scholarly journals Decision support for agricultural water management

2013 ◽  
Vol 14 (3) ◽  
pp. 255-263 ◽  
Keyword(s):  
Decision Support ◽  
Water Use ◽  
Irrigation Water ◽  
Agricultural Land ◽  
Crop Yields ◽  
Swat Model ◽  
Irrigation Scheduling ◽  
Agricultural Landscapes ◽  
Agricultural Water ◽  
Matlab Programming

Irrigation water use is the major pressure limiting the availability of fresh water resources in the Mediterranean. Efficient irrigation scheduling programs (IRSPs) are able to reduce water consumption; however, their selection and placement in large agricultural landscapes depend on location specific characteristics and economic indicators. Towards this end, a novel and efficient Decision Support Tool (DST) is developed in MATLAB-programming, able to assess the effectiveness of different IRSPs in reducing total agricultural water use at the catchment scale along with their impact on crop yields. The DST integrates a look-up table with data on irrigation water amounts and crop yields at different locations within a catchment, populated by a hydrological and crop growth estimator: the process-based SWAT model, into a multi-objective Genetic Algorithm, which serves as the optimization engine for the allocation of measures across the agricultural land. The optimization scheme leads rapidly to the optimal trade-off frontier between the conflicting objectives providing spatial allocations of IRSPs. The tool was implemented in the Ali Efenti catchment demonstrating optimal solutions that could save more than 10% of water by reducing cotton yields less than 5% from the baseline. The study highlights the potential of the tool to assist in the development of cost-effective water saving plans at the catchment level in order to reduce the risk of desertification in intensively cultivated areas.

Irrigation Scheduling Based on Evaporation and Crop Water Requirement for Summer Peanuts1

1984 ◽  
Vol 11 (1) ◽  
pp. 4-6 ◽  
Author(s):  
D. K. Pahalwan ◽  
R. S. Tripathi
Keyword(s):  
Water Use ◽  
Irrigation Water ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Pan Evaporation ◽  
Crop Water ◽  
Formation Stage ◽  
Evaporation Ratio ◽  
Pod Development

Abstract Field experiment was conducted during dry season of 1981 and 1982 to determine the optimal irrigation schedule for summer peanuts (Arachis hypogaea L.) in relation to evaporative demand and crop water requirement at different growth stages. It was observed that peanut crop requires a higher irrigation frequency schedule during pegging to pod formation stage followed by pod development to maturity and planting to flowering stages. The higher pod yield and water use efficiency was obtained when irrigations were scheduled at an irrigation water to the cumulative pan evaporation ratio of 0.5 during planting to flowering, 0.9 during pegging to pod formation and 0.7 during pod development to maturity stage. The profile water contribution to total crop water use was higher under less frequent irrigation schedules particularly when the irrigations were scheduled at 0.5 irrigation water to the cumulative pan evaporation ratio up to the pod formation stage.

scholarly journals Optimization of irrigation water in South Africa for sustainable and beneficial use

2017 ◽  
Author(s):  
◽  
Akinola Mayowa Ikudayisi
Keyword(s):  
South Africa ◽  
Water Use ◽  
Crop Yield ◽  
Optimization Algorithm ◽  
Irrigation Water ◽  
Irrigation Scheduling ◽  
Crop Water ◽  
Land Area ◽  
Water Requirements ◽  
Irrigation Water Use

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.

Irrigation management through a coupled energy-water balance and crop growth model driven by remote sensing data

2021 ◽  
Author(s):  
Marco Mancini ◽  
Chiara Corbari ◽  
Imen Ben Charfi ◽  
Ahmad Al Bitar ◽  
Drazen Skokovic ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Water Use ◽  
Irrigation Water ◽  
Crop Yields ◽  
Irrigation Management ◽  
Balance Model ◽  
Soil Parameters ◽  
Area Index ◽  
Landsat 7

