Journal articles on the topic 'Irrigation water Measurement Mathematical models'
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1
Kumar, R., M. K. Jat, and V. Shankar. "Methods to estimate irrigated reference crop evapotranspiration – a review." Water Science and Technology 66, no. 3 (August 1, 2012): 525–35. http://dx.doi.org/10.2166/wst.2012.191.
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Efficient water management of crops requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Irrigation is applied to replenish depleted moisture for optimum plant growth. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. Mathematical models are useful tools to estimate the evapotranspiration and water requirement of crops, which is essential information required to design or choose best water management practices. In this paper the most commonly used models/approaches, which are suitable for the estimation of daily water requirement for agricultural crops grown in different agro-climatic regions, are reviewed. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions.
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Su, Lijun, Wanghai Tao, Yan Sun, Yuyang Shan, and Quanjiu Wang. "Mathematical Models of Leaf Area Index and Yield for Grapevines Grown in the Turpan Area, Xinjiang, China." Agronomy 12, no. 5 (April 20, 2022): 988. http://dx.doi.org/10.3390/agronomy12050988.
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The Leaf Area Index (LAI) strongly influences crop biomass production and yields. The variation characteristic of LAI and the development of crop growth models can provide a theoretical basis for predicting crops’ water consumption, fruit quality and yields. This paper analyzes the relationship between measurements of aboveground grape biomass and trends in LAI and dry biomass production in grapes grown in the Turpan area. The LAI changes in grapes were estimated using the modified logistic model, the modified Gaussian model, the log-normal model, the cubic polynomial model, and the Gaussian model. Universal models of LAI were established in which the applied irrigation quota was applied to calculate the maximum LAI. The relationship between the irrigation quota and biomass production, yields, and the harvest index was investigated. The developed models could accurately predict the LAI of grapevines grown in an extremely arid area. However, the Gaussian and cubic polynomial models produced less accurate results than the other models tested. The Michaelis–Menten model analyzed the relationship between biomass and LAI, providing a numerical method for predicting dynamic changes in grapevine LAI. Moreover, the crop biomass increased linearly with the irrigation quota for quotas between 6375 and 13,200 m3/hm. This made it possible to describe the grape yield and harvest index with a quadratic polynomial function, which increases during the early stages of the growing season and then decreases. The analyses of the relationship between yield and harvest index provide important theoretical insights that can be used to improve water use efficiency in grape cultivation and to identify optimal irrigation quotas.
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Smith, Jaclyn E., Jennifer L. Wolny, Robert L. Hill, Matthew D. Stocker, and Yakov Pachepsky. "Examining the Relationship between Phytoplankton Community Structure and Water Quality Measurements in Agricultural Waters: A Machine Learning Application." Environments 9, no. 11 (November 12, 2022): 142. http://dx.doi.org/10.3390/environments9110142.
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Phytoplankton community composition has been utilized for water quality assessments of various freshwater sources, but studies are lacking on agricultural irrigation ponds. This work evaluated the performance of the random forest algorithm in estimating phytoplankton community structure from in situ water quality measurements at two agricultural ponds. Sampling was performed between 2017 and 2019 and measurements of three phytoplankton groups (green algae, diatoms, and cyanobacteria) and three sets of water quality parameters (physicochemical, organic constituents, and nutrients) were obtained to train and test mathematical models. Models predicting green algae populations had superior performance to the diatom and cyanobacteria models. Spatial models revealed that water in the ponds’ interior sections had lower root mean square errors (RMSEs) compared to nearshore waters. Furthermore, model performance did not change when input datasets were compounded. Models based on physicochemical parameters, which can be obtained in real time, outperformed models based on organic constituent and nutrient parameters. However, the use of nutrient parameters improved model performance when examining cyanobacteria data at the ordinal level. Overall, the random forest algorithm was useful for predicting major phytoplankton taxonomic groups in agricultural irrigation ponds, and this may help resource managers mitigate the use of cyanobacteria bloom-laden waters in agricultural applications.
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Domínguez-Niño, Jesús María, Gerard Arbat, Iael Raij-Hoffman, Isaya Kisekka, Joan Girona, and Jaume Casadesús. "Parameterization of Soil Hydraulic Parameters for HYDRUS-3D Simulation of Soil Water Dynamics in a Drip-Irrigated Orchard." Water 12, no. 7 (June 28, 2020): 1858. http://dx.doi.org/10.3390/w12071858.
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Although surface drip irrigation allows an efficient use of water in agriculture, the heterogeneous distribution of soil water complicates its optimal usage. Mathematical models can be used to simulate the dynamics of water in the soil below a dripper and promote: a better understanding, and optimization, of the design of drip irrigation systems, their improved management and their monitoring with soil moisture sensors. The aim of this paper was to find the most appropriate configuration of HYDRUS-3D for simulating the soil water dynamics in a drip-irrigated orchard. Special emphasis was placed on the source of the soil hydraulic parameters. Simulations parameterized using the Rosetta approach were therefore compared with others parameterized using that of HYPROP + WP4C. The simulations were validated on a seasonal scale, against measurements made using a neutron probe, and on the time course of several days, against tensiometers. The results showed that the best agreement with soil moisture measurements was achieved with simulations parameterized from HYPROP + WP4C. It further improved when the shape parameter n was empirically calibrated from a subset of neutron probe measurements. The fit of the simulations with measurements was best at positions near the dripper and worsened at positions outside its wetting pattern and at depths of 80 cm or more.
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RIGHETTO, L., R. U. ZAMAN, Z. H. MAHMUD, E. BERTUZZO, L. MARI, R. CASAGRANDI, M. GATTO, S. ISLAM, and A. RINALDO. "Detection ofVibrio choleraeO1 and O139 in environmental waters of rural Bangladesh: a flow-cytometry-based field trial." Epidemiology and Infection 143, no. 11 (December 11, 2014): 2330–42. http://dx.doi.org/10.1017/s0950268814003252.
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SUMMARYPresence ofVibrio choleraeserogroups O1 and O139 in the waters of the rural area of Matlab, Bangladesh, was investigated with quantitative measurements performed with a portable flow cytometer. The relevance of this work relates to the testing of a field-adapted measurement protocol that might prove useful for cholera epidemic surveillance and for validation of mathematical models. Water samples were collected from different water bodies that constitute the hydrological system of the region, a well-known endemic area for cholera. Water was retrieved from ponds, river waters, and irrigation canals during an inter-epidemic time period. Each sample was filtered and analysed with a flow cytometer for a fast determination ofV. choleraecells contained in those environments. More specifically, samples were treated with O1- and O139-specific antibodies, which allowed precise flow-cytometry-based concentration measurements. Both serogroups were present in the environmental waters with a consistent dominance ofV. choleraeO1. These results extend earlier studies whereV. choleraeO1 and O139 were mostly detected during times of cholera epidemics using standard culturing techniques. Furthermore, our results confirm that an important fraction of the ponds’ host populations ofV. choleraeare able to self-sustain even when cholera cases are scarce. Those contaminated ponds may constitute a natural reservoir for cholera endemicity in the Matlab region. Correlations ofV. choleraeconcentrations with environmental factors and the spatial distribution ofV. choleraepopulations are also discussed.
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Hilal, Yousif Yakoub, Montaser Khairie Khessro, Jos van Dam, and Karrar Mahdi. "Automatic Water Control System and Environment Sensors in a Greenhouse." Water 14, no. 7 (April 6, 2022): 1166. http://dx.doi.org/10.3390/w14071166.
