Methodology for the determination of trends for climatic and hydrometric parameters upstream of the Dez Dam

In recent years, extreme droughts have occurred in the Middle East. In order to produce forecasts which ascertain the possibility of continuing drought, consideration of climatic and hydrometric data is necessary. This article presents a case study of three hydrometric stations – Telezang, Tang 5 Bakteari and Sepeed Dasht Sezar – upstream of the Dez Dam in Iran. The data examined were temperature, precipitation and flow discharge from 1977 to 2008. The non‐parametric Mann–Kendall test and the Theil‐Sen approach were used for the detection of data trends. Different probability distributions were also used, and momentum, linear momentum and maximum likelihood methods were employed in order to determine their parameters. The Akaike Information Criterion and Bayesian Information Criterion were used to determine the governing probability distributions for the data. By using of a part of the time series (1977–1996), monthly flow discharges at the three stations were forecasted using the non‐parametric method (MK test and TSA) and regression relations were established between monthly flow discharges and other climatic and hydrometric data. This study uses the remainder of the time series (1997–2008) for the verification of monthly flow discharge forecasts. Comparison between observed data (1997–2008) and forecasted monthly flow discharges (using the Root Mean Square Error method) determines the best method for forecasting monthly flow discharge at each station. This research illustrates that the governing probability distributions for observed and forecasted data are similar. The non‐parametric method shows that monthly flow discharges and precipitation have a decreasing trend for most months, and that mean, maximum and minimum temperatures have an increasing trend in summer and a decreasing trend in winter