Water Analysis and Climatic History of Gilgit and Hunza Valleys A Dendroclimatic Approach

Twenty-nine samples from different locations of Upper Indus Basin from Gilgit and Hunza valleys were selected for the investigation of physico-chemical characteristics. Sampling was performed during July in the year 2012. Eleven parameters were chosen for water analysis to assess water quality and to observe the variations among different sites. Physical factors were analyzed at site while chemical analysis was carried out in the laboratory using standard techniques of water analysis developed by (American Public Health Association, APHA) and spectrophotometeric techniques. Multivariate statistical techniques including principal component analysis (PCA) and cluster analysis (CA) were employed to interpret the data and to unravel the causes of water pollution. Results of physico-chemical properties showed that values of all parameters were in accordance with the permissible limits proposed by World Health Organization (WHO) but the high values of total alkalinity shows that water is of bicarbonate type. Knowledge of past climate variability is necessary for understanding present and future climate tendencies. This study used three species (Picea smithiana, Juniperu sexcelsa and Pinus gerardiana) ring-width chronologies to investigate palaeo-temperature history in Gilgit and Hunza valleys Northern Pakistan. The resultant reconstruction is among the first palaeo-series from Picea smithina produced for Pakistan to date. It is in good agreement with other tree-ring based records, and with instrumental (both local and grid) data. Ten pine chronologies including three species were developed. Ring-width measurements were detrended using the standardization method to preserve as much climatic signals as possible. Crossdating exposed the presence of a strong common signal among trees. Inter-site comparison showed that a common control mechanism affected tree growth not only within sites, but also across sites. To determine whether climate was the main factor that controlled the growth of three species from Gilgit and Hunza, correlation and response functions were analyzed. Temperature and precipitation were tested for their relationship with tree growth. Mean monthly temperature and total monthly precipitation were observed as the primary growth-limiting factor. Chronologies were negatively correlated with temperature and precipitation of spring season, and climate correlation modeling showed that temperature and precipitation explained 39-63% variance in the tree-ring data. Tree- vring data from Picea smithiana Jutial contained the strong temperature signal, was picked for reconstruction. The Jutial chronology was then used to reconstruct March-June temperatures back to A.D. 1523. The calibration model explained 38.16% of the variance in temperature, and all calibration and verification tests were passed at good levels of significance. The reconstructed temperature was tested over decadal and century time-scale. The coolest decadal time scale period revealed that 17 th century experienced lowest degree of temperature and ensuing the period of “Little Ice Age” (LIA). The temperatures reached their maximum in 19 th century over century time-scale. As Pinus gerardiana Chaprot chronology exhibited strongest temperature signal among all chronologies therefore, separate exercise was performed where Jutial chronology reconstruction was compared with Chaprot reconstruction. Two species demonstrated the common pattern in spring temperatures. However, the temperature reconstruction from Chaprot was insufficient to produce a long term proxy temperature. This research has strengthened the Pakistan network of chronology sites, and confirmed that Picea smthiana, Juniperus excelsa and Pinus gerardiana have great dendro-climatic value. The last more than 450 years of temperature fluctuations were reconstructed with a high degree of fidelity. The current reconstruction added similar trend of temperature in comparison with the other studies throughout central Asia.