Physics and Chemistry of the Earth xxx (xxxx) xxx Please cite this article as: Mehdi Ahmadi, Physics and Chemistry of the Earth, https://doi.org/10.1016/j.pce.2019.09.002 Available online 24 September 2019 1474-7065/© 2019 Elsevier Ltd. All rights reserved. Assessment of climate change impact on surface runoff, statistical downscaling and hydrological modeling Mehdi Ahmadi a , Motamedvaziri Baharak a, * , Hassan Ahmadi b , Abolfazl Moeini a , Gholam Reza Zehtabiyan b a Department of Forest, Range and Watershed Management, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran b Department of Reclamation of Arid and Mountainous Regions, University of Tehran, Karaj, Iran A R T I C L E INFO Keywords: Artifcial neural networks Climate change IHACRES RCP scenario SDSM ABSTRACT Over the last few decades, the climate change has been increased due to the increased industrial activities, greenhouse gas emissions, and CO 2 level. This change has affected the water resource management so that the amount of water entered from upstream of watersheds has been transformed every year, and the water resource management has become diffcult for the surface runoff, entered water, food and drought. The problem becomes more serious when the study area (Kan watershed) is located upstream of such urban watershed as Tehran, where the climate change studies on the water resources are very important. In this study, using the Statistical downscaling model (SDSM), the data of CanESM2 Canadian general circulation model (GCM) was downscaled under the Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. In order to study the climate change, the artifcial neural network (ANN) and IHACRES models were used over the period of 2010–2040. The study results showed that the temperature is increased in the upcoming period of 2006–2100 (0.8–5.6 C � ), and the highest temperature changes are related to winter and summer. The precipitation in the upcoming period shows an increasing trend on the annual average, but, in general, it can be said that the 4–55% precipitation shows an increasing trend. The runoff in the upcoming period of 2010–2040 under RCP2.6, RCP4.5 and RCP8.5 is 4, 26 and 2 percent in the ANN model and 26, 28 and 33 percent in the IHACRES model, respectively. 1. Introduction Today, numerous studies conducted in Iran and around the world deal with the potential impacts of climate change on the water re- sources, including the impact on water quantity, hydrology and water demand. Using the global data available since the last century, it was found that the global runoff is increased by 4% with the earth temper- ature rising by 1% (Vera et al., 2006; Narsimlu et al., 2013). Over the past few decades, the climate change phenomenon has caused the changes in the food, drought, surface runoff, and water resource management (Rahimi et al., 2018). The policies of authorities and countries should be planned so as to deal with these phenomena. In order to plan and manage water resources, the climate change and its effect on surface runoff should be understood (Narsimlu et al., 2013; Chang et al., 2017). Generally, it can be stated that surface runoff causes the food, drought, storage, and loss. Thus, it is found that with simulating the surface runoff or the rainfall-runoff modeling, many questions can be answered (Tibebe et al., 2017). In order to investigate the effects of climate change on different systems in upcoming periods, the future climate variables should be initially simulated. There are several methods for simulating the climate variables in the upcoming periods, and the most valid method is the use of climate outputs of Atmosphere-Ocean General Circulation Model (AOGCM). In these models, some efforts have been made to simulate the processes that are effective on the climate and the climate situation to be predicted for the upcoming years based on the processes. Since the prediction of future climate conditions is not possible under the infu- ence of climate change phenomenon, the alternative solution is to determine the possibility of various events, which is ultimately per- formed using the emission scenarios (Ashraf Vaghef et al., 2014; Deh- ghan et al., 2019). One of the drawbacks of large-scale models is the large size of the * Corresponding author. E-mail addresses: Ahmadimehdi533@yahoo.com (M. Ahmadi), bmvaziri@gmail.com (B. Motamedvaziri), Ahmadi@ut.ac.ir (H. Ahmadi), abmoeini@yahoo.com (A. Moeini), ghzehtab@ut.ac.ir (G.R. Zehtabiyan). Contents lists available at ScienceDirect Physics and Chemistry of the Earth journal homepage: http://www.elsevier.com/locate/pce https://doi.org/10.1016/j.pce.2019.09.002 Received 20 July 2019; Received in revised form 31 August 2019; Accepted 20 September 2019