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1
Wheaton, T. Adair, Lawrence R. Parsons, and K. T. Morgan. "Simulating Annual Irrigation Requirement for Citrus on Excessively Drained Soils." HortScience 41, no. 6 (October 2006): 1487–92. http://dx.doi.org/10.21273/hortsci.41.6.1487.
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A water use simulation for citrus (Citrus sinensis) was used to estimate the effects of climate, soil-available water, rooting depth, allowable depletion of available water, and partial coverage irrigation on the annual irrigation requirements. The soil in the study was excessively drained Candler sand (hyperthermic, uncoated Typic Quartzipsamments) of the Central Florida Ridge. Variation of annual rainfall from 667 to 1827 mm had a relatively small impact on annual irrigation requirements. Soil-available water, depth of root zone, and allowable depletion of available water all affected irrigation management and the number of irrigations annually. Simulated annual irrigation requirements varied over a wide range depending on the allowable depletion of soil-available water, irrigation depth, and the fraction of the land area that is irrigated. Effective rain estimated by the TR21 method during months of high rainfall was higher than estimates by the water budget. Monthly irrigation requirements varied seasonally and peaked in normally dry spring months of April and May. The irrigation simulation is a useful tool for examining the range of management strategies that can be considered for citrus.
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Clemmens, A. J., and C. M. Burt. "Accuracy of Irrigation Efficiency Estimates." Journal of Irrigation and Drainage Engineering 123, no. 6 (November 1997): 443–53. http://dx.doi.org/10.1061/(asce)0733-9437(1997)123:6(443).
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ShalekBriski, Abby, B. Wade Brorsen, Jon T. Biermacher, Charles T. Rohla, and Will Chaney. "Effect of Irrigation Method on Tree Growth, Foliar Nutrient Levels, and Nut Characteristics of Young Pecan Trees in the Southern Great Plains." HortTechnology 29, no. 2 (April 2019): 109–13. http://dx.doi.org/10.21273/horttech04162-18.
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Although irrigation is a common practice in pecan (Carya illinoinensis) orchards, the effects of different methods of irrigation on young tree growth, nut quality, and nutrient uptake have not been estimated. Five irrigation systems and one nonirrigated control system were established. Tree performance was characterized by change in trunk diameter, weight per nut, average kernel percentage, and total trunk diameter growth. Nutrient uptake was determined by foliar levels. The five irrigation systems were a microsprinkler with a 35-ft diameter, a microsprinkler with a 70-ft diameter, two subsurface driplines irrigating for 2 days/week alternating between water for 2 hours and no water for 2 hours, two subsurface driplines irrigating 1 day/week for 20 hours continuously (LI2), and four subsurface driplines irrigating for 10 hours continuously for 1 day/week (LI4). Irrigation systems affected foliar levels of potassium (K), boron (B), and manganese (Mn) levels. Irrigation system did not affect change in trunk diameter or kernel percentage. A spatial Durbin error model was estimated to use trunk diameter estimates from all trees in the orchard. This model found the trunk diameters of nonirrigated and LI4 system trees to be significantly less than those trees that were irrigated by the LI2 system. When observations were pooled over all years, LI4 trees had individual pecan nut weights that were significantly less than all other systems.
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Pavione, D. M. S., R. K. X. Bastos, and P. D. Bevilacqua. "Quantitative microbial risk assessment applied to irrigation of salad crops with waste stabilization pond effluents." Water Science and Technology 67, no. 6 (March 1, 2013): 1208–15. http://dx.doi.org/10.2166/wst.2013.674.
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A quantitative microbial risk assessment model for estimating infection risks arising from consuming crops eaten raw that have been irrigated with effluents from stabilization ponds was constructed. A log-normal probability distribution function was fitted to a large database from a comprehensive monitoring of an experimental pond system to account for variability in Escherichia coli concentration in irrigation water. Crop contamination levels were estimated using predictive models derived from field experiments involving the irrigation of several crops with different effluent qualities. Data on daily intake of salad crops were obtained from a national survey in Brazil. Ten thousand-trial Monte Carlo simulations were used to estimate human health risks associated with the use of wastewater for irrigating low- and high-growing crops. The use of effluents containing 103–104E. coli per 100 ml resulted in median rotavirus infection risk of approximately 10−3 and 10−4 pppy when irrigating, respectively, low- and high-growing crops; the corresponding 95th percentile risk estimates were around 10−2 in both scenarios. Sensitivity analyses revealed that variations in effluent quality, in the assumed ratios of pathogens to E. coli, and in the reduction of pathogens between harvest and consumption had great impact upon risk estimates.
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Souto, Camilo, Octavio Lagos, Eduardo Holzapfel, Christopher Ruybal, David R. Bryla, and Gladys Vidal. "Evaluating a Surface Energy Balance Model for Partially Wetted Surfaces: Drip and Micro-Sprinkler Systems in Hazelnut Orchards (Corylus Avellana L.)." Water 14, no. 24 (December 8, 2022): 4011. http://dx.doi.org/10.3390/w14244011.
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A multi-layer surface energy balance model was previously developed to estimate crop transpiration (T) and soil evaporation (E) in orchards partially wet by micro-irrigation systems. The model, referred to as SEB-PW, estimates latent (λE), sensible (H), and soil heat fluxes (G) and separates actual evapotranspiration (ETa) into dry and wet soil E and crop T. The main goal of this work was to evaluate the ability of the SEB-PW model to estimate ETa and analyze the diurnal and seasonal dynamics of E and T in two hazelnut (Corylus avellana L.) orchards irrigated by drip or micro-sprinkler systems. The assessment showed that simulated hourly ET was highly correlated with estimates from nearby weather stations and with measurements from micro-lysimeters (MLs). Hourly ET estimates were evaluated by root-mean-square error (RMSE), mean absolute error (MAE), the Nash–Sutcliffe coefficient (NSE), and the index of agreement (da), which equaled 58.6 W m−2, 35.6 W m−2, 0.85, and 0.94, respectively. Daily E estimates were also evaluated and equaled 0.27 mm day−1, 0.21 mm day−1, 0.87, and 0.94, respectively, and obtained a coefficient of determination (r2) of 0.85 when compared to the measurements from the MLs. Within a day of irrigation, E accounted for 28 and 46% of ET. In accordance with the obtained results, the proposed SEB-PW model improves estimates of soil E by allowing the wetted and non-wetted areas to be estimated separately, which could be useful for optimizing irrigation methods and practices in hazelnut orchards.
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Norrie, J., M. E. D. Graham, P. A. Dubé, and A. Gosselin. "Improvements in Automatic Irrigation of Peat-grown Greenhouse Tomatoes." HortTechnology 4, no. 2 (April 1994): 154–59. http://dx.doi.org/10.21273/horttech.4.2.154.
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An automatic irrigation system was designed for use on green-house tomatoes growing in peat-based substrates. This system uses electronic tensiometers to monitor continuously substrate matric potential (SMP) in peat-bags. The system also uses the Penman equation to evaluate potential evapotranspiration (PET) through the acquisition of many greenhouse environmental parameters. Through a series of linear equations, estimates of PET are used in a computer-controller system to vary the electrical conductivity (EC) of irrigated nutrient solutions, as well as SMP setpoints at which irrigations are started. Such modifications to current irrigation management systems may improve fruit quality and reduce the risk of water stress during periods of high PET by irrigating more frequently with less-concentrated nutrient solutions. Conversely, during periods of low PET, irrigation is less frequent with more-concentrated nutrient solutions. Although no differences were found in fruit number or overall yield using variable nutrient solution EC, plant fresh weight was higher in those treatments. It is concluded that an integrated tensiometer-PET system may give increased precision to irrigation management and the control of crop growth in the greenhouse.
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Devitt, D. A., M. Berkowitz, P. J. Schulte, and R. L. Morris. "Estimating Transpiration for Three Woody Ornamental Tree Species using Stem-flow Gauges and Lysimetry." HortScience 28, no. 4 (April 1993): 320–22. http://dx.doi.org/10.21273/hortsci.28.4.320.
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We compared transpiration estimates of three common desert landscape tree species using stem-flow gauges and lysimetry. Argentine mesquite (Prosopis alba Grisebach), desert willow [Chilopsis linearis (cav.) Sweet var. linearis], and southern live oak (Quercus virginiana Mill., seedling selection) were subjected to three irrigation regimes. Leaching fractions of +0.25, 0.00, and -0.25 were imposed for 2 years. During the summer of the second year, we conducted a comparative transpiration study. Trees growing in 190-liter plastic containers had a highly linear correlation (r = 0.98, P = 0.001) between transpiration estimated by stem-flow gauges and lysimetry. An average 18% error was measured between paired data (total runs of 14 to 72.5 hours) of stem-flow gauge and lysimetry transpiration estimates. However, a lower error was correlated significantly with longer run times (r = -0.37, P = 0.05). Based on field measurements taken in this experiment, run times would have to be >68 hours to maintain an associated error below 10%. Higher cumulative transpiration also was associated with longer run times (r = 0.80, P = 0.001). These results suggest that the stem-flow gauge can be used to estimate transpiration accurately to schedule irrigation for woody ornamental trees in an arid environment, provided that irrigation predictions are not based on short-term stem-flow gauge estimates (<68 hours).
