Drought trends projection under future climate change scenarios for Iran region

parameters on describing drought in Iran reported that temperature and precipitation param- eters had the most influential effect on the fluctuation of drought severity in Iran [37]. Further- more, previous works suggested this method in Iran [36, 38]. Therefore, PET was estimated by the HS equation which utilizes maximum and minimum temperatures, mean temperature and solar radiation as follows: PET ¼ 0:0023RaðT þ 17:8Þ ffiffiffiffiffiffi TR p ð8Þ where, PET is the potential evapotranspiration (mm), T is the mean air temperature (˚C), TR is the difference between Tmax and Tmin (˚C), and Ra is the extraterrestrial radiation (MJm- 2day -1). The Ref-ET software was implemented for estimating PET. Finally, considering the precipitation parameter during future years, the magnitude of the SPEIs were predicted for the future 102 years from 2011 to 2112 under each scenario. For assessing the changes in the trend of SPEI between 2011 and 2112, the Mann-Kendall test was used. The Mann-Kendall test is applied to see whether Y values tend to decrease or increase with T (monotonic change). It can be hypothesized as the concentration independent of time of the chemical parameters [39] or H0: no correlation between x and y; Ha: x and y are correlated. To apply the test, Kendall’s S statistic is calculated from the Y, T data pairs: S ¼ P M ð9Þ where, P = the number of Yi<Yj for all i<j, M = the number of Yi>Yj for i<j: t ¼ s nðn 1Þ=2 for n > 10 ð10Þ

ss ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðn=18Þ � ðn 1Þ � ð2n þ 5Þ p ; Zs ¼ S þ 1 ss if S < 0 0 if S ¼ 0 S 1 ss if S > 0 ð11Þ * Positive values of Z show upward trends while negative values of Z indicate downward trends. 3. Modeling results and analysis Evaluating the accuracy of LARS-WG performance in simulating meteorological variables plays a key role in predicting weather parameters for the future periods. For this purpose, the consequences of statistical error indices in the base period are presented in Table 2. According to the information of Table 2, it can be inferred that the calibration of the model was successful with high accuracy. The values of NRMSE and MBE confirm the lowest error in simulating weather variables. Although there are significant differences among the values of NRMSE and MBE in few stations, in general, the results of Table 2 verify proper performance of the model in creating connection between observed and simulated values. Then, the prediction of the weather parameters for the upcoming period was done as earlier described in the materials and methods section. PET values were calculated using Eq 8 while the monthly spatial precipitation and PET distribution for the considered period and for up to the next 102 years (2011 to 2112) under different climate scenarios is shown in Fig 3. These fig- ures were produced with ArcGIS 10.3 using the inverse distance weighted (IDW) procedure. PLOS ONE

Drought trends projection under future climate change scenarios for Iran region PLOS ONE | https://doi.org/10.1371/journal.pone.0290698 November 9, 2023 7 / 24