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Wind energy forecasting is significantly affected by the strong volatility, intermittency and variability of the wind speed sequence itself. Therefore, to improve forecast accuracy and stability, based on nonlinear auto-regressive model with exogenous inputs (NARX) and the hybrid chaos-cloud salp swarm algorithm (CC-SSA), a short-term wind speed prediction method is proposed. Firstly, to reduce the complexity of the original wind speed data and generate subcomponents with different patterns and low complexity, a mixed modal decomposition method is carried out by combining variational modal decomposition (VMD) based on Pearson correlation coefficient and generalized S-transform (GST) based on adaptive sample entropy. Therefore, the complementary advantages of different mode decompositions are obtained by combining the two different subcomponents into a mixed component. Secondly, by using cloud model and chaotic map, the improved CC-SSA algorithm is proposed to improve the convergence performance of salp swarm algorithm (SSA). Finally, by using CC-SSA algorithm to optimize the weights of NARX, the CC-SSA-NARX forecasting model is established to predict wind speed. The experimental results show that for the 1-Step, 2-Step, and 3-Step datasets of the actual wind speed in the studied region, the MAE, MAPE, RMSE, and R 2 of the CC-SSA-NARX model are 0.23, 6 %, 0.27, and 0.97 respectively. The proposed model present the highest prediction index among the other 7 comparative models, showing high accuracy and generalization ability in short-term wind speed prediction, it can provide a certain reference for enhancing the stability of wind power generation and promoting the sustainable development of the wind power industry to some extent. • A mixed decomposition method using VMD and generalized S-transform is proposed. • An improved SSA algorithm based on chaotic cloud (CC-SSA) is proposed. • The proposed CC-SSA is applied to optimize the parameter of NARX. • A short-term wind speed prediction model of CC-SSA-NARX is constructed. [ABSTRACT FROM AUTHOR]

Based on the hydrological characteristics of a rice-based irrigation system in Southern China, the SWAT (Soil and Water Assessment Tool) model was modified in order to develop the Rice Irrigation System-Soil and Water Assessment Tool (RIS-SWAT). The irrigation water movement, water balance module, and rice yield calculations of the paddy field were improved within the SWAT model. In addition, the seepage of the irrigation canal and the pond’s effect on the irrigation modules were added to the RIS-SWAT. The impact of water management on the water cycle of the small watershed irrigation system (SWIS) was evaluated by conducting a scenario analysis with RIS-SWAT. The results indicated that an increase in the maximum water ponding depth of a paddy field could decrease irrigation water and rainfall loss. The canal water supply was reduced by 20%, resulting in an increase in irrigation water productivity without a reduction in the rice yield. The temporal and spatial distributions of the irrigation water in different subbasins did not significantly affect the water cycle within the SWIS. Furthermore, when the canal water supply was reduced by 20–40% and the pond water supply was increased, the rice yield was not affected. Thus, the water productivity of irrigation systems could be improved through the implementation of water management policies and practices that reduce field outflows and reuse the return flows captured by ponds. [ABSTRACT FROM AUTHOR]

Abstract Copper and Fe are redox-sensitive metals, and their isotopic compositions may potentially record changes of oxidation conditions in high-temperature magmatic Ni–Cu mineralization systems. High-precision Cu and Fe isotope data for sulfides (chalcopyrite) and whole-rock samples of the Tulaergen magmatic Ni–Cu system (NW China) were analyzed to evaluate redox-induced fractionation during segregation of sulfide melt from silicate melt and internal fractionation within segregated sulfide melt. Sulfide mineralization includes disseminated and massive types, with massive sulfides being further divided into Cu- and Fe-rich ores. Numerical modeling using mass-balance and Rayleigh equations indicate that disseminated sulfide mineralization was generated from a common parental magma, and massive sulfides were formed by monosulfide solid-solution (MSS)–residual sulfide liquid fractionation. During segregation of sulfide melt from silicate melt, crystallization of olivine and pyroxenes with sulfide segregation, in an Fe2+-dominated phase, led to the incorporation of lighter Fe isotopes in these minerals. The residual silicate melt became progressively more oxidized, with δ56Fe whole-rock values increasing as melts evolved. The disseminated chalcopyrite formed in early stages has lighter Cu and heavier Fe isotopic compositions than the disseminated sulfides formed in later stages due to charge-balance effects. Minor accumulated Ni–Cu sulfide melt was fractionated into an Fe-rich MSS cumulate and a Cu-rich sulfide liquid. MSS crystallization caused the oxygen fugacity of the evolved sulfide liquid to increase, which was accompanied by increasing δ65Cu and decreasing δ56Fe values in chalcopyrite. Iron isotopic compositions of the whole system were shifted towards heavier values from MSS cumulate to the evolved sulfide melt. Numerical modeling using the Rayleigh equation indicates that the fractionation factors α65Cu residual sulfide melt–MSS and α56Fe residual sulfide melt–MSS are ∼1.0011 and ∼1.0005, respectively, during internal fractionation within segregated sulfide melt. This study demonstrates that redox reactions play a key role in Cu and Fe isotope fractionation in high-temperature magmatic Ni–Cu mineralization systems. Furthermore, Cu and Fe isotopes can be used to trace concealed orebodies. Elevated δ65Cu and δ56Fe whole-rock values may indicate Cu-rich mineralization potential, while light Cu and Fe isotopic compositions imply favorable hosts for disseminated and Fe-rich orebodies in mafic–ultramafic intrusions. [ABSTRACT FROM AUTHOR]

