Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment. 相似文献
The spread of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) has become an increasingly serious global public health issue. This study investigated the distribution characteristics and influencing factors of ARB and ARGs in greenhouse vegetable soils with long-term application of manure. Five typical ARGs, four heavy metal resistance genes (MRGs), and two mobile genetic elements (MGEs) were quantified by real-time quantitative polymerase chain reaction (qPCR). The amount of ARB in manure-improved soil greatly exceeded that in control soil, and the bacterial resistance rate decreased significantly with increases in antibiotic concentrations. In addition, the resistance rate of ARB to enrofloxacin (ENR) was lower than that of tylosin (TYL). Real-time qPCR results showed that long-term application of manure enhanced the relative abundance of ARGs in vegetable soils, and the content and proportion of quinolone resistance genes were higher than those of macrolide resistance genes. Redundancy analysis (RDA) showed that qepA and qnrS significantly correlated with total and available amounts of Cu and Zn, highlighting that certain heavy metals can influence persistence of ARGs. Integrase gene intI1 correlated significantly with the relative abundance of qepA, qnrS, and ermF, suggesting that intI1 played an important role in the horizontal transfer of ARGs. Furthermore, there was a weakly but not significantly positive correlation between specific detected MRGs and ARGs and MGEs. The results of this study enhance understanding the potential for increasing ARGs in manure-applied soil, assessing ecological risk and reducing the spread of ARGs.