Recorded Wind Speed Research Articles

Uncertainty evaluation for wind speed measurement part (2): “Input quantity correlation”

When the “Guide to the expression of uncertainty in measurement” (GUM) is used to evaluate the uncertainty of wind speed sensors, there is a lack of input quantities correlation research, which leads to the deviation of the uncertainty evaluation result. This paper takes the calibration result of an automatic weather station's three-cup wind speed sensor as an example to evaluate the uncertainty of wind speed sensor measurement based on the correlation of input quantities. First, the calibration point of 10.00 m/s wind speed is taken as an example, and the original wind speed record is obtained by calibrating the three-cup wind speed sensor. Then, according to the GUM evaluation method, the uncertainty of the wind speed measurement result is analyzed and evaluated, And analyze and explore the correlation between the input quantities (considering the influence of the stability and uniformity of the wind tunnel on the measurement result, and the existence of a certain interdependence between them, an experimental plan was developed to test the stability and uniformity of the wind tunnel, and the correlation coefficient between them was calculated to be 0.1561 at the wind speed point of 10.00 m/s). Finally, the input quantities correlation (the correlation coefficient of wind tunnel stability and uniformity) is integrated into the uncertainty evaluation, and the uncertainty evaluation result is obtained at 10.00 m/s wind speed point (where U = 0.22 m/s, U95 = 0.22 m/s). Through comparison, the uncertainty results evaluated without considering the correlation of input quantities have generated negative deviation, with deviation values being −0.00022 m/s. Due to the relatively small deviation, in practical applications, it can be determined whether to correct it based on the accuracy requirements of the measurement result and actual needs.

Statistical post-processing of numerical weather prediction data using distribution-based scaling for wind energy

The performance of numerical weather prediction models has improved dramatically recently. However, model biases remain a fundamental limitation prohibiting the direct implementation of model results. There are several ways to describe wind speed data. The Weibull and lognormal distributions are used to obtain the best-fit model for the wind speed data. This study aims to develop a statistical post-processing method based on the distribution-based scaling (DBS) approach, which scales NWP data to fit the distribution derived using recorded wind speed at that site location. The performance of the suggested method was evaluated using four different error measures. The optimal model is anticipated to have the lowest Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean square Error (RMSE), and variance (s2) values. It was determined that employing a DBS strategy significantly improved the NWP by at least 75%.

The Return Period Wind Speed Prediction of Beijing Urban Area Based on Short-Term Measured Wind Speed

To predict and explore the return period wind speed distribution in Beijing urban area, based on the short-term measured wind speed record, the measured independent storm peak samples are extracted and the Monte–Carlo numerical simulation method is used to randomly generate pseudo-independent storm peak samples with the same distribution as the independent storm peak samples. In addition, the appropriate threshold is used to select and extract the over-threshold independent storm peak samples from the measured samples. And, then, the return period wind speed of the whole wind direction is predicted. Further, the traditional Cook method is used to predict and analyze the return period wind speed of each wind direction according to the measured wind speed data. The results show that the return period wind speed prediction results of the whole wind direction corresponding to the simulated pseudo samples and the measured over-threshold samples are basically close to each other, and the maximum relative deviation is less than 7%. The mean relative deviation of the return period wind speed prediction results is about 10.6% between each wind direction and the whole wind direction, and the mean relative deviation is about 9.4% between the RPWS prediction result of each wind direction and the design value of the code. In addition, the return period wind speed prediction values of the west by southwest, northwest and north by northeast wind directions exceed the design value of the code, while the predicted values of the other wind directions are within the envelope range of the design value of the code. Finally, the research content of this paper can provide some reference for the wind resistance design analysis of building structures in Beijing area.

Wind Speed Characteristics and Energy Potentials in Lafia, Nasarawa State, Nigeria

Renewable energy, specifically wind power, is vital for reducing fossil fuel dependency, greenhouse gas emissions, and improving energy security. With advancements in technology, wind energy has become cost-effective and competitive. Wind energy research in Lafia is essential to developing solutions in harnessing its potential as a significant renewable energy source for Nigeria, which has abundant but untapped wind energy resources. This study investigates the wind energy potential in Lafia, Nasarawa State, using daily averaged wind speed data from MERRA-2 measured at 2, 10, and 50-metre altitudes. The Weibull distribution function was applied to determine Lafia's wind energy potential, and the outcomes revealed that the highest yield for wind harvest occurred during the peak of the dry season in February, while the lowest yield for wind harvest occurred during the beginning of the dry season in October. Moreover, the monthly mean power densities peaked in February, 2001 at 341.87 W/m2 (class 3: 300 < PD ≤ 399), indicating moderate potential, and in January, 2002 at 454.12 W/m2 (class 4: 400 < PD ≤ 499), indicating good potential. However, the peak monthly mean power densities in December, 2003 and February, 2004 were poor and marginal, respectively, according to the Wind Resource Potential (WRP) classification. Furthermore, at 50 metres altitude, the recorded wind speeds were above the recommended minimum (3.00 – 4.00 m/s) for most wind turbines to start producing electricity. The findings indicate significant wind resource potential at high altitudes (50 metres) in Lafia, which suggests great potential for wind energy generation.

62 The Impact of Hair Coat Color on Body Temperature in Beef Cattle

Abstract Ambient temperature has a fundamental role in animal health and performance. Selecting for coat color may improve animal productivity and welfare through management and breeding decisions. The thermoneutral zone of cattle, 0°C - 25°C, is characterized as the range in ambient temperature that does not require cattle to expend energy to maintain core body temperature. When the ambient temperature is above or below these values, cattle must expend energy to keep their body temperature in homeostasis resulting in a reduction in efficiency. A proper herd management plan to mitigate heat stress can increase efficiency and decrease mortality in serious cases. Registered Hereford and commercial black cows (n = 39; average 4 yr of age) were placed in a 23-ha pasture, to determine if coat color affects internal body temperature. Cattle were on a typical fescue dominated pasture located in Mountain Grove, MO, with areas of shade and one pond centralized in the pasture. Cattle were divided into treatments based on hair coat color: black (n =13) or red (n = 26). Using temperature data loggers, vaginal temperatures were recorded in 5-min intervals during a 14-d period in Mid-July 2022, and combined into 6-hour timing intervals, A = 0400-1000 h, B = 1001-1600 h, C = 1601-2200 h, and D = 2201-0359 h. Environmental temperature data loggers were suspended in two locations of partial sun to record ambient temperature. In addition, the Mountain Grove weather station operated by the University of Missouri Extension provided a daily data archive that recorded wind speed, total precipitation, maximum and minimum air temperature. Throughout the study, the mean environmental temperature was 34.4°C and ranged from 19.5°C to 40.2°C. Temperature data were evaluated using the Glimmix procedure of SAS and pairwise comparisons between timepoints were determined utilizing the GLM procedure of SAS. Differences were considered significant at P = 0.05. Black-haired cattle were warmer at all intervals (P ≤ 0.04) with temperature differences between the treatments of 0.07, 0.10, 0.03, and 0.09°C for timepoints A, B, C and D, respectively (Table 1). Based on our results black-hided cattle get warmer earlier in the day and take longer to dissipate heat than those with red hair coats.

Soil Pollution Prediction from Enterprise for Coking Industry in China Based on Machine Learning and Scenario Analysis

