渤、黄海生态环境模拟的参数敏感度空间差异分析

随着海洋生态系统模型的发展，生态变量增多，众多生物过程参数量值的确定成为制约生态环境模拟的瓶颈问题，生态系统结构区域性要求模型中的生态参数具有区域差异。为探究不同海区的关键参数及参数敏感度的空间差异，本研究在渤、黄海建立了ROMS-CoSiNE物理–生物耦合的高分辨率生态系统模型，并对13种生态参数的敏感度空间分布进行分析。结果表明:南黄海中部与渤海及近岸海域的敏感度差异较大。渤海敏感度最大的参数为决定光合速率的浮游植物P-I曲线初始斜率，其次为浮游动物捕食半饱和常数和浮游动物最大捕食率。而南黄海中部敏感度最大的参数为浮游动物最大捕食率，其次为浮游植物死亡率和浮游植物P-I曲线初始斜率。结合敏感度分布及浮游植物生物量收支得出，渤海水体透明度较南黄海偏低、浮游植物生长光限制较强，是引起浮游植物P-I曲线初始斜率敏感度在渤海高于黄海的主要原因。浮游动物最大捕食率及浮游植物死亡率的敏感度空间差异，受渤、黄海浮游植物生物量差异的影响，与生态系统中的高度非线性特征有关。     

风和径流量对长江口缺氧影响的数值模拟

受自然和人类活动的影响，海洋缺氧现象日益严重，威胁着海洋生态环境，海洋缺氧问题已经引起了人们的广泛关注。本文应用区域海洋模式并耦合生态模式，对东海的生态系统进行了数值模拟和分析研究。与观测数据比较显示，该模型能较好地模拟长江口外生态变量的分布趋势。另外本文通过设置不同敏感性实验，探讨风和径流量对长江口底层缺氧现象的影响，结果分析表明，风和径流量对长江口外缺氧区的形成有显著的影响。径流量变化虽然对长江口外缺氧区的季节变化影响并不显著，但是对缺氧区域面积却存在显著的影响。径流量增加，水体层化增强，表层叶绿素浓度增加，最终导致缺氧区域范围扩展；径流量减小，水体层化减弱，表层叶绿素浓度减小，缺氧区域范围缩小。风向和风速的改变不仅影响长江口外缺氧区的季节变化，还影响缺氧区域面积。     

Study of the flood control scheduling scheme for the Three Gorges Reservoir in a catastrophic flood

The Three Gorges Project is the world's largest water conservancy project. According to the design standards for the 1,000‐year flood, flood diversion areas in the Jingjiang reach of the Yangtze River must be utilized to ensure the safety of the Jingjiang area and the city of Wuhan. However, once these areas are used, the economic and life loss in these areas may be very great. Therefore, it is vital to reduce this loss by developing a scheme that reduces the use of the flood diversion areas through flood regulation by the Three Gorges Reservoir (TGR), under the premise of ensuring the safety of the Three Gorges Dam. For a 1,000‐year flood on the basis of a highly destructive flood in 1954, this paper evaluates scheduling schemes in which flood diversion areas are or are not used. The schemes are simulated based on 2.5‐m resolution reservoir topography and an optimized model of dynamic capacity flood regulation. The simulation results show the following. (a) In accord with the normal flood‐control regulation discharge, the maximum water level above the dam should be not more than 175 m, which ensures the safety of the dam and reservoir area. However, it is necessary to utilize the flood diversion areas within the Jingjiang area, and flood discharge can reach 2.81 billion m³. (b) In the case of relying on the TGR to impound floodwaters independently rather than using the flood diversion areas, the maximum water level above the dam reaches 177.35 m, which is less than the flood check level of 180.4 m to ensure the safety of the Three Gorges Dam. The average increase of the TGR water level in the Chongqing area is not more than 0.11 m, which indicates no significant effect on the upstream reservoir area. Comparing the various scheduling schemes, when the flood diversion areas are not used, it is believed that the TGR can execute safe flood control for a 1,000‐year flood, thereby greatly reducing flood damage.     