<p>The conflicting use of water is becoming more and more evident, also in regions that are traditionally rich in water. With the world’s population projected to increase to 8.5 billion by 2030, the simultaneous growth in income will imply a substantial increase in demand for both water and food. Climate change impacts will further stress the water availability enhancing also its conflictual use. The agricultural sector is the biggest and least efficient water user, accounts for around 24% of total water use in Europe, peaking at 80% in the southern regions.</p><p>This paper shows the implementation of a system for real-time operative irrigation water management at high spatial and temporal able to monitor the crop water needs reducing the irrigation losses and increasing the water use efficiency, according to different agronomic practices supporting different level of water users from irrigation consortia to single farmers. The system couples together satellite (land surface temperature LST and vegetation information) and ground data, with pixel wise hydrological crop soil water energy balance model. In particular, the SAFY (Simple Algorithm for Yield) crop model has been coupled with the pixel wise energy water balance FEST-EWB model, which assimilate satellite LST for its soil parameters calibration. The essence of this coupled modelling is that the SAFY provides the leaf area index (LAI) evolution in time used by the FEST-EWB for evapotranspiration computation while FEST-EWB model provides soil moisture (SM) to SAFY model for computing crop grow for assigned water content.</p><p>The FEST-EWB-SAFY has been firstly calibrated in specific fields of Chiese (maize crop) and Capitanata (tomatoes) where ground measurements of evapotranspiration, soil moisture and crop yields are available, as well as LAI from Sentinel2-Landsat 7 and 8 data. The FEST-EWB-SAFY model has then been validated also on several fields of the RICA farms database in the two Italian consortia, where the economic data are available plus the crop yield. Finally, the modelled maps of LAI have then been validated over the whole Consortium area (Chiese and Capitanata) against satellite data of LAI from Landsat 7 and 8, and Sentinel-2.</p><p>Optimized irrigation volumes are assessed based on a soil moisture thresholds criterion, allowing to reduce the passages over the field capacity threshold reducing the percolation flux with a saving of irrigation volume without affecting evapotranspiration and so that the crop production. The implemented strategy has shown a significative irrigation water saving, also in this area where a traditional careful use of water is assessed.</p><p>The activity is part of the European project RET-SIF (www.retsif.polimi.it).</p>

scholarly journals Potential and Actual Water Savings through Improved Irrigation Scheduling in Small-Scale Vegetable Production

Agronomy ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 888 ◽  
Author(s):  
Christoph Studer ◽  
Simon Spoehel
Keyword(s):  
Water Use ◽  
Irrigation Water ◽  
Drip Irrigation ◽  
Water Productivity ◽  
Irrigation Scheduling ◽  
Small Scale ◽  
Vegetable Production ◽  
Usual Practice ◽  
Irrigation Water Use ◽  
Small Scale Farmers

Appropriate irrigation scheduling for efficient water use is often a challenge for small-scale farmers using drip irrigation. In a trial with 12 farmers in Sébaco, Nicaragua, two tools to facilitate irrigation scheduling were tested: the Water Chart (a table indicating required irrigation doses) and tensiometers. The study aimed at evaluating if and to what extent simple tools can reduce irrigation water use and improve water productivity in drip-irrigated vegetable (beetroot; Beta vulgaris L.) production compared with the farmers’ usual practice. Irrigation water use was substantially reduced (around 20%) when farmers irrigated according to the tools. However, farmers did not fully adhere to the tool guidance, probably because they feared that their crop would not get sufficient water. Thus they still over-irrigated their crop: between 38% and 88% more water than recommended was used during the treatment period, resulting in 91% to 139% higher water use than required over the entire growing cycle. Water productivity of beetroot production was, therefore, much lower (around 3 kg/m3) than what can be achieved under comparable conditions, although yields were decent. Differences in crop yield and water productivity among treatments were not significant. The simplified Water Chart was not sufficiently understandable to farmers (and technicians), whereas tensiometers were better perceived, although they do not provide any indication on how much water to apply. We conclude that innovations such as drip irrigation or improved irrigation scheduling have to be appropriately introduced, e.g., by taking sufficient time to co-produce a common understanding about the technologies and their possible usefulness, and by ensuring adequate follow-up support.

