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Technical note: Seamless extraction and analysis of river networks in R 技术说明:R中河网的无缝提取和分析
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-23 DOI: 10.5194/hess-27-3733-2023
Luca Carraro
Abstract. Spatially explicit mathematical models are key to a mechanistic understanding of environmental processes in rivers. Such models necessitate extended information on networks' morphology, which is often retrieved from geographic information system (GIS) software, thus hindering the establishment of replicable script-based workflows. Here I present rivnet, an R package for GIS-free extraction and analysis of river networks based on digital elevation models (DEMs). The package exploits TauDEM's flow direction algorithm in user-provided or online accessible DEMs, and allows for computing covariate values and assigning hydraulic variables across any network node. The package is designed so as to require minimal user input while allowing for customization for experienced users. It is specifically intended for application in models of ecohydrological, ecological or biogeochemical processes in rivers. As such, rivnet aims to make river network analysis accessible to users unfamiliar with GIS-based and geomorphological methods and therefore enhance the use of spatially explicit models in rivers.
摘要空间显式数学模型是对河流环境过程的机械理解的关键。这种模型需要关于网络形态的扩展信息,这些信息通常是从地理信息系统(GIS)软件中检索的,从而阻碍了基于脚本的可复制工作流的建立。在这里,我介绍了rivnet,一个基于数字高程模型(dem)的无gis河网提取和分析的R包。该软件包在用户提供或在线访问的dem中利用TauDEM的流向算法,并允许计算协变量值,并在任何网络节点上分配水力变量。该包的设计,使需要最少的用户输入,同时允许定制为有经验的用户。它特别适用于河流生态水文、生态或生物地球化学过程的模型。因此,rivnet的目标是让不熟悉地理信息系统和地貌学方法的用户可以访问河网分析,从而增强空间明确模型在河流中的使用。
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引用次数: 0
Technical note: Discrete in situ vapor sampling for subsequent lab-based water stable isotope analysis 技术说明:用于后续实验室水稳定同位素分析的离散原位蒸汽取样
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-20 DOI: 10.5194/hess-27-3701-2023
Barbara Herbstritt, Benjamin Gralher, Stefan Seeger, Michael Rinderer, Markus Weiler
Abstract. Methodological advancements have been made in in situ observations of water stable isotopes that have provided valuable insights into ecohydrological processes. The continuous measurement capabilities of laser-based analyzers allow for high temporal resolutions and non-destructive minimally invasive study designs of such in situ approaches. However, isotope analyzers are expensive, heavy, and require shelter and access to electrical power, which impedes many in situ assays. Therefore, we developed a new inexpensive technique to collect discrete water vapor samples in the field via diffusion-tight inflatable bags that can later be analyzed in the lab. In a series of structured experiments, we tested different procedural settings, bag materials, and closure types for diffusion tightness during storage as well as for practical handling during filling and extraction. To facilitate reuse of sampling bags, we present a conditioning procedure using ambient air as primer. In order to validate our method, direct measurements through hydrophobic in situ probes were compared to repeated measurements of vapor sampled with our bags from the same source. All steps are summarized in a detailed standard operating procedure (SOP). This procedure represents the preparation and measurement of calibration and validation vapor standards necessary for processing of unknown field-collected vapor samples in the foreseen application. By performing pertinent calibration procedures, accuracy was better than 0.4 ‰ for δ18O and 1.9 ‰ for δ2H after 1 d of storage. Our technique is particularly suitable when used in combination with minimally invasive water vapor sampling in situ probes that have already been employed for soils and tree xylem. It is an important step towards minimally invasive monitoring of stable isotope distributions and also time series in virtually undisturbed soils and trees without the need to have an analyzer in the field. It is therefore a promising tool for many applications in ecohydrology and meteorology.