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Iraqi greenhouses require an active microcontroller system to ensure a suitable microclimate for crop production. At the same time, reliable and timely Water Consumption Rate (WCR) forecasts provide an essential means to reduce the amount of water loss and maintain the environmental conditions inside the greenhouses. The Arduino micro-controller system is tested to determine its effectiveness in controlling the WCR, Temperature (T), Relative Humidity (RH), and Irrigation Time (IT) levels and improving plant growth rates. The Arduino micro-controller system measurements are compared with the traditional methods to determine the quality of the work of the new control system. The development of mathematical models relies on T, RH, and IT indicators. Based on the results, the new system proves to reliably identify the amount of WCR, IT, T, and RH necessary for plant growth. A t-test for the values from the Arduino microcontroller system and traditional devices for both conditions show no significant difference. This means that there is solid evidence that the WCR, IT, T, and RH levels for these two groups are no different. In addition, the linear, two-factor interaction (2FI), and quadratic models display acceptable performance very well since multiple coefficients of determination (R2) reached 0.962, 0.969, and 0.977% with IT, T, and RH as the predictor variables. This implies that 96.9% of the variability in the WCR is explained by the model. Therefore, it is possible to predict weekly WCR 14 weeks in advance with reasonable accuracy.
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Abbass, Ahmad Dnan, and Hayder A. K. AL-Thamiry. "Field Evaluating of Wetting Pattern from Surface Drip Irrigation System for Sand and Sandy Loam Soils." Association of Arab Universities Journal of Engineering Sciences 26, no. 2 (June 30, 2019): 19–27. http://dx.doi.org/10.33261/jaaru.2019.26.2.004.
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Water distribution through soils from trickle source is very important issue since it affects irrigation efficiency, wetted surface area and wetted soil profile. Many attempts to determine wetting pattern under drip irrigation using mathematical and numerical models were carried out. The verification of the validity of which model will be suitable for Iraqi soils need a detailed study. In this paper, the field work measurements of wetted pattern in two Iraqi soils (sand and sandy loam) were conducted to investigate the validity of the application of wetting pattern formulas predicted by Dawood (2016), Amin and Ekhmaj, (2006) and Schwartzman and Zur (1986). The work was divided into two parts: the first one was the laboratory work of soil texture, field capacity, permanent wilting point, and soil porosity. The second one includes field operations through landing, installation of trickle irrigation system, installation of equipment’s and sensors, adjustment of emitter discharge by the valve on the supply pipe. In each run, initial water content was measured and the system was operated for three continuous hours with three different discharges, discharges were selected as 1, 3 and 6 l/hr. the wetted diameter and depth were recorded hourly during each run test .The field measurements of wetted area were compared with that predicted by the previous studies. The obtained result indicate that the value of the wetted diameter and depth increase with increasing of water contents, the wetted diameter are inversely proportional was saturated hydraulic conductivity, and the wetted depth was directly proportional to the saturated hydraulic conductivity. Amin and Ekhmaj 2006 formula was suitable for wetted depth in sandy loam soil with average error 13.40% and Schwartzman and Zur, 1986 formulas gave a good prediction for wetted diameters with average error 12.79% for same soil. Finally Dawood (2016) formulas were more suitable than others for sand soil with average error for wetted diameter and depth 11.49%, 16.79% respectively.
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Thomas, R. Quinn, Evan B. Brooks, Annika L. Jersild, Eric J. Ward, Randolph H. Wynne, Timothy J. Albaugh, Heather Dinon-Aldridge, et al. "Leveraging 35 years of <i>Pinus taeda</i> research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments." Biogeosciences 14, no. 14 (July 26, 2017): 3525–47. http://dx.doi.org/10.5194/bg-14-3525-2017.
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Abstract. Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
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Aydarova, Aysulu. "MATHEMATIC MODELS OF WATER RESOURCES MANAGEMENT FOR IRRIGATION SYSTEMS." TECHNICAL SCIENCES 5, no. 3 (May 30, 2020): 64–70. http://dx.doi.org/10.26739/2181-9696-2020-5-10.
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This article explores the models of water resources management in irrigation systems. The article provides a classification of mathematical models for the optimal distribution of water resources. The work also substantiates the need to develop a new model of water resources management for distributed irrigation systems.
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Shnaidman, V. M., and R. Sh Zhemukhov. "Environmental Aspects in Mathematical Modeling of Irrigation Systems Planning." Water Science and Technology 26, no. 5-6 (September 1, 1992): 1439–47. http://dx.doi.org/10.2166/wst.1992.0587.
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This paper deals with applying computer-oriented technology while selecting water and land resources management strategies lor irrigation systems with special reference to environmental aspects. The technology is based on a system of coordinated mathematical models. The system includes a simulation model of irrigation system functioning, a model for irrigation water demand computation, a set of simplified mathematical models of the anthropogenic impact, viz. soil salinization, non-point pollutions from agricultural plots, rising level of subsurface water and its mineralization. The system also takes into account equations for crop yields as functions of both water consumption and fertilization. This makes it possible to analyze various strategies of irrigation system management with the help of a multicriterial procedure. The models are described in sufficient detail and a computation example is given.
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Abdulaev, A., and N. A. Omorova. "MATHEMATICAL MODELS OF DISCRETE IRRIGATION TECHNOLOGIES FOR AGRICULTURAL CROPS IN FURROWS." Herald of KSUCTA n a N Isanov, no. 2-2021 (June 24, 2021): 258–62. http://dx.doi.org/10.35803/1694-5298.2021.2.258-262.
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The article discusses mathematical modeling of discrete technology of irrigation of crops by furrows, based on joint consideration of the system of Saint-Venan equations and equations of moisture and heat transfer in soils. The boundary conditions are described in detail in accordance with the technologies of irrigation by furrows at discrete water supply.
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Babazadeh, Hossein, Mahdi Sarai Tabrizi, and Hossein Hassanpour Darvishi. "Adopting adequate leaching requirement for practical response models of basil to salinity." International Agrophysics 30, no. 3 (July 1, 2016): 275–83. http://dx.doi.org/10.1515/intag-2016-0002.
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Abstract Several mathematical models are being used for assessing plant response to salinity of the root zone. Objectives of this study included quantifying the yield salinity threshold value of basil plants to irrigation water salinity and investigating the possibilities of using irrigation water salinity instead of saturated extract salinity in the available mathematical models for estimating yield. To achieve the above objectives, an extensive greenhouse experiment was conducted with 13 irrigation water salinity levels, namely 1.175 dS m−1 (control treatment) and 1.8 to 10 dS m−1. The result indicated that, among these models, the modified discount model (one of the most famous root water uptake model which is based on statistics) produced more accurate results in simulating the basil yield reduction function using irrigation water salinities. Overall the statistical model of Steppuhn et al. on the modified discount model and the math-empirical model of van Genuchten and Hoffman provided the best results. In general, all of the statistical models produced very similar results and their results were better than math-empirical models. It was also concluded that if enough leaching was present, there was no significant difference between the soil salinity saturated extract models and the models using irrigation water salinity.
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A. A., Yuldashov, and Karimov G. X. "Models of Distribution of Flow Parameters in Intensive Garden Irrigation, System Pipes." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 838–44. http://dx.doi.org/10.22214/ijraset.2022.40692.
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Annotation: The mathematical description of the movement of water in the systems of irrigation pipelines, based on the equation of continuity of the medium, the system of Navy-Stokes equations. The resulting mathematical package describes a system with distributed parameters and is performed based on the condition of dynamic balance at the point of flow, taking into account the dependence on the nature of the flow and the physical properties of the environment. Calculation is executed with use of functions Besseliya. Methodology for calculating the hydrodynamic component of water movement in irrigation water supply systems. Pipelines are universal in nature and can be used in the calculation, construction and assessment of the stability of water supply hydraulic systems; the technique can be used to describe the object of operation in the construction of control systems for the hydraulic parameters of the water supply system. Keywords: pipeline, irrigation systems, non-uniformity, liquid, water, strength, function, three-dimensional, water supply, hydrodynamics, hydrostatics, quasi-one-dimensional, unsteady, flow, potential, surface, coordinate system, stresses, projection, velocity, cylindrical coordinates, unsteady motion , asymmetric, viscous, compressible fluid, plastic pipe
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N.N., Adamushko, and Zverkov M.S. "The mathematical presupposition for the issue of the soil moisture movement under drip irrigation." Ekologiya i stroitelstvo 4 (2016): 30–35. http://dx.doi.org/10.35688/2413-8452-2016-04-005.
