Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Tidal effects on temperature front in the Yellow Sea

Temperature front (TF) is one of the important features in the Yellow Sea, which forms in spring, thrives in summer, and fades in autumn as thermocline declines. TF intensity ⋎S _T ⋎ is defined to describe the distribution of TF. Based on the MASNUM wave-tide-circulation coupled model, temperature distribution in the Yellow Sea was simulated with and without tidal effects. Along 36°N, distribution of TF from the simulated results are compared with the observations, and a quantitative analysis is introduced to evaluate the tidal effects on the forming and maintaining processes of the TF. Tidal mixing and the circulation structure adapting to it are the main causes of the TF. Supported by the National Basic Research Program of China (No. G1999043809) and the National Science Foundation of China (No. 49736190).     

青海省沙柳河南区有色金属矿成矿物质来源及矿床成矿模式探讨

本文简述了沙柳河南区有色金属矿床的基本特征。通过对成矿热液及成矿物质的来源与性质的研究,认为该矿床的成因类型为火山沉积—接触交代改造叠加型,进而探讨了该矿床的成矿模式。     

THE CHARACTERISTIC OF MARINE ENVIRONMENT IN LINGDINGYANG ESTUARY

1 HYDROLOGIC FEATURES Lingdingyang Estuary, located at the middle south of Guangdong Province, is a bell-shaped estuary with a north-south direction. Its area is about 2100km2. The north of Qi′ao Island and Inner-Lingding Island, and the south of Humen are grouped as Neilingdingyang Estuary, having an area of 1041km2. Affected by topography, runoff and tide, its dynamic condition is very complicated. Different water areas have different hydrologic features. The topography under …     

斑节对虾白斑综合症杆状病毒感染的实验模式

在建立斑节对虾实验室养殖模式的基础上，对野外采集的有白斑综合症病毒（WSSV）病典型症状的斑节对虾初步纯化其病毒，并进行WSSV的PCR检测，得到WSSV的感染用样品。对健康斑节对虾分别进行浸浴感染，投喂感染和注射感染。对感染死亡个体进行WSSA的PCR检测和细菌检测，证实WSSV感染性和致死性。浸浴感染、投喂感染和注射感染的感染量分别为4mL/L、0.2g/10g虾体、1/2稀释液0.05mL/10g虾体，死亡开始时间分别为16d、42h、28h，三种感染模式最终死亡率100%，从开始死亡到全部死亡延续时间分别为15d、82h、44h。     

辽宁省深部构造特征及其地质意义

本文应用了最新取得的“五统一”区域重力成果，并经过对浅表松散槽（如下辽河断陷，大岩体等）的密度亏损进行补偿改正后，求取了全省的区域重力场及其垂向二次导数，计算了莫氏面等深度图。在分析区域重力场及其垂向二次导数异常特征和莫氏面起伏特征的基础上，划分出辽宁深部构造的基本格局。从平面上探讨了深部构造与地形地势、地质构造及矿产分布的关系，从剖面上剖析了辽宁省地壳分层的宏观特征     

用遗传算法对自动控制系统数学模型寻优

探讨用遗传算法对数学模型进行优化。考虑到控制系统稳健性的要求 ,用遗传算法寻找出控制系统最佳稳定域 ,实现控制系统数学模型的寻优。阐述了用遗传算法求解问题的步骤和参数的取值 ,并用仿真实验对优化结果进行了检验。结果表明 :在控制系统数学模型的优化中 ,遗传算法具有其他算法无可比拟的优越性。     

专项气象服务经济效益的评价理论与技术

当前，由于缺乏对气象服务投入量与产出量准确而完整的统计，要对气象服务的各种经济效益作出总体评价是困难的。然而，在专项气象服务中，却不乏原始、完整而准确的资料。作者从此出发，讨论了专项气象服务经济效益评价的理论。并通过实地调查，以彭州市气象局几项专项气象服务为例探讨了评价技术。     

Evidence of climatic warming in the southern Urals region derived from borehole temperatures and meteorological data

Thirty borehole temperature–depth profiles in the central and southern Urals, Russia were scrutinized for evidence of ground surface temperature histories. We explored two inversion schemes: a simple ramp inversion in which solutions are parameterized in terms of an onset time and magnitude of change and a more sophisticated functional space inverse algorithm in which the functional form of the solution is left unspecified. To enhance and potentially identify latitudinal differences in the ground surface temperature signal, we subdivided the data into three groups based on geographic proximity and simultaneously inverted the borehole temperature–depth logs. The simultaneous inversions highlighted 13 temperature–depth logs that could not both fit a common ground surface temperature history and a priori models within reasonable bounds. Our results confirm that this is an effective way to reduce site-specific noise from an ensemble of boreholes. Each inversion scheme gives comparable results indicating locally variable warming on the order of 1°C starting between 1800 and 1900 AD. Similarly surface air temperature records from 12 nearby meteorological stations exhibit locally variable warming also on the order of 1°C of warming during the 20th century. To explore the degree to which borehole temperatures and surface air temperature (SAT) time series are responding to the same signal, we average the SAT data into the same three groups and used these averages as a forcing function at the Earth's surface to generate synthetic transient temperature profiles. Root mean square (RMS) misfits between these synthetic temperature profiles and averaged temperature–depth profiles are low, suggesting that first-order curvature in borehole temperatures and variations in SAT records are correlated.