摘要在水稳定同位素的原位观测方面取得了方法学上的进步,为生态水文过程提供了有价值的见解。激光分析仪的连续测量能力允许这种原位方法的高时间分辨率和非破坏性微创研究设计。然而,同位素分析仪价格昂贵,重量大,需要遮蔽物和电力,这阻碍了许多原位分析。因此,我们开发了一种新的廉价技术,通过扩散密封充气袋在现场收集离散的水蒸气样本,然后在实验室进行分析。在一系列结构化的实验中,我们测试了不同的程序设置、袋材料和封闭类型,用于储存过程中的扩散密封性以及填充和提取过程中的实际处理。为了便于采样袋的重复使用,我们提出了一种使用环境空气作为底火的调理程序。为了验证我们的方法,通过疏水原位探针进行的直接测量与用我们的袋子从同一来源采样的蒸汽的重复测量进行了比较。所有的步骤都总结在一个详细的标准操作程序(SOP)中。本程序代表了在预期应用中处理未知现场收集的蒸汽样品所需的校准和验证蒸汽标准的制备和测量。通过相应的校准程序,储存1 d后δ18O和δ2H的准确度分别优于0.4‰和1.9‰。我们的技术特别适合与已经用于土壤和树木木质部的微创水汽取样原位探针结合使用。这是在几乎不受干扰的土壤和树木中进行稳定同位素分布和时间序列的微创监测的重要一步,而无需在现场使用分析仪。因此,它在生态水文学和气象学的许多应用中是一个很有前途的工具。
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引用次数: 0
The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators 湿地内在势工具:通过多尺度湿地指标遥感代理的机器学习绘制湿地内在势
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-20 DOI: 10.5194/hess-27-3687-2023
Meghan Halabisky, Dan Miller, Anthony J. Stewart, Amy Yahnke, Daniel Lorigan, Tate Brasel, Ludmila Monika Moskal
Abstract. Accurate, unbiased wetland inventories are critical to monitor and protect wetlands from future harm or land conversion. However, most wetland inventories are constructed through manual image interpretation or automated classification of multi-band imagery and are biased towards wetlands that are easy to directly detect in aerial and satellite imagery. Wetlands that are obscured by forest canopy, that occur ephemerally, and that have no visible standing water are, therefore, often missing from wetland maps. To aid in the detection of these cryptic wetlands, we developed the Wetland Intrinsic Potential (WIP) tool, based on a wetland-indicator framework commonly used on the ground to detect wetlands through the presence of hydrophytic vegetation, hydrology, and hydric soils. Our tool uses a random forest model with spatially explicit input variables that represent all three wetland indicators, including novel multi-scale topographic indicators that represent the processes that drive wetland formation, to derive a map of wetland probability. With the ability to include multi-scale topographic indicators that help identify cryptic wetlands, the WIP tool can identify areas conducive to wetland formation while providing a flexible approach that can be adapted to diverse landscapes. For a study area in the Hoh River watershed in western Washington, USA, classification of the output probability with a threshold of 0.5 provided an overall accuracy of 91.97 %. Compared to the National Wetlands Inventory, the classified WIP tool output identified over 2 times the wetland area and reduced errors of omission from 47.5 % to 14.1 % but increased errors of commission from 1.9 % to 10.5 %. The WIP tool is implemented as an ArcGIS toolbox using a combination of R and Python scripts.
摘要准确、公正的湿地清单对于监测和保护湿地免受未来的危害或土地转换至关重要。然而,大多数湿地清单是通过人工图像解译或多波段图像自动分类构建的,并且偏向于在航空和卫星图像中易于直接检测的湿地。被森林冠层遮蔽的湿地,转瞬即逝的湿地,没有可见的死水,因此,在湿地地图上经常会遗漏。为了帮助检测这些潜在湿地,我们开发了湿地内在潜力(WIP)工具,该工具基于地面上常用的湿地指标框架,通过水生植被、水文学和含水土壤的存在来检测湿地。我们的工具使用一个随机森林模型,该模型具有空间明确的输入变量,代表所有三个湿地指标,包括代表驱动湿地形成过程的新型多尺度地形指标,以得出湿地概率图。WIP工具能够包含多尺度地形指标,帮助识别隐藏湿地,从而识别有利于湿地形成的区域,同时提供一种灵活的方法,可以适应不同的景观。对于美国华盛顿西部Hoh河流域的一个研究区域,输出概率分类的阈值为0.5,总体准确率为91.97%。与国家湿地清单相比,分类WIP工具的输出识别了超过2倍的湿地面积,将遗漏误差从47.5%减少到14.1%,但将委托误差从1.9%增加到10.5%。WIP工具是使用R和Python脚本的组合作为ArcGIS工具箱实现的。
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引用次数: 2
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics 基于主成分的降水强度-持续时间-频率(IDF)统计区划策略
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-20 DOI: 10.5194/hess-27-3719-2023
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, Julia Lutz
Abstract. Intensity–duration–frequency (IDF) statistics describing extreme rainfall intensities in Norway were analysed with the purpose of investigating how the shape of the curves is influenced by geographical conditions and local climate characteristics. To this end, principal component analysis (PCA) was used to quantify salient information about the IDF curves, and a Bayesian linear regression was used to study the dependency of the shapes on climatological and geographical information. Our analysis indicated that the shapes of IDF curves in Norway are influenced by both geographical conditions and 24 h precipitation statistics. Based on this analysis, an empirical model was constructed to predict IDF curves in locations with insufficient sub-hourly rain gauge data. Our new method was also compared with a recently proposed formula for estimating sub-daily rainfall intensity based on 24 h rain gauge data. We found that a Bayesian inference of a PCA representation of IDF curves provides a promising strategy for estimating sub-daily return levels for rainfall.
