Soil erosion vulnerability under scenarios of climate land-use changes after the development of a large reservoir in a semi-arid area

Climate and land-use/cover changes (LUCC) influence soil erosion vulnerability in the semi-arid region of Alqueva, threatening the reservoir storage capacity and sustainability of the landscape. Considering the effect of these changes in the future, the purpose of this study was to investigate soil erosion scenarios using the Revised Universal Soil Loss Equation (RUSLE) model. A multi-agent system combining Markov cellular automata with multi-criteria evaluation was used to investigate LUCC scenarios according to delineated regional strategies. Forecasting scenarios indicated that the intensive agricultural area as well as the sparse and xerophytic vegetation and rainfall-runoff erosivity would increase, consequently causing the soil erosion to rise from 1.78 Mg ha^?1 to 3.65 Mg ha^?1 by 2100. A backcasting scenario was investigated by considering the application of soil conservation practices that would decrease the soil erosion considerably to an average of 2.27 Mg ha^?1. A decision support system can assist stakeholders in defining restrictive practices and developing conservation plans, contributing to control the reservoir's siltation.     

基于LabVIEW的自动配料控制系统设计

针对传统工业生产过程配料系统精度差、效率低、维修量大、人机界面不友好、成本高等问题,将总线控制技术、分时复用技术和精确称重技术相结合,设计了一套基于Labview的自动混配料控制系统。给出了系统的通讯设计,软件设计及硬件设计。现场应用结果证明,该系统能够自动、快捷、友好、精确可靠的完成配料生产。     

复杂气井套管力学分析与可靠度评价

为建立考虑地层和套管参数随机性的套管可靠度评价理论方法,以便得到复杂井况下套管传统设计安全系数与可靠指标之间的关系,提出了非均匀地应力和内压联合作用下,沿套管最大外挤力方向管壁任意位置发生屈服失效时外壁等效均匀外挤力的计算方法;建立了套管抗挤和抗内压三轴强度计算公式以及有效内压计算方法;根据套管载荷和强度影响因素统计参数以及评价过程中参数测试标准值,利用蒙特卡洛法（MC）建立了完整的套管可靠度计算和评价方法;通过实例对传统安全系数与可靠指标的对应关系进行了研究。研究结果表明:指定条件下,套管安全系数与可靠指标之间存在对应关系;利用建立的方法编制计算程序可以为传统设计法中安全系数代表的安全程度进行量化;可靠度评价方法能够为安全系数的选取提供指导。     

高温高压下煤孔隙结构的变化对瓦斯吸附特性的影响

为了研究高温高压条件下煤孔隙结构变化对瓦斯吸附特性的影响,选取九里山矿无烟煤,在压力为7 MPa、温度为40～130℃的条件下进行等温吸附实验和压汞实验。研究结果表明:煤样对甲烷的等温吸附曲线在该压力、温度条件下符合Ⅰ型吸附曲线特性,吸附规律符合Langmuir吸附模型;在压力7 MPa和温度130℃条件下,煤样的孔隙结构发生一定的变化,煤的比表面积增大、累计孔体积降低,可见孔及裂隙的数量比例增高,加强了煤样孔隙之间的连通度,导致原本吸附在煤样表面的甲烷分子大量解吸;在压力不变的情况下,随着温度的不断增高,煤的极限吸附量逐渐减小,其主要原因是样品孔隙结构的破坏和分子间作用力的变化。     

高效石油烃降解菌的筛选及其对原油污染土壤的修复

从陕北原油污染土壤中筛选出7株高效石油烃降解菌,其中黄杆菌属CC-2、不动细菌属SC-5、假单胞菌属SC-6表现出较强的石油烃降解能力。通过单因素试验和正交试验考察总石油烃(TPH)降解效果的影响因素,得出各因素对TPH降解率影响程度的大小次序为:溶液p H降解温度降解菌接种量摇床转速,且在降解菌接种量为7%(φ)、溶液p H为7、降解温度为30℃、摇床转速为150 r/min的最适处理条件下,菌株SC-6的TPH降解率可达61.23%。原油污染土壤生物修复实验结果表明:高效石油烃降解菌的投加有利于土壤TPH降解率和酶活性的提高;"菌株SC-6+营养剂"组修复处理42 d后的TPH降解率可达57.59%。     

