Suat Irmak

Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems

Abstract Precision agriculture (PA) refers to a series of practices and tools necessary to correctly evaluate farming needs. The accuracy and effectiveness of PA solutions are highly dependent on accurate and timely analysis of the soil conditions. In this paper, a proof-of-concept towards an autonomous precision irrigation system is provided through the integration of a center pivot (CP) irrigation system with wireless underground sensor networks (WUSNs). This Wireless Underground Sensor-Aided Center Pivot (WUSA-CP) system will provide autonomous irrigation management capabilities by monitoring the soil conditions in real time using wireless underground sensors. To this end, field experiments with a hydraulic drive and continuous-move center pivot irrigation system are conducted. The results are used to evaluate empirical channel models for soil-air communications. The experiment results show that the concept of WUSA-CP is feasible. Through the design of an underground antenna, communication ranges can be improved by up to 400% compared to conventional antenna designs. The results also highlight that the wireless communication channel between soil and air is significantly affected by many spatio-temporal aspects, such as the location and burial depth of the sensors, soil texture and physical properties, soil moisture, and the vegetation canopy height. To the best of our knowledge, this is the first work on the development of an autonomous precision irrigation system with WUSNs.

Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX)

Surface energy and water vapor fluxes play a critical role in understanding the response of agro-ecosystems to changes in environmental and atmospheric parameters. These fluxes play a crucial role in exploring the dynamics of water and energy use efficiencies of these systems. Quantification of the fluxes is also necessary for assessing the impact of land use and management changes on water balances. Accomplishing these goals requires measurement of water vapor and energy exchanges between various vegetation surfaces and microclimates for long-enough periods to understand the behavior and dynamics involved with the flux transfer so that robust models can be developed to predict these processes under different scenarios. Networks of flux towers such as AMERIFLUX, FLUXNET, FLUXNET-CANADA, EUROFLUX, ASIAFLUX, and CAR-BOEUROPE have been collecting data on exchange processes between biosphere and atmosphere for multiple years across the globe to better understand the functioning of terrestrial ecosystems and their role in regional and/or continental and global carbon, water, and energy cycles, providing a unique service to the scientific community. Nonetheless, there is an imperative need for these kinds of networks to increase in number and intensity due to the great diversity among ecosystems and agro-ecosystems in species composition, physiological properties, physical structure, microclimatic and climatic conditions, and management practices. The Nebraska Water and Energy Flux Measurement, Modeling, and Research Network (NEBFLUX) is a comprehensive network that is designed to measure surface energy and water vapor fluxes, microclimatic variables, plant physiological parameters, soil water content, surface characteristics, and their interactions for various vegetation surfaces. The NEBFLUX is a network of micrometeorological tower sites that uses mainly Bowen ratio energy balance systems (BREBS) to measure surface water vapor and energy fluxes between terrestrial agro-ecosystems and microclimate. At present, ten BREBSs and one eddy covariance system are operating on a long-term and continuous basis for vegetation surfaces ranging from tilled and untilled irrigated and rainfed croplands, irrigated and rainfed grasslands, alfalfa, to Phragmites (Phragmites australis)-dominated cottonwood (Populus deltoides var. occidentalis) and willow stand (Willow salix) plant communities. The NEBFLUX project will provide good-quality flux and other extensive supportive data on plant physiology [leaf area index, stomatal resistance, