Mohammadi, FarnazPu, Jaan H.Guo, YakunHanmaiahgari, P.R.Mohammadi, O.Mohammadi, M.Al-Qadami, E.Razi, M.A.M.2025-07-082025-07-152025-07-082025-07-152025-06Mohammadi F, Pu JH, Guo Y et al (2025) Hydro-climatic variability and peak discharge response in Zarrinehrud River Basin, Iran, between 1986 and 2018. Atmosphere. 16(6): 681.RMSID:25872https://bradscholars.brad.ac.uk/handle/10454/20517YesIn recent years, both anthropogenic and climate changes have caused the depletion of surface water resources, shifts in rainfall and accelerations in temperature, which indicates the importance of their examination to flood forecasting analyses. This paper studies the importance of synchronised water management strategies, considering upstream and downstream dynamics using field data from 1986 to 2018. Seasonal and decadal variations show the need for adaptive management strategies to address potential climate change impacts on discharge, precipitation and temperature patterns in the Zarrinehrud River, Iran. The regression analysis was considered via R2 values, and the statistical analysis was regarded by p-values. The regression analysis of monthly river peak discharge indicates strong correlations between the discharge of specific months (September–October upstream, December–January downstream). By the 2000s and 2020s, both stations showed a shift in peak precipitation to the spring months (April–May for upstream and May–June for downstream). This confirms a synchronisation of rainfall trends, which are influenced by climate changes or regional hydrological patterns. This temporal offset between stations confirms the spatial and seasonal variation in rainfall distribution across the basin. Higher temperatures during the dominant months, particularly late summer to early autumn, accelerate snowmelt from upstream catchments. This aligns with the river discharge peaks observed in the hydrograph. The statistical analysis of river peak discharge indicated that the Weibull (p-value = 0.0901) and the Lognormal (p-value = 0.1736) distributions are the best fitted distributions for the upstream and downstream stations, respectively.en© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).Flood forecastingClimate changeRiver peak dischargePrecipitationTemperatureArticlehttps://doi.org/10.3390/atmos16060681CC-BY2025-07-08