Data in Brief (Dec 2024)
Dataset on sub-daily vertical profiles of physicochemical parameters and chlorophyll concentration in El Val reservoir, together with its daily meteorological data, storage state and downstream flow (2018–2022)
Abstract
The dataset addressed in this article contains parameters about El Val reservoir (province of Zaragoza, Spain). It includes physicochemical variables, the water level, the stored water volume, its meteorological conditions and the flow rate of its effluent, the Queiles River, a few metres downstream of the dam. The El Val reservoir stores water from the Val River, but it also receives water from the Queiles River through a pipeline and from several ravines. The dam releases on the Queiles River, which is a tributary of the Ebro River (the second one in Spain in length and discharge rate). A multiparametric probe (aquaDam, Adasa Systems), hanging from a structure located in the dam, every 6 h makes a vertical profile taking the measurements at each metre of depth from the surface to approximately 573 m above sea level (m.a.s.l.), in other words, between 2 and 3 m above the bottom outlet. This probe collects data of water temperature, pH, ORP, conductivity, dissolved oxygen, turbidity and chlorophyll concentration. Meteorological data are collected in the nearest weather station, located in the municipality of Los Fayos which is about 500 m downstream of the dam. These include daily accumulated precipitation, daily maximum and average solar irradiance, daily maximum, minimum and average air temperature and daily average wind speed. The water level and volume of stored water and the flow rate of the Queiles River are collected in the El Val monitoring station and the Queiles River gauge station respectively, and are also provided on a daily basis.These data are useful to feed deterministic, data driven or hybrid hydrological models with different purposes, like the identification of the impact of meteorological conditions on the physicochemical properties of the reservoir as well as the assessment of different management strategies in the reservoir.This is a data article that additionally supports the work published in Ecological Informatics [1] where the use of common and readily available open data is promoted through its use to feed data driven models, in particular to infer the depth of the thermocline in reservoirs that are periodically or permanently thermally stratified. In that article a dataset derived from the one presented in this article is used.