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The article discusses a mathematical models to describe the process of movement of moisture with drip irrigation. In the Federal target program «Development of reclamation of agricultural lands of Russia for 2014−2020» the task is saving water. One such water-saving technologies is drip irrigation. This method of irrigation is widespread in different countries of the world. It is noted that the accuracy and effectiveness of the regulation of the water regime is defined as frequent and less watering. Indicates that the application in practice of traditional methods of calculation of drip irrigation causes farmers a lot of questions. In the absence of engineers, reclamation specialists on the production of farmers can not apply developed in a large number of recent recommendations and are forced to set their own water supply mode, because of this reduced efficiency in the use of drip irrigation systems. It is shown that observation of the movement of moisture using the balance method with drip irrigation is difficult. It is noted that numerous studies have shown the high accuracy and efficiency the calculation of irrigation regimes using models of moisture transport, among which the most widespread are based on the basis of an expression L. Richards.
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Kheybari, Siamak, and Reza Salehpour. "The optimization of the paddy field irrigation scheduling using mathematical programming." Water Supply 15, no. 5 (May 19, 2015): 1048–60. http://dx.doi.org/10.2166/ws.2015.062.
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In planting rice, a significant amount of irrigation water is required to prepare the farmlands and do transplanting and this is directly related to the number of machines and workers available; that is, the more the length of plowing and transplanting process due to the lack of required machinery and labor, the more the water volume consumed. Therefore, in such conditions, it is important to have an appropriate planning for the optimized allocation of machinery and labor for the agricultural lands. Determining the optimal times of opening and closing valves based on the factors directly influencing the volume of the water in paddy fields is also of great importance. To meet the above conditions and by using linear and non-linear programming, two different models are developed in this article, with the purpose of reducing the time period of plowing and transplanting operations and also lowering the water consumption, respectively. Comparing the outputs of these two models with the real irrigation situation demonstrates the efficiency of the proposed models.
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Terleev, Vitaly, Wilfried Mirschel, Aleksandr Nikonorov, Roman Ginevsky, Viktor Lazarev, Alex Topaj, Kirill Moiseev, et al. "Five models of hysteretic water-retention capacity and their comparison for sandy soil." MATEC Web of Conferences 193 (2018): 02036. http://dx.doi.org/10.1051/matecconf/201819302036.
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A description of five mathematical models of the water-retention capacity of soil is given, taking into account the hysteresis phenomena. A computational experiment was carried out with these models using data on sandy soil. The experiment consisted of: (i) tuning of the models (parameter identification) by the method of dot-approximation of experimental data on the main drying and wetting branches of the hysteresis loop using an optimizing algorithm; (ii) the predictive calculation of the scanning branches of the hysteresis loop; (iii) a comparison of the errors in tuning results and the predictive calculation using the Williams-Kloot criteria. The commensurate and sufficiently low errors in the adjustment of the models have been achieved. The differences in the calculation of the scanning hysteresis branches are revealed. The practical significance of the mathematical models presented is to ensure the calculation of precision irrigation rates. The application of such rates in irrigation farming will help to prevent excess moisture from flowing beyond the root layer of the soil under the influence of gravity and, thus, to minimize the losses (unproductive consumption) of irrigation water, fertilizers, meliorants and plant protection products, and also reduce the risk of groundwater contamination with agrochemicals and eutrophication of water bodies.
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Yousif, Jabar H., and Khaled Abdalgader. "Experimental and Mathematical Models for Real-Time Monitoring and Auto Watering Using IoT Architecture." Computers 11, no. 1 (January 3, 2022): 7. http://dx.doi.org/10.3390/computers11010007.
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Manufacturing industries based on Internet of Things (IoT) technologies play an important role in the economic development of intelligent agriculture and watering. Water availability has become a global problem that afflicts many countries, especially in remote and desert areas. An efficient irrigation system is needed for optimizing the amount of water consumption, agriculture monitoring, and reducing energy costs. This paper proposes a real-time monitoring and auto-watering system based on predicting mathematical models that efficiently control the water rate needed. It gives the plant the optimal amount of required water level, which helps to save water. It also ensures interoperability among heterogeneous sensing data streams to support large-scale agricultural analytics. The mathematical model is embedded in the Arduino Integrated Development Environment (IDE) for sensing the soil moisture level and checking whether it is less than the pre-defined threshold value, then plant watering is performed automatically. The proposed system enhances the watering system’s efficiency by reducing the water consumption by more than 70% and increasing production due to irrigation optimization. It also reduces the water and energy consumption amount and decreases the maintenance costs.
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А. V. Kabulov et al.,, А. V. Kabulov et al ,. "Mathematical Models of the Optimal Distribution of Water in the Channels of Irrigation Systems." International Journal of Mechanical and Production Engineering Research and Development 10, no. 3 (2020): 14193–202. http://dx.doi.org/10.24247/ijmperdjun20201355.
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Zekri, Slim, Hemesiri Kotagama, and Houcine Boughanmi. "Temporary Water Markets in Oman." Journal of Agricultural and Marine Sciences [JAMS] 11 (January 1, 2006): 77. http://dx.doi.org/10.24200/jams.vol11iss0pp77-84.
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Market vis-à-vis command and control approaches have been widely adopted in natural resource and environmental management since the 1980s. Adoption of markets in managing irrigation water resources is also emerging. It has been argued that markets are ineffective in managing the demand for irrigation water due to very low price elasticity. Most studies have been based on mathematical models simulating water markets and not on observed prices and quantities in real water markets since such data are rarely available. In Oman, perhaps in response to the extreme scarcity of water, elaborate water demand management institutions emulating markets have evolved and have been used for centuries. Water entitlements are leased based on prices through a community auction. The traded quantities of water and related prices have been recorded. This study uses this unique data set to estimate the elasticity of irrigation water. A log function on quantity and price of irrigation water is used with dummy variables on time and type of irrigation system. The price elasticity varies from -0.10 to -0.28, depending on the specifications of the econometric model. These estimates are higher than most estimates reported in past studies, indicating the efficacy of the indigenous market-based irrigation water management institution adopted in Oman.
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Berbel, J., D. Viaggi, and B. Manos. "Estimating demand for irrigation water in European Mediterranean countries through MCDM models." Water Policy 11, no. 3 (June 1, 2009): 348–61. http://dx.doi.org/10.2166/wp.2009.043.
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This paper reports results from the European project WADI which evaluates the sustainability of the European irrigation sector under different policy scenarios. Results presented are based on the generation of farm level water demand curves through multicriteria mathematical programming models. The results are compared across regions and matched against a review of water pricing policies that were in place in various European Union member states and accession countries prior to the entering into force of the Water Framework Directive (WFD). The results emphasise the variability of behaviour of irrigated systems and the need for a more clear understanding of policy objectives before implementing any policy instrument. Once the objectives are clarified, economic models can contribute to understanding the appropriateness of different management strategies and to the effectiveness of different policy instruments.
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Wang, Ning Na, and Qin Lin Zhou. "Mathematical Models for Predicting and Managing Water Resources — The Case of China in 2025." Applied Mechanics and Materials 448-453 (October 2013): 995–1001. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.995.
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An effective management of water supply is critically significant to a countrys water utilities, and accurate prediction of water supply and demand is of key importance for water supply management. The objectives of this paper are to use Grey System Model (GSM) and Linear Regression Model to forecast the water demand and water supply respectively in China 2025, and then propose a new Optimal Allocation Model (OAM) to generate solution so that analysts and decision makers can gain insight and understanding. The two predictive models take into account four major factors including domestic development, agriculture, industries and eco-environment, calculating a deficit between water demand and water supply in China 2025. Then the OAM, which considers desalinization, irrigation saving and urban recycling, provides a feasible solution to fill the gap and an effectual management of water supply.
