# The Importance of Incorporating Denitrification in the Assessment of Groundwater Vulnerability
## 1 Introduction
### Denitrification in Groundwater Vulnerability Assessment  
To properly protect the groundwater resources, an effective prevention from contamination is essential [18]. In this contest of prevention, vulnerability maps play an important role thanks to their ability to show complex hydrogeological systems in an easily understandable way [19]. Groundwater vulnerability can be classified in two categories [20]: (i) intrinsic vulnerability, which depends only on the geological and hydrogeological features of the aquifer system, and (ii) specific vulnerability, that refers to the vulnerability of groundwater to specific contaminants and involves in the evaluation the physical-chemical properties of each contaminant. In the last 50 years, different methods for groundwater vulnerability and risk mapping for NO\({}_{3}\)\({}^{-}\) pollution have been proposed and tested in many regions of the world. They are distinguished in two main categories: (i) deterministic models, that include the simulation of the physical, biological and chemical NO\({}_{3}\)\({}^{-}\) leaching processes occurring in the vadose and saturated zones, and (ii) overlay and index techniques. The first require a huge amount of data but are also quite efficient. [PERSON] et al. [21] recently showed how reactive modeling might represent a valuable tool to quantify the complex biogeochemical reactions which can take place in underground environments. [PERSON] et al. [22] and [PERSON] et al. [17] enhanced Soil and Water Assessment Toll (SWAT) model to properly simulate denitrification in alluvial wetlands and in riparian zones, respectively. Despite the high reliability of deterministic models, the overlay indices are the most used worldwide, due to their ease of use and data accessibility. DRASTIC [23], SINTACS [24] and AVI [25] are three of the most used and modified overlay indices. They usually asses the aquifer vulnerability through the analysis of several factors like: depth to the water table, aquifer recharge, aquifer media, soil media, topography, impact of the vadose zone, hydraulic conductivity and hydraulic resistance. However, these methodologies suffer for different drawbacks [26]: (i) they can be extremely subjective especially in the rating scale and weighting selection, and (ii) they do not analyze physical processes occurring within the aquifers, such as denitrification and NO\({}_{3}\)\({}^{-}\) dilution/dispersion. To overcome these drawbacks and to include processes like nitrification and denitrification in the vulnerability evaluation, some modified and new methodologies have been proposed. Following the EU Nitrates Directive [27], [PERSON] and [PERSON] [28] created the Improved flux Prototypes for NO\({}_{2}\) emission from Agriculture (IPNOA index). This methodology, unlike the other rating methods, provides the evaluation of different factors that can be directly connected to denitrification processes, such as climate, irrigation, type of agricultural practices, together with the amount and kind of fertilizer used. IPNOA has been applied and modified to assess the \"nitrate vulnerable zones\" on the European territory [29; 30; 31]. However, this method requires very specific information, and this could shrink its application only in well-characterized areas. [PERSON] et al. [32] proposed a simplified version of IPNOA called Protection from Natural and Anthropogenic sources (PNA), maintaining some parameters like soil organic carbon and irrigation in the evaluation but making it more broadly applicable. Within the category of the rating methods, [PERSON] and [PERSON] [6] proposed a DRASTIC modification named DRASTIC-PA where superficial run-off and N losses through soils were introduced in the vulnerability evaluation. [PERSON] et al. [33] defined and calculated the annual losses of water and N from percolation and superficial run-off via the LOS indices. These indices account for nitrification/denitrification processes in the vulnerability evaluation, normally neglected by the overly indices. In the same way [PERSON] et al.