scholarly journals Combined simulation and optimization framework for irrigation scheduling in agriculture fields

2021 ◽  
Author(s):  
Mireia Fontanet ◽  
Daniel Fernàndez-Garcia ◽  
Gema Rodrigo ◽  
Francesc Ferrer ◽  
Josep Maria Villar
Keyword(s):  
Crop Yields ◽  
Root Zone ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Traditional Methods ◽  
Simulation And Optimization ◽  
Optimization Framework ◽  
Net Margin ◽  
Combined Simulation

AbstractIn the context of growing evidence of climate change and the fact that agriculture uses about 70% of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is, therefore, one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil–water–crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.

scholarly journals Combined Simulation and Optimization Framework for Irrigation Scheduling in Agriculture Fields

2020 ◽  
Author(s):  
Mireia Fontanet ◽  
Daniel Fernàndez-Garcia ◽  
Gema Rodrigo ◽  
Francesc Ferrer ◽  
Josep Maria Villar
Keyword(s):  
Crop Yields ◽  
Root Zone ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Traditional Methods ◽  
Simulation And Optimization ◽  
Optimization Framework ◽  
Net Margin ◽  
Combined Simulation

Abstract. In the context of growing evidence of climate change and the fact that agriculture uses about 70 % of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is therefore one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil-water-crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.

Detecting changes in root zone soil moisture from radar vegetation backscatter

2020 ◽  
Author(s):  
Coleen Carranza ◽  
Tim van Emmerik ◽  
Martine van der Ploeg
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Hydrological Cycle ◽  
Root Zone ◽  
Water Status ◽  
Roughness Parameter ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Vegetation Water Content ◽  
Vegetation Water

<p>Root zone soil moisture (θ<sub>rz</sub>) is a crucial component of the hydrological cycle and provides information for drought monitoring, irrigation scheduling, and carbon cycle modeling. During vegetation conditions, estimation of θ<sub>rz</sub> thru radar has so far only focused on retrieving surface soil moisture using the soil component of the total backscatter (σ<sub>soil</sub>), which is then assimilated into physical hydrological models. The utility of the vegetation component of the total backscatter (σ<sub>veg</sub>) has not been widely explored and is commonly corrected for in most soil moisture retrieval methods. However, σ<sub>veg </sub>provides information about vegetation water content. Furthermore, it has been known in agronomy that pre-dawn leaf water potential is in equilibrium with that of the soil. Therefore soil water status can be inferred by examining  the vegetation water status. In this study, our main goal is to determine whether changes in root zone soil moisture (Δθ<sub>rz</sub>) shows corresponding changes in vegetation backscatter (Δσ<sub>veg</sub>) at pre-dawn. We utilized Sentinel-1 (S1) descending pass and in situ soil moisture measurements from 2016-2018 at two soil moisture networks (Raam and Twente) in the Netherlands. We focused on corn and grass which are the most dominant crops at the sites and considered the depth-averaged θ<sub>rz</sub> up to 40 cm to capture the rooting depths for both crops. Dubois’ model formulation for VV-polarization was applied to estimate the surface roughness parameter (H<sub>rms</sub>) and σ<sub>soil </sub>during vegetated periods. Afterwards, the Water Cloud Model was used to derive σ<sub>veg</sub> by subtracting σ<sub>soil</sub> from S1 backscatter (σ<sub>tot</sub>). To ensure that S1 only measures vegetation water content, rainy days were excluded to remove the influence of intercepted rainfall on the backscatter. The slope of regression lines (β) fitted over plots of Δσ<sub>veg</sub> against Δθ<sub>rz</sub> were used investigate the dynamics over a growing season. Our main result indicates that Δσ<sub>veg </sub>- Δθ<sub>rz</sub> relation is influenced by crop growth stage and changes in water content in the root zone. For corn, changes in β’s over a growing season follow the trend in a crop coefficient (K<sub>c</sub>) curve, which is a measure of crop water requirements. Grasses, which are perennial crops, show trends corresponding to the mature crop stage. The correlation between soil moisture (Δθ) at specific soil depths (5, 10, 20, and 40 cm) and Δσ<sub>veg </sub> matches root growth for corn and known rooting depths for both corn and grass. Dry spells (e.g. July 2018) and a large increase in root zone water content in between two dry-day S1 overpass (e.g. from rainfall) result in a lower β, which indicates that Δσ<sub>veg</sub> does not match well with Δθ<sub>rz</sub>. The influence of vegetation on S1 backscatter is more pronounced for corn, which translated to a clearer Δσ<sub>veg</sub> - Δθ<sub>rz</sub> relation compared to grass. The sensitivity of Δσ<sub>veg</sub> to Δθ<sub>rz</sub> in corn means that the analysis may be applicable to other broad leaf crops or forested areas, with potential applications for monitoring  periods of water stress.</p>

