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1.
We introduce the freely available web-based Water in an Agricultural Landscape—NUčice Database (WALNUD) dataset that includes both hydrological and meteorological records at the Nučice experimental catchment (0.53 km2), which is representative of an intensively farmed landscape in the Czech Republic. The Nučice experimental catchment was established in 2011 for the observation of rainfall–runoff processes, soil erosion processes, and water balance of a cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9%, and the climate is humid continental (mean annual temperature 7.9°C, annual precipitation 630 mm). The catchment is drained by an artificially straightened stream and consists of three fields covering over 95% of the area which are managed by two different farmers. The typical crops are winter wheat, rapeseed, and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed across the basin, and a flume with an H-type facing that is used to monitor stream discharge, water turbidity, and basic water quality indicators. Additionally, the groundwater level and soil water content at various depths near the stream are recorded. Recently, large-scale soil moisture monitoring efforts have been introduced with the installation of two cosmic-ray neutron sensors for soil moisture monitoring. The datasets consist of observed variables (e.g. measured precipitation, air temperature, stream discharge, and soil moisture) and are available online for public use. The cross-seasonal, open access datasets at this small-scale agricultural catchment will benefit not only hydrologists but also local farmers.  相似文献   
2.
Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western United States where ID thresholds for post-wildfire debris flows are well established, namely the Transverse Ranges of southern California. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within five burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm h−1 lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-min rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern California may be attributed, in large part, to differences in the hydraulic properties of burned soils. © 2019 John Wiley & Sons, Ltd.  相似文献   
3.
The simultaneous transfer of pore fluid and vapour was studied in the unsaturated shallow subsurface of a Plio-Pleistocene marine mudstone badland slope in southwestern Taiwan during the dry season using field monitoring data and numerical simulations. Data from field monitoring show mass-basis water contents of ~0.05 to ~0.10 that decrease towards the unsaturated ground surface and were invariant during the middle part of the dry season, except for daily fluctuations. In addition, the observed daily fluctuations in water content correlate with fluctuations in bedrock temperature, especially at depths of 2.5–5.0 cm. Periodic increases in water content occurred most notably during the day, when the bedrock temperature showed the greatest increase. Water contents then decreased to the previous state as bedrock temperature decreased during the night. Calculated vapour fluxes within the mudstone during the day increased up to 6 × 10−6–1 × 10−5 kg m−2 s−1, deriving a 0.01–0.02 increase in mass-basis water content at 2.5 cm depth for a 12-h period. This agrees with field monitoring data, suggesting that increases in water content occurred due to vapour intrusions into the bedrock. Pore water electrical conductivity (EC) showed periodic variations due to vapour intrusion, and gradually increased between the ground surface and depths of 2.5–5.0 cm. In contrast, pore water EC gradually decreased between 15 and 40 cm depth. Calculated water fluxes at depths of 2.5–40.0 cm varied from −4 × 10−6 to −2 × 10−9 kg m−2 s−1. These fluxes generated an increase in solute concentrations at the ground surface, with negative values of water flux indicating an upwards movement of water towards the surface. We show that the increase in solute content due to solute transfer from depth is highly dependent on variations in water flux with depth. © 2020 John Wiley & Sons, Ltd.  相似文献   
4.
