# GIS-Based Flood Assessment Using Hydraulic Modeling and Open Source Data: An Example of Application  
[PERSON]  
1 Department of Sustainable Development and Environmental Engineering, Faculty of Agriculture, University of Life Sciences \"[PERSON]\" from Timisoara, 300645 Timisoara, Romania; [EMAIL_ADDRESS] (L.C. ); [PERSON] (C.A.P. ); [EMAIL_ADDRESS] (M.V.H.) [PERSON]  
2 Department of Hydrotechnical Engineering, Faculty of Civil Engineering, Politechnica University Timisoara, 300006 Timisoara, Romania; [EMAIL_ADDRESS] (E.T.M. ); [EMAIL_ADDRESS] (R.B. ); [EMAIL_ADDRESS] (A.C.); [EMAIL_ADDRESS] (O.S.C)  
2 Department of Agricultural Technologies, Faculty of Agriculture, University of Life Sciences \"[PERSON]\" from Timisoara, 300645 Timisoara, Romania  
3 Department of Agricultural Technologies, Faculty of Agriculture, University of Life Sciences \"[PERSON]\" from Timisoara, 300645 Timisoara, Romania  
Floods generate complex effects on natural and anthropogenic environments, including soil erosion, destruction of natural habitats, water pollution through the dispersion of waste and toxic substances, destruction of agricultural crops, and damage to infrastructure, housing, and economic activities. These impacts result in significant biodiversity losses, depletion of resources, and human casualties [12; 13]. According to the Global Assessment Report on Disaster Risk Reduction [14], floods affect millions of people worldwide each year, causing severe damage to infrastructure and the economy. For example, in 2023, natural disasters resulted in 86,473 deaths and affected 93.1 million people, with their impact exceeding the 20-year average in terms of human losses, highlighting the increased vulnerability of exposed communities [14]. Flooding of agricultural lands, in addition to the direct precipitation effect caused by raindrops, creates complex abiotic stress [15], including reduced light availability [16], anaerobic conditions that affect microbial metabolism and the biogeochemical cycle of nutrients [17; 18], and changes in the physical and chemical properties of soil [19], leading to reduced fertility [20]. All these factors negatively impact the growth and development of crops [21; 22], reducing their productivity. In the context of increasing hydrological risk phenomena caused by climate change and socio-economic factors, increasingly precise methods and models have been developed for hydrological risk modeling and identifying flood-prone areas [23; 24; 25]. These approaches rely on Geographic Information Systems (GIS), remote sensing, and hydrological and hydraulic modeling techniques [11; 26; 27; 28; 29; 30; 31; 32]. GIS plays an important role in flood analysis by mapping flood-prone areas [33; 34; 35], integrating hydraulic and hydrological applications [36; 37], and assessing risk through multi-criteria analysis [38]. Passive and active remote sensing data allow for monitoring flood extent [39], conducting temporal flood analysis [40], and planning land use to prevent risks [41; 42]. Additionally, hydraulic modeling enables the analysis of water flow, flow assessment, and forecasting of river behavior [43; 44; 45]. Currently, numerous specialized computer models and software programs simulate flow characteristics (depth, speed, etc.) and flood-affected areas, including TELEMAC-2D, River-2D, HEC-HMS, HEC-RAS (are open-source and free), MIKE11, and MIKE (are commercial software, requiring a paid license) [25; 46]. Among them, HEC-RAS (Hydrogic Engineering Center's River Analysis System), version 6.5 [47], used in this study, is a program developed by the US Army Corps of Engineers for modeling water flows in rivers and channels. It supports both subcritical and supercritical flows and includes sediment analysis and pollutant transport. Its applications include one-dimensional and two-dimensional river flow modeling, flood modeling, and erosion analysis.