Agricultural Water Management (AGR WATER MANAGE )

Publisher: Elsevier


The journal is concerned with the publication of scientific papers of international significance to the management of agricultural water. The scope includes such diverse aspects as irrigation and drainage of cultivated areas, collection and storage of precipitation water in relation to soil properties and vegetation cover; the role of ground and surface water in nutrient cycling, water balance problems, exploitation and protection of water resources, control of flooding, erosion and desert creep, water quality and pollution both by, and of, agricultural water, effects of land uses on water resources, water for recreation in rural areas, and economic and legal aspects of water use. Basic soil-water-plant relationships will be considered only as far as is relevant to agricultural water management.

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    Agricultural water management (Online)
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    • Publisher last contacted on 18/10/2013
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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Evaluating irrigation systems based on classical efficiency can lead to misleading conclusions.•Effective efficiency well represented the occurred irrigation management at the farm scale.•Combined application of these concepts is preferable for improving irrigation water management.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: A combined evaporation-optimal pumping scheduling model has been developed.•The model was applied to an irrigation water district in Southern Spain.•Energy and water savings were achieved when considering evaporation in the optimisation model.•The developed model can be a useful decision support system for irrigation managers.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: Blueberry yield on sandy soil was affected by the number of drip laterals per row.•Increasing the drip lateral number enlarge the percentage of exportable fruit.•The largest fruit yield was obtained with four drips laterals per row.•Irrigation frequencies did not affect the blueberry production.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: Modeling in agriculture represents an important tool to understand processes as water and nutrient losses by drainage, or to test different conditions and scenarios of soil and crop management. Among the existing computational models to describe hydrological processes, SWAP (Soil, Water, Atmosphere and Plant model) has been successfully used under several conditions. This model was originally developed to simulate short cycle crops and its use also to cover longer cycles, e.g. perennial crops, is a new application. This report shows a SWAP application to a mature coffee crop over one-production cycle, focusing on deep drainage losses in a typical soil-plant-atmosphere system of the Brazilian savanna (Cerrado). The estimated annual deep drainage Q = 1019 mm obtained by SWAP was within 99% of the value determined by the climatologic water balance of 1010 mm. Monthly results of SWAP for Q compared to the estimative using the climatological method presented a determination coefficient of 0.77. A variety of coffee fertigation scenarios were simulated using SWAP and compared to farmer’s management scenario, leading to the conclusion that larger irrigation intervals result in lower Q losses, better water productivity and higher crop yield.
    Agricultural Water Management 01/2015; 148:130-140.
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    ABSTRACT: Factors determining farmers’ adaptation responses to water scarcity are identified.•Farmers’ adaptation choices are examined in comparison to the groundwater irrigation.•Groundwater dependency raises issues of sustainable agricultural adaptation.•Strategies to cope with water-stressed regimes in drought-prone environments are recommended.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: We investigated the nutrient-leaching losses in an Ultisol cultivated with sugarcane.•The leaching of N, was 22.5 kg ha−1 N derived from the 100 kg ha−1 applied N fertilizer.•The S leached was between 4.6 and 8.4 kg ha−1 and P between 0.3 and 1.2 kg ha−1.•The maximum leaching of K, Ca, and Mg were 53.6, 135.7 and 39.8 kg ha−1, respectively.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: Water scarcity and water salinity are major constrains for agricultural production in arid and semi-arid regions of Iran. Salt tolerant and high nutritious crop, quinoa, has been introduced all around the world. However, little documented investigations are presented about the effect of different saline groundwater depths and irrigation water salinities on plant growth, yield and water use of quinoa. Therefore, the aim of this study was to investigate the influence of saline groundwater depths, SGD (0.3, 0.55 and 0.80 m) with salinity equivalent to irrigation water and irrigation water salinity, WS (10, 20, 30 and 40 dS m−1) on growth and yield of quinoa and groundwater contribution to its water use in cylindrical lysimeters in greenhouse conditions. Results indicated that increasing in WS caused significant decrease in seed yield (SY) and shoot dry matter (SDM) and at all SGDs. However, root dry matter (RDM), harvest index (HI), protein content, 1000-seed weight (SW), number of panicle per plant (NP) and plant height (PH) are reduced by WS higher than 20 dS m−1. Furthermore, at all WSs increasing in SGD resulted in significant increase in SY, SDM, RDM and ET. Results indicated that quinoa is able to extract water (groundwater contribution to evapotranspiration ratio, GWC/ET as 18 to 66%) from saline groundwater, even at no deficit irrigation conditions. Contour plot was developed to show the combined effect of WS and SGD on GWC/ET. It is indicated that non-saline groundwater depth lower than 1.62 m could contribute to quinoa water use. In presence of saline groundwater (SGD as m), the salinity should be considered by the equation .Yield-salinity functions indicated that maximum threshold ECe for SY (20.7 dS m−1) occurred at 0.80 m SGD and seed yield reduction coefficient (b) was on average, 7.7% per unit soil salinity increase. Also, increasing in SGD resulted in significant decrease in RDM reduction coefficient. Minimum RDM reduction coefficient was 5.5% per unit soil salinity increase. It showed that quinoa root is more tolerant to salinity than shoots.
