Water-saving technologies affect the grain characteristics and recovery of fine-grain rice cultivars in semi-arid environment

Water use efficiency control for a maize field under mulched drip irrigation

Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation model, relative importance analysis and principal component analysis were used to quantify the regulation effects of environmental and biological factors on WUE at different time scales, in different growth stages and under different hydrothermal conditions. The results showed that annual WUE varied between 2.18 g C Kg^-1 H₂O and 3.60 g C Kg^-1 H₂O, with a multi-year mean of 2.91 g C Kg^-1 H₂O. The total effects of air temperature on the daily WUE in the whole growth period, the vegetative growth stage, the warm and dry years, the cold and wet years, and the warm and wet years were the largest, with values of 0.61, 0.80, 0.70, 0.70 and 0.91 respectively. However, vapor pressure deficit and net radiation had the largest total effect in the cold and dry years (-0.63) and the reproductive growth stage (-0.49), respectively. Leaf biomass played a leading role in regulating the daily and interannual WUE, and the relative importance of leaf biomass to WUE in the vegetative growth stage was up to 75 %. In the warm and wet years, the relative importance of root biomass to WUE was 33 %, slightly higher than that of leaf biomass (31 %). At the same time, we found that Ta has the potential to increase WUE under future climate warming. Our results improve the understanding of carbon-water coupling mechanisms and provide important enlightenment on how crop ecosystems should adapt to future climate change.

Who cares what parents think or do? Observational learning and experience-based learning through communication in rice farmers' willingness to adopt sustainable agricultural technologies in Hubei Province, China

Sustainable agricultural technologies are of great significance in fully utilizing agricultural resources and promoting agricultural production. However, the adoption rates of these technologies are often characterized as low in rural areas in China. To figure out the potential salient determinants of rice farmers' willingness to adopt sustainable agricultural technologies, this paper, by employing the multivariate probit model and ordered probit model, particularly and firstly explores the roles of observational learning and experience-based learning through communication from parents within the household on rice farmers' willingness to adopt these technologies. Results show that there are strong complementarities and substitutabilities between sustainable agricultural technologies that rice farmers are willing to adopt, and that observational learning and experience-based learning through communication within the household do have pronounced effects on rice farmers' willingness to adopt some sustainable agricultural technologies and on their intensive use intentions. Therefore, while formulating policies to improve the adoption rates and adoption intensity of these technologies, relevant government agencies should take the complementarities and substitutabilities between sustainable agricultural technologies as well as observational learning and experience-based learning through communication from parents into consideration.

Optimal water resource management for sustainable development of the chemical industrial park under multi-uncertainty and multi-pollutant control

Two major concerns over the chemical industrial park (CIP) operations are high consumption of water resources and large amount of pollutant emissions. This study develops an interval chance-constrained programming model for industrial water resources management (ICCP-IWM) with consideration of multi-uncertainty and multi-environmental constraints. Uncertainties expressed as intervals and probability distributions are merged in the ICCP-IWM framework. The developed model is used to solve a real-world water resource management problem in the Shenyang Chemical Industrial Park to demonstrate its capacity and effectiveness, where the objective is to minimize the system cost of water pathways and pollutant-emission control under a series of constraints. Interval solutions with respect to water resources allocation, wastewater management, and pollutant emissions could be generated. Results indicate that a lower violation risk leads to an increased strictness of the constraints, then to a higher system cost; conversely, a higher violation risk results in a lower system cost, at the expense of an increase in the risk. These findings would be recommended by the decision-makers because of their applicability for practical decision process providing the optimal strategy for sustainable water resource management under multiple uncertainties.