Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China.

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies. In this study, we comprehensively investigated the combined effects of multiple large-scale atmospheric circulation patterns on precipitation changes in China. Specifically, Pearson correlation analysis and Partial Wavelet Coherence (PWC) were used to identify the primary teleconnection factors influencing precipitation dynamics. Furthermore, we used the cross-wavelet method to elucidate the temporal lag and periodic relationships between multiple teleconnection factors and their interactions. Finally, the multiple wavelet coherence analysis method was used to identify the dominant two-factor and three-factor combinations shaping precipitation dynamics. This analysis facilitated the quantification and determination of interaction types and influencing pathways of teleconnection factors on precipitation dynamics, respectively. The results showed that: (1) the Atlantic Multidecadal Oscillation (AMO), EI Niño-Southern Oscillation (ENSO), East Asia Summer Monsoon (EASM), and Indian Ocean Dipole (IOD) were dominant teleconnection factors influencing Standardized Precipitation Index (SPI) dynamics; (2) significant correlation and leading or lagging relationships at different timescales generally existed for various teleconnection factors, where AMO was mainly leading the other factors with positive correlation, while ENSO and Southern Oscillation (SO) were mainly lagging behind other factors with prolonged correlations; and (3) the interactions between teleconnection factors were quantified into three types: enhancing, independent and offsetting effects. Specifically, the enhancing effect of two-factor combinations was stronger than the offsetting effect, where AMO + NAO (North Atlantic Oscillation) and AMO + AO (Atlantic Oscillation) had a larger distribution area in southern China. Conversely, the offsetting effect of three-factor combinations was more significant than that of the two-factor combinations, which was mainly distributed in northeast and northwest regions of China. This study sheds new light on the mechanisms of modulation and pathways of influencing various large-scale factors on seasonal precipitation dynamics.

Meteorological drought migration characteristics based on an improved spatiotemporal structure approach in the Loess Plateau of China.

The development of drought has spatial and temporal synchronization. Previous studies usually explore the spatial and temporal evolution of drought separately. Moreover, existing approaches are based on a fixed overlapping area and do not consider the variable drought cluster area during development. This study proposes an improved and simple approach to derive dynamic overlapping area threshold for 3-dimensional droughts extraction. Based on the one monthly Nonparametric Standardized Precipitation Index (NSPI), this improved approach was applied for investigating the migration characteristics of meteorological drought events in the Loess Plateau of China. Then, Random Forest and Extreme Gradient Boosting model with Shapley additive explanation values were used to quantify the importance of driving factors on the dynamics of drought characteristics. The results showed that: (1) the improved approach has a better performance on identifying prolonged droughts than the method using a fixed overlap area threshold; (2) spatially, meteorological drought events with high severity (DS), long duration (DD), large effected area (DA) and fast migration velocity (DV) mainly occur in the central region; (3) temporally, droughts are expected to aggravate with significantly increased DS and DA which are mainly caused by increased temperature and vegetation; and (4) meteorological droughts have a preferred westward migration direction and three dominant migration paths, which are crucial for local drought prevention and control. The findings of this study provide new perspectives on drought migration characteristics, which are important for the exploration of drought-driven mechanisms, risk assessment and future prediction.

Insights from CMIP6 SSP scenarios for future characteristics of propagation from meteorological drought to hydrological drought in the Pearl River Basin.

Drought is a common and widely distributed natural hazard. Analyzing and predicting drought characteristics and propagation are important for the early warning, prevention, and mitigation of drought disasters. This study used the precipitation and runoff outputs from General Circulation Models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) to evaluate the meteorological drought (MD) and hydrological drought (HD) characteristics in the Pearl River Basin (PRB) under two Shared Socioeconomic Pathways (SSPs) (i.e., SSP2-4.5 and SSP5-8.5). The propagation characteristics of external propagation (response between different type of drought) and internal propagation (drought development and recovery stages of a single type of drought) were also comprehensively investigated based on CMIP6. The results revealed that: 1) the percentage of grids within the dry range of MD and HD will decrease from the historical period to the future period under the two scenarios. The PRB is projected to exhibit wetter patterns; 2) Higher emission scenarios (SSP5-8.5) are more likely to weaken dryness conditions; 3) regarding the external propagation, the drought response time from MD to HD would be 2 months, and there would be no significant change under two scenarios; and 4) regarding the internal propagation, during three study periods (1971-2010, 2021-2060 and 2061-2100), the MD (HD) average recovery time changed from 3.90 (3.36) to 3.75 (3.41) and then to 3.95 (3.43) months under the SSP2-4.5 scenario, and changed from 3.93 (3.46) to 3 (3.51) and then to 3.7 (3.25) months under the SSP5-8.5 scenario. These results aid in understanding future drought characteristics and drought propagation under climate change.