scholarly journals Model based irrigation water application of maize (zeamays l.) to improve water productivity in irrigated agriculture

2020 ◽  
pp. 37918-37925
Author(s):  
Keyword(s):  
Crop Yields ◽  
Water Productivity ◽  
Irrigation Schedule ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Irrigated Agriculture ◽  
Accurate Estimation ◽  
Crop Water ◽  
Maize Crop ◽  
Irrigation Requirements

Under the semiarid and arid climate of Eastern Europe, accurate estimation of crop water requirement and irrigation scheduling is important for water management and planning. The objectives of this study were to estimate maize water requirement and irrigation scheduling in variable climatic conditions. CROPWAT model is decision support system developed by United Nations Food and Agriculture Organization (FAO) and it is used as a practical tool to carry out standard calculations for reference evapotranspiration, crop water requirements, irrigation scheduling, and also allows helps in planning and decision making in the areas where water resource availability is varying and scarce. The study result indicated that Maize seasonal amounts of irrigation requirements varied from 439.5 to 615.0 mm. Maize actual daily evapotranspiration (ETa) varied from 0.12 to 4.13 mm and from 0.27 to 4.68 mm in 2010 and 2011 respectively. Net irrigation schedule for all growing periods in 2010 was zero for initial and late but for development 138.9 mm and 45.9 mm for mid-stage of the growing period. However, 2011 were zero, 83.7 mm, 178 mm, and 98.2 mm in initial, mid, and development and late stages respectively. Besides in the study area, 2010 was the wettest year but 2011 was determined as the driest year this may cause adverse conditions on maize crop yields quantity and quality. Irrigation requirements for maize should be adjusted to the local meteorological conditions for optimizing maize irrigation requirements and improving maize water productivity under such climatic variable conditions.

Irrigation scheduling and water requirements for cowpea using evaporation pan at middle of Iraq

1970 ◽  
pp. 13-17
Author(s):  
Saifuldeen A. Salim ◽  
Isam Kudhier Hamza ◽  
Laith Farhan Jar
Keyword(s):  
Water Productivity ◽  
Irrigation Treatment ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Water Requirements ◽  
Applied Water ◽  
Fresh Seed ◽  
Irrigation Interval ◽  
Biological Yield ◽  
Evaporation Pan

The present study was conducted to find out the water requirements and most suitable irrigation frequencies for cowpea (Vigna unguiculata L.) var grown under drip irrigation. The treatments were based on the IW:CPE ratio at different empirical pan factors 0.6 , 0.8, 1.0, 1.,1.4 , and 1.6 Ef (where Ef = IW/CPE). It was observed that the irrigation interval was variable values decreased by increasing Ef value and with the progress of the growing season. The 1.2 and 1.0 IW: CPE treatments with approximately 4 days irrigation interval were achieved the best results. The total amount of applied water during Cowpea growing season was varied between 247.7 and 266.5mm with 254.8mm as a mean. Irrigation treatment with Ef1.2 was superior over the rest of other treatments in fresh seed yield (5.13 ton.hec.-1), crop water productivity (2.14 kg.m-3), biological yield (6.88 ton.hec.-1) , fresh pod yield (7.33 ton.hec.-1), weight of 100 seed (31.28gm), number of seed/pod (9.34) and netting percentage (37.1). The lowest values of the most parameters used in this study were obtained by Ef 0.6 irrigation treatment.  