Owing to the lack of sequential monitoring data of soil pollutants in coking industry enterprises, it is hard to accurately predict their soil pollution. To predict the trend of soil pollution of coking industry enterprises in the future, a prediction model should be developed using machine learning based on the influencing factors. A total of 13 potential factors were selected from the enterprise characteristics, enterprise management level, pollutant characteristics, and natural factors, and the main controlling factors were identified. On this basis, the prediction models were developed using a support vector machine, BP neural network model, decision tree model, and logistic model, and then the pollution situation of enterprises in the coking industry in 2025 and 2030 was predicted under different scenarios. The results indicated that time of service for the enterprise, time of establishment for the enterprise, the environmental illegal record, soil clay, and annual wind speed were the major controlling factors of soil pollution of enterprises in the coking industry. Compared with the support vector machine, BP neural network model, and decision tree model, the logistic model had a robust performance index, with an area under the receiver operating characteristic curve of 0.91. The accurate rate and recall rate were 84% and 88%, respectively. Under the optimistic scenario, there will be 1599 and 1695 plots with a high probability of pollution in the coking industry in 2025 and 2030, respectively; under the pessimistic scenario, there will be 1671 and 1715 plots with a high probability of pollution in the coking industry in 2025 and 2030, respectively. The results of this study provided a scientific basis for soil environmental remediation and eco-environmental strategy development for the coking industry.

The effect of water currents on wind drag – a case study of tidal currents and sea breeze in a semi-enclosed embayment

The details of how energy and momentum are exchanged at the interface between ocean surface and the atmosphere is complex and the subject of new and more complete models. The need to improve models of how wind interacts with oceans is driven in part by the growth of offshore wind farms, and the need to predict their likely performance. The geographic features of Shark Bay allow several of the factors affecting the influence of currents on wind speed to be separated and analysed. Shark Bay is the largest semi-enclosed embayment on the Australian coast. It is tidal and aligned north–south in the direction of the sea breeze. The prevailing southerly wind, and the absence of openings to the ocean in the south of the bay, limits the fetch of waves, providing waves of predictable age in the bay with an absence of longer wavelength swell. The sea breeze in this region is characterised among the strongest and most reliable anywhere in the world. Although the tide heights are not large, the geography of the bay ensures strong tidal currents. Hence Shark Bay provides an excellent opportunity to study the effects of currents on winds. This study demonstrates that the effects of the tidal current are apparent in the wind speed record. It shows that simply subtracting a 29-day running average of the particular time of day from the wind speed reveals the effect of an incoming or outgoing tide. Time-series analysis of this outcome shows the periodicity and modulation of the tides. The analysis is further improved through using the Weather Research and Forecasting (WRF) code and subtracting its predictions from the raw data. Time-series analysis of the outcome demonstrates that the resultant difference has two diurnal and two semi-diurnal components with the correct periods and amplitudes of the known tidal variations in that region of Shark Bay. Hence the neglect of the interaction between water currents and wind stress is demonstrated to produce a systematic deviation in the predictions of the WRF from the measured wind values for Shark Bay.

Validation of wind measurements from a multirotor RPAS-mounted ultrasonic wind sensor using a ground-based LiDAR system

The aim of this research was to establish the validity of wind measurements from on board a multirotor Remotely Piloted Aircraft System (RPAS) for the purposes of wind monitoring applications. A custom-built hexacopter RPAS recorded wind speed and direction by means of an onboard ultrasonic wind sensor, whilst operating in the inherently highly stochastic nature of open field atmospheric conditions. Experimental data were collected during open field hovering flights subject to different ambient conditions with free stream horizontal wind speeds reaching up to 12 m/s. Flights were conducted at different altitudes above ground level and in proximity to a Light Detection and Ranging (LiDAR) remote wind measurement unit that was used as a low-resolution reference meteorological station. Very good correlation was obtained between the RPAS and LiDAR unit for both wind speed and wind direction measurements across all hovering flight altitudes. The RPAS-based wind speed measurements were found to have a consistent 1 m/s positive offset, whilst the RPAS-based wind direction readings had a 6.16° negative offset. These were potentially caused by differences in the localized wind fields between the LiDAR and RPAS measuring positions, as well as by localized RPAS rotor-induced air flows for wind speed measurements and potential slight misalignments in the instruments’ reference datum for wind direction readings.