Precipitation and vegetation transpiration variations dominate the dynamics of agricultural drought characteristics in China.

Agricultural drought posing a significant threat to agricultural production is subject to the complex influence of ocean, terrestrial and meteorological multi-factors. Nevertheless, which factor dominating the dynamics of agricultural drought characteristics and their dynamic impact remain equivocal. To address this knowledge gap, we used ERA5 soil moisture to calculate the standardized soil moisture index (SSI) to characterize agricultural drought. The extreme gradient boosting model was then adopted to fully examine the influence of ocean, terrestrial and meteorological multi-factors on agricultural drought characteristics and their dynamics in China. Meanwhile, the Shapley additive explanation values were introduced to quantify the contribution of multiple drivers to drought characteristics. Our analysis reveals that the drought frequency, severity and duration in China ranged from 5-70, 2.15-35.02 and 1.76-31.20, respectively. Drought duration is increasing and drought intensity is intensifying in southeast, north and northwest China. In addition, potential evapotranspiration is the most significant driver of drought characteristics at the basin scale. Regarding the dynamic evolution of drought characteristics, the percentages of raster points for drought duration and severity with evapotranspiration as the dominant factor are 30.7 % and 32.7 %, and the percentages with precipitation are 35.3 % and 35.0 %, respectively. Precipitation in northern regions has a positive effect on decreasing drought characteristics, while in southern regions, evapotranspiration dominates the dynamics in drought characteristics due to increasing vegetation transpiration. Moreover, the drought severity is exacerbated by the Atlantic Multidecadal Oscillation in the Yangtze and Pearl River basins, while the contribution of the North Atlantic Oscillation to the drought duration evolution is increasing in the Yangtze River basin. Generally, this study sheds new insights into agricultural drought evolution and driving mechanism, which are beneficial for agricultural drought early warning and mitigation.

An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification.

BACKGROUND AND OBJECTIVE: Lung cancer has the highest cancer-related mortality worldwide, and lung nodule usually presents with no symptom. Low-dose computed tomography (LDCT) was an important tool for lung cancer detection and diagnosis. It provided a complete three-dimensional (3-D) chest image with a high resolution.Recently, convolutional neural network (CNN) had flourished and been proven the CNN-based computer-aided diagnosis (CADx) system could extract the features and help radiologists to make a preliminary diagnosis. Therefore, a 3-D ResNeXt-based CADx system was proposed to assist radiologists for diagnosis in this study. METHODS: The proposed CADx system consists of image preprocessing and a 3-D CNN-based classification model for pulmonary nodule classification. First, the image preprocessing was executed to generate the normalized volumn of interest (VOI) only including nodule information and a few surrounding tissues. Then, the extracted VOI was forwarded to the 3-D nodule classification model. In the classification model, the RestNext was employed as the backbone and the attention scheme was embedded to focus on the important features. Moreover, a multi-level feature fusion network incorporating feature information of different scales was used to enhance the prediction accuracy of small malignant nodules. Finally, a hybrid loss based on channel optimization which make the network learn more detailed information was empolyed to replace a binary cross-entropy (BCE) loss. RESULTS: In this research, there were a total of 880 low-dose CT images including 440 benign and 440 malignant nodules from the American National Lung Screening Trial (NLST) for system evaluation. The results showed that our system could achieve the accuracy of 85.3%, the sensitivity of 86.8%, the specificity of 83.9%, and the area-under-curve (AUC) value was 0.9042. It was confirmed that the designed system had a good diagnostic ability. CONCLUSION: In this study, a CADx composed of the image preprocessing and a 3-D nodule classification model with attention scheme, feature fusion, and hybrid loss was proposed for pulmonary nodule classification in LDCT. The results indicated that the proposed CADx system had potential for achieving high performance in classifying lung nodules as benign and malignant.

Time-scale dependent mechanism of atmospheric CO2 concentration drivers of watershed water-energy balance.

