Water-Table Depth and Irrigation Effects on Applied-Water-Use Efficiencies of Three Crops

1978 ◽  
Vol 21 (4) ◽  
pp. 0723-0728 ◽  
Author(s):  
L. C. Benz ◽  
G. A. Reichman ◽  
E. J. Doering ◽  
R. F. Follett
Keyword(s):  
Water Use ◽  
Water Table ◽  
Water Table Depth ◽  
Applied Water ◽  
Water Use Efficiencies ◽  
Irrigation Effects

scholarly journals Water use efficiency and yield of cowpea and nutrient loss in lysimeter experiment under varying water table depth, irrigation schedules and irrigation method

2017 ◽  
Vol 14 (2) ◽  
pp. 46-55 ◽  
Author(s):  
Binny Dasila ◽  
Veer Singh ◽  
HS Kushwaha ◽  
Ajaya Srivastava ◽  
Shri Ram
Keyword(s):  
Grain Yield ◽  
Water Use Efficiency ◽  
Nutrient Uptake ◽  
Water Use ◽  
Water Table ◽  
Root Length ◽  
Water Table Depth ◽  
Nutrient Loss ◽  
Lysimeter Experiment ◽  
Use Efficiency

Lysimeter experiment was conducted at Govind Ballabh Pant University of Agriculture & Technology, Pantnagar during summer season 2013 to study the effect of irrigation schedules and methods on yield, nutrient uptake and water use efficiency of cowpea as well as nutrient loss from silty clay loam soil under fluctuating water table conditions. The experiment was laid out in factorial randomized block design having three irrigation schedules at IW/CPE ratio of 0.3. 0.2 and 0.15 with two irrigation methods (flood and sprinkler) and at 30±1.5, 60±1.5 and 90±1.5 cm water tables replicated thrice. Maximum root length (129.4 cm) and root length density (0.395 cm/cm3) were obtained when irrigation was scheduled at IW: CPE 0.3 associated with 30±1.5 cm water table depth using sprinkler method. Increase in water table depth and IW: CPE ratio decreased water use efficiency where IW: CPE 0.3 produced highest grain yield (1411.6 kg ha-1) with the WUE of 1.15 kg ha mm-1. Significant nutrients uptake response was observed owing to variation in water table depth, irrigation schedules and methods. Analysis of lysimeter leached water showed that with deep drainage and more IW:CPE, leaching losses of N,P and K were more however water applied through sprinkler saved 20.1, 53.7 and 24.4% N, P and K, respectively, over flooded method. Irrigation given at IW: CPE 0.3 through sprinkler form at 60±1.5 cm water table depth favours the higher grain yield and nutrient uptake by crop whereas flooded irrigation with deep water table condition accelerated nutrient leaching.SAARC J. Agri., 14(2): 46-55 (2016)

scholarly journals Water Table Depth Effect on Water Use and Tuber Yield for Subirrigated Caladium Production

2002 ◽  
Vol 12 (4) ◽  
pp. 679-681 ◽  
Author(s):  
C.D. Stanley ◽  
B.K. Harbaugh
Keyword(s):  
Water Use ◽  
Water Table ◽  
Management Practices ◽  
Organic Soil ◽  
Water Table Depth ◽  
Depth Effect ◽  
Production Index ◽  
Tuber Production ◽  
Current Water ◽  
Rain Events

A study was conducted to determine the effect of water table depth on water use and tuber yields for subirrigated caladium (Caladium × hortulanum) production. A field-situated drainage lysimeter system was used to control water table depths at 30, 45 and 60 cm (11.8, 17.7, and 23.6 inches). Water use was estimated by accounting for water added or removed (after rain events) to maintain the desired water table depth treatments. In 1998, tuber weights, the number of Jumbo grade tubers, and the production index (tuber value index) of `White Christmas' were greater when plants were grown with the water table maintained at 30 or 45 cm compared to 60 cm. In 1999, tuber weights, the number of Mammoth grade tubers, and the production index, also were greater when plants were grown at water table depths of 30 or 45 cm compared to 60 cm. The average estimated daily water use was 6.6, 5.1, and 3.3 mm (0.26, 0.20, and 0.13 inch) for plants grown at water table depths of 30, 45, and 60 cm, respectively, indicating an inverse relationship with water table depth. While current water management practices in the caladium industry attempt to maintain a 60-cm water table, results from this study indicate that, for subirrigated caladium tuber production, the water table should be maintained in at 30 to 45 cm for maximum production on an organic soil.

Water table depth affects productivity, water use, and the response to nitrogen addition in a savanna system

2008 ◽  
Vol 38 (8) ◽  
pp. 2118-2127 ◽  
Author(s):  
Chelcy R. Ford ◽  
Robert J. Mitchell ◽  
Robert O. Teskey
Keyword(s):  
Water Use ◽  
Water Table ◽  
Net Primary Productivity ◽  
Longleaf Pine ◽  
Pinus Palustris ◽  
High Water ◽  
Life Forms ◽  
Water Table Depth ◽  
N Addition ◽  
Aboveground Net Primary Productivity

We investigated annual aboveground net primary productivity (ANPP) and transpiration (E) of the dominant plant life forms, longleaf pine (Pinus palustris Mill.) trees and wiregrass (Aristida stricta Michx.), in a fire-maintained savanna. Experimental plots spanned a natural hydrologic gradient (xeric and mesic site types) mediated by soil moisture (θ) and water table depth (WTD), and received additions of either 0 or 100 kg N·ha–1·year–1. Low rates of ANPP (1.3–2.2 Mg·ha–1) and annual E (108–380 mm) were observed in these communities. WTD and N addition explained 95% of the variation in community ANPP, whereas site type and WTD explained 83% of variation in community E. Between tree and grass life forms, longleaf pine ANPP was more coupled to WTD than wiregrass. For any given leaf area supported, ANPP of longleaf pine increased linearly with increasing water use and decreasing WTD. The longleaf pine ANPP response to N addition was greater in sites with high water use compared with those with low water use, indicating that this savanna system is colimited by nutrient and water availability and that water table depth plays a role in regulating savanna productivity.