    Agricultural Water Management 01/2015; 148.
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    ABSTRACT: tDue to the absence of experimental reference evapotranspiration (ETo) records, data-driven models con-sider in most cases calculated ETotargets to train and test the models, usually according to the standardFAO56 Penman Monteith equation (FAO56-PM). This procedure is also adopted for calibrating more conventional empirical approaches like the well-known Hargreaves (HG) equation. This study aims at assessing the performance implications derived from using calculated targets instead of experimental measurements for training and testing data-driven models or calibrating empirical methods. Therefore an application of a gene expression programming (GEP) based approach for estimating ETois presentedconsidering calculated and lysimetric targets fed with two different input combinations and assessed through k-fold testing. The same procedure is adopted to evaluate the calibration of the HG equation.Finally, the FAO56-PM and the HG equations are compared with their corresponding GEP models bearing in mind the type of targets used. The locally trained GEP4 and GEP6 models trained using the experimental lysimetric targets are more accurate than the corresponding HG and FAO56-PM equations, assessed using lysimetric benchmarks. The external performance accuracy of GEP4 and GEP6 models decreases considerably in the cross-station approach using experimental targets. In this case, the FAO56-PM and the HG equations might be preferable. The accuracy of the GEP models trained with calculated targets decreases considerably when the performance is assessed using experimental benchmarks. The conclusions drawn when only calculated benchmarks are used might be not sound or even false. The sameapplies for empirical equations calibrated with calculated targets. Four new GEP-based equations (one per input combination and station) are provided to estimate ETo.
    Agricultural Water Management 01/2015; 149:81-90.
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    ABSTRACT: Storm events that increase flow rates can disturb sediments and produce overland runoff in watersheds with animal agriculture, and, thus, can increase surface water concentrations of fecal bacteria and risk to public health. We tested the hypothesis that strategically designed and placed ponds in watersheds with animal agriculture would attenuate downstream fluxes of fecal bacteria. We measured concentrations and fluxes of fecal indicator bacteria (commensal Escherichia coli and fecal enterococci) and manure pathogens (Salmonella and E. coli 0157:H7) in in- and outflows of Bishop Pond in the Southern Piedmont of Georgia during three storm events and in- and outflow concentrations and fluxes of fecal indicator bacteria at Ponds A and C in the Coastal Plain of Georgia during two storm events. Mean concentrations and fluxes of fecal indicator bacteria associated with pond in- and outflow during hydrograph rise, peak, fall, and 5-days after peak flow at Bishop Pond were significantly greater than their mean base flow concentrations and fluxes. In storm flow Bishop Pond significantly reduced the outflow concentrations and fluxes of fecal indicator bacteria compared with corresponding inflow measurements. Unlike fecal indicator bacteria, Bishop Pond appeared not to reduce outflow concentrations and fluxes of Salmonella or E. coli 0157:H7. At Ponds A and C in the Coastal Plain mean in- and outflow concentrations and fluxes of the fecal indicator bacteria associated with the hydrograph rise and peak flows of the storms were not different. Bishop Pond, with a length to width ratio of 3.3, attenuated downstream fluxes of fecal bacteria. In contrast, Ponds A and C were not effective at reducing downstream fluxes of fecal bacteria under storm flow conditions. The ineffectiveness of Ponds A and C may be attributed to their having length to width ratios of 1.2 and 2.5, respectively, both of which are below the minimum for effective pond performance. Our results indicated that in the humid Southeast an appropriately placed and configured pond in watersheds with animal agriculture can reduce storm flow loads of fecal indicator bacteria but not necessarily pathogenic E. coli 0157:H7.
    Agricultural Water Management 01/2015; 148:97–105.
