Corn and grain sorghum response to limited irrigation, drought, and hail

A field study was conducted for eight years in southwest Kansas near Garden City to measure the response of corn and grain sorghum to limited irrigation in the region. An irrigation variable was imposed on each crop, with six irrigation treatments from full irrigation scheduled to minimize soil water deficits to minimal or no irrigation. To create differences in the amount of irrigation across treatments, the time between 25-mm irrigation events increased as irrigation decreased. A historic drought occurred during 2011 and 2012 when cropping season precipitation, the precipitation occurring from the harvest of the prior crop through the harvest of the next crop, was 60% of the 30-year average. Except for 2008, average cropping season precipitation was 8% above average during the prior six years. Linear regressions of corn and sorghum grain yields (GY) and dry matter yields (DMY) versus crop evapotranspiration (ETc) from all years combined, except hail damaged sorghum in 2005, produced R2 values from 0.71 to 0.79. One hailstorm during 2005 damaged sorghum to the extent that yields did not vary with respect to ETc or irrigation. Hail events in 2005 and 2006 occurred at nearly the same growth stage for corn caused lower leaf area and yields than during other wet years with no hail. Using quadratic regressions, corn yields during wet years with no hail, wet years with hail, and dry years had distinctly different dependence on irrigation. Although sorghum yields during wet years tended to increase as irrigation increased, sorghum’s response to irrigation was less than for corn during the same years. During dry years, sorghum and corn were highly dependent on irrigation. Net economic returns (NR) of continuous corn, continuous sorghum, cornsorghum, corn-wheat, and sorghum-wheat rotations were each higher with a year receiving average precipitation (460 mm) than a year receiving 60% of average precipitation (280 mm). The NR of continuous corn dominated the rest of the rotations when irrigation was more than 230 to 330 mm in the dry year and 90 to 180 mm in wet year. As farmers choose crop rotations, they need to consider management factors and crop tolerance to soil water stress in addition to potential NR

Effects of irrigation amount and timing on alfalfa nutritive value

Citation: Holman, J., Min, D., Klocke, N., Kisekka, I., & Currie, R. (2016). Effects of irrigation amount and timing on alfalfa nutritive value. Transactions of the Asabe, 59(4), 849-860. doi:10.13031/trans.59.11456Most hay producers in southwest Kansas irrigate their alfalfa (Medicago sativa L.) because precipitation is insufficient for profitable rainfed production. However, water supplies in the central Great Plains are dwindling, particularly in the central and southern Ogallala Aquifer region. Irrigating many field crops in this region, including alfalfa, is therefore becoming a challenge. We determined the effects of irrigation quantity and timing on alfalfa forage nutritive value during a five-year field study of alfalfa in southwest Kansas. Nutritive value was quantified in the form of crude protein, acid detergent fiber, neutral detergent fiber, total digestible nutrients, and relative feed value. In general, applying the highest amount of irrigation (610 mm during the growing season) resulted in the lowest forage nutritive value compared to lower amounts of irrigation (0, 200, and 380 mm irrigation). Nutritive value concentrations (g kg-1) under full irrigation averaged 211 for crude protein, 316 for acid detergent fiber, and 422 for neutral detergent fiber, while concentrations (g kg-1) in rainfed production averaged 225 for crude protein, 247 for acid detergent fiber, and 370 for neutral detergent fiber. Alfalfa nutritive value was not affected whether the same amount of irrigation water was applied either before green-up and between each cutting, or before green-up and between all cuttings except between cuttings 2 and 3. However, there was a tendency for lower forage nutritive value at the fourth cutting when irrigation was withheld between cuttings 2 and 3, and that saved water was added to the amount of irrigation applied to the fourth cutting. When averaged over irrigation treatments, alfalfa nutritive value was lower from the first and second cuttings than from the third and fourth cuttings. Annual yields, averaged over years, declined from 1.53 kg m-2 with 610 mm of irrigation to 0.43 kg m-2 for rainfed production. Annual yields were the same when irrigation was distributed over the growing season or withheld between the second and third cuttings. Irrigation amounts less than full crop requirement resulted in a 13% higher dollar value product based on relative feed value, but decreasing irrigation from 610 to 380 mm reduced yield by 19%. © 2016 American Society of Agricultural and Biological Engineers

