Predicting quantiles of water quality from catchment characteristics     

Danlu Guo  Shuci Liu  Dhananjay Singh  Andrew W. Western 《水文研究》2021,35(1):e13996

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.  相似文献   

A regime shift in sediment export from a coastal watershed during a record wet winter,California: Implications for landscape response to hydroclimatic extremes          下载免费PDF全文

Amy E. East  Andrew W. Stevens  Andrew C. Ritchie  Patrick L. Barnard  Pamela Campbell‐Swarzenski  Brian D. Collins  Christopher H. Conaway 《地球表面变化过程与地形》2018,43(12):2562-2577

Small, steep watersheds are prolific sediment sources from which sediment flux is highly sensitive to climatic changes. Storm intensity and frequency are widely expected to increase during the 21st century, and so assessing the response of small, steep watersheds to extreme rainfall is essential to understanding landscape response to climate change. During record winter rainfall in 2016–2017, the San Lorenzo River, coastal California, had nine flow peaks representing 2–10‐year flood magnitudes. By the third flood, fluvial suspended sediment showed a regime shift to greater and coarser sediment supply, coincident with numerous landslides in the watershed. Even with no singular catastrophic flood, these flows exported more than half as much sediment as had a 100‐year flood 35 years earlier, substantially enlarging the nearshore delta. Annual sediment load in 2017 was an order of magnitude greater than during an average‐rainfall year, and 500‐fold greater than in a recent drought. These anomalous sediment inputs are critical to the coastal littoral system, delivering enough sediment, sometimes over only a few days, to maintain beaches for several years. Future projections of megadroughts punctuated by major atmospheric‐river storm activity suggest that interannual sediment‐yield variations will become more extreme than today in the western USA, with potential consequences for coastal management, ecosystems, and water‐storage capacity. The occurrence of two years with major sediment export over the past 35 years that were not associated with extremes of the El Niño Southern Oscillation or Pacific Decadal Oscillation suggests caution in interpreting climatic signals from marine sedimentary deposits derived from small, steep, coastal watersheds, to avoid misinterpreting the frequencies of those cycles. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.  相似文献   

A multiscaling‐based intensity–duration–frequency model for extreme precipitation          下载免费PDF全文

Hans Van de Vyver 《水文研究》2018,32(11):1635-1647

Rainfall intensity–duration–frequency (IDF) curves are a standard tool in urban water resources engineering and management. They express how return levels of extreme rainfall intensity vary with duration. The simple scaling property of extreme rainfall intensity, with respect to duration, determines the form of IDF relationships. It is supposed that the annual maximum intensity follows the generalized extreme value (GEV) distribution. As well known, for simple scaling processes, the location parameter and scale parameter of the GEV distribution obey a power law with the same exponent. Although, the simple scaling hypothesis is commonly used as a suitable working assumption, the multiscaling approach provides a more general framework. We present a new IDF relationship that has been formulated on the basis of the multiscaling property. It turns out that the GEV parameters (location and scale) have a different scaling exponent. Next, we apply a Bayesian framework to estimate the multiscaling GEV model and to choose the most appropriate model. It is shown that the model performance increases when using the multiscaling approach. The new model for IDF curves reproduces the data very well and has a reasonable degree of complexity without overfitting on the data.  相似文献   

Continuous real‐time analysis of the isotopic composition of precipitation during tropical rain events: Insights into tropical convection          下载免费PDF全文

Shaoneng He  Nathalie F. Goodkin  Dominik Jackisch  Maria Rosabelle Ong  Dhrubajyoti Samanta 《水文研究》2018,32(11):1531-1545