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Coelho, Eugênio Ferreira, Marcos de Souza Campos, Marcelo Rocha dos Santos, Rafael Dreux Miranda Fernandes, and Jailson Lopes Cruz. "Soil water-balance-based approach for estimating percolation with lysimeter and in field with and without mulch under micro irrigation." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 16, no. 5 (October 6, 2021): 1–12. http://dx.doi.org/10.4136/ambi-agua.2760.
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Precise, accurate knowledge of percolation is key to reliable determination of soil water balance and a crop’s water-use efficiency. This work evaluated an approach to estimate the amount of water percolated in the root zone using soil water content (SWC) data measured at different time intervals. The approach was based on the difference of soil water content within and below the effective root zone of banana plants at different time intervals. A drainage lysimeter was used to compare the measured and estimated percolation data. The approach was then used in a banana orchard under drip and micro sprinkler irrigation, with and without the use of mulch. The soil water storage in the banana’s root zone was evaluated within a two-dimensional soil profile with time domain reflectometry (TDR). Mean percolation measured in the lysimeters did not differ from the approach’s estimates using intervals between SWC readings equal to or longer than 6 h from the end of an irrigation event. Percolation estimates under drip and micro sprinkler irrigation in the field, with and without mulch, were consistent with those measured in the lysimeters, considering the 6-h interval of SWC measurements. Percolation was greater under the drip irrigation system with mulch. The amount of water percolated was not influenced by the presence of mulch under the micro sprinkler system.
Keywords: localized irrigation, soil water balance, soil water content sensor.
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Chiew, FHS, and TA Mcmahon. "Groundwater recharge from rainfall and irrigation in the campaspe river basin." Soil Research 29, no. 5 (1991): 651. http://dx.doi.org/10.1071/sr9910651.
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Reliable estimates of groundwater recharge are required for effective evaluation of management options for salinity control and high water-tables in the Riverine Plain of south-eastern Australia. This paper provides a brief description of the integrated surface and groundwater modelling approach used to estimate regional recharge rates and presents the recharge rates estimated for the Campaspe River Basin. The integrated model is a powerful management tool as it can predict the relationship between rainfall, irrigation, recharge and rises in the water-table levels. The model predicted that approximately 15% of irrigation water recharges the shallow aquifer. Approximately 6% of rainfall contributes to recharge in the irrigated areas while 4 to 5% of rainfall becomes recharge in the dryland areas. Rainfall makes a greater contribution in the irrigation areas compared to the dryland areas because irrigation predisposes the soil to recharge from rainfall. The water-table levels in the irrigation areas are currently rising at approximately 0.14 m yr-1. This rate of rise will increase faster than the increase in irrigation applications.
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Muchow, R. C., and B. A. Keating. "Assessing irrigation requirements in the Ord Sugar Industry using a simulation modelling approach." Australian Journal of Experimental Agriculture 38, no. 4 (1998): 345. http://dx.doi.org/10.1071/ea98023.
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Summary. Sustainable irrigation guidelines that maximise profitability and minimise water losses and accession to the watertable are required for the new Ord Sugar Industry. In addition, knowledge on crop water requirements is needed to guide water allocation and costing policies for the expanding Ord Irrigation Area where sugarcane is likely to be a dominant crop. Field data indicating water requirements for sugar in the Ord Irrigation Area are few and this paper deploys a modelling approach to extrapolate from knowledge of water requirements in other parts of the world. The approach links long-term climatic data with soil water characteristics of the main soil type, with a cropping systems model, to develop indicative estimates of irrigation water requirement and yield consequences for different management options for sugarcane production in the Ord. Analyses of the growth of 12-month old ratoon crops were conducted using the APSIM–Sugarcane model with historical climatic data from 1960 to 1985 and either a deep (188 mm available water to 160 cm depth) or shallow (144 mm of water to 120 cm depth) Cununurra clay soil. Under maximum attainable growth conditions where crops were irrigated after half the soil water supply was depleted, average sucrose yield ranged from 26.7 to 29.0 t/ha, and the irrigation requirement (assuming 100% application efficiency) ranged from 22.7 to 23.8 ML/ha depending on ratooning date. Soil water holding capacity had a major effect on the number of irrigations and the interval between irrigation for a given irrigation schedule but little effect on yield or irrigation requirement. Varying the irrigation schedule by changing the level of soil water depletion before irrigation and thus the irrigation frequency, showed the tradeoff between yield and irrigation requirement with the most profitable irrigation schedule depending on the price of sucrose and the cost of irrigation relative to other costs. Most of the year-to-year variation in irrigation water requirement could be explained by the highly variable effectiveness in soil storage of rainfall which ranged from 44 to 93%. This study has provided insight and indicative estimates of the yield and irrigation requirements for different irrigation management options for use in the establishment of an Ord River sugar industry. These estimates will be further refined as field data become available.
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van Dijk, Albert I. J. M., Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts. "Global 5 km resolution estimates of secondary evaporation including irrigation through satellite data assimilation." Hydrology and Earth System Sciences 22, no. 9 (September 27, 2018): 4959–80. http://dx.doi.org/10.5194/hess-22-4959-2018.
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Abstract. A portion of globally generated surface and groundwater resources evaporates from wetlands, waterbodies and irrigated areas. This secondary evaporation of “blue” water directly affects the remaining water resources available for ecosystems and human use. At the global scale, a lack of detailed water balance studies and direct observations limits our understanding of the magnitude and spatial and temporal distribution of secondary evaporation. Here, we propose a methodology to assimilate satellite-derived information into the landscape hydrological model W3 at an unprecedented 0.05∘, or ca. 5 km resolution globally. The assimilated data are all derived from MODIS observations, including surface water extent, surface albedo, vegetation cover, leaf area index, canopy conductance and land surface temperature (LST). The information from these products is imparted on the model in a simple but efficient manner, through a combination of direct insertion of the surface water extent, an evaporation flux adjustment based on LST and parameter nudging for the other observations. The resulting water balance estimates were evaluated against river basin discharge records and the water balance of closed basins and demonstrably improved water balance estimates compared to ignoring secondary evaporation (e.g., bias improved from +38 to +2 mm yr−1). The evaporation estimates derived from assimilation were combined with global mapping of irrigation crops to derive a minimum estimate of irrigation water requirements (I0), representative of optimal irrigation efficiency. Our I0 estimates were lower than published country-level estimates of irrigation water use produced by alternative estimation methods, for reasons that are discussed. We estimate that 16 % of globally generated water resources evaporate before reaching the oceans, enhancing total terrestrial evaporation by 6.1×1012 m3 yr−1 or 8.8 %. Of this volume, 5 % is evaporated from irrigation areas, 58 % from terrestrial waterbodies and 37 % from other surfaces. Model-data assimilation at even higher spatial resolutions can achieve a further reduction in uncertainty but will require more accurate and detailed mapping of surface water dynamics and areas equipped for irrigation.
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Vassallo, Robert, and Marco Dimech. "Irrigation-Water Demand in the Maltese Islands – A Comparative Study between CROPWAT Analysis and In-Situ Monitoring for Ten Horticulture Crops." MCAST Journal of Applied Research & Practice 3, no. 1 (May 15, 2019): 97–112. http://dx.doi.org/10.5604/01.3001.0014.4376.
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In Malta, freshwater resources are scarce and their availability and accessibility are likely to be further exacerbated as a result of changing climatic patterns and increased urbanization. The agriculture sector, namely the consequence of irrigation demand, is heavily dependent on freshwater, making use of private boreholes to extract freshwater from underground aquifers. Numerous studies and reports have attempted to quantify and estimate the water use by agriculture. However, there exists a great deal of variability in the reported estimates as well in the models themselves. This paper presents an up-to-date compilation of the current irrigation use models and datasets for the Maltese islands and provides a critical assessment of the main principles behind the methodologies used. In order to understand better the adequacy and suitability of current estimates, a series of field studies were carried out to monitor the irrigation use in ten horticulture crops and compared against evapotranspiration and irrigation demand modelling using CROPWAT analysis. Field studies have indicated that irrigation was applied with care and overall resulted in lower water consumption (44%) when compared to model-generated estimations. Our study indicates that water consumption for crop production on a national scale is significantly lower than previously reported estimates. For the first time, irrigation demand figures have been compiled on a crop-by-crop basis, based on both field data and CROPWAT estimates. This study leads the way for the inclusion of crop-specific parameterisation which can be implemented into future water demand models, thus minimizing the risk of parameter errors and uncertainty for national water-use estimations.