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Zahrati, Uli, Azmeri Azmeri, and Syamsidik Syamsidik. "Pemodelan Matematis Pola Tanam dan Jadwal Tanam Daerah Irigasi Baro untuk Memaksimalkan Keuntungan." Jurnal Arsip Rekayasa Sipil dan Perencanaan 2, no. 3 (September 20, 2019): 235–41. http://dx.doi.org/10.24815/jarsp.v2i3.13460.
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Daerah Irigasi (D.I.) Baro has a total area of 11.950 ha which consists of Baro Kanan area of 8,920 Ha and Baro Kiri area of 3.030 Ha. Maximum cropping intensity indeks of D.I. Baro ranged between 183%-213%. This shows that D.I. Baro is unable to meet the water needs for his extensive irrigation services. One of the factors that influence the planning and regulation of irrigation water is cropping pattern. The aims of this research is to get the best cropping pattern, so that the distribution of irrigation water discharge available in D.I. Baro can be done optimally, knowing the need of irrigation water in D.I. Baro, knowing the maximum plantable area that irrigation can irrigate, and knowing the maximum profit that can be achieved by optimization. Compilation of mathematical models to get the maximum benefit that can be achieved by optimizing land area. The data collected in this study is secondary data. The method used is an optimization method using a linear program.
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Basterrechea, Daniel A., Javier Rocher, Mar Parra, Lorena Parra, Jose F. Marin, Pedro V. Mauri, and Jaime Lloret. "Design and Calibration of Moisture Sensor Based on Electromagnetic Field Measurement for Irrigation Monitoring." Chemosensors 9, no. 9 (September 6, 2021): 251. http://dx.doi.org/10.3390/chemosensors9090251.
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Soil moisture control is crucial to assess irrigation efficiency in green areas and agriculture. In this paper, we propose the design and calibration of a sensor based on inductive coils and electromagnetic fields. The proposed prototypes should meet a series of requirements such as low power consumption, low relative error, and a high voltage difference between the minimum and maximum moisture. We tested different prototypes based on two copper coils divided into two different sets (P1–P15 and NP1–NP4). The prototypes have different characteristics: variations in the number and distribution of spires, existence or absence of casing, and copper wires with a diameter of 0.4 or 0.6 mm. In the first set of experiments carried out in commercial soil, the results showed that the best prototypes were P5, P8, and P9. These prototypes were used in different types of soils, and P8 was selected for the subsequent tests. We carried the second set of experiments using soil from an agricultural field. Based on the data gathered, mathematical models for the calibration of prototypes were obtained and verified. In some cases, two equations were used for different moisture intervals in a single prototype. According to the verification results, NP2 is the best prototype for monitoring the moisture in agricultural lands. It presented a difference in induced voltage of 1.8 V, at 500 kHz, between wet and dry soil with a maximum voltage of 5.12 V. The verification of the calibration determined that the calibration using two mathematical models offers better results, with an average absolute error of 2.1% of moisture.
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Bai, Chen, Lixiao Yao, Cheng Wang, Yongxuan Zhao, and Weien Peng. "Simulation of Water–Energy Nexus of the Spatial Patterns of Crops and Irrigation Technologies in the Cascade Pump Station Irrigation District." Water 14, no. 7 (March 30, 2022): 1090. http://dx.doi.org/10.3390/w14071090.
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Cascade pump station irrigation districts (CPSIDs) consume vast amounts of irrigation water and energy. The aim of this study was to adjust the spatial patterns of crops and irrigation technologies in the CPSID to reduce the consumption of water and energy under the condition of conserving crop irrigation water. The irrigation district (ID) is divided into several sub-districts according to the topography elevation difference and the distribution of cascade pump stations (CPSs). The mathematical models of the irrigation water and energy consumption in each sub-district were established based on the relationship between the spatial patterns of crops and irrigation technologies in each sub-district. According to the present situation of the Jingdian Phase I Irrigation District in the arid region of northwest China, three modes of adjusting the crop planting structure and drip irrigation area were proposed. Based on the combination of these modes, three schemes of the spatial patterns of crops and irrigation technologies were generated. The annual energy consumption and irrigation water consumption of each sub-district in the ID of these three schemes were obtained through simulation. Compared with the present spatial patterns of crops and irrigation technologies in the Jingdian Phase I Irrigation District, Scheme 3 has the best water-saving and energy-saving effects, with an annual water saving and energy saving of 1753 × 104 m3 and 2898 × 104 kWh, and the water-saving rate and energy-saving rate were 12.34% and 15.74%, respectively. This paper also shows that the synchronous adjustment of crops and irrigation technologies among the sub-districts of ID can achieve significant water-saving and energy-saving effects.
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Liu, Zhigang, and Qinchao Xu. "An Automatic Irrigation Control System for Soilless Culture of Lettuce." Water 10, no. 11 (November 20, 2018): 1692. http://dx.doi.org/10.3390/w10111692.
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To achieve precise measurement of moisture content in the substrate and intelligent water-saving irrigation, a simple and low cost automatic irrigation control system based on ZigBee wireless network has been developed. A software with irrigation strategy was proposed based on the models of substrate wetting pattern, lettuce root zone and the evapotranspiration. The system could detect substrate moisture in real-time and irrigate automatically according to the threshold of substrate and the irrigation strategy. The average fresh weight per plant under intelligent irrigation are 16.60% and 11.37% higher than manual control irrigation at least in different growth stages in spring and summer, the average drainage rate of intelligent irrigation is 16.08% and 17.06% smaller than manual control irrigation in spring and summer, and the irrigation water use efficiency of intelligent irrigation is 68.03% and 98.61% higher than manual control irrigation in spring and summer. The results show that the system is a promising tool for scientific and rational irrigation decision.
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Ravazzani, Giovanni, Chiara Corbari, Alessandro Ceppi, Mouna Feki, Marco Mancini, Fabrizio Ferrari, Roberta Gianfreda, et al. "From (cyber)space to ground: new technologies for smart farming." Hydrology Research 48, no. 3 (December 5, 2016): 656–72. http://dx.doi.org/10.2166/nh.2016.112.
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Increased water demand and climate change impacts have recently enhanced the need to improve water resources management, even in those areas which traditionally have an abundant supply of water, such as the Po Valley in northern Italy. The highest consumption of water is devoted to irrigation for agricultural production, and so it is in this area that efforts have to be focused to study possible interventions. Meeting and optimizing the consumption of water for irrigation also means making more resources available for drinking water and industrial use, and maintaining an optimal state of the environment. In this study we show the effectiveness of the combined use of numerical weather predictions and hydrological modelling to forecast soil moisture and crop water requirement in order to optimize irrigation scheduling. This system combines state of the art mathematical models and new technologies for environmental monitoring, merging ground observed data with Earth observations from space and unconventional information from the cyberspace through crowdsourcing.
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Letseku, Violet, and Bennie Grové. "Crop Water Productivity, Applied Water Productivity and Economic Decision Making." Water 14, no. 10 (May 17, 2022): 1598. http://dx.doi.org/10.3390/w14101598.
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Increasing productive water use in agriculture is seen as paramount to meet future food demand with limited water supplies. The main objective of this paper is to gain a better understanding of the interrelated linkages between crop water productivity (CWP) and applied water productivity (AWP) as affected by irrigation management decisions in order to assess the impact of economic decision making on CWP and AWP under area-limiting and water-limiting conditions. A daily soil water balance mathematical programming model that explicitly models the impact of technology choice and stochastic weather on water use efficiency was used to study the interactions. The assumption is made that a rational decision maker will allocate water to maximize expected profits. The results showed that CWP is, to a large extent, unresponsive to increasing irrigation water applications, especially when water applications are approaching maximum potential crop yields. The difference between optimal crop yields for the area-limiting and water-limiting scenarios is small, which shows that the portion of water production function that is relevant for economic decision making is small and falls within the unresponsive range of CWP changes. Profit maximizing decision makers will not try to maximize CWP or AWP since these objectives will result in profit losses.
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Karpenko, S., and H. Rudakova. "Mathematical model of closed irrigation system as an object of control." System technologies 3, no. 140 (April 8, 2022): 60–70. http://dx.doi.org/10.34185/1562-9945-3-140-2022-06.
