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Environmental isotopes and noble gases in groundwater samples from the Kazan Trona Ore Field are studied to establish the temperature change between the Holocene and the late Pleistocene. Noble gas temperatures (NGTs) presented in this study add an important facet to the global paleotemperature map in the region between Europe and North Africa. The groundwater system under investigation consists of three different aquifers named shallow, middle and deep in which δ18O and δ2H vary from − 8.10‰ to − 12.80‰ and from − 60.89‰ to − 92.60‰ VSMOW, respectively. The average isotopic depletion between unconfined and confined parts of the system is − 2.5‰ in δ18O and − 20‰ in δ2H. It is not possible to explain this depletion solely with the elevation effect. Recharge temperatures derived from dissolved atmospheric noble gases reflect the current average yearly ground temperatures (13°C) for samples collected near the recharge area but are 3 to 8°C lower than today's temperatures in the deep aquifer system. Low 14C activities and high He excesses in the confined parts of the aquifer system suggest that the water in the deep aquifer was recharged during the last Pleistocene under considerably cooler climatic conditions.

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An optimization model that may be used by reservoir system operators to improve daily, real‐time operations and to evolve better long‐term operating guidelines is developed and tested. The four multipurpose reservoirs in the Green River Basin (GRB) of Kentucky are used as a case study. The GRB Operation Optimization Model (GRBOOM) is a linear program constructed to imitate the decision‐ making process that results in actual reservoir release decisions. The model is easily modifiable and very flexible, which allows sensitivity analysis and experimentation with new operating guidelines. This experimentation should permit the operators to evolve improved operating policies. The inputs to the model are data that are readily available, and the outputs may be presented in easily interpreted graphical form.

Trend analyses of meteorological variables play an important role in assessing the long-term changes in water levels for sustainable management of shallow lakes that are extremely vulnerable to climatic variations. Lake Mogan and Lake Eymir are shallow lakes offering aesthetic, recreational, and ecological resources. Trend analyses of monthly water levels and meteorological variables affecting lake levels were done by the Mann-Kendall (MK), Modified Mann-Kendall (MMK), Sen Trend (ST), and Linear trend (LT) methods. Trend analyses of monthly lake levels for both lakes revealed an increasing trend with the Mann-Kendall, Linear, and Sen Trend tests. The Modified Mann-Kendall test results were statistically significant with an increasing trend for Eymir lake levels, but they were insignificant for Mogan lake due to the presence of autocorrelation. While trend analyses of meteorological variables by Sen Test were significant at all tested variables and confidence levels, Mann-Kendall, Modified Mann-Kendall, and Linear trend provided significant trends for only humidity and wind speed. The trend analyses of Sen Test gave increasing trends for temperature, wind speed, cloud cover, and precipitation; and decreasing trends for humidity, sunshine duration, and pan evaporation. These results show that increasing precipitation and decreasing pan evaporation resulted in increasing lake levels. The results further demonstrated an inverse relationship between the trends of air temperature and pan evaporation, pointing to an apparent “Evaporation Paradox”, also observed in other locations. However, the increased cloud cover happens to offset the effects of increased temperature and decreased humidity on pan evaporation. Thus, all relevant factors affecting pan evaporation should be considered to explain seemingly paradoxical observations.