Modeling the role of irrigation in winter wheat yield, crop water productivity, and production in China

Irrigation plays an important role in increasing food production in China. The impact of irrigation on crop yield (Y), crop water productivity (CWP), and production has not been quantified systematically across regions covering the whole country. In this study, a GIS-based EPIC model (GEPIC) was applied to simulate Y and CWP for winter wheat (Triticum aestivum L.) in China at a grid resolution of 5arc-minutes and to analyze the impacts of reducing irrigation water on wheat production. The findings show that irrigation is especially important in improving CWP of winter wheat in the North China Plain (NCP), the "bread basket” of China. On average, the provincial aggregate CWP was 56% higher under the irrigated than that under the rainfed conditions. The intensification of water stress and the associated increase in environmental problems in much of the NCP require critical thoughts about reducing water allocation for irrigated winter wheat. Two scenarios for irrigation reduction in the NCP provinces are presented: reducing irrigation depth (S1), and replacing irrigated winter wheat by rainfed winter wheat (S2). The simulation results show that S1 and S2 have similar effects on wheat production when the reduction in irrigation water supply is below 20% of the current level. Above this percentage, S2 appears to be a better scenario since it leads to less reduction in wheat production with the same amount of water savin

Amylopectin chain length distribution in grains of japonica rice as affected by nitrogen fertilizer and genotype

This study investigated the chain length distribution (CLD) of two japonica rice cultivars under six nitrogen (N) treatments by high performance size exclusion chromatography, with the aims to elucidate the effect of N on rice quality and its biological mechanism. Results showed significant influence of N on CLD. In comparison with low N rate, high N lowered the percentage of short amylopectin branches. Fitting with the CLD model of Wu-Gilbert, it suggested that relative activity of SBE to SS was lower at high N rate, thus producing fewer short amylopectin branches. Comparison of CLD between N rates and between cultivars revealed that decrease in short amylopectin branches or the relative ratio of short to long amylopcetin branches correlated with increase in flour gelatinization temperatures (T, T, and T) and decrease in pasting values (except PaT) and amylose-lipid gelatinization temperatures. In addition, quality traits of Wuyujing3, a cultivar with premium eating quality, expressed stably across N treatments compared with the high-yielding cultivar Wuyunjing7

Urban waterlogging prediction and risk analysis based on rainfall time series features: A case study of Shenzhen

In recent years, the frequency of extreme weather has increased, and urban waterlogging caused by sudden rainfall has occurred from time to time. With the development of urbanization, a large amount of land has been developed and the proportion of impervious area has increased, intensifying the risk of urban waterlogging. How to use the available meteorological data for accurate prediction and early warning of waterlogging hazards has become a key issue in the field of disaster prevention and risk assessment. In this paper, based on historical meteorological data, we combine domain knowledge and model parameters to experimentally extract rainfall time series related features for future waterlogging depth prediction. A novel waterlogging depth prediction model that applies only rainfall data as input is proposed by machine learning algorithms. By analyzing a large amount of historical flooding monitoring data, a “rainfall-waterlogging amplification factor” based on the geographical features of monitoring stations is constructed to quantify the mapping relationship between rainfall and waterlogging depths at different locations. After the model is trained and corrected by the measured data, the prediction error for short-time rainfall basically reaches within 2 cm. This method improves prediction performance by a factor of 2.5–3 over featureless time series methods. It effectively overcomes the limitations of small coverage of monitoring stations and insufficient historical waterlogging data, and can achieve more accurate short-term waterlogging prediction. At the same time, it can provide reference suggestions for the government to conduct waterlogging risk analysis and add new sensor stations by counting the amplification factor of other locations

Physical and virtual water transfers for regional water stress alleviation in China

Water can be redistributed through, in physical terms, water transfer projects and virtually, embodied water for the production of traded products. Here, we explore whether such water redistributions can help mitigate water stress in China. This study, for the first time to our knowledge, both compiles a full inventory for physical water transfers at a provincial level and maps virtual water flows between Chinese provinces in 2007 and 2030. Our results show that, at the national level, physical water flows because of the major water transfer projects amounted to 4.5% of national water supply, whereas virtual water flows accounted for 35% (varies between 11% and 65%at the provincial level) in 2007. Furthermore, our analysis shows that both physical and virtualwater flows do not play a major role in mitigating water stress in the water-receiving regions but exacerbate water stress for the water-exporting regions of China. Future water stress in the main water-exporting provinces is likely to increase further based on our analysis of the historical trajectory of the major governing socioeconomic and technical factors and the full implementation of policy initiatives relating to water use and economic development. Improving water use efficiency is key to mitigating water stress, but the efficiency gains will be largely offset by the water demand increase caused by continued economic development. We conclude that much greater attention needs to be paid to water demand management rather than the current focus on supply-oriented management

