A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

High-frequency monitoring of hydrological and biogeochemical fluxes in forested catchments of southern Chile

The variability of rainfall-dependent streamflow at catchment scale modulates many ecosystem processes in wet temperate forests. Runoff in small mountain catchments is characterized by a quick response to rainfall pulses which affects biogeochemical fluxes to all downstream systems. In wet-temperate climates, water erosion is the most important natural factor driving downstream soil and nutrient losses from upland ecosystems. Most hydrochemical studies have focused on water flux measurements at hourly scales, along with weekly or monthly samples for water chemistry. Here, we assessed how water and element flows from broad-leaved, evergreen forested catchments in southwestern South America, are influenced by different successional stages, quantifying runoff, sediment transport and nutrient fluxes during hourly rainfall events of different intensities. Hydrograph comparisons among different successional stages indicated that forested catchments differed in their responses to high intensity rainfall, with greater runoff in areas covered by secondary forests (SF), compared to old-growth forest cover (OG) and dense scrub vegetation (CH). Further, throughfall water was greatly nutrient enriched for all forest types. Suspended sediment loads varied between successional stages. SF catchments exported 455 kg of sediments per ha, followed by OG with 91 kg/ha and CH with 14 kg/ha, corresponding to 11 rainfall events measured from December 2013 to April 2014. Total nitrogen (TN) and phosphorus (TP) concentrations in stream water also varied with rainfall intensity. In seven rainfall events sampled during the study period, CH catchments exported less nutrients (46 kg/ha TN and 7 kg/ha TP) than SF catchments (718 kg/ha TN and 107 kg/ha TP), while OG catchments exported intermediate sediment loads (201 kg/ha TN and 23 kg/ha TP). Further, we found significant effects of successional stage attributes (vegetation structure and soil physical properties) and catchment morphometry on runoff and sediment concentrations, and greater nutrients retention in OG and CH catchments. We conclude that in these southern hemisphere, broad-leaved evergreen temperate forests, hydrological processes are driven by multiple interacting phenomena, including climate, vegetation, soils, topography, and disturbance history.     

The isotopic signature of monsoon conditions,cloud modes,and rainfall type

This work provides a comprehensive physically based framework for the interpretation of the north Australian rainfall stable isotope record (δ¹⁸O and δ²H). Until now, interpretations mainly relied on statistical relationships between rainfall amount and isotopic values on monthly timescales. Here, we use multiseason daily rainfall stable isotope and high resolution (10 min) ground‐based C‐band polarimetric radar data and show that the five weather types (monsoon regimes) that constitute the Australian wet season each have a characteristic isotope ratio. The data suggest that this is not only due to changes in regional rainfall amount during these regimes but, more importantly, is due to different rain and cloud types that are associated with the large scale circulation regimes. Negative (positive) isotope anomalies occurred when stratiform rainfall fractions were large (small) and the horizontal extent of raining areas were largest (smallest). Intense, yet isolated, convective conditions were associated with enriched isotope values whereas more depleted isotope values were observed when convection was widespread but less intense. This means that isotopic proxy records may record the frequency of which these typical wet season regimes occur. Positive anomalies in paleoclimatic records are most likely associated with periods where continental convection dominates and convection is sea‐breeze forced. Negative anomalies may be interpreted as periods when the monsoon trough is active, convection is of the oceanic type, less electric, and stratiform areas are wide spread. This connection between variability of rainfall isotope anomalies and the intrinsic properties of convection and its large‐scale environment has important implications for all fields of research that use rainfall stable isotopes.     

CHANGE OF NUTRIENT IMPORT AND EXPORT IN PROCESS OF RAINFALL IN AILAO MOUNTAIN OF YUNNAN PROVINCE

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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.     

Multiple stellar populations in the Sextans dwarf spheroidal galaxy?

We present wide-field     multiband ( BVI ) CCD photometry (down to     of the very low surface brightness dwarf spheroidal galaxy Sextans. In the derived colour–magnitude diagrams we find evidence suggesting the presence of multiple stellar populations in this dwarf spheroidal. In particular, we discover (i) a blue horizontal branch tail that appears to lie on a brighter sequence with respect to the prominent red horizontal branch and the RR Lyrae stars, very similar to what was found by Majewski et al. for the Sculptor dwarf spheroidal, (ii) hints of a bimodal distribution in colour of the red giant branch stars, (iii) a double red giant branch bump. All of these features suggest that (at least) two components are present in the old stellar population of this galaxy: the main one with     and a minor component around     . The similarity to the Sculptor case may indicate that multiple star formation episodes are also common in the most nearby dwarf spheroidals that ceased their star formation activity at very early epochs.     

Extreme Rainfall Events and Associated Natural Hazards in Alaknanda Valley, Indian Himalayan Region

Introduction The Himalaya is considered to be the youngest mountains on the earth, and is tectonically very active, and hence inherently (geologically) vulnerable to hazards. Extreme rainfall events, landslides, debris flows, torrents and flash floods due…     

松辽盆地三肇凹陷葡萄花油层成藏模式初探

运用源控含油气系统理论与综合分析技术,按成藏“层次分析”方法,通过对生、储、盖、圈(闭)静态要素及其内生、排、运、聚、散(失)动态过程的综合研究,对松辽盆地中央坳陷的三肇凹陷葡萄花油层成藏条件进行探讨,提出了以次级凹陷为中心、不同类型的油气聚集带紧邻并围绕次级凹陷最低部位呈环带状分布的大型凹陷内成藏模式,并进一步提出永乐次级凹陷中心及其三级聚油环带及徐家围子次级凹陷以西为"网式"运聚特征;在凹陷级成藏模式的指导下,通过对大面积密井网开发区综合解剖,提出三级构造带中单个的局部构造圈闭(群)、单个的(局部构造——)岩性圈闭(群)控油和成藏规律,为认识本区基本控油单元、油水分布规律、油气勘探及扩大新探区提供重要的理论依据。     

强降雨条件下土质边坡瞬态稳定性分析

基于实际降雨气象资料,设计了单峰降雨和8个不同时间间隔的双峰降雨计算方案,利用非饱和土力学理论,对边坡的瞬态稳定性进行了计算和分析,研究了水分在坡体内的运移对边坡稳定性的时间空间影响效应,同时考察了降雨入渗造成的土性渗透特性的改变。分析发现：一次降雨的影响历时约12 d,降雨后约0.5 d该类土质边坡最危险;不同时间间隔的两次降雨对边坡稳定的影响比单峰降雨的最小安全系数滞后约0.3 d～0.8 d,影响历时基本保持不变;土体物理力学性质、边坡最危险滑动面及其对应的安全系数随水分在坡体内渗透运移而变化。