Highlights • Four types of wind speed data were used in reduced set Penman-Monteith model for ETo forecasting. • Three modified reduced set Penman-Monteith models were proposed. • ETo forecast performance can be significantly improved through considering wind speed. • Wind speed data type was recommended for each station in different climate zone. Abstract Farm irrigation management and real-time irrigation decisions are based on a series of parameters including irrigation water demand predictions which estimated by the short-term daily reference evapotranspiration (ETo). Based on the temperature data, a simplest empirical model called the temperature-based method, was developed to forecast near-future ETo. Although temperature is one of the most influential weather variables in ETo forecasting, wind velocity also has non-ignorable impact on the forecast performance of ETo. Therefore, we employed the Reduced-set Penman-Monteith (RPM) model for short-term ETo forecasting using temperature data derived from public weather forecasts and wind speed data. Four different types of wind speed data were adopted as model inputs, including wind speed assumed as a default value, i.e., u 2 = 2.0 m s−1 (W1), forecasted wind speed (W2), long-term daily average wind speed (W3) and annual average wind speed (W4). Based on the above-mentioned wind speed inputs, we presented four types of RPM models (RC, RF, RD and RM models respectively corresponding to W1, W2, W3 and W4) to forecast daily ETo for lead times up to 7 days for eight weather stations in China. The results confirmed that the highest precision wind speed input was W3, followed by W4, W1 and W2, and the most accurate ETo forecasts of four RPM models was provided by RC, followed with RD, RM and RF. By comparing with one of the most common used temperature-based models, the Hargreaves-Samani (HS), it was found that the performance of RPM approaches were better than that of HS model for arid and sub-arid regions whereas opposite results were found in sub-tropical area, suggesting inclusion of wind speed parameter makes positive impact on ETo forecast for arid and semi-arid regions. Further, it was found that the greatest type of RPM model, the RC model, was superior to HS method for most climate regions, including arid, humid, sub-arid and sub-humid areas, thus, the W1 wind speed type could be highly recommended for ETo forecasting for most climate regions. [ABSTRACT FROM AUTHOR]

Abstract: Multicharged ions (, , , ) at constant speed (Bohr velocity) were used to irradiate PC (polycarbonate) foils which were subsequently chemically etched. Because of the low ion dose of , pores on the surface were discrete. The diameters of the pores were measured by means of scanning electron microscopy (SEM). From the linear dependence of the pore diameter on the etching time, the transversal etching rate can be obtained. It was found that the transversal etching rate decreased with ion charge. These results can mainly be explained by the variation of the charge exchange process for ions with a different charge state. [Copyright &y& Elsevier]

Abstract: The size of alpha-particle tracks on electrochemically etched ultraviolet-irradiated polyallyldiglycol carbonate (PADC) films were studied. PADC films were first irradiated with 3MeV alpha particles and then pre-etched chemically using aqueous 6.25N NaOH solution for 2h. The films were then exposed to incoherent broad-band ultraviolet (UV) radiation provided by a mercury lamp for different durations up to 2h. The films were then electrochemically etched in a 6.25N NaOH solution, with an a.c. voltage of about 1200 and a frequency of 5kHz, for 2h at room temperature. The mean sizes of the tracks (or trees) were measured and were found to increase for short UV exposures and decrease for prolonged UV exposures. The results can be explained by the dominance of chain scission at the beginning of UV exposure and the dominance of cross linking for prolonged UV exposure. This explanation is further supported by results from X-ray photo-electron spectroscopy (XPS). Here, the C–O–C bonds decrease for short UV exposures, which is explained by scission of the polymer chains, and increase again for prolonged UV exposure, which indicates cross linking. From nano-indentation measurements, the hardness and the reduced modulus increase monotonically with the UV irradiation. Apparently, these quantities only characterize the amount of cross linking, and do not give information on the initial scission process. [Copyright &y& Elsevier]