Flow in complex karst aquifers is challenging to conceptualize and model, especially in poorly investigated areas, in semiarid climates, and under changing climatic conditions; however, it is necessary in order to implement long-term sustainable water management practices. Thus, the objectives of this work were to propose a calibration approach based on time series analyses for a karst aquifer and to assess the impact of climate change on spring discharge. Based on more than 3 years of high-resolution continuous monitoring, a semi-distributed lumped model was calibrated and validated for the Qachqouch karst spring, north of Beirut (Lebanon). Time series analyses and decomposition of spring hydrographs revealed that the system has a high regulatory function, with considerable storage capacity providing stable flow (minimum flow of 0.2 m3 s−1) during the dry season and with flow rates exceeding 10 m3 s−1 during the wet season, which is similar to other karst aquifers in the region. Based on this detailed understanding of the hydrodynamics of the system, the model geometry and parameters were validated. Three linear reservoirs were implemented to reproduce the combined contribution of the different flow components of the system. A satisfactory simulation (Nash–Sutcliffe efficiency coefficient, NSE, of 0.72) of the measured spring flow rates was obtained after calibration. Climate change conditions (+1 to +3 ∘C warming, −10 % to −30 % less precipitation annually, and the intensification of rain events) were added to a baseline climatic year to produce scenarios of expected spring flow responses. Results show that the Qachqouch karst aquifer is sensitive to decreasing rainfall, which is associated with more pronounced recessions, with flow rates decreasing by 34 % and 1-month longer dry periods. Because of the limited influence of snow on the spring flow rate, a warming climate has less impact on spring flow conditions than a reduction in precipitation. Although the model shows that increasing rainfall intensity induces larger floods, recessions, and shorter low-flow periods, the real impact of high-intensity precipitation events remains uncertain, as the model does not account for complex unsaturated and epikarstic processes. This work shows that calibrating a semi-distributed lumped model using time series analyses can be an efficient approach to improve simulations of complex karst aquifers, thereby providing useful models for long-term sustainable water management.