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.
Organic pollutants, especially persistent organic pollutants were examined in the water and surface sediments of Taihu Lake, China. Both 12 water and 12 sediment samples were collected over the lake. C-18 solid-phase extraction technique was applied to extract organic pollutants in collected water samples. Soxhlet extraction procedure was used to extract organic pollutants in sediment samples. The analysis was performed by GC-MS controlled by a Hewlett Packard chemstation. Two hundred and seventy-three kinds of organic chemicals in water were examined, 200 more than that detected in 1985; 188 kinds of chemicals in sediments were detected as well. Among them 21 kinds of chemicals belong to priority pollutants as well as 17 kinds to be the endocrine disruptors. The concentrations of the pollutants were more than 2 times higher than that in 1985. The possible source and relation to anthropogenic activity were discussed. 相似文献
The North China Plain (NCP) is one of the most important regions for food production in China, with its agricultural system being significantly affected by the undergoing climate change and vulnerable with water stress. In this study, the Vegetation Interface Processes (VIP) model is used to evaluate crop yield, water consumption (ET), and water use efficiency (WUE) of a winter wheat (Triticum aestivum L.)–summer maize (Zea mays L.) double cropping system in the NCP from 1951 to 2006. Their responses to future climate scenarios of 21st century projected by the GCM (HadCM3) with Intergovernmental Panel on Climate Change Special Report on Emission Scenario (IPCC SRES) A2 and B1 emissions are investigated. The results show a rapid enhancement of crop yield in the past 56 years, accompanying with slight increment of ET and noticeable improvement of WUE. There exist spatial patterns of crop yield stemmed mainly from soil quality and irrigation facilities. For climate change impacts, it is found that winter wheat yield will significantly increase with the maximum increment in A2 occurring in 2070s with a value of 19%, whereas the maximum in B1 being 13% in 2060s. Its ET is slightly intensified, which is less than 6%, under both A2 and B1 scenarios, giving rise to the improvement of WUE by 10% and 7% under A2 and B1 scenarios, respectively. Comparatively, summer maize yield will gently decline by 15% for A2 and 12% for B1 scenario, respectively. Its ET is obviously increasing since 2050s with over 10% relative change, leading to a lower WUE with more than 25% relative change under both scenarios in 2090s. Therefore, possible adaptation countermeasures should be developed to mitigate the negative effects of climate change for the sustainable development of agro-ecosystems in the NCP. 相似文献