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Irrigation machines of the Frigate series are mainly used in closed irrigation systems in the south of Ukraine. During the operation of such systems there are problems with pressure control in the system, the problem of remote control of irrigation. A possible solution to these problems is to control the pressure in the water supply line of sprinklers, by automatically controlling the pumping equipment and installing appropriate sensors (pressure, flow meters, etc.) for feedback to the control system. By controlling the pumping equipment that creates pressure in the mains, it is possible to ensure proper modes of operation in the water supply mains of the DMU. Appropriate software for statistical data collection and management is also needed to improve watering and remote monitoring of the system. The aim of the study is to build a mathematical model of a closed irrigation system as an object of management, which will analyze the processes occurring in the system and evaluate the effectiveness of management methods being developed. The article considers the scheme of relationships between the main components of a closed irrigation system such as pump unit, distribution and irrigation pipeline, shut-off valves, universal sprinklers, control system with further mathematical description of each component. The main parameters of the system that affect its operation are identified. Set quality indicators that are put forward to the control system. The system as an object of control is analyzed, input, output and internal parameters of the system are revealed. The mathematical model of ZSS is built from the considered models of components, gives the chance to analyze the processes proceeding in system, and to estimate efficiency of the management methods developed. To determine the adequacy of the mathematical model, which is created by the proposed approach, it is advisable to simulate the operation of the ZSS for real conditions in different modes of operation. To determine the properties of ZSS as an object of control, such as inertia, controllability, stability, observation, it is necessary to obtain a model of the complex in the space of states.
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Parizi, Ana R. C., Adroaldo D. Robaina, Ana C. dos S. Gomes, Marcia X. Peiter, and Fátima C. Soares. "Corn yield under various simulated irrigation depths." Engenharia Agrícola 36, no. 3 (June 2016): 503–14. http://dx.doi.org/10.1590/1809-4430-eng.agric.v36n3p503-514/2016.
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ABSTRACT Mathematical models are tools to estimate and understand system behaviors against diverse situations; they may help in decision-making through simplified representations of the reality, allowing simulating various scenarios and estimating impacts of different courses of action on production systems, assisting thus in activity planning. Thus, this paper proposed a simulation of corn crop yields according to different field experiment characteristics and weather conditions in which it was conducted, with the purpose of setting a simulation model already calibrated and tested for corn crop cycle in the region of Santiago – RS, Brazil. The increasing water levels had a positive effect on grain yield and corn dry matter. On the other hand, a level of 800 mm reduced corn yield, as well as water application efficiency decreased from 550 mm. The proposed model can be used as a tool for regional planning in corn crop implementation under irrigation and enables identifying irrigation strategies for high grain yields, being considered a tool for yield prediction in irrigated crops.
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Moiseev, K., V. Terleev, T. Turutina, and D. Surinsky. "Physical modeling of water-retention capacity of soils." IOP Conference Series: Earth and Environmental Science 937, no. 2 (December 1, 2021): 022007. http://dx.doi.org/10.1088/1755-1315/937/2/022007.
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Abstract The function of the water-retention capacity of the soil is necessary, for example, when calculating irrigation norms in irrigation agriculture. Various mathematical models are used to approximate the water-retention capacity, which have a number of disadvantages inherent in these models. For example, the absence of physically adequate analytical descriptions for the coefficients of a given function. The use of physical fractal models for predicting and calculating the water-retention capacity of soils seems promising. Application of the fractal model Pore-Solid-Fractal is necessary to perform the calculation of desorption curves of water-retention capacity of some types of alpha-humus and texture-differentiated soils of light particle size distribution has been performed. The calculated data for the drying branches of the WRC are compared with the experimental data. The study of statistical differences between samples (data convergence) was carried out using the Mann-Whitney test (U). The empirical values of the U-test are from 17.5 to 20. The critical value of the U-test for a given number of compared data series at a probability level of 0.99 is 8. The critical value of the U-test for a given sample size is less than the calculated one, respectively, the difference between the series of empirical and the calculated data in the sample are not statistically significant. The fractal model allows calculating the water-retention capacity function of soils with high accuracy.
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Fuentes, Sebastián, and Carlos Chávez. "Modeling of Border Irrigation in Soils with the Presence of a Shallow Water Table. I: The Advance Phase." Agriculture 12, no. 3 (March 18, 2022): 426. http://dx.doi.org/10.3390/agriculture12030426.
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The overelevation of the water table in surface irrigation plots is one of the main factors affecting salinization in agricultural soils. Therefore, it is necessary to develop simulation models that consider the effect of a shallow water table in the process of advance-infiltration of the water in an irrigation event. This paper, the first in a series of three, develops a simple mathematical model for the advance phase of border irrigation in soils with the presence of a shallow water table. In this study, the hydrodynamic model of the Barré de Saint-Venant equations is used for the water surface flow, and the equations are solved using a Lagrangian finite-differences scheme, while in the subsurface flow, an analytical solution for infiltration in soils with a shallow water table is found using the bisection method to search for roots. In addition, a hydraulic resistance law is used that eliminates the numerical instabilities presented by the Manning–Strickler law. The model results for difference irrigation tests show adjustments with an R2 > 0.98 for the cases presented. It is also revealed that, when increasing the time step, the precision is maintained, and it is possible to reduce the computation time by up to 99.45%. Finally, the model proposed here is recommended for studying the advance process during surface irrigation in soils with shallow water tables.
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Zhu, Tao. "Research and Simulation of Optical Measurement Model in Chemical Pollution of Water." Applied Mechanics and Materials 644-650 (September 2014): 1042–45. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1042.
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Currently, the chemical pollution of water detection is mainly based on optical method. However, the optical detector is easily restricted by light and weather conditions. Optical measurement can be set on the target feature point, such as the laser reflection apparatus in laser measurement. This article applied the optical measurement method to research detection of water chemical pollution. Use theoretical and mathematical models of optical measurement method to perform the detection of chemical contamination in water. Optical measurement method is the trend of future development.
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Evans, Michael R., Giampaolo Zanin, and Todd J. Cavins. "E-values Generated from Substrate Dry-down Models as a Physical Property Measurement for Evaluating and Classifying Wetness of Root Substrates." HortScience 46, no. 4 (April 2011): 627–31. http://dx.doi.org/10.21273/hortsci.46.4.627.
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Water-holding capacity represents the volume of water retained by a substrate after a saturating irrigation and drainage, and it is often referred to as container capacity. However, water-holding capacity is a time-specific measurement that is limited to the status of the substrate immediately after saturation and drainage. It does not provide information regarding how quickly water is lost from the substrate, the substrate water status over time, or the irrigation frequency required for a substrate under specific conditions. A new procedure was developed that generated a single numeric value that described the wetness of a substrate and in so doing took into account the substrate's water-holding capacity and drying rate. This value was referred to as an E-value. For substrates included in this study, E-values ranged from a low of 6 for parboiled fresh rice hulls (PBH) to a high of 93 for the commercial substrate Metro Mix 360. The procedure was shown to generate E-values that were as would be expected for the evaluated substrates and also ranked the substrates as would have been expected. Over repeated evaluations, the procedure was demonstrated to have a maximum inherent variability of plus or minus one E-value.
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Vadiati, Meysam, Deasy Nalley, Jan Adamowski, Mohammad Nakhaei, and Asghar Asghari-Moghaddam. "A comparative study of fuzzy logic-based models for groundwater quality evaluation based on irrigation indices." Journal of Water and Land Development 43, no. 1 (December 1, 2019): 158–70. http://dx.doi.org/10.2478/jwld-2019-0074.
