Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach          下载免费PDF全文

Poulomi Ganguli  M. Janga Reddy 《水文研究》2014,28(19):4989-5009

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Metrics to assess how longitudinal channel network connectivity and in‐stream Atlantic salmon habitats are impacted by hydropower regulation          下载免费PDF全文

Willem B. Buddendorf  Iain A. Malcolm  Josie Geris  Mark E. Wilkinson  Chris Soulsby 《水文研究》2017,31(12):2132-2142

Habitat fragmentation in channel networks and riverine ecosystems is increasing globally due to the construction of barriers and river regulation. The resulting divergence from the natural state poses a threat to ecosystem integrity. Consequently, a trade‐off is required between the conservation of biodiversity in channel networks and socio‐economic factors including power generation, potable water supplies, fisheries, and tourism. Many of Scotland's rivers are regulated for hydropower generation but also support populations of Atlantic salmon (Salmo salar L.) that have high economic and conservation value. This paper investigates the use of connectivity metrics and weightings to assess the impact of river barriers (impoundments) associated with hydropower regulation on natural longitudinal channel connectivity for Atlantic salmon. We applied 2 different weighting approaches in the connectivity models that accounted for spatial variability in habitat quality for spawning and fry production and contrasted these models with a more traditional approach using wetted area. Assessments of habitat loss using the habitat quality weighted models contrasted with those using the less biologically relevant wetted area. This highlights the importance of including relevant ecological and hydrogeomorphic information in assessing regulation impacts on natural channel connectivity. Specifically, we highlight scenarios where losing a smaller area of productive habitat can have a larger impact on Atlantic salmon than losing a greater area of less suitable habitat. It is recommended that future channel connectivity assessments should attempt to include biologically relevant weightings, rather than relying on simpler metrics like wetted area which can produce misleading assessments of barrier impacts.  相似文献   

Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data          下载免费PDF全文

Antonio‐Juan Collados‐Lara  Eulogio Pardo‐Igúzquiza  David Pulido‐Velazquez 《水文研究》2017,31(10):1966-1982

Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources.  相似文献   

2000-2015年柴达木盆地植被覆盖度时空变化及其与环境因子的关系          下载免费PDF全文

张斯琦  陈辉  宋明华  付阳  牛慧慧  杨祎  张博雄 《干旱区地理》2019,42(5):1124-1132

基于MODIS-NDVI、DEM和气象数据，分析柴达木盆地2000—2015年植被覆盖度（FVC）时空变化特征，并与降水、温度、日照时数、相对湿度、蒸散量和海拔进行相关、偏相关或叠加分析，探讨FVC与各环境因子的关系。结果表明：FVC整体自东南向西北内陆呈半环状递减，FVC集中在20%以下，人类活动及径流等打破植被地带性规律；2000—2015年FVC明显改善，广泛分布于盆地中西部地区，2001—2002年年际变化最显著；FVC与降水、相对湿度以正相关为主，与温度关系不显著，与日照时数和蒸散量主要为负相关，降水对FVC贡献最大，温度通过影响蒸散量等间接影响FVC，而土壤蒸发对蒸散量的影响大于植物蒸腾；FVC与等高线空间分布较吻合，FVC在2 800~2 900 m和4 600~4 700 m出现两个峰值，4 700 m以上FVC迅速降低。  相似文献   

Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata     

Tingting Xu  Jay Gao  Giovanni Coco 《International journal of geographical information science》2019,33(10):1960-1983

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.  相似文献   

Assessment of flow paths and confluences for saltwater intrusion in a deltaic river network          下载免费PDF全文

Baoshan Cui  Xiaojing Shao  Zhiming Zhang 《水文研究》2015,29(20):4549-4558

Saltwater intrusion is a serious issue in estuarine deltas all over the world due to rapid urban sprawl and water shortage. Therefore, detecting the major flow paths or locations at risk of saltwater intrusion in estuarine ecosystems is important for mitigating saltwater intrusion. In this paper, we introduce a centrality index, the betweenness centrality (BC), to address this problem. Using the BC as the weighted attribute of the river network, we identify the critical confluences for saltwater intrusion and detect the preferential flow paths for saltwater intrusion through the least‐cost‐path algorithm from a graph theory approach. Moreover, we analyse the responses of the BC values of confluences calculated in the river network to salinity. Our results show that the major flow paths and critical confluences for saltwater intrusion in a deltaic river network can be represented by the least cost paths and the BC values of confluences, respectively. In addition, a significant positive correlation between the BC values of confluences and salinity is determined in the Pearl River Delta. Changes in the salinity can produce significant variation in the BC values of confluences. Therefore, freshwater can be diverted into these major flow paths and critical confluences to improve river network management under saltwater intrusion. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

