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81.
Concentration–discharge relationships in the coal mined region of the New River basin and Indian Fork sub‐basin,Tennessee, USA 下载免费PDF全文
For many basins, identifying changes to water quality over time and understanding current hydrologic processes are hindered by fragmented and discontinuous water‐quality and hydrology data. In the coal mined region of the New River basin and Indian Fork sub‐basin, muted and pronounced changes, respectively, to concentration–discharge (C–Q) relationships were identified using linear regression on log‐transformed historical (1970s–1980s) and recent (2000s) water‐quality and streamflow data. Changes to C–Q relationships were related to coal mining histories and shifts in land use. Hysteresis plots of individual storms from 2007 (New River) and the fall of 2009 (Indian Fork) were used to understand current hydrologic processes in the basins. In the New River, storm magnitude was found to be closely related to the reversal of loop rotation in hysteresis plots; a peak‐flow threshold of 25 cubic meters per second (m3/s) segregates hysteresis patterns into clockwise and counterclockwise rotational groups. Small storms with peak flow less than 25 m3/s often resulted in dilution of constituent concentrations in headwater tributaries like Indian Fork and concentration of constituents downstream in the mainstem of the New River. Conceptual two or three component mixing models for the basins were used to infer the influence of water derived from spoil material on water quality. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
82.
Water temperature (Tw) is a key determinant of freshwater ecosystem status and cause for concern under a changing climate. Hence, there is growing interest in the feasibility of moderating rising Tw through management of riparian shade. The Loughborough University Temperature Network (LUTEN) is an array of 36 water and air temperature (Ta) monitoring sites in the English Peak District set‐up to explore the predictability of local Tw, given Ta, river reach, and catchment properties. Year 1 of monitoring shows that 84%–94% of variance in daily Tw is explained by Ta. However, site‐specific logistic regression parameters exhibit marked variation and dependency on upstream riparian shade. Perennial spring flows in the lower River Dove also affect regression model parameters and strongly buffer daily and seasonal mean Tw. The asymptote of the models (i.e. maximum expected Tw) is particularly sensitive to groundwater inputs. We conclude that reaches with spring flows potentially offer important thermal refuges for aquatic organisms against expected long‐term warming of rivers and should be afforded special protection. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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The recent rise in agricultural commodity prices and the expectation that high price will persist have triggered a wave of farmland expansion in regions where land resources are still available. One such region is the former Soviet Union, where the collapse of socialism caused massive agricultural abandonment and where some of these lands are now being brought back into production. Yet, the extent and spatial patterns of recultivation, and what determines these patterns, remains unclear. We examined the extent of recultivation of abandoned agricultural land in Ukraine since 2007 using a new, satellite-based recultivation map and assessed the effect of biophysical and socioeconomic determinants on recultivation patterns using boosted regression trees. We found key predictors of recultivation to be related to the suitability of land for agriculture (i.e., soil quality, temperature). Accessibility to major cities was also important, with most recultivation happening closer to settlements, but this influence varied across Ukraine. Variables related to agricultural management (fertilizer input, mechanization) and demography were negligible in explaining recultivation in our analyses. These factors suggest that recultivation patterns were primarily driven by factors related to land productivity, with recultivation focusing on the most promising areas. Given the remaining large amount of unused agricultural land in Eastern Europe and the former Soviet Union, and considering that much abandonment occurred in areas only marginally suited to agriculture, our findings provide important insights into where recultivation can be expected to happen and thus for assessing the potential socioeconomic and environmental impacts of recultivation. 相似文献
84.
A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions. 相似文献
85.
利用阿克苏及邻近地区12个气象站1980—2013年雷暴资料,以及同期高空资料,统计了各站年均雷暴日数,对发生区域雷暴天气的环流形势进行分类,归纳出各型的入型指标。通过逐步回归法,建立阿克苏及邻近地区区域雷暴概率回归预报模型,并对2013年进行试预报。结果表明:(1)阿克苏及邻近地区区域雷暴的影响系统主要分为4类:巴湖低槽型、急流型、西北气流型和温度槽型。(2)对2002—2012年5—9月(共1683 d)历史资料进行判别,满足入型条件的样本数为876 d,消空率为48%;对2013年5—9月(共153 d)历史资料进行判别,入型样本数为80 d,消空率为48%。(3)对2002—2012年5—9月所有入型样本进行回代检验,平均准确率为72.0%(平均TS评分为30.1%);对2013年5—9月所有入型样本进行试预报,平均准确率为63.2%(平均TS评分为28.2%)。 相似文献
86.
SAR图像海岸线检测的区域距离正则化几何主动轮廓模型 总被引:2,自引:0,他引:2
合成孔径雷达(SAR)卫星遥感图像可以极大地提高全国海岸线覆盖频率,然而受到海洋波浪所引起的随机海水表面粗糙度的影响,海岸目标与海水背景边界易混淆不清,因此本文提出了基于区域距离正则化几何主动轮廓模型(RDRGAC),引入距离正则项,解决重复初始化水平集函数为符号距离函数的问题,提高了算法收敛速度。此外,将区域面积项系数与SAR图像等效视数(ENL)建立非线性拟合关系,实现RDRGAC模型根据不同SAR遥感图像的自适应调整,改善海岸线自动提取精度。通过河北省北戴河和大连市金州湾SAR数据海岸线提取对比试验,验证了所提方法的有效性。 相似文献
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Mritunjay Kumar Singh R.D. Gupta Snehmani Anshuman Bhardwaj Ashwagosha Ganju 《国际地球制图》2016,31(5):506-526
The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy. 相似文献
90.
文中探讨了加权Logistic回归模型在宁芜盆地中段火山岩型铜矿预测中的应用。首先,结合研究区的成矿地质背景,提取地质体、构造、围岩蚀变三大类证据因子;其次,分析各证据因子与铜矿点之间的空间关系,认为姑山旋回、娘娘山旋回火山机构控制了本区火山岩型铜矿的空间分布,根据计算结果,选取与火山岩型铜矿密切相关的龙王山组、姑山组地层,姑山旋回粗面斑岩、娘娘山旋回二长斑岩、NW向构造1.5 km缓冲区、NE向构造1.3 km缓冲区、EW向构造4.5 km缓冲区、硅化、褐铁矿化、黄铜矿化等作为模型自变量;最后采用加权Logistic回归模型进行成矿概率计算,并结合成矿地质背景,圈定四个成矿远景区,分别为P1、P2、P3、P4,其中P1、P2、P3呈北东向展布,主要受娘娘山和姑山火山机构控制,P4为东西向分布,主要受龙王山火山机构控制,在这些预测区中,均存在已发现的铜矿体,说明预测可信度较高。 相似文献