摘要对描述挪威极端降雨强度的强度-持续时间-频率统计数据进行了分析,目的是调查地理条件和当地气候特征对曲线形状的影响。为此,利用主成分分析(PCA)量化IDF曲线的显著信息,并利用贝叶斯线性回归研究IDF曲线形状与气候和地理信息的相关性。我们的分析表明,挪威IDF曲线的形状受到地理条件和24 h降水统计的影响。在此基础上,构建了预测亚时雨量计数据不足地区IDF曲线的经验模型。我们的新方法还与最近提出的基于24 h雨量计数据的次日降雨强度估算公式进行了比较。我们发现IDF曲线的PCA表示的贝叶斯推理为估计降雨的次日回归水平提供了一个有希望的策略。
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引用次数: 0
Improving the quantification of climate change hazards by hydrological models: a simple ensemble approach for considering the uncertain effect of vegetation response to climate change on potential evapotranspiration 利用水文模型改进气候变化危害的量化:考虑植被对气候变化响应对潜在蒸散不确定影响的简单集合方法
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-19 DOI: 10.5194/hess-27-3663-2023
Thedini Asali Peiris, Petra Döll
Abstract. Almost no hydrological model takes into account that changes in evapotranspiration are affected by how vegetation responds to changing CO2 and climate. This severely limits their ability to quantify the impact of climate change on evapotranspiration and, thus, water resources. As the simulation of vegetation responses is both complex and very uncertain, we recommend a simple approach to considering (in climate change impact studies with hydrological models) the uncertainty that the vegetation response causes with respect to the estimation of future potential evapotranspiration (PET). To quantify this uncertainty in a simple manner, we propose running the hydrological model in two variants: with its standard PET approach and with a modified approach to compute PET. In the case of PET equations containing stomatal conductance, the modified approach can be implemented by adjusting the conductance. We introduce a modified approach for hydrological models that computes PET as a function of net radiation and temperature only, i.e., with the Priestley–Taylor (PT) equation. The new PT-MA approach is based on the work of Milly and Dunne (2016) (MD), who compared the change in non-water-stressed actual evapotranspiration (NWSAET) as computed by an ensemble of global climate models (GCMs), which simulate vegetation response as well as interactions between the atmosphere and the land surface, with various methods to compute PET change. Based on this comparison, MD proposed estimating the impact of climate change on PET as a function of only the change in net energy input at the land surface. PT-MA retains the impact of temperature on daily to interannual as well as spatial PET variations but removes the impact of the long-term temperature trend on PET such that long-term changes in future PET are driven by changes in net radiation only. We implemented PT-MA in the global hydrological model WaterGAP 2.2d and computed daily time series of PET between 1901 and 2099 using the bias-adjusted output of four GCMs. Increases in GCM-derived NWSAET between the end of the 20th and the end of the 21st century for Representative Concentration Pathway 8.5 (RCP8.5) are simulated well by WaterGAP if PT-MA is applied but are severely overestimated with the standard PT method. Application of PT-MA in WaterGAP results in smaller future decreases or larger future increases in renewable water resources (expressed as the variable RWR) compared with the standard PT method, except in a small number of grid cells where increased inflow from upstream areas due to increased upstream runoff leads to enhanced evapotranspiration from surface water bodies or irrigated fields. On about 20 % of the global land area, PT-MA leads to an increase in RWR that is more than 20 % higher than in the case of standard PT, while on more than 10 % of the global land area, the projected RWR decrease is reduced by more than 20 %. While the modified approach to compute PET is likely to avoid the o
