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Herein, we describe how computational mechanistic understanding has led directly to the discovery of new 2H‐phosphindole for C−CAr bond activation and dearomatization reaction. We uncover an unexpected intramolecular C−H bond activation with a 2H‐phosphindole derivative. This new intriguing experimental observation and further theoretical studies led to an extension of the reaction mechanism with 2H‐phosphindole. Through DFT calculations, we confirm that within a five‐membered ring, the polarizable PC3 unit orchestrates the formation of an electrophilic phosphorus atom (P+) and a nucleophilic carbon atom (C−). This kinetically accessible ambiphilic phosphorus/carbon couple is spatially separated by geometric constraints, and their reactivity is modulated through structural resonance. [ABSTRACT FROM AUTHOR]

Drought is a natural disaster that occurs globally and can damage the environment, disrupt agricultural production and cause large economic losses. The accurate prediction of drought can effectively reduce the impacts of droughts. Deep learning methods have shown promise in drought prediction, with convolutional neural networks (CNNs) being particularly effective in handling spatial information. In this study, we employed a deep learning approach to predict drought in the Fenhe River (FHR) basin, taking into account the meteorological conditions of surrounding regions. We used the daily SAPEI (Standardized Antecedent Precipitation Evapotranspiration Index) as the drought evaluation index. Our results demonstrate the effectiveness of the CNN model in predicting drought events 1~10 days in advance. We evaluated the predictions made by the model; the average Nash–Sutcliffe efficiency (NSE) between the predicted and true values for the next 10 days was 0.71. While the prediction accuracy slightly decreased with longer prediction lengths, the model remained stable and effective in predicting heavy drought events that are typically difficult to predict. Additionally, key meteorological variables for drought predictions were identified, and we found that training the CNN model with these key variables led to higher prediction accuracy than training it with all variables. This study approves an effective deep learning approach for daily drought prediction, particularly when considering the meteorological conditions of surrounding regions. [ABSTRACT FROM AUTHOR]

Climate warming exacerbates the degradation of the mountain cryosphere, including glacier retreat, reduction in snow cover area, and permafrost degradation. These changes dramatically alter the local and downstream hydrological regime, posing significant threats to basin-scale water resource management and sustainable development. However, there is still a lack of systematic research that evaluates the variation of cryospheric elements in mountainous catchments and their impacts on future hydrology and water resources. In this study, we developed an integrated cryospheric-hydrologic model, referred to as the FLEX-Cryo model. This model comprehensively considers glaciers, snow cover, frozen soil, and their dynamic impacts on hydrological processes in the mountainous Hulu catchment located in the Upper Heihe river of China. We utilized the state-of-the-art climate change projection data from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate the future changes in the mountainous cryosphere and their impacts on hydrology. Our findings showed that the two glaciers in the Hulu catchment will completely melt out around the years 2045–2051. By the end of the 21st century, the annual maximum snow water equivalent is projected to decrease by 41.4 % and 46.0 %, while the duration of snow cover will be reduced by approximately 45 and 70 days. The freeze onset of seasonal frozen soil is expected to be delayed by 10 and 22 days, while the thaw onset of permafrost is likely to advance by 19 and 32 days. Moreover, the maximum freeze depth of seasonal frozen soil is projected to decrease by 5.2 and 10.9 cm per decade, and the depth of the active layer will increase by 8.2 and 15.5 cm per decade. Regarding hydrology, runoff exhibits a decreasing trend until the complete melt-out of glaciers, resulting in a total runoff decrease of 15.6 % and 18.1 %. Subsequently, total runoff shows an increasing trend, primarily due to an increase in precipitation. Permafrost degradation causes the duration of low runoff in the early thawing season to decrease, and the discontinuous baseflow recession gradually transitions into linear recessions, leading to an increase in baseflow. Our results highlight the significant changes expected in the mountainous cryosphere and hydrology in the future. These findings enhance our understanding of cold-region hydrological processes and have the potential to assist local and downstream water resource management in addressing the challenges posed by climate change. [ABSTRACT FROM AUTHOR]

