天津市地下水开采对地面沉降影响的多元回归分析

地下水的过量开采是天津市引起地面沉降的主要原因。因此天津市提出了“压缩地下水开采量”、“地下水人工回灌”、“调整地下水开采层次”等控制地面沉降的3大技术措施。经过多年的努力,控制地面沉降效果明显。如何解决地下水开发与控制地面沉降的关系,更好的贯彻这3大技术措施,是该文编写的初衷。即在开采同样地下水量的情况下,如何使地面沉降量最小;或在地面沉降量容许的情况下,如何开采最大量的地下水。压缩地下水开采量是治理地面沉降的根本措施,亦即如何压缩采水量或调整开采层次会达到最好效果。论文对天津市某区各个地下水开采层的多年累计开采量、累计沉降量进行数据统计分析,建立了该地区累计沉降量及各个地下水开采层的多元相关方程。在此基础上,分析了各个地下水开采层对地面沉降影响的相关程度。以此为该区控制地面沉降的提供依据。     

Regression‐based approach to low flow prediction in the Maryland Piedmont region under joint climate and land use change

We examine the low flow records for six urbanized watersheds in the Maryland Piedmont region and develop regression equations to predict annual minimum low flow events. The effects of both future climate (based on precipitation and temperature projections from two climate models: Hadley and the Canadian Climate Centre (CCC)) and land use change are incorporated to illustrate possible future trends in low flows. A regression modelling approach is pursued to predict the minimum annual 7‐day low flow estimates for the proposed future scenarios. A regional regression model was calibrated with between 10 and 50 years of daily precipitation, daily average temperature, annual imperviousness, and the daily observed flow time‐series across six watersheds. Future simulations based on a 55 km² urbanizing watershed just north of Washington, DC, were performed. When land use and climate change were employed singly, the former predicted no trends in low flows and the latter predicted significant increasing trends under Hadley and no trends under CCC. When employed jointly, however, low flows were predicted to decrease significantly under CCC, whereas Hadley predicted no significant trends in low flows. Antecedent precipitation was the most influential predictor on low flows, followed by urbanization. Copyright © 2006 John Wiley & Sons, Ltd.     

SOFTWARE REVIEWS

AMOS—Analysis of MOment Structures . James Arbuckle CLIMATEDATA–Summary of the Day . (Version 1.10). HYDRODATA–U.S.G.S. Daily Values (Version 2.0). The MAP SETS (includes EUROPEAN MAPSET, US MAPSET and WORLD MAPSET). James Taylor     

Forced regressive shoreface sandstone from Himalayan foreland: Implications to early Himalayan tectonic evolution

Sedimentology and sequence stratigraphic analysis of the ∼ 31 Ma old marker White sandstone unit from the Subathu Sub-basin, NW Himalayan foreland, suggest it to be a forced regressive wedge (FRW) formed during the transition from the marine Subathu Formation to the continental Dagshai Formation. The FRW is bounded between the “Surf diastem” below and type 1 unconformity at the top and differs from RSME (regressive surface of marine erosion, occurring below) bounded FRWs described from other classical coastal/foreland settings. Correct identification of bounding surfaces of a FRW has an important implication to the estimation of rate of relative sea-level (RSL) fall. A faster rate of RSL fall, higher than the sedimentation rate, has been postulated for the erosion of the lower shoreface and RSME. Using the logged thickness of the Subathu/Dagshai transition zone including the White sandstone (bounded between the “Surf diastem” and unconformity), available chronology and eustatic sea-level fall (0.023 mm/year at 31 Ma), a higher RSL fall than the sedimentation rate (0.07 mm/year) has been inferred during the deposition of the White sandstone. Petrography of sandstones and their Sr and Nd isotopic compositions indicate a major provenance switch-over from dominant mafic/ultramafic to metamorphic source from White sandstone (∼ 31 Ma) onwards attesting the link between hinterland tectonics, provenance and forced regression. The provenance switch-over at 31 Ma was earlier inferred to be driven by proto-Himalayan thrust propagation in the foreland. Using a simple isostatic model, on the contrary, a mechanism of accelerated surface uplift (at a rate of > 0.10-0.15 mm/year) is suggested for both provenance change and forced regression.     

基于地理加权回归的吉林省人口城镇化动力机制分析

以吉林省各县域(市辖区)为基本单元,借助第六次人口普查和统计年鉴的相关数据,结合地理加权回归模型和空间自相关分析方法,讨论人口城镇化水平和国有动力、非国有动力、农业动力及外向动力等因素的空间相关关系,并以此解释人口城镇化分县域(市辖区)差异的影响因素。结果表明:国有动力对吉林省人口城镇化的影响作用最大,影响强度由中北部向西南、东南两个方向递减;农业动力和非国有动力分居二、三位,但差别不明显。其中农业动力的影响强度由西北向东南方向递减,非国有动力的影响强度由东南向西北递减;外向动力对人口城镇化的影响力较弱,影响强度各地区差别较大。吉林省人口城镇化未来发展应重视非国有动力的影响和农村现代化的作用;关注人口城镇化动力多元化,考虑实现错位发展和个性化发展。     

Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley,Italy

This article presents a multidisciplinary approach to landslide susceptibility mapping by means of logistic regression, artificial neural network, and geographic information system (GIS) techniques. The methodology applied in ranking slope instability developed through statistical models (conditional analysis and logistic regression), and neural network application, in order to better understand the relationship between the geological/geomorphological landforms and processes and landslide occurrence, and to increase the performance of landslide susceptibility models. The proposed experimental study concerns with a wide research project, promoted by the Tuscany Region Administration and APAT-Italian Geological Survey, aimed at defining the landslide hazard in the area of the Sheet 250 “Castelnuovo di Garfagnana” (1:50,000 scale). The study area is located in the middle part of the Serchio River basin and is characterized by high landslide susceptibility due to its geological, geomorphological, and climatic features, among the most severe in Italy. Terrain susceptibility to slope failure has been approached by means of indirect-quantitative statistical methods and neural network software application. Experimental results from different methods and the potentials and pitfalls of this methodological approach have been presented and discussed. Applying multivariate statistical analyses made it possible a better understanding of the phenomena and quantification of the relationship between the instability factors and landslide occurrence. In particular, the application of a multilayer neural network, equipped for supervised learning and error control, has improved the performance of the model. Finally, a first attempt to evaluate the classification efficiency of the multivariate models has been performed by means of the receiver operating characteristic (ROC) curves analysis approach.     

舟山近海日本囊对虾(Marsupenaeus japonicus)野生群体与露天养殖越冬群体间的形质差异

鉴于舟山沿海日本囊对虾秋苗养殖成活率显著低于春季和夏季人工养殖苗种之实际,深入开展适合于本地沿海养殖的日本囊对虾秋苗的优质亲体的选种研究显得十分必要。为此,作者采用聚类分析、主成分分析和判别分析等方法定量研究了舟山近海日本囊对虾野生群体和露天池塘越冬养成群体间的形质特征差异。结果表明:两者在本研究所涉18项形质评价指标中的相似性指数仅为11.11%,欧氏距离为4.243(P0.01);经主成分分析,提取到的5个特征值均大于1的主成分,累计贡献率达85.27%,其中第1主成分为以营养生理状况指数、额剑上缘锯齿数以及腹部肌肉发达程度为主导的体质强壮因子,第2主成分为以寻食视野与胸腔空间大小为主导的捕食运动功能因子,后3个主成分为以尾节肌肉发达程度为主导的避敌运动功能因子;采用逐步判别法,以判别贡献率较大的9项形质评价指标为自变量,所建Fisher分类函数方程组可清晰区分日本囊对虾野生群体和越冬养成群体,其中野生群体的判别准确率P1、P2分别为99.33%和96.13%,越冬养成群体的判别准确率P1、P2分别为96%和99.31%,两者综合判别准确率为97.67%。因此,日本囊对虾秋苗野生亲本形质特征的选择,应以秋苗越冬养成群体为参照。     

Estimation of suspended sediment concentration in the Saint John River using rating curves and a machine learning approach

ABSTRACT

Sedimentation in navigable waterways and harbours is of concern for many water and port managers. One potential source of variability in sedimentation is the annual sediment load of the river that empties in the harbour. The main objective of this study was to use some of the regularly monitored hydro-meteorological variables to compare estimates of hourly suspended sediment concentration in the Saint John River using a sediment rating curve and a model tree (M5?) with different combinations of predictors. Estimated suspended sediment concentrations were multiplied by measured flows to estimate suspended sediment loads. Best results were obtained using M5? with four predictors, returning an R² of 0.72 on calibration data and an R² of 0.46 on validation data. Total load was underestimated by 1.41% for the calibration period and overestimated by 2.38% for the validation period. Overall, the model tree approach is suggested for its relative ease of implementation and constant performance.

EDITOR M.C. Acreman; ASSOCIATE EDITOR B. Touaibia     

云南地区地震动衰减特性的研究

根据发生在云南地区震级大于3.0级的地震资料,采用最小二乘法对该地区的峰值加速度、加速度反应谱、峰值速度、峰值位移、均方根加速度等多个地震动参数进行回归分析。结果表明,该地区的地震动衰减关系的形态与前人的研究基本一致,但水平向差异较大;长周期部分的离散性较大,需进一步收集资料进行研究。     

Modelling real earthquake activity with reverse engineering based on evolutionary computation methods

Hazard assessment of dangerous natural phenomena is critical because of their evident results concerning loss of human life and property, especially in dense populated areas. Earthquakes are probably the most devastating phenomenon since their immediate and long-term consequences are severe. This study is focused on the earthquake data analysis in different regions of Greece, characterised by different seismicity levels. In specific, a novel model is proposed based on evolutionary computation methods, such as symbolic regression by genetic programming and genetic algorithms in order to elucidate preliminary hidden mathematical relations and patterns found in the seismological signals under study. Furthermore, the model is calibrated using reverse engineering and closes the loop from the data collection to initial hypothesis. In this way, the model formation is achieved. The presented simulation results qualitatively and quantitatively reveal some of the fundamental characteristics of each studied geographical region located in Greece that stem from its geodynamic properties.