Identification of factors influencing hydrologic model performance using a top-down approach in a large number of U.S. catchments

Investigating the performance that can be achieved with different hydrological models across catchments with varying characteristics is a requirement for identifying an adequate model for any catchment, gauged or ungauged, just based on information about its climate and catchment properties. As parameter uncertainty increases with the number of model parameters, it is important not only to identify a model achieving good results but also to aim at the simplest model still able to provide acceptable results. The main objective of this study is to identify the climate and catchment properties determining the minimal required complexity of a hydrological model. As previous studies indicate that the required model complexity varies with the temporal scale, the study considers the performance at the daily, monthly, and annual timescales. In agreement with previous studies, the results show that catchments located in arid areas tend to be more difficult to model. They therefore require more complex models for achieving an acceptable performance. For determining which other factors influence model performance, an analysis was carried out for four catchment groups (snowy, arid, and eastern and western catchments). The results show that the baseflow and aridity indices are the most consistent predictors of model performance across catchment groups and timescales. Both properties are negatively correlated with model performance. Other relevant predictors are the fraction of snow in the annual precipitation (negative correlation with model performance), soil depth (negative correlation with model performance), and some other soil properties. It was observed that the sign of the correlation between the catchment characteristics and model performance varies between clusters in some cases, stressing the difficulties encountered in large sample analyses. Regarding the impact of the timescale, the study confirmed previous results indicating that more complex models are needed for shorter timescales.     

Evaluating soil moisture estimation from ground-penetrating radar hyperbola fitting with respect to a systematic time-domain reflectometry data collection in a boreal podzolic agricultural field

The upper 30 cm of the soil profile, which hosts the majority of the root biomass, can be considered as the shallow agricultural root zone of most temperate crops. The electromagnetic wave velocity in the soil obtained from reflection hyperbolas in ground-penetrating radar (GPR) data can be used to estimate soil moisture (SM). Finding shallow hyperbolas in a radargram and minimizing the subjective error associated with the hyperbola fitting are the main challenges in this approach. Nevertheless, we were motivated by the recent improvements of hyperbola fitting algorithms, which can reduce the subjective error and processing time. To overcome the difficulty of finding very shallow hyperbolas, we applied the hyperbola fitting method to reflections ranging from 27- to 50-cm depth using a 500-MHz centre-frequency GPR and compared the estimated moisture with vertically installed, 30-cm-long time-domain reflectometry (TDR) sensors. We also compared TDR and GPR sample areas in a 2-D plane using different GPR survey types and different hyperbola depths. SM measured with TDR and GPR were not significantly different according to Mann–Whitney's test. Our analyses showed that a root mean square error of 0.03 m³ m⁻³ was found between the two methods. In conclusion, the proposed method might be suitable to estimate SM with an acceptable accuracy within the root zone if the soil profile is fairly uniform within the application depth range.     

无水硝酸镁制备过程中的水解特性

在槽式太阳能热发电领域,硝酸镁基熔盐逐渐引起关注。通过六水硝酸镁煅烧法制备无水硝酸镁,采用拉曼、DSC与XRD表征脱水产物,系统研究了环境压力、脱水温度与时间对六水硝酸镁脱水和水解的影响。结果表明,六水硝酸镁在煅烧过程中水解为碱式硝酸镁Mg_3(OH)_4(NO_3)_2,在水溶液中进一步分解为Mg(OH)_2。随着煅烧温度和时间的增加,脱水产物中的含水量逐渐减少,同时水解产物Mg_3(OH)_4(NO_3)_2含量逐渐增加。真空环境下煅烧,可显著降低硝酸镁的水解反应。六水硝酸镁在真空环境下230℃煅烧1.5 h,所制备的无水硝酸镁中水解产物含量为3.63%。制备的硝酸镁可进一步用于硝酸镁基熔盐的研究。     