Field Measurements and Simulation of Nitrogen Fate under Citrus Production

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 498c-498
Author(s):  
A. Fares ◽  
A.K. Alva ◽  
S. Paramasivam
Keyword(s):  
Mass Balance ◽  
Best Management Practices ◽  
Rainy Season ◽  
Crop Production ◽  
Management Practices ◽  
Root Zone ◽  
Field Measurements ◽  
Irrigation Scheduling ◽  
N Leaching ◽  
Citrus Production

Water and nitrogen (N) are important inputs for most crop production. The main objectives of nitrogen best management practices (NBMP) are to improve N and water management to maximize the uptake efficiency and minimize the leaching losses. This require a complete understanding of fate of N and water mass balance within and below the root zone of the crop in question. The fate of nitrogen applied for citrus production in sandy soils (>95% sand) was simulated using a mathematical model LEACHM (Leaching Estimation And Chemistry Model). Nitrogen removal in harvested fruits and storage in the tree accounted the major portion of the applied N. Nitrogen volatilization mainly as ammonia and N leaching below the root zone were the next two major components of the N mass balance. A proper irrigation scheduling based on continuous monitoring of the soil water content in the rooting was used as a part of the NBMP. More than 50% of the total annual leached water below the root zone was predicted to occur in the the rainy season. Since this would contribute to nitrate leaching, it is recomended to avoid N application during the rainy season.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

scholarly journals THE WATER RELATIONS AND IRRIGATION REQUIREMENTS OF SUGAR CANE (SACCHARUM OFFICINARUM): A REVIEW

2011 ◽  
Vol 47 (1) ◽  
pp. 1-25 ◽  
Author(s):  
M. K. V. CARR ◽  
J. W. KNOX
Keyword(s):  
Water Stress ◽  
Water Relations ◽  
Sugar Cane ◽  
Root Zone ◽  
Water Productivity ◽  
Crop Coefficient ◽  
Saccharum Officinarum ◽  
Irrigation Scheduling ◽  
Background Information ◽  
Technology Choice

SUMMARYThe results of research on the water relations and irrigation needs of sugar cane are collated and summarized in an attempt to link fundamental studies on crop physiology to irrigation practices. Background information on the centres of production of sugar cane is followed by reviews of (1) crop development, including roots; (2) plant water relations; (3) crop water requirements; (4) water productivity; (5) irrigation systems and (6) irrigation scheduling. The majority of the recent research published in the international literature has been conducted in Australia and southern Africa. Leaf/stem extension is a more sensitive indicator of the onset of water stress than stomatal conductance or photosynthesis. Possible mechanisms by which cultivars differ in their responses to drought have been described. Roots extend in depth at rates of 5–18 mm d−1 reaching maximum depths of > 4 m in ca. 300 d providing there are no physical restrictions. The Penman-Monteith equation and the USWB Class A pan both give good estimates of reference crop evapotranspiration (ETo). The corresponding values for the crop coefficient (Kc) are 0.4 (initial stage), 1.25 (peak season) and 0.75 (drying off phase). On an annual basis, the total water-use (ETc) is in the range 1100–1800 mm, with peak daily rates of 6–15 mm d−1. There is a linear relationship between cane/sucrose yields and actual evapotranspiration (ETc) over the season, with slopes of about 100 (cane) and 13 (sugar) kg (ha mm)−1 (but variable). Water stress during tillering need not result in a loss in yield because of compensatory growth on re-watering. Water can be withheld prior to harvest for periods of time up to the equivalent of twice the depth of available water in the root zone. As alternatives to traditional furrow irrigation, drag-line sprinklers and centre pivots have several advantages, such as allowing the application of small quantities of water at frequent intervals. Drip irrigation should only be contemplated when there are well-organized management systems in place. Methods for scheduling irrigation are summarized and the reasons for their limited uptake considered. In conclusion, the ‘drivers for change’, including the need for improved environmental protection, influencing technology choice if irrigated sugar cane production is to be sustainable are summarized.

