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A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Water Management".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 29818

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Special Issue Editor

Dr. Dongwei Gui

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Guest Editor

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: water resource management in arid area; desertification and oasification; model simulations; decision support system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water is the greatest constraining factor for higher agricultural productivity in drylands which accounts for 45% of Earth’s surface. Water availability is threatened by the reduction in surface and ground water due to diminishing biomass, climate change, poor management of resources, inaccessibility and droughts. Unplanned water management may cause aquifer depletion, soil and/or water salinization, land degradation and loss of water through evapotranspiration due to inadequate irrigation systems. Therefore, precise water management in drylands is fundamental to improve food production, sustainability of water resources and economic growth, as well as maximize water use efficiency. Precision water management will encompass optimization of irrigation water at the farm level, allocation of surface and ground water at the regional level and harnessing water at the watershed level. Modern day smart and intelligent information processing and data analytics approaches, such as modeling techniques, remote sensing, machine learning, unmanned aerial systems (UAS), wireless sensor networks (WSN), geographical information systems (GIS), and spectral images, can help ensure better decision making about water management for drylands.

This Special Issue on “Precision water management in dryland agriculture” is intended to provide new perspectives on dryland water management at the farm, regional and watershed levels, driven by smart technologies. Therefore, research articles, review articles and case studies involving emerging technologies and their use in water resource optimization, allocation, exploration and management, with a special focus on dryland agriculture, are warmly welcome.

Dr. Dongwei Gui
Guest Editor

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Keywords

dryland agriculture
irrigation management
model simulations
Internet of Things (IoT)
decision support system

Published Papers (13 papers)

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Research

15 pages, 3902 KiB

Open AccessArticle

Deep Machine Learning for Forecasting Daily Potential Evapotranspiration in Arid Regions, Case: Atacama Desert Header

by Edwin Pino-Vargas, Edgar Taya-Acosta, Eusebio Ingol-Blanco and Alfonso Torres-Rúa

Agriculture 2022, 12(12), 1971; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12121971 - 22 Nov 2022

Cited by 5 | Viewed by 1848

Abstract

Accurately estimating and forecasting evapotranspiration is one of the most important tasks to strengthen water resource management, especially in desert areas such as La Yarada, Tacna, Peru, a region located at the head of the Atacama Desert. In this study, we used temperature, humidity, wind speed, air pressure, and solar radiation from a local weather station to forecast potential evapotranspiration (ETo) using machine learning. The Feedforward Neural Network (Multi-Layered Perceptron) algorithm for prediction was used under two approaches: “direct” and “indirect”. In the first one, the ETo is predicted based on historical records, and the second one predicts the climate variables upon which the ETo calculation depends, for which the Penman-Monteith, Hargreaves-Samani, Ritchie, and Turc equations were used. The results were evaluated using statistical criteria to calculate errors, showing remarkable precision, predicting up to 300 days of ETo. Comparing the performance of the approaches and the machine learning used, the results obtained indicate that, despite the similar performance of the two proposed approaches, the indirect approach provides better ETo forecasting capabilities for longer time intervals than the direct approach, whose values of the corresponding metrics are MAE = 0.033, MSE = 0.002, RMSE = 0.043 and RAE = 0.016. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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14 pages, 3948 KiB

Open AccessArticle

Effects of Farmland Landscape Fragmentation on Agricultural Irrigation in Hotan Oasis

by Lei Zhang, Yunfei Liu, Changjun Yin, Dongping Xue, Dongwei Gui and Zhiming Qi

Agriculture 2022, 12(9), 1503; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12091503 - 19 Sep 2022