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Kannan, Narayanan, Sujoy B. Roy, John S. Rath, Carrie S. Munill, and Robert A. Goldstein. "Estimating Crop Consumption of Irrigation Water for the Conterminous U.S." Transactions of the ASABE 62, no. 4 (2019): 985–1002. http://dx.doi.org/10.13031/trans.13102.
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Abstract. Water consumption for crop irrigation is the largest single use of water in the U.S. but is poorly quantified because of limitations in data and the inherent challenges in measuring water consumption. In this study, water consumption for irrigated agriculture was estimated across the U.S. to improve understanding of water budgets in different regions. Published data on cropping patterns and water application were used in conjunction with a national-scale analysis to estimate water application and crop water consumption using the SWAT (Soil and Water Assessment Tool) watershed model. Crop water consumption estimates were based on evapotranspiration, with supporting information on the diversity of crops, irrigated area, water quantity and source, and local weather conditions. Quantification of water consumption supports broader analyses of the food-energy-water nexus and allows evaluation of the efficiency of irrigation water use at different spatial scales. Focusing on 2005 data, it is estimated that 60% of water reported as withdrawn from various sources is applied to fields, indicating a potentially large and poorly understood conveyance loss that occurs in a small number of states. Of the field-applied irrigation water, roughly 65% is directly used by crops or is lost in the field, with large regional variations. This may be compared to consumption estimates in prior studies that ranged from 16% to 90%. Areas that dominate the national aggregate estimate of crop water consumption include California’s Central and Imperial Valleys, areas overlying the Ogallala Aquifer in the central U.S., the Lower Colorado Basin, and the eastern part of the Pacific Northwest Basin. Keywords: Crop water use, Irrigated agriculture, SWAT, Watershed model, Water withdrawal.
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Dabney, S., and D. Yoder. "How Irrigation Affects Soil Erosion Estimates of RUSLE2." Agrociencia 19, no. 3 (December 2015): 12–17. http://dx.doi.org/10.31285/agro.19.246.
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RUSLE2 is a robust and computationally efficient conservation planning tool that estimates soil, climate, and land management effects on sheet and rill erosion and sediment delivery from hillslopes, and also estimates the size distribution and clay enrichment of sediment delivered to the channel system. In the U.S.A., RUSLE2 is supported by extensive databases maintained by the USDA-Natural Resources Conservation Service. Examples are presented of how input climate, soil and management descriptions might be built outside the U.S.A. using data from Uruguay. In addition to average annual erosion and sediment delivery, recent enhancements give RUSLE2 the ability to predict a representative runoff event sequence for a particular location, soil, management, and user-specified return period that can be coupled with a channel erosion and routing model.
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Woodforth, A., J. Triantafilis, J. Cupitt, R. S. Malik, R. Subasinghe, M. F. Ahmed, A. I. Huckel, and H. Geering. "Mapping estimated deep drainage in the lower Namoi Valley using a chloride mass balance model and EM34 data." GEOPHYSICS 77, no. 4 (July 1, 2012): WB245—WB256. http://dx.doi.org/10.1190/geo2011-0373.1.
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The Murray Darling Basin accounts for half of all water used for irrigation in Australia. However, improvements in water use efficiency (WUE) are required, owing to increasing demands on water (e.g., environmental flows). This requires data on the spatial distribution of soil-hydrological properties, such as deep drainage (DD). Measuring DD using lysimeters, although accurate, is site-specific. Alternatively, estimates are commonly made using chloride mass balance (CMB) models. Gaining this information across a large area is still problematic due to the prohibitive cost of drilling, sampling, and laboratory analysis. Ancillary data, obtained from electromagnetic (EM) instruments, have been used to add value to a limited number of DD estimates. We evaluated the use of a hierarchical spatial regression technique to map the estimated DD using a steady state CMB model coupled to EM34 measurements. We first compared a standard least squares and a stepwise multiple linear regression model. The former includes the use of EM34 signal data in the horizontal (EM34-10H, EM34-20H, and EM34-40H) and vertical (EM34-10V, EM34-20V, and EM34-40V) dipoles, as well as two trend surface variables (scaled easting and northing). The latter model only includes a statistically significant ancillary variable (EM34-10H) and a trend surface parameter (scaled northing), and we use this to estimate DD across the lower Namoi Valley. EM34 data available on a 1 km grid proved useful for mapping DD on a reconnaissance level, with the results closely related to the physiography. In particular, large DD estimates are associated with the prior stream channels. Conversely, smaller DD estimates characterize the agriculturally significant clay plain which is used extensively for irrigated cotton production. The map of estimated DD will allow improved siting of dams and irrigation fields, as well as indicate where more efficient cropping or irrigation systems can be implemented to increase WUE.
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Jensen, Kevin B., Blair L. Waldron, Joseph G. Robins, Thomas A. Monaco, and Michael D. Peel. "Breeding meadow bromegrass for forage characteristics under a line-source irrigation design." Canadian Journal of Plant Science 88, no. 4 (July 1, 2008): 695–703. http://dx.doi.org/10.4141/cjps07099.
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Production from less productive lands limited by irrigation can be increased if genetically improved pasture grasses are developed with increased dry matter production (DMY) and nutritional quality. In 2000, 18 half-sib families of meadow bromegrass were seeded in a modified strip-plot design with four replications and water levels (WL) applied as nonrandom strips ranging from 10.1 mm wk-1 at WL-5 to 36.8 mm wk-1 at WL-1. The objective was to estimate genetic variability and parameters as affected by irrigation level and harvest date for DMY, crude protein (CP), in vitro true digestibility (IVTD), neutral detergent fiber (NDF), and digestible neutral detergent fiber (dNDF). Low h2 estimates for DMY suggest that gains in total DMY from selection within these half-sib families (HSF) are not likely. Crude protein concentrations were more influenced by harvest date than WL. Heritability estimates were relatively high regardless of WL or harvest date for IVTD. The effect of WL on h2 estimates for NDF were less defined, suggesting that gains might be achieved faster if selection was done on forage harvested later in the growing season at less than optimum irrigation. Heritability estimates for dNDF were either small or associated with large standard errors. Key words: Heritability, irrigation rates, forage yield and quality, crude protein, neutral detergent fiber, in vitro true digestibility
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Sheet, Eman H., and Entesar M. Ghazal. "EFFECT OF GROUND WATERTABLE ONIRRIGATION SCHEDULING MODEL." Tikrit Journal of Engineering Sciences 12, no. 1 (March 31, 2005): 20–35. http://dx.doi.org/10.25130/tjes.12.1.03.
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An irrigation scheduling model was developed based on daily soil water balance which takes into account the effect of water table on irrigation water requirement for wheat crop at Mosul area for eleven years. Capillary rise of water table was estimated with Darcy's equation .Crop evapotranspiration was estimated by pan evaporation method. The model inputs are daily climatological data for eleven years at Mosul Station, soil data (total available water, field capacity, permanent wilting point, allowable percent depletion, saturated hydraulic conductivity),and crop data(root depth for wheat crop, crop coefficient).The model estimates daily and seasonal actual evapotranspiration, effective rainfall, irrigation requirement and upward capillary rise from water table. Using the model for wheat, the seasonal irrigation requirements were reduced by 40% for silt loam soil and 90% for loam soil ,avoiding crop water stress or excessive irrigation.
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Sheet, Eman H., and Entesar M. Ghazal. "Effect of Ground Water Table on Irrigation Scheduling Model." Tikrit Journal of Engineering Sciences 12, no. 3 (August 31, 2005): 20–35. http://dx.doi.org/10.25130/tjes.12.3.08.
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An irrigation scheduling model was developed based on daily soil water balance which takes into account the effect of water table on irrigation water requirement for wheat crop at Mosul area for eleven years. Capillary rise of water table was estimated with Darcy’s equation .Crop evapotranspiration was estimated by pan evaporation method. The model inputs are daily climatological data for eleven years at Mosul Station, soil data (total available water, field capacity, permanent wilting point, allowable percent depletion, saturated hydraulic conductivity),and crop data(root depth for wheat crop, crop coefficient).The model estimates daily and seasonal actual evapotranspiration, effective rainfall, irrigation requirement and upward capillary rise from water table. Using the model for wheat, the seasonal irrigation requirements were reduced by 40% for silt loam soil and 90% for loam soil ,avoiding crop water stress or excessive irrigation.
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Biemans, Hester, Christian Siderius, Ashok Mishra, and Bashir Ahmad. "Crop-specific seasonal estimates of irrigation-water demand in South Asia." Hydrology and Earth System Sciences 20, no. 5 (May 17, 2016): 1971–82. http://dx.doi.org/10.5194/hess-20-1971-2016.
