Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan          下载免费PDF全文

Meng‐Jung Tsai  Robert J. Abrahart  Nick J. Mount  Fi‐John Chang 《水文研究》2014,28(3):1055-1070

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

River discharge,land use change,and surface water quality in the Xiangjiang River,China          下载免费PDF全文

Zhao Zhang  Yi Chen  Pin Wang  Jiabing Shuai  Fulu Tao  Peijun Shi 《水文研究》2014,28(13):4130-4140

To compare the impacts of river discharge on the surface water quality of the Xiangjiang River in China, 12 surface water quality parameters recorded at 31 sampling sites from January 1998 to December 2008 along the river and its main tributaries were analyzed. Significantly higher concentrations of total nitrogen, ammoniacal nitrogen, and total phosphorus, and biochemical oxygen demand were observed during low‐flow periods than during high‐flow periods, implying a higher risk to local residents drinking untreated water during low‐flow periods. Pollution indexes, including the inorganic pollution index and integrated pollution index (IPI), were negatively related to impervious surface area (ISA) and cropland area (CLA) when ISA (CLA) was less than 160 (3000) km². However, the relationship was positive when ISA (CLA) was larger than 160 (3000) km², which provided a reasonable explanation for the observed spatial patterns of water quality. Distinct increasing temporal trends for two kinds of pollution indexes were also found. The annual ISA was significantly related to the rapid degradation of water quality from 1998 to 2008, with correlation coefficient (r) values of 0.816 (p = 0.002) and 0.711 (p = 0.014) for the organic pollution index (OPI) and IPI, respectively. However, annual rainfall was negatively correlated with the two indexes with r values of 0.785 (p = 0.002) and 0.448 (p = 0.093) for OPI and IPI, respectively. Our study highlights that decision makers should be more aware of recent increases in the pollution of the Xiangjiang River, especially at downriver sites and during low‐flow periods. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

A rainfall‐runoff model parameterized from GIS and runoff data          下载免费PDF全文

Thomas Skaugen  Christian Onof 《水文研究》2014,28(15):4529-4542

A guiding principle in hydrological modelling should be to keep the number of calibration parameters to a minimum. A reduced number of parameters to be calibrated, while maintaining the accuracy and detail required by modern hydrological models, will reduce parameter and model structure uncertainty and improve model diagnostics. In this study, the dynamics of runoff are derived from the distribution of distances from points in the catchments to the nearest stream. This distribution is unique for each catchment and can be determined from a geographical information system. The distribution of distances, will, when a celerity of (subsurface) flow is introduced, provide a distribution of travel times, or a unit hydrograph (UH). For spatially varying levels of saturation deficit, we have different celerities and, hence, different UHs. Runoff is derived from the superposition of the different UHs. This study shows how celerities can be estimated if we assume that recession events represent the combined UHs for different levels of saturation deficit. A new soil moisture routine which estimates saturated and unsaturated volumes of subsurface water and with only one parameter to calibrate is included in the new model. The performance of the new model is compared with that of the Swedish HBV model and is found to perform equally well for eight Norwegian catchments although the number of parameters to be calibrated in the module concerning soil moisture and runoff dynamics is reduced from seven in the HBV model to one in the new model. It is also shown that the new model has a more realistic representation of the subsurface hydrology. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

一种海洋混合层深度的智能识别方法研究     

张康  郭双喜  黄鹏起  屈玲  鲁远征  岑显荣  于璐莎  周伟东  周生启 《热带海洋学报》2019,38(5):32-41

文章提出了一种识别混合层深度的人工智能方法。该方法在温度(密度)与压强(或深度)间建立线性模型, 并且将其系数和方差做成一组表征廓线特征的统计量。初始时为模型设定一个主观的先验分布, 在一个自海表向下移动的窗口内通过贝叶斯链式法则和最小描述长度原理学习新数据, 得到系数均值的最大后验概率估计。用F-检验识别系数发生突变的位置, 以此确定混合层的存在性及其深度。通过2017年2月太平洋海域的地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography, ARGO)数据进行测试, 并且以质量因子(Quality Index, QI)值作为判断识别混合层深度结果准确性的依据, 发现该方法相比于梯度法、阈值法、混合法、相对变化法、最大角度法和最优线性插值法在识别结果上具备更大的QI值。表明该方法能够准确识别混合层深度。  相似文献   

库岸斜坡失稳及其涌浪灾害风险分析          下载免费PDF全文

罗冠枝  高文伟  王国卫  蒋明光  陈全明 《中国地质灾害与防治学报》2020,31(1):8-17

库岸斜坡失稳及其引发涌浪问题是库岸斜坡灾害的重要研究部分,开展库岸斜坡失稳及其涌浪灾害风险分析研究对指导库岸斜坡防灾减灾具有重要意义。以湖南省麻阳县大水冲水库滑坡为例,探讨库岸斜坡失稳引发涌浪灾害的分析方法,采用Geostudio软件进行10年和50年一遇5日累积降雨的滑坡稳定性模拟分析,绘制滑坡影响范围内建筑物风险变化图和室内人员风险变化图。总结了在最危险工况下,大水冲水库滑坡总经济风险为249.3万元,室内人员的风险值达到27.8,并有产生翻坝的可能,但对沟口居民和水库坝体破坏的风险低。  相似文献   