四川雅安地区古冲积扇主量元素特征及其意义

第四系是与人类生活关系密切的地层,山区地带的第四系主要由河流沉积物组成,这些沉积物的表面风化程度具有重要的环境意义。四川省雅安市地区发育了中更新统砾石层构成的古冲积扇名邛冲积扇和丹思冲积扇,现今废弃于岷江与青衣江之间,遭受了不同程度的侵蚀风化。对两个冲积扇不同位置采集样品,尝试利用主量元素分析冲积扇的风化程度。经过实验发现,主量元素分析可以很好地应用于第四系的测试,砾石间填充的基质砂能够合理反映沉积物经历的风化过程。实验结果表明,沉积物主量元素中长石矿物元素Ca、Na大量流失,而稳定矿物元素Si、Ti等偏高,说明冲积扇经历了长期的风化淋溶作用。A-CN-K图解体现出冲积扇经历了早期的斜长石风化,已经进入以钾长石和伊利石风化为标志的中期阶段。Pettijohn图解表明名邛冲积扇样品含有更多的石英砂岩,沉积物的成熟度较高。这些指标说明名邛冲积扇相比丹思冲积扇经历了更强的风化作用。结合冲积扇的年龄发现,风化速度随年龄的增长呈现减速的特征,体现了风化作用的阶段性.     

Stable carbon isotope signatures of cellulose in macrophytes collected from three eutrophic lakes in China

Aquatic plants are essential for maintaining the diversity and stability of a lake ecosystem. Stable carbon isotopes (δ¹³C) of macrophytes have been widely used as a powerful tool to study ecological processes and paleoenvironmental evolution in lakes. Varying results are obtained when using the δ¹³C of macrophytes to study the changes in the lake environment at different spatio-temporal scales. Thus, sample preparation and subsequent laboratory analyses are crucial for studying environmental changes using the isotopic signal retained in the macrophytes, and are essential for the interpretation of isotope-environment relationships. This study analyzed the δ¹³C of different tissue components of macrophytes in three lakes of the lower Yangtze River basin, and a correlation analysis was performed on aquatic environments influencing the δ¹³C values in the different tissue components of macrophytes. The test results showed the difference between the δ¹³C values of the whole sample and cellulose. Relative analyses indicated that the major factors contributing to the δ¹³C variability in macrophytes were pH and the concentration of dissolved inorganic carbon (DIC). The δ¹³C of α-cellulose (δ¹³C_AC) is more sensitive to environmental variables than that of the whole sample (δ¹³C_W) and holocellulose (δ¹³C_HC). The results of this study imply that extraction of α-cellulose is a prerequisite for research on the changes in lake environment using δ¹³C of macrophytes. This study aims to provide theoretical and data basis for further research on the environmental and ecological change using stable carbon isotopes of aquatic plants.     

关键金属元素分析测试技术方法应用进展

以稀有、稀散、稀土、铂族元素为主体的战略性关键金属矿产资源,在新材料、新能源和信息技术等新兴产业中发挥着越来越关键的作用。随着我国关键矿产资源地质调查的不断深入,关键金属元素以其赋存基体复杂、不同矿物含量差异大、化学性质不稳定等特点对分析测试技术提出了新的挑战。本文根据化学组成不同,对关键金属元素主要赋存基体进行了分类,主要分为硅酸盐、碳酸盐、硫酸盐、钨酸盐、磷酸盐、氧化物、硫化物、卤化物等。对于不同的基体岩石矿物,通常采用酸溶法(硝酸-氢氟酸组合、王水)或碱熔法等传统溶样方法进行化学消解。评述了当前关键金属元素测试常用的电子探针、电感耦合等离子体质谱、电感耦合等离子体发射光谱、X射线荧光光谱等仪器的特点及应用,总结了关键金属元素分析过程中出现的样品难溶解、回收率不完全、测试过程氧化物和同质异位素干扰、样品和标准基体不一致等常见问题,并提出了相应的解决方案。微区原位分析凭借其高效率、低成本、高空间分辨率的优势,以及野外现场分析凭借其简单快速、贴近野外工作的特点是关键金属元素测试技术发展的主要趋势。     