Grand Canonical Monte Carlo Simulations of Ethanol Conversion to Propylene Over Zeolite Catalysts

The transformation of ethanol to propylene (ETP) was investigated over H-ZSM-5 (40) and H-LEV (40) catalysts. For H-ZSM-5 (40), the propylene yield kept constant at about 20.0% during 8 h. For H-LEV (40), higher initial propylene yield reached 34.0%. However, there is almost no propylene obtained over H-LEV (40) catalyst after 2 h. H-ZSM-5 (40) catalyst exhibited higher stability than H-LEV (40). The lower stability of H-LEV (40) is probably due to coke deposition. The reactant and products adsorption performances in the ethanol conversion reaction over H-ZSM-5 (40) and H-LEV (40) catalysts were studied by Monte Carlo simulations. Results show that the higher adsorption amount of ethanol, ethylene and propylene in H-LEV (40) led to the more difficult desorption of products and higher content of coke deposition

China's coal-fired power plants impose pressure on water resources

Coal is the dominant fuel for electricity generation around the world. This type of electricity generation uses large amounts of water, increasing pressure on water resources. This calls for an in-depth investigation in the water-energy nexus of coal-fired electricity generation. In China, coal-fired power plants play an important role in the energy supply. Here we assessed water consumption of coal-fired power plants (CPPs) in China using four cooling technologies: closed-cycle cooling, once-through cooling, air cooling, and seawater cooling. The results show that water consumption of CPPs was 3.5 km3, accounting for 11% of total industrial water consumption in China. Eighty-four percent of this water consumption was from plants with closed-cycle cooling. China's average water intensity of CPPs was 1.15 l/kWh, while the intensity for closed-cycle cooling was 3-10 times higher than that for other cooling technologies. About 75% of water consumption of CPPs was from regions with absolute or chronic water scarcity. The results imply that the development of CPPs needs to explicitly consider their impacts on regional water resources

Research advances in huntingtin-associated protein 1 and its application prospects in diseases

Huntingtin-associated protein 1 (HAP1) was the first protein discovered to interact with huntingtin. Besides brain, HAP1 is also expressed in the spinal cord, dorsal root ganglion, endocrine, and digestive systems. HAP1 has diverse functions involving in vesicular transport, receptor recycling, gene transcription, and signal transduction. HAP1 is strongly linked to several neurological diseases, including Huntington’s disease, Alzheimer’s disease, epilepsy, ischemic stroke, and depression. In addition, HAP1 has been proved to participate in cancers and diabetes mellitus. This article provides an overview of HAP1 regarding the tissue distribution, cell localization, functions, and offers fresh perspectives to investigate its role in diseases

Pain in Huntington’s disease and its potential mechanisms

Pain is common and frequent in many neurodegenerative diseases, although it has not received much attention. In Huntington’s disease (HD), pain is often ignored and under-researched because attention is more focused on motor and cognitive decline than psychiatric symptoms. In HD progression, pain symptoms are complex and involved in multiple etiologies, particularly mental issues such as apathy, anxiety and irritability. Because of psychiatric issues, HD patients rarely complain of pain, although their bodies show severe pain symptoms, ultimately resulting in insufficient awareness and lack of research. In HD, few studies have focused on pain and pain-related features. A detailed and systemic pain history is crucial to assess and explore pain pathophysiology in HD. This review provides an overview concentrating on pain-related factors in HD, including neuropathology, frequency, features, affecting factors and mechanisms. More attention and studies are still needed in this interesting field in the future

Timing the first emergence and disappearance of global water scarcity

Alleviating water scarcity is at the core of Sustainable Development Goal 6. Yet the timing of water scarcity in its onset and possible relief in different regions of the world due to climate change and changing human population dynamics remains poorly investigated. Here we assess the timing of the first emergence of water scarcity (FirstWS) and disappearance of water scarcity (EndWS), by using ensembles of simulations with six Global Hydrological Models under two representative concentration pathways (i.e., RCP2.6, RCP6.0) combined with two shared socioeconomic pathways (i.e., SSP2, SSP3) for 1901–2090. Historically (1901–2020), FirstWS occurred predominantly in Asia (e.g., China and India) and Africa (e.g., East Africa); the peak time of emerging water scarcity began around the 1980s. Under all the four future RCPs-SSPs scenarios (2021–2090), FirstWS will likely occur mainly in some regions of Africa, for which the newly added area is double that in Asia. On the other hand, EndWS will mostly occur in China after 2050, primarily due to the projected declining population. We, therefore, call for specific attention and effort to adapt to the looming water scarcity in Africa