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ABSTRACT:One of the potential impacts of climate change (CC) is the change on flood frequency and magnitude. Assessment of impact on floods involves many uncertainties. Difficulty in preparing reliable continuous time series of climate variables with fine time step and capturing extreme rainfalls for future climate scenarios has led to limited studies aimed at investigation of the change of flood regime due to CC. Weather Generators (WGs) have the potential for downscaling of GCMs (General Climate Models) outputs. However, WGs inabilities in relation to producing extreme rainfalls and low-frequency variabilities have caused WGs to receive limited attention in flood studies. In this study, a new WG model, that removes the aforementioned WGs' inabilities, is coupled with a continuous daily rainfall-runoff model to assess the CC impacts on floods of a basin in Iran. Changes in different characteristics of climate variables are applied in the downscaling procedure. Results indicated that, aside from the large uncertainty of emission scenarios, the climate change will lead to considerable increase in flood magnitude in the study basin.

The evaluation of climate change and its side effects on the hydrological processes of the basin can increasingly help in dealing with the challenges that water resource managers and planners face in future courses. These side effects are investigated using the simulation of hydrological processes with the help of physical rainfall‐runoff model. Hydrological models provide a framework for examining the relationship between climate and water resources. This research aims at the investigation of the effect of climate change on the runoff of Gharesou, which is one of the main branches of the “Karkheh” River in Iran during the periods 2040–2069. To achieve this, the distributed hydrological model Soil and Water Assessment Tool (SWAT) – a model that is sensitive to the changes in land, water, and climate – has been used with the aim of evaluating the impact of climate change on the hydrology of the Gharesou Basin. For this reason, first, the continuous distributed model of rainfall‐runoff SWAT for the period 1971–2000 has been calibrated and validated. Next, with the aim of evaluating the impact of climate change and global warming on the basin hydrology for the period 2040–2069, HadCM3‐AR4 global climate model data under the A2 scenario – from the SRES scenario set‐haves been downscaled. Eventually, the downscaled climate data haves been introduced in the SWAT model, and the future runoff changes have been studied. The results showed that the temperature increases in most of the months, and the precipitation rate exhibits a change in the range of ±30%. Moreover, the produced runoff in this period changes from −90 to 120% during different months.

This study develops and applies the first coupled surface water-groundwater (SW-GW) flow model for the irrigated Miyandoab plain located in the Urmia basin, in the northwest of Iran. The model is implemented using a dynamic coupling between MODFLOW and WEAP and consists of spatially distributed monthly water balances for the aquifer, root-zone, rivers, canals, and reservoirs. Multi-objective calibration of the model using river discharge and GW level data yields accurate simulation of historical conditions, and results in better constrained parameters compared to using either data source alone. Model simulations show that crop water demand cannot be met during droughts due to limited GW pumping capacity, and that increased GW pumping has a relatively strong impact on GW levels due to the small specific yield of the aquifer. The SW-GW model provides a unique tool for exploring management options that sustain agricultural production and downstream flow to the shrinking Urmia Lake.

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