Entrepreneurship plays an important role in developing the agricultural sector and increasing opportunities for farmers to promote sustainable livelihoods. The study aims to enhance discussion and ...gain an in-depth understanding of farm entrepreneurship in the context of sustainability in China. We conducted a case study of five farmers practicing organic farming through semi-structured face-to-face interviews. The analysis shows that organic farms enhance sustainability through many economic, social and environmental contributions. Additionally, emerging societal awareness of healthy foods and the increasing demand for organic products are among the most important opportunities contributing to the growth of organic farming. Despite this, farm entrepreneurship among organic farms faces many challenges, such as land use rights, lack of business networks and government subsidies. However, the government is the main player in promoting sustainability practices among entrepreneurs and society through agricultural policy development and promotion of organic products. We believe that this paper is the first attempt to study organic farm entrepreneurship in China from an entrepreneurs' viewpoint. The conclusions could have potential implications and guidelines for promoting organic agriculture policies in national and international contexts. The conclusions have significant implications and potential guidelines for promoting sustainability in national and international contexts.
•A 3D regional MODFLOW model is developed.•A surrogate-based calibration framework for MODFLOW models is implemented.•Efficiency, flexibility, and accuracy of the proposed method are ...illustrated.•Parameter importance is quantitatively evaluated by a sensitivity analysis.
Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol’ method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.
Groundwater depletion and seawater intrusion constitute major challenges along coastal aquifers in arid areas. This paper assesses the role of groundwater recharge dams constructed to replenish ...aquifers and fight seawater intrusion with reference to AlKhod dam, Oman, sited 7 km from the coast on a gravely unconfined aquifer. Water table rise in piezometers located downstream from the dam shows regular patterns correlating with magnitude of wadi flow, whereas upstream piezometers show irregular patterns. Controlled release of water captured by the dam optimizes water percolation and enhances artificial recharge which was estimated in the wet years 1997, 2003 and 2005 as 15, 22 and 27 Mm
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, respectively, using water table fluctuation method. Recharge contributed 40–60 % of the total annual abstraction. Groundwater salinity increased in the 1980s and 1990s and the saline/freshwater interface advanced inland, but has receded partially after 1997 (highest rainfall) and completely after 2005 indicated by reduction in electrical conductivity and thickening of freshwater lens. The recession is attributed to the dam’s induced recharge and reduction of pumping in 2004 following the commissioning of Barka desalination plant. Integrating artificial recharge with groundwater resources management is therefore an effective measure to replenish aquifers in arid areas and mitigate seawater intrusion along the coasts.
This paper introduces a kinodynamic motion planning algorithm for Unmanned Aircraft Systems (UAS), called MP-RRT
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. MP-RRT
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joins the potentialities of RRT
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with a strategy based on Model ...Predictive Control to efficiently solve motion planning problems under differential constraints. Similar to other RRT-based algorithms, MP-RRT
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explores the map constructing an asymptotically optimal graph. In each iteration the graph is extended with a new vertex in the reference state of the UAS. Then, a forward simulation is performed using a Model Predictive Control strategy to evaluate the motion between two adjacent vertices, and a trajectory in the state space is computed. As a result, the MP-RRT
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algorithm eventually generates a feasible trajectory for the UAS satisfying dynamic constraints. Simulation results obtained with a simulated drone controlled with the PX4 autopilot corroborate the validity of the MP-RRT
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approach.
