Subirrigation System Control for Water use Efficiency

Due to its geographical location and its poor economic conditions, Africa  is the continent most exposed to the adverse consequences of climate change, particularly on agriculture. The very low percentage of land equipped for irrigation, 3.5% in Sub-Saharan Africa, is another element of concern, sensibly reducing the ability to mitigate the likely productivity losses caused by increasing climate variability and extreme events. Fostering irrigation in Africa is therefore a priority, but due to a limited amount of resources, both in economic and physical (e.g. harvestable water) terms, irrigation projects have to be planned carefully and appropriate locations should be prioritized. The present paper tries to assess the potentials of irrigation in Sub-Saharan Africa and to individuate the locations to be prioritized. The analysis focuses on four cereals, maize, millet, sorghum and wheat, among the most common staples in the region, and relies on a mix of crop modelling (DSSAT) and machine learning (XGBoost) to draw its conclusions. Specifically, for all four crops, crop simulations under rain-fed conditions and optimal irrigation, with DSSAT adding water every time a need for it is observed, are performed on a sample of all Sub-Saharan agricultural plots. Yields differentials and water requirements for optimal irrigation are then computed. Subsequently, yields and water requirements are predicted for all remaining agricultural locations through machine learning, using as explanatory variables the same inputs, soil characteristics, management practices and weather variables, required by DSSAT. Water productivity, defined as the ratio of yields differentials over water requirements for irrigation, is finally computed to individuate the locations where irrigation projects would be most beneficial. By further relying on a continental map of run-off values, we individuate two types of priority locations: areas where simple water capture and storage devices are viable and areas where more complex systems are necessary. The paper points out the importance of irrigation in Sub-Saharan Africa, showing significant gains in yields, up to 100% compared to rain-fed conditions. It also finds high potentials for water capture and storage devices in the south-eastern part of the continent and in South Africa, while the western part and the stripe bordering the Sahara desert would have to rely on more complex irrigation systems.

Similar to many complex systems, the operation process of electric balanced forklifts has characteristics such as time-varying model parameters and nonlinearity. Establishing an accurate mathematical model becomes challenging, making it difficult to apply model-based control methods in engineering practice. Aiming at the longitudinal control system of electric forklifts containing external disturbances, this paper proposes an improved full-format dynamic linearization model-free adaptive PID control (iFFDL-MFA-PID) method. Firstly, the full-format dynamic linearization (FFDL) method is employed to transform the operating system of the electric balanced forklift into a virtual equivalent linear data model. Secondly, the nonlinear residual term and pseudo-gradient (PG) of the data model are estimated using the difference estimation algorithm and the optimal criterion function, respectively. Furthermore, in order to enhance the robustness of the system, the idea of intelligent PID (iPID) is introduced and the principle of equivalent feedback is utilized to derive the iFFDL-MFA-PID control scheme. The design process of this scheme only requires the use of the input and output data of the system, without relying on the mathematical model of the system. Finally, the iFFDL-MFA-PID method proposed in this paper is simulated and tested with the EFG-BC/320 counterbalanced forklift equipped in the Special Equipment Testing Center and compared with the model-free adaptive control method (FFDL-MFAC) and the PID control method. Simulation results show that the speed-tracking error of the electric forklift truck under the action of the iFFDL-MFA-PID algorithm is maintained within ±0.132 m/s throughout the process, achieving higher tracking accuracy and better robustness compared to the MFAC and PID methods.

Driving range evaluation of electric vehicle with transcritical CO2 thermal management system under different battery temperature controls

In this work, a direct torque control (DTC) method for multi-machine systems is applied to electric vehicles (EVs). Initially, the DTC control method associated with the model reference adaptive system (MRAS) is used for speed control, and management of the magnetic quantities is ensured by the variable master-slave control (VMSC). In order to increase the technical performance of the studied system, a DTC method has been associated with a fuzzy logic approach. These two control methods are applied to the traction chain of an electric vehicle to highlight its speed, precision, stability, and robustness metric during particular stress tests imposed on the wheel motor. The results obtained in MATLAB/Simulink software made feasible a comparison of two proposed methods based on their technical performances. It should be noted that the direct fuzzy logic torque control (DFTC) has better performance than the DTC associated with the MRAS system as a rise time reduction of 1.4%, an oscillation of torque, and flux amplitude of less than 9%, static steady-state error near zero. The DTFC control method responds favorably to electric vehicle traction chain systems by the nature of the comfort and safety provided.

