Understanding temporal stability: a long-term analysis of USDA ARS watersheds

ABSTRACT

The U.S. Department of Agriculture’s Agricultural Research Service (USDA-ARS) maintains seven in situ soil moisture networks throughout the continental United States, some since 2002. These networks are crucial for understanding the spatial and temporal extent of droughts in their historical context, parameterization of hydrologic models, and local agricultural decision support. However, the estimates from these networks are dependent upon their ability to provide reliable soil moisture information at a large scale. It is also not known how many network stations are sufficient to monitor watershed scale dynamics. Therefore, the objectives of this research were to: (1) determine how temporally stable these networks are, including the relationships between various sensors on a year-to-year and seasonal basis, and (2) attempt to determine how many sensors are required, within a network, to approximate the full network average. Using data from seven in situ, it is concluded that approximately 12 soil moisture sensors are sufficient in most environments, presuming their locations are distributed to capture the hydrologic heterogeneity of the watershed. It is possible to install a temporary network containing a suitable number of sensors for an appropriate length of time, glean stable relationships between locations, and retain these insights moving forward with fewer sensor resources.

KEYWORDS:

• Soil moisture
• temporal stability
• in situ networks

Acknowledgement

This research was a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture and available through the National Agricultural Library or STEWARDS database. USDA is an equal opportunity employer and provider.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

Notes: Numbers in parentheses refer to the number of sensors available for that year of study. All correlations are significant with a p-value of less than 0.01.

Note: Number of available sensors used in the study for each watershed in parentheses.