Combining the FAO56 agrohydrological model and remote sensing data to assess water demand in a Sicilian irrigation district

2020 ◽  
Author(s):  
Matteo Ippolito ◽  
Mario Minacapilli ◽  
Giuseppe Provenzano
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Use ◽  
Irrigation Water ◽  
Remote Sensing Data ◽  
Irrigation Scheduling ◽  
Irrigation District ◽  
Sensing Data ◽  
Spatiotemporal Distributions ◽  
Crop Parameters

<p>Agricultural water use in irrigated areas plays a key role in the Mediterranean regions characterized by semi-arid climate and water shortage. In the face of optimizing irrigation water use, farmers must revise their irrigation practices to increase the drought resilience of agricultural systems and to avoid severe damages in agro-ecosystems. In this direction, during the last decades, the research has been focused on mathematical models to simulate the process of driving mass transport and energy exchanges in the Soil-Plant-Atmosphere system.</p><p>The objective of the paper was to test the suitability of the combination of FAO56 agro-hydrological model with remote sensing data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform, to assess the spatiotemporal distributions of crop water requirement and to schedule irrigation in an irrigation district of the south-west of Sicily, Italy.</p><p>The proposed approach allowed obtaining the spatiotemporal distributions of soil and crop parameters used in the FAO56 model implemented in a GIS environment to simulate the water balance, as well as to assess the actual irrigation strategy. The GIS database was organized to include soil and crop parameters, as well as the irrigation volumes actually delivered to each farmer; the latter data can be used not only as input for water balance to evaluate the efficiency of the actual irrigation strategies but also to identify different irrigation scheduling scenario obtained by the FAO56 procedure.</p><p>The first application was carried out for the period 2014-2017, to identify a combination of irrigation scheduling parameters to be implemented in the model aimed at reproducing the ordinary strategy adopted by the farmers, based on the spatiotemporal variability of soil and climate forcings. When the model outputs were aggregated for single crop types, a fairly good agreement was found between simulated and actual seasonal irrigation volumes delivered either at the level of district and secondary units. Alternative scenarios of irrigation water distribution were then identified and analyzed, to provide irrigation technicians and policymakers a decision support tool to improve the efficiency of irrigation systems and to optimize the distribution based on the availability of water resources.</p>

scholarly journals Assessment of Irrigation Water Use Patterns Using Remote Sensing Data in Mexico’s Northeast

10.29007/qz1w ◽  
2018 ◽  
Author(s):  
Saul Arciniega ◽  
Jose A. Breña-Naranjo ◽  
Adrián Pedrozo-Acuña ◽  
Antonio Hernández-Espriú
Keyword(s):  
Remote Sensing ◽  
Water Use ◽  
Irrigation Water ◽  
Land Surface ◽  
Irrigation System ◽  
Functional Model ◽  
Remote Sensing Data ◽  
Irrigation Scheduling ◽  
Sensing Data ◽  
Irrigation Water Use

Irrigation water use (IWU) or withdrawal is a key component for the water management of a region since it tends to exceed the crops consumptive water use, especially in water-stressed regions where groundwater is the main source of water. Nevertheless, temporal IWU information is missing in many irrigation areas. Remote sensing (RS) data is commonly used for crop water requirements estimations in areas with lack of data, however, IWU is more complex to approach since it also depends on water use efficiency, irrigation system type, irrigation scheduling, and water availability, among others. This work explores the use of remote sensing data (TRMM, MODIS) and land surface hydrological products (GLDAS 2 and MERRA 2) to obtain insights about the space-time annual IWU patterns across croplands located within Mexico’s northeast region. Reported IWU in three irrigation districts (Don Martín, Región Lagunera and Bajo Río Bravo) was used to obtain a functional model using satellite data derived. Results suggest strong relationship between reported IWU with soil moisture content from GLDAS and the maximum annual EVI from MODIS, where a potential regression shown statistical correlations of 0.83 and 0.77, respectively.

