Regionalization of unit hydrograph parameters: 1. Comparison of regression analysis techniques     

Y. -K. Tung  K. -C. Yeh  J. -C. Yang 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(2):145-171

Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.  相似文献   

冬春季切变类冰雹发生条件的对比分析   总被引：2，自引：4，他引：2       下载免费PDF全文

张艳玲  袁媛  张鹏  徐云 《气象科学》2004,24(3):357-360

本文以 1996年 12月 31日和 1981年 5月 1日为例 ,对冬、春季节发生在江苏的较大范围的切变类冰雹天气过程作了对比分析。结果指出 ,无论冬季或春季当高原东部有深槽东移 ,冷暖空气在江淮地区交汇 ,地面抬升系统为暖切 ,并有大气层结不稳定 (Δθse( 50 0 - 850 ) <0℃ =中心和较强的风向和风速垂直切变、85 0hPa西南急流轴、85 0hPa最大水汽通量轴线、5 0 0和 85 0hPa正涡度中心等相配置时 ,就可能导致江苏地区较大范围强对流天气的发生。  相似文献   

南昌多普勒雷达与713-C雷达降水回波产品对比分析初探     

苏涵智  应冬梅  支树林  黄祖辉 《气象与减灾研究》2004,27(1):43-45

通过对比多普勒雷达和713-C雷达在同一时间、同一站点对降水回波的探测资料,找出它们在同类产品上的差异,对完成713-C雷达观测向多普勒雷达观测的过渡,用好多普勒雷达提供参考性意见。  相似文献   

Accuracy analysis, dem generation and validation using russian tk-350 stereo-images     

Gürcan Büyüksalih  Güven Koçak  Murat Oruç  Hakan Akçin  Karsten Jacobsen 《The Photogrammetric Record》2004,19(107):200-218

TK-350 stereo-scenes of the Zonguldak testfield in the north-west of Turkey have been analysed. The imagery had a base-to-height ratio of 0·52 and covered an area of 200 km × 300 km, with each pixel representing 10 m on the ground. Control points digitised from 1:25 000 scale topographic maps were used in the test. A bundle orientation was executed using the University of Hanover program BLUH and PCI Geomatica OrthoEngine AE software packages. Tests revealed that TK-350 stereo-images can yield 3D geopositioning to an accuracy of about 10 m in planimetry and 17 m in height. A 40 m resolution digital elevation model (DEM) was generated by the PCI system and compared against a reference DEM, which was derived from digitised contour lines provided by 1:25 000 scale topographic maps. This comparison showed that accuracy depends mainly on the surface structure and the slope of the local terrain. Root mean square errors in height were found to be about 27 and 39 m outside and inside forested areas, respectively. The matched DEM demonstrated a systematic shift against the reference DEM visible as an asymmetric shift in the frequency distribution. This is perhaps caused by the presence of vegetation and buildings.  相似文献   

Severe soil erosion during a 3‐day exceptional rainfall event: combining modelling and field data for a fallow cereal field          下载免费PDF全文

Manuel López‐Vicente  Laura Quijano  Leticia Gaspar  Leticia Palazón  Ana Navas 《水文研究》2015,29(10):2358-2372

Exceptional rainfall events cause significant losses of soil, although few studies have addressed the validation of model predictions at field scale during severe erosive episodes. In this study, we evaluate the predictive ability of the enhanced Soil Erosion and Redistribution Tool (SERT‐2014) model for mapping and quantifying soil erosion during the exceptional rainfall event (~235 mm) that affected the Central Spanish Pyrenees in October 2012. The capacity of the simulation model is evaluated in a fallow cereal field (1.9 ha) at a high spatial scale (1 × 1 m). Validation was performed with field‐quantified rates of soil loss in the rills and ephemeral gullies and also with a detailed map of soil redistribution. The SERT‐2014 model was run for the six rainfall sub‐events that made up the exceptional event, simulating the different hydrological responses of soils with maximum runoff depths ranging between 40 and 1017 mm. Predicted average and maximum soil erosion was 11 and 117 Mg ha^?1 event^?1, respectively. Total soil loss and sediment yield to the La Reina gully amounted to 16.3 and 9.0 Mg event^?1. These rates are in agreement with field estimations of soil loss of 20.0 Mg event^?1. Most soil loss (86%) occurred during the first sub‐event. Although soil accumulation was overestimated in the first sub‐event because of the large amount of detached soil, the enhanced SERT‐2014 model successfully predicted the different spatial patterns and values of soil redistribution for each sub‐event. Further research should focus on stream transport capacity. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures          下载免费PDF全文

J. L. McCreight  A. G. Slater  H. P. Marshall  B. Rajagopalan 《水文研究》2014,28(3):933-957

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Modelling sediment deposition and phosphorus retention in a river floodplain          下载免费PDF全文