Modeling soil water dynamics considering measurement uncertainty

In shallow water table controlled environments, surface water management impacts groundwater table levels and soil water dynamics. The study goal was to simulate soil water dynamics in response to canal stage raises considering uncertainty in measured soil water content. WAVE (Water and Agrochemicals in the soil, crop and Vadose Environment) was applied to simulate unsaturated flow above a shallow aquifer. Global sensitivity analysis was performed to identify model input factors with greatest influence on predicted soil water content. Nash-Sutcliffe increased and Root Mean Square Error reduced when uncertainties in measured data were considered in goodness-of-fit calculations using measurement probability distributions and probable asymmetric error boundaries; implying that appropriate model performance evaluation should be done using uncertainty ranges instead of single values. Although uncertainty in the experimental measured data limited evaluation of the absolute predictions by the model, WAVE was found a useful exploratory tool for estimating temporal variation in soil water content. Visual analysis of soil water content time series under proposed changes in canal stage management indicated that sites with land surface elevation of less than 2.0 m NGVD29 were predicted to periodically experience saturated conditions in the root zone and shortening of the growing season if canal stage is raised more than 9 cm and maintained at this level. The models developed could be combined with high resolution digital elevation models in future studies to identify areas with the greatest risk of experiencing saturated root zone. The study also highlighted the need to incorporate measurement uncertainty when evaluating performance of unsaturated flow models

Dynamic factor analysis of surface water management impacts on soil and bedrock water contents in Southern Florida Lowlands

As part of the C111 spreader canal project, structural and operational modifications involving incremental raises in canal stage are planned along one of the major canals (i.e., C111) separating Everglades National Park and agricultural production areas to the east of the park. This study used Dynamic Factor Analysis (DFA) as an alternative tool to physically based models to explore the relationship between different hydrologic variables and the effect of proposed changes in surface water management on soil and bedrock water contents in south Florida. To achieve the goal, objectives were to: (1) use DFA to identify the most important factors affecting temporal variation in soil and bedrock water contents, (2) develop a simplified DFA based regression model for predicting soil and bedrock water contents as a function of canal stage and (3) assess the effect of the proposed incremental raises in canal stage on soil and bedrock water contents. DFA revealed that 5 common trends were the minimum required to describe unexplained variation in the 11 time series studied. Introducing canal stage, water table evaporation and net recharge resulted in lower Akaike information criterion (AIC) and higher Nash-Sutcliffe (C[subscript eff]) values. Results indicated that canal stage significantly (t > 2) drives temporal variation in soil and bedrock water contents, which was represented as scaled frequency while net surface recharge was significant in 7 out of the 11 time series analyzed. The effect of water table evaporation was not significant at all sites. Results also indicated that the most important factor influencing temporal variation in soil and bedrock water contents in terms of regression coefficient magnitude was canal stage. Based on DFA results, a simple regression model was developed to predict soil and bedrock water contents at various elevations as a function of canal stage and net recharge. The performance of the simple model ranged from good (C[subscript eff] ranging from 0.56 to 0.74) to poor (C[subscript eff] ranging from 0.10 to 0.15), performance was better at sites with smaller depths to water table (< 1 m) highlighting the effect of micro-topography on soil and bedrock water content dynamics. Assessment of the effect of 6, 9 and 12 cm increases in canal stage using the simple regression model indicated that changes in temporal variation in soil and bedrock water contents were negligible (average<1.0% average change) at 500 to 2000 m from C111 (or low elevations) which may be attributed to the near saturation conditions already occurring at these sites. This study used DFA to explore the relationship between soil and bedrock water dynamics and surface water stage in shallow water table environments. This approach can be applied to any system in which detailed physical modeling would be limited by inadequate information on parameters or processes governing the physical system

Evaluating effects of deficit irrigation strategies on grain sorghum attributes and biofuel production

With reduced water resources available for agriculture, scientists and engineers have developed innovative technologies and management strategies aimed at increasing efficient use of irrigation water. The objective of this research was to study the impact of deficit irrigation strategies on sorghum grain attributes and bioethanol production. Grain sorghum was planted at Southwest Research-Extension Center near Garden City, KS, under five different irrigation capacities (1 inch every 4, 6, 8,10, or 12 days) and dryland in 2015 and 2016 growing seasons. Results showed average kernel weight, kernel diameter and test weight of grain sorghum increased as irrigation capacity increased, whereas kernel hardness index decreased as irrigation capacity increased. Starch and protein contents of sorghum ranged from 69.45 to 72.82% and 8.22e12.50%, respectively. Starch pasting temperature and peak time decreased as irrigation capacity increased. Irrigation capacity had a positive impact on bioethanol yield, whereas both year and interaction between irrigation capacity and year did not show significant effect on bioethanol yield resulting from above normal rainfall received during the growing seasons

