Crop coefficient (Kc) is a very useful and widely used variable in evapotranspiration estimation in cropland. Traditional methods in calculating Kc are based on field water balance, which is limited by long measurement interval and small study area. In addition, there is the need for Kc under new agronomy practice such as plastic mulching and drip irrigation in arid environments. This study calculated and analyzed Kc of a drip-irrigated and plastic-mulched cotton field in Aksu Oasis of the arid Tarim River Basin, China, and its relationships with several crop-, soil- and management variables such as relative growth days (RGD), leaf area index (LAI), extractable soil water (ESW), and irrigation, based on two years’ observations. The results showed that daily Kc varied within the range of 0.08‒1.28, with an average of 0.54 for the entire cotton growth season, in 2013 and 2014. Compared to non-mulched condition already published, the Kc of mulched cotton for the entire growth season decreased by 16 to 39%. The largest reductions in Kc due to plastic mulch were found in the initial and developmental growth stage. Kc could be calculated by a third-degree polynomial model in relation to RGD, which was satisfactorily validated and can be used in other studies under the same or similar pedo-climatic and management conditions. Cotton LAI and ESW were found to be important factors influencing Kc, particularly their critical values of 3.0 in LAI and 0.5 for ESW. Moreover, the results showed that irrigation significantly increased Kc, i.e., 29% on average, partly due to arid advection. This study provided up-to-date and detailed information on cotton crop coefficient under plastic mulching and drip irrigation conditions in arid environment, and it is useful for improved management of agricultural water resources.
Desert ecosystems exposed to extreme droughts are vulnerable to climate change. Multi-scale mechanism of hydrological adaptation of desert plants to drought are not fully understood, creating uncertainty in risk assessment of desert ecosystems to climate change by ecological modelling. In this study, we investigated multi-scale water use strategies of Haloxylon ammodendron, a dominant desert shrub across central Asia. We found that whole plant water use of H. ammodendron was significantly reduced during most of the daytime period (ca. 79%). At low light water use was controlled by photosynthetic photon flux density (PPFD) and at high vapour pressure deficit (VPD) it was further conserved by stomatal closure. It appears that water conservation in H. ammodendron at leaf-scale may behave differently with that at whole plant scale. High stomatal sensitivity to VPD at whole plant scale means more conservative water use strategy at plant scale than branch- and leaf-scale. Response of transpiration and stomata to climate drivers were non-convergent among leaf, branch and whole plant scales for this desert shrub. Therefore, one must be cautious in up scaling leaf-scale data to infer canopy scale water conservation to avoid overestimation of plant response to climate drivers. Nonetheless, our results enrich the database of multi-scale water use response of desert plants to climate drivers, which is critical for ecological modelling aiming to predict arid land vulnerability to climate change.
To increase Japanese soybean yield, both practical and genetic improvements are needed. Early sowing improved yields in the United States, where indeterminate cultivars may produce better yields than determinate cultivars, particularly with early sowing. However, the mechanism for the yield response is not fully understood. Furthermore, whether these results are valid for cool regions in northern Japan is unknown. This study tested the effects of early sowing on yield and its attributes in three years using a Japanese determinate cultivar (Ryuhou) and three indeterminate cultivars (Karikei-881 and Karikei-879, recombinant inbred lines from determinate × indeterminate crosses; UA4910, a high-yield American cultivar). The effects of early sowing varied among the years. Early sowing significantly increased pod number and seed yield by increasing cumulative intercepted solar radiation (thus, growth during early reproductive stages) in years with high precipitation during mid-season (July and August). High precipitation potentially inhibited canopy development from vegetative to early reproductive stages more strongly in normally sown plants than in early sown plants. In contrast, no significant effect of early sowing was observed in a year with low precipitation during mid-season, when low precipitation during vegetative stage promoted canopy development in both sowing dates. Therefore, early sowing could escape from excess water stress and ameliorate canopy development and thereby seed yield in this region. There was no significant sowing date × cultivar interaction for seed yield in any year; thus, the indeterminate cultivars did not benefit more from early sowing in northern Japan. UA4910 had greater seed yield than Ryuhou owing to its longer growth duration and greater aboveground biomass and pod number; Karikei-881, Karikei-879, and Ryuhou showed similar seed yields. Thus, indeterminate cultivars did not necessarily have higher yields in northern Japan. These results suggest that early sowing could be effective for increasing soybean yield in northern Japan.
