Understanding the occurrence and fate of antibiotics from different categories is vital to predict their environmental exposure and risks. This study presents the spatiotemporal occurrence of 45 ...multi-class antibiotics and their associations with suspended particulate matter (SPM) in Xiaoqing River (XRB) and Yellow River (YRB) via 10-month monitoring in East China. Thirty-five and 31 antibiotics were detected in XRB and YRB, respectively. Among them, fluoroquinolones (FQs) had the highest total mean concentration (up to 24.8 μg/L in XRB and 15.4 μg/L in YRB), followed by sulfonamides (SAs) (14.0 μg/L and 15.4 μg/L) and macrolides (MLs) (1.1 μg/L and 1.6 μg/L). Significant spatial-temporal variations were found in both rivers where higher concentrations of antibiotics were observed in urban and densely populated areas during winter and spring. Hydrological factors such as river flow and water volume, instream attenuation and antibiotic usage may cause the observed variabilities in the seasonal patterns of antibiotic pollution. Using linear regression analysis, for the first time, this study confirmed that the total concentrations of MLs (p < 0.05), FQs (p < 0.001) and SAs (p < 0.001) were strongly correlated with the turbidity/total suspended solids in the studied rivers (except MLs in YRB). It is thus suggested that partitioning processes onto SPM might affect the distribution of detected antibiotics in rivers, which are largely dependent on SPM composition and characteristics. The risk quotient (RQ) determined for up to 87 % of individual compound was below 0.1 in both rivers; however, the high joint toxicity reflected by the mixed RQs of detected antibiotics may rise risk alarm for aquatic species. Further aspects regarding active mechanisms of SPM-antibiotic interactions and ecological risks of coexistence of multiple antibiotics need to be investigated.
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•More than thirty multi-class antibiotics were detected at high concentrations and frequencies in river water.•Seasonal variabilities were related to antibiotic usage, removal rate, and hydrology.•SPM bound pollutant was obtained via regressions of turbidity vs. total antibiotics.•Partitioning processes are correlated with the SPM characteristics and compositions.•Antibiotic mixtures posed extremely high joint risks to aquatic species.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Moments of rainfall spatial variability, which quantify how flood response time scales are affected when spatially variable rainfall is considered, compared to when rainfall is spatially uniform, ...have been suggested as a useful tool for forecasters to guide their choice between lumped or distributed rainfall information for runoff modelling. However, the approaches used to evaluate the validity of moments suffer from limitations. Hence, we adopt a novel approach for their evaluation by comparing moments to the relationship between observed hydrograph characteristics generated by spatially variable and by uniform rainfall events in the same catchment. We further investigate the usefulness of moments by testing whether the performance of a lumped hydrological model for events classified by moments as spatially variable is lower than for uniform events. Results confirmed that moments can identify spatially variable events and characterize differences in hydrograph features compared to uniform events, providing a useful tool for forecasters.
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•Light interception by smallholder crops can be monitored accurately with digital camera images taken from just above the crop or with UAV derived indices.•Ground cover derived from UAV or digital ...images explained up to 74–78% of within-field variation in relative yield and relative yield response to fertility treatments.•Relationships between light interception, relative yield and yield response to fertility treatments were strongly affected by between-field variability.•Differences in within-field spatial variability between fields were related to catena position and may be used as an indicator for soil responsiveness and fertility.•Combinations of vertical photographs or high-resolution, remotely sensed vegetation indices with crop growth models will improve the accuracy of yield and crop production assessments.
Agricultural intensification and efficient use and targeting of fertilizer inputs on smallholder farms is key to sustainably improve food security. The objective of this paper is to demonstrate how high-resolution satellite and unmanned aerial vehicle (UAV) images can be used to assess the spatial variability of yield, and yield response to fertilizer. The study included 48 and 50 smallholder fields monitored during the 2014 and 2015 cropping seasons south-east of Koutiala (Mali), cropped with the five major crops grown in the area (cotton, maize, sorghum, millet and peanuts). Each field included up to five plots with different fertilizer applications and one plot with farmer practice. Fortnightly, in-situ in each field data were collected synchronous with UAV imaging using a Canon S110 NIR camera. A concurrent series of very high-resolution satellite images was procured and these images were used to mask out trees. For each plot, we calculated vegetation index means, medians and coefficients of variation. Cross-validated general linear models were used to assess the predictability of relative differences in crop yield and yield response to fertilizer, explicitly accounting for the effects of fertility treatments, between-field and within-field variabilities. Differences between fields accounted for a much larger component of variation than differences between fertilization treatments.