Sensitivity analysis and parameter estimation for an approximate analytical model of canal-aquifer interaction applied in the C-111 basin

The goal of this study was to better characterize parameters influencing the exchange of surface water in south Florida’s C-111 canal and Biscayne aquifer using the analytical model STWT1. A three-step model evaluation framework was implemented as follows: (1) qualitative parameter ranking by comparing two Morris method sampling strategies, (2) quantitative variance-based sensitivity analysis using Sobol’s method, and (3) estimation of parameter posterior probability distributions and statistics using the Generalized Likelihood Uncertainty Estimator (GLUE) methodology. Results indicated that the original Morris random sampling method underestimated total parameter effects compared to the improved global Morris sampling strategy. However, parameter rankings from the two sampling methods were similar. For the STWT1 model, only four out of the six parameters analyzed were important for predicting water table response to canal stage and recharge fluctuations. Morris ranking in order of decreasing importance resulted in specific yield (ASY), aquifer saturated thickness (AB), horizontal hydraulic conductivity (AKX), canal leakance (XAA), vertical hydraulic conductivity (AKZ), and half-width of canal (XZERO). Sobol’s sensitivity indices for the four most critical parameters revealed that summation of first-order parameter effects was 1.0, indicating that STWT1 behaved as an additive model or negligible parameter interactions. We estimated parameter values of 0.07 to 0.14 for ASY, 11,000 to 14,300 m d-1 for AKX, 13.4 to 18.3 m for AB, and 99.8 to 279 m for XAA. The estimated values were within the range of values estimated using more complex methods at nearby sites. The Nash-Sutcliffe coefficient of efficiency and root mean square error for estimated parameters ranged from 0.66 to 0.95 and from 4 to 7 cm, respectively. This study demonstrates a simple and inexpensive way to characterize hydrogeological parameters controlling groundwater-surface interactions in any region with aquifers that are highly permeable without using standard pumping tests or canal drawdown experiments. Hydrogeological parameters estimated using this approach could be used as starting values in large-scale numerical simulations

Simulating the Impacts of Irrigation Levels on Soybean Production in Texas High Plains to Manage Diminishing Groundwater Levels

There is an increasing need to strategize and plan irrigation systems under varied climatic conditions to support efficient irrigation practices while maintaining and improving the sustainability of groundwater systems. This study was undertaken to simulate the growth and production of soybean [Glycine max (L.)] under different irrigation scenarios. The objectives of this study were to calibrate and validate the CROPGRO-Soybean model under Texas High Plains’ (THP) climatic conditions and to apply the calibrated model to simulate the impacts of different irrigation levels and triggers on soybean production. The methodology involved combining short-term experimental data with long-term historical weather data (1951–2012), and use of mechanistic crop growth simulation algorithms to determine optimum irrigation management strategies. Irrigation was scheduled based on five different plant extractable water levels (irrigation threshold [ITHR]) set at 20%, 35%, 50%, 65%, and 80%. The calibrated model was able to satisfactorily reproduce measured leaf area index, biomass, and evapotranspiration for soybean, indicating it can be used for investigating different strategies for irrigating soybean in the THP. Calculations of crop water productivity for biomass and yield along with irrigation water use efficiency indicated soybean can be irrigated at ITHR set at 50% or 65% with minimal yield loss as compared to 80% ITHR, thus conserving water and contributing toward lower groundwater withdrawals

Simulating water table response to proposed changes in surface water management in the C-111 agricultural basin of south Florida

As part of an effort to restore the hydrology of Everglades National Park (ENP), incremental raises in canal stage are proposed along a major canal draining south Florida called C-111, which separates ENP from agricultural lands. The study purpose was to use monitoring and modeling to investigate the effect of the proposed incremental raises in canal stage on water table elevation in agricultural lands. The objectives were to: (1) develop a MODFLOW based model for simulating groundwater flow within the study area, (2) apply the developed model to determine if the proposed changes in canal stage result in significant changes in water table elevation, root zone saturation or groundwater flooding and (3) assess aquifer response to large rainfall events. Results indicate the developed model was able to reproduce measured water table elevation with an average Nash-Sutcliffe > 0.9 and Root Mean Square Error 2 year return period storm), reduced water table intrusion into the root zone. We conclude that the impact of operational changes in canal stage management on root zone saturation and groundwater flooding depended on micro-topography within the field and depth of storm events. The findings of this study can be used in fine tuning canal stage operations to minimize root zone saturation and groundwater flooding of agricultural fields while maximizing environmental benefits through increased water flow in the natural wetland areas. This study also highlights the benefit of detailed field scale simulations