High resolution data for solar radiation are particularly useful for precise cultivation management of hilly or mountainous terrains and hourly minima for both direct and diffuse solar radiation are needed to determine global solar radiation in such terrain. Estimation methods based on statistical models for determining hourly direct and diffuse solar radiation on a horizontal surface have been developed using low-cost public data. These methods use a statistical model for atmospheric transmittance. Direct solar radiation was estimated from hourly atmospheric transmittance data using a multiple regression equation with two meteorological variables, i.e., sunshine duration and extraterrestrial solar radiation on a horizontal surface. Diffuse solar radiation was estimated using a dimensionless parameter Kds based on direct solar radiation, whenever sunshine duration was greater than zero. When sunshine duration was zero, diffuse solar radiation was estimated using a multiple regression equation with two other meteorological variables, i.e., precipitation and normal extraterrestrial solar radiation. The root mean square errors of estimated data for both hourly direct and diffuse solar radiation were ~0.3 MJ m-2 h-1. Hourly direct and diffuse solar radiation estimated using the proposed method will be useful throughout Japan to facilitate better agricultural crop management. In addition, development of estimation methods for hourly direct and diffuse solar radiation using a numerical weather prediction model was also explored. It proved to be difficult to use estimated hourly data in the numerical model, but this numerical approach appears to be feasible for daily values.
Recently, Moso bamboo forests have been expanding in Japan because they were left unmanaged and because of the characteristically fast growth rate of bamboo. In this study, trees of 14 bamboo species in two bamboo forests and an exhibition garden in Japan were screened for biogenic volatile organic compound (BVOC) emissions by using a leaf cuvette. The screening showed that 12 out of 14 species (86%) emitted isoprene at rates of 0.7-99.1 nmol m-2 s-1. No monoterpene and sesquiterpene emitters were identified. Our result indicated that several bamboo species, such as Phyllostachys spp., Semiarundinaria spp., and Bambusa spp., should be categorized as strong isoprene emitters. We also measured the diurnal patterns of isoprene emissions for Phyllostachys heterocycla and Phyllostachys bambusoides in spring and summer, 2015. The isoprene emission rates of both species increased on summer days, reaching a maximum level (78.1 nmol m-2 s-1 and 57.6 nmol m-2 s-1, respectively) around noon, and were lower in spring (<5 nmol m-2 s-1). Our results indicate that the increasing areas of bamboo forest in future could contribute to increasing atmospheric concentrations of ozone and other photochemical oxidants.
The purposes of this research were to increase artificial rainfall and evaluate the area affected by artificial rainfall. The experiment involved the seeding of liquid carbon dioxide at a height of 2500 m with a seeding rate of 11.1 g/s for 6 min around Karatsu, Saga, Japan on Dec. 26, 2013. The height of the cloud increased significantly, and a virga was observed under the cloud bottom at 2100 m at 30 min after the seeding. The cloud top of the previous seeding cloud was at 3350 m, the cloud bottom was at 2100 m, and the cloud depth was 1250 m. The cloud top after 30 min was at 3500 m, the cloud bottom was at 2100 m, the cloud depth was 1400 m, and the depth had increased by 150 m. The wind direction and speed around the seeding time at 3050 m were WSW and 13.9 m/s, respectively. At 1 h after the seeding, artificial clouds around Fukutsu and Munakata were clearly recognized, and after 1 h 30 min the clouds were around Kitakyushu. The final distance affected by artificial clouds was over 100 km after 2 h. The artificial rainfall (precipitation) amounts at Munakata, Yahata, and Shimonoseki were estimated to be 1.0, 1.0, and 0.5 mm, respectively. The amounts of artificial and natural rainfall or water resources were both estimated to be 0.15 million tons each after 2 h. The estimation of artificial rainfall by radar echo and the surface rainfall agreed well with each other. The artificial rainfall was observed at a target region and the amount of rainfall ultimately increased.
Climate change is virtually certain and efforts for adaptation is essential not only to decrease the negative consequences but also to increase the opportunities. To achieve the goal, we need to address emerging research topics in the field of agricultural meteorology with regard to climate change adaptation. We touch upon how harvesting insights from crop models with different complexities can be improved, the detection and attribution of impacts on agricultural ecosystems associated with climate and technological changes, and how crop and weather datasets can be improved. We conclude by discussing important knowledge gaps that need to be addressed in future research.