Pasture performance of 924 dairy farms in a major irrigation district of Australia was investigated for their water use and water productivity during the 2015-2016 summer which was the peak irrigation period. Using satellite images from Landsat-8 and Sentinel-2, estimates of crop coefficient (Kc) were determined on the basis of a strong linear relationship between crop evapotranspiration (ETc) and vegetation index (NDVI) of pasture in the region. Utilizing estimates of Kc and crop water requirement (CWR), NDVI-dependent estimates of Irrigation Water Requirement (IWR) were derived based on the soil water balance model. In combination with daily weather information and seasonal irrigation water supply records, IWR was the key component in the understanding of current irrigation status at farm level, and deriving two irrigation performance indicators: (1) Relative Irrigation Water Use (RIWU) and (2) Total Irrigation Water Productivity (TIWP). A slightly higher proportion of farm irrigators were found to be either matching the irrigation requirement or under-watering (RIWU ≤ 1.0). According to TIWP, a few dairy farms (3%) were found to be in the category of high yield potential with excess water use, and very few (1%) in the category of limited water supply to pastures of high yield potential. A relatively high number of farms were found to be in the category where excess water was supplied to pastures of low-medium yield potential (27%), and farms where water supply compromised pastures with a sub-maximal vegetation status (15%). The results of this study will assist in objectively identifying where significant improvement in efficient irrigation water use can be achieved.

Water and nitrogen are the main limiting factors affecting agricultural production in arid and semiarid regions. Therefore, improving the efficiency of these factors is very important. The method of fertilizer application is affecting water and fertilizer use efficiency. The objective of this study was to investigate the effect of furrow fertigation on fertilizer use efficiency (FUE), water use efficiency (WUE), and corn yield. A field experiment was carried out in furrows which have 165m length and 0.006 (m/m) slope in Karaj. The corn Hybrid 370 double-cross was planted on June 2008. A factorial design based on randomized complete block design with 4 replicates. Four levels (0, 60, 80 and 100%) of the recommended fertilizer value and four levels (60, 80, 100, and 120%) of the irrigation water requirement were applied. These 16 treatments were compared with traditional fertilizer application method. Fertilizer treatments were accomplished in four critical stages of the growth (before cultivation, in seven leaves stage, shooting stage and Flowering stage) for fertigation treatments and two stages (before cultivation and seven leaves stage) for the traditional method. Results showed that effects of levels of different water and fertilizer on yield component were significant. Water use efficiency (WUE) was significantly affected by nitrogen rate. On the other hand, water treatments significantly affected fertilizer use efficiency. Increasing fertilizer increased water use efficiency. Increasing water levels to 100% of ETC resulted in increasing fertilizer use efficiency. Highest yield was obtained from the full irrigation treatments (W100%). Albeit the difference among W120%, W100% and W80% was not significant (P=0.05), because W100% was always higher than W120%, treatment of W80% recommends as optimum water level for arid and semi arid region. The maximum and minimum WUE was 2.24 and 0.66 (kg/m3) in W80%N100% and W100%N60%, and The maximum and minimum FUE was 29.85 and 8.52 (kg/kg) in W100%N100% and traditional method, respectively. Key words: Fertigation, Fertilizer use efficiency, Productivity, Corn

Climate change is a well-known phenomenon all over the globe. The influence of projected climate change on agricultural production, either positive or negative, can be assessed for various locations. The present study was conducted to investigate the impact of projected climate change on rice’s production, water demand and phenology for the state of Bihar, India. Furthermore, this study assessed the irrigation water requirement to increase the rice production by 60%, for the existing current climate scenario and all the four IPCC climate change scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) by the 2050s (2050–2059). Various management practices were used as adaptation methods to analyze the requirement of irrigation water for a 60% increase in rice production. The climate data obtained from the four General Circulation Models (GCMs) (bcc_csm1.1, csiro_mk3_6_0, ipsl_cm5a_mr and miroc_miroc5) were used in the crop growth model, with the Decision Support System for Agrotechnology Transfer (DSSAT) used to simulate the rice yield, phenological days and water demand under all four climate change scenarios. The results obtained from the CERES-Rice model in the DSSAT, corresponding to all four GCMs, were ensembled together to obtain the overall change in yield, phenology and water demand for 10 years of interval from 2020 to 2059. We investigated several strategies: increasing the rice’s yield by 60% with current agronomic practice; increasing the yield by 60% with conservation agricultural practice; and increasing the rice yield by 30% with current agronomic practice as well as with conservation agricultural practices (assuming that the other 30% increase in yield would be achieved by reducing post-harvest losses by 30%). The average increase in precipitation between 2020 and 2059 was observed to be 5.23%, 13.96%, 9.30% and 9.29%, respectively, for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5. The decrease in yield during the 2050s, from the baseline period (1980–2004), was observed to be 2.94%, 3.87%, 4.02% and 5.84% for RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5, respectively. The irrigation requirement was predicted to increase by a range of 39% to 45% for a 60% increase in yield using the current agronomic practice in current climate scenario and by 2050s with all the four climate change scenarios from the baseline period (1980–2004). We found that if we combine both conservation agriculture and removal of 30% of the post-harvest losses, the irrigation requirement would be reduced by 26% (45 to 19%), 20% (44 to 24%), 21% (43 to 22%), 22% (39 to 17%) and 20% (41 to 21%) with current climate scenario, RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 conditions, respectively. This combination of conservation practices suggests that the irrigation water requirement can be reduced by a large percentage, even if we produce 60% more food under the projected climate change conditions.