Water Vapor Transport Across an Arid Sand Surface—Non‐Linear Thermal Coupling, Wind‐Driven Pore Advection, Subsurface Waves, and Exchange With the Atmospheric Boundary Layer

AbstractAlthough vapor exchanged across hyper‐arid surfaces without free liquid affects the water budget of sand seas, its mechanism is poorly documented for want of accurate instruments with fine spatial resolution. To rectify this, we report bulk density profiles and spatiotemporal variations of vapor mass fraction just below the surface of a mobile dune, acquired with a multi‐sensor capacitance probe sensitive to tiny water films adsorbed on sand grains. We also record wind speed and direction, ambient temperature and relative humidity, net radiation flux, and subsurface temperature profiles over 2 days. The data validate a non‐linear model of vapor mass fraction. Unlike heat, which conducts through grains, vapor percolates across the interstitial pore space by advection and diffusion. On time scales longer than evaporation, adsorbed films equilibrate with their surroundings and hinder molecular diffusion. Their non‐linear coupling with subsurface temperature generates inflections in vapor profiles without counterpart in simpler diffusive systems. Pore advection arises as wind induces subtle pressure variations over the topography. During periods of aeolian transport, flowing sand dehydrates the surface intermittently, triggering evanescent vapor waves of amplitude decaying exponentially downward on a characteristic length implying an adsorption rate governed by a kinetic‐limited activated process. Finally, the probe yields diffusive and advective exchanges with the atmospheric boundary layer. During the day, their combined flux is smaller than expected, yet nearly proportional to the difference between vapor mass fraction at the surface and aloft. Under stabler stratification at night, or during aeolian sand transport, this relation no longer holds.

Multi-year variation of near-surface ozone at Zhongshan Station, Antarctica

With the support of the Chinese National Antarctic Research Expedition, near-surface ozone (O3) was continuously monitored at Zhongshan Station (ZOS) (69°22′12″ S, 76°21′49″ E, 18.5 m above sea level) in East Antarctica from 2008 to 2020. The seasonal and diurnal variability of near-surface O3 at ZOS were investigated. O3 enhancement events (OEEs) were frequently observed in the warm season (OEEs in January accounted for 23.0% of all OEEs). The OEEs at ZOS were related to the photochemical reaction processes under the influences of O3 and solar radiation in the stratosphere and synoptic-scale air mass transport from coastal areas (Princess Elizabeth Land, Wilkes Land, and Queen Mary Land), as evidenced by the recorded wind speed, solar shortwave irradiance, and total column ozone data and the computed potential source contribution function and concentration-weighted trajectory models. The results computed by the tool Stratosphere-to-Troposphere Exchange Flux indicated that stratosphere-to-troposphere transport had no direct impact on OEEs at ZOS. Therefore, synoptic-scale air mass transport is the main cause of OEEs in Antarctica, which is consistent with previous studies. Unlike OEEs at inland Antarctic stations, which are mainly affected by air mass transport from inland plateaus, OEEs at ZOS, a coastal station, are mainly affected by air mass transport from coastal land in East Antarctica.

Correction of Field-Measured Wind Speed Affected by Deterministic Interference Factors

The observations of meteorological wind speed may be biased due to the influence of various distractions. Therefore, the original measured data should be corrected in a targeted manner. Wind tunnel tests (WTT) and computational fluid dynamics (CFD) numerical simulation methods are used to study the local wind environment characteristics of observation sites in Noi Ling Ding Island (NLDI) and Ping An International Financial Center (PAFC) in the Shenzhen area. The interference effects of NLDI and the building components and instruments in the hollow-layer atop PAFC on their corresponding anemometer measurement results were analyzed, and a quantitative description was provided with the wind speed influence coefficient (CVI), which is the wind speed ratio in disturbed and undisturbed cases. Results show that the CVI of WTT at the NLDI site is slightly higher than that of CFD, and the wind speed in the wind-sensitive direction is accelerated by 12% due to the influence of NLDI. The large pillars at the corner of PAFC have a considerable occlusion effect on the wind speed under the wind direction of 45°. An acceleration effect with CVI of 1.163 is found in the dominant wind direction when instruments are absent atop the hollow-layer, whereas a sheltering effect is observed with the CVI of 0.593 when instruments are present. These results are used to correct the recorded wind speed at the NLDI and PAFC sites during Super Typhoon Manghut with No. 201822, and then converted into the 10 min mean wind pressure value at 10 m height under the standard landform. The reference wind pressure values obtained are 0.526 and 0.505 kPa. The analogous conversion values achieve the purpose of mutual verification, and the effectiveness and reliability of the methodologies are presented.

