Abstract

In many Italian regions, and particularly in southern Italy, karst aquifers are the main sources of drinking water and play a crucial role in the socio-economic development of the territory. Hence, estimating the groundwater recharge of these aquifers is a fundamental task for the proper management of water resources, while also considering the impacts of climate changes. In the southern Apennines, the assessment of hydrological parameters that is needed for the estimation of groundwater recharge is a challenging issue, especially for the spatial and temporal inhomogeneity of networks of rain and air temperature stations, as well as the variable geomorphological features and land use across mountainous karst areas. In such a framework, the integration of terrestrial and remotely sensed data is a promising approach to limit these uncertainties. In this research, estimations of actual evapotranspiration and groundwater recharge using remotely sensed data gathered by the Moderate Resolution Imaging Spectrometer (MODIS) satellite in the period 2000–2014 are shown for karst aquifers of the southern Apennines. To assess the uncertainties affecting conventional methods based on empirical formulas, the values estimated by the MODIS dataset were compared with those calculated by Coutagne, Turc, and Thornthwaite classical empirical formulas, which were based on the recordings of meteorological stations. The annual rainfall time series of 266 rain gauges and 150 air temperature stations, recorded using meteorological networks managed by public agencies in the period 2000–2014, were considered for reconstructing the regional distributed models of actual evapotranspiration (AET) and groundwater recharge. Considering the MODIS AET, the mean annual groundwater recharge for karst aquifers was estimated to be about 448 mm·year−1. In contrast, using the Turc, Coutagne, and Thornthwaite methods, it was estimated as being 494, 533, and 437 mm·year−1, respectively. The obtained results open a new methodological perspective for the assessment of the groundwater recharge of karst aquifers at the regional and mean annual scales, allowing for limiting uncertainties and taking into account a spatial resolution greater than that of the existing meteorological networks. Among the most relevant results obtained via the comparison of classical approaches used for estimating evapotranspiration is the good matching of the actual evapotranspiration estimated using MODIS data with the potential evapotranspiration estimated using the Thornthwaite formula. This result was considered linked to the availability of soil moisture for the evapotranspiration demand due to the relevant precipitation in the area, the general occurrence of soils covering karst aquifers, and the dense vegetation.

Highlights

  • Groundwater resources of karst aquifers are of fundamental relevance worldwide for human and agricultural water supplies and for sustaining fluvial ecosystems with great geo- and biodiversities [1]

  • Given this recognition of the scientific literature, the results obtained via the modeling of parameters that control groundwater recharge in karst aquifers of southern Apennines revealed useful advances in the management of these types of estimates, which are of fundamental relevance in the framework of an appropriate assessment of these groundwater resources

  • A first important result achieved in reconstructing the regional distributed models of groundwater recharge was the recognition of the orographic barrier effect of the Apennine chain, which strongly controls the spatial distribution of the mean annual precipitation, via the identification of windward and leeward pluviometric zones, where each zone provided a specific correlation of precipitation with altitude

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Summary

Introduction

Groundwater resources of karst aquifers are of fundamental relevance worldwide for human and agricultural water supplies and for sustaining fluvial ecosystems with great geo- and biodiversities [1]. Due to the mainly mountainous features of karst aquifers, the estimation of groundwater recharge is a challenging issue to be tackled due to the lack of high-altitude rain and air temperature gauges, as well as the spatial and temporal discontinuity of recordings [2]. In such a framework, the integration of terrestrial and remotely sensed data is a promising approach to limit these uncertainties and to account for variable land use in karst areas controlling the evapotranspiration demand

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