## 3 Materials and Methods
### Process-Based or Conceptual Models
Therefore, it is of crucial importance to use integrated biogeochemical-ecosystem models and estimate intra-/inter-annual gross primary productivity (GPP) variations, e.g., Biome-BGC [91; 92; 93], to monitor ecosystem response against extreme events. Interactions of ten hydrological and ecological processes were taken into consideration, including runoff, canopy evaporation, soil-water storage, soil evaporation/respiration, transpiration, net primary productivity (NPP), net ecosystem exchange, nitrogen mineralization and leaching. Once more, nitrogen propagation incurs nitrate pollution and is considered to be of high-priority concern when the Good Environmental Status (GES) or even the Good Ecological Status is to be assessed. The model focuses on carbon (C) and nitrogen (N) fluxes on a preset time scale (i.e., daily, monthly, annual). Model parameterization is achieved by making use of site characteristics data (e.g., soil texture/relief/depth, terrain elevation), meteorological data (e.g., precipitation, humidity, temperature, etc. ), and eco-parameters (e.g. canopy growth and expansion, photosynthetic rate, carbon to nitrogen ratio of leafage, lignin fraction of the dead wood) [94]. As regards the part of the daily soil-water balance, the one-dimensional soil-plant-atmosphere DAISY, Danish model simulation (version 4.01) [95] was employed to cover the water and nitrogen balance in agro-ecosystems for crop cultivation [96]. The model comprises three main modules, i.e., a biocimate, vegetation, and a soil component. Soil-water retention and transport were simulated by employing the DAISY model and using the Makink equation, while evapotranspiration was determined from the daily global radiation and mean temperature [97]. Variables for nitrate leaching, i.e., nitrate percolation, entail crop classification into groups according to (N) uptake performance, residual (N), contribution to leachate and (N) mineralization, i.e., transformation into inorganic form (NH\({}_{4}\)+) [98]. Nitrate leaching predictions and nitrogen conc. in monitoring sites in Denmark, including various parameters, i.e., soil type, climatic data, crop consequence, nitrogen fertilizer appliance rate, soil winter capping, etc., were conducted, making use of multivariable experiments. A linear regression was applied to identify and assess the influence of gravity of a leaching year (hydrological year). A certain number of sites were selected and the DAISY model (ver. 4.01) [95] (Figure 3) was implemented to simulate water percolation and balance at the depth of the rhizosphere. Each DAISY module processes individual fields based on well-tested and widely accepted scientific experience. All modules require a heap of time series datasets, which are not always easy to obtain, and verification. Soil stratification forms individual modules with domain equations, e.g., the Mualem-van Genuchten eq., which describes water retention curves and soil hydraulic conductivity, a critical parameter for solid prediction or soil water flux by making use of Richards' equations. Module results are interchangeable between different processing fields for the optimized final outcome. The DAISY model is employed for quantitative description of water flow into an unsaturated soil zone and makes use of certain soil quality characteristics, i.e., water retention, unsaturated hydraulic conductivity, which were fitted earlier to the Mualem-van Genuchten equations [80; 99] and RETC optimization computer programming code [100]. In the specific case, the DAISY model simulates the water balance regarding different soil-crop productions. The model incorporates [PERSON]'s equation [78] to calculate soil water flux. Different soil sites and differentiated climatic data help deduce new estimatedvalues of nitrate leaching; therefore, proper cropping strategies should be followed for soil nutrient balancing [101]. 'MIKE SHE' is a complex model package which describes distributed and physically based water/solute flow in catchment areas.