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AbstractGroundwater quality modelling plays an important role in water resources management decision making processes. Accordingly, models must be developed to account for the uncertainty inherent in the modelling process, from the sample measurement stage through to the data interpretation stages. Artificial intelligence models, particularly fuzzy inference systems (FIS), have been shown to be effective in groundwater quality evaluation for complex aquifers. In the current study, fuzzy set theory is applied to groundwater-quality related decision-making in an agricultural production context; the Mamdani, Sugeno, and Larsen fuzzy logic-based models (MFL, SFL, and LFL, respectively) are used to develop a series of new, generalized, rule-based fuzzy models for water quality evaluation using widely accepted irrigation indices and hydrological data from the Sarab Plain, Iran. Rather than drawing upon physiochemical groundwater quality parameters, the present research employs widely accepted agricultural indices (e.g., irrigation criteria) when developing the MFL, SFL and LFL groundwater quality models. These newly-developed models, generated significantly more consistent results than the United States Soil Laboratory (USSL) diagram, addressed the inherent uncertainty in threshold data, and were effective in assessing groundwater quality for agricultural uses. The SFL model is recommended as it outperforms both MFL and LFL in terms of accuracy when assessing groundwater quality using irrigation indices.
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Zhao, Rong-Heng, Wu-Quan He, Zong-Ke Lou, Wei-Bo Nie, and Xiao-Yi Ma. "Synchronization Optimization of Pipeline Layout and Pipe Diameter Selection in a Self-Pressurized Drip Irrigation Network System Based on the Genetic Algorithm." Water 11, no. 3 (March 8, 2019): 489. http://dx.doi.org/10.3390/w11030489.
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A synchronous optimization method for self-pressure drip irrigation pipe network system is proposed. We have generalized the optimization design problem of the system and have established the mathematical models for the simultaneous optimization design of pipeline layout and pipe diameters. A genetic algorithm based on the infeasibility degree of the solution was used to solve the model. A typical example is used to validate the presented method. The method exhibits effective performance in the case studied. Designers can use the results of this study to efficiently design self-pressurized drip irrigation network systems.
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Demchuk, Olena, Pavlo Kovalchuk, Roman Kovalenko, Volodymyr Kovalchuk, and Hanna Balykhina. "System Modeling and Management of Water Resources in Ingulets Basin." Modeling, Control and Information Technologies, no. 4 (October 23, 2020): 113–16. http://dx.doi.org/10.31713/mcit.2020.24.
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Mathematical models have been developed for managing the water resources of the Ingulets River in accordance with the requirements of the EU Water Framework Directive on the establishment of cost-effective water use with ensuring good or excellent ecological river status. The structural and functional diagram of the system model includes the subsystems: water supply by the Dnipro-Ingulets canal; flushing the Ingulets River from the Karachunivske reservoir and displacing the saline prism into the Dnipro River; environmental safety when discharging pollution into the river Ingulets; water supply for irrigation in the Ingulets irrigation system, prevention of soil salinization. Integrated management is carried out by subsystems, by types of management and by a system of criteria. A system of economic and environmental criteria for evaluating integrated management by the basin principle has been developed. Simulation of scenarios based on operational management is carried out. Scenarios are optimized according to the Pareto principle. An example of evaluating the effectiveness of the proposed control system and its comparison with the existing regulations for flushing the Ingulets River is given.
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Yakirevich, Alexander. "Water Flow, Solute and Heat Transfer in Groundwater." Water 12, no. 7 (June 28, 2020): 1851. http://dx.doi.org/10.3390/w12071851.
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Groundwater is an essential and vital water resource for drinking water production, agricultural irrigation, and industrial processes. The better understanding of physical and chemical processes in aquifers enables more reliable decisions and reduces the investments concerning water management. This Special Issue on “Water Flow, Solute and Heat Transfer in Groundwater” of Water focuses on the recent advances in groundwater dynamics. In this editorial, we introduce 12 high-quality papers that cover a wide range of issues on different aspects related to groundwater: protection from contamination, recharge, heat transfer, hydraulic parameters estimation, well hydraulics, microbial community, colloid transport, and mathematical models. By presenting this integrative volume, we aim to transfer knowledge to hydrologists, hydraulic engineers, and water resources planners who are engaged in the sustainable development of groundwater resources.
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El-Shafei, Ahmed A., and Mohamed A. Mattar. "Irrigation Scheduling and Production of Wheat with Different Water Quantities in Surface and Drip Irrigation: Field Experiments and Modelling Using CROPWAT and SALTMED." Agronomy 12, no. 7 (June 21, 2022): 1488. http://dx.doi.org/10.3390/agronomy12071488.
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Water is a key factor in global food security, which is critical to agriculture. The use of mathematical models is a strategy for managing water use in agriculture, and it is an effective way to predict the effect of irrigation management on crop yields if the accuracy of these models is demonstrated. The CROPWAT and SALTMED models were tested in this study, with water quantities applied to surface and drip irrigation (SI and DI) systems to estimate irrigation scheduling and wheat yield. For this purpose, field experiments were conducted for two consecutive years to study the effects of irrigation water levels of 80%, 100%, and 120% crop evapotranspiration (I80, I100, and I120) on the yield and water productivity (WP) of wheat in SI and DI systems. Irrigation treatments affected yield components such as plant height, number of spikes, spike length, and 1000-kernel weight, though they were not statistically different in some cases. In the I80 treatment, the biological yield was 12.8% and 8.5% lower than in the I100 and I120 treatments, respectively. I100 treatment under DI resulted in the highest grain yield of a wheat crop. When DI was applied, there was a maximum (22.78%) decrease in grain yield in the I80 treatment. The SI system was more water-consuming than the DI system was, which was reflected in the WP. When compared with the WP of the I80 and I100 treatments, the WP was significantly lower (p < 0.05) in the I120 treatment in the SI or DI system. To evaluate irrigation scheduling and estimate wheat yield response, the CROPWAT model was used. Since the CROPWAT model showed that increasing irrigation water levels under SI for water stress coefficient (Ks) values less than one increased deep percolation (DP), the I120 treatment had the highest DP value (556.15 mm on average), followed by the I100 and I80 treatments. In DI, I100 and I120 treatments had Ks values equal to one throughout the growing seasons, whereas the I80 treatment had Ks values less than one during wheat’s mid- and late-season stages. The I100 and I80 treatments with DI gave lower DP values of 93.4% and 74.3% compared with that of the I120 treatment (on average, 97.05 mm). The I120 treatment had the lowest irrigation schedule efficiency in both irrigation systems, followed by the I100 and I80 treatments. In both seasons, irrigation schedule deficiencies were highest in the I80 treatment with DI (on average, 12.35%). The I80 treatment with DI had a significant yield reduction (on average, 21.9%) in both seasons, while the irrigation level treatments with SI had nearly the same reductions. The SALTMED model is an integrated model that considers irrigation systems, soil types, crops, and water application strategies to simulate soil water content (SWC) and crop yield. The SALTMED model was calibrated and validated based on the experimental data under irrigation levels across irrigation systems. The accuracy of the model was assessed by the coefficients of correlation (R), root mean square errors (RMSE), mean absolute errors (MAE), and mean absolute relative error (MARE). When simulating SWC, the SALTMED models’ R values, on average, were 0.89 and 0.84, RMSE values were 0.018 and 0.019, MAE values were 0.015 and 0.016, and MARE values were 8.917 and 9.133%, respectively, during the calibration and validation periods. When simulating crop yield, relative errors (RE) for the SALTMED model varied between −0.11 and 24.37% for biological yield and 0.1 and 19.18% for grain yield during the calibration period, while in the validation period, RE was in the range of 3.8–29.81% and 2.02–25.41%, respectively. The SALTMED model performed well when simulating wheat yield with different water irrigation levels under SI or DI.
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Olgarenko, Gennadii, and Tatiana Kapustina. "Dynamics of the Variability of Heat and Moisture Supply Indicators and Irrigation Norms in the Сonditions of the Astrakhan Region." E3S Web of Conferences 295 (2021): 03003. http://dx.doi.org/10.1051/e3sconf/202129503003.