中国石化枯竭气藏型储气库注采技术及发展建议   总被引：1，自引：0，他引：1  

何祖清 《地质与勘探》2020,56(3):605-613

经长输管线输送的天然气注入到地下空间而形成的人工气藏称为地下储气库。国内外现有储气库大多数是枯竭气藏型地下储气库。中国石化储气库建设起步较晚,基础较为薄弱,同时与国内外已建成储气库相比,中石化储气库建设面临的地质条件和注采工况也较为复杂。以中国在建最大储气库项目中原文23储气库为例,其复杂地质条件以及面临的"快瞬变非稳态增压"注采难题需要进行专门研究。分析了目前中石化枯竭型气藏储气库建库现状,提出了建库技术挑战,总结了现阶段取得的注采关键技术研究成果,通过分析中国石化枯竭气藏型储气库注采技术研究现状和最新进展,提出了国产化技术完善、智能化注采营运、一体化模拟实验室的建设等方面的发展建议和要求,为持续加强规模化储气库群建设的支持提供参考。  相似文献   

台风暴雨型浅层滑坡失稳机理研究   总被引：1，自引：0，他引：1  

闫金凯  黄俊宝  李海龙  陈亮  张艳玲 《地质力学学报》2020,26(4):481-491

针对台风暴雨耦合作用下浅层滑坡的失稳机理进行研究。在总结福建台风暴雨型滑坡灾害特征的基础上，提出风荷载对斜坡变形失稳的影响机理是通过植被造成坡体开裂，从而影响坡体的入渗规律。应用GeoStudio软件计算台风暴雨入渗条件下裂隙坡体中暂态非饱和渗流场的变化，以及对斜坡稳定性的影响。计算结果表明:裂隙坡体由于在裂隙处形成集中入渗点，雨水的入渗速度大于无裂隙的坡体，坡体达到饱和状态所需要的时间大为缩短。裂隙深度、间距对滑坡稳定系数的影响较大，裂隙深度越大、间距越小，在相同的降雨条件下滑坡的稳定系数越小，滑坡失稳需要的降雨时长越短。裂隙宽度对滑坡稳定性的影响相对较小。   相似文献   

一例异育银鲫(Carassius auratus gibelio)暴发性出血病病原分析     

袁雪梅  潘晓艺  郝贵杰  刘莉  吕孙建  蔺凌云  沈锦玉 《海洋与湖沼》2019,50(4):913-920

2016年6月,江苏某异育银鲫(Carassius auratus gibelio)养殖场暴发一种传染性急性出血病,造成养殖银鲫大量死亡。为分析此次疾病病因及流行规律,本研究从发病养殖场采集患出血病的异育银鲫,从细菌、病毒及寄生虫三个方面对病原进行了分析。采用病原菌分离、组织病理学观察、超薄切片电镜观察、病毒核酸分析、回感实验等对病原进行鉴定。结果显示从发病鲫鱼体内分离到病毒一株,未发现寄生虫及细菌感染。经测序及序列分析,该病毒为鲤疱疹病毒Ⅱ型(Cyprinid herpesvirus2,CyHV-2)病毒,组织病理学观察结果显示患病鱼的鳃和肾脏有明显病变,电镜下可观察到病鱼脾脏组织有带囊膜的球形病毒,囊膜直径约为170—200nm,病毒衣壳直径约为110—120nm,核心直径约为60nm,用组织匀浆感染鲫鱼囊胚细胞系(CGB)可稳定地观察到典型的细胞病变,用患病鱼组织匀浆液人工感染异育银鲫的死亡率高达100%,荧光定量PCR检测到该病毒可感染多器官,其中以脾脏中病毒含量最高,其次是脑,肝脏中最少。本研究可为CyHV-2的诊断防控及疫苗研制提供资料。  相似文献   

Inference of in situ stress from thermoporoelastic borehole breakouts based on artificial neural network     

Hua Zhang  Shunde Yin 《国际地质力学数值与分析法杂志》2019,43(16):2493-2511

The determination of in situ stresses is very important in petroleum engineering. Hydraulic fracturing is a widely accepted technique for the determination of in situ stresses nowadays. Unfortunately, the hydraulic fracturing test is time-consuming and expensive. Taking advantage of the shape of borehole breakouts measured from widely available caliper and image logs to determine in situ stress in petroleum engineering is highly attractive. By finite element modeling of borehole breakouts considering thermoporoelasticity, the authors simulate the process of borehole breakouts in terms of initiation, development, and stabilization under Mogi-Coulomb criterion and end up with the shape of borehole breakouts. Artificial neural network provides such a tool to establish the relationship between in situ stress and shape of borehole breakouts, which can be used to determine in situ stress based on different shape of borehole breakouts by inverse analysis. In this paper, two steps are taken to determine in situ stress by inverse analysis. First, sets of finite element modeling provide sets of data on in situ stress and borehole breakout measures considering the influence of drilling fluid temperature and pore pressure, which will be used to train an artificial neural network that can eventually represent the relationship between the in situ stress and borehole breakout measures. Second, for a given measure of borehole breakouts in a certain drilling fluid temperature, the trained artificial neural network will be used to predict the corresponding in situ stress. Results of numerical experiments show that the inverse analysis based on finite element modeling of borehole breakouts and artificial neural network is a promising method to determine in situ stress.  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