Vegetation indices from UAV images strongly related to ground cover (R2 = 0.85), light interception (R2 = 0.79) and vegetation indices derived from satellite images (R2 values of about 0.8). Within-plot distributions of UAV-derived vegetation index values were negatively skewed, and within-plot variability of vegetation index values was negatively correlated with yield. Plots on shallow soils with poor growing conditions showed the largest within-plot variability. GLM models including UAV derived estimates of light interception explained up to 78% of the variation in crop yield and 74% of the variation in fertilizer response within a single field. These numbers dropped to about 45% of the variation in yield and about 48% of the variation in fertilizer response when lumping all fields of a given crop, with Q2 values of respectively 22 and 40% respectively when tested with a leave-field-out procedure. This indicates that remotely sensed imagery doesn’t fully capture the influence of crop stress and management. Assessment of crop fertilizer responses with vegetation indices therefore needs a reference under similar management. Spatial variability in UAV-derived vegetation index values at the plot scale was significantly related to differences in yields and fertilizer responses. The strong relationships between light interception and ground cover indicate that combining vertical photographs or high-resolution remotely sensed vegetation indices with crop growth models allows to explicitly account for the spatial variability and will improve the accuracy of yield and crop production assessments, especially in heterogeneous smallholder conditions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In ...comparison to their predecessors, the new methods allow for a more robust bias adjustment of extreme values, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling. The new statistical downscaling method is stochastic and better at adjusting spatial variability than the old interpolation method. Improvements in bias adjustment and trend preservation are demonstrated in a cross-validation framework.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The surrogate models become increasingly used in slope reliability problems, in which the expensive-to-evaluate slope deterministic analysis model is replaced with the cheap-to-evaluate surrogate ...model. However, the surrogate models are frequently criticized in spatially variable soil slopes where a large number of random variables are involved and establishment of the surrogate model requires extensive evaluations of the slope deterministic model. To address this issue, this paper proposed a novel dimension reduction-based metamodel approach for efficient slope reliability analysis, abbreviated as SBR-SRS-MGPR because it contains three steps: (a) using the novel slice method-based dimension reduction (SBR) to reduce the input variables’ dimension; (b) using the strength reduction sampling (SRS) technique to expand the training samples; and (c) training the multiple Gaussian process regression (MGPR) model to approximate the slope deterministic model. The Monte Carlo simulation (MCS) is then used to estimate the probability of failure (pf) of slope system based on the well-constructed MGPR model. Two slope examples are employed to demonstrate the performance of the proposed method. The results show that the proposed method outperforms the previous surrogate model-based methods in terms of computational efficiency with fewer number of slope stability analysis and simultaneously gives smaller uncertainty of the estimated pf.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The precipitation concentration index (PCI) is a powerful indicator for temporal precipitation distribution and is also very useful for the assessment of seasonal precipitation changes. The primary ...objectives of this study are to investigate and analyse the temporal–spatial variability patterns of annual and seasonal PCI values based on monthly precipitation data. These data were collected from 597 meteorological stations located throughout China, for the time period of 1960–2016, and were used to assess the impacts of geographical parameters (latitude, longitude, and altitude) on the PCI. Additionally, the possible teleconnection with the large‐scale circulation pattern was investigated. Our results reveal that the variation trend of annual PCI values has decreased significantly at a rate of −.234/10 year (α = .01) in China over the past 57 years. For all studied station records, 434 (72.7%) stations showed decreasing trends of PCI values, and these stations are distributed over large areas in China. On an annual scale, the average PCI value ranged from 11 in Hunan province to 44 in Qinghai province. The precipitation concentration in China can be described as strongly irregular in the western and northern parts of the northwest and in the northern region of the Tibetan Plateau, while it is irregular in the southwest and the north of China, and moderately irregular in some parts of the middle‐lower regions of the Yangtze River and southern China. The regularity of the annual precipitation pattern significantly decreased in spring, autumn, and winter from southeastern to northwestern China, and was the most in winter. However, the summer precipitation dispersion and the pattern in the considered period were more regular than those of the other seasons. Furthermore, changes in the PCI appear to be rather complex and possibly related to global atmospheric characteristics as well as geographical factors (latitude, longitude, and altitude). The results presented in this study indicate that the PCI is an essential feature for water resource planning, prediction of risk due to droughts or floods, and the management of natural resources.
