## 3 Materials and Methods
### Process-Based or Conceptual Models
A trade-off between crop yield and nitrogen soil leaching was drawn in certain scenarios of an increase in wheat and maize yield for various regions. The integrated assessment model MESSAGE was employed to simulate fertilizing appliances, making use of drivers such as representative concentration pathways 8.5 [85]. The distribution of nitrogen application rate information was derived by using the (LPJ-GUESS) model after being fed with data selected from the Common Agricultural Policy Regionalized Impact (CAPRI) model at a terrain grid level up to 1 km2. Climate and land use change projection assess nitrogen leaching, CO2 mitigation and crop yield [86]. A new approach of monitoring nitrate leaching of land fertilization is obtained by the NIT-DRAIN model [87]. It simulates nitrate conc. at a subsurface drainage network's outflow. It is a drainage discharge simulation model instead of a monitoring/observation model. Water and soluble nitrates are transferred through the soil profile, which is separated into three successive, interconnected, subsurface stratifications, segregated by drain and mid-drain layers. Thus, there is a distinguishable water-nitrate fast transfer throughout the macro-porous upper layer, located above the pipe network. Low and residual nitrate transfers are accomplished through the lower conceptual soil stratifications. The nitrogen load to the ground is divided into two discrete phases. First is the seasonal applied nitrogen quantity, which entails all predicted nitrogen transformations at the cropland scale, and second is the remaining off-seasonal nitrogen pool, which undergoes extended leaching phenomena when the winter season starts. Both prediction data are required. The model also requires updated variable input at the commencement of a new hydrological cycle. It involves seven nitrate leaching and water flow parameters and employs two different transfer functions as long as nitrogen fate lasts. Model calibration is based on Generalized Reduced Gradient (GRG), a non-linear regression algorithm and the hierarchical scheme for validation by making use of the split-sample test [88]. GOSSYM is a mass balance mechanistic two-dimensional (2D) gridded soil model that simulates water, carbon and nitrogen interactions in soil, plant root zone and crop response to climate variables and water irrigation. It incorporates many routines as components, such as daily weather information, soil profile characteristics and parameters, plant growth  
Figure 2: Schematic of best soil management practice by using HYDRUS 1-D soil-soluble water simulation adopted. HYDRUS obtains information from various submodules/processed data based on simulation mathematical modeling with proper feedback over interrelated aspects, i.e., dynamic ongoing phenomena (e.g., nitrification/denitrification/hydraulic conductivity, climatic data, physicochemical interactions), and calibration as self-correction of each individual step. data, etc. Modification is presented by coupling the 2 DSOIL mechanistic 2D finite element soil process model. The latter simulates underground processes, i.e., mineralization, organic matter immobilization, nitrification and denitrification [89]. The modified GOSSYM simulates a variety of potential climate scenarios encountered and facilitates decision and policymakers as regards sustainable strategies. GOSSYM is also to be used coupled with the COMAX expert system developed ad hoc. The inference engine incorporated is very useful for cultivation practices, model result interpretation and irrigation and fertilizing regulation [18; 90]. GOSSYM-COMAX is widely validated by being tested under different environmental conditions and crop practices. The new climate regime over certain regions in Europe incurs even more extreme rainfall incidents with catastrophic ecological results. The abstraction of the humic topsoil tends to be a severe negative outcome.