## 3 Groundwater and Surface Water Data Sources and Availability  
The modeling process in the groundwater-surface water (GW-SW) system is essential in understanding the interactions between these two water sources and how they impact each other. This process requires adjusting the hyperparameters of the system to ensure the simulations produced are reliable and accurate. However, data availability can sometimes pose a challenge in modeling, particularly in small areas or basins where data may be limited. Despite this, the use of GW and SW models has increased significantly in recent years due to the availability of a growing number of regional and global datasets. Global model products and open data, which contain a large amount of environmental information, have become easily accessible and, combined with the advancement of remote sensing data, provide a strong foundation for developing some water models. One of the advantages of these models is the ability to obtain critical structural aspects such as watershed boundaries, surface flow direction, and slope. This information can be taken from managing products of a digital elevation model (DEM) with the help of GIS spatial analysis. A MERIT DEM is a popular product in this field, it is a worldwide map with a resolution of approximately 90 m. The development took place using current spatial DEMs. Numerous error components, such as stripe noise, speckle noise, tree height bias, and absolute bias, have been removed to provide an unbiased representation of terrain elevation [35]. In conclusion, the modelling process in the GW-SW system is essential for understanding the interactions between these two water sources. Although data availability can sometimes pose a challenge, the use of GW and SW prototypes has dramatically increased in recent years due to the availability of open data and global model products, which provide a solid foundation for building water models. The processing of DEM products allows for the easy extraction of critical morphological features, such as surface flow direction, watershed boundaries, and slope, making it an indispensable tool in this field. In any situation, a DEM with a finer resolution designed for a specific region or nation can also be obtained from light detection and ranging (LiDAR) products or by spatially interpolating point elevations. Soil properties of spatial division, such as texture (proportion of clay, sand, and silt), organic matter, porosity, bulk density, and hydraulic conductivity, can greatly affect the modeling results, particularly in the surface water (SW) component. These properties play a crucial role in determining soil quality and infiltration capacity [36]. The coherent world soil catalog provides a global distribution of soil characteristics [37]. Additionally, the World Soil Information Service (WOSIS) offers access to over 196,000 soil columns [38]. The given dataset contains information about soil that is standardized and ideal for mapping soil and the Earth's system modeling. Hydrological modeling can be affected by the lack of climate data, so many databases have been created to offer first-class meteorological data. One of these databases is the Climate Forecast System Reanalysis (CFSR) [39], which extends global meteorological information for 36 years at a resolution of less than 1 degree, allowing for detailed historical data analysis. Furthermore, the CORDEX program under the World Climate Research Program (www.euro-cordex.net) provides a platform for the compilation of comprehensive climate data at the continental level, both for historical and future predictions. These data are commonly utilized in water modeling [40; 41]. Obtaining information about subsurface elements, such as hydraulic conductivity and porosity, typically requires permeability tests, which can be both expensive and time-consuming. The other solution is the version 2.0 of Global Hydrogeology Maps (GLHYMPS) of porosity and permeability [42].