Articles | Volume 14, issue 8
https://doi.org/10.5194/essd-14-3715-2022
https://doi.org/10.5194/essd-14-3715-2022
Data description paper
 | 
17 Aug 2022
Data description paper |  | 17 Aug 2022

QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany

Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff

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Cited articles

Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. 
Addor, N., Do, H. X., Alvarez-Garreton, C., Coxon, G., Fowler, K., and Mendoza, P. A.: Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrolog. Sci. J., 65, 712–725, https://doi.org/10.1080/02626667.2019.1683182, 2020. 
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018. 
Bach, M. and Frede, H.-G.: Agricultural nitrogen, phosphorus and potassium balances in Germany – Methodology and trends 1970 to 1995, Z. Pflanz. Bodenkunde, 161, 385–393, https://doi.org/10.1002/jpln.1998.3581610406, 1998. 
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Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
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