scholarly journals Theoretical and applied aspects of the use of agricultural and forest meliorative plantations of Ukraine for energy purposes

Bioenergy ◽  
2021 ◽  
Author(s):  
M. V. Roik ◽  
Ya. D. Fuchylo ◽  
O. M. Hanzhenko
Keyword(s):  
Agricultural Land ◽  
Crop Yields ◽  
Positive Impact ◽  
Agricultural Landscapes ◽  
Forest Plantations ◽  
Bioenergy Feedstock ◽  
Forest Protection ◽  
Protective Forest ◽  
Surrounding Areas

Protective forest plantations are an important part of forest-agricultural landscapes and one of the most effective long-term and relatively inexpensive measures to combat wind and water soil erosion. They have a positive effect on the microclimate of the surrounding areas and can significantly increase crop yields. Also, under certain conditions, they can become an important source of bioenergy feedstock. Goal. Development of theoretical bases and practical measures of the use of agroforestry reclamation plantations of Ukraine for energy purposes. Methods. In the course of the research it was envisaged to develop schemes of protective forest plantations on the basis of the analysis of the existing information, long-term production and scientific experience which, at full performance of ecological functions, can be used for obtaining bioenergy feedstock. Results. It is established that for the simultaneous use of protective forest plantations as a source of energy biomass it is necessary to include fast-growing woody plants (willow, poplar, acacia, maple, etc.) in rows or backstage, which are expected to be periodically cut for biomass. Such plants are then intensively restored by growth from stumps. The basis of such plantations for long-term and permanent performance of their protective functions should mainly consists of the rows of oak trees. Conclusions. Protective forest plantations, in addition to the positive impact on the microclimate of the environment and a significant increase in the productivity of agricultural land, can also play an important role as a source of bioenergy feedstock. Today, forest protection plantations are losing their functions for various reasons and need to be reconstructed. At the same time, along with the restoration of protective plantations, it will be possible to obtain about 54.6 million tons of wood for energy needs and form new protective plantations, which, along with improving the ecological environment, will create a reliable feedstock base for bioenergy. The schemes presented in the article can be applied at the stage of restoration and expansion of the field protection system to increase their energy role.

scholarly journals Salt Tolerance Analysis of Crops using the SWAP Model

2017 ◽  
Vol 14 (2) ◽  
pp. 643-649
Author(s):  
Forough Kamyab-Talesh ◽  
Behrouz Mostafazadeh-Fard ◽  
Majid Vazifedoust ◽  
Mohammad Shayannejad ◽  
Maryam Navabian
Keyword(s):  
Irrigation Water ◽  
Arid Regions ◽  
Good Accuracy ◽  
Crop Yields ◽  
Tolerance Analysis ◽  
Irrigation Scheduling ◽  
Threshold Values ◽  
Irrigation Network ◽  
Swap Model ◽  
Semi Arid

ABSTRACT: Soil and water salinities are major environmental factors limiting the productivity of agricultural lands especially in arid and semi arid regions. To determine salinity threshold values and slope of the yield decrements for crops of wheat, barley and maize, SWAP model was study for an arid region located in Semnan Province (52◦25' N 35◦11' E), central part of Iran with area of 35000 ha including 94 villages belonged to irrigation network of Garmsar district. The data collected from the above 94 villages for years 1998 to 2007 were used to calibrate and simulate yield of wheat, barley and maize using the SWAP model. The irrigation water salinities of 2, 4, 6 and 8 dS m-1 were used and yield reductions versus soil saturation extracts were evaluated and salinity threshold values and slope of the yield reductions were determined for each of the above crops. The results showed that the SWAP model predict crop yields with good accuracy and the threshold values and slope of the yield reductions are site dependent. These values should be determined for each area in order to be able to plan better irrigation scheduling for arid regions which have soil and irrigation water salinities problems.

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