Journal of Hydrology X最新文献

{"title":"A statistics-based automated flood event separation","authors":"Svenja Fischer,&nbsp;Andreas Schumann,&nbsp;Philipp Bühler","doi":"10.1016/j.hydroa.2020.100070","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100070","url":null,"abstract":"<div><p>The classification of characteristics of flood events, like peak, volume, duration and baseflow components is essential for many hydrological applications such as multivariate flood statistics, the validation of rainfall-runoff models and comparative hydrology in general. The basis for estimations of these characteristics is formed by flood event separation. It requires an indicator for the time when a flood peak occurs as well as the definition of the beginning and end of a flood event and a subdivision of the total volume into direct and baseflow components. However, the variable nature of runoff and the multiple processes and impacts that determine rainfall-runoff relationships make a separation difficult, especially an automation of it. We propose a new statistics-based flood event separation that was developed to analyse long series of daily discharges automatically to obtain flood events for flood statistics. Moreover, the related flood-inducing precipitation is identified, allowing the estimation of the flood-inducing rainfall and the runoff coefficient. With an additional tool to manually check the separation results easily and quickly, expert knowledge can be included without much effort. The algorithm was applied to seven basins in Germany, covering alpine, mountainous and flatland catchments with different runoff processes. In a sensitivity analysis, the impact of chosen parameters was evaluated. The results show that the algorithm delivers reasonable results for all catchments and only needs manual adjustment for long timeslots with increasing or high baseflow. It reliably separates flood events only instead of all runoff events and the estimated beginning and end of an event was shifted in mean by less than one day compared to manual separation.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72092441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variability of precipitation areal reduction factors in the conterminous United States","authors":"Shih-Chieh Kao ,&nbsp;Scott T. DeNeale ,&nbsp;Elena Yegorova ,&nbsp;Joseph Kanney ,&nbsp;Meredith L. Carr","doi":"10.1016/j.hydroa.2020.100064","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100064","url":null,"abstract":"<div><p>Many hydrologic and hydraulic (H&amp;H) engineering applications require spatial rainfall distribution over a watershed, but point precipitation frequency estimates, such as those provided by NOAA Atlas 14, are only applicable for relatively small areas. For larger areas, areal reduction factors (ARFs) are commonly used to transform a point precipitation frequency estimate of a given duration and frequency to a corresponding areal estimate. The most common source of ARFs for the United States is Technical Paper 29 (TP-29), published in 1958, although there have been significant increases in record length and types of available data and several new methods for computing ARFs have been proposed over the last several decades. This study applied up-to-date precipitation data products and analysis methods with a watershed-based approach to investigate factors that affect ARF variabilities, and to compare ARFs across multiple US hydrologic regions. Our overall findings are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. In particular, we found a strong geographical variability across different US hydrologic regions, suggesting that ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of record length, especially for long return period ARFs. The study demonstrates the need to improve ARFs with new data and methods to support more reliable areal precipitation frequency estimates for H&amp;H applications.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72119454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum regarding missing Declaration of Competing Interest Statements in previously published articles","authors":"","doi":"10.1016/j.hydroa.2020.100068","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100068","url":null,"abstract":"","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100068","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72092954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sentinel-1 soil moisture content and its uncertainty over sparsely vegetated fields","authors":"Harm-Jan F. Benninga ,&nbsp;Rogier van der Velde ,&nbsp;Zhongbo Su","doi":"10.1016/j.hydroa.2020.100066","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100066","url":null,"abstract":"<div><p>Soil moisture content (SMC) retrievals from synthetic aperture radar (SAR) observations do not exactly match with in situ references due to imperfect retrieval algorithms, and uncertainties in the model parameters, SAR observations and in situ references. Information on the uncertainty of SMC retrievals would contribute to their applicability. This paper presents a methodology for deriving the SMC retrieval uncertainty and decomposing this in its constituents. A Bayesian calibration framework was used for deriving the total uncertainty and the model parameter uncertainty. The methodology was demonstrated with the integral equation method (IEM) surface scattering model, which was employed for reproducing Sentinel-1 backscatter (<span><math><mrow><msup><mrow><mi>σ</mi></mrow><mrow><mn>0</mn></mrow></msup></mrow></math></span>) observations and the retrieval of SMC over four sparsely vegetated fields in the Netherlands. For two meadows the calibrated surface roughness parameter distributions are remarkably similar between the ascending and