海水中铯-137的γ能谱测量不确定度评估

为科学评价测量结果的可靠性，对海水中137Cs γ能谱分析方法的不确定度进行了评估。根据《化学分析中不确定度的评估指南》，分析不确定度的来源并逐一对各不确定度分量进行了量化，最终计算了合成相对标准不确定度。结果表明，影响海水中137Cs γ能谱测量不确定度的因素分别为样品源137Cs峰区计数、标准源活度、取样体积、化学回收率、本底137Cs峰区计数及标准源137Cs峰区计数，其中样品源137Cs峰区计数的不确定度贡献最为突出。对于137Cs活度浓度为1.28 mBq/L的海水样品，其合成相对标准不确定度为9.78%。     

Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

Dynamic modelling of retrogressive landslides with emphasis on the role of clay sensitivity

This paper presents a detailed numerical study of the retrogressive failure of landslides in sensitive clays. The dynamic modelling of the landslides is carried out using a novel continuum approach, the particle finite element method, complemented with an elastoviscoplastic constitutive model. The multiwedge failure mode in the collapse is captured successfully, and the multiple retrogressive failures that have been widely observed in landslides in sensitive clays are reproduced with the failure mechanism, the kinematics, and the deposition being discussed in detail. Special attention has been paid to the role of the clay sensitivity on each retrogressive failure as well as on the final retrogression distance and the final run‐out distance via parametric studies. Moreover, the effects of the viscosity of sensitive clays on the failure are also investigated for different clay sensitivities.     

Geophysical Signature of the Shallow Water Flow in the Deepwater Basin of the Northern South China Sea

Shallow water flow (SWF), a disastrous geohazard in the continental margin, has threatened deepwater drilling operations. Under overpressure conditions, continual flow delivering unconsolidated sands upward in the shallow layer below the seafloor may cause large and long-lasting uncontrolled flows; these flows may lead to control problems and cause well damage and foundation failure. Eruptions from over-pressured sands may result in seafloor craters, mounds, and cracks. Detailed studies of 2D/3D seismic data from a slope basin of the South China Sea (SCS) indicated the potential presence of SWF. It is commonly characterized by lower elastic impedance, a higher Vp/Vs ratio, and a higher Poisson’s ratio than that for the surrounding sediments. Analysis of geological data indicated the SWF zone originated from a deepwater channel system with gas bearing over-pressured fluid flow and a high sedimentation rate. We proposed a fluid flow model for SWF that clearly identifies its stress and pressure changes. The rupture of previous SWF zones caused the fluid flow that occurred in the Baiyun Sag of the northern SCS.     

玉米素和水杨酸对雨生红球藻(Haematococcus pluvialis)生长及虾青素积累的影响

虾青素是一种具有强抗氧化活性的类胡萝卜素,而雨生红球藻是天然虾青素的主要来源。本文以雨生红球藻(Haematococcus pluvialis)为材料,研究了植物激素玉米素和水杨酸对雨生红球藻的生长、虾青素含量及相关基因表达的影响。分别添加5种浓度的玉米素或水杨酸,结果发现0.05mg/L玉米素或25mg/L水杨酸处理5d后雨生红球藻虾青素积累最多。该浓度玉米素或水杨酸可显著提高光胁迫下藻细胞密度,最高分别达到3.4×10~5cell/mL和3.0×10~5cell/mL;同时玉米素与水杨酸组中虾青素含量显著上升,分别为1.7%和1.6%,比对照组分别增加29.2%和25.6%。玉米素缓解了高光逆境条件下光合作用基因——Rubisco大亚基(rbcL)及其活化酶(rca)、碳酸酐酶(ca)的下调表达,但对虾青素合成途径β-胡萝卜素酮化酶基因(bkt)的表达量没有显著影响;而水杨酸则相反,在胁迫后期不能缓解光合作用相关基因的下调表达,但可使bkt基因显著上调,最高可达对照组的2.5倍。本研究首次比较了玉米素和水杨酸对雨生红球藻生长和虾青素积累的影响,发现玉米素比水杨酸具有更好的促进雨生红球藻中虾青素积累的效果。     

Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

Preprocessing photospheric vector magnetograms for nonlinear force-free field extrapolation of the global corona

Nonlinear force-free magnetic field(NLFFF) extrapolation based on the observed photospheric magnetic field is the most important method to obtain the coronal magnetic field nowadays.However, raw photospheric magnetograms contain magnetic forces and small-scale noises, and fail to be consistent with the force-free assumption of NLFFF models. The procedure for removing the forces and noises in observed data is called preprocessing. In this paper, we extend the preprocessing code of Jiang Feng to spherical coordinates for a full sphere. We first smooth the observed data with Gaussian smoothing, and then split the smoothed magnetic field into a potential field and a non-potential field.The potential part is computed by a numerical potential field model, and the non-potential part is preprocessed using an optimization method to minimize the magnetic forces and magnetic torques. Applying the code to synoptic charts of the vector magnetic field from SDO/HMI, we find it can effectively reduce the noises and forces, and improve the quality of data for a better input which will be used for NLFFF extrapolations applied to the global corona.