Cited by 1 | Viewed by 1516

Abstract

Farmland landscape fragmentation is an important problem affecting the agricultural modernization process in China. However, farmland landscape fragmentation leads to land being wasted and increases management costs, particularly in the dryland’s oasis regions. Therefore, investigating the impact of farmland landscape fragmentation on agricultural irrigation is of great significance in developing oasis agriculture. This paper used the landscape quantitative index (DIVISION), the moving window method, and gradient analysis methods to study the temporal and spatial pattern changes in farmland fragmentation in the Hotan Oasis. Additionally, the impact of fragmentation on irrigation in the oasis was elaborated upon by exploring the relationship between evapotranspiration and its components in farmland fragmentation. The results showed that the farmland area of the Hotan Oasis increased from 1546.19 km² in 2000 to 2068.23 km² in 2020, and farmland landscape fragmentation increased with the expansion of the Hotan Oasis. In addition, a significant relationship between farmland fragmentation and evapotranspiration and its components was evident. A lower DIVISION value corresponded to a higher ET value, a lower ETs/ETc ratio, and a higher water use efficiency. When the total farmland area is assumed to remain unchanged, the irrigation water consumption is reduced by 4.82 × 10⁸ m³ according to the size and proportion of arable land with the lowest degree of fragmentation (L1, division value of 0.46). In addition, with the increase in the proportion of farmland, the scale of oasis decreases by 2431.56 km² for the reduction in field roads, shelterbelt, and bare land. These findings suggest that solving the problem of farmland fragmentation can effectively reduce irrigation water consumption, realize the internal expansion of the oasis through intensive land use, and relieve the pressure of the external expansion of the oasis. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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13 pages, 3394 KiB

Open AccessArticle

Optimizing Deficit Irrigation Management to Improve Water Productivity of Greenhouse Tomato under Plastic Film Mulching Using the RZ-SHAW Model

by Haomiao Cheng, Shu Ji, Hengjun Ge, Mohmed A. M. Abdalhi, Tengyi Zhu, Xiaoping Chen, Wei Ding and Shaoyuan Feng

Agriculture 2022, 12(8), 1253; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12081253 - 18 Aug 2022

Viewed by 1630

Abstract

Deficit irrigation (DI) is a widely recognized water-saving irrigation method, but it is difficult to precisely quantify optimum DI levels in tomato production. In this study, the Root Zone Water Quality-Simultaneous Heat and Water (RZ-SHAW) model was used to evaluate the potential effects of different DI levels on tomato growth in a drip-irrigated field. Combinations of five DI scenarios were tested in greenhouse field experiments under plastic film mulching according to the percentage of crop evapotranspiration (ET), i.e., ET50, ET75, ET100, ET125, and ET150. The model was calibrated by using the ET100 scenario, and validated with four other scenarios. The simulation results showed that the predictions of tomato growth parameters and soil water were in good agreement with the observed data. The relative root mean square error (RRMSE), the percent bias (PBIAS), index of agreement (IoA) and coefficient of determination (R²) for leaf area index (LAI), plant height and soil volumetric water content (VWC) along the soil layers were <23.5%, within ±16.7%, >0.72 and >0.56, respectively. The relative errors (REs) of simulated biomass and yield were 3.5–8.7% and 7.0–14.0%, respectively. There was a positive correlation between plant water stress factor (PWSF) and DI levels (p < 0.01). The calibrated model was subsequently run with 45 different DI scenarios from ET0 to ET225 to explore optimal DI management for maximizing water productivity (WP) and yield. It was found that the maximum WP and yield occurred in ET95 and ET200, with values of 28.3 kg/(ha·mm) and 7304 kg/ha, respectively. The RZ-SHAW demonstrated its capacity to evaluate the effects of DI management on tomato growth under plastic film mulching. The parameterized model can be used to optimize DI management for improving WP and yield based on the water stress-based method. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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18 pages, 5186 KiB

Open AccessArticle

Study on the Spatial Allocation of Receding Land and Water Reduction under Water Resource Constraints in Arid Zones

by Xin Yan, Yuejian Wang, Yuejiao Chen, Guang Yang, Baofei Xia and Hailiang Xu

Agriculture 2022, 12(7), 926; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12070926 - 26 Jun 2022