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Abstract. Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight into these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation-water demand resulting from the typical practice of multiple cropping in South Asia was accounted for by introducing double cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest state-level statistics of India, Pakistan, Bangladesh and Nepal. The improvements in seasonal land use and cropping periods lead to lower estimates of irrigation-water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation-water demand differs sharply between seasons and regions; in Pakistan, winter (rabi) and monsoon summer (kharif) irrigation demands are almost equal, whereas in Bangladesh the rabi demand is ∼ 100 times higher. Moreover, the relative importance of irrigation supply versus rain decreases sharply from west to east. Given the size and importance of South Asia improved regional estimates of food production and its irrigation-water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple cropping and monsoon-dependent planting dates should not be ignored.
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Biemans, H., C. Siderius, A. Mishra, and B. Ahmad. "Crop-specific seasonal estimates of irrigation water demand in South Asia." Hydrology and Earth System Sciences Discussions 12, no. 8 (August 12, 2015): 7843–73. http://dx.doi.org/10.5194/hessd-12-7843-2015.
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Abstract. Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight in these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation water demand resulting from the typical practice of multiple-cropping in South Asia was accounted for by introducing double-cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest subnational statistics of India, Pakistan, Bangladesh and Nepal. The representation of seasonal land use and more accurate cropping periods lead to lower estimates of irrigation water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation water demand differs sharply between seasons and regions; in Pakistan, winter (Rabi) and summer (Kharif) irrigation demands are almost equal, whereas in Bangladesh the Rabi demand is ~ 100 times higher. Moreover, the relative importance of irrigation supply vs. rain decreases sharply from west to east. Given the size and importance of South Asia, improved regional estimates of food production and its irrigation water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple-cropping and monsoon-dependent planting dates should not be ignored.
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Adhikari, Sagar, Parth Mahapatra, Vikrant Sapkota, and Siva Puppala. "Characterizing Emissions from Agricultural Diesel Pumps in the Terai Region of Nepal." Atmosphere 10, no. 2 (February 1, 2019): 56. http://dx.doi.org/10.3390/atmos10020056.
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Diesel irrigation pumps are a source of air pollution in the Indo-Gangetic Plain (IGP). The environmental implications of these pumps are often overlooked and very rarely addressed in the IGP. Few studies in the past have estimated the amount of diesel consumed by irrigation pumps in the IGP or other proxy variables to estimate the amount of emissions. A considerable amount of uncertainty remains in calculating emission factors (EF) using real-time measurements. We measured pollutants from nine diesel irrigation pumps in the southern ‘Terai’ belt of Nepal. Fuel-based EF were then estimated using the carbon mass balance method. The average EF for fine particulate matter (PM2.5), CO2, CO and black carbon (BC) were found to be 22.11 ± 3.71, 2218.10 ± 26.8, 275 ± 17.18 and 2.54 ± 0.71 g/L, respectively. Depending upon the pump characteristics (age, design, make, hours used, etc.) and fuel mixtures, the EF of PM2.5, BC and CO had larger inter-variability. This study provides estimates for an under-represented source of ambient air pollution which will assist in the development of better emission inventories and informed policy making.
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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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Caron, Jean, Simon Bonin, Steeve Pepin, Leroy Kummer, Clay Vanderleest, and William L. Bland. "Determination of irrigation set points for cranberries from soil- and plant-based measurements." Canadian Journal of Soil Science 96, no. 1 (March 1, 2016): 37–50. http://dx.doi.org/10.1139/cjss-2015-0037.
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Cranberry production requires accurate irrigation management to optimize crop yield and reduce water use. However, irrigation guidelines for that crop are scarce and empirical. The objective of this study was to identify appropriate soil matric potential (ψ) irrigation set points for cranberry production. A three-step process was used to evaluate the set points. Crop water requirements were first evaluated in the field and, second, combined to soil physical properties with a hydrological model to estimate irrigation set points. Third, experimental measurements were carried out in a growth cabinet and in the field to validate the set point estimates from independent observations. Irrigation set point estimates obtained from yield response curves, photosynthesis and transpiration measurements, and soil physical properties were all consistent and suggest that soil matric potential be maintained between −4.0 and −7.0 kPa to ensure an adequate water supply to the crop and optimal fruit yield. Yield responses suggest that cranberries are highly sensitive to small changes in soil matric potential, showing differences of about 20 000 kg ha−1 when outside of the −4.0 to −7.0 range, with a maximum yield between 35 000 and 40 000 kg ha−1, depending on the site.
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Akoko, George, Tasuku Kato, and Le Hoang Tu. "Evaluation of Irrigation Water Resources Availability and Climate Change Impacts—A Case Study of Mwea Irrigation Scheme, Kenya." Water 12, no. 9 (August 19, 2020): 2330. http://dx.doi.org/10.3390/w12092330.
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Rice is an important cereal crop in Kenya, where it is mainly grown in the Mwea Irrigation Scheme, MIS. The serious challenges of MIS include low water use efficiency and limited available water resources. The objective of this study is to analyze the current and future irrigation water resource availability for the improvement of future water management. A Soil Water Assessment Tool (SWAT), a public domain software supported by the United States Department of Agriculture’s Agricultural Research Service in Bushland, TX, USA, was used to estimate the current and future water resources availability from the MIS’s main irrigation water supply sources (River Thiba and River Nyamindi). CropWat, a computer program developed by the Land and Water Division of the Food and Agriculture Organization (FAO), Rome, Italy, was used to estimate irrigation water requirements from 2013–2016 and into the future (2020–2060 and 2061–2099). Future climatic data for total available flow and irrigation requirement estimations were downloaded from three General Circulation Models (GCMs). The data was bias corrected and down-scaled (with observed data) using a Climate Change Toolkit, a toolkit for climate change analysis developed by the Water Weather and Energy Ecosystem, Zurich, Switzerland. The results indicated that the highest irrigation water deficits were experienced in July and August based on the existing cropping pattern. Under a proposed future pattern, estimates show that MIS will experience water deficits mainly from June to October and from January to February. This study recommends that MIS management should put into strong consideration the simulated future estimates in irrigation water availability for the improvement of water management.
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Kelley, Jason, Dalyn McCauley, G. Aaron Alexander, Wilton F. Gray, Rylie Siegfried, and Holly J. Oldroyd. "Using Machine Learning to Integrate On-Farm Sensors and Agro-Meteorology Networks into Site-Specific Decision Support." Transactions of the ASABE 63, no. 5 (2020): 1427–39. http://dx.doi.org/10.13031/trans.13917.
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HighlightsMachine learning can incorporate a variety of data from low-cost sensors and estimate actual ET by comparison with short-term, higher-cost measurements.On-farm weather monitoring can be leveraged to estimate site-specific crop-water requirements.Expanding spatial coverage of weather and actual ET through on-farm monitoring will facilitate localization and leverage publicly available weather data to guide irrigation decisions and improve irrigation water management.Abstract. One of the basic challenges to adopting science-based irrigation scheduling is providing reliable, site-specific estimates of actual crop water demand. While agro-meteorology networks cover most agricultural production areas in the U.S., widely spaced stations represent regionally specific, rather than site-specific, conditions. A variety of low to moderate cost commercial weather stations are available but do not provide directly useful information, such as actual evapotranspiration (ETa), or the ability to incorporate additional sensors. We demonstrate that machine learning methods can provide real-time, site-specific information about ETa and crop water demand using on-farm sensors and public weather information. Two years of field experiments were conducted at four irrigated field sites with crops including snap beans, alfalfa, and pasture. On-farm data were compared to publicly available data originating at nearby agro-meteorology network stations. The machine learning procedure can robustly estimate ETa using data from a few basic sensors, but the resulting estimate is sensitive to the range of conditions that are used as training data. The results demonstrate that machine learning can be used with affordable sensors and publicly available data to improve local estimates of crop water demand when high-quality measurements can be co-located for short periods of time. Supplementary sensors can also be integrated into a tailored monitoring plan to estimate crop stress and other operational considerations. Keywords: Agro-meteorology, Irrigation requirement, Machine learning, Site-specific Irrigation.
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Fernandes, Rafael Dreux Miranda, Jefferson vieira José, Wagner Wolff, Jéfferson de oliveira Costa, and Marcos Vinícius Folegatti. "PROBABILITY DISTRIBUTION FUNCTIONS APPLIED IN THE WATER REQUIREMENT ESTIMATES IN IRRIGATION PROJECTS." Revista Caatinga 32, no. 1 (March 2019): 189–99. http://dx.doi.org/10.1590/1983-21252019v32n119rc.
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ABSTRACT Spain contains a third the entire irrigated area of Europe, accounting for 15% of the cultivated area of the country and almost 60% of the national agricultural production. Knowledge of the spatial and temporal variability of reference evapotranspiration (ETo) and the probabilistic theory of extreme events is crucial for the elaboration of sustainable irrigation projects. The objective of this work was to define the frequency distribution that best describes ETo for the design of irrigation systems in the region of Andalusia. We used ETo data for the period 2001 to 2015 from 56 meteorological stations. The values were accumulated over three consecutive days. For all accumulated periods, nine probability distributions were adjusted. The probability distribution that best described ETo for the design of irrigation systems in the region was the Gumbel II distribution. The maximum daily ETo to be considered in irrigation projects in this region is, on average, 10 mm. The accumulated ETo for periods of 5, 10, and 30 days that should be considered are, on average, 42 mm, 78, mm and 224 mm, respectively.