Various characteristics of precipitation concentration index and its possible teleconnection with atmospheric circulation patterns in China between 1960 and 2016.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
In an urbanization process, infrastructure elements such as tunnels and deep excavations are widely used to service the development of cities. Owing to the lengthy geological processes of ...geomaterials and the limited availability of site-specific test data, soil and rock properties exhibiting spatial variability are frequently encountered in geological and geotechnical engineering. This paper presents a comprehensive review of the application of spatial variability in tunneling and deep excavation over the past 20 years. It is found that the spatial variability is generally modeled as a random field (RF) in finite element software, based on random field theory (RFT). This model has been widely used in the design, stability evaluation, and probabilistic analysis of tunnels and excavations. Previous works have proven that the performance of tunnels and deep excavations can be better captured by considering the spatial variability, as compared with conventional deterministic analysis methods. Nonetheless, current research still faces many factual scientific problems. Therefore, this paper also identifies some research gaps, as well as recommendations for further investigations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Catchment baseflow is jointly controlled by climate and landscape properties. Previous studies have recognized that spatial variability of mean annual baseflow coefficient (BFC = Qb/P, ratio of ...baseflow to precipitation) is primarily controlled by aridity index and storage capacity. However, an analytical solution of BFC in terms of the dominant controlling factors has not yet been established. The objective of this study was to develop an analytical BFC curve to depict spatial variability of BFC based on the “limit” concept of the Budyko framework. The BFC curve relates the baseflow coefficient to aridity index and storage capacity without resolving complex interactions between evapotranspiration and baseflow generation. The proposed BFC curve showed that, in the arid catchments, baseflow coefficient was primarily limited by available water (precipitation, P) and, in the humid catchments, was jointly controlled by both the available energy (potential evapotranspiration, Ep) and catchment retention capability (ratio of catchment storage capacity to P, i.e., Sp/P). Observed hydrological data from 950 catchments in Australia, the conterminous United States and the United Kingdom with diverse hydro‐climatic conditions (BFC = 0.001–0.650) were collected to demonstrate the capability of the developed curve. Results showed that the BFC curve captured the spatial variability of observed BFC in the 950 study catchments (R2 = 0.75, RMSE = 0.058). Mean annual baseflow estimated by the BFC curve agreed well with observed baseflow (R2 = 0.86, RMSE = 0.19 mm). The developed analytical curve provides an analytical solution for understanding how aridity index and storage capacity control mean annual catchment baseflow, and will improve predictability of baseflow at ungauged basins.
Key Points
An analytical curve was established to depict the spatial variability of mean annual baseflow based on the Budyko “limit” framework
The curve directly relates aridity index and storage capacity (Sp) to estimate baseflow and shows dominant control of Sp in humid catchments
The developed curve performed well with observed data from 950 catchments located in the Australia, CONUS and UK
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Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to ...sparse or non‐existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite‐based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite‐based rainfall products with relatively high spatial and temporal resolutions and quasi‐global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10‐day) and monthly time‐scales. The evaluation was done by comparing the satellite products with rain‐gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time‐scales, while TAMSAT performed better at the daily time‐scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.
The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are evaluated over East Africa by comparing with rain‐gauge data from about 1,200 stations as well as with other similar satellite products (the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT)). The above figure compares the skill (Eff) for different satellite products. The grey scale in the background is elevations in metres.
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Data from 38,105 wells were used to characterize fluoride (F) occurrence in untreated United States (U.S.) groundwater. For domestic wells (n = 11,032), water from which is generally not purposely ...fluoridated or monitored for quality, 10.9% of the samples have F concentrations >0.7 mg/L (U.S. Public Health Service recommended optimal F concentration in drinking water for preventing tooth decay) (87% are <0.7 mg/L); 2.6% have F > 2 mg/L (EPA Secondary Maximum Contaminant Level, SMCL); and 0.6% have F > 4 mg/L (EPA MCL). The data indicate the biggest concern with F in domestic wells at the national scale could be one of under consumption of F with respect to the oral-health benchmark (0.7 mg/L). Elevated F concentrations relative to the SMCL and MCL are regionally important, particularly in the western U.S. Statistical comparisons of potentially important controlling factors in four F-concentration categories (<0.1–0.7 mg/L; >0.7–2 mg/L; >2–4 mg/L; >4 mg/L) at the national scale indicate the highest F-concentration category is associated with groundwater that has significantly greater pH values, TDS and alkalinity concentrations, and well depths, and lower Ca/Na ratios and mean annual precipitation, than the lowest F-concentration category. The relative importance of the controlling factors appears to be regionally variable. Three case studies illustrate the spatial variability in controlling factors using groundwater-age (groundwater residence time), water-isotope (evaporative concentration), and water-temperature (geothermal processes) data. Populations potentially served by domestic wells with F concentrations <0.7, >0.7, >2, and >4 mg/L are estimated to be ~28,200,000, ~3,110,000; ~522,000; and ~172,000 people, respectively, in 40 principal aquifers with at least 25 F analyses per aquifer.
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•Data from 38,105 wells used to characterize F occurrence in U.S. groundwater.•85–87% of F concentrations are below the 0.7 mg/L oral-health benchmark.•Multiple factors control F concentrations in groundwater.•Three case studies illustrate processes that produce elevated F concentrations.•~28,200,000 people potentially served by domestic wells with F < 0.7 mg/L.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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