

Soil moisture is listed as an Essential Climate Variable by the Global Climate Observing System Program. This is because soil moisture is a key factor in controlling the exchange of water and energy fluxes between the hydrosphere, biosphere, and the atmosphere through its impact on the partitioning of moisture for evapotranspiration and surface-sensible and latent heat fluxes. This characteristic of soil moisture also plays an important role within the hydrologic cycle due to its ability to control the rainfall-runoff response. Therefore, soil moisture is important in determining available water content and can have implications on water resources management for food and energy production. Thus, the evaluation of surface soil moisture at basin-scale is needed to understand spatiotemporal soil moisture trends and their implications on water resources management. Soil moisture To evaluate basin-level soil moisture trends, surface soil moisture estimates from SPoRT-LIS (0-10 cm layer) were used. Managed by NASA’s Short-term Prediction Research and Transition (SPoRT) Center, the SPoRT-LIS is an observation-driven, real-time simulation of the Noah land surface model at a 3-km resolution over the full continental United States. This soil moisture product is at a higher spatial and temporal resolution than is currently available with remotely sensed satellite estimates or in situ measurements of the same product. Seasonal trend analysis was done using TIMESAT to determine soil moisture hydrometrics. Hydrometrics characterize the important seasonal components of soil moisture such as the start and end of the season and the corresponding levels of soil moisture throughout the season. To determine the TIMESAT parameter settings, a sensitivity analysis was done using soil hydrologic groups. Results from the TIMESAT analysis captured intra-annual soil moisture variability and highlighted the impact of soil texture and climate on the availability of soil moisture. Next, the hydrometrics were compared to climate and soil variables to determine the impact that they have on the seasonality trends. This was done using a regression model with a space site effect. The results showed that all three variables, precipitation, temperature, and hydrologic soil groups significantly impacted hydrometrics. Precipitation had the largest impact on the available water content, field capacity, and wilting point of the soil where temperature had the largest impact on the start, middle, and end of season dates. This shows that precipitation drives soil water storage capacity where temperature is the driver of the seasonal timing of soil water storage. However, season length was the only hydrometric that was impacted the most by hydrologic soil groups. Ecoregions were also compared to the hydrometrics. This showed that there are additional drivers that impact hydrometrics which could include land cover, land use, and topography. From this, there is a better understanding of the spatiotemproal soil moisture variations throughout the Great Plains region which can help scientists, land managers, and policy makers to make decisions concerning reservoir management, irrigation applications, and farming practices.