SATELLITE MICROWAVE OBSERVATIONS OF SOIL MOISTURE VARIATIONS1

ABSTRACT: Results from studies in the Illinois-Indiana and Texas-Oklahoma areas indicate that satellite microwave observations at the 1.55 cm wavelength are responsive to relative moisture variations in the near surface layer of the soil. Because significant vegetation cover absorbs the 1.55 cm microwave emission from the soil, the target area must be predominately bare soil or low density vegetation cover for meaningful measurements to result. The 25 km resolution of the satellite sensor limits application of the microwave techniques to large areas such as watersheds or agricultural districts rather than individual fields. In general, at 1.55 cm. there is an inverse relationship between microwave brightness temperature and changes in soil moisture levels (as indicated by antecedent rainfall) in agricultural regions before the planting of crops or during the early growing season when vegetation cover is sparse. Even early season observations should be of great value in deciding on the time and type of crop planting and for initial irrigation scheduling when the root zone is still in close proximity to the surface.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Determination of explosion limits – Criterion for ignition under non-atmospheric conditions

Many industrial processes are run at non-atmospheric conditions (elevated temperatures and pressures, other oxidizers than air). To judge whether and if yes to what extent explosive gas(vapor)/air mixtures will occur or may be generated during malfunction it is necessary to know the safety characteristic data at the respective conditions. Safety characteristic data like explosion limits, are depending on pressure, temperature and the oxidizer. Most of the determination methods are standardized for ambient conditions. In order to obtain determination methods for non-atmospheric conditions, particularly for higher initial pressures, reliable ignition criteria were investigated. Ignition tests at the explosion limits were carried out for mixtures of methane, propane, n-butane, n-hexane, hydrogen, ammonia and acetone in air at initial pressures up to 20 bar. The tests have been evaluated according to different ignition criteria: visual flame propagation, temperature and pressure rising. It could be shown that flame propagation and occasionally self-sustained combustion for several seconds occurred together with remarkable temperature rise, although the pressure rise was below 3%. The results showed that the combination of a pressure rise criterion of 2% and a temperature rise criterion of 100 K seems to be a suitable ignition criterion for the determination of explosion limits and limiting oxidizer concentration at higher initial pressures and elevated temperatures. The tests were carried out within the framework of a R&D project founded by the German Ministry of Economics and Technology.     

江苏省印染污泥现状分析

对江苏省四大纺织基地进行调研,掌握了17家典型的印染企业污水处理量、污泥脱水及处置方式.同时,取样分析了印染污泥中重金属镉(Cd)、铅(Pb)、总铬(Cr)、铜(Cu)、锌(Zn)和镍(Ni)及含水率、低位热值、灰分和氯离子含量的变化情况.研究表明:采用板框压滤脱水的印染污泥平均含水率可达66.42%,便于焚烧处置;将近1/2的污泥低位热值低于污泥助燃焚烧的限值,需对污泥处理工艺和脱水方式加以改进;污泥处理过程中含氯药剂的加入使得Cl-含量波动较大,焚烧时需加强对二英的监测;17家印染企业污泥中重金属平均含量均低于江苏省城市污泥重金属平均含量,但Zn的含量却远高于评价标准.本文可为江苏省印染污泥焚烧及污染防治工作提供技术支持.     

Evaluation of Saccharomyces cerevisiae strains as probiotic agent with aflatoxin B1 adsorption ability for use in poultry feedstuffs

In this study the aflatoxin B₁ (AFB₁) removal capacity, the tolerance to salivary and gastrointestinal conditions, autoaggregation and coaggregation with pathogenic bacteria of Saccharomyces cerevisiae strains isolated from broiler feces, were evaluated. Only four of twelve isolated strains were identified as Saccharomyces cerevisiae using molecular techniques. The results obtained in AFB₁ binding studies indicated that the amount of AFB₁ removed was both strain and mycotoxin-concentration dependent. Therefore, a theoretical model was applied in order to select the most efficient strain to remove AFB₁ in a wide range of mycotoxin concentration. The results indicated that S. cerevisiae 08 and S. cerevisiae 01 strains were the most efficient microorganisms in the mycotoxin removal. Viability on simulated salivary and gastrointestinal conditions was investigated and S. cerevisiae 08 strain showed the best results, achieving 98% of total survival whereas S. cerevisiae 01 reached only 75%. Autoaggregation and coaggregation assays showed S. cerevisiae 08 as the most appropriate strain, mainly because it was the unique strain able to coaggregate with the four bacterial pathogens assayed. Consequently, S. cerevisiae 08 is the best candidate for future in vivo studies useful to prevent aflatoxicosis. Further quantitative in vitro and in vivo studies are required to evaluate the real impact of yeast-binding activity on the bioavailability of AFB₁ in poultry. However, this study could be useful in selecting efficient strains in terms of AFB₁ binding and provide an important contribution to research into microorganisms with potential probiotic effects on the host.     