The Mekong River is the largest transboundary river in Southeast Asia and the main source of water supply for agricultural irrigation in the Lower Mekong River Basin (LMRB), supporting socioeconomic development and the livelihoods of millions of people. Irrigation accounts for more than 70% of water use in the LMRB, and issues of water use and allocation in the basin attract much attention, especially in dry years. However, there is a lack of systematic and up-to-date estimation of irrigation water requirements (IWR) in the LMRB, for historical and climate change conditions, which are essential for water resources planning and management in the basin. We use gridded meteorological and crop land use data to estimate monthly IWR at 5-arc minute resolution in the five LMRB countries, namely Myanmar, Laos, Thailand, Cambodia and Vietnam, using meteorological observations of 1991-2020 and climate projections for 2031-2060 and 2061-2090 by five global climate models under two climate scenarios, SSP126 and SSP585. Crop water productivity and water footprint are also estimated along with IWR. Under historical climate, the total IWR in the LMRB is estimated to be 20.44 billion m3, with Vietnam having the largest share of 9.18 billion m3, followed by Thailand with 7.54 billion m3. IWR concentrates in the dry season of November-April, accounting for 78.4% of annual IWR. Rice is the main water-consuming crop, accounting for 86.7% of total IWR. Relative to historical climate condition, SSP126 generally leads to slightly decreased IWR, whereas SSP585 leads to a large increase in IWR. Crop water productivity of rice is unevenly distributed in the basin, being higher in Vietnam and Laos and lower in Cambodia and Thailand. Green water footprint of rice is about 3.7 times higher than that of blue water footprint, indicating most of rice water consumption is from precipitation. Under SSP126, there is little change in water footprint, however under SSP585 blue water footprint increases significantly, in 2061-2090. This study provides update-to-date and high-resolution IWR estimates which can support water use and allocation dialogue, policy-making and management in the basin.

In this paper we provide a review of the state of the art for active vibration control of axially moving materials (string and beam, etc.) in the past ten years, with particular regard to the subjects of some important active control methods of axially moving strings. First, an introduction is given to explain the aims and scope of this paper. This is followed by a comprehensive discussion of the active wave control methods presented by many investigators in the past ten years, including feedback control methods (such as the modal control method, the direct velocity feedback control method and the control method via transfer function formulation), active wave control methods combining transfer function, boundary control methods using the Lyapunov function, the variable structure control method, the adaptive control method, the vibration control of an axially moving beam and the active control of a moving material with arbitrarily varying length, etc. Finally, we conclude with a discussion of several issues for future research in this area.

Understanding crop water requirements (CWR) in semi-arid region is essential for better irrigation practices, scheduling and efficient use of water since the water supply through rainfall is limited. This paper estimated the crop reference and actual evapotranspiration (Eto and ETc) respectively and the irrigation water requirement of rice (Oryza sativa L.) in Benin’s sub-basin of Niger River (BSBNR) of west Africa, using CROPWAT model. The long recorded climatic data, crop and soil data from 1942 to 2012 were computed with the Cropwat model which is based on the United Nations’ Food and Agriculture Organization (FAO) paper number 56 (FAO56). The Penman-Monteith method was used to estimate ETo. Crop coefficients (Kc) from the phenomenological stages of rice were applied to adjust and estimate the actual evapotranspiration ETc through a water balance of the irrigation water requirements (IR). The results showed the BSBNR annual reference evapotranspiration (ETo) was estimated at 1 967 mm. The lowest monthly value of ETo of 123 mm, was observed in August month, middle of the rainy season while the highest value 210 mm was observed in March within dry season. The crop evapotranspiration ETc and the crop irrigation requirements were estimated at 651 mm and 383 mm, respectively in rainy season and 920 mm and 1 148 mm, respectively within a dry season. Irrigation projects of these seasons can then be scheduled for water use efficiency based on these findings. Keywords: crop evapotranspiration, irrigation water requirement, rice, CROPWAT, model, Benin DOI: 10.3965/j.ijabe.20150802.1290

1   ABSTRACT   The objective of this research was to estimate the future water requirements for rice paddy irrigation in the Pardo River Basin (Brazil) taking into account the changes in cultivation systems that are likely to occur in the near future in that region. After identifying the major trends in the rice cultivation systems, different scenarios were set and the water requirements for these scenarios were estimated using mathematical modelling and geoprocessing techniques. Census data indicate that the rice-growing area in the Pardo River Basin is expanding. However, the use of water per hectare is decreasing, as a result of increasing water use efficiency. The main agent behind this higher efficiency is land-levelling, which allows for a reduced volume of water required for flooding the paddies. Despite this improvement however, the overall water demands in future scenarios will still be greater than the current demands due to the expansion of the farmed area. However, these demands can be minimized if land-levelling is adopted more intensively across the entire Basin. Otherwise, there will be a need for either controlling the expansion of the rice-growing area, or increasing water availability through construction of additional reservoirs to minimize potential conflict amongst water users in the near future.   Keywords: rice, water requirements, irrigation, GIS, water availability demand

Estimating water requirements and water balance for irrigated agricultural areas are important and will facilitate the efficient allocation of water resources for agriculture while minimizing the impact on natural ecosystems in arid regions. Based on the Penman-Monteith formula and GIS technology, the irrigation water requirements (IWR) of three main crops (cotton, corn and wheat) during the growing season were estimated and their spatio-temporal changes over the past 23 years (1995–2017) were analyzed in Xinjiang province, China. Our results indicated a dramatic increase in IWR from 14.12 billion m3 in 1995 to 38.99 billion m3 in 2017 due to the rapid cropland expansion of approximately 2.58 × 104 km2 in this period. Monthly IWR usually peaked in summer from May to July and varied in different basins. From the perspective of crops, cotton was identified to have consumed the largest amount of water, reaching 26.39 billion m3 in 2017, accounting for 67.68% of total water consumption. Spatially, the fastest increasing rate of IWR was Tarim Basin, which was attributable to the increase in water requirement of cotton. By comparing IWR and actual irrigation of Xinjiang in 2014, the amount of water scarcity had reached −15.01 billion m3 (−9.80 billion m3 in Tarim Basin and −6.58 billion m3 in Junggar Basin). The planting areas of three main crops (wheat, corn and cotton) were more sensitive to IWR than rising temperature indicated by our model. This study is of great significance for the scientific allocation of water resources in the irrigated areas of the different prefectures of Xinjiang.

Groundwater resources have a fundamental importance to satisfy the rapidly increasing agricultural, livestock and domesticwater requirements within the region especially in Robit watershed. Hence the quantification of this water resource is important for the efficient and sustainable water resource management. In this study spatial variability of irrigation water requirement, water use (abstractions) and groundwater recharge were estimated for Robit watershed within the eastern part of Lake Tana. Satellite image of Planet Scope on 2nd February 2017 was used to estimate area and type of crops cultivated in the watershed. CROPWAT model has been used to calculate the particular evapotranspiration and water requirement for irrigation using local climatic data. This was calculated for the dominant irrigated crops of Khat (Catha edulis Forsk), hop (Rhamnus prinoides), coffee, tomato and green pepper within the study area. Calibrated QSWAT model was applied to estimate net ground water recharges using local climatic data, soil map, crop management data and derived land use map from satellite image processing. The assessment showed that the entire amount of water applied for irrigation, domestic and livestock purposes was estimated as 1.35 Mm3/year, 0.02 Mm3/year and 0.03 Mm3/year respectively. Net groundwater recharge was estimated as 3.18 Mm3/year within the watershed. The estimation from the water abstraction survey showed that the total volume of water abstracted within the watershed was estimated as 1.40 Mm3/year. From the assessment it can be clearly seen that only 44% of ground water resource is extracted annually within the area and there is some potential to expand irrigation areas and the current water usage for various purposes in the future.KeywordsWater abstraction surveyPLANETSCOPE imageERDAS IMAGINEQSWATGW rechargesCROPWATSWATCUP

An AMB is not widely used because of its high cost and because its dimensions are significantly larger than those of mechanical bearings. Since a 6 salient-pole type AMB has fewer poles than the usual 8 salient-pole type AMB, it is easier and less costly to miniaturize. However, because the magnetic circuit is not independent in the x and y directions, bearing forces for coil currents become complicated. To solve this problem, two control methods have been proposed. One is a minimum energy control method, which minimizes copper loss in coils. The other is a maximum bearing force control method, which generates a larger bearing force than that of the minimum energy control method. In this study, the two control methods are introduced and rotational tests are carried out for comparison. The rotor could rotate up to 53,000 rpm with the minimum energy control and maximum bearing force control methods. Moreover, rotational tests were carried out with attaching a weight to the rotor. The rotor could rotate up to 42,000 rpm and 38,000 rpm with the minimum energy control method and maximum bearing force control method, respectively. Experimental results show that the minimum energy control method provides less power consumption than the maximum bearing force control method. On the other hand, the maximum force control method provides smaller maximum coil current than that of the minimum energy control method.

Declining trends of water requirements of dry season Boro rice in the north-west Bangladesh