The impacts of droughts and floods can be particularly severe if they occur in areas with high human presence. To reduce the negative impacts of hydrologic extremes in a world where rivers are hardly in natural conditions, we need estimates of their magnitude and frequency under regulated conditions. These estimates for regulated conditions are expected to differ from those under natural conditions because flow regulations such as reservoir operation, water abstractions, and flow deviations have been shown to both aggravate and alleviate drought and flood severity [Verbunt et al., 2005; He et al., 2017; Tijdeman et al., 2018; van Oel et al., 2018]. This master thesis aims to enhance our understanding of the statistical behavior of hydrologic extremes in the Piedmont region under both natural and regulated conditions. More specifically, it aims to (1) identify pairs of natural and regulated catchments up- and downstream of reservoirs and regulated lakes, respectively and (2) quantify the impact of reservoir operation or lake regulation on drought and flood characteristics.

Streamflow data for natural and regulated gauged in Piedmont will be provided by Arpa (Agenzia Regionale per la Protezione Ambientale) Piedmont for the period 1990-2019 (https://www.arpa.piemonte.it/rischinaturali/tematismi/acqua/risorsa-idrica/H-Q-giornaliere.html). The student will identify several pairs of natural upstream and regulated downstream catchments [Rangecroft et al., 2019] using geo data searched and organized through Piedmont’s geoportal (http://www.geoportale.piemonte.it/geocatalogorp/; diga, lago, …, data still needs to be ordered). To quantify the impact of flow regulation on hydrologic extremes, they will compare flood and drought characteristics of natural and regulated catchments identified in the observed streamflow time series using peak-over-threshold and threshold-level approaches, respectively [Lang et al., 1999; Heudorfer and Stahl, 2017]. Characteristics of interest include drought duration, deficit, and intensity [Brunner et al., 2019], flood duration, peak, and volume [Brunner et al., 2016], the relationships between different variable pairs, temporal clustering behavior of extreme events [Merz et al., 2016], and drought-flood transitions [He and Sheffield, 2020]. The results of this analysis will quantify to which degree drought and flood characteristics in regulated catchments in Piedmont differ from the ones in natural catchments.

Dr. Manuela Brunner (University of Freiburg, manuela.brunner@hydrology.uni-freiburg.de)

Manuela Brunner manuela.brunner@hydrology.uni-freiburg.de

English

• Brunner, M. I., J. Seibert, and A.-C. Favre (2016), Bivariate return periods and their importance for flood peak and volume estimation, Wire’s Water, 3, 819–833, doi:10.1002/wat2.1173.
• Brunner, M. I., K. Liechti, and M. Zappa (2019), Extremeness of recent drought events in Switzerland: Dependence on variable and return period choice, Nat. Hazards Earth Syst. Sci., 19(10), 2311–2323, doi:10.5194/nhess-19-2311-2019.
• He, X., and J. Sheffield (2020), Lagged compound occurrence of droughts and pluvials globally over the past seven decades, Geophys. Res. Lett., 1–32, doi:10.1029/2020gl087924.
• He, X., Y. Wada, N. Wanders, and J. Sheffield (2017), Intensification of hydrological drought in California by human water management, Geophys. Res. Lett., 44(4), 1777–1785, doi:10.1002/2016GL071665.
• Heudorfer, B., and K. Stahl (2017), Comparison of different threshold level methods for drought propagation analysis in Germany, Hydrol. Res., 48(5), 1311–1326, doi:10.2166/nh.2016.258.
• Lang, M., T. B. M. J. Ouarda, and B. Bobée (1999), Towards operational guidelines for over-threshold modeling, J. Hydrol., 225, 103–117.
• Merz, B., V. D. Nguyen, and S. Vorogushyn (2016), Temporal clustering of floods in Germany: Do flood-rich and flood-poor periods exist?, J. Hydrol., 541, 824–838, doi:10.1016/j.jhydrol.2016.07.041.
• van Oel, P. R., E. S. P. R. Martins, A. C. Costa, N. Wanders, and H. A. J. van Lanen (2018), Diagnosing drought using the downstreamness concept: the effect of reservoir networks on drought evolution, Hydrol. Sci. J., 63(7), 979–990, doi:10.1080/02626667.2018.1470632.
• Rangecroft, S., A. F. Van Loon, H. Maureira, K. Verbist, and D. M. Hannah (2019), An observation-based method to quantify the human influence on hydrological drought: upstream-downstream comparison, Hydrol. Sci. J., 64(3), 276–287, doi:10.1080/02626667.2019.1581365.
• Tijdeman, E., J. Hannaford, and K. Stahl (2018), Human influences on streamflow drought characteristics in England and Wales, Hydrol. Earth Syst. Sci., 22(2), 1051–1064, doi:10.5194/hess-22-1051-2018.
• Verbunt, M., M. Groot Zwaaftink, and J. Gurtz (2005), The hydrologic impact of land cover changes and hydropower stations in the Alpine Rhine basin, Ecol. Modell., 187(1 SPEC. ISS.), 71–84, doi:10.1016/j.ecolmodel.2005.01.027.