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During the scientific researches, scientific and methodological recommendations have been developed for determining the irrigation norms of crops for years with different water balance deficit availability, including a method for assessing and zoning a territory according to the coefficient of natural heat and moisture supply (moisture index) Mi, calculation models for rationing irrigation taking into account territorial and temporal variability, irrigation requirements for main crops, differentiated by natural and climatic zones within the Astrakhan Region. Based on statistical research and mathematical analysis of the main climatic indicators - air temperature and precipitation, trends and the degree of change in these indicators were investigated and identified according to observation data, as well as rational ecologically balanced regimes of irrigation of crops in the Astrakhan Region were calculated. According to the research results, based on the developed methodology, net irrigation requirements (mm) were calculated for the main forage and vegetable crops in years of different humidity (supply), taking into account the climatic zones identified by the moisture index (Mi) in the Astrakhan Region.
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Romashchenko, M. I., V. O. Bogaenko, A. P. Shatkovskyi, T. V. Matyash, S. S. Kolomiets, S. A. Shevchuk, Yu Yu Danylenko, and A. S. Sardak. "Conceptual principles of watering control under irrigation." Міжвідомчий тематичний науковий збірник "Меліорація і водне господарство", no. 1 (July 6, 2022): 5–17. http://dx.doi.org/10.31073/mivg202201-328.
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The conceptual principles of watering control under irrigation using decision support systems are outlined. Based on the analysis and research of foreign and domestic authors, it has been proven that the effectiveness of watering control depends to a large extent on the methodological approaches used to determine the terms and rates of watering in various decision support systems. It is shown that the most complete potential of varieties and hybrids of various types of crops under irrigation can be realized when establishing and implementing irrigation regimes ensuring the moisture supply of the soil root layer in a narrow range of high humidity (close to field water-holding capacity (FWHC) during the entire growing season.
It was grounded that the implementation of such irrigation regimes is possible only by applying decision support systems using GIS technologies, which combine hydrogeological models for calculation and forecasting of watering terms and rates, based on the use of soil moisture potential as a criterion of moisture supply availability for plants and Earth remote sensing data (ERSD). Such a combination makes it possible to analyze and apply measurement and forecasting data to the areas not covered by ground observations and provides highly efficient ecologically safe irrigation providing high irrigation water productivity and ecological safety of irrigation.
The implementation of these principles in the practice of irrigation management ensures the yield of irrigated crops as of 0.85-0.90 of the potential of modern varieties and hybrids, while simultaneously reducing the consumption of irrigation water per unit of yield, as well as minimizing or eliminating losses of irrigation water due to infiltration, development of flooding processes, salinization, and secondary salinization of soils.
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Kizilova, N. M., and N. L. Rychak. "Probabilistic models of water resources management on urbanized areas." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 4 (2020): 22–27. http://dx.doi.org/10.17721/1812-5409.2020/4.3.
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Gradual global climate change poses new challenges to the mathematical sciences, which are related to forecasting of meteorological conditions, preparing the infrastructure for possible rains, storms, droughts, and other climatic disasters. One of the most common approaches is synthetic regression-probability models, which use the spatio-temporal probability density functions of precipitation level. This approach is applied to the statistics of precipitation in the Kharkiv region, which shows the tendency to a gradual increase in air temperature, high indices of basic water stress, indices of drought and riverside flood threats. Open data on temperature distributions and precipitation were processed using various probability statistics. It is shown that the lognormal distribution most accurately describes the measurement data and allows making more accurate prognoses. Estimates of drought and flood probabilities in Kharkiv region under different scenarios of climate change dynamics have been carried out. The results of the study can be used for management of water resources on urban territories at global climate warming.
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Shehu, Musa D., A. A. Ahmed, and A. Abdulrahim. "Mathematical models and comparative analysis for rice irrigation crop water requirements: A case study of bida basin Niger State, Nigeria." New Trends in Mathematical Science 9 Special Issue, no. 1 (July 4, 2021): 17–20. http://dx.doi.org/10.20852/ntmsci.2021.422.
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Lopez-Jimenez, Jorge, Alain Vande Wouwer, and Nicanor Quijano. "Dynamic Modeling of Crop–Soil Systems to Design Monitoring and Automatic Irrigation Processes: A Review with Worked Examples." Water 14, no. 6 (March 12, 2022): 889. http://dx.doi.org/10.3390/w14060889.
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The smart use of water is a key factor in increasing food production. Over the years, irrigation has relied on historical data and traditional management policies. Control techniques have been exploited to build automatic irrigation systems based on climatic records and weather forecasts. However, climate change and new sources of information motivate better irrigation strategies that might take advantage of the new sources of information in the spectrum of systems and control methodologies in a more systematic way. In this connection, two open questions deserve interest: (i) How can one deal with the space–time variability of soil conditions? (ii) How can one provide robustness to an irrigation system under unexpected environmental change? In this review, the different elements of an automatic control system are described, including the mathematical modeling of the crop–soil systems, instrumentation and actuation, model identification and validation from experimental data, estimation of non-measured variables and sensor fusion, and predictive control based on crop–soil and weather models. An overview of the literature is given, and several specific examples are worked out for illustration purposes.
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Vilas Boas, Marcio Antonio. "PROGRAMA COMPUTACIONAL PARA SIMULAÇÃO DA IRRIGAÇÃO POR SUPERFÍCIE." IRRIGA 4, no. 3 (August 20, 1999): 124–31. http://dx.doi.org/10.15809/irriga.1999v4n3p124-131.
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PROGRAMA COMPUTACIONAL PARA SIMULAÇÃO DA IRRIGAÇÃO POR SUPERFÍCIE Márcio Antônio Vilas BoasUNIOESTE - Universidade Estadual do Oeste do ParanáDepartamento Engenharia - Cx. Postal 711Fone: (045) 225 -2100 (R-249) - Fax : (045) 223-4584CEP: 85814-110 - Cascavel - PR - Brasil 1 RESUMO Os modelos matemáticos propostos para simular o processo de irrigação por superfície constituem recursos valiosos, capazes de incluir inúmeras alternativas de dimensionamento, a um custo e tempo reduzidos. O objetivo do presente trabalho resumiu-se no desenvolvimento de um programa computacional para simular todas as fases do processo de irrigação por superfície, utilizando a aproximação Zero-inércia das equações de Saint-Venant. A linguagem de programação utilizada foi Visual Basic, em ambiente Windows 95. Para proceder à avaliação do modelo utilizou-se dados de irrigação em sulco e faixa obtidos em campos experimentais de precisão. Os resultados mostraram-se plenamente satisfatórios para a simulação de todas as fases da irrigação. O programa computacional desenvolvido pode ser útil também como instrumento didático. UNITERMOS: irrigação, irrigação por sulcos, simulação computacional. VILAS BOAS, M. A . Software for simulation of the surface irrigation 2 ABSTRACT The use of mathematical models to predict surface irrigation process may be a valuable tool wich allows several design alternatives, at reduced cost and time. The aim of this work is to develop a software to simulate all phases of surface irrigation, under the Zero-inertia approach, using a complete equations to describe surface flow. The computer program was developed in Visual Basic in Windows 95 environment. The model performance was evaluated by comparison with a precision furrow and border irrigation data. The results of both approaches were in good agreement with field data. The program may be also a useful tool for teaching. KEYWORDS: irrigation, surface irrigation furrow, computer simulation.
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Maiolo, Mario, Manuela Carini, Gilda Capano, Daniela Pantusa, and Marco Iusi. "Trends in metering potable water." Water Practice and Technology 14, no. 1 (December 10, 2018): 1–9. http://dx.doi.org/10.2166/wpt.2018.120.
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Abstract Sustainable management of drinking water distribution systems requires information on the operating status of system components to identify the best operational management measures. The ability to acquire information on tank levels, pipeline flow and real-time pressure offers an efficient and cost-effective management perspective, and enables wider monitoring, which can improve (physical) security as well. The technology of measuring instruments for hydrodynamic variables, used to monitor potable water systems, differs in their independence from electronic data acquisition components and ability to connect to remote data communication systems. Advanced water measurement infrastructure is characterized by the ability to capture data with measurable errors from anywhere in the system, without restrictions on communication type. This paper deals with the measurement of hydrodynamic parameters and a proposal for water meter classification. It includes analysis of the main water meter and data tele-acquisition infrastructure. Several selection criteria are evaluated with respect to their ability to support mathematical hydraulic models and expert systems for water distribution system management.
