Texas Water Observatory: A Distributed Network for Monitoring Water, Energy, and Carbon Cycles under Variable Climate and Land Use on Gulf Coast Plains

In the Gulf Coastal Plains of Texas, a state-of-the-art distributed network of field observatories, known as the Texas Water Observatory (TWO), is developed to better understand the water, energy, and carbon cycles across the critical zone (encompassing aquifers, soils, plants, and atmosphere) at different spatiotemporal scales. Using more than 300 advanced real-time/near-real-time sensors, this observatory monitors high-frequency water, energy, and carbon storage and fluxes in the Brazos River corridor, which are critical for coupled hydrologic, biogeochemical, and land–atmosphere process understanding in the region. TWO provides a regional resource for better understanding and/or managing agriculture, water resources, ecosystems, biodiversity, disasters, health, energy, and weather/climate. TWO infrastructure spans com-mon land uses in this region, including traditional/aspirational cultivated agriculture, rangelands, native prairie, bottomland hardwood forest, and coastal wetlands. Sites represent landforms from low-relief erosional uplands to depositional lowlands across climatic and geologic gradients of central Texas. We present the overarching vision of TWO and describe site design, instrumentation specifications, data collection, and quality control protocols. We also provide a comparison of water, energy, and carbon budget across sites, including evapotranspiration, carbon fluxes, radiation budget, weather, profile soil moisture and soil temperature, soil hydraulic properties, hydrogeophysical surveys, groundwater levels, and groundwater quality reported at TWO primary sites for 2018–20 (with certain data gaps). In conjunction with various Earth-observing remote sensing and legacy databases, TWO provides a master testbed to evaluate process-driven or data-driven critical zone science, leading to improved natural resource management and decision support at different spatiotemporal scales.