摘要几乎没有水文模型考虑到植被对二氧化碳和气候变化的反应会影响到蒸散的变化。这严重限制了它们量化气候变化对蒸散的影响的能力,从而也限制了它们量化水资源的能力。由于植被响应的模拟既复杂又非常不确定,我们建议采用一种简单的方法来考虑(在水文模型的气候变化影响研究中)植被响应引起的不确定性,从而对未来潜在蒸散量(PET)进行估计。为了以一种简单的方式量化这种不确定性,我们建议以两种变体运行水文模型:使用其标准PET方法和使用改进的方法来计算PET。对于含有气孔导度的PET方程,可以通过调整气孔导度来实现改进的方法。我们为水文模型引入了一种改进的方法,该方法仅将PET作为净辐射和温度的函数计算,即使用Priestley-Taylor (PT)方程。新的PT-MA方法是基于Milly和Dunne (2016) (MD)的工作,他们比较了由全球气候模式(GCMs)集合计算的非水分胁迫实际蒸散(NWSAET)的变化,该模式模拟植被响应以及大气与陆地表面之间的相互作用,与各种计算PET变化的方法。在此基础上,MD建议将气候变化对PET的影响仅作为陆地表面净能量输入变化的函数来估计。PT-MA保留了温度对日至年际以及空间PET变化的影响,但消除了长期温度趋势对PET的影响,因此未来PET的长期变化仅由净辐射变化驱动。我们在全球水文模型WaterGAP 2.2d中实现了PT-MA,并使用四个gcm的偏差调整输出计算了1901 - 2099年的PET日时间序列。如果采用PT- ma方法,WaterGAP可以很好地模拟20世纪末至21世纪末代表浓度路径8.5 (RCP8.5)的gcm衍生的NWSAET的增加,但标准PT方法严重高估了这一点。与标准PT方法相比,在WaterGAP中应用PT- ma,可再生水资源(以变量RWR表示)的未来减少量较小或未来增加量较大,但在少数网格单元中,由于上游径流增加,上游地区的流入增加,导致地表水体或灌溉田的蒸散量增加。在大约20%的全球陆地面积上,PT- ma导致的RWR增加比标准PT情况下高出20%以上,而在超过10%的全球陆地面积上,预估的RWR减少减少了20%以上。虽然计算PET的改进方法可能避免在许多地区(如果不是大多数地区)对未来干旱的高估,但其他地区的植被响应可能是这样的,即应用标准PET可能导致PET更有可能发生变化。由于这些区域无法确定,因此提出的两种水文模型变量的集合方法用于表示由于植被对气候变化的响应而导致的水文变化的不确定性,而这在模型中没有表示。
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引用次数: 1
Accounting for precipitation asymmetry in a multiplicative random cascade disaggregation model 在乘法随机级联分解模型中考虑降水不对称性
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-18 DOI: 10.5194/hess-27-3643-2023
Kaltrina Maloku, Benoit Hingray, Guillaume Evin
Abstract. Analytical multiplicative random cascades (MRCs) are widely used for the temporal disaggregation of coarse-resolution precipitation time series. This class of models applies scaling models to represent the dependence of the cascade generator on the temporal scale and the precipitation intensity. Although determinant, the dependence on the external precipitation pattern is usually disregarded in the analytical scaling models. Our work presents a unified MRC modelling framework that allows the cascade generator to depend in a continuous way on the temporal scale, precipitation intensity and a so-called precipitation asymmetry index. Different MRC configurations are compared for 81 locations in Switzerland with contrasted climates. The added value of the dependence of the MRC on the temporal scale appears to be unclear, unlike what was suggested in previous works. Introducing the precipitation asymmetry dependence into the model leads to a drastic improvement in model performance for all statistics related to precipitation temporal persistence (wet–dry transition probabilities, lag-n autocorrelation coefficients, lengths of dry–wet spells). Accounting for precipitation asymmetry seems to solve this important limitation of previous MRCs. The model configuration that only accounts for the dependence on precipitation intensity and asymmetry is highly parsimonious, with only five parameters, and provides adequate performances for all locations, seasons and temporal resolutions. The spatial coherency of the parameter estimates indicates a real potential for regionalisation and for further application to any location in Switzerland.
