Hydrology of the Po River: looking for changing patterns in river discharge

Scientists and public administrators are devoting increasing attention to the Po River, in Italy, in view of concerns related to the impact of increasing urbanisation and exploitation of water resources. A better understanding of the hydrological regime of the river is necessary to improve water resources management and flood protection. In particular, the analysis of the effects of hydrological and climatic change is crucial for planning sustainable development and economic growth. An extremely interesting issue is to inspect to what extent river flows can be naturally affected by the occurrence of long periods of water abundance or scarcity, which can be erroneously interpreted as irreversible changes due to human impact. In fact, drought and flood periods alternatively occurred in the recent past in the form of long-term fluctuations. This paper presents advanced graphical and analytical methods to gain a better understanding of the temporal distribution of the Po River discharge. In particular, we present an analysis of river flow variability and persistence properties, to gain a better understanding of natural patterns, and in particular long-term changes, which may affect the future flood risk and availability of water resources.

[1]  L. Oxley,et al.  Estimators for Long Range Dependence: An Empirical Study , 2009, 0901.0762.

[2]  Demetris Koutsoyiannis,et al.  Two-dimensional Hurst–Kolmogorov process and its application to rainfall fields , 2011 .

[3]  Demetris Koutsoyiannis A random walk on water , 2009 .

[4]  Demetris Koutsoyiannis,et al.  HESS Opinions: "Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability" , 2008 .

[5]  M. Taqqu,et al.  Estimating long-range dependence in the presence of periodicity: An empirical study , 1999 .

[6]  D. Zanchettin,et al.  Po River discharges: a preliminary analysis of a 200-year time series , 2008 .

[7]  Salvatore Grimaldi,et al.  Linear Parametric Models Applied to Hydrological Series , 2004 .

[8]  Günter Blöschl,et al.  Climate change impacts—throwing the dice? , 2009 .

[9]  M. Taqqu,et al.  Fractionally differenced ARIMA models applied to hydrologic time series: Identification, estimation, and simulation , 1997 .

[10]  Patrice Abry,et al.  Long-Range Dependence: Theory and Applications , 2002 .

[11]  Demetris Koutsoyiannis,et al.  A blueprint for process‐based modeling of uncertain hydrological systems , 2012 .

[12]  Manfred Mudelsee,et al.  Long memory of rivers from spatial aggregation , 2007 .

[13]  Demetris Koutsoyiannis,et al.  Climate change, the Hurst phenomenon, and hydrological statistics , 2003 .

[14]  Demetris Koutsoyiannis,et al.  HESS Opinions "A random walk on water" , 2009 .

[15]  Suraje Dessai,et al.  Robust adaptation to climate change , 2010 .

[16]  H. E. Hurst,et al.  Long-Term Storage Capacity of Reservoirs , 1951 .

[17]  J. R. Wallis,et al.  Noah, Joseph, and Operational Hydrology , 1968 .

[18]  Demetris Koutsoyiannis,et al.  Statistical analysis of hydroclimatic time series: Uncertainty and insights , 2007 .

[19]  Timothy A. Cohn,et al.  Nature's style: Naturally trendy , 2005 .

[20]  W. Willinger,et al.  ESTIMATORS FOR LONG-RANGE DEPENDENCE: AN EMPIRICAL STUDY , 1995 .