京津唐地区HFMD时空变异分析与影响因子探测     

张湘雪  王丽  尹礼唱  徐成东  李霞  刘杨 《地球信息科学学报》2019,21(3):398-406

手足口病（HFMD）是一种多发于儿童的常见传染病。近年来,中国HFMD发病人数逐年上升,疾病疫情也日益受到社会广泛关注。虽已有不少相关研究,但对于探测其时空异质性及量化潜在影响因子解释力的研究仍然较少。本文采用地理探测器及贝叶斯时空层次模型,对2009-2013年京津唐地区HFMD发病率的时空异质性进行分析,并量化各影响因子及其两两交互作用对HFMD发病率的解释力。结果表明：① HFMD的相对风险存在时间异质性,其发病风险在春夏季（5-7月）达到峰值,而冬季（12-次年2月）发病风险最低;② HFMD的相对风险存在空间异质性,在经济发达的地区HFMD发病率较高;③ 影响HFMD发病率时间异质性的主要气象因子为平均温度、累积降水、相对湿度,解释力分别为0.38,0.27,0.13,且交互作用都大于独自影响的作用,如平均温度和相对湿度、平均温度和降水,平均温度和风速两两交互的解释力分别为0.43, 0.40, 0.42。通过研究京津唐地区HFMD发病率的时空异质性以及影响因子的量化状况,为本地区HFMD的预防和控制提供理论依据。  相似文献   

中国道路网引起的景观破碎格局及其对保护区的影响     

黄梦娜  马廷 《地球信息科学学报》2019,21(8):1183-1195

道路的修建往往带来景观破碎、生态系统功能受损等后果。有关道路网络的生态影响格局及其影响因素,是当前道路生态学、地理空间分析等领域共同关注的问题。本文利用2015年全国道路网络数据,采用定量空间分析方法,刻画了当前中国铺装道路所引起的陆表景观破碎的格局特征,并分析了道路网络对自然保护区的干扰及与多变量的影响关系。结果表明：① 全国铺装道路的生态影响面积占陆地面积的10%,将陆表切割成3万多个斑块,并呈现小斑块数目众多,大斑块数目较少的分布特点;同时,陆表破碎化程度呈现明显的东西分异规律,空间格局与人口分布、经济发展水平等影响因素的地理分布规律趋同;② 全国约58%的自然保护区受到道路干扰,保护区的受干扰情况存在高等级保护区受干扰弱、低等级保护区次之、国家公园受干扰程度最强等差异特征,且国家公园处于受干扰高于未设保护区域的状态;③ 主要人类活动因素与保护区受干扰程度呈正相关,保护区面积、地形因素与受干扰程度呈负相关,具有面积小、受保护等级低、位于平原地区、气候适宜等特征的保护区更易受到道路干扰,处于已经受到人类活动破坏,生态脆弱的状态。因此,中国道路建设应追求社会发展与生态保护双平衡,同时道路干扰受到自然以及人文要素的共同作用,在相关影响机制研究和生态保护政策制定中应进行综合考虑。  相似文献   

利用跨断层形变资料研究天山中段断层现今活动特征     

韩桂红  滕海涛  高歌  李桂荣  张治广 《大地测量与地球动力学》2019,39(1):72-76

利用2001年以来天山中段多个跨断层形变场地的测量资料，从断层运动方向和断层平均速率2个方面分析天山中段3条断层现今活动特征。结果表明，霍玛吐断裂呼图壁段断层的活动性质为正、逆断和左、右旋交替活动；北轮台-辛格尔断裂库尔勒段断层表现为右旋运动特征，活动性质为逆断性；妖魔山F2断裂乌鲁木齐段的断层活动性质以逆断为主。妖魔山F2断裂乌鲁木齐段断层的活动程度最高，霍玛吐断裂呼图壁段最低。霍玛吐断裂、北轮台-辛格尔断裂、妖魔山F2断裂垂直方向上基本均处于张性变化，前两者水平向处于挤压状态；断层活动速率的时间进程具有阶段性特征，各个时间段转折点有较好的匹配性。  相似文献   

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach     

Jian Zhao  Yanguo Fan  Yuxiang Mu 《Marine Geodesy》2019,42(4):344-366

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.  相似文献