## 3 Materials and Methods
### Process-Based or Conceptual Models
Furthermore, it estimates greenhouse gas (GHG) emissions from terrestrial ecosystems and carbon sequestration [39; 40]. A basic component of the model simulates crop growth and decomposition by processing data of soil conditions, i.e., moisture, redox potential, temperature, etc., and another component covers carbon and nitrogen transformation through aerobic nitrification, anoxic denitrification, and even anaerobic fermentation by means of biotic micro-population in soil. Furthermore, biogeochemical interactions are taken into consideration, and nitrogen is finally released into the atmosphere or even beaches in deeper soil sequestration after hydrological processing by means of nitrogen adsorption phenomena, plants' uptake in the rhizosphere, microbial assimilation, nitrification/denitrification, etc. [41; 42]. [PERSON] et al. (2021) [43] applied the DNDC biogeochemical model to quantify denitrification-decomposition bioprocessing as a mechanism and a part of overall nitrogen management of greenhouse vegetable fields in China. The model is developed for extrapolating prediction in extended time and carbon/nitrogen soil dynamics. As with the other process-based models, it requires time series data for a long period, usually over a decade, and long, intense calibration testing. However, cases of underestimation of measured N-NO\({}_{3}\) concentrations in soil leachate in certain parts of the year were recorded [43]. The DayCent model [44] simulated the nitrogen cycle in soils for various ecosystems, (e.g., cropland and forest). It simulates N\({}_{2}\)O emissions and mineral nitrogen leaching under different types of landscapes, exploiting a variety of meteorological data, soil properties, irrigation practices, and crop particularities. More specifically, nitrogen leaching presentsremarkable spatial and temporal variations, known as hot spots and hot moments (HSHM). Nitrogen leaching and loss within HSHM could be easily tracked and managed by means of applying the proper model to achieve suitable fertilizing management, local climate factors, soil profile properties and the local topography [45]. TETIS [46; 47] is a process-based, hydrological, conceptual, distributed model that simulates aquifers' recharge and soil nitrogen leaching, enabling the study of the long-term groundwater quantified response to nitrogen leaching. It incorporates precipitation data from meteorological time series, different irrigation and fertilization practices and potential evapotranspiration. The latter is obtained by means of the Hargreaves-Samani equation [48]. The nitrogen cycle is dependent on fertilization and atmospheric deposition. Corine land uses, maps, and 'Pedotransfer' functions were involved [47; 49]. They were employed in combination with functions exploiting raw soil data upgraded into useful information tools via predictive functions of certain soil properties. Fifty years of meteorological data were combined with irrigation and fertilizing practices as well as the digital elevation model from the geographical survey of the site of interest. All selected data were the input of the TETIS model. Finally, the quantification and sensitivity of nitrogen recharge and nitrogen leaching corresponding to a variety of weather conditions were estimated on certain temporal bases in the Valencian region (location in Spain) [50]. STICS is a one-dimensional, daily-step, soil-crop dynamic model [51; 52]. It simulates the quantities of daily drained water, (N) leaching in soil-water phases, (N) plant uptake and fixation, (N) fluxes, and dynamic interrelation between hybrid tested crops and soil type under various climatic parameters, e.g., air temperature, rainfall density, solar radiation, 'Penman' evapotranspiration, C:N ratio, pH, calcium carbonate equivalent action, etc., which finally affects crops' biomass production [53]. Pedoclimatic characteristics (i.e., soil water content, nitrogen abundance in soil, bulk density, soil infiltration rate) and soil exploitation practices are used as initial inputs for the running of the simulation.