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OMAR, MH, and AM MEHANNA. "Comparison of measured and estimated crop evapotranspiration over Egypt." MAUSAM 37, no. 2 (April 11, 2022): 153–58. http://dx.doi.org/10.54302/mausam.v37i2.2216.
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Mehanna (1976) estimated potential evapotranspiration (PE) for a number of meteorological stations in Egypt, using Penman's method with adjustment of the constants of the radiation term and the aerodynamic term, such that they would agree with measurements of radiation in Egypt and with estimates by Omar ( 1971) of PE in a large field at Giza. Omar and Mehanna (1984) compared seasonal measurements of PE at Bahtim (near Cairo) using potential evapotranspirometers with Mehanna's estimates of PE at Bahtim and with estimates by the methods given in the FAO Irrigation and Drainage Paper No.24 on "Crop Water Requirements” by Doorenbos and Pruitt (1977). The main features of the comparisons were that Mehanna, and three of thc FAO estimates (Blanev-Cridd1e, radiation, and pan evaporation) are within +- 10% of the measurements while the Penman estimate was 15% higher.
Mehanna's estimates of FE were used to calculite ET- crop (as -defined in 1he FAO paper) for 4 main crops in Egypt [cotton, maize, wheat and berseem (cover] at 9 meteorological stations, using crop coefficients given in the FAO paper. The estimated ET crop values- at meteorological stations enabled to calculate ET crop at a number of agricultural research stations. Estimates of ET crop were compared with measurements of crop evapotranspiration in conditions--similar-to those of ET crop, and also with measurements in all conditions including those of ET crop. The average ratio, for the four crops, of measured to estimated evapotranspiration was 0.95 and 0.80 respectively. Average ratios were also given corresponding to cases when the FAO Blaney.Criddle,' radiation and Penman methods were used to estimate PE. It is concluded that the comparisons may probably confirm the reliability of applying Mehanna's estimates of PE to the crop coefficients given in the FAO paper to estimate ET crop over Egypt.
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Ao, Xiangyu, C. S. B. Grimmond, H. C. Ward, A. M. Gabey, Jianguo Tan, Xiu-Qun Yang, Dongwei Liu, Xing Zhi, Hongya Liu, and Ning Zhang. "Evaluation of the Surface Urban Energy and Water Balance Scheme (SUEWS) at a Dense Urban Site in Shanghai: Sensitivity to Anthropogenic Heat and Irrigation." Journal of Hydrometeorology 19, no. 12 (December 1, 2018): 1983–2005. http://dx.doi.org/10.1175/jhm-d-18-0057.1.
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Abstract The Surface Urban Energy and Water Balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux QF and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of QF are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data, and dynamic population density. The QF is estimated to be largest in summer (mean daily peak 236 W m−2). When QF is omitted, the SUEWS sensible heat flux QH reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When QF is included, the QH estimates are improved in spring, summer, and autumn but are poorer in winter, indicating winter QF is overestimated. Inclusion of QF has little influence on the simulated latent heat flux QE but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on QE. When irrigation is not considered, the simulated QE is underestimated for all seasons. The mean summer daytime QE is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly outdoor water use. This study highlights the importance of appropriately including QF and irrigation in urban land surface models—terms not generally considered in many previous studies.
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Marek, Thomas Henry, Dana Porter, Terry A. Howell, Gary W. Marek, and David Brauer. "The Impact and Value of Accurate Evapotranspiration Networks in Texas High Plains Production Agriculture." Applied Engineering in Agriculture 36, no. 4 (2020): 451–55. http://dx.doi.org/10.13031/aea.13913.
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Highlights Irrigation scheduling using accurate ET network data can conserve energy and water. ET networks can be a valuable, cost effective, and feasible management tool in water policy. The Texas High Plains ET Network saved irrigated producers an estimated $US 22M dollars annually. ET network benefits and use extend beyond the agricultural sector. Abstract . Evapotranspiration (ET) networks have been developed and used to support weather and related ET information needs of U.S. agricultural production for nearly half a century, but many networks have been affected by inherent problems associated with sustaining operations. Consequently, these challenges have led to the discontinuation of network service in many cases. Most ET networks have been impacted by inadequate financial support compounded by inadequate public awareness and understanding of their usefulness and value in irrigation management, water conservation and water planning, and policy activities. Data accuracy is vital to usefulness, yet network data quality is often degraded when limited resources result in reduced equipment maintenance and data QA/QC. A discussion of ET network requirements and associated costs is presented. Estimates of the value and pumping reduction using the Texas High Plains ET networks are presented documenting the improvements of crop water use estimates and the impact associated with these improvements on irrigation groundwater withdrawal. Keywords: ET network, Evapotranspiration network, Irrigation scheduling, Irrigation value, Water management tools, Water savings.
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Jägermeyr, J., D. Gerten, J. Heinke, S. Schaphoff, M. Kummu, and W. Lucht. "Water savings potentials of irrigation systems: global simulation of processes and linkages." Hydrology and Earth System Sciences 19, no. 7 (July 10, 2015): 3073–91. http://dx.doi.org/10.5194/hess-19-3073-2015.
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Abstract. Global agricultural production is heavily sustained by irrigation, but irrigation system efficiencies are often surprisingly low. However, our knowledge of irrigation efficiencies is mostly confined to rough indicative estimates for countries or regions that do not account for spatiotemporal heterogeneity due to climate and other biophysical dependencies. To allow for refined estimates of global agricultural water use, and of water saving and water productivity potentials constrained by biophysical processes and also non-trivial downstream effects, we incorporated a process-based representation of the three major irrigation systems (surface, sprinkler, and drip) into a bio- and agrosphere model, LPJmL. Based on this enhanced model we provide a gridded world map of irrigation efficiencies that are calculated in direct linkage to differences in system types, crop types, climatic and hydrologic conditions, and overall crop management. We find pronounced regional patterns in beneficial irrigation efficiency (a refined irrigation efficiency indicator accounting for crop-productive water consumption only), due to differences in these features, with the lowest values (< 30 %) in south Asia and sub-Saharan Africa and the highest values (> 60 %) in Europe and North America. We arrive at an estimate of global irrigation water withdrawal of 2469 km3 (2004–2009 average); irrigation water consumption is calculated to be 1257 km3, of which 608 km3 are non-beneficially consumed, i.e., lost through evaporation, interception, and conveyance. Replacing surface systems by sprinkler or drip systems could, on average across the world's river basins, reduce the non-beneficial consumption at river basin level by 54 and 76 %, respectively, while maintaining the current level of crop yields. Accordingly, crop water productivity would increase by 9 and 15 %, respectively, and by much more in specific regions such as in the Indus basin. This study significantly advances the global quantification of irrigation systems while providing a framework for assessing potential future transitions in these systems. In this paper, presented opportunities associated with irrigation improvements are significant and suggest that they should be considered an important means on the way to sustainable food security.
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Jägermeyr, J., D. Gerten, J. Heinke, S. Schaphoff, M. Kummu, and W. Lucht. "Water savings potentials of irrigation systems: dynamic global simulation." Hydrology and Earth System Sciences Discussions 12, no. 4 (April 1, 2015): 3593–644. http://dx.doi.org/10.5194/hessd-12-3593-2015.
Full textAbstract:
Abstract. Global agricultural production is heavily sustained by irrigation, but irrigation system efficiencies are often surprisingly low. However, our knowledge of irrigation efficiencies is mostly confined to rough indicative estimates for countries or regions that do not account for spatio-temporal heterogeneity due to climate and other biophysical dependencies. To allow for refined estimates of global agricultural water use, and of water saving and water productivity potentials constrained by biophysical processes and also non-trivial downstream effects, we incorporated a dynamic representation of the three major irrigation systems (surface, sprinkler, and drip) into a process-based bio- and agrosphere model, LPJmL. Based on this enhanced model we provide a gridded worldmap of dynamically retrieved irrigation efficiencies reflecting differences in system types, crop types, climatic and hydrologic conditions, and overall crop management. We find pronounced regional patterns in beneficial irrigation efficiency (a refined irrigation efficiency indicator accounting for crop-productive water consumption only), due to differences in these features, with lowest values (< 30%) in South Asia and Sub-Saharan Africa and highest values (> 60%) in Europe and North America. We arrive at an estimate of global irrigation water withdrawal of 2396 km3 (2004–2009 average); irrigation water consumption is calculated to be 1212 km3, of which 511 km3 are non-beneficially consumed, i.e. lost through evaporation, interception, and conveyance. Replacing surface systems by sprinkler or drip systems could, on average across the world's river basins, reduce the non-beneficial consumption at river basin level by 54 and 76%, respectively, while maintaining the current level of crop yields. Accordingly, crop water productivity would increase by 9 and 15%, respectively, and by much more in specific regions such as in the Indus basin. This study significantly advances the global quantification of irrigation systems while providing a framework for assessing potential future transitions in these systems. Here presented opportunities associated with irrigation improvements are significant and suggest that they should be considered an important means on the way to sustainable food security.