The elevated atmospheric carbon dioxide concentration (CO2), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO2 influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined. Subsequently, the Empirical Mode Decomposition method was applied to explore the impact of CO2 on watershed water-energy balance dynamics at multiple time scales. Results indicate that (1) in the context of warming and drying condition, annual n series in the WRB displays a significantly increasing trend, while that in the JRB and BLRB presents non-significantly decreasing trends; (2) the non-stationary n series was divided into 3-, 7-, 18-, exceeding 18-year time scale oscillations and a trend residual. In the WRB and BLRB, the overall variation of n was dominated by the residual, whereas in the JRB it was dominated by the 7-year time scale oscillation; (3) the relationship between CO2 concentration and n series was significant in the WRB except for 3-year time scale. In the JRB, CO2 concentration and n series were significantly correlated on the 7- and exceeding 7-year time scales, while in the BLRB, such a significant relationship existed only on the 18- and exceeding 18-year time scales. (4) CO2-driven temperature rise and vegetation greening elevated the aridity index and evaporation ratio, thus impacting watershed water-energy balance dynamics. This study provided a deeper explanation for the possible impact of CO2 concentration on the watershed hydrological processes.

Watershed water-energy balance dynamics and their association with diverse influencing factors at multiple time scales.

The Budyko parameter, which controls the shape of Budyko curve, represents the superimposed impact of various periodic factors (including climatic factors, catchment characteristics, large-scale climate patterns, solar activity and anthropogenic activity) on the watershed water-energy balance dynamics. However, this superimposition is not conducive to identifying the drivers of Budyko parameter dynamics at different time scales, and thus affects parameter estimation. Here we obtain the Budyko parameter ω in the Fu's equation (one form of the Budyko framework) for the Wei River Basin (WRB), and then adopt the Empirical Mode Decomposition method to reveal the relationships between factors and ω series at multiple time scales by considering the interplay among different influencing factors. Results indicate that (1) ω series are decomposed into 4-, 12-, 20-, exceeding 20-year time scale oscillations and a residual component with an significantly increasing trend in the mainstream of the WRB, a non-significantly decreasing trend in the Jing River Basin and Beiluo River Basin; (2) by analyzing the residual trend component, evaporation ratio, soil moisture and effective irrigated area are found to induce the significant increase of ω in the upstream of the WRB, whereas that in the middle and lower reaches is dominated by baseflow and Niño 3.4; (3) ω dynamics at the 4-year time scale is dominated by evaporation ratio, aridity index, baseflow and soil moisture; baseflow, Pacific Decadal Oscillation (PDO) and sunspots attribute to the dynamics at 12-year time scale; all the factors except baseflow and soil moisture contribute to the dynamics at 20- or exceeding 20-year time scales. The results of this study will help identify the connection between watershed water-energy balance dynamics and changing environment at multiple time scales, and also be beneficial for guiding water resources management and ecological development planning on the Loess Plateau.

Propagation thresholds of meteorological drought for triggering hydrological drought at various levels.

What the extent of meteorological drought could trigger the corresponding hydrological drought with different levels? This question is an important topic in the field of drought propagation, which however has not been resolved. Therefore, a novel model based on a Bayesian network was proposed to address this issue in this study. In this model, the drought pooling and excluding methods were applied to eliminate minor drought events. A drought matching approach based on drought propagation time was proposed to achieve the one by one matching between different types of drought. Moreover, based on the matched drought events and the copula-based conditional probability model, the drought propagation thresholds of meteorological drought for triggering hydrological drought at various levels were determined. In addition, the interval conditional probability was calculated to further explore the sensitivity of hydrological drought response to different meteorological drought conditions. Furthermore, the propagation ratio was proposed to characterize the differences of drought propagation threshold among various regions. The Wei River Basin was selected as a case study. Results indicated that the results of drought propagation threshold were reliable and accurate. The increase of interval conditional probability showed a typical S-curve, which can intuitively obtain the probability of hydrological drought occurrence at different levels under specific meteorological drought condition, so as to effectively guide drought preparedness and mitigation. The propagation ratio can describe the overall resistance of the basin to meteorological drought, and it mainly depended on the meteorological and underlying surface conditions as well as groundwater supply.

Recent changes in county-level maize production in the United States: Spatial-temporal patterns, climatic drivers and the implications for crop modelling.