Effect of water-table management and nitrogen supply on yield, plant growth and water use of corn in undisturbed soil columns

1996 ◽  
Vol 76 (2) ◽  
pp. 229-235 ◽  
Author(s):  
C. S. Tan ◽  
C. F. Drury ◽  
J. D. Gaynor ◽  
I. van Wesenbeeck ◽  
M. Soultani
Keyword(s):  
Zea Mays ◽  
Stomatal Conductance ◽  
Plant Growth ◽  
Water Use ◽  
Water Table ◽  
Soil Surface ◽  
Water Table Depth ◽  
Grain Yields ◽  
Water Table Management ◽  
N Rates

The effect of three water-table depths (30, 60 and 80 cm below the soil surface) and four N rates (0, 45, 90 and 135 kg ha−1) on plant growth, yield and water use were evaluated for corn (Zea mays L.). Research was conducted in a greenhouse, using 36 undisturbed foil columns (20 cm i.d. and 90 cm length) collected with a Meta-Drill vibrating core sampler from a Fox sandy loam soil at Harrow Research Centre. Corn grown in the 80-cm water-table depth had the greatest degree of water stress, as indicated by low volumetric soil water content, low stomatal conductance and transpiration rates, and elevated soil-surface and leaf-surface temperatures. There was a substantial increase in plant dry weight and grain yields as the N rates increased from 0 to 135 kg ha−1 with the 30- and 60-cm water-table depths. Under our experimental conditions, maximum grain yields were obtained with a 60-cm water-table depth. Grain yields were significantly reduced with the 80-cm water-table depth. With this water-table depth, grain yield was also reduced by N addition. Key words: Water-table management, Zea mays, yield, stomatal conductance, leaf temperature

scholarly journals Temporal and Local Heterogeneities of Water Table Depth under Different Agricultural Water Management Conditions

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2148
Author(s):  
Jonathan A. Lafond ◽  
Silvio J. Gumiere ◽  
Virginie Vanlandeghem ◽  
Jacques Gallichand ◽  
Alain N. Rousseau ◽  
...  
Keyword(s):  
Water Management ◽  
Water Table ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Sprinkler Irrigation ◽  
Water Table Depth ◽  
Management Systems ◽  
Integrated Water Management ◽  
Growing Seasons ◽  
Good Drainage

Integrated water management has become a priority for cropping systems where subirrigation is possible. Compared to conventional sprinkler irrigation, the controlling water table can lead to a substantial increase in yield and water use efficiency with less pumping energy requirements. Knowing the spatiotemporal distribution of water table depth (WTD) and soil properties should help perform intelligent, integrated water management. Observation wells were installed in cranberry fields with different water management systems: Bottom, with good drainage and controlled WTD management; Surface, with good drainage and sprinkler irrigation management; Natural, without drainage, or with imperfectly drained and conventional sprinkler irrigation. During the 2017–2020 growing seasons, WTD was monitored on an hourly basis, while precipitation was measured at each site. Multi-frequential periodogram analysis revealed a dominant periodic component of 40 days each year in WTD fluctuations for the Bottom and Surface systems; for the Natural system, periodicity was heterogeneous and ranged from 2 to 6 weeks. Temporal cross correlations with precipitation show that for almost all the sites, there is a 3 to 9 h lag before WTD rises; one exception is a subirrigation site. These results indicate that automatic water table management based on continuously updated knowledge could contribute to integrated water management systems, by using precipitation-based models to predict WTD.

Yield and water use efficiencies of maize and cowpea as affected by tillage and cropping systems in semi-arid Eastern Kenya

2012 ◽  
Vol 115 ◽  
pp. 148-155 ◽  
Author(s):  
J.M. Miriti ◽  
G. Kironchi ◽  
A.O. Esilaba ◽  
L.K. Heng ◽  
C.K.K. Gachene ◽  
...  
Keyword(s):  
Water Use ◽  
Cropping Systems ◽  
Water Use Efficiencies ◽  
Semi Arid

Modelling response of infiltration loss toward water table depth using RBFN, RNN, ANFIS techniques

2021 ◽  
Vol 25 (2) ◽  
pp. 227-234
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo
Keyword(s):  
Neural Network ◽  
Mean Square Error ◽  
Water Table ◽  
Environmental Sustainability ◽  
Model Development ◽  
Water Table Depth ◽  
Water Levels ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Inference System

Accurate prediction of water table depth over long-term in arid agricultural areas are very much important for maintaining environmental sustainability. Because of intricate and diverse hydrogeological features, boundary conditions, and human activities researchers face enormous difficulties for predicting water table depth. A virtual study on forecast of water table depth using various neural networks is employed in this paper. Hybrid neural network approach like Adaptive Neuro Fuzzy Inference System (ANFIS), Recurrent Neural Network (RNN), Radial Basis Function Neural Network (RBFN) is employed here to appraisal water levels as a function of average temperature, precipitation, humidity, evapotranspiration and infiltration loss data. Coefficient of determination (R2), Root mean square error (RMSE), and Mean square error (MSE) are used to evaluate performance of model development. While ANFIS algorithm is used, Gbell function gives best value of performance for model development. Whole outcomes establish that, ANFIS accomplishes finest as related to RNN and RBFN for predicting water table depth in watershed.

Sign in / Sign up

Export Citation Format

Share Document