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Chen, Ling-Hsi, Jiunyuan Chen, and Chiachung Chen. "Effect of Environmental Measurement Uncertainty on Prediction of Evapotranspiration." Atmosphere 9, no. 10 (October 12, 2018): 400. http://dx.doi.org/10.3390/atmos9100400.
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Evapotranspiration (ET) is a typical biological environmental process to influence leaf temperature, crop water requirement, and greenhouse microclimate. Affecting factors of ET include air temperature, air relative humidity, wind speed, solar radiation, longwave radiation, soil moisture, CO2 concentration, and crop state. In this study, two ET models of indoor cultivation commonly adopted in literature were selected to evaluate the effect of the performance of sensors on the model uncertainty. The method of the International Organization for Standardization, Guides to the expression of Uncertainty in Measurement (ISO GUM) was adopted. The result indicated that the performance of leaf area index (LAI) and solar radiation (Is) sensors were primary sources of uncertainty. The uncertainty of ET models due to sensor performance needs to be considered. To ensure the predictive ability for applying the ET model for crops irrigation management and greenhouse environmental control, the improvements in the measurement of environmental variables for calculating ET would be of particular importance. The method of this study can be used for evaluating the uncertainty of ET models that calculate ET based on environmental variables measured by meteorological sensors or the remote sensing technique.
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Metselaar, Pinheiro, and Lier. "Mathematical Description of Rooting Profiles of Agricultural Crops and its Effect on Transpiration Prediction by a Hydrological Model." Soil Systems 3, no. 3 (July 8, 2019): 44. http://dx.doi.org/10.3390/soilsystems3030044.
Full textAbstract:
The geometry of rooting systems is important for modeling water flows in the soil-plant-atmosphere continuum. Measured information about root density can be summarized in adjustable equations applied in hydrological models. We present such descriptive functions used to model root density distribution over depth and evaluate their quality of fit to measured crop root density profiles retrieved from the literature. An equation is presented to calculate the mean root half-distance as a function of depth from root length density profiles as used in single root models for water uptake. To assess the importance of the shape of the root length density profile in hydrological modeling, the sensitivity of actual transpiration predictions of a hydrological model to the shape of root length density profiles is analyzed using 38 years of meteorological data from Southeast Brazil. The cumulative root density distributions covering the most important agricultural crops (in terms of area) were found to be well described by the logistic function or the Gompertz function. Root length density distribution has a consistent effect on relative transpiration, hence on relative yield, but the common approach to predict transpiration reduction and irrigation requirement from soil water storage or average water content is shown to be only partially supported by simulation results.
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Xu, Hui-Lian, Jianfang Bai, Saneyuki Kawabata, and Tingting Chang. "Applications of Xerophytophysiology and Signal Transduction in Plant Production—Flower Qualities in Eustoma grandiflorum Were Improved by Sub-Irrigation." Sustainability 15, no. 2 (January 13, 2023): 1578. http://dx.doi.org/10.3390/su15021578.
Full textAbstract:
Relatively mild xerophytic or hardening treatments can induce healthy development of plants. In the present study, as one of xerophytophysiological applications, sub-irrigation was applied to a flower plant of Eustoma grandiflorum to confirm whether the sub-irrigation improved flowering quality in addition to plant growth and physiology. As shown by the results, long-term sub-irrigation induced osmotic adjustment, with osmolyte concentration increasing 32.8 osmol m−3 (p ≤ 0.01), improved leaf photosynthetic activities, with more than 10% (p ≤ 0.05) increase in photosynthetic capacity, and promoted plant growth, with a shoot biomass increase by 27.5% (p ≤ 0.01) and a root increase by 50.5% (p ≤ 0.01). These improvements were attributed to turgor maintenance and cell water re-compartmentation into the symplasm, which were both the consequence of osmotic adjustment. The lower osmotic potential and lower relative leaf water potential at incipient plasmolysis suggested that plants in sub-irrigation plots might be more resistant to environmental stresses. Sub-irrigation also improved flower quality shown by increased anthocyanin concentration (16% up, p ≤ 0.01). Flower quality improvement might be attributed to up-regulation of the PAL gene, which could catalyze the synthesis of anthocyanins. PAL gene up-regulation might be associated with a concentration increase in salicylic acid (SA), which was suggested as a plant hormone for signaling. Sub-irrigation also affected the flower opening and closing oscillations with less changed opening size or oscillation amplitude. We adopted mathematical models and thoroughly analyzed dynamic changes in photosynthesis, plant growth, and flower opening oscillations. In conclusion, sub-irrigation was a feasible practice and could be used in E. grandiflorum culture to improve plant growth and flower opening quality.
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Hsu, Hung Cheng, and Wei Shang Fan. "Engineering Management on Modeling of Environmental Protection." Advanced Materials Research 734-737 (August 2013): 3352–55. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.3352.
Full textAbstract:
Management on modeling and measuring are seldom seen in management research but it is a good measurement to some issues. Environment & Energy issues are important but still no optimal solution. In the study, we use the mathematical model to deal with the management application. Earth pollutions are getting more and more serious. The Environment & Energy issues are two significant problems nowadays. The pollutions on earth are needed to be limited. We should do something on controlling the limited pollutions on earth as possible as we can. The study pays attention on the optimal control of the pollutions by mathematical models. We try to make the optimal solution on the pollutions origin. With the efficient control of the pollutions, the earth can absorb and invert the pollutions. This is the main purpose of the study and the methodology are seldom seem in researches. The study also uses mathematical model to make this issue to be a discussible model. With the mathematical models and Euler equation in the study, we can get the optimal solution in scientific method and it is available for governments to handle with the pollution control. In the study, we take water pollution for example because air and water are two main matters for human beings. If water pollutions are getting serious, we hardly survive. Key words: Euler equation, mathematical models
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Ghiat, Ikhlas, Hamish R. Mackey, and Tareq Al-Ansari. "A Review of Evapotranspiration Measurement Models, Techniques and Methods for Open and Closed Agricultural Field Applications." Water 13, no. 18 (September 15, 2021): 2523. http://dx.doi.org/10.3390/w13182523.
Full textAbstract:
Detailed knowledge of energy and mass fluxes between land and the atmosphere are necessary to monitor the climate of the land and effectively exploit it in growing agricultural commodities. One of the important surface land fluxes is evapotranspiration, which combines the process of evaporation from the soil and that of transpiration from plants, describing the movement of water vapour from the land to the atmosphere. Accurately estimating evapotranspiration in agricultural systems is of high importance for efficient use of water resources and precise irrigation scheduling operations that will lead to improved water use efficiency. This paper reviews the major mechanistic and empirical models for estimating evapotranspiration including the Penman–Monteith, Stanghellini, Priestly–Taylor, and Hargreaves and Samani models. Moreover, the major differences between the models and their underlined assumptions are discussed. The application of these models is also reviewed for both open and closed field mediums and limitations of each model are highlighted. The main parameters affecting evapotranspiration rates in greenhouse settings including aerodynamic resistance, stomatal resistance and intercepted radiation are thoroughly discussed for accurate measurement and consideration in evapotranspiration models. Moreover, this review discusses direct evapotranspiration measurements systems such as eddy covariance and gas exchange systems. Other direct measurements appertaining to specific parameters such as leaf area index and surface leaf temperature and indirect measurements such as remote sensing are also presented, which can be integrated into evapotranspiration models for adaptation depending on climate and physiological characteristics of the growing medium. This review offers important directions for the estimation of evapotranspiration rates depending on the agricultural setting and the available climatological and physiological data, in addition to experimentally based adaptation processes for ET models. It also discusses how accurate evapotranspiration measurements can optimise the energy, water and food nexus.