Base flows are important for tropical regions with pronounced dry seasons, which are facing increasing water demands. Base flow generation, however, is one of the most challenging hydrological processes to characterize in the tropics. In many years during the May–December wet season in the Panama Canal Watershed (PCW), base flows in rivers abruptly increase. This increase persists until the start of the December–April dry season. Understanding this unusual base flow jump (BFJ) behaviour is critical to improve water provisioning in the seasonal tropics, especially during droughts and extended dry seasons. This study developed an integrated approach combining piecewise regression on cumulative average base flow and sensitivity analysis to calculate the timing and magnitude of BFJ. Rainfall, forest cover, mean land surface slope, catchment area, and estimated subsurface storage were tested as predictors for the occurrence and magnitude of the BFJs in seven subcatchments of the PCW. Sensitivity analysis on correlated predictors allowed ranking of predictor contributions due to isolated and cross-correlation effects. Correlations between observed BFJs and BFJs predicted by watershed and rainfall-related predictors were 0.92 and 0.65 for BFJ timing and magnitude, respectively. Forest cover was the second most significant predictor after cumulative rainfall for jump magnitude, owing to larger subsurface storage and groundwater recharge in forests than pastures. Catchments in the mountainous eastern PCW always generated larger jumps due to their higher rainfall and greater forest cover than the western PCW catchments. The cross-correlations between predictors contributed to more than 50% of the jump variances. The results demonstrate the importance of rainfall gradient and catchment characteristics in affecting the sudden and sustained BFJs, which can help inform land management decisions intended to enhance water supplies in the tropics. This study underscores the need for more research to further understand the hydrological processes involved in the BFJ phenomenon, including better BFJ models and field characterizations, to help improve tropical ecosystem services under a changing environment.  相似文献   
5.
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.  相似文献   
6.
7.
Time series of hydrogen and oxygen stable isotope ratios (δ2H and δ18O) in rivers can be used to quantify groundwater contributions to streamflow, and timescales of catchment storage. However, these isotope hydrology techniques rely on distinct spatial or temporal patterns of δ2H and δ18O within the hydrologic cycle. In New Zealand, lack of understanding of spatial and temporal patterns of δ2H and δ18O of river water hinders development of regional and national-scale hydrological models. We measured δ2H and δ18O monthly, together with river flow rates at 58 locations across New Zealand over a two-year period. Results show: (a) general patterns of decreasing δ2H and δ18O with increasing latitude were altered by New Zealand's major mountain ranges; δ2H and δ18O were distinctly lower in rivers fed from higher elevation catchments, and in eastern rain-shadow areas of both islands; (b) river water δ2H and δ18O values were partly controlled by local catchment characteristics (catchment slope, PET, catchment elevation, and upstream lake area) that influence evaporation processes; (c) regional differences in evaporation caused the slope of the river water line (i.e., the relationship between δ2H and δ18O in river water) for the (warmer) North Island to be lower than that of the (cooler, mountain-dominated) South Island; (d) δ2H seasonal offsets (i.e., the difference between seasonal peak and mean values) for individual sites ranged from 0.50‰ to 5.07‰. Peak values of δ18O and δ2H were in late summer, but values peaked 1 month later at the South Island sites, likely due to greater snow-melt contributions to streamflow. Strong spatial differences in river water δ2H and δ18O caused by orographic rainfall effects and evaporation may inform studies of water mixing across landscapes. Generally distinct seasonal isotope cycles, despite the large catchment sizes of rivers studied, are encouraging for transit time analysis applications.  相似文献   
8.
针对悬臂柱顶有拉梁和无拉梁层间隔震体系的抗震性能问题,运用增量动力分析(IDA)方法进行弹塑性分析,模拟结构从弹性到弹塑性直至最后倒塌的全过程。通过调幅地震动得到相应的层间位移角及峰值加速度,分别绘制单条与多条IDA曲线分析拉梁对隔震结构动力响应的影响,研究两种结构的抗震性能。结果表明:在相同性能点,有拉梁和无拉梁对纤维铰弯矩值和曲率值基本无影响,而在不同性能点,纤维铰状态明显不同;两种体系从正常使用阶段到防止倒塌阶段所需的加速度峰值的差距慢慢增大;在极罕遇地震下,柱顶有拉梁层间隔震体系的下部结构抗震性能要高于柱顶无拉梁层间隔震体系。  相似文献   
9.
通过对电磁监测试验卫星地面对比观测原型系统中古丰、寺滩和坪城地电场观测数据特征研究,结果表明:(1)3个台站的地电场观测数据均具有较为明显的正常日变化形态;(2)在磁暴发生期间,地电场各测向均记录到了同步的地电暴变化,其最大变幅均明显高于正常日变;(3)寺滩地电场记录到临震前的数据异常现象,在时间和空间上都与地震事件吻合较好。  相似文献   
10.
Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   
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