Prediction of climate change on surface water using NARX neural network model: a case study on Ghezel Ozan River, Northwest, Iran.

The quantity and quality of surface waters are affected by climate change. Therefore, the study of the impact of climate change on surface water is very important. In the first part of the study, the output of the HadGM2-ES model was used to generate a future climatic pattern under two Representative Concentration Pathway (RCP) scenarios: RCP2.6 and RCP8.5. The atmospheric circulation data from the model were utilized for this purpose. In the second part of the study, the climate model Long Ashton Research Station Weather Generator (LARS-WG) was employed to downscale climate data, including precipitation flow, temperatures, total solids (TS), and electrical conductivity (EC) parameters of the Ghezel Ozan River until 2050. In the final section, we evaluated the NARX neural network model for simulating the quality and quantity parameters. The results proved that the LARS-WG software has an extraordinary ability to downscale and generate synthetic series of climatic variables. According to the emission scenarios RCP2.6 and RCP8.5, an increasing trend in minimum and maximum temperature was predicted over the future time period. The highest temperature was obtained under the worst situation of RCP8.5. Additionally, the results showed that the highest decrease in precipitation is estimated as 15.38% in mid-winter and 18.68% in early spring during the future period. With the decrease in precipitation, the river flow is projected to decrease by 42.59% in late winter and 76.32% in early spring compared to the observation period. As a result of decreased precipitation and discharge, the EC parameter is expected to increase by 52.06% in late winter and 81.27% in early spring compared to the base period. Overall, our findings indicate that these parameters are strongly influenced by climate change, posing a risk of water shortage and drought to the ecosystem of many aquatic organism's dependent on this river. [ABSTRACT FROM AUTHOR]