Equivalent Modeling of a Direct-Drive Wind Farm Based on the Measured Data

In view of the difference between the wind speed and the actual wind speed in the example, the wind farm with fifteen direct-drive permanent magnet synchronous motors draws the recorded wind speed data on the coordinates of time and wind speed by linear regression to group the change trend. Secondly, the detailed model of wind farm is built in PSCAD, and the multi-machine equivalent model of wind farm is built by the control current source replacing the permanent magnet synchronous motor and the control part. Finally, the simulation analysis shows that the equivalent model reduces the simulation time and accurately reflects the dynamic and transient properties of the wind farm.

A techno-economic analysis for power generation through wind energy: A case study of Pakistan

Pakistan needs to overcome the cost of power generation and the ever-increasing demand for energy with environment-friendly renewable energy resources. Several research efforts have been made with the support of Pakistan Meteorological Department in the last two decades for wind resource assessment (WRA) across the country. However, the practical installation of wind farms is quite a fraction of the total forecast wind energy potential. In this feasibility, WRA of Umerkot and Sujawal districts located in Sindh provinces of Pakistan has been analyzed by analyzing mean wind speeds, estimated Weibull parameters, power and energy densities calculation for various heights of selected wind turbines. Further, this paper analyzes the overall energy potential for these locations with implementation cost and pay-back period for investment. These locations are selected by the World Bank initiative of wind profiling campaigns to record wind speed data during 2016 and 2018 with 10 min resolution. It is observed that Umerkot and Sujawal sites are suitable for energy production. The highest values of power and energy densities for Sujawal are 414.18 W/m2 and 3628.22 kWh/m2/Yr and for Umerkot these values are 303.86 W/m2 and 2661.81 kWh/m2/Yr. The results indicate that using Nordex N90/2500 wind turbines are highly beneficial for Umerkot and Sujawal. The associated costs of energy are 0.074 $/kWh and 0.056 $kWh respectively and the payback period is estimated to be around 7 years with 20 years life time of the project. This work suggests the possibility of wind farm installation and commissioning based on power density calculation and cost of land acquisition. This work emphasizes the investment for wind farms at Sujawal and Umerkot for the sustainable growth of the country. This helps out policymakers for long term planning, development of wind energy projects and attracting investment for the country.

Tropical cyclone damage assessment of distributed infrastructure systems under spatially correlated wind speeds

Probabilistic damage evaluation and loss estimation of spatially distributed infrastructure systems (e.g. an electric power system or a building portfolio) under a scenario tropical cyclone must consider the spatial correlation of cyclone wind speeds to estimate their impact on the built environment statistically. Previous studies have seldom considered the impact of this spatial correlation on damage assessments of distributed civil infrastructure. In this paper, a stochastic field model is developed to capture the uncertainty of cyclone wind speeds and their spatial correlation for the North Atlantic region. A series of recorded wind speed fields of historical cyclone events are examined. The bias values between the recorded wind speeds and computed wind speeds based on a widely used cyclonic wind field model are obtained. The statistics of the wind field bias are estimated using geostatistical tools. The effect of wind speed uncertainty and spatial correlation on performance assessment of distributed infrastructure systems is illustrated using an electric power system, where the metrics of performance are damage ratio, outage ratio and outage cost.