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    ABSTRACT: Better understanding of the relationship between soil properties and soil function is required to minimise nutrient losses from agriculture and protect the environment. There is a need to predict the solute movement through horticultural soils because of the intensive management practices. Thus, the mobile water content (θm), the active fraction of soil water content engaged in solute transport, is a suitable soil property to investigate further. Accurate measurement of such solute transport properties in the field are costly, labour intensive and time consuming but there are opportunities to establish predictive relationships. θm was measured together with other basic soil properties to test established predictive relationships (known as pedotransfer functions, PTFs) and to develop new PTFs. The field measurements were taken on a diverse range of vineyard soils across New South Wales (NSW), Australia. Poor predictions were found with available PTFs for θm and the mobile water fraction f (=θm/θfm; where θfm = volumetric water content at which θm was measured). Backward stepwise multiple regression analysis produced better PTF model predictions than the multiple linear regression analysis for new PTFs that were calculated. Differences in the analysis methods showed a trade-off between the prediction capacity and the number of predictor variables in each PTF model. A prediction accuracy of between 80 to 90% was found with 3 predictor variables in the PTFs for θm and f. Both the PTFs developed were in strong agreement with the measured properties (minimum R2 = 0.82). For the θm PTF, the % clay content (varied from 11 to 59) was the strongest predictor variable while bulk density (ranged from 1.2 to 1.51 g cm−3) contributed the smallest. The PTF for f was similar to θm except it was the % soil organic carbon which had the smallest contribution. These relationships are useful to predict θm and f from easily measured soil physical properties of vineyard soils in NSW, but further testing on a wider range of soils is required.
    Agricultural Water Management 01/2015; 148:34–42.
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    ABSTRACT: While the use of evapotranspiration-based or ET-based scheduling to improve on the efficient use of water for irrigation has advanced considerably in recent decades, there is still a need to improve the estimation of ET in regions with multiple microclimates and where the vegetation is mixed or fetch is inadequate for measurement of ET using traditional methods. This paper describes the Landscape Irrigation Management Program (LIMP) model, which addresses these problems. More importantly, the paper describes methods to adjust reference evapotranspiration (ETo) for microclimate and to measure ET from small fields to provide “site-specific” coefficients for estimating ET. The LIMP model was developed as a scientific approach to estimating landscape water requirements, and the methodology is also helpful for estimating crop ET in regions with multiple microclimates and where crops differ in morphology, physiology, plant density, sensitivity to water stress, etc. A similar approach to LIMP was described in the Irrigation Association book “Irrigation Sixth Edition”. Although the LIMP model is useful, there is a paucity of literature on how to correct ETo for microclimate or how to determine the input coefficients for LIMP to estimate ET. In this paper, we discuss a method to estimate microclimate coefficients to account for spatial ETo variation and we discuss the use of the surface renewal method to measure in-situ ET, which can help to determine “site-specific” coefficients for locations with inadequate fetch to use other ET measurement methods. In addition to using the presented techniques for landscape ET estimation, the procedures are equally useful for estimation of ET in small cropped fields of uniform or mixed vegetation, riparian vegetation, climate controlled greenhouses, in undulating terrain, and regions with multiple microclimates.
    Agricultural Water Management 01/2015; 147:187–197.
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    ABSTRACT: This study was conducted to investigate the effects of four irrigation regimes on yield, growth parameters and water use efficiency of cucumber crop under greenhouse cultivation. A field experiment was carried out at the experimental farm of Palestine Technical University Kadoorie, located at Tulkarm, Palestine. Cucumber seedlings were planted on 14 February 2012 in greenhouse at a rate of 1500 seedlings per 1000 square meters. Four irrigation regimes were examined during the growing period as follows: farmer irrigation (FI), tensiometer based irrigation (TI), irrigation at full ETc data (ETc), and irrigation at 70% of ETc (70% ETc). Plant data were collected during the growing period for evaluating the total yield, plant height, number of harvested fruits per plant, weight of harvested fruits per plant, dry matter of above and under ground parts. The results indicated that the 70% ETc treatment obtained the highest crop yield followed by ETc, FI, and TI treatments, respectively. On average, cucumber yield under 70% ETc treatment was 24%, 6% and 4% higher than that under TI, FI and ETc treatments, respectively. At the end of harvesting stage plant height, above-ground dry matter obtained by 70% ETc treatment was higher than the other treatments. The smallest plant height and dry matter was obtained under TI treatment. Results also indicated that, when using scheduled irrigation methods large amount of water were saved and found to be 139, 104 and 26 mm for TI, 70% ETc and ETc treatments, respectively, compared to FI treatment. The highest water use efficiency (WUE) was obtained under 70% ETc treatment followed by ETc, TI and FI treatments, respectively.
    Agricultural Water Management 01/2015; 148:10–15.