The present study assesses groundwater resources of the densely populated area of the Khartoum State, Sudan by integrating conventional hydrochemistry and statistical analysis. Groundwater is ...exploited from two aquifers: Gezira and Nubian. The Gezira aquifer, which occupies the upper part, is separated by impermeable unit from the lower Nubian aquifer. Both aquifers are part of thick sedimentary accumulations formed under fluviolacustrine environment during Tertiary and Cretaceous, respectively. The groundwater flows in the two aquifers from the White and Blue Niles (both rivers bound the area from west and east, respectively) into the center of the study area suggesting recharge from the rivers. This river-induced recharge is demonstrated by the hydrochemical evolution of the groundwater along the flow direction. Groundwater evolves in the Nubian aquifer from Ca²⁺–Mg²⁺–HCO₃ ⁻ type in the vicinity of the Niles to Na⁺–K⁺–Cl⁻–SO₄ ²⁻ type in the central part of the area indicating precipitation of carbonates and dissolution of clay minerals and evaporites reported in the well logs. A third type of groundwater Na⁺–K⁺–HCO₃ ⁻ is formed in the mid zones between the Niles and the central part showing the ionic exchange and minerals dissolution/precipitation with the flow direction. In the Gezira aquifer, the water only changes from Ca²⁺–Mg²⁺–HCO₃ ⁻ type to Na⁺–K⁺–HCO₃ ⁻ type indicating a lesser degree of mineral dissolution. The factor analysis reveals three factors controlling the chemistry of groundwater in the study area: mineral dissolution and weathering, carbonate system, and anthropogenic effect. Factor 1 (mineral dissolution and weathering) includes high values of TDS, EC, Na⁺, K⁺, CI⁻, HCO₃ ⁻, and SO₄ ²⁻ in respective order; Factor 2 (carbonate system) includes Ca²⁺, Mg²⁺, CO₃ ²⁻, and pH; Factor 3 (anthropogenic effect) includes NO₃ ⁻ and F⁻. It has been demonstrated that the integration of conventional hydrochemical analysis with factor analysis represents a powerful mean to understand the factors controlling groundwater chemistry.
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management, hydrological processes, and agricultural production. The FAO-56 Penman-Monteith ...(FAO-56PM) approach is recommended as the standard model for ETo estimation; nevertheless, the absence of comprehensive meteorological variables at many global locations frequently restricts its implementation. This study compares shallow learning (SL) and deep learning (DL) models for estimating daily ETo against the FAO-56PM approach based on various statistic metrics and graphic tool over a coastal Red Sea region, Sudan. A novel approach of the SL model, the Catboost Regressor (CBR) and three DL models: 1D-Convolutional Neural Networks (1D-CNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) were adopted and coupled with a semi-supervised pseudo-labeling (PL) technique. Six scenarios were developed regarding different input combinations of meteorological variables such as air temperature (Tmin, Tmax, and Tmean), wind speed (U2), relative humidity (RH), sunshine hours duration (SSH), net radiation (Rn), and saturation vapor pressure deficit (es-ea). The results showed that the PL technique reduced the systematic error of SL and DL models during training for all the scenarios. The input combination of Tmin, Tmax, Tmean, and RH reflected higher performance than other combinations for all employed models. The CBR-PL model demonstrated good generalization abilities to predict daily ETo and was the overall superior model in the testing phase according to prediction accuracy, stability analysis, and less computation cost compared to DL models. Thus, the relatively simple CBR-PL model is highly recommended as a promising tool for predicting daily ETo in coastal regions worldwide which have limited climate data.
•A novel approach using hybrid models of SL and DL with the pseudo-labeled (PL) technique.•PL improved the models' performance in various scenarios.•Relative humidity is an important meteorological parameter for predicting ETo.•CBR-PL model outperformed the LSTM-PL, GRU-PL, and 1D-CNN-PL models.•CBR-PL showed high accuracy, lower complexity, and faster computation than DL models.
The agricultural industry in Qatar is highly dependent on using soil enhancing materials due to challenging soil and climatic conditions. Hence, this work investigated the potential of industrial ...biosludge from the wastewater treatment plant (WWTP) of a Gas-to-Liquids (GTL) plant to enhance an arid soil compared to fertilizer and compost. A fodder crop, buffel grass (Cenchrus ciliaris), was grown in semi-controlled pots containing a typical Qatari agricultural soil and admixtures over a 12-month period. The treatments included soil plus five biosludge percentage contents: 0.75, 1.5, 3, 6 and 12%. These were compared with soil only, soil plus 20-20-20 NPK fertilizer and soil plus 3% compost controls. Analyses of soil physical and chemical properties, the resulting leachate, and plant growth characteristics were conducted at set periods. The results indicate that up to 3% biosludge content led to better plant growth compared to the controls, with the optimum at 1.5% biosludge content for all growth characteristics studied. Biosludge addition to soil increased the volume of different pore types, especially micropores, which enhanced water retention and influenced plant growth. Regression modelling identified leachate Si and Fe concentrations, and biomass K content as the most influential variables for fresh biomass weight, plant height and the number of tillers, respectively. Biosludge addition to the soil around the optimum level did not cause detrimental changes to the resulting leachate and plant biomass. The findings of this work could lead to minimization of biosludge landfilling and allow for savings in fertilizers and irrigation water in arid regions.
