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Water resources is a

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Photosynthesis response to carbon dioxide concentration can provide data on a number of important parameters related to leaf physiology. The genetic algorithm (GA), which is a robust stochastic evolutionary computational algorithm inspired by both natural selection and natural genetics, is proposed to simultaneously estimate the parameters [including maximum carboxylation rate allowed by ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco) carboxylation rate (Vcmax), potential lightsaturated electron transport rate (Jmax), triose-phosphate utilization (TPU), leaf dark respiration in the light (Rd) and mesophyll conductance (gm)] of the photosynthesis models presented by Farquhar, von Caemmerer and Berry, and Ethier and Livingston. The results show that by properly constraining the parameter bounds the GA-based estimate methods can effectively and efficiently obtain globally (or, at least near globally) optimal solutions, which are as good as or better than those obtained by non-linear curve fitting methods used in previous studies. More complicated problems such as taking the gm variation response to CO2 into account can be easily formulated and solved by using GA. The influence of the crossover probability (Pc), mutation probability (Pm), population size and generation on the performance of GA was also investigated.

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The Heihe River Basin is a typical arid inland river basin for examining stress on groundwater resources in northwest China. The basin is composed of large volumes of unconsolidated Quaternary sediments of widely differing grain size, and during the past half century, rapid socioeconomic development has created an increased demand for groundwater resources. Understanding the hydrogeochemical processes of groundwater and water quality is important for sustainable development and effective management of groundwater resources in the Heihe River basin. To this end, a total of 30 representative groundwater samples were collected from different wells to monitor the water chemistry of various ions and its quality for irrigation. Chemical analysis shows that water presents a large spatial variability of chemical facies (SO 4 2--HCO 3 -, SO 4 2--Cl -, and Cl --SO 4 2-) as groundwater flow from recharge area to discharge area. The ionic ratio indicates positive correlation between the flowing pairs of parameters: Cl -and Na ? (r = 0.95), SO 4 2-and Na ? (r = 0.84), HCO 3 -and Mg 2? (r = 0.86), and SO 4 2-and Ca 2? (r = 0.91). Dissolution of minerals, such as halite, gypsum, dolomite, silicate, and Mirabilite (Na 2 SO 4 Á10H 2 O) in the sediments results in the Cl -, SO 4 2-, HCO 3 -, Na ? , Ca 2? and Mg 2? content in the groundwater. Other reactions, such as evaporation, ion exchange, and deposition also influence the water composition. The suitability of the groundwater for irrigation was assessed based on the US Salinity Laboratory salinity classification and the Wilcox diagram. The results show that most of the groundwater samples are suitable for irrigation uses barring a few locations in the dessert region in the northern sub-basin.