Hydrological modeling is the bridge between what climate models predict in terms of rainfall and what actually happens on the ground as surface runoff. The HEC-HMS hydrologic modeling system, developed by the Hydrologic Engineering Center of the U.S. Army Corps of Engineers, is among the leading tools used for this purpose. It simulates the process of converting rainfall into runoff in both natural and urban catchments, and it is used in flood analysis and water supply estimation. In the study under discussion, version 4.11 was used to build a model of two basins in the Middle Euphrates region: Hilla and Diwaniyah. The work began by delineating the boundaries of the two basins and dividing them into sub-basins, 15 in Hilla and 14 in Diwaniyah, based on the SRTM digital elevation model at 30-meter resolution. Soil data from the Food and Agriculture Organization database, land-use maps derived from Landsat imagery, and daily rainfall data from CHIRPS for the period 1991–2020 were then entered, to compensate for the lack of sufficient daily measurements at ground stations. The model rests on two main components. The first is the loss model, for which the study adopted the SCS Curve Number (SCS-CN) method, which calculates runoff from rainfall depth and the soil’s maximum retention, itself determined by the curve number that combines soil type and land use. The second is the transform model, for which the SCS unit hydrograph was used. It requires the lag time, estimated at roughly 0.6 of the time of concentration calculated with the Bransby-Williams equation. Lag time values across the sub-basins ranged from about two to seven hours, depending on the sub-basin’s area and the length and slope of its flow path. The curve number values showed that both basins respond very strongly to rainfall, ranging from about 88 to 91 across all sub-basins, while the initial abstraction was roughly five to seven mm. This means the surface of the two basins is nearly impervious, so only a small amount of rain is needed for runoff to begin, and a large share of heavy rainfall turns into direct runoff. This also explains why the runoff volume from each sub-basin is related to its area and its curve number value. To test the model’s behavior, two years representing extreme conditions according to drought indices were selected: one dry and one wet. In Hilla, peak flow at the outlet reached about 131 m³/s in the dry year 2002, compared with 194 m³/s in the wet year 2018. In Diwaniyah, it reached about 135 m³/s in the dry year 2000, compared with 224 m³/s in 2018. The simulated runoff volume increased roughly 2.7-fold between the two years in both basins, which shows how strongly runoff is affected by year-to-year variability in rainfall. In the final stage, the model was fed with rainfall series projected by the LARS-WG weather generator under the moderate scenario RCP4.5 and the high scenario RCP8.5. A future wet year and a future dry year were selected for each basin according to drought indices: 2038 and 2050 for Diwaniyah, and 2026 and 2042 for Hilla. The results varied between the two basins and between the two scenarios. In Diwaniyah, the projected peak in the wet year 2038 reached about 259 m³/s under the moderate scenario, an increase of roughly 15% over the peak simulated for 2018, and dropped to about 140 m³/s under the high scenario, a decrease of roughly 37%. In the dry year 2050, the peak was about 142 m³/s under the moderate scenario, roughly 5% higher than the historical drought year, and about 102 m³/s under the high scenario, a decrease of roughly 25%. In Hilla, the projected peaks ranged between about 112 and 277 m³/s. These figures summarize an important idea: the overall trend of future runoff is neither a steady decline nor a steady increase, but fluctuates according to the year, the scenario, and the characteristics of the basin. Years of severe drought reduce runoff, while wet years may produce sharp peaks due to impervious soil and concentrated rainfall, which means that the dual risk of drought and flash floods may coexist in the same region. Nevertheless, these results have limitations that must be recognized. They are based on satellite-derived rainfall, on climate models whose results differ from one another, and on the SCS-CN method, which reduces the complex characteristics of a basin to a single number. They should therefore be read as indicators of possible trends that help in planning water harvesting, protecting infrastructure, and early warning, rather than as precise predictions. Presented by: Zahraa Hussein Mohammed (Assistant Engineer) Source: Zahraa Hussein Mohammed Aziz (2024). Projections of Climate Changes in Hydrological Regime of the middle Mesopotamian plain.