This study puts forward a novel approach to identify Parishan Lake drying up roots by studying the dynamic evolutions in the study sub-basin. SPI, extreme climate indices, and several parameters (precipitation, evaporation, and temperature) were employed for 16 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018). To obtain the object of the study, the phase space reconstruction method of delays and chaos theory were applied. Reconstruction of the phase space exposed that some attractors were elliptical shape and some were point. The temperature, evaporation, TXn, and PET suggested periodic time-series. However, TX90p, TX10p, TN10p, and SPI revealed aperiodic time-series, and, RX1day, Rx5day, and precipitation exhibited quasi-periodic behavior in time-series. The trajectory dispersion of all the parameters except TN10p, TX90p, and SPI reflected low chaos, while TN10p, TX90p, and SPI presented random behavior. The phase space behavior of RX1day, Rx5day, TN10p, precipitation, TX90p, and TX10p was nonsinusoidal. By contrast, temperature, evaporation, TXn, PET, and SPI displayed sinusoidal phase space behavior. The findings confirmed that Parishan Lake sub-basin has experienced climate changes which have generated anomalies in climatic and nonclimatic parameters. The comparison between reconstructed phase space of study sub-basin and control sub-basin verified that climate change yielded equal impacts on the study and control sub-basins. As it was highly improbable that the Parishan Lake could be dried up in less than 10 years due to climate change, other affecting factors were also addressed. The findings indicated that excessive groundwater exploitation (as the key factor) increased dryness in the Parishan Lake sub-basin.