To investigate stable isotopic variability of precipitation in Singapore, we continuously analysed the δ‐value of individual rain events from November 2014 to August 2017 using an online system composed of a diffusion sampler coupled to Cavity Ring‐Down Spectrometer. Over this period, the average value (δ¹⁸O_Avg), the lowest value (δ¹⁸O_Low), and the initial value (δ¹⁸O_Init) varied significantly, ranging from ?0.45 to ?15.54‰, ?0.9 to ?17.65‰, and 0 to ?13.13‰, respectively. All 3 values share similar variability, and events with low δ¹⁸O_Low and δ¹⁸O_Avg values have low δ¹⁸O_Init value. Individual events have limited intraevent variability in δ‐value (Δδ) with the majority having a Δδ below 4‰. Correlation of δ¹⁸O_Low and δ¹⁸O_Avg with δ¹⁸O_Init is much higher than that with Δδ, suggesting that convective activities prior to events have more control over δ‐value than on‐site convective activities. The d‐excess of events also varies considerably in response to the seasonal variation in moisture sources. A 2‐month running mean analysis of δ¹⁸O reveals clear seasonal and interannual variability. Seasonal variability is associated with the meridional movement of the Intertropical Convergence Zone and evolution of the Asian monsoon. El Niño–Southern Oscillation is a likely driver of interannual variability. During 2015–2016, the strongest El Niño year in recorded history, the majority of events have a δ¹⁸O value higher than the weighted average δ¹⁸O of daily precipitation. δ¹⁸O shows a positive correlation with outgoing longwave radiation in the western Pacific and the Asian monsoon region, and also with Oceanic Niño Index. During El Niño, the convection centre shifts eastward to the central/eastern Pacific, weakening convective activities in Southeast Asia. Our study shows that precipitation δ‐value contains information about El Niño–Southern Oscillation and the Intertropical Convergence Zone, which has a significant implication for the interpretation of water isotope data and understanding of hydrological processes in tropical regions.  相似文献   

The impact of climate change on extreme precipitation in Sicily,Italy          下载免费PDF全文

Angelo Forestieri  Elisa Arnone  Stephen Blenkinsop  Angela Candela  Hayley Fowler  Leonardo V. Noto 《水文研究》2018,32(3):332-348

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.  相似文献   

近30 a甘肃省河东地区极端气温指数时空变化特征及趋势预测          下载免费PDF全文

黄浩  张勃  黄涛  王怀军  马尚谦  马彬  王晓丹  崔艳强 《干旱区地理》2020,43(2):319-328

基于甘肃省河东地区61个气象站点1988—2017年逐日气温数据，利用Mann-Kendall检验，Sen’s斜率估计方法分析甘肃省河东地区极端气温指数的时空变化趋势，并探讨极端气温指数与其影响因素之间的关系，最后利用NAR神经网络结合Hurst指数对甘肃省河东地区极端气温指数变化进行预测分析。结果表明：(1)从时间上看，冷极值相对指数呈下降趋势，冷极值绝对指数、暖极值以及气温日较差、作物生长期呈上升趋势。(2)从空间上看，对冷极值变化反应最为敏感的是高寒湿润区，对暖极值变化反应最为敏感的是温带半湿润区和北亚热带湿润区，除北亚热带湿润区外各区域作物生长期的变化都达到了显著水平，而气温日较差仅在温带半湿润区达到了显著水平。(3)多数极端气温指数与经纬度、海拔之间有显著相关性，但受区域自然特点影响，经度与海拔对其影响实为一类。(4)亚洲区极涡强度、北半球极涡强度以及青藏高原指数B与极端气温指数变化有密切关系，而太阳黑子等只与个别指数之间存在显著的相关性。(5)预测出的极端气温指数冷极值相对指数仍呈现下降趋势，冷极值的绝对指数、暖极值以及气温日较差、作物生长期仍然呈现增加趋势，但大多数指数与1988—2017年相比变化幅度有所降低。（6）与其他区域相比甘肃省河东地区大多数气温指数变化幅度处于中间水平，表现出其为多种不同气候区、自然区交界地带的特色。  相似文献   

新疆哈密2018·7·31特大暴雨山洪汇水量估算与应用研究          下载免费PDF全文

王梅霞  张太西  余行杰  张连成  张旭 《干旱区地理》2020,43(4):939-945

在干旱少雨的山区开展小流域的暴雨山洪预报预警关键技术研究,对防灾减灾意义重大。2018年7月31日新疆哈密北部山区出现特大暴雨,发生罕见的山洪灾害,致使射月沟流域水库漫坝溃口,下游受灾严重。射月沟流域气象观测站点少且缺乏水文监测资料,为客观定量分析射月沟流域大暴雨面雨量、形成的洪水汇水量以及致灾水库过程。通过采用空间插值法和多源融合逐时降水资料（CMPAS）计算了射月沟水库上游面雨量并进行检验分析。根据不同面雨量驱动Floodarea模型得出射月沟水库上游累计汇水量,结果表明：多源融合降水产品估算所得最大洪峰流量和累计汇水量与水利部门事后调查数据较吻合,最大洪峰量为1 756 m³·s^-1,精确性达到调查值的95%,射月沟水库上游暴雨山洪总量为2.64×10⁷ m³,远超该水库的防洪库容和溢洪道承载能力。  相似文献   