SOIL CONDITIONERS—THEIR EFFECT ON COARSE-TEXTURED SOILS, CROP YIELDS AND COMPOSITION

1957 ◽  
Vol 37 (2) ◽  
pp. 102-112
Author(s):  
R. M. Holmes ◽  
S. J. Toth
Keyword(s):  
Structural Changes ◽  
Crop Yields ◽  
Cultural Practices ◽  
Sandy Soils ◽  
Growing Season ◽  
Soil Aggregate ◽  
Crop Response ◽  
The Third ◽  
Soil Conditioners ◽  
The Stability

Crop response to soil structural changes caused by soil conditioner amendments was studied in several different sandy soils of New Jersey. The response varied with the crop and treatment. Those chemicals that were slightly hydrophobic were most effective and generally crop response was greatest on these treatments. Cations such as Na may be added in large amounts as part of some conditioners, and this may result in reduced uptake of other nutrients such as Mg. and K. Except for this effect, conditioners did not reduce nutrient uptake by plants. When elements such as Na and N are added in large amounts as part of some conditioners, there may be an increased uptake of these nutrients.Catalin and VAMA conditioners produced a dry surface mulch which appeared to reduce evaporation. Moisture reserves were, therefore, preserved through a drought and this resulted in increased growth of crops over those grown on other treatments. Cultural practices destroyed the stability of the conditioned aggregates, since in most cases the effect had largely disappeared by the third growing season. Chemicals which were effective in soil aggregate stabilization were also effective as anti-crustants when crusting was a problem.

scholarly journals Root-zone fertilization improves crop yields and minimizes nitrogen loss in summer maize in China

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Chaoqiang Jiang ◽  
Dianjun Lu ◽  
Chaolong Zu ◽  
Jianmin Zhou ◽  
Huoyan Wang
Keyword(s):  
Crop Yields ◽  
Root Zone ◽  
Nitrogen Loss ◽  
Summer Maize

scholarly journals PRODUCTIVITY OF PERENNIAL GRASSES AND MIXTURES WITH DIFFERENT SOWING DATES IN WESTERN SIBERIA

2020 ◽  
pp. 24-32
Author(s):  
V. A. Petruk
Keyword(s):  
Dry Matter ◽  
Crop Yields ◽  
Growing Season ◽  
Single Species ◽  
Field Studies ◽  
Perennial Grasses ◽  
First Year ◽  
Sowing Dates ◽  
Second Year ◽  
Sowing Period

The results of field studies for 2017 - 2019 are presented. yields of perennial grasses sown at different times of the growing season. Spring, summer, and winter sowing periods were compared. Alfalfa, clover, rump, and also their mixtures were sown in 2017 under the cover of barley. The value of the cover crop yield of spring and summer sowing periods did not differ significantly and amounted to 4-5 t / ha of absolutely dry matter. Winter barley crops have not formed. On average, over 2 years of use, the highest yields were observed in alfalfa-crust grass mixtures - 3.4 t / ha of absolutely dry matter. The lowest yield was obtained in the single-species seeding of the rump. Correspondingly, in the spring, summer and winter periods of sowing, the yield of rump was 1.6; 1.1 and 1.3 t / ha. With a late sowing period, the yield of perennial grasses is significantly lower compared to spring and summer. With winter sowing periods, the yield was the highest for grass stands of alfalfa and alfalfacrust grass mixture - 2.3 and 2.4 t / ha. It should be noted that in the second year of use, the yield by the sowing dates in single-species crops and grass mixtures is leveled. The winter crops of perennial grasses in the first year of use formed a low yield. Only in the second year (third year of life) the productivity of perennial grasses of winter sowing began to increase. Consequently, in the area under perennial grasses of the winter sowing period, during one growing season (the next year after sowing), the crop was not actually formed. Based on the data obtained, production can be recommended for spring and summer planting of perennial grasses under the cover of barley. The winter sowing period provides economically valuable crop yields only by the third year of life.

Sign in / Sign up

Export Citation Format

Share Document