Under global warming, flooding has become one of the most destructive natural disasters along the China–Pakistan Economic Corridor (CPEC), which significantly jeopardizes the construction and ongoing stability of the CPEC. The assessment of regional flood potential is, therefore, crucial for effective flood prevention and relief measures. In light of this, our study applied MIKE 11 hydrodynamic model for the Indus River Basin of Pakistan to achieve a comprehensive analysis of the flood-affected locations and depths under typical scenarios. The flood risk zones along the CPEC were evaluated using the indicator system method in conjunction with the combination weighting method. The results show that the hydrodynamic model has a Nash–Sutcliffe efficiency of 0.86, allowing for the investigation of floods at more precise temporal and spatial scales. Punjab, Sindh, and Balochistan Provinces are the main inundation areas under a 100-year flood scenario, with inundation depths ranging from 1 to 4 m. The coastal regions of Sindh and Hafizabad in Punjab witnessed the most severe floods, with maximum inundation depths exceeding 8 m. Flooding predominantly impacts the southeastern region of the CPEC. The medium- to high-risk zones comprise 25.56% of the region, while high-risk areas constitute 4.18%. Particularly, the eastern and southern regions of Punjab, along with the central and southern regions of Sindh, have been pinpointed as high-risk areas, primarily due to their dense population and riverine characteristics. Overall, our findings provide a scientific basis for informed decision making pertaining to disaster reduction and flood prevention. [ABSTRACT FROM AUTHOR]

This study investigates the early-age behaviour of continuously reinforced concrete pavement (CRCP) on the semi-rigid base, including structural behaviour during transverse crack propagation and curling behaviour both in the longitudinal and transverse direction. Field experiments are operated on a CRCP section in Wuhan, China. Vibrating wire strain gauges were installed at mid-slab and slab edge in the longitudinal and transverse direction for concrete strain and temperature measurement. Testing results showed the complexity of early-age behaviour of CRCP on semi-rigid base and curing with wet burlap sheets. An early-age transverse crack may originate from the bottom of the concrete slab due to the water absorption of the dry semi-rigid base. The development of a transverse crack took several cooling cycles. Curling behaviour in the longitudinal direction did not correspond to the temperature gradient after transverse crack occurrence. Typical curling motion in the transverse direction was found in the mid-slab rather than the slab edge. The findings of this study would lead to a better understanding of the early-age structure behaviour of CRCP on semi-rigid base and its impact on later road performance. [ABSTRACT FROM AUTHOR]

An iridium complex based on the unsymmetrical pyrenyl‐thiophene‐benzothiazole ligand was synthesized, and the iridium complex was supported on reduced graphene oxide successfully. The developed iridium catalyst PTB‐Ir@rGO was characterized through SEM, TEM, XPS, EDS. Meanwhile, we found that this heterogeneous iridium catalyst had high catalytic activity in N‐alkylation of benzamide with alcohols via borrowing hydrogen strategy. Moreover, several control reactions and preliminary mechanism explorations were carried out to study this transformation. Finally, the recycling experiment showed that the catalyst could be reused at least five times without a significant decrease in catalytic activity. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Isoindigo (IID) is widely used as organic dye and conjugated unit in opto‐electronic materials. Functionalization of IID to increase its structural complexity is demanding for obtaining diversity properties. Herein, we developed a direct C—H/N—H activation method of IIDs via double alkyne annulations and synthesized π‐extended IIDs with two pairs of 5/7 membered rings. The structure of the π‐extended IIDs was characterized and confirmed by 1H NMR, 13C NMR, HRMS and X ray crystal analysis. Their physical properties were characterized by UV‐vis absorption, cyclic voltammetry and thermogravimetric analysis. The absorption coefficient of the annulated products enhanced significantly compared with the non‐annulated analogue. [ABSTRACT FROM AUTHOR]