Coastal Wind Power in Southern Santa Catarina, Brazil

A light detection and ranging (LIDAR) wind profiler was used to estimate the wind speed in the southern coast of Santa Catarina State, Brazil. This profiler was installed on a coastal platform 250 m from the beach, and recorded wind speed and direction from January 2017 to December 2018. The power generation from three wind turbines was simulated, to obtain estimations of the average power, energy generation and capacity factor, as well as to assess the performance of a hypothetical wind farm. The scale and shape parameters of the Weibull distribution were evaluated and compared with those of other localities in the state. The prevailing winds tend to blow predominantly from the northeast and southwest directions. Wind magnitudes are higher for the NE and SW ocean sectors where the average wind power density can reach 610–820 W m−2. The Vestas 3.0 turbine spent the largest percentage of time in operation (>76%). The higher incidence of strong northeasterly winds in 2017 and more frequent passage of cold fronts in 2018 were attributed to the cycle of the South Atlantic subtropical high. The results demonstrate a significant coastal wind power potential, and suggest that there is a significant increase of resources offshore.

Domesticating Commercially Important Native Tree Species in the Philippines: Early Growth Performance Level

Selection of native tree species for commercial purposes is a continuing challenge and an opportunity in tropical silviculture. Because of this, we explored domesticating 33 native species in the Philippines that were tested for survival rate, total height, and diameter-at-ground-level (dgl) increments. The first five years (2014–2018) of assessment showed that 13 species (40%) of the 33 native species reached a survival rate of more than 80%. Grouped as ‘slow’-, ‘medium’- and ‘fast’-growing field trial species, a 709 cm average total height at five years was attained by the fast-growing cluster where Bagalunga (Melia dubia L.) and Kupang (Parkia javanica (D.C.) Merr.) were among the fastest-growing species. Slow-growing trees like Tindalo (Afzelia rhomboidei (Blanco)) and Kamagong (Diospyros blancoi (Willd)) were among the slowest-growing with an average height of 193.8 cm. Dipterocarps like Yakal (Shorea stylosa (Foxw.)), Tanguile (Shorea polysperma (Blanco)) and Mayapis (Shorea squamata (Blanco) Merr.) had the lowest diameter at ground level (dgl) increments (average 25.9 mm) while diametric expansion of fast-growing species spanned up to 93.5 mm. Overall, height and dgl increments were almost five times the original measurement five years after planting. A sudden surge in the rate of change in total height (83%) and dgl (72%) occurred a year after planting, yet a sudden decline occurred in the fifth year with only 21% for height and 23% for diameter growth suggesting the first 3–4 years as the crucial stage in seedling development. Survival rate is better correlated with the changes in dgl increment (R2 = 0.19, p < 0.05) than the height growth (R2 = 0.12, p < 0.05). Increasing rainfall and optimum air temperature significantly correlated with height and diameter growth while any increase in recorded wind speed slightly reduced the growth of the species. Our findings are initial steps towards developing appropriate silvicultural and management interventions when planning for the massive plantation development of domesticated Philippine native trees in the future.

Gravity Wave Excitation during the Coastal Transition of an Extreme Katabatic Flow in Antarctica

Abstract The offshore extent of Antarctic katabatic winds exerts a strong control on the production of sea ice and the formation of polynyas. In this study, we make use of a combination of ground-based remotely sensed and meteorological measurements at Dumont d’Urville (DDU) station, satellite images, and simulations with the Weather Research and Forecasting Model to analyze a major katabatic wind event in Adélie Land. Once well developed over the slope of the ice sheet, the katabatic flow experiences an abrupt transition near the coastal edge consisting of a sharp increase in the boundary layer depth, a sudden decrease in wind speed, and a decrease in Froude number from 3.5 to 0.3. This so-called katabatic jump manifests as a turbulent “wall” of blowing snow in which updrafts exceed 5 m s−1. The wall reaches heights of 1000 m and its horizontal extent along the coast is more than 400 km. By destabilizing the boundary layer downstream, the jump favors the trapping of a gravity wave train—with a horizontal wavelength of 10.5 km—that develops in a few hours. The trapped gravity waves exert a drag that considerably slows down the low-level outflow. Moreover, atmospheric rotors form below the first wave crests. The wind speed record measured at DDU in 2017 (58.5 m s−1) is due to the vertical advection of momentum by a rotor. A statistical analysis of observations at DDU reveals that katabatic jumps and low-level trapped gravity waves occur frequently over coastal Adélie Land. It emphasizes the important role of such phenomena in the coastal Antarctic dynamics.

