10.5061/DRYAD.3FFBG79JF
Schoener, Gerhard
0000-0002-1183-0419
Southern Sandoval County Arroyo Flood Control Authority
Stone, Mark C.
University of New Mexico
Data from: Monitoring soil moisture at the catchment scale – A novel
approach combining antecedent precipitation index and radar-derived
rainfall data
Dryad
dataset
2021
University of New Mexico
https://ror.org/05fs6jp91
2021-09-08T00:00:00Z
2021-09-08T00:00:00Z
en
https://doi.org/10.1016/j.jhydrol.2020.125155
https://doi.org/10.5281/zenodo.5495004
23102 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Knowledge about soil moisture is important for event-based rainfall-runoff
models but monitoring conditions at the catchment scale is not a trivial
task. Soil moisture is highly variable in space and time, particularly in
dry climates with seasonal and spatially heterogeneous rainfall. Point
measurements are difficult to upscale, and remotely sensed (RS) data often
lack in spatial or temporal resolution for local or regional studies.
Longer latency periods – the time required before data becomes available –
of some RS data make them less applicable to time-sensitive analyses such
as flash flood forecasting. This study evaluated a novel approach for
estimating catchment-scale volumetric soil moisture using an antecedent
precipitation index (API) -based model. The model was trained and tested
using in-situ soil moisture measurements collected during a 3-month field
sampling campaign in a 142 km2 study area in central New Mexico. The
calibrated model was applied at the catchment scale to produce soil
moisture grids from radar-derived rainfall estimates. Model performance,
resolution and latency were compared to satellite-based soil moisture
estimates. Benefits of the proposed new method include high spatial
resolution (1 × 1 km or less depending on the precipitation data source)
and high prediction accuracy (root mean square errors 0.014–0.018 m3/m3).
Given the short latency period for radar-derived rainfall data, the method
has potential for use in operational flood risk assessment and
forecasting.
This dataset contains soil moisture measurements collected at 25 locations
in central New Mexico on 15 separate sampling days between June 25 and
October 7, 2019. Volumetric moisture content (m3/m3) was measured for
depths of 0-7.5 cm and 7.5-15 cm using a portable time-domain
reflectometer calibrated to in-situ soil conditions.