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•Biosludge from wastewater of a gas-to-liquids plant improved arid soil behavior.•Up to 3% biosludge content caused better grass growth than fertilizer and compost.•The optimum level for all growth characteristics studied was 1.5% biosludge content.•Biosludge addition increased micropores volume and enhanced soil water retention.•The findings support waste utilization and fertilizer and irrigation water savings.
This paper proposes an approach to estimate groundwater recharge using an optimization‐based water‐table fluctuation method combined with a groundwater balance model in an arid hardrock‐alluvium ...region, located at the Oman–United Arab Emirates border. We introduce an “effective hardrock thickness” term to identify the percentage of the considered hardrock thickness in which effective groundwater flow takes place. The proposed method is based upon a Thiessen polygon zoning approach. The method includes subpolygons to represent specific geologic units and to enhance the confidence of the estimated groundwater recharge. Two linear and 1 nonlinear submodels were developed to evaluate the model components for the calibration (October 1996 to September 2008) and validation (October 2008 to September 2013) periods. Long‐term annual groundwater recharge from rainfall and return flow over the model domain are estimated as 24.62 and 5.71 Mm3, respectively, while the effective groundwater flow circulation is found to occur in the upper 7% of the known hardrock thickness (42 m), confirming conclusions of previous field studies. Considering a total difference in groundwater levels between eastern and western points of the study area of the order of 220 m and a 12‐year monthly calibration period, a weighted root mean squared error in predicted groundwater elevation of 2.75 m is considered quite reasonable for the study area characterized by remarkable geological and hydrogeological diversity. The proposed approach provides an efficient and robust method to estimate groundwater recharge in regions with a complex geological setting in which interaction between fractured and porous media cannot be easily assessed.
This article introduces a new two-dimensional direction of arrival (DOA) elevation and azimuth angles estimation technique for global positioning system (GPS) jamming signals in challenging ...environments based on the fast orthogonal search (FOS) method. FOS-DOA estimation is accommodated to process array structure optimized for interference rejection. Performance of FOS-DOA is compared to the predominant multiple signal classification (MUSIC) DOA estimation method. Results showed significant improvement in jamming detection of the multiple sources of interference with slight variations in their amplitude at jamming to signal ratio (JSR) 15 and 45 dB. The improvement introduced by the proposed DOA estimation technique is mainly in the accuracy of detecting the number of jammers and their DOA.
GPS jamming is a considerable threat to applications that rely on GPS position, velocity, and time. Jamming detection is the first step in the mitigation process. The direction of arrival (DOA) ...estimation of jamming signals is affected by resolution. In the presence of multiple jamming sources whose spatial separation is very narrow, an incorrect number of jammers can be detected. Consequently, mitigation will be affected. The ultimate objective of this research is to enhance GPS receivers' anti-jamming abilities. This research proposes an enhancement to the anti-jamming detection ability of GPS receivers that are equipped with a uniform linear array (ULA) and uniform circular array (UCA). The proposed array processing method utilizes fast orthogonal search (FOS) to target the accurate detection of the DOA of both single and multiple in-band CW jammers. Its performance is compared to the classical method and MUSIC. GPS signals obtained from a Spirent GSS6700 simulator and CW jamming signals were used. The proposed method produces a threefold advantage, higher accuracy DOA estimates, amplitudes, and a correct number of jammers. Therefore, the anti-jamming process can be significantly improved by limiting the erroneous spatial attenuation of GPS signals arriving from an angle close to the jammer.
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