摘要解析乘法随机级联(MRCs)被广泛用于粗分辨率降水时间序列的时间分解。这类模型采用尺度模型来表示梯级发生器对时间尺度和降水强度的依赖关系。虽然是决定性的,但在解析标度模型中通常忽略了对外部降水模式的依赖。我们的工作提出了一个统一的MRC建模框架,该框架允许级联发生器以连续的方式依赖于时间尺度、降水强度和所谓的降水不对称指数。不同的MRC配置比较了81个地点在瑞士的对比气候。与之前的研究不同,MRC在时间尺度上的依赖性的附加价值似乎不清楚。在模型中引入降水不对称依赖会导致与降水时间持久性相关的所有统计数据(干湿转换概率、滞后自相关系数、干湿期长度)的模型性能的急剧改善。考虑降水不对称似乎解决了以前MRCs的这一重要限制。仅考虑降水强度和不对称性依赖的模式配置非常简洁,只有5个参数,并提供了所有地点、季节和时间分辨率的足够性能。参数估计的空间一致性表明了区域化和进一步应用于瑞士任何地点的真正潜力。
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引用次数: 1
Technical note: NASAaccess – a tool for access, reformatting, and visualization of remotely sensed earth observation and climate data 技术说明:NASAaccess——一个获取、重新格式化和可视化遥感地球观测和气候数据的工具
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-13 DOI: 10.5194/hess-27-3621-2023
Ibrahim Nourein Mohammed, Elkin Giovanni Romero Bustamante, John Dennis Bolten, Everett James Nelson
Abstract. The National Aeronautics and Space Administration (NASA) has launched a new initiative, the Open-Source Science Initiative (OSSI), to enable and support science towards openness. The OSSI supports open-source software development and dissemination. In this work, we present NASAaccess, which is an open-source software package and web-based environmental modeling application for earth observation data accessing, reformatting, and presenting quantitative data products. The main objective of developing the NASAaccess platform is to facilitate exploration, modeling, and understanding of earth data for scientists, stakeholders, and concerned citizens whose objectives align with the new OSSI goals. The NASAaccess platform is available as software packages (i.e., the R and conda packages) as well as an interactive-format web-based environmental modeling application for earth observation data developed with Tethys Platform. NASAaccess has been envisioned as lowering the technical barriers and simplifying the process of accessing scalable distributed computing resources and leveraging additional software for data and computationally intensive modeling frameworks. Specifically, NASAaccess has been developed to meet the need for seamless earth observation remote-sensing and climate data ingestion into various hydrological modeling frameworks. Moreover, NASAaccess is also contributing to keeping interested parties and stakeholders engaged with environmental modeling, accessing the information available in various remote-sensing products. NASAaccess' current capabilities cover various NASA datasets and products that include the Global Precipitation Measurement (GPM) data products, the Global Land Data Assimilation System (GLDAS) land surface states and fluxes, and the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate change dataset products.
摘要美国国家航空航天局(NASA)发起了一项新的倡议,即开源科学倡议(OSSI),以使和支持科学走向开放。OSSI支持开源软件的开发和传播。在这项工作中,我们提出了NASAaccess,这是一个开源软件包和基于web的环境建模应用程序,用于对地观测数据的访问,重新格式化和呈现定量数据产品。开发nasa访问平台的主要目标是促进科学家、利益相关者和相关公民对地球数据的探索、建模和理解,他们的目标与新的OSSI目标一致。NASAaccess平台可作为软件包(即R和conda软件包)以及与Tethys平台一起开发的基于web的交互式环境建模应用程序,用于地球观测数据。NASAaccess被设想为降低技术壁垒,简化访问可扩展的分布式计算资源的过程,并为数据和计算密集型建模框架利用额外的软件。具体来说,NASAaccess的开发是为了满足将地球观测、遥感和气候数据无缝摄取到各种水文建模框架中的需求。此外,NASAaccess还有助于使有关各方和利益攸关方参与环境建模,获取各种遥感产品中提供的信息。NASAaccess目前的能力涵盖各种NASA数据集和产品,包括全球降水测量(GPM)数据产品、全球陆地数据同化系统(GLDAS)陆地表面状态和通量,以及NASA地球交换全球每日缩小预估(NEX-GDDP)耦合模式比对项目第5阶段(CMIP5)和耦合模式比对项目第6阶段(CMIP6)气候变化数据集产品。
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引用次数: 0
Modelling groundwater recharge, actual evaporation, and transpiration in semi-arid sites of the Lake Chad basin: the role of soil and vegetation in groundwater recharge 乍得湖流域半干旱区地下水补给、实际蒸发和蒸腾模拟:土壤和植被在地下水补给中的作用
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-12 DOI: 10.5194/hess-27-3601-2023
Christoph Neukum, Angela Morales-Santos, Melanie Ronelngar, Aminu Bala, Sara Vassolo
