In the threshold of the appearance of global warming from theory to reality, extensive research has focused on predicting the impact of potential climate change on water resources using results from Global Circulation Models (GCMs). This research carries this further by statistical analyses of long term meteorological and hydrological data. Seventy years of historical trends in precipitation, temperature, and streamflows in the Great Lakes of North America are developed using long term regression analyses and Mann-Kendall statistics. The results generated by the two statistical procedures are in agreement and demonstrate that many of these variables are experiencing statistically significant increases over a seven-decade period. The trend lines of streamflows in the three rivers of St. Clair, Niagara and St. Lawrence, and precipitation levels over four of the five Great Lakes, show statistically significant increases in flows and precipitation. Further, precipitation rates as predicted using fitted regression lines are compared with scenarios from GCMs and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are higher than GCM predictions for Lakes Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes particularly for the precipitation in the Great Lakes Basin may be demonstrating influences arising from global warming and climate change.

The combination of climate change and natural periodicities in meteorological variables are demonstrating significant impacts on the water resources of Lake Superior within the Laurentian Great Lakes system of North America. Statistical analyses of long-term records are used to demonstrate how changes over time may be interpreted very differently, depending upon the timeframe over which the analyses are made. Non-linear regression modelling shows that, while increasing trends in overland and overlake precipitation, flows and runoff occurred during the first decades of the twentieth century, very different trends are apparent for the period 1970–2005. For this latter period, increasing rates of air overlake temperature and lake evaporation are occurring but all other parameters are demonstrating decreasing trends. The result is a decline in water levels in Lake Superior at the rate of approximately 1 cm per year over the last 35 years. The results are used to show that to avoid decreasing water levels in Lake Superior, the discharge through St Mary's River must be decreased to approximately one-half the long-term annual average, the results of which will have dramatic implications for ships' cargo levels and hydroelectric energy generation.

Qanats (Kanats) have been an ancient, sustainable system facilitating the harvesting of water for centuries in Iran, and more than 34 additional countries of the world. These subterranean channels have been used for the transference of snowmelt water from the mountainous terrain for thousands of years. Agricultural, industrial and urban demands for fresh water have brought about increasing demands for water, the elixir of life. In response, the harvesting of water via deep groundwater wells throughout arid zones has disturbed the aquifers, and resulted in the abandonment of some qanats. Qanats in the province of Yazd City are witnessing this depletion. This paper introduces qanats, objectives causing their creation, construction materials, locations and their importance in different times, as well as their present role in Iran. Further, current qualitative and quantitative analyses of the qanats in Tehran are identified.

Four statistical models (linear regression, exponential regression, Poisson regression and logistic regression) applied to analyze the variables in pipe vulnerabilities with the objective of finding equations to predict probable future pipe accidents. The most effective variables in pipe failures are material, age, length, diameter and hydraulic pressure. To evaluate these models, the data collected in recent years in the water distribution network of district 1 in Tehran were used, with a total length of 582,702 m of pipes, and 48,500 consumers. The results demonstrate that among the four studied models, the logistic regression model is best able to give a good performance and is capable of predicting future accidents with a higher probability.

Estimates of the impact of climate change on Sardabrud River located downstream of Alam-Kuh glacier in northern Iran, ultimately draining into the Caspian Sea, are described. In this research, the GCMs’ projection data with CMIP5 scenarios have been used to predict the situation of this River over the two next decades. Projected data using GCMs (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIRO-C5 and MPI-ESM-MR) for the period of 2021–2040 are employed with a 35-year observation period of 1984–2014. For data downscaling the LARS-WG method on its version 6.0 was used. Identification of the lowest error indicates (including RMSE and R²) were used to find the model with the best fit to projections from the historical period; the EC-EARTH model was used to show the changes in the basin’s flow to the Sardabrud River in the period 2021–2040. Results from a conceptual glacier-hydrologic model (GSM-SOCONT) for joint simulation of daily discharges of the glacier are described. Despite a predicted 6% decrease in precipitation, the results point to an increase of 10% in flows in the Sardabrud River, meaning there is definitive evidence of reduction of annual glacier mass due to increasing temperatures and the melting of the glacier, as caused by climate change.