Drought Risk Analysis and Springs Discharge Forecasting: A Coupled Method for an Optimal Fresh Water Management

Abstract

Since ever the availability of water affects the health of natural ecosystems and consequently several human activities (i.e. drinking water supply, crop production, electricity production and recreation, among the other). Undoubtly, the concept of water availability is closely related to that of the broad term "drought". The latter is a complex phenomenon, for which no universal definition exist. Since numerous variables are attributable to its understanding and as many impacts are traceable to its effects, it is generally accepted that its definition depends on the objective of the study itself. Our study aims to estimate, through a straightforward method, the inter-seasonal variations of the minimum flow discharges of the main karst aquifers of the Latium-Abruzzi carbonate ridge in Central Italy. Considering that, in this paper we will refer to drought, as hydrological drought, that is, as a lack of water in hydrological systems: the occurrence of minimum flow discharge in rivers, below-normal levels in lakes and aquifers. Since the time of the ancient Romans, the karst system of springs of the Apennine hydrostructures (in Central Italy) have been the main source of drinking water supply for the city of Rome and the surrounding areas, satisfying nowadays the needs of over 4 million inhabitants. During the last 100 years, ACEA ATO2, the local water agency (i.e. Corporation) collects the legacy of the ancient Romans, managing about 15,000 km of water distribution network deployed over an area of 5,400 km2. In this context, ACEA ATO2 in order to plan a sustainable water resource exploitation here proposes the application of a coupled model (i.e. precipitation-discharge) aiming to the evaluation of the water resources status in the area. The proposed model is based on an existing and robust method (broadly tested in Italy) that uses as input the Standard Precipitation Index (SPI) and series of monthly spring discharge values for the estimation of the minimum annual spring discharge. For the calculation of SPI, is essential the availability of long time series of undisturbed, good quality precipitation data. We use monthly gridded precipitation data specifically developed for drought monitoring. Although, the proposed methodology can be considered simple, we retain that it represents a robust decision-makers oriented tool for the identification of the trigger factors for an early detection of potential drought events.