M. González‐Sanchis  J. Murillo  A. Cabezas  J. E. Vermaat  F. A. Comín  P. García‐Navarro 《水文研究》2015,29(3):384-394

Phosphorus (P) is one of the major limiting nutrient in many freshwater ecosystems. During the last decade, attention has been focused on the fluxes of suspended sediment and particulate P through freshwater drainage systems because of severe eutrophication effects in aquatic ecosystems. Hence, the analysis and prediction of phosphorus and sediment dynamics constitute an important element for ecological conservation and restoration of freshwater ecosystems. In that sense, the development of a suitable prediction model is justified, and the present work is devoted to the validation and application of a predictive soluble reactive phosphorus (SRP) uptake and sedimentation models, to a real riparian system of the middle Ebro river floodplain. Both models are coupled to a fully distributed two‐dimensional shallow‐water flow numerical model. The SRP uptake model is validated using data from three field experiments. The model predictions show a good accuracy for SRP concentration, where the linear regressions between measured and calculated values of the three experiments were significant (r² ≥ 0.62; p ≤ 0.05), and a Nash–Sutcliffe coefficient (E) that ranged from 0.54 to 0.62. The sedimentation model is validated using field data collected during two real flooding events within the same river reach. The comparison between calculated and measured sediment depositions showed a significant linear regression (p ≤ 0.05; r² = 0.97) and an E that ranged from 0.63 to 0.78. Subsequently, the complete model that includes flow dynamics, solute transport, SRP uptake and sedimentation is used to simulate and analyse floodplain sediment deposition, river nutrient contribution and SRP uptake. According to this analysis, the main SRP uptake process appears to be the sediment sorption. The analysis also reveals the presence of a lateral gradient of hydrological connectivity that decreases with distance from the river and controls the river matter contribution to the floodplain. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

鞍山地区东鞍山花岗岩年代学、地球化学特征及成因研究   总被引：2，自引：1，他引：1  

朱凯  刘正宏  徐仲元  王兴安 《岩石学报》2016,32(2):590-604

鞍山地区位于华北地台东北部辽宁省,区内保留有3.8~2.5Ga连续的地质记录。对位于鞍山市南侧的东鞍山花岗岩进行了SHRIMP锆石U-Pb同位素分析、白云母Ar-Ar同位素分析及岩石地球化学分析。SHRIMP测年结果为3004±7Ma,代表岩石的形成年龄,Ar-Ar测年结果为2545±16Ma,代表岩石受到构造热事件扰动的时间。岩体地化特征为富硅(Si O2=72.95%~75.37%,平均值为74.18%)、富碱(K2O+Na2O=7.05%~8.45%)、富铝(Al2O3=12.95%~15.44%),低钙(Ca O=0.13%~0.66%)。在稀土元素配分图上,曲线呈明显的右倾趋势,且有较明显的负Eu异常,重稀土分馏不明显。在微量元素洋中脊玄武岩标准化蛛网图上可以看出,东鞍山花岗岩强烈亏损Nb、P、Sr、Ti,富集大离子亲石元素Rb、K、Nd和高场强元素Th、U。岩石地球化学特征表明东鞍山花岗岩岩浆来源为壳源,残留相可能由石榴石+辉石+角闪石+斜长石组成。将鞍山-本溪地区3个3.0Ga花岗岩(东鞍山花岗岩岩体、铁架山二长花岗岩岩体以及弓长岭片麻状花岗岩)的地球化学数据进行对比,发现三者的地球化学存在较大差异,为三个独立的岩体。三个岩体最初可能发育在一个陆块之上,然后在25.5亿年左右分离开来,最后在25亿年左右再次拼贴到一起。  相似文献   

基于客观分析的多源卫星叶绿素a浓度产品融合方法研究     

施英妮  张亭禄  石立坚  胡晓华  南明星 《海洋学报》2016,38(3):82-87

本文基于Aqua/MODIS、Terra/MODIS和Envisat/MERIS多源卫星叶绿素a浓度产品,研究了客观分析融合方法,制作了西北太平洋海域(0°~50°N,100°~150°E)叶绿素a浓度融合产品,并从有效数据空间覆盖率和产品精度两个方面对融合方法进行了评价。与单传感器以及欧洲太空局发布的GSM模型业务化融合产品相比,客观分析融合产品空间覆盖率明显提高;与收集的2002-2012年间叶绿素a浓度实测数据比较,GSM模型业务化融合产品的匹配数据点为578个,偏差为-0.20 mg/m3,均方根误差为0.37 mg/m3,客观分析法融合产品的匹配数据点为1432个,偏差为-0.21 mg/m3,均方根误差为0.36 mg/m3。结果表明:本文研究的客观分析融合方法在保证融合产品精度的同时可显著提高产品的空间覆盖率,在海洋水色融合应用前景广阔。  相似文献   

Age and growth of Cape stumpnose Rhabdosargus holubi (Pisces: Sparidae) in the Eastern Cape,South Africa     

MW Farthing  NC James  WM Potts 《African Journal of Marine Science》2016,38(1):65-71

Rhabdosargus holubi is a small (maximum weight=2.4?kg) yet important fishery species in the estuaries of the south-east coast of South Africa. Little is known of its biology and specifically its growth rate, which is essential for sustainable management of the fishery. We examined and counted the opaque zones in the sectioned otoliths of 134 R. holubi to determine its age and growth parameters. The otoliths from two recaptured fish marked with oxytetracycline confirmed that one opaque zone was deposited annually. The species reached a maximum age of 18 years and growth was adequately described by a von Bertalanffy growth function of the form: L_t = 358.1 (1 – e^{?0.24(t+0.77)}) mm fork length. There were no significant differences between any of the male and female growth parameters (likelihood ratio test: p = 0.3). The growth was slow (omega index: ω = 86.56); however, despite this, the unique life history of R. holubi may provide a degree of resilience to heavy fishing pressure in estuaries.  相似文献