Seasonal connections between meteoric water and streamflow generation along a mountain headwater stream

In snowmelt-driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ¹⁸O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivity or more prolonged mixing, especially in high-relief mountainous catchments. We characterized δ¹⁸O and δD values in stream water along an elevational gradient in a mountain headwater catchment in southwestern Montana. Stream water isotopic compositions related most strongly to elevation between February and March, exhibiting higher δ¹⁸O and δD values with decreasing elevation. These elevational isotopic lapse rates likely reflect increased connection between stream flow and proximal snow-derived water sources heavily subject to elevational isotopic effects. These patterns disappeared during summer sampling, when consistently lower δ¹⁸O and δD values of stream water reflected contributions from snowmelt or colder rainfall, despite much higher δ¹⁸O and δD values expected in warmer seasonal rainfall. The consistently low isotopic values and absence of a trend with elevation during summer suggest lower connectivity between summer precipitation and stream flow generation as a consequence of drier soils and greater transpiration. As further evidence of intermittent seasonal connectivity between the stream and adjacent groundwaters, we observed a late-winter flush of nitrate into the stream at higher elevations, consistent with increased connection to accumulating mineralized nitrogen in riparian wetlands. This pattern was distinct from mid-summer patterns of nitrate loading at lower elevations that suggested heightened human recreational activity along the stream corridor. These observations provide insights linking stream flow generation and seasonal water storage in high elevation mountainous watersheds. Greater understanding of the connections between surface water, soil water and groundwater in these environments will help predict how the quality and quantity of mountain runoff will respond to changing climate and allow better informed water management decisions.     

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.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

A modified numerical model for moisture-salt transport in unsaturated sandy soil under evaporation

Soil salinization, caused by salt migration and accumulation underneath the soil surface, will corrode structures. To analyze the moisture-salt migration and salt precipitation in soil under evaporation conditions, a mathematical model consisting of a series of theoretical equations is briefly presented. The filling effect of precipitated salts on tortuosity factor and evaporation rate are taken into account in relevant equations. Besides, a transition equation to link the solute transport equation before and after salt precipitation is proposed. Meanwhile, a new relative humidity equation deduced from Pitzer ions model is used to modify the vapor transport flux equation. The results show that the calculated values are in good agreement with the published experimental data, especially for the simulation of volume water content and evaporation rate of Toyoura sand, which confirm the reliability and applicability of the proposed model.     

A CASE STUDY ON CONCENTRATION AND DECENTRALIZATION：BEHAVIOR AND DYNAMIC MECHANISM OF SPATIAL EVOLUTION IN METROPOLITAN AREA，NANJING，CHINA

In rapid socio-economic development,the process of concentration and dispersal of various elements tends to be more dramatic,tremendously influencing the shaping and transformation of the space in metropolitan area.Survey of spatial concentration and decentralization has thus become a basic method in examining metropolitan spatial evolution.In this research,three elements were selected as the essential indicators of the process:demographic density distribu-tion,employment density distribution and business office location.Performance of these elements in Nanjing City was exam-ined historically.As Nanjing City could be regarded as a representative of metropolitan areas in China,its situation large-ly suggestes the general characteristics in similar areas of China.Hence based on the investigation of Nanjing City,four general implications were highlighted.First ,metropolitan areas in China are in a violent process and shift of spatial concentra-tion and decentralization.Second,from now to at least the near future,concentration will continue to be the central fea-ture.Third,the landscape of metropolitan areas basically exhibits a dual structure character.The gap in environmental and ecological qualities among different districts will continue for a long time.Fourth,Central Business District (CBD) is playing an important role in helping to convert the traditionally single-centered city structure into a polycentric one.     

地壳对海洋潮汐的响应

应用三维动态有限元方法研究了中国北部地区的地壳对邻近的渤海与黄海海平面变化的响应。虽然此应力场过于微弱不足以引发地震，但发现应力集中的位置及应力场变化较大的位置恰好与某些现代地震的震中一致。这一结果表明研究地壳对广泛分布的载荷的响应对研究区域地震构造是有帮助的。     

MATLAB在运用系统建模处理南海气象数据过程中应用

介绍了MATLAB语言特点和系统建模方法的基本理论.根据南海气象数据的实际建模处理过程,给出了建模的详细步骤及其MATLAB实现过程以及MATLABTM的主要实现程序.试验讨论和结果表明利用MATLAB语言可以方便地对南海气象数据用系统建模方法进行建模和处理,MATLAB在运用系统建模法处理南海气象数据方面具有明显的优越性.     

小波分析理论在GPS技术中的应用

在GPS数据处理中 ,存在着误差影响、影响波的干扰、周跳和数据量大等问题。误差影响和影响波的干扰实质是在接收卫星信号时受到其它因素的影响 ;周跳是由于卫星信号的失锁而造成信号的不连续 ;数据量大是因为GPS观测需要采样间隔小又连续观测所致。由于小波理论具有时频分析、波形分解、特征提取和快速小波变换等特性 ,应用小波变换和波形分解可以解决误差影响和影响波的干扰的问题 ;应用特征提取可以解决周跳检测问题 ;应用快速小波变换可进行数据压缩     

地震前后垂直形变场动态演化的量化指标

提出一种表达垂直形变场动态演化过程的量化指标——区域应变率、应变集中度。在此基础上，对南北地震带各水准监测区近30年的垂直形变资料进行了实际计算．并结合具体震例进行了对比研究。结果表明：量化指标在一定程度上能够反映地震前后形变场的动态演化过程和地壳运动状态，对地震的中长期预报有一定的积极意义。