Despite the fact that it is the total crop production that shapes future food supply rather than one of its single component, previous studies have mainly focused on the changes in crop yield. It is possible that recent gains in crop production are mainly due to improvement of yield rather than growth of harvest area. However, it remains unclear about the geographical patterns of their relative contributions at fine scales and the possible mechanisms. Analysis of US maize production shows that maize production has increased significantly at a rate of 2.1%/year during 1980-2010. Although yield is the dominant factor contributing to production growth for the country as a whole, the importance of harvest area has become more evident with time. In 56% of US's maize growing counties, harvest area has also contributed more than yield to production changes. High spatial correlation between the change rates of harvest area and production is observed (R = 0.96), while a weak relation (R = 0.21) is found between the spatial patterns of yield and production. This suggests that harvest area has exerted the dominant role in modulating the spatial distribution pattern of maize production changes. Further analysis suggests that yield and harvest area respond differently to climate variability, which has great implications for adaptation strategies. Comparing 11 state-of-the-art crop model simulations against census data reveals large bias in the simulated spatial patterns of maize production. Nevertheless, such bias can be reduced substantially by incorporating the observed dynamics of harvest area, pointing to a potential pathway for future model improvement. This study highlights the importance of accounting for harvest area dynamics in assessing agricultural production empirically or with crop models.

Assessing the non-stationarity of low flows and their scale-dependent relationships with climate and human forcing.

It is necessary to assess the non-stationarity of a hydrological series under changing environments. This study aimed to determine the validity of the stationarity of low flow series in terms of trends and possible change points, as well as the time-scale that is responsible for the production of trends and change points in low flow series. Further, we investigated how climatic variables affect low flow variations by studying their scale-dependent relationships. The modified Mann-Kendall trend test, heuristic segmentation method, discrete wavelet transform, and Pearson correlation coefficient were co-utilized to achieve these objectives. The Wei River Basin (WRB), a typical Loess Plateau region in China, was selected as the case study. Results showed significantly decreasing trends and change points in the low flow series, indicating that its stationarity assumption is invalid. The 2-year and 4-year events were the most important time-scales contributing to the trend of the original low flow series, and the 8-year periodic scale was the most influential frequency component for change point generation. Additionally, the strongest scale-dependent relationships among high frequency components (2-year and 4-year scales) of the low flow series and climatic variables (precipitation, potential evaporation, and soil moisture) demonstrated the importance of climatic factors for driving the trends of a low flow series. In contrast, human activities, including water withdrawals and water and soil conservation projects showed strong influences on the non-stationarity of low flows via affecting the low frequency component (8-year frequency and approximate components). These findings contribute to a better understanding temporal variations of low flow and their responses to changing environments, and the results also would be helpful for local water resources management as well as agricultural and ecological sustainable development.

Deeply seeing through highly turbid water by active polarization imaging.

We hereby proposed and experimentally demonstrated an active polarization imaging technique, based on wavelength selection, for seeing through highly turbid water where targets are always visually lost. The method was realized by making use of the dependence of light scattering on wavelength in turbid water. Red light illumination was selected to minimize scattering occurring in light propagation and to guarantee accurate estimation of degree of polarization. Experiments demonstrate its contribution to turn targets in highly turbid water from "undetectable" to "detectable."

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin.

The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970.

Effects of soil organic matter and ageing on remediation of diesel-contaminated soil.

Bioremediation of diesel-contaminated soil was investigated for the effects of soil organic matter (SOM) and ageing time in two sets of experiments (Batch I and II, respectively). This study examined degradation efficiency in soil artificially contaminated with diesel oil (maximum total petroleum hydrocarbons (TPH) concentration of 9000 mg/kg soil). Batch I data showed that the values of the first-order degradation rate, k, were relatively high in the low-SOM soil batches. The quantity of SOM negatively correlated with the TPH degradation rates and with the total TPH degradation efficiency (%). Introduction of rhamnolipid to the soil proved to be a useful solution to resolve the problem of the residual TPH in the soil with high SOM. In Batch II, the k values decreased with the length of ageing time: 0.0245, 0.0128 and 0.0090 l/d in samples ST0 (freshly contaminated), ST38 (aged for 38 days) and ST101 (aged for 101 days), respectively. The TPH degradation efficiency (%) also decreased along with the ageing time. The research also applied molecular technology to analyse the bacterial community dynamics during the bioremediation course. Multivariate statistics based on terminal-restriction fragment length data indicated: 1) the soils with different SOM resulted in separate bacterial community structures, 2) ageing time created a variety of bacterial communities, 3) the bacterial community dynamics was associated with the hydrocarbon consumption. The SOM content in soils affected the TPH degradation rate and efficiency and the bacterial community structures. Aged soil is more difficult to remediate than freshly contaminated soil, and the resulting bacterial community was less dynamic and showed a lack of succession.