Spatio-Temporal Distribution and Variability of High Threshold Wind Speed and Significant Wave Height for the Indian Ocean

Space-borne satellites provide extensive coverage of measuring sea surface wind field and wave heights on a global scale. The present study provides a comprehensive assessment of distribution of extreme wind and wave fields over the Indian Ocean (IO) utilizing satellite-based scatterometer and altimeter datasets. Merged scatterometer data from ERS-1/2, QuikSCAT, and ASCAT for a period of 27 years produced continuous record of wind speed, whereas the calibrated altimeter data for different satellite missions provided information on the significant wave height. A comparison study between merged scatterometer and calibrated altimeter derived long-term maximum wind speed shows an overestimation of altimeter product by an average measure of 3 m/s and higher as compared to the scatterometer winds in 92.8% of the total observational points considered. A decadal variability was observed in the inter-annual spatial distribution of the 90th and 95th percentile winds for the study region. Interestingly, the study reveals a declining trend in the dispersion of higher waves (90th, 95th, and 99th percentiles) in the entire IO except the South China Sea. Further, 2011 onwards there is an increasing trend in the annual distribution of extreme winds and waves for the Extra-tropical South Indian Ocean having implications on the generation of swell wave fields.

A novel hybrid approach based on dynamic adaptive variable-weight optimization for short-term wind speed prediction

One of the most important preconditions for guaranteeing a smooth link between wind farms and the power system is to develop an accurate model for forecasting the wind speed. This paper describes a novel wind speed prediction model based on dynamic adaptive variable-weight optimization theory that considers the relevance of historical observations. The model applies signal preprocessing to recorded wind speed observations using ensemble empirical mode decomposition. The decomposed signals are then subjected to a random noise reduction procedure, which improves the robustness of the prediction model. An autoregressive integrated moving average model, general regression neural network, and long short-term memory are used to recognize the different features of each decomposed subsequence. Brain storm optimization is then applied to further promote the forecasting performance by integrating different forecasting models with dynamically adapted variable weights. To evaluate the prediction capacity of the proposed method, three case studies are conducted. The experimental outcomes reveal that the method presented in this paper provides more satisfactory prediction ability and robustness than other models.

Crop water requirement calculations of Longan (Dimorcapus longan L.) in Nawungan Orchard, Selopamioro Village, Imogiri Sub-District, Bantul, D.I. Yogyakarta

This research was aimed to measure actual evapotranspiration, to determine of water requirement and crop coefficient (Kc) of longan (Dimorcapus longan Lour.) was cultivated in Longan Nawungan orchard, Selopamioro Village, Imogiri Sub-district. Plot scale of water balance was applied to determine ETa, with input components were rainfall and irrigation, while output were ETa, water storage (ΔSM), and surface runoff (SRO). Components of runoff was measured using tank and the moisture content was measured using gravimetry method. Automatic weather station was installed in Nawungan orchard to record rainfall, wind speed, air humidity, and intensity of solar radiation. Later, the climatic data were used to calculate the reference evapotranspiration (ETo) using Penman-Monteith method. Due to agroforestry and mix cropping system, longan trees were cultivated among seasonal crops and other trees, then the dual crop coefficient (Kc) was preffered. During February-Maret 2019, the value of rainfall and surface runoff were 640 mm during observation period and 0,08 mm, respectively. The reference evapotranspiration (ETo) and actual evapotranspiration (ETa) were 5,76 mm/day and 7,90 mm/day, respectively. The crop coefficient of longan in the site study area was 0,30.