CHOSEN: A synthesis of hydrometeorological data from 30 intensively
monitored watersheds across the US
Abstract
Hydrological analyses and their associated uncertainties are a function
of their supporting observational datasets. Publicly available
large-sample hydrology datasets covering a range of climates, times, and
locations can be used to support inter-watershed comparisons, pattern
identification, and watershed regionalization studies. However, most of
the large-sample datasets are limited to a series of basic measurements
such as precipitation, air temperature, and streamflow. Here we
synthesized data from 30 intensively monitored catchments with soil
moisture, snowmelt, and other hydrometeorological observations at daily
scale across the US. This data synthesis product, CHOSEN
(CONUS/Comprehensive Hydrologic Observatory SEnsor Network), includes
watersheds from the Long-Term Ecological Research (LTER) and Critical
Zone Observatory (CZO) networks, and several other ecological and
hydrological observatories. Catchments span diverse climate gradients
and encompass multiple biomes and ecosystems. To achieve a consistent
and standardized data product, we first implemented data cleaning and
control procedures with strict variable naming conventions and unit
conversions. Following data quality control, data processing methods,
including gap filling by interpolation, linear regression, and climate
catalog-based techniques, were implemented to produce alternative
level-2 products. The data and metadata were written into
self-describing NetCDF files, facilitating ease of access by multiple
computer platforms. All python coding scripts, ranging from processing
to accessing the NetCDF files, are publicly available, along with a
user-friendly tutorial. The standardizations adopted here, and the
availability of the data-processing pipeline, will facilitate future
additions of new observations to this database. We anticipate that this
synthesis will support comparative long-term hydrological studies and
contribute to a growing body of open-source research in watershed and
ecosystem science.