新疆S214公路台特玛湖干涸湖盆段风沙危害及防治     

蔡东旭  李生宇  王海峰  俞祥祥  王世杰  徐新文 《中国沙漠》2020,40(1):1-11

新疆S214（考干-米兰，考米线）公路位于库鲁克塔格沙漠东南缘，穿越台特玛湖干涸湖盆。由于该区气候干旱，风力强劲，沙源丰富，流动沙丘广布且快速移动，风沙危害对公路运输构成严重威胁。通过对风沙环境和风沙危害定位观测和土壤水盐特征系统调查，确定了风沙危害极为严重的公路区段，提出了合理的风沙防护措施及防沙体系结构。结果表明：该区具有明显的单风向风况，主要盛行ENE和NE风，偶有反向风沙活动，起沙风频率、输沙势、输沙率极高，属于高能-大比率风能环境；受土壤水分、盐分含量影响，地表紧实度差异较大，部分地段为极疏松的沙层，部分地段为紧实的盐壳；S214公路风沙危害防护区段为K4+900~K18+200，设计建造的阻-固-输相结合的机械-植物复合防沙体系，防沙效果明显，保障了道路安全运营。这一强风沙、高盐区公路防沙体系建设模式可为类似环境地区工程防沙提供借鉴。  相似文献   

中国主要经济区的近期气候变化特征评估     

张学珍  郑景云  郝志新 《地理科学进展》2020,39(10):1609-1618

论文在中国《第三次气候变化国家评估报告》基础上,根据2012年以来的最新研究成果和中国气候公报,综合评估了环渤海经济区、长江经济带、华南经济圈和东北经济区的近期气候变化特征。主要结论有：① 1961—2018年,环渤海经济区、长江经济带、华南经济圈和东北经济区的平均气温上升趋势分别达0.35 ℃/10 a、0.20 ℃/10 a、0.20 ℃/10 a和0.33 ℃/10 a;尽管在1998—2014年间这些区域均出现了增暖趋缓特征,但除东北经济区外,环渤海经济区、长江经济带和华南经济圈均在2014年之后突破了其前最暖年的年均气温记录。② 1961—2018年各经济区(圈、带)的降水趋势变化虽均低于1 mm/10 a,但其间年际和年代际波动显著;2012—2018年降水虽总体偏多,但时空差异较大,其中东北经济区2013年和长江经济带2016年降水为1961年以来最多,而辽宁2014年降水却为1961年以来最少。③ 2014—2018年,各经济区(圈、带)最高气温超历史极值或极端阈值(发生概率≤10%的分位值)的极端高温事件频发,同时环渤海和东北经济区的区域性跨季连旱和极端特大暴雨等事件的发生频率增多,长江经济带暴雨日数偏多,华南经济区受台风影响呈加重态势;长江经济带和东北经济区在增暖同时也出现了多次大范围的极端低温事件。  相似文献   

Data-based modelling approach for variable density flow and solute transport simulation in a coastal aquifer   总被引：1，自引：1，他引：0  

Basant Yadav  Shashi Mathur  Sudheer Ch  Brijesh Kumar Yadav 《水文科学杂志》2018,63(2):210-226

Data-based models, namely artificial neural network (ANN), support vector machine (SVM), genetic programming (GP) and extreme learning machine (ELM), were developed to approximate three-dimensional, density-dependent flow and transport processes in a coastal aquifer. A simulation model, SEAWAT, was used to generate data required for the training and testing of the data-based models. Statistical analysis of the simulation results obtained by the four models show that the data-based models could simulate the complex salt water intrusion process successfully. The selected models were also compared based on their computational ability, and the results show that the ELM is the fastest technique, taking just 0.5 s to simulate the dataset; however, the SVM is the most accurate, with a Nash-Sutcliffe efficiency (NSE) ≥ 0.95 and correlation coefficient R ≥ 0.92 for all the wells. The root mean square error (RMSE) for the SVM is also significantly less, ranging from 12.28 to 77.61 mg/L.  相似文献