Preliminary studies on potential remediation of acid mine drainage‐impacted soils by amendment with drinking‐water treatment residuals

Mining operations result in a wide range of environmental impacts: acid mine drainage (AMD) and acid sulfate soils being among the most common. Due to their acidic pH and high soluble metal concentrations, both AMD and acid sulfate soils can severely damage the local ecosystems. Proper post‐mining management practices are necessary to control AMD‐related environmental issues. Current AMD‐impacted soil treatment technologies are rather expensive and typically not environmentally sustainable. We conducted a 60‐day bench‐scale study to evaluate the potential of a cost‐effective and environment‐friendly technology in treating AMD‐impacted soils. The metal binding and acid‐neutralizing capacity of an industrial by‐product, drinking water treatment residuals (WTRs) were used for AMD remediation. Two types of locally generated WTRs, an aluminum‐based WTR (Al‐WTR) and a lime‐based WTR (Ca‐WTR) were used. Highly acidic AMD‐impacted soil containing very high concentrations of metals and metalloids, such as iron, nickel, and arsenic, was collected from the Tab‐Simco coal mine in Carbondale, Illinois. Soil amendment using a 1:1 Al‐ and Ca‐WTR mix, applied at 5 and 10 percent rates significantly lowered the soluble and exchangeable fractions of metals in the AMD‐impacted soil, thus lowering potential metal toxicity. Soil pH increased from an extremely acidic 2.69 to a near‐neutral 6.86 standard units over the 60‐day study period. Results from this preliminary study suggest the possibility of a successful scale‐up of this innovative, cost‐effective, and environmentally sustainable technology for remediating AMD‐impacted acid sulfate soils.     

皂素和柠檬酸复合淋洗土壤中的钍

采用振荡淋洗和土柱动态淋洗实验研究了皂素和柠檬酸复合对土壤中钍的淋洗性能。实验结果表明:将质量浓度为20 g/L的皂素与浓度为20 mmol/L的柠檬酸以体积比1∶10配制复合淋洗液对污染土壤中钍的去除效果最佳,淋洗3.0 h,钍去除率为84.98%;准一级动力学方程能更好地描述复合淋洗液对钍的淋洗动力学特征;动态淋洗实验中当复合淋洗液用量为1 600 mL时,钍的累积去除量为73.66 mg/kg;淋洗后土壤中钍的酸可提取态、氧化结合态和有机结合态含量分别减少了79.63%、38.13%和20.34%,残渣态含量变化不大;淋洗后土壤中钍的稳定性增加。     

Impacts of Changes in Precipitation Amount and Distribution on Water Resources Studied Using a Model Rainwater Harvesting System

Water supply reliability is expected to be affected by both precipitation amount and distribution changes under recent and future climate change. We compare historical (1951‐2010) changes in annual‐mean and annual‐maximum daily precipitation in the global set of station observations from Global Historical Climatology Network and climate models from the Inter‐Sectoral Impact Model Intercomparison Project (ISI‐MIP), and develop the study to 2011‐2099 for model projections under high radiative forcing scenario (RCP8.5). We develop a simple rainwater harvesting system (RWHS) model and drive it with observational and modeled precipitation. We study the changes in mean and maximum precipitation along with changes in the reliability of the model RWHS as tools to assess the impact of changes in precipitation amount and distribution on reliability of precipitation‐fed water supplies. Results show faster increase in observed maximum precipitation (10.14% per K global warming) than mean precipitation (7.64% per K), and increased reliability of the model RWHS driven by observed precipitation by an average of 0.2% per decade. The ISI‐MIP models show even faster increase in maximum precipitation compared to mean precipitation. However, they imply decreases in mean reliability, for an average 0.15% per decade. Compared to observations, climate models underestimate the increasing trends in mean and maximum precipitation and show the opposite direction of change in reliability of a model water supply system.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.