the descending Sentinel-1 orbits as well as between the two meadows, and yield consistent SMC retrievals for the calibration and validation periods (<em>RMSD</em>s of 0.076 m³ m⁻³ to 0.11 m³ m⁻³). These results are promising for operational retrieval of SMC over meadows. In contrast, the surface roughness parameter distributions of two fallow maize fields differ significantly and the surface roughness conditions changing over time result in less consistent SMC retrievals (calibration <em>RMSD</em>s of 0.096 m³ m⁻³ and 0.13 m³ m⁻³ versus validation <em>RMSD</em>s of 0.26 m³ m⁻³). The SMC retrieval uncertainty derived with the Bayesian calibration successfully reproduces the uncertainty estimated empirically using in situ references. The main uncertainty originates from the in situ references and the Sentinel-1 observations, whereas the contribution from the surface roughness parameters is relatively small. The presented research yields further insights into the surface roughness of agricultural fields and SMC retrieval uncertainties, and these insights can be used to guide SAR-based SMC product developments.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72119453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of flood hazard assessment criteria for pedestrians with a refined mechanics-based method","authors":"G. Musolino,&nbsp;R. Ahmadian,&nbsp;R.A. Falconer","doi":"10.1016/j.hydroa.2020.100067","DOIUrl":"10.1016/j.hydroa.2020.100067","url":null,"abstract":"<div><p>Floods have caused severe destruction and affected communities in different ways throughout history. Flood events are being exacerbated by climate change and hence it is increasingly necessary to have a more accurate understanding of various aspects of flood hazard, particularly for pedestrians. The focus of this study is therefore to investigate different criteria to assess the flood hazard for pedestrians and to propose improvements in assessing such hazards. The revised mechanics-based approach reported herein gives results based on a full physical analysis of the forces acting on a body and can be universally applied as the method can be fine-tuned for different region of the world. The results from flood hazard assessments can be used to: design evacuation plans, improve resilience of sites prone to flooding and plan more resilient future developments. Extreme flood events in the UK and documented for Boscastle (2004) and Borth (2012) were used as case studies. Two approaches were considered, including: (i) a mechanics-based approach, and (ii) an experimental-based approach, with the criteria for the stability of pedestrians in floods being compared for the criteria used by regulatory authorities in Australia, Spain, UK and USA. The results obtained in this study demonstrate that the mechanics-based methods are preferable in determining flood hazard rating assessments.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46183051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A synthetic experiment to investigate the potential of assimilating LAI through direct insertion in a land surface model","authors":"Azbina Rahman ,&nbsp;Xinxuan Zhang ,&nbsp;Yuan Xue ,&nbsp;Paul Houser ,&nbsp;Timothy Sauer ,&nbsp;Sujay Kumar ,&nbsp;David Mocko ,&nbsp;Viviana Maggioni","doi":"10.1016/j.hydroa.2020.100063","DOIUrl":"10.1016/j.hydroa.2020.100063","url":null,"abstract":"<div><p>This study evaluates the potential of assimilating phenology observations using a direct insertion (DI) method by constraining the modeled terrestrial carbon dynamics with synthetic observations of vegetation condition. Specifically, observations of leaf area index (LAI) are assimilated in the Noah-Multi Parameterization (Noah-MP) land surface model across the continental United States during a 5-year period. An observing system simulation experiment (OSSE) was developed to understand and quantify the model response to assimilating LAI information through DI when the input precipitation is strongly biased. This is particularly significant in data poor regions, like Africa and South Asia, where satellite and re-analysis products, known to be affected by significant biases, are the only available precipitation data to drive a land surface model. Results show a degradation in surface and rootzone soil moisture after assimilating LAI within Noah-MP, but an improvement in intercepted liquid water and evapotranspiration with respect to the open-loop simulation (a free run with no LAI assimilation). In terms of carbon and energy variables, net ecosystem exchange, amount of carbon in shallow soil, and surface soil temperature are improved by the LAI DI, although canopy sensible heat is degraded. Overall, the assimilation of LAI has larger impact in terms of reduced systematic and random errors over the Great Plains (cropland, shrubland, and grassland). Moreover, LAI DA shows a greater improvement when the input precipitation is affected by a positive (wet) bias than the opposite case, in which precipitation shows a dry bias.