Event-based classification for global study of river flood generating processes

Better understanding of which processes generate floods in a catchment can improve flood frequency analysis and potentially climate change impacts assessment. However, current flood classification methods are either not transferable across locations or do not provide event-based information. We therefore developed a location-independent, event-based flood classification methodology that is applicable in different climates and returns a classification of all flood events, including extreme ones. We use precipitation time series and very simply modelled soil moisture and snowmelt as inputs for a decision tree. A total of 113,635 events in 4155 catchments worldwide were classified into one of five hydro-climatological flood generating processes: short rain, long rain, excess rainfall, snowmelt and a combination of rain and snow. The new classification was tested for its robustness and evaluated with available information; these two tests are often lacking in current flood classification approaches. According to the evaluation, the classification is mostly successful and indicates excess rainfall as the most common dominant process. However, the dominant process is not very informative in most catchments, as there is a high at-site variability in flood generating processes. This is particularly relevant for the estimation of extreme floods which diverge from their usual flood generation pattern, especially in the United Kingdom, Northern France, Southeastern United States, and India.     

地区场选样洪水计算在西部流域应用分析

为采用地区场选样洪水计算方法分析研究建立了西部祖厉河流域设计洪水计算经验公式,设计计算成果经与皮尔逊三型频率曲线设计计算成果比较分析,计算成果精度较高。由此确定了该流域设计洪水计算相关成果图及查算表,为该流域设计洪水计算提供技术支撑。     

熔融制样-X射线荧光光谱法测定电气石中12种主次量元素

电气石是一类含硼的铝硅酸盐矿物,化学成分复杂、化学稳定性强,不易湿法分解,B_2O_3含量较高,导致其主次量元素的同时测定存在一定困难。本文采用熔融法制样,建立了X射线荧光光谱法测定电气石Na_2O、MgO、Al_2O_3、SiO_2、P_2O_5、K_2O、CaO、TiO_2、V_2O_5、Cr_2O_3、MnO、TFe_2O_3等主次量元素的分析方法。样品与四硼酸锂-偏硼酸锂-氟化锂(质量比为4.5∶1∶0.4)混合熔剂的稀释比例为1∶10,消除了粒度效应和矿物效应;在缺少电气石标准物质的情况下,选择土壤、水系沉积物及多种类型的地质标准物质绘制校准曲线,利用含量与电气石类似的标准物质验证准确度,测定结果的相对标准偏差小于4.2%。采用所建方法测定四种不同类型电气石实际样品,测定值与经典化学法基本吻合。本方法解决了电气石不易湿法分解和硼的干扰问题,测定结果准确可靠,与其他方法相比操作简便,分析周期短。     

电感耦合等离子体质谱-X射线衍射法研究云南玉溪和美国内华达地区黏土型锂资源矿物学特征

中国云南玉溪和美国内华达均已发现大量黏土型锂资源,目前关于两地区样品矿物学特征的研究相对不足,而对黏土型锂资源进行充分的矿物学特征研究是锂提取工作开展的重要前提。本文采用X射线荧光光谱、电感耦合等离子体质谱、X射线粉晶衍射、扫描电镜等分析技术,从化学组成、矿物组成、微观形貌等角度对云南玉溪的两个黏土型锂资源样品(YM-1和YM-2)和美国内华达的两个黏土型锂资源样品(Ame-1和Ame-2)进行对比分析。结果表明:玉溪地区和内华达地区样品的锂含量均高于1000μg/g,具有一定的开发利用价值,但这两个地区的黏土型锂资源样品在主要化学成分、矿物组成、微观形貌和锂赋存状态四个方面均存在较大差异。具体来说,(1)主要化学成分差异:玉溪地区样品的主要化学成分为SiO_2和Al_2O_3(硅、铝氧化物总量超过80%),而内华达地区样品的主要化学成分为SiO_2(60.39%)或CaO(42.30%)。(2)矿物组成差异:玉溪地区样品的主要矿物为高岭石和蒙脱石,而内华达地区样品的主要矿物为石英、绿脱石、斯皂石或方解石。(3)微观形貌差异:玉溪地区样品是由表面平坦、边缘圆滑且大小相对均一的片层状结构堆叠而成,而内华达地区样品主要表现为大小不一的块状矿物聚集体。(4)锂赋存状态差异:玉溪地区样品中的锂主要赋存于蒙脱石中,而内华达地区样品中的锂主要赋存于蒙皂石族矿物中。本研究结果基本明确了云南玉溪地区和美国内华达地区黏土型锂资源的矿物学特征,可为这两个地区黏土型锂资源后期的开发利用提供科学依据。