Abstract. The Lake Chad basin, located in the centre of northern Africa, is characterized by strong climate seasonality with a pronounced short annual precipitation period and high potential evapotranspiration. Groundwater is an essential source for drinking-water supply, as well as for agriculture and groundwater-related ecosystems. Thus, assessment of groundwater recharge is very important although also difficult because of the strong effects of evaporation and transpiration, as well as the limited available data. A simple, generalized approach, which requires only limited field data, freely available remote sensing data, and well-established concepts and models, is tested for assessing groundwater recharge in the southern part of the basin. This work uses the FAO dual-Kc concept to estimate E and T coefficients at six locations that differ in soil texture, climate, and vegetation conditions. Measured values of soil water content and chloride concentrations along vertical soil profiles together with different scenarios for E and T partitioning and a Bayesian calibration approach are used to numerically simulate water flow and chloride transport using Hydrus-1D. Average groundwater recharge rates and the associated model uncertainty at the six locations are assessed for the 2003–2016 time period. Annual groundwater recharge varies between 6 and 93 mm and depends strongly on soil texture and related water retention and on vegetation. Interannual variability of groundwater recharge is generally greater than the uncertainty of the simulated groundwater recharge.
摘要乍得湖盆地位于北非中部,气候季节性强,年降水周期短,潜在蒸散量大。地下水是饮用水供应以及农业和与地下水有关的生态系统的重要来源。因此,评估地下水补给是非常重要的,尽管由于蒸发和蒸腾的强烈影响以及现有数据有限也很困难。试验了一种简单、广义的方法来评估盆地南部的地下水补给,该方法只需要有限的实地数据、可免费获得的遥感数据和完善的概念和模型。本研究使用粮农组织的双kc概念估算了土壤质地、气候和植被条件不同的六个地点的E和T系数。利用Hydrus-1D软件对垂直土壤剖面上土壤含水量和氯离子浓度的实测值、不同的E和T划分方案以及贝叶斯校准方法进行了数值模拟。评估了2003-2016年期间六个地点的平均地下水补给率和相关的模式不确定性。地下水年补给量在6至93毫米之间变化,在很大程度上取决于土壤质地和相关的保水能力以及植被。地下水补给的年际变化一般大于模拟地下水补给的不确定性。
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引用次数: 0
A Bayesian model for quantifying errors in citizen science data: application to rainfall observations from Nepal 公民科学数据误差量化的贝叶斯模型:在尼泊尔降雨观测中的应用
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-09 DOI: 10.5194/hess-27-3565-2023
Jessica A. Eisma, Gerrit Schoups, Jeffrey C. Davids, Nick van de Giesen
Abstract. High-quality citizen science data can be instrumental in advancing science toward new discoveries and a deeper understanding of under-observed phenomena. However, the error structure of citizen scientist (CS) data must be well-defined. Within a citizen science program, the errors in submitted observations vary, and their occurrence may depend on CS-specific characteristics. This study develops a graphical Bayesian inference model of error types in CS data. The model assumes that (1) each CS observation is subject to a specific error type, each with its own bias and noise, and (2) an observation's error type depends on the static error community of the CS, which in turn relates to characteristics of the CS submitting the observation. Given a set of CS observations and corresponding ground-truth values, the model can be calibrated for a specific application, yielding (i) number of error types and error communities, (ii) bias and noise for each error type, (iii) error distribution of each error community, and (iv) the single error community to which each CS belongs. The model, applied to Nepal CS rainfall observations, identifies five error types and sorts CSs into four static, model-inferred communities. In the case study, 73 % of CSs submitted data with errors in fewer than 5 % of their observations. The remaining CSs submitted data with unit, meniscus, unknown, and outlier errors. A CS's assigned community, coupled with model-inferred error probabilities, can identify observations that require verification and provides an opportunity for targeted re-training of CSs based on mistake tendencies.