A new class of phosphorus-doped triptycenes was designed and synthesized via a Diels–Alder reaction between alkynylphosphonates and anthracene, followed by oxidative cyclization. The packing interaction and molecular alignment in the single crystals revealed that the weak C–H⋯π (2.825 Å) interaction guides the self-assembly of phosphindole oxide iptycenes. The photophysical and electrochemical properties of these photoluminescent phosphorus-doped iptycenes were characterized to gain a deeper understanding of their fluorescence tunability. The presence of functional groups on the phenyl ring of the P-doped fin and the chemical environment of the P atom both had an effect on the fluorescence emission. [ABSTRACT FROM AUTHOR]

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere‐based and land‐based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in‐situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC) and DOC concentrations (CDOC) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC, as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual‐scale estimates and large rivers. Results show that over the period 2001–2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2, p =.01), but little change in CDOC (−0.001 mg/L/year, p >.10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p <.05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (−0.043 and −0.014 mg/L/year, p =.01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio‐temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC, the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate. [ABSTRACT FROM AUTHOR]

Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validation of measurements. Triple collocation (TC) methods can assess the inherent uncertainties of the above ET products using just three independent variables as a triplet input. However, both the severity with which the variables in the triplet violate the assumptions of zero error correlations and the corresponding impact on the error estimation are unknown. This study proposed a cross-correlation analysis approach to discover the optimal triplet of satellite-derived ET products with regard to providing the most reliable error estimation. All possible triple collocation solutions for the same product were first evaluated by the extended triple collocation (ETC), among which the optimum was selected based on the correlation between ETC-based and in-situ-based error metrics, and correspondingly, a statistic experiment based on ranked triplets demonstrated how the optimal triplet was valid for all pixels of the product. Six popular products (MOD16, PML_V2, GLASS, SSEBop, ERA5, and GLEAM) that were produced between 2003 to 2018 and which cover China's mainland were chosen for the experiment, in which the error estimates were compared with measurements from 23 in-situ flux towers. The findings suggest that (1) there exists an optimal triplet in which a product as an input of TC with other collocating inputs together violate TC assumptions the least; (2) the error characteristics of the six ET products varied significantly across China, with GLASS performing the best (median error: 0.1 mm/day), followed by GLEAM, ERA5, and MOD16 (median errors below 0.2 mm/day), while PML_V2 and SSEBop had slightly higher median errors (0.24 mm/day and 0.27 mm/day, respectively); and (3) removing seasonal variations in ET signals has a substantial impact on enhancing the accuracy of error estimations. [ABSTRACT FROM AUTHOR]

The crop drought risk assessment is an important basis for mitigating the effects of drought on crops. The study of drought using crop growth models is an integral part of agricultural drought risk research. The current Decision Support System for Agrotechnology Transfer (DSSAT) model is not sufficiently sensitive to moisture parameters when performing simulations, and most studies that conduct different scenario simulations to assess crop drought vulnerability are based on the site-scale. In this paper, we improved the moisture sensitivity of the Crop Environment Resource Synthesis System (CERES)-Wheat to improve the simulation accuracy of winter wheat under water stress, and then we assessed the drought intensity in the Beijing-Tianjin-Hebei region and constructed a gridded vulnerability curve. The grid vulnerability curves (1 km × 1 km) were quantitatively characterized using key points, and the drought risk distribution and zoning of winter wheat were evaluated under different return periods. The results show that the stress mechanism of coupled water and photosynthetic behavior improved the CERES-Wheat model. The accuracy of the modified model improved in terms of the above-ground biomass and yield compared with that before the modification, with increases of 20.39% and 11.45% in accuracy, respectively. The drought hazard intensity index of winter wheat in the study area from 1970 to 2019 exhibited a trend of high in the southwest and low in the southeast. The range of the multi-year average drought hazard intensity across the region was 0.29–0.61. There were some differences in the shape and characteristic covariates of the drought vulnerability curves among the different sub-zones. In terms of the cumulative loss rates, almost the entire region had a cumulative drought loss rate of 49.00–54.00%. Overall, the drought risk index decreased from west to east and from north to south under different return periods. This quantitative evaluation of the drought hazard intensity index provides a reference for agricultural drought risk evaluation. [ABSTRACT FROM AUTHOR]