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Colombo, Alberto, Lívia A. Alvarenga, Myriane S. Scalco, Randal C. Ribeiro, and Giselle F. Abreu. "Water storage in wetted strips under irrigated coffee trees with different criteria of irrigation management." Engenharia Agrícola 33, no. 2 (April 2013): 249–57. http://dx.doi.org/10.1590/s0100-69162013000200004.
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The increasing demand for water resources accentuates the need to reduce water waste through a more appropriate irrigation management. In the particular case of irrigated coffee planting, which in recent years presented growth with the predominance of drip irrigation, the improvement of drip irrigation management techniques is a necessity. The proper management of drip irrigation depends on the knowledge of the spatial pattern of soil moisture distribution inside the wetted strip formed under the irrigation lines. In this study, grids of 24 tensiometers were used to determine the water storage within the wetted strip formed under drippers, with a 3.78 L h-1 discharge, evenly spaced by 0.4 m, subjected to two different management criteria (fixed irrigation interval and 60 kPa tension). Estimates of storage based on a one-dimensional analysis, that only considers depth variations, were compared with two-dimensional estimates. The results indicate that for high-frequency irrigation the one-dimensional analysis is not appropriate. However, under less frequent irrigation, the two-dimensional analysis is dispensable, being the one-dimensional sufficient for calculating the water volume stored in the wetted strip.
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Jiang, Hongfei, Jack D. Fry, and Steve C. Wiest. "Variability in Turfgrass Water Requirements on a Golf Course." HortScience 33, no. 4 (July 1998): 689–91. http://dx.doi.org/10.21273/hortsci.33.4.689.
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Microclimates can vary significantly across a golf course, and directly influence turf irrigation requirements. The objective of this study was to quantify the extent of this variability in water demand, and evaluate the accuracy of weather station—generated evapotranspiration (ET) estimates for determining irrigation need for one Kansas golf course. Evaporation was measured using black Bellani plate atmometers placed on four golf tees and near the weather station at the Manhattan Country Club, Manhattan, Kans., in 1995 and 1996. Evaporation was measured On a total of 62 precipitation-free summer days in 1995 and 1996. Probably because the weather station was situated over nonirrigated turf, evaporation at the weather station was up to 22% higher than that at locations on tees. Evaporation varied by >20% among tees. Evaporation on a north-facing slope was 8% lower than that on a level surface or south-facing slope. Weather station—estimated empirical ET (Penman model) was consistently higher than ET estimated from atmometer evaporation, particularly when ET was >4 mm·day-1. Superintendents should be aware of the potential variability in water demand across a golf course, and that weather-station ET estimates may differ from turf ET primarily because of microclimatic differences and potential inaccuracies in the empirical model employed by the weather station to estimate turf ET.
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Anderson, R. G., M. H. Lo, S. Swenson, J. S. Famiglietti, Q. Tang, T. H. Skaggs, Y. H. Lin, and R. J. Wu. "Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models." Geoscientific Model Development 8, no. 10 (October 2, 2015): 3021–31. http://dx.doi.org/10.5194/gmd-8-3021-2015.
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Abstract. Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and a lack of conservation of water volume for models using a prescribed soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) compared to ET from a suite of land surface models without irrigation. We then incorporate the irrigation flux into the Community Land Model (CLM) and use a systematic trial-and-error procedure to determine the ground- and surface-water withdrawals that are necessary to balance the new irrigation flux. The resulting CLM simulation with irrigation produces ET that matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month−1 and a correlation of 0.95. Differences between the new CLM ET values and satellite-observed ET values are always less than 30 mm month−1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.
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Ramos, Tiago B., Lucian Simionesei, Ana R. Oliveira, Ramiro Neves, and Hanaa Darouich. "Exploring the Use of Vegetation Indices for Validating Crop Transpiration Fluxes Computed with the MOHID-Land Model. Application to Vineyard." Agronomy 11, no. 6 (June 17, 2021): 1228. http://dx.doi.org/10.3390/agronomy11061228.
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The success of an irrigation decision support system (DSS) much depends on the reliability of the information provided to farmers. Remote sensing data can expectably help validate that information at the field scale. In this study, the MOHID-Land model, the core engine of the IrrigaSys DSS, was used to simulate the soil water balance in an irrigated vineyard located in southern Portugal during three growing seasons. Modeled actual basal crop coefficients and transpiration rates were then compared with the corresponding estimates derived from the normalized difference vegetation index (NDVI) computed from Sentinel-2 imagery. On one hand, the hydrological model was able to successfully estimate the soil water balance during the monitored seasons, exposing the need for improved irrigation schedules to minimize percolation losses. On the other hand, remote sensing products found correspondence with model outputs despite the conceptual differences between both approaches. With the necessary precautions, those products can be used to complement the information provided to farmers for irrigation of vine crop, further contributing to the regular validation of model estimates in the absence of field datasets.
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Dari, Jacopo, Luca Brocca, Pere Quintana-Seguí, María José Escorihuela, Vivien Stefan, and Renato Morbidelli. "Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region." Remote Sensing 12, no. 16 (August 12, 2020): 2593. http://dx.doi.org/10.3390/rs12162593.
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Despite irrigation being one of the main sources of anthropogenic water consumption, detailed information about water amounts destined for this purpose are often lacking worldwide. In this study, a methodology which can be used to estimate irrigation amounts over a pilot area in Spain by exploiting remotely sensed soil moisture is proposed. Two high-resolution DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled soil moisture products have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) at 1 km. The irrigation estimates have been obtained through the SM2RAIN algorithm, in which the evapotranspiration term has been improved to adequately reproduce the crop evapotranspiration over irrigated areas according to the FAO (Food and Agriculture Organization) model. The experiment exploiting the SMAP data at 1 km represents the main work analyzed in this study and covered the period from January 2016 to September 2017. The experiment with the SMOS data at 1 km, for which a longer time series is available, allowed the irrigation estimates to be extended back to 2011. For both of the experiments carried out, the proposed method performed well in reproducing the magnitudes of the irrigation amounts that actually occurred in four of the five pilot irrigation districts. The SMAP experiment, for which a more detailed analysis was performed, also provided satisfactory results in representing the spatial distribution and the timing of the irrigation events. In addition, the investigation into which term of the SM2RAIN algorithm plays the leading role in determining the amount of water entering into the soil highlights the importance of correct representation of the evapotranspiration process.
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Savige, C. L., A. N. French, A. W. Western, J. P. Walker, M. Abuzar, J. M. Hacker, and J. D. Kalma. "Remote sensing estimates of actual evapotranspiration in an irrigation district." Australasian Journal of Water Resources 10, no. 2 (January 2006): 207–12. http://dx.doi.org/10.1080/13241583.2006.11465293.
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Short, D. C., and T. D. Colmer. "Development and use of a variable-speed lateral boom irrigation system to define water requirements of 11 turfgrass genotypes under field conditions." Australian Journal of Experimental Agriculture 47, no. 1 (2007): 86. http://dx.doi.org/10.1071/ea05157.
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Improved irrigation scheduling is one strategy by which water management can be improved in turfgrass systems. The development and testing of a variable-speed lateral boom irrigation system for use in field-based irrigation trials is reported. Christiansen’s coefficient of uniformity was greater than 92% and the efficiency of irrigator discharge was greater than 90% for application depths (mm/unit land area) of 0.5–13 mm. The minimum irrigation requirements were determined for 11 turfgrass genotypes from a summer irrigation dose–response field trial that applied daily treatments of 100 (control), 80, 60, 40 and 20% of the previous day’s net evaporation measured using a US Class A pan. Responses of several shoot parameters, including clipping production, green leaf area index, leaf chlorophyll and leaf water status were evaluated to define minimum irrigation requirements for the turfgrasses. Minimum irrigation requirements (as defined by declines of 10% in several shoot responses) for C3 and C4 turfgrasses were 64–94% and 32–78% of US Class A pan, respectively. Variability in irrigation requirements within C3 or C4 types was due mainly to variations in estimates based on the different shoot parameters. The results demonstrate the opportunity for water conservation by using C4 rather than C3 turfgrasses in locations with hot dry summers (and mild winters) typical of a Mediterranean-type climate.
