基于BP神经网络的鄱阳湖水位模拟

考虑到鄱阳湖水位受流域五河与长江来水等多因素的共同作用而表现出高度非线性响应,采用典型的三层BPNN神经网络模型来模拟鄱阳湖水位与其主控因子之间的响应关系。分别将湖口、星子、都昌、棠荫和康山水位作为目标变量进行BPNN模型构建和适用性评估。结果显示：综合考虑流域五河及长江来水（汉口或九江）的BPNN水位模型,空间站点水位模拟精度（R2和Ens）可达090以上,各站点的均方根误差（RMSE）变化范围约050～10 m,若忽略长江来水的影响作用,仅将流域五河来水作为湖泊水位的主控影响因子,模型训练期与测试期的纳希效率系数（Ens）和确定性系数（R2）显著降低,且低于050,均方根误差（RMSE）也明显增大（124～288 m）,意味着综合考虑流域五河与长江来水是获取结构合理、精度保证的鄱阳湖水位模型的重要前提。同时建议针对鄱阳湖湖盆变化对水位的影响,尽可能选择一致性较好的长序列数据集来训练和测试BPNN模型。所构建的BPNN神经网络模型可进一步结合流域水文模型,用来预测气候变化与人类活动下流域径流变化对湖泊水位的潜在影响,也可作为一种有效的模型工具来回答当前鄱阳湖一些备受关注的热点问题,如定量区分流域五河与长江来水对湖泊洪枯水位的贡献分量,为湖泊洪涝灾害的防治和对策制定提供科学依据     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

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.     

Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

Structure optimization and annual performance analysis of the lens-walled compound parabolic concentrator

The primary lens-walled compound parabolic concentrator (lens-walled CPC) has a significant advantage of a larger half acceptance angle as a static solar concentrator, but it also has a drawback of a low optical efficiency. In order to overcome this drawback, in this article, series of structure parameters were investigated and compared to further improve the optical efficiency within the half acceptance angle combined with the material properties. The average optical efficiencies of the improved lens-walled CPCs could achieve more than 82% within the half acceptance angle of 35?. Experiments were adopted to verify the credibility and validity of the simulation. Moreover, annual performance of the lens-walled CPCs comparison with that of the mirror CPC for Nottingham was analyzed. Results show that the improved lens-walled CPC has a higher optical performance for actual building application.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Linking landscape development intensity within watersheds to methyl-mercury accumulation in river sediments

An indicator of the disturbance of natural systems, the landscape development intensity (LDI) index, was used to assess the potential for land-use within watersheds to influence the production/accumulation of methyl-mercury (MeHg) in river sediments. Sediment samples were collected from locations impacted by well-identified land-use types within the Mobile-Alabama River Basin in Southeastern USA. The samples were analyzed for total-Hg (THg) and MeHg concentrations and the obtained values correlated to the calculated LDI indexes of the sampled watersheds to assess the impact of prevalent land use/land cover on MeHg accumulation in sediments. The results show that unlike THg, levels of MeHg found in sediments are impacted by the LDI indexes. Overall, certain combinations of land-use types within a given watershed appear to be more conducive to MeHg accumulation than others, therefore, pointing to the possibility of targeting land-use practices as potential means for reducing MeHg accumulation in sediments, and ultimately, fish contamination.     

Effect of alginate on the aggregation kinetics of copper oxide nanoparticles (CuO NPs): bridging interaction and hetero-aggregation induced by Ca<Superscript>2+</Superscript>

The stability of CuO nanoparticles (NPs) is expected to play a key role in the environmental risk assessment of nanotoxicity in aquatic systems. In this study, the effect of alginate (model polysaccharides) on the stability of CuO NPs in various environmentally relevant ionic strength conditions was investigated by using time-resolved dynamic light scattering. Significant aggregation of CuO NPs was observed in the presence of both monovalent and divalent cations. The critical coagulation concentrations (CCC) were 54.5 and 2.9 mM for NaNO₃ and Ca(NO₃)₂, respectively. The presence of alginate slowed nano-CuO aggregation rates over the entire NaNO₃ concentration range due to the combined electrostatic and steric effect. High concentrations of Ca²⁺ (>6 mM) resulted in stronger adsorption of alginate onto CuO NPs; however, enhanced aggregation of CuO NPs occurred simultaneously under the same conditions. Spectroscopic analysis revealed that the bridging interaction of alginate with Ca²⁺ might be an important mechanism for the enhanced aggregation. Furthermore, significant coagulation of the alginate molecules was observed in solutions of high Ca²⁺ concentrations, indicating a hetero-aggregation mechanism between the alginate-covered CuO NPs and the unabsorbed alginate. These results suggested a different aggregation mechanism of NPs might co-exist in aqueous systems enriched with natural organic matter, which should be taken into consideration in future studies.

Open image in new window

Graphical abstract Hetero-aggregation mechanism of CuO nanoparticles and alginate under high concentration of Ca²⁺

     

近50a江西省旱、涝变化趋势及驱动因素研究

基于江西省5个气象站(赣县、吉安、南城、南昌、景德镇)近50 a(1961~2010年)平均气温、最高、最低平均气温、相对湿度、风速、日照时数、降雨量等逐月平均资料,计算江西省干旱侦测指数(Reconnaissance drought index,RDI),分析旱情、涝情变化趋势。同时,运用多元回归法分析主要驱动因素。研究结果表明,1961~2010年江西省年及四个季节的降雨量、平均相对湿度与RDIst值均呈现极显著的正相关关系(p0.01),而日照时数则与RDIst值呈现极显著的负相关关系(p0.01)。降雨量对江西省旱、涝变化的贡献率最大,为42%~58%;其次是平均气温和相对湿度,分别为11%~19%和7%~19%;平均风速和日照时数对江西省旱、涝变化的贡献率较小。降雨量、相对湿度的增加,日照时数的减少共同导致了1961~2010年江西省年际尺度和春季RDIst值的增加,表明江西省总体从偏旱向偏涝转变。1961~2010年江西省夏季、秋季和冬季RDIst没有明显的增长或降低趋势。