Swiss data quality: augmenting CAMELS-CH with isotopes, water quality, agricultural and atmospheric chemistry data

Thiago V. M. do Nascimento , Marvin Höge, Ursula Schönenberger, Sandra Pool, Rosi Siber, Martina Kauzlaric, Maria Staudinger, Pascal Horton, Marius Floriancic, Florian Storck, Päivi Rinta, Jan Seibert, Fabrizio Fenicia

In the era of large-sample hydrology (LSH) datasets, there is still limited availability of water quality data. Here, we introduce CAMELS-CH-Chem, an extension of CAMELS-CH (Catchment Attributes and Meteorology for Large-sample Studies in Switzerland), incorporating up to 40 water quality parameters for 115 catchments across Switzerland. This new dataset spans the period 1981–2020 and allows for seamless integration with the original CAMELS-CH hydro-meteorological and landscape attribute data. The dataset includes time series of over 30 stream water chemistry constituents, covering both field and laboratory measurements of water temperature, dissolved oxygen, pH, and electrical conductivity at hourly and daily time resolution; along with (bi)monthly measurements of alkalinity (HCO3), ammonium, Ca, Cl, dissolved organic carbon (DOC), dissolved reactive phosphorus (DRP), total organic carbon (TOC), K, Mg, Na, total filtered phosphorus, total hardness, total nitrogen, total phosphorus, NO3, NO2, Si, and SO4. Additionally, the dataset also includes (bi)monthly time series of stream and rainwater isotope data (deuterium and oxygen-18). Finally, we complement the chemical data of each catchment with annual land cover, agricultural data (crop types and livestock density), and atmospheric deposition concentrations for NO3, NH4, NH3, NO2 and total inorganic nitrogen. This is mainly due to the importance of farming activities for nitrogen inputs into the environment in many Swiss lowland catchments. CAMELS-CH-Chem offers a relevant contribution to the field of LSH, providing the opportunity to combine extensive catchment characteristics and streamflow data with a detailed collection of water quality parameters, facilitating advances particularly in the field of hydrological modelling.