Nowadays, the balance between incoming precipitation and stream or spring discharge is a challenging aspect in many scientific disciplines related to water management. In this regard, although advances in the methodologies for water balance calculation concerning each component of the water cycle have been achieved, the Thornthwaite–Mather method remains one of the most used, especially for hydrogeological purposes. In fact, in contrast to physical-based models, which require many input parameters, the Thornthwaite–Mather method is a simple, empirical, data-driven procedure in which the error associated with its use is smaller than that associated with the measurement of input data. The disadvantage of this method is that elaboration times can be exces-sively long if a classical MS Excel file is used for a large amount of data. Although many authors have attempted to automatize the procedure using simple algorithms or graphical user interfaces, some bugs have been detected. For these reasons, we propose a WebApp for monthly water balance calculation, called WaterbalANce. WaterbalANce was written in Python and is driven by a server-less computing approach. Two respective European watersheds are selected and presented to demonstrate the application of this method.

Waterbalance, a webapp for thornthwaite–mather water balance computation: Comparison of applications in two European watersheds

Mammoliti E.;Fronzi D.;Mancini A.;Tazioli A.
2021-01-01

Abstract

Nowadays, the balance between incoming precipitation and stream or spring discharge is a challenging aspect in many scientific disciplines related to water management. In this regard, although advances in the methodologies for water balance calculation concerning each component of the water cycle have been achieved, the Thornthwaite–Mather method remains one of the most used, especially for hydrogeological purposes. In fact, in contrast to physical-based models, which require many input parameters, the Thornthwaite–Mather method is a simple, empirical, data-driven procedure in which the error associated with its use is smaller than that associated with the measurement of input data. The disadvantage of this method is that elaboration times can be exces-sively long if a classical MS Excel file is used for a large amount of data. Although many authors have attempted to automatize the procedure using simple algorithms or graphical user interfaces, some bugs have been detected. For these reasons, we propose a WebApp for monthly water balance calculation, called WaterbalANce. WaterbalANce was written in Python and is driven by a server-less computing approach. Two respective European watersheds are selected and presented to demonstrate the application of this method.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/292985
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