Dissolved organic matter (DOM) has been shown to inhibit the oxidation of aromatic amines initiated by excited triplet states, an effect that was attributed to the reduction of oxidation intermediates back to their parent compounds. The present study focuses on the quantification of an analogous inhibitory effect of DOM on aqueous oxidations induced by the sulfate radical (SO4 · –). Second-order rate constants for the SO4 · –-induced transformation of selected anilines and sulfonamide antibiotics were determined by competition kinetics in the presence and absence of DOM from three different isolates at pH 8. In the presence of 1 mgC L–1 of DOM, a significant reduction in the rate constant was observed for most of the compounds compared to DOM-free solutions, but for two electron-rich anilines, increases in the rate constant were measured. For 4-cyanoaniline and sulfamethoxazole, the DOM concentration dependence of the rate constant consisted of a sharp decrease up to ∼1.0 mgC L–1 of DOM followed by a region of slight changes or even increases for higher DOM concentrations (up to 5 mgC L–1). This behavior was attributed to the occurrence of the aforementioned inhibitory effect and a counteracting accelerated transformation of the contaminants due to reactions with secondary radical oxidants resulting from DOM oxidation by SO4 · –. Both effects of inhibition and secondary oxidants should be considered when assessing the abatement of aromatic amines in SO4 · –-based advanced oxidation processes.
Abstract. We present CAMELS-CH (Catchment Attributes and MEteorology for large-sample Studies - Switzerland), a large-sample hydro-meteorological data set for hydrological Switzerland in Central Europe. This domain covers 331 basins within Switzerland and neighboring countries. About one third of the catchments are located in Austria, France, Germany and Italy. As an Alpine country, Switzerland covers a vast diversity of landscapes, including mountainous environments, karstic regions, and several strongly cultivated regions, along with a wide range of hydrological regimes, i.e. catchments that are glacier-, snow- or rain-dominated. Similar to existing data sets, CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes. CAMELS-CH (Höge et al., 2023, available at: https://doi.org/10.5281/zenodo.7957061) encompasses 40 years of data between 1st January 1981 and 31st December 2020, including daily time series of stream flow and water levels, and of meteorological data such as precipitation and air temperature. It also includes daily snow water equivalent data for each catchment starting from 2nd September 1998. Additionally, we provide annual time series of land cover change and glacier evolution per catchment. The static catchment attributes cover location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers. This Swiss data set complements comparable publicly accessible data sets, providing data from the "water tower of Europe".
<p>Over recent years, numerous open catchment datasets have been published.&#160;In 2017, the first CAMELS (catchment attributes and meteorology for large-sample studies) dataset was released for the continental US by Addor et al. (2017). It comprises data for several hundreds of catchments including dynamic time series of daily resolution over several decades for discharge, precipitation and temperature - originally compiled by Newman et al. (2015) - as well as static basin attributes such as indices on topography, soil, geology and climate. Subsequently, similar datasets for several other countries were made or will be made publicly available. Some of these also contain additional data such as attributes on glaciers or human influence like, e.g., the CAMELS datasets for Chile (Alvarez-Garreton et al., 2018) and Great Britain (Coxon et al., 2020). Such datasets build an accessible and unified basis for reproducible and complementary research. &#160;They led to a high stimulation of hydrological research with methodologies that could not be applied before, like the joint evaluation of a large number of catchments.</p><p>We present CAMELS-CH, a new dataset for about 200 basins in Switzerland that will be released in 2022. In this collaborative project, several academic institutions and agencies work together to publish a hydro-meteorological dataset that covers both dynamic and static catchment data, and that accounts for the wide range of hydrological regimes in Switzerland, e.g., alpine environment, hydropower usage, densely populated and cultivated regions, etc. We summarize the current state of the project, remaining challenges, in particular regarding translating base data into the CAMELS format, and the final steps toward dataset publication.</p><p>&#160;</p><p><strong>References</strong></p><p>Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences, 21, 5293-5313, 2017</p><p>Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Cortes, G., Garreaud, R., McPhee, J., Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies-Chile dataset, Hydrology and Earth System Sciences, 22, 5817&#8211;5846, 2018</p><p>Coxon, G., Addor, N., Bloomfield, J., Freer, J., Fry, M., Hannaford, J., Howden, N., Lane, R., Lewis, M., Robinson, E., Wagener, T.,and Woods, R.: CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth System Science Data 12, 2459&#8211;2483, 2020</p><p>Newman, A., Clark, M., Sampson, K., Wood, A., Hay, L., Bock, A., Viger, R., Blodgett, D., Brekke, L., Arnold, J.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences, 19, 209-223, 2015</p><p>&#160;</p>
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