The Zayandeh-Rud River basin, Iran, is projected to face spatiotemporally heterogeneous temperature increase and precipitation reduction that will decrease water supply by mid-century. With projected increase (0.70–1.03 °C) in spring temperature and reduction (6–55%) in winter precipitation, the upper Zayandeh-Rud sub-basin, the main source of renewable water supply, will likely become warmer and drier. In the lower sub-basin, 1.1–1.5 °C increase in temperature and 11–31% decrease in annual precipitation are likely. A system dynamics model was used to analyze adaptation strategies taking into account feedbacks between water resources development and biophysical and socioeconomic sub-systems. Results suggest that infrastructural improvements, rigorous water demand management (e.g., replacing high water demand crops such as rice, corn, and alfalfa), and ecosystem-based regulatory prioritization, complemented by supply augmentation can temporarily alleviate water stress in a basin that is essentially governed by the Limits to Growth archetype.

This paper applies HEC-HMS to the Karkheh River basin (KRB), Iran, and facilitates the calibration of a continuous hydrologic model (CHM) with soil moisture accounting (SMA) and snowmelt degree-day parameters. Manual calibration was performed to ensure the physical relevance of HEC-HMS parameter values. Because manual calibration entails changing each parameter value in a user-defined setting, it is often a time-consuming procedure complicated by multitude of interacting parameters. To address this setback, an event-based calibration technique (EBCT) was implemented in KRB and its interior sub-basins whereby the governing parameters of specific fall, spring, and winter events were initially estimated in a precalibration step and used as inputs to facilitate calibration of the CHM. Model performance analyzed based on goodness-of-fit criteria with respect to peak flows, low flows, and hydrograph shape reflects uncertainties associated with streamflow naturalization and use of average annual parameter values for the snowmelt component. Sensitivity analysis provided insights into the basin’s snowfall and melt characteristics, distinguishing antecedent temperature index (ATI) cold rate coefficient and baseflow recession coefficient as key parameters affecting hydrograph shape and magnitude of the peak flow, respectively. Results based on goodness of fit metrics suggest that event-based parameter estimation using seasonal characteristics improved the efficiency and accuracy of the continuous HEC-HMS model (CORRL and NSE 0.78–0.87 and 0.5–0.7, respectively) while facilitating application to a large, data-poor river basin with heterogeneous climatic conditions.