Parameterization of Soil Hydraulic Parameters for HYDRUS-3D Simulation of Soil Water Dynamics in a Drip-Irrigated Orchard

Although surface drip irrigation allows an efficient use of water in agriculture, the heterogeneous distribution of soil water complicates its optimal usage. Mathematical models can be used to simulate the dynamics of water in the soil below a dripper and promote: a better understanding, and optimization, of the design of drip irrigation systems, their improved management and their monitoring with soil moisture sensors. The aim of this paper was to find the most appropriate configuration of HYDRUS-3D for simulating the soil water dynamics in a drip-irrigated orchard. Special emphasis was placed on the source of the soil hydraulic parameters. Simulations parameterized using the Rosetta approach were therefore compared with others parameterized using that of HYPROP + WP4C. The simulations were validated on a seasonal scale, against measurements made using a neutron probe, and on the time course of several days, against tensiometers. The results showed that the best agreement with soil moisture measurements was achieved with simulations parameterized from HYPROP + WP4C. It further improved when the shape parameter n was empirically calibrated from a subset of neutron probe measurements. The fit of the simulations with measurements was best at positions near the dripper and worsened at positions outside its wetting pattern and at depths of 80 cm or more.info:eu-repo/semantics/publishedVersio

Assessing deficit irrigation strategies for corn using simulation

Citation: Kisekka, I., Aguilar, J. P., Rogers, D. H., Holman, J., O'Brien, D. M., & Klocke, N. (2016). Assessing deficit irrigation strategies for corn using simulation. Transactions of the Asabe, 59(1), 303-317. doi:10.13031/trans.59.11206Declining groundwater levels in the Ogallala aquifer due to withdrawals exceeding annual recharge result in diminished well capacities that eventually become incapable of meeting full crop water needs. Producers need recommendations for deficit irrigation strategies that can maximize net returns in most years under low well capacities. The objectives of this study were to (1) calibrate and validate the CERES-Maize model in DSSAT-CSM v4.6 under southwest Kansas soils and climatic conditions and (2) apply the calibrated model to assess three factors related to irrigation management: (i) the optimum plant-available water threshold to initiate irrigation for maximizing net returns, (ii) the effect of percentage soil water depletion at planting on yield, seasonal transpiration, water productivity, extractable soil water at maturity, and net returns, and (iii) the effect of late irrigation season termination on extractable soil water at physiological maturity, yield, and net returns. The CERES-Maize model in DSSAT-CSM v4.6 in conjunction with short-term experimental data and 63 years (1950 to 2013) of historical weather data were used in this study. The calibrated model was able to predict end of season grain yield with acceptable accuracy (NSE &gt; 0.9, 0.13 &lt; %RMSE &lt; 0.19), indicating that the model could be used for assessing alternative management strategies for optimizing the use of limited water for irrigating corn in southwest Kansas. Irrigation scheduling based on a 50% plant-available water threshold maximized net returns compared to initiating irrigation at greater soil water content at corn prices ranging from $0.10 to$0.26 kg-1. Accounting for inter-annual variations in weather and irrigation downtime due to repairs, 14 to 17 irrigation applications of 25 mm of water each would be needed to maintain soil water at 50% of plant-available water during the season. Having soil water in the top 1.2 m of the soil profile between 0% and 25% depleted at planting maximized net returns, although it also resulted in more extractable soil water at physiological maturity. Terminating irrigation 90 or 95 days after planting depending on corn price maximized net returns and resulted in the lowest amount of extractable soil water at physiological maturity, implying that opportunities exist to mine stored soil water toward the end of the season even under deficit irrigation. We recommend that late season irrigation termination be done in conjunction with soil water monitoring and management- allowable depletion techniques to minimize potential reduction in yields. Before adopting any of the management strategies assessed in this study, producers should consider the unique yield potential constraints for their farm. The concepts explored in this analysis, which combined experimental data, computer simulation, and long-term weather data to generate optimum management recommendations, could be applied in other areas with constrained water supplies for irrigation. © 2016 American Society of Agricultural and Biological Engineers