南水北调中线水源地不同植被类型坡地土壤水分特征研究

为了解不同植被类型土壤水资源的变化规律，选择南水北调中线水源区宁陕县寨沟区域典型植被针阔混交林、针叶林、板栗林、灌木林、荒坡草地和坡耕地为研究对象，通过样地调查与实验分析的方法对其土壤水分物理特征及有机质含量进行测定研究。结果表明，各种有林地的土壤容重、孔隙度和有机质等理化特征均优于荒坡和坡耕地；针阔混交林土壤含水量最高，蓄水能力明显好于其它植被类型；在垂直剖面上，各种植被类型坡地土壤含水量和饱和蓄水量随土壤深度的增加基本呈递减趋势，但有林地下降幅度较大，表层含水量明显高于荒坡与坡耕地表层。由此可见，在涵养水源方面，针阔混交林最好，针叶林、板栗林与灌木林次之，荒坡与坡耕地较差。     

固定化白地霉处理高硬度及高矿化度岩溶水的研究

为了使白地霉固定化小球处理太原市地下岩溶水达到最佳絮凝效果,分别研究了白地霉菌体的最佳扩大培养条件.同时,分别选用海藻酸钠(SA)、聚乙烯醇-海藻酸钠(PVA-SA)及聚乙烯醇-海藻酸钠-明胶(PVA-SA-明胶)作为固定化剂,固定化白地霉菌体,进行絮凝性能分析.最后,确定了固定化小球处理岩溶水的最佳搅拌时间及投加量,并与六水合氯化铝、自制三元复合吸附剂及壳聚糖的5%冰醋酸溶液的絮凝效果进行了比较.结果表明,将白地霉种子培养基按3%的接种量接入白地霉扩大培养基3中进行扩大培养,可在第2d获取活性较好的大量白地霉菌体进行固定化.处理岩溶水时应选用PVA-SA-明胶固定化的白地霉小球,并在其投加量为4g·L-1、搅拌时间为60min时,对岩溶水矿化度、硬度的最大絮凝率分别为96.88%、50.00%.经与化学混凝剂絮凝性能对比发现,微生物絮凝剂具有操作简便、无二次污染、絮凝效果较好的优点.     

厌氧微网反应器处理生活污水膜污染物研究

采用涤纶网加工的微网膜组件与厌氧反应器结合构成厌氧微网生物反应器用于处理城市生活污水。在不同反应器形式和水力停留时间条件下反应器稳定运行了144 d。研究结果表明完全搅拌反应器在膜通量12 L/(m2.h)条件下跨膜压差变化较小,整体出水水质高于无搅拌式反应器。通过膜面SS含量测定、粒径和三维荧光光谱分析等方法对膜面污染物进行了系统分析。无搅拌式AnFBR随着停留时间的延长,膜面污染物的SS减少,粒径减小;完全搅拌式AnFBR膜面污染物的SS最少,粒径最小。三位荧光分析表明SMP主要有2个类蛋白质荧光峰A和B,中心位置(Ex/Em)分别位于230~235/335~350 nm及280~290/330~355 nm,EPS样品中除了峰A和峰B外还有2个峰,峰C位置(Ex/Em)在340~350/435~445 nm,与类富里酸物质有关,峰D位于420~440/465~515 nm,与类腐殖酸物质有关。     

喷灌和沟灌方式对农田土壤NH3挥发的影响

研究了2016和2017年传统灌溉（沟灌）和节水灌溉（喷灌）方式氨（NH₃）挥发的季节年际动态变化特征及其影响因素.采用通气法进行原位监测,分析了土壤温度、体积含水量、铵态氮（NH₄⁺-N）、硝态氮（NO₃^--N）以及气温降水等因素对NH₃挥发的影响.结果表明,NH₃挥发速率的峰值出现在施用氮肥后1~2周,喷灌有效降低NH₃挥发峰值,喷灌和沟灌的NH₃挥发速率峰值在2016年分别为2.67kg/（hm²·d）和11.11kg/（hm²·d）,2017年分别为2.42kg/（hm²·d）和11.73kg/（hm²·d）;马铃薯生长季NH₃挥发存在明显的季节变化,挥发高峰主要发生在7~8月,追肥期高于基肥期.2016~2017年农田土壤NH₃累积挥发量均表现为喷灌<沟灌,与沟灌相比,喷灌分别减少58.15%和43.55%.NH₃挥发速率与土壤温度呈显著正相关（P<0.05）,与体积含水量、NH₄⁺-N、NO₃^--N浓度呈极显著正相关（P<0.01）.     

基于多源遥感数据的锡尔河中下游农田土壤水分反演

机器学习结合多源遥感数据反演土壤水分含量（SMC）是目前SMC研究的热点,因较少考虑温度、蒸散等重要SMC影响因子,反演结果存在一定的不确定性。利用Sentinel-1影像、MODIS产品和SRTM数据,提取雷达后向散射系数等32个SMC影响因子,经相关分析选择27个显著的SMC影响因子（P<0.05）作为反演因子,并设计三组因子组合。这三组因子组合分别与随机森林、支持向量回归、BP神经网络三种机器学习方法结合,发现基于随机森林结合所有因子的方案,其SMC反演精度最高,该组合均方根误差RMSE为0.039 m³/m³,将该方案被用于反演2017年生长季锡尔河流域中下游平原区农田SMC。结果表明：从上部至下部SMC总体呈逐渐增加的态势,但存在显著时空差异,春季和秋季SMC较高而夏季较低。SMC差异主要由土壤质地、热量条件和地表植被状况差异引起。春季平原区下部农田SMC要高于上部,SMC的主控因子是土壤质地和地表植被状况;在夏季,土壤水分的主控因子是热量条件,农田灌溉弥补了热量条件差异对土壤水分的影响,导致空间上平原上部和下部土壤SMC空间差异不显著;秋季SMC的主控因子植被状况抵消地表温度和土壤质地差异对SMC的影响,使得秋季SMC空间差异不显著。本文采用的研究方法在一定程度上克服了因考虑SMC影响因子不足而获取更高SMC精度的限制。