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49083834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WITHDRAWN: Description of an indirect method (IDPR) to determine spatial distribution of infiltration and runoff and its hydrogeological applications to the French territory","authors":"V. Mardhel, S. Pinson, D. Allier","doi":"10.1016/j.hydroa.2020.100065","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100065","url":null,"abstract":"","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47277305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intense summer floods may induce prolonged increases in benthic respiration rates of more than one year leading to low river dissolved oxygen","authors":"M.G. Hutchins ,&nbsp;G. Harding ,&nbsp;H.P. Jarvie ,&nbsp;T.J. Marsh ,&nbsp;M.J. Bowes ,&nbsp;M. Loewenthal","doi":"10.1016/j.hydroa.2020.100056","DOIUrl":"10.1016/j.hydroa.2020.100056","url":null,"abstract":"<div><p>The supply of readily-degradable organic matter to river systems can cause stress to dissolved oxygen (DO) in slow-flowing waterbodies. To explore this threat, a multi-disciplinary study of the River Thames (UK) was undertaken over a six-year period (2009–14). Using a combination of observations at various time resolutions (monthly to hourly), physics-based river network water quality modelling (QUESTOR) and an analytical tool to estimate metabolic regime (Delta method), a decrease in 10th percentile DO concentration (10-DO, indicative of summer low levels) was identified during the study period. The assessment tools suggested this decrease in 10-DO was due to an increase in benthic heterotrophic respiration. Hydrological and dissolved organic carbon (DOC) data showed that the shift in 10-DO could be attributed to summer flooding in 2012 and consequent connection of pathways flushing degradable organic matter into the river. Comparing 2009–10 and 2013–14 periods, 10-DO decreased by 7.0% at the basin outlet (Windsor) whilst median DOC concentrations in a survey of upstream waterbodies increased by 5.5–48.1%. In this context, an anomalous opposing trend in 10-DO at one site on the river was also identified and discussed. Currently, a lack of process understanding of spatio-temporal variability in benthic respiration rates is hampering model predictions of river DO. The results presented here show how climatic-driven variation and urbanisation induce persistent medium-term changes in the vulnerability of water quality to multiple stressors across complex catchment systems.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47401534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shallow aquifer monitoring using handpump vibration data","authors":"Achut Manandhar ,&nbsp;Heloise Greeff ,&nbsp;Patrick Thomson ,&nbsp;Rob Hope ,&nbsp;David A. Clifton","doi":"10.1016/j.hydroa.2020.100057","DOIUrl":"10.1016/j.hydroa.2020.100057","url":null,"abstract":"<div><p>We present a novel technology for monitoring changes in aquifer depth using handpump vibration data. This builds on our previous works using data to track handpump usage and facilitate handpump maintenance systems in rural parts of Kenya. Our motivation is to develop a cost-effective and scalable infrastructure to monitor shallow aquifers in regions where handpumps are already part of water infrastructure, but where traditional sources of groundwater monitoring data may be limited or non-existent. The data is generated using accelerometer sensors attached to the handles of nine handpumps in the study site in Kenya, instrumented for a year. These time-series data from handpumps are individually modelled using machine learning methods to track the changes in the water level with respect to the bottom of the rising main. Results show promise in modelling handpump vibration data with machine learning approaches to provide useful aquifer monitoring information from the “accidental infrastructure” of community handpumps. This technology is intended to complement existing hydrogeological modelling, and one of our key future goals is to integrate these machine learning outputs with hydrogeological information to develop more refined and robust models for shallow aquifer monitoring.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46327229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal variability of summer precipitation and precipitation extremes and associated large-scale mechanisms in Central Asia during 1979–2018","authors":"Qianrong Ma ,&nbsp;Jie Zhang ,&nbsp;Asaminew Teshome Game ,&nbsp;Yi Chang ,&nbsp;Shuangshuang Li","doi":"10.1016/j.hydroa.2020.100061","DOIUrl":"https://doi.org/10.1016/j.hydroa.2020.100061","url":null,"abstract":"<div><p>The spatiotemporal variability of precipitation extremes dramatically affects various socio-economic activities in dryland. Based on the long-term and high-resolution daily precipitation obtained from the National Oceanic and Atmosphere Administration (NOAA) Climate Prediction Center (CPC), the total summer precipitation (TSP), precipitation extreme and persistent precipitation extreme (PPE) characteristics are revealed in Central Asia (CA) (34.3°N–55.4°N and 46.5°E–96.4°E) during 1979–2018. Results show that TSP, precipitation extreme and PPE in CA are significantly increased and the abrupt increasing occurred mainly in 1998. Additionally, proportion of precipitation extreme in TSP also increases. More significant positive trends of TSP, precipitation extreme and PPE occur in zones of northern Kazakhstan (NKZ) and Tienshan mountain range (TSM). Notably, although PEP in other regions exhibit indistinctive changes, PPE in some particular years abnormally frequent which may leads disasters. Further analyses indicate TSP and precipitation extreme in CA have significant positive correlation with the increasing water vapor transport from the southern boundary. Meanwhile, increasing horizontal moisture advection and enhanced vertical moisture advection, contributes to increasing in TSP and precipitation extreme in NKZ and TSM. In addition, negative phase of East Atlantic/West Russia (EA/WR) may result in the cyclone anomalous and deepened trough over CA, which cooperates with enhanced vertical advection and abnormal south moisture, finally provides favorable conditions for precipitation and precipitation extreme.</p></div>","PeriodicalId":36948,"journal":{"name":"Journal of Hydrology X","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.hydroa.2020.100061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72094830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}