摘要高质量的公民科学数据有助于推动科学走向新的发现和对未被观察到的现象的更深入的理解。然而,公民科学家数据的错误结构必须有明确的定义。在公民科学项目中,提交的观察结果中的错误各不相同,它们的发生可能取决于cs的特定特征。本研究建立了CS数据误差类型的图形贝叶斯推理模型。该模型假设:(1)每个CS观测值都有特定的误差类型,每个观测值都有自己的偏差和噪声;(2)观测值的误差类型取决于CS的静态误差社区,而静态误差社区又与提交观测值的CS的特性有关。给定一组CS观测值和相应的真值,模型可以针对特定应用进行校准,产生(i)错误类型和错误社区的数量,(ii)每种错误类型的偏差和噪声,(iii)每个错误社区的错误分布,以及(iv)每个CS所属的单个错误社区。该模型应用于尼泊尔CS降雨观测,确定了5种错误类型,并将CS分为4个静态的、模型推断的群落。在案例研究中,73%的CSs提交的数据误差小于5%。其余的CSs提交的数据有单位、半月板、未知和异常值错误。CS的指定社区,加上模型推断的错误概率,可以识别需要验证的观察结果,并为基于错误倾向的CS提供有针对性的重新训练机会。
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引用次数: 0
Remote quantification of the trophic status of Chinese lakes 中国湖泊营养状况的远程定量研究
1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2023-10-09 DOI: 10.5194/hess-27-3581-2023
Sijia Li, Shiqi Xu, Kaishan Song, Tiit Kutser, Zhidan Wen, Ge Liu, Yingxin Shang, Lili Lyu, Hui Tao, Xiang Wang, Lele Zhang, Fangfang Chen
Abstract. Assessing eutrophication in lakes is of key importance, as this parameter constitutes a major aquatic ecosystem integrity indicator. The trophic state index (TSI), which is widely used to quantify eutrophication, is a universal paradigm in the scientific literature. In this study, a methodological framework is proposed for quantifying and mapping TSI using the Sentinel Multispectral Imager sensor and fieldwork samples. The first step of the methodology involves the implementation of stepwise multiple regression analysis of the available TSI dataset to find some band ratios, such as blue/red, green/red and red/red, which are sensitive to lake TSI. Trained with in situ measured TSI and match-up Sentinel images, we established the XGBoost of machine learning approaches to estimate TSI, with good agreement (R2= 0.87, slope = 0.85) and fewer errors (MAE = 3.15 and RMSE = 4.11). Additionally, we discussed the transferability and applications of XGBoost in three lake classifications: water quality, absorption contribution and reflectance spectra types. We selected XGBoost to map TSI in 2019–2020 with good-quality Sentinel-2 Level-1C images embedded in the ESA to examine the spatiotemporal variations of the lake trophic state. In a large-scale observation, 10 m TSI products from 555 lakes in China facing eutrophication and unbalanced spatial patterns associated with lake basin characteristics, climate and anthropogenic activities were investigated. The methodological framework proposed herein could serve as a useful resource for continuous, long-term and large-scale monitoring of lake aquatic ecosystems, supporting sustainable water resource management.
摘要评估湖泊富营养化至关重要,因为这一参数构成了主要的水生生态系统完整性指标。营养状态指数(TSI)被广泛用于量化富营养化,是科学文献中的通用范式。在这项研究中,提出了一种方法框架,用于使用Sentinel多光谱成像仪传感器和实地工作样本来量化和绘制TSI。该方法的第一步涉及对可用的TSI数据集进行逐步多元回归分析,以找到一些对湖泊TSI敏感的波段比率,如蓝/红、绿/红和红/红。使用原位测量的TSI和匹配的Sentinel图像进行训练,我们建立了XGBoost的机器学习方法来估计TSI,一致性好(R2= 0.87,斜率= 0.85),误差更小(MAE = 3.15, RMSE = 4.11)。此外,我们还讨论了XGBoost在三种湖泊类型(水质、吸收贡献和反射光谱类型)中的可转移性及其应用。我们选择XGBoost,利用ESA中嵌入的高质量Sentinel-2 Level-1C图像,绘制2019-2020年湖泊营养状态的时空变化图。对中国555个湖泊的10 m TSI产品进行了大尺度观测,研究了湖泊富营养化及其与湖泊流域特征、气候和人为活动相关的不平衡空间格局。本文提出的方法框架可为湖泊水生生态系统的连续、长期和大规模监测提供有用的资源,支持可持续水资源管理。
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引用次数: 2
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Hydrology and Earth System Sciences
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