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Banerjee, Swagata “Ban”, Irfan Y. Tareen, Lewell F. Gunter, Jimmy Bramblett, and Michael E. Wetzstein. "Forecasting Irrigation Water Demand: A Case Study on the Flint River Basin in Georgia." Journal of Agricultural and Applied Economics 39, no. 3 (December 2007): 641–55. http://dx.doi.org/10.1017/s1074070800023324.
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Southeast drought conditions have accentuated the demand for irrigation in the face of restricted water supply. For allocating this supply, Georgia held an auction for withdrawing irrigated acreage. This auction withdrew 33,000 acres from irrigation, resulting in a physical estimate of a 399 acre-feet daily increase in water flow. The actual reduction is driven by crop distributional changes on the basis of economic substitution and expansion effects. In contrast to the physical estimates, an econometric model that considers these effects is developed. The differences between the physical and econometric models result in an increase in the estimate of water savings of around 19% to 24%.
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Robinson, John R. C., Ari M. Michelsen, and Noel R. Gollehon. "Mitigating water shortages in a multiple risk environment." Water Policy 12, no. 1 (November 1, 2009): 114–28. http://dx.doi.org/10.2166/wp.2009.099.
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This paper estimates the economic value of irrigation water shortfalls and mitigation responses of farmers in the Lower Rio Grande Valley of Texas. The water shortage levels closely correspond to supply shortfalls experienced by the U.S. during the 1990s when Mexico fell behind on treaty delivery obligations. We identify and evaluate a range of crop choices, appropriate irrigation technology use, water source substitution, and other mitigation strategies used by farmers to deal with water shortages. The effects of exogenous crop price and yield risk, as well as other structural considerations are incorporated in the estimation of the marginal value of irrigation water. Results show that South Texas farmers react to risk by diversifying their crop mix, with implications for the imputed value of water and soil resources. The inclusion of exogenous risk refines the prediction of what decision makers would have grown assuming strict Mexican treaty compliance. The resulting marginal values reflect grower adjustments for risk using crop mix, irrigation level, and irrigation technology. The aggregate damage estimates using this approach are realistically smaller than previous damage estimates that were based on fixed cropping patterns and average water values.
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Montoya, Francisco, Juan M. Sánchez, José González-Piqueras, and Ramón López-Urrea. "Is the Subsurface Drip the Most Sustainable Irrigation System for Almond Orchards in Water-Scarce Areas?" Agronomy 12, no. 8 (July 28, 2022): 1778. http://dx.doi.org/10.3390/agronomy12081778.
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The expansion of irrigated almond orchards in arid and semi-arid areas with scarce water available raises key issues related to the sustainability of the water resources. A 3-year field experiment was conducted on a commercial young almond orchard located in the southeast of Spain to study the effect of two drip irrigation systems (surface, DI and subsurface, SDI) on almond crop growth and their physiological responses under fully-irrigated conditions. Crop evapotranspiration (ETc) and its components (crop transpiration, Tc and soil evaporation, Es) were monitored as well as the irrigation water and nitrogen productivities. To estimate ETc, a simplified two-source energy balance (STSEB) approach was used. Although a lower irrigation water amount was applied in SDI compared to DI (differences between 10% and 13.8%), the almond crop growth and physiological responses as well as the yield components and kernel yield showed no significant differences. The ETc estimates resulted in small differences for spring and fall periods (0.1–0.2 mm day−1) for both treatments, while differences were significant during higher ETo periods (May–August), being 1.0–1.3 mm day−1 higher for the DI treatment than for the SDI treatment. The irrigation water productivity (IWP) was significantly higher in the SDI treatment than in the DI treatment. However, no significant differences between the two treatments were observed for nitrogen productivity. It can be concluded that the SDI system is a suitable strategy for irrigating almond crops, reducing consumptive water use and increasing IWP.
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Bird, TL, TM Willis, and GJ Melville. "Subsoil hydraulic conductivity estimates for the Lower Macquarie Valley." Soil Research 34, no. 2 (1996): 213. http://dx.doi.org/10.1071/sr9960213.
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Field saturated hydraulic conductivity was measured in situ, at two depths in the B horizon, on irrigated soils in the Lower Macquarie Valley. Measurements were made with constant head well permeameters, using the single-head method, and water of moderate sodicity and high salinity. The hydraulic conductivity data were log-normally distributed for all soil groups and there were significant differences between some of these soil groups in mean hydraulic conductivity. Three soils exhibited significant differences in mean hydraulic conductivity between depths. Hydraulic conductivity measurements ranged up to 3 orders of magnitude within a soil. Variation in hydraulic conductivity estimates, both between and within soil groups, confirmed the variation observed in previous predictions of deep drainage, which were obtained using a semi-empirical model. A cluster analysis on hydraulic conductivity indicated that similar morphological soil properties did not necessarily reflect similar hydrologic properties. There was a strong relationship between hydraulic conductivity and exchangeable sodium percentage (ESP), hydraulic conductivity and clay content, and ESP and clay content. A model was developed to predict field saturated hydraulic conductivity from ESP and clay content data. Hydraulic conductivity measured in this study may not have been representative of percolation rates which would occur with low salinity irrigation water, but can be used to assess the risk of recharge from irrigation on different soils in the lower Macquarie Valley. Shallow watertables may potentially develop when the application of irrigation water greatly exceeds crop water requirements. Quantification of groundwater recharge will allow the likelihood of shallow watertable development in the Lower Macquarie Valley to be assessed.
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Ells, James E., E. Gordon Kruse, and Ann E. McSay. "Scheduling Irrigations for Cucumbers." HortScience 24, no. 3 (June 1989): 448–52. http://dx.doi.org/10.21273/hortsci.24.3.448.
Full textAbstract:
Abstract Cucumber (Cucumis sativus L.) irrigation scheduling was studied during the 4 years of 1983-1986. Tensiometers were used during the first year to determine when to irrigate, and the USDA irrigation scheduling program was used to determine the amount of water to apply. The data from the first year’s study indicated that the plants had not been stressed; therefore, the following year, estimates of the available water depletion were made with the USDA irrigation scheduling program, with tensiometers used only for comparison. After 4 years of study, we concluded that the best combination of high yield, high water use efficiency, and fewest number of irrigations was obtained if cucumbers were irrigated when the original scheduling program determined that 40% of the available water was depleted, applying only 70% of the water that the program indicated was required. This signaled that the program was overestimating the rate at which water was being depleted. Therefore, as a final step, a revised set of cucumber coefficients that approximated daily evapotranspiration (ET) more closely was determined. When using the revised coefficients, cucumbers should receive the exact amount of water called for by the irrigation program.
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Anderson, R. G., M. H. Lo, S. Swenson, J. S. Famiglietti, Q. Tang, T. H. Skaggs, Y. H. Lin, and R. J. Wu. "Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models." Geoscientific Model Development Discussions 8, no. 4 (April 29, 2015): 3565–92. http://dx.doi.org/10.5194/gmdd-8-3565-2015.
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Abstract. Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and conservation of water volume for soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) against ET from a suite of land surface models without irrigation. We then apply this water flux into the Community Land Model (CLM) and use an iterative approach to estimate groundwater recharge and partition the water flux between groundwater and surface water. The ET simulated by CLM with irrigation matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month−1 and a correlation of 0.95. Differences between the new CLM ET values and observed ET values are always less than 30 mm month−1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.
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Mila, Asimina L., and Themis J. Michailides. "Use of Bayesian Methods to Improve Prediction of Panicle and Shoot Blight Severity of Pistachio in California." Phytopathology® 96, no. 10 (October 2006): 1142–47. http://dx.doi.org/10.1094/phyto-96-1142.
Full textAbstract:
Panicle and shoot blight, caused by a Fusicoccum sp., is one of the major aboveground diseases of pistachio in California. The effects of temperature, number of continuous rainy days in April and May, irrigation system, and incidence of latent infection of the Fusicoccum sp. on severity of panicle and shoot blight of pistachio leaves and fruit have been quantified previously, using data collected from 1999 through 2001. A predictive model for leaves and another model for fruit with good explanatory power were generated. In 2003 and 2004, newly collected data were used to evaluate the two models with non-Bayesian and Bayesian methods. The 95% credible (i.e., confidence) intervals of initial (before modification with non-Bayesian and Bayesian methods) and updated parameter estimates were used to investigate their prognostic validity. In 2003, the non-Bayesian analysis resulted in all parameter estimates, with the exception of cumulative daily mean temperature from 1 June until harvest, having different 95% confidence intervals than the parameter estimates of the original models. In addition, the parameter estimates for drip irrigation for the leaf infection and the parameter estimates for drip irrigation and number of continuous rainy days in April and May for fruit infection were not statistically significant. With Bayesian methods, the reestimated model parameters had overlapping 95% credible intervals with the initial estimated parameters, except for the number of continuous rainy days in April and May. When the two sets of modified parameter estimates were used to predict disease severity, statistically significant (α = 0.05) differences between observed and predicted disease severities were found with non-Bayesian analysis for leaf infection in three locations and with Bayesian analysis for fruit infection in one orchard. The parameter estimates were modified again at the end of the 2004 season and were all statistically significant with both non-Bayesian and Bayesian methods. Both sets of parameter estimates gave predictions that were not significantly different from observed disease severity on leaves and fruit in all monitored orchards in 2004. In summary, Bayesian methods gave more consistent results when used to update parameter estimates with new information and yielded predictions not statistically different from observed disease severity in more cases than the non-Bayesian analysis.
