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In recent decades, according to Intergovernmental Panel on Climate Change reports, the impact of climate change on hydro‐meteorological events has increased substantially. This point is obvious in many rainfall–runoff time series as a negative or positive trend. In this paper, first of all such trend possibilities are searched graphically according to Şen's 1:1 (45°) straight‐line method, which has been proposed instead of the classical methods including Mann–Kendall, Spearman's rho and linear regression approaches. Additionally, these trends are quantified by using frequency–intensity–duration (FID) curves, instead of intensity–duration–frequency (IDF) curves obtained from a set of single storm rainfall records. The FID curves provide practical, easy and clear representation of rainfall intensity variation through fitted exponential curves with coefficient of determination that is almost equal to 1 (R2 ≈ 1). FID curves are drawn on semilogarithmic paper with rainfall intensity estimations from the convenient Gamma probability distribution functions (PDFs) or cumulative distribution functions (CDFs). In this study 46‐year rainfall records are used from Florya station, which is located in Istanbul, Turkey. The comparisons generally indicated that a negative trend is valid at this station, and accordingly, representative FID curves are obtained on ordinary and semilogarithmic papers for this station.

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The non-revenue water (NRW) ratio parameter is significantly important for performance evaluation of water distribution systems. In order to evaluate the NRW ratio, the variables influencing this parameter should be determined. Therefore, the first aim of the paper is to define the variables which are influential on the estimation of the NRW ratio and then analyze these variables by using artificial neural networks (ANNs) methodology by means of 50 models with one, two, three, and four-variable input. Secondly, in this study, the NRW ratios have been predicted for the first time by using the Kriging methodology through only two variables. By using the data measured in 12 district meter areas (DMA) in Kocaeli, 60 models in total have been established for NRW ratio prediction through the ANN and Kriging methodologies. The ANN models are closed-box models and therefore the interpretation of the ANN model results requires higher expert opinion. As a consequence, the results show that Kriging model graphs produce much more useful information than ANN models in terms of application and interpretation.