Simulation of the impact of climate change on runoff and drought in an arid and semiarid basin (the Hablehroud, Iran)

Abstract

This study evaluates the impact of climate change (CC) on runoff and hydrological drought trends in the Hablehroud river basin in central Iran. We used a daily time series of minimum temperature (Tmin), maximum temperature (Tmax), and precipitation (PCP) for the baseline period (1982–2005) analysis. For future projections, we used the output of 23 CMIP5 GCMs and two scenarios, RCP 4.5 and RCP 8.5; then, PCP, Tmin, and Tmax were projected in the future period (2025–2048). The GCMs were weighed based on the K-nearest neighbors algorithm. The results indicated a rising temperature in all months and increasing PCP in most months throughout the Hablehroud river basin's areas for the future period. The highest increase in the Tmin and Tmax in the south of the river basin under the RCP 8.5 scenario, respectively, was 1.87 °C and 1.80 °C. Furthermore, the highest reduction in the PCP was 54.88% in August under the RCP 4.5 scenario. The river flow was simulated by the IHACRES rainfall-runoff model. The annual runoff under the scenarios RCP 4.5 and RCP 8.5 declined by 11.44% and 13.13%, respectively. The basin runoff had a downward trend at the baseline period; however, it will have a downward trend in the RCP 4.5 scenario and an upward trend in the RCP 8.5 scenario for the future period. This study also analyzed drought by calculating the streamflow drought index for different time scales. Overall, the Hablehroud river basin will face short-term and medium-term hydrological drought in the future period.

Evaluating the effects of CMIP6 model uncertainty on extreme flows of the Caspian Hyrcanian forest watersheds by BMA method

“…Therefore, it can be concluded that the omission of some models and the use of a limited number of them cannot provide a reliable estimate of runoff and climatic variables in the future. This result is consistent with the statements (Alinezhad et al, 2021;Ashrafi et al, 2020;Lotfirad et al, 2021). Therefore, in this study, the BMA method was used to maintain the capacity of all models and reduce the uncertainty caused by using a single model (Najafi et al, 2011).…”

“…In this study, the IHACRES semi-conceptual model simulated the rainfall-runoff process. This model consists of two modules, linear and nonlinear, which convert PCP into effective PCP and effective PCP into the runoff, respectively see Jakeman & Hornberger (1993) and Lotfirad et al (2021). For rainfall-runoff simulations in this study, the 19-year period (1994 to 2012) was considered as the calibration period, and the 7-year period (2013 to 2018) was considered as the validation period.…”

“…Therefore, studying the effect of climate change on the basin's runoff is of particular importance. To understand the past and future changes of global and regional climate events, general circulations models (GCMs) are used (Lotfirad et al, 2021;Vaghefi et al, 2019;Zarrin & Dadashi-Roudbari, 2021;Zhang et al, 2019).…”

“…Another method is climatic variables forecasting based on multiple GCMs and their weighting (Ashofteh et al, 2015;Lotfirad et al, 2021;Zamani & Berndtsson, 2019;Zareian et al, 2015).…”

“…The weighting method itself is divided into subcategories, including uniform weighting for all GCMs (Araji et al, 2018), weighting based on their differences with observed monthly climatic data in the historical period (Lotfirad et al, 2021), and probabilistic weighting based on their efficiency in each month in the historical period (Najafi et al, 2011). Among the mentioned methods, the probabilistic-based method has a better performance in forecasting hydro-climatic processes (Javanshiri et al, 2021;Madadgar & Moradkhani, 2014;Raftery et al, 2005).…”