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Rolle, Matteo, Stefania Tamea, and Pierluigi Claps. "ERA5-based global assessment of irrigation requirement and validation." PLOS ONE 16, no. 4 (April 30, 2021): e0250979. http://dx.doi.org/10.1371/journal.pone.0250979.
Full textAbstract:
While only 20% of harvested lands are actually irrigated, 40% of global agricultural production originates from irrigated areas. Therefore, assessing irrigation requirements is essential for the development of effective water-related policies for an efficient management of water resources. Moreover, global-scale analyses are becoming increasingly relevant, motivated by globalized production and international trade of food as well as by the need of common strategies to address climate change. In this study, a comprehensive model to estimate crop growth and irrigation requirements of 26 main crops at global scale is presented. The model computes a soil water balance using daily precipitation and reference evapotranspiration based on a high-resolution ERA5 reanalysis dataset from the European Copernicus Program. The irrigation requirement, defined as the minimum water volume to avoid water stress, is computed for year 2000 at the resolution of 5 arc-min (or 0.0833°) and aggregated at different spatial and temporal scales for relevant analyses. The estimated global irrigation requirements for 962 km3 is described in detail, also in relation to the spatial variability and to the monthly variation of the requirements. A focus on different areas of the world (California, Northern Italy and India) highlights the wealth of information provided by the model in different climatic conditions. National data of irrigation withdrawals have been used for an extensive comparison with model results. A crop-specific validation has also been made for the State of California, comparing model results with local data of irrigation volume and independent estimates of crop water use. In both cases, we found a good agreement between model results and real data.
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Bautista, Eduardo, and James L. Schlegel. "Estimation of Infiltration and Hydraulic Resistance in Furrow Irrigation, with Infiltration Dependent on Flow Depth." Transactions of the ASABE 60, no. 6 (2017): 1873–84. http://dx.doi.org/10.13031/trans.12263.
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Abstract. Estimation of infiltration and hydraulic resistance model parameters from furrow irrigation evaluation data was investigated. A semi-physical, flow-depth dependent furrow infiltration model was used for the analysis. Macropore infiltration was modeled empirically as a constant volume of water per unit area that is absorbed instantaneously. The estimated infiltration parameters were the saturated hydraulic conductivity and the macropore constant. Hydraulic resistance was modeled with the Manning equation; thus, the estimated resistance parameter was the Manning coefficient. The estimation procedure uses volume balance calculations and unsteady flow simulation. Estimation of the flow-depth dependent infiltration parameters requires first the estimation of an empirical infiltration function, via volume balance, and of the resistance parameter, via unsteady flow simulation. Simulated flow depth hydrographs as a function of distance are then used as inputs for a second set of volume balance calculations with the semi-physical infiltration model. This procedure takes advantage of the fact that similar surface flow conditions (advance and recession times, flow depths, and runoff rate) can be predicted with different infiltration functions. The procedure was tested with two irrigation data sets, each consisting of three furrows. With both data sets, the semi-physical infiltration model fitted the measured volume balance data as well as empirical infiltration models. For each group of furrows, estimates of the hydraulic conductivity were of comparable magnitude and were consistent with published values for the particular soil texture. Likewise, estimates of the macroporosity parameter were consistent for each group of furrows. Estimates of the Manning coefficient suggest very uniform hydraulic resistance. Finally, results show that the effect of flow-depth dependent infiltration on irrigation distribution uniformity depends on soil and hydraulic conditions. For one of the data sets, distribution uniformity computed with the proposed infiltration model was only slightly different from the uniformity computed assuming that infiltration depends only on opportunity time, because of the large macropore flow contribution and the shallow flow conditions. Keywords: Distribution uniformity, Furrows, Green-Ampt, Hydraulic conductivity, Hydraulic modeling, Hydraulic resistance, Infiltration, Inverse modeling, Irrigation, Parameter estimation.
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Zappa, Luca, Stefan Schlaffer, Bernhard Bauer-Marschallinger, Claas Nendel, Beate Zimmerman, and Wouter Dorigo. "Detection and Quantification of Irrigation Water Amounts at 500 m Using Sentinel-1 Surface Soil Moisture." Remote Sensing 13, no. 9 (April 29, 2021): 1727. http://dx.doi.org/10.3390/rs13091727.
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Detailed information about irrigation timing and water use at a high spatial resolution is critical for monitoring and improving agricultural water use efficiency. However, neither statistical surveys nor remote sensing-based approaches can currently accommodate this need. To address this gap, we propose a novel approach based on the TU Wien Sentinel-1 Surface Soil Moisture product, characterized by a spatial sampling of 500 m and a revisit time of 1.5–4 days over Europe. Spatiotemporal patterns of soil moisture are used to identify individual irrigation events and estimate irrigation water amounts. To retrieve the latter, we include formulations of evapotranspiration and drainage losses to account for vertical fluxes, which may significantly influence sub-daily soil moisture variations. The proposed approach was evaluated against field-scale irrigation data reported by farmers at three sites in Germany with heterogeneous field sizes, crop patterns, irrigation systems and management. Our results show that most field-scale irrigation events can be detected using soil moisture information (mean F-score = 0.77). Irrigation estimates, in terms of temporal dynamics as well as spatial patterns, were in agreement with reference data (mean Pearson correlation = 0.64) regardless of field-specific characteristics (e.g., crop type). Hence, the proposed approach has the potential to be applied over large regions with varying cropping systems.
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Reyes González, Arturo, David Guadalupe Reta Sánchez, Juan Isidro Sánchez Duarte, Esmeralda Ochoa Martínez, Karla Rodríguez Hernández, and Pablo Preciado Rangel. "Estimación de la evapotranspiración de maíz forrajero apoyada con sensores remotos y mediciones in situ." REVISTA TERRA LATINOAMERICANA 37, no. 3 (July 15, 2019): 279. http://dx.doi.org/10.28940/terra.v37i3.485.
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Irrigated agriculture requires better estimates of crop water demand. The aim of this study was to estimate the evapotranspiration (ETc) in forage corn through vegetation indices obtained in situ and estimated with remote sensing in the Comarca Lagunera, Mexico. The research was carried out in 2011 and 2012 in four 900 m2 plots irrigated with a subsurface drip irrigation system. Normalized Difference Vegetation Index (NDVI) and crop coeff icient (Kc) during crop development were determined. The initial, maximum and f inal NDVI values were 0.13, 0.79 and 0.63 for both methods and in both cycles. The maximum Kc values were obtained 54 and 48 days after sowing (DDS) with GreenSeeker, and at 61 and 59 DDS with satellite images in 2011 and 2012, respectively. The results showed a good relationship between ETc estimated in situ and ETc estimated with remote sensing (r = 0.98) for both years. Although the variation of ETc using both methods was 1.2 mm day‑1, early in the cycle and 7.4 mm day-1 to flowering start-milky grains. Water needs of forage corn were estimated with similar precision using remote sensing and in situ measurements. Therefore, both methods can be used to improve irrigation scheduling and preserve water resources in agriculture.
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Wei, Shiqi, Tianfang Xu, Guo-Yue Niu, and Ruijie Zeng. "Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains." Remote Sensing 14, no. 13 (June 23, 2022): 3004. http://dx.doi.org/10.3390/rs14133004.
Full textAbstract:
Groundwater-based irrigation has dramatically expanded over the past decades. It has important implications for terrestrial water, energy fluxes, and food production, as well as local to regional climates. However, irrigation water use is hard to monitor at large scales due to various constraints, including the high cost of metering equipment installation and maintenance, privacy issues, and the presence of illegal or unregistered wells. This study estimates irrigation water amounts using machine learning to integrate in situ pumping records, remote sensing products, and climate data in the Kansas High Plains. We use a random forest regression to estimate the annual irrigation water amount at a reprojected spatial resolution of 6 km based on various data, including remotely sensed vegetation indices and evapotranspiration (ET), land cover, near-surface meteorological forcing, and a satellite-derived irrigation map. In addition, we assess the value of ECOSTRESS ET products for irrigation water use estimation and compare with the baseline results by using MODIS ET. The random forest regression model can capture the temporal and spatial variability of irrigation amounts with a satisfactory accuracy (R2 = 0.82). It performs reasonably well when it is calibrated on the western portion of the study area and tested on the eastern portion that receives more rain than the western one, suggesting its potential transferability to other regions. ECSOTRESS ET and MODIS ET yield a similar irrigation estimation accuracy.