Cited by 1 | Viewed by 1304

Abstract

The withdrawal of cultivated land policy is not only an important task to promote cultivated land rest and alleviate the contradiction between supply and demand of water resources in arid areas, but also an important way to realize the sustainable development of agriculture and social economy. This study adopted the minimum per capita area method, ESPR (Exposure-Sensitivity-Pressure-Response) vulnerability assessment model, grey prediction model, and GIS spatial analysis. Furthermore, based on the characteristics of water resource constraints in the arid zone, Manas County was used as the study area. By exploring and analyzing the area of land retreat, through identifying its occurrence and position, the spatial zoning layout of land retreat can be realized to guarantee the effective implementation of water retreat and reduction. The following points were noted from the results: (1) the upper and lower limits of the area of receding land in Manas County were measured using the minimum per capita area method and the principle of balancing water supply and demand. The receding land in Manas County measured 16,493.68–20,749.90 hm², which accounted for 24.31–30.58% of the total area of cultivated land. (2) The results obtained from constructing the ESPR vulnerability assessment model, used to assess the vulnerability of cultivated land in Manas County, showed that the overall vulnerability of cultivated land in Manas County was high, with 94.74% of the county’s cultivated land being moderately vulnerable or worse, which necessitates the optimization of land use. (3) The area of cultivated land withdrawal under the water resource constraint was used as a constraint for the withdrawal of cultivated land. Based on the evaluation of the vulnerability of cultivated land, with the results arranged from small to large, it was concluded that the area of cultivated land withdrawal in Manas County could reach up to 16,787.34 hm². There are four types of cultivated land withdrawals: desertified withdrawal, saline withdrawal, groundwater overexploitation withdrawal, and soil contamination withdrawal. The results of this study can provide a reference for Manas County to scientifically formulate a reasonable and orderly withdrawal system of farmland to reduce water use. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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24 pages, 2764 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Agricultural Water Resources Carrying Capacity and Its Influencing Factors: A Case Study of Townships in the Arid Region of Northwest China

by Penglong Wang, Yao Wei, Fanglei Zhong, Xiaoyu Song, Bao Wang and Qinhua Wang

Agriculture 2022, 12(5), 700; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050700 - 16 May 2022

Cited by 15 | Viewed by 2227

Abstract

The water resources carrying capacity (WRCC) strongly determines the agricultural development in arid areas. Evaluation of WRCC is important in balancing the availability of water resources with society’s economic and environmental demands. Given the demand for sustainable utilization of agricultural water resources, we combine the water stress index and comprehensive index of WRCC and use multi-source data to evaluate agricultural WRCC and its influencing factors at the township scale. It makes up for the deficiencies of current research, such as the existence of single-index evaluation systems, limited calibration data, and a lack of a sub-watershed (i.e., township) scale. By applying multi-source data, this study expands the spatial scale of WRCC assessment and establishes a multidimensional evaluation framework for the water resources in dryland agriculture. The results indicate water stress index ranges from 0.52 to 1.67, and the comprehensive index of WRCC ranges from 0.25 to 0.70, which are significantly different in different types of irrigation areas and townships. Water quantity and water management are key factors influencing WRCC, the water ecosystem is an area requiring improvement, and the water environment is not a current constraint. Different irrigation areas and different types of townships should implement targeted measures to improve WRCC. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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14 pages, 9925 KiB

Open AccessArticle

RZWQM2 Simulated Drip Fertigation Management to Improve Water and Nitrogen Use Efficiency of Maize in a Solar Greenhouse

by Haomiao Cheng, Qilin Yu, Mohmed A. M. Abdalhi, Fan Li, Zhiming Qi, Tengyi Zhu, Wei Cai, Xiaoping Chen and Shaoyuan Feng

Agriculture 2022, 12(5), 672; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050672 - 08 May 2022

Cited by 5 | Viewed by 1717

Abstract

The drip fertigation technique is a modern, efficient irrigation method to alleviate water scarcity and fertilizer surpluses in crop production, while the precise quantification of water and fertilizer inputs is difficult for drip fertigation systems. A field experiment of maize (Zea mays L.) in a solar greenhouse was conducted to meet different combinations of four irrigation rates (I₁₂₅, I₁₀₀, I₇₅ and I₅₀) and three nitrogen (N) fertilizer rates (N₁₂₅, N₁₀₀ and N₇₅) under surface drip fertigation (SDF) systems. The Root Zone Water Quality Model (RZWQM2) was used to assess the response of soil volumetric water content (VWC), leaf area index (LAI), plant height and maize yield to different SDF managements. The model was calibrated by the I₁₀₀N₁₀₀ scenario and validated by the remaining five scenarios (i.e., I₁₂₅N₁₀₀, I₇₅N₁₀₀, I₅₀N₁₀₀, I₁₀₀N₁₂₅ and I₁₀₀N₇₅). The predictions of VWC, LAI and plant height were satisfactory, with relative root mean square errors (RRMSE) < 9.8%, the percent errors (PBIAS) within ±6%, indexes of agreement (IoA) > 0.85 and determination of coefficients (R²) > 0.71, and the relative errors (RE) of simulated yields were in the range of 1.5–7.2%. The simulation results showed that both irrigation and fertilization had multiple effects on water and N stresses. The calibrated model was subsequently used to explore the optimal SDF scenarios for maximizing yield, water use efficiency (WUE) or nitrogen use efficiency (NUE). Among the SDF managements of 21 irrigation rates × 31 N fertilizer rates, the optimal SDF scenarios were I₁₂₀N₁₃₀ for max yield (10516 kg/ha), I₅₀N₇₀ for max WUE (47.3 kg/(ha·mm)) and I₁₂₅N₇₅ for max NUE (30.2 kg/kg), respectively. The results demonstrated that the RZWQM2 was a promising tool for evaluating the effects of SDF management and achieving optimal water and N inputs. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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14 pages, 10116 KiB

Open AccessArticle

Prediction of the Irrigation Area Carrying Capacity in the Tarim River Basin under Climate Change

by Qi Liu, Yi Liu, Jie Niu, Dongwei Gui and Bill X. Hu

Agriculture 2022, 12(5), 657; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050657 - 30 Apr 2022

Cited by 7 | Viewed by 2076

Abstract

The Tarim River Basin (TRB) is one of the world’s largest cotton-producing areas, and its agricultural water use accounts for up to 95% of the total water consumption in the basin. Quantifying the future changes in the irrigation area carrying capacity under global warming is therefore essential in TRB. In this study, we analyzed the variation in the irrigation area in TRB over the last few decades, utilized the nonlinear autoregressive with an exogenous input neural network to simulate the future changes in the available water resources, and predicted the future irrigation area carrying capacity based on the water balance equation. The results showed that the present (1970–2020) irrigation area in TRB exhibited an increasing trend from 491 km² in 1970s to 1382 km² in 2020, as most of the natural vegetation was transformed into cropland. In the future (2022–2050), the available water resource will show an upward tendency while the irrigation area carrying capacity mainly ranges from

12 \times 10^{2} - 21 \times 10^{2} {km}^{2}

and

17 \times 10^{2} - 30 \times 10^{2} {km}^{2}

under scenarios SSP (shared socioeconomic pathway) 245 and SSP585, respectively. The simulated results will provide useful information for the allocation of water resources and the regional sustainable development of TRB. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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Graphical abstract

18 pages, 14882 KiB

Open AccessArticle

Interaction Simulation of Vadose Zone Water and Groundwater in Cele Oasis: Assessment of the Impact of Agricultural Intensification, Northwestern China

by Dongping Xue, Heng Dai, Yi Liu, Yunfei Liu, Lei Zhang and Wengai Lv

Agriculture 2022, 12(5), 641; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050641 - 28 Apr 2022

Cited by 2 | Viewed by 2931

Abstract

Agricultural intensification has boosted land productivity, but it has also created new sustainability issues. As one of the most important human habitations and agricultural farming areas in arid areas, the Cele Oasis has a very developed agricultural system. This paper studies the long-term effects of different types of agricultural intensification strategies on groundwater level fluctuations in the Cele Oasis. A soil water flow (HYDRUS-1D) and aquifer simulation (MODFLOW) coupling model were used to construct the geometric structures of the vadose zone and saturated zone in the Cele Oasis and to analyze the recharge and discharge mechanism of the oasis. The results showed that HYDRUS-1D accurately simulated soil moisture transport in the Cele Oasis, providing reliable data for calibration of the MODFLOW model. The groundwater level simulated by MODFLOW was in good agreement with the observed value. The results of the R², RMSE, and NSE were ranges of 0.77–0.90, 0.45–0.74 m, and 0.76–0.87, respectively. The errors were acceptable limits. The coupling model predicted the responses of different agricultural types and cropping scenarios to groundwater. Predictions showed that the groundwater level in the Cele Oasis remained stable under the current cropping scenario (100% cropping intensity), and that the groundwater level decreased slightly under the cropping scenario (110% cropping intensity and 130% cropping intensity). When the cropping scenario was at 170% cropping intensity, the groundwater level decreased rapidly, and the maximum drawdown value was 7 m. Therefore, the maximum cropping intensity of the Cele Oasis in the future should be 130% of the current cropping intensity. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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17 pages, 4930 KiB

Open AccessArticle

Conservation Agriculture in Semi-Arid Zimbabwe: A Promising Practice to Improve Finger Millet (Eleusine coracana Gaertn.) Productivity and Soil Water Availability in the Short Term

by Vengai Mbanyele, Florence Mtambanengwe, Hatirarami Nezomba, Jairos Rurinda and Paul Mapfumo

Agriculture 2022, 12(5), 622; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050622 - 27 Apr 2022

Cited by 3 | Viewed by 2439

Abstract

Increasing within-season dry spells in Southern Africa in recent years have generated growing interest in conservation agriculture (CA) to secure crop yields, especially under rainfed systems. This study aimed to evaluate the effects of CA on finger millet’s (Eleusine coracana (L.) Gaertn) growth, yield and water use efficiency on nutrient-depleted sandy soils. Five treatments, namely (conventional tillage (control), conventional tillage + mulch (partial CA1), reduced tillage only (partial CA2), reduced tillage + mulching (partial CA3) and reduced tillage + mulching + intercropping (full CA)) were evaluated over two consecutive cropping seasons (2015/16 and 2016/17) on-farm in the village of Chidora in Hwedza District, southeast Zimbabwe. All mulched treatments had 15–32% more soil water content over the two growing seasons compared to the control. The higher soil water content under the mulched treatments significantly improved finger millet growth and development during both seasons as evidenced by the lower number of days to emergence (3 days less), greater shoot biomass, higher number of productive tillers and higher number of fingers produced. The full CA treatment achieved the best finger millet grain yield of 1.07 and 1.29 t ha⁻¹ during the 2015/16 and 2016/17 seasons, respectively. Full CA, partial CA3 and partial CA1 increased finger millet grain yield by 70%, 14% and 17% during the 2015/16 cropping season compared to the control. During the 2016/17 cropping season, a similar trend in finger millet grain yield was observed. Full CA was also among the most efficient methods in terms of water utilization (WUE), especially during the 2015/16 season. We concluded that CA, particularly when practiced in full, was more effective at offsetting the water limitations imposed by intra-seasonal dry spells on finger millet and significantly improved productivity. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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16 pages, 7059 KiB

Open AccessArticle

A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas

by Changjun Yin, Yunfei Liu, Dongwei Gui, Yi Liu and Wengai Lv

Agriculture 2022, 12(5), 612; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12050612 - 26 Apr 2022

Cited by 3 | Viewed by 2246

Abstract

Free surface evaporation is an important process in regional water cycles and energy balance. The accurate calculation of free surface evaporation is of great significance for evaluating and managing water resources. In order to improve the accuracy of estimating reservoir evaporation in data-scarce arid regions, the applicability of the energy balance method was assessed to calculate water surface evaporation based on the evaporator and reservoir evaporation experiment. A correlation analysis was used to assess the major meteorological factors that affect water surface temperature to obtain the critical parameters of the machine learning models. The water surface temperature was simulated using five machine learning algorithms, and the accuracy of results was evaluated using the root mean square error (RMSE), correlation coefficient (r), mean absolute error (MAE), and Nash efficiency coefficient (NSE) between observed value and calculated value. The results showed that the correlation coefficient between the evaporation capacity of the evaporator, calculated using the energy balance method and the observed evaporation capacity, was 0.946, and the RMSE was 0.279. The r value between the calculated value of the reservoir evaporation capacity and the observed value was 0.889, and the RMSE was 0.241. The meteorological factors related to the change in water surface temperature were air temperature, air pressure, relative humidity, net radiation and wind speed. The correlation coefficients were 0.554, −0.548, −0.315, −0.227, and 0.141, respectively. The RMSE and MAE values of five models were: RF (0.464 and 0.336), LSSVM (0.468 and 0.340), LSTM (1.567 and 1.186), GA-BP (0.709 and 0.558), and CNN (1.113 and 0.962). In summary, the energy balance method could accurately calculate the evaporation of evaporators and reservoirs in hyper-arid areas. As an important calculation parameter, the water surface temperature is most affected by air temperature, and the RF algorithm was superior to the other algorithms in predicting water surface temperature, and it could be used to predict the missing data. The energy balance model and random forest algorithm can be used to accurately calculate and predict the evaporation from reservoirs in hyper-arid areas, so as to make the rational allocation of reservoir water resources. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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15 pages, 3274 KiB

Open AccessArticle

Optimizing Irrigation Strategies to Improve Water Use Efficiency of Cotton in Northwest China Using RZWQM2

by Xiaoping Chen, Shaoyuan Feng, Zhiming Qi, Matthew W. Sima, Fanjiang Zeng, Lanhai Li, Haomiao Cheng and Hao Wu

Agriculture 2022, 12(3), 383; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12030383 - 09 Mar 2022

Cited by 10 | Viewed by 2670

Abstract

Irrigated cotton (Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content (θ), soil temperature (

T_{soil}^{°}

) and plant transpiration (T), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and

T_{soil}^{°}

, as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha⁻¹) and net income (US $3165 ha⁻¹), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha⁻¹ mm⁻¹) and net water production (0.94 $ m⁻³). These results provided farmers guidelines to adopt deficit irrigation strategies. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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10 pages, 10443 KiB

Open AccessArticle

Hydrogels Are Reinforced with Colombian Fique Nanofibers to Improve Techno-Functional Properties for Agricultural Purposes

by Marcelo A. Guancha-Chalapud, Liliana Serna-Cock and Diego F. Tirado

Agriculture 2022, 12(1), 117; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture12010117 - 14 Jan 2022

Cited by 6 | Viewed by 2238

Abstract

Colombia is the world’s largest producer of fique fibers (Furcraea bedinghausii), with a net production of 30,000 tons per year. This work proposes to revalue waste from the Colombian fique agroindustry. For this purpose, cellulose nanofibers were obtained from fique and used as reinforcement material to create acrylic superabsorbent hydrogels. Unreinforced acrylic hydrogels (AHR0) and acrylic hydrogels reinforced with fique nanofibers at 3% w/w (AHR3), 5% w/w (AHR5), and 10 % w/w (AHR10) were synthesized using the solution polymerization method. The best hydrogel formulation for agricultural purposes was chosen by comparing their swelling behavior, mechanical properties, and using scanning electron microscopy (SEM). By raising the nanofiber concentration to 3% (AHR3), the best-chosen formulation, the interaction between the nanofibers and the polymer matrix increased, which favored the network stability. However, beyond AHR3, there was a higher viscosity of the reactive system, which caused a reduction in the mobility of the polymer chains, thus disfavoring the swelling capacity. The reinforced hydrogel proposed in this study (AHR3) could represent a contribution to overcoming the problems of land dryness present in Colombia, an issue that will worsen in the coming years due to the climate emergency. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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16 pages, 4457 KiB

Open AccessArticle

Evapotranspiration Partition and Dual Crop Coefficients in Apple Orchard with Dwarf Stocks and Dense Planting in Arid Region, Aksu Oasis, Southern Xinjiang

by Hui Cao, Hongbo Wang, Yong Li, Abdoul Kader Mounkaila Hamani, Nan Zhang, Xingpeng Wang and Yang Gao

Agriculture 2021, 11(11), 1167; https://0-doi-org.brum.beds.ac.uk/10.3390/agriculture11111167 - 19 Nov 2021

Cited by 4 | Viewed by 2199

Abstract

Crop coefficients are critical to developing irrigation scheduling and improving agricultural water management in farmland ecosystems. Interest in dwarf cultivation with high density (DCHD) for apple production increases in Aksu oasis, southern Xinjiang. The lack of micro-irrigation scheduling limits apple yield and water productivity of the DCHD-cultivated orchard. A two-year experiment with the DCHD-cultivated apple (Malus × domestica ‘Royal Gala’) orchard was conducted to determine crop coefficients and evapotranspiration (ET_a) with the SIMDualKc model, and to investigate apple yield and water productivity (WP) in response to different irrigation scheduling. The five levels of irrigation rate were designed as W1 of 13.5 mm, W2 of 18.0 mm, W3 of 22.5 mm, W4 of 27.0 mm, and W5 of 31.5 mm. The mean value of basal crop coefficient (K_cb) at the initial-, mid-, and late-season was 1.00, 1.30, and 0.89, respectively. The Kc-local (ET_a/ET₀) range for apple orchard with DCHD was 1.11–1.20, 1.33–1.43, and 1.09–1.22 at the initial, middle, and late season, respectively. ET_a of apple orchard in this study ranged between 415.55–989.71 mm, and soil evaporation accounted for 13.85–29.97% of ET_a. Relationships between total irrigation amount and apple yield and WP were developed, and W3 was suggested as an optimum irrigation schedule with an average apple yield of 30,540.8 kg/ha and WP of 4.45 kg/m³ in 2019–2020. The results have implications in developing irrigation schedules and improving water management for apple production in arid regions. Full article

(This article belongs to the Special Issue Precision Water Management in Dryland Agriculture)

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Precision Water Management in Dryland Agriculture

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