Floods are among the most devastating disasters in terms of socio-economics and casualties. However, these natural disasters can be managed and their effects can be minimized by flood modeling performed before the occurrence of a flood. In this study, flood modeling was developed for the Göksu River Basin, Mersin, Türkiye. Flood hazard and risk maps were prepared by using GIS, HEC-RAS, and HEC-HMS. In hydraulic modeling, Manning’s n values were obtained from 2018 CORINE data, return period flow rates (Q25, Q50, Q100, Q500) were obtained from HEC-HMS, and the application was carried out on a 5 m resolution digital surface model. In the study area, the water depths could reach up to 10 m, and water speeds were approximately 0.7 m/s. Considering these values and the fact that the study area is an urban area, hazard maps were obtained according to the UK Department for Environment, Food and Rural Affairs (DEFRA) method. The results indicated that possible flood flow rates from Q25 to Q500, from 1191.7 m³/s to 1888.3 m³/s, were detected in the study area with HEC-HMS. Flooding also occurred under conditions of the Q25 flow rate (from 4288 km² to 5767 km²), and the impacted areas were classified as extremely risky by the DEFRA method.

Trend analyses of meteorological variables play an important role in assessing the long-term changes in water levels for sustainable management of shallow lakes that are extremely vulnerable to climatic variations. Lake Mogan and Lake Eymir are shallow lakes offering aesthetic, recreational, and ecological resources. Trend analyses of monthly water levels and meteorological variables affecting lake levels were done by the Mann-Kendall (MK), Modified Mann-Kendall (MMK), Sen Trend (ST), and Linear trend (LT) methods. Trend analyses of monthly lake levels for both lakes revealed an increasing trend with the Mann-Kendall, Linear, and Sen Trend tests. The Modified Mann-Kendall test results were statistically significant with an increasing trend for Eymir lake levels, but they were insignificant for Mogan lake due to the presence of autocorrelation. While trend analyses of meteorological variables by Sen Test were significant at all tested variables and confidence levels, Mann-Kendall, Modified Mann-Kendall, and Linear trend provided significant trends for only humidity and wind speed. The trend analyses of Sen Test gave increasing trends for temperature, wind speed, cloud cover, and precipitation; and decreasing trends for humidity, sunshine duration, and pan evaporation. These results show that increasing precipitation and decreasing pan evaporation resulted in increasing lake levels. The results further demonstrated an inverse relationship between the trends of air temperature and pan evaporation, pointing to an apparent “Evaporation Paradox”, also observed in other locations. However, the increased cloud cover happens to offset the effects of increased temperature and decreased humidity on pan evaporation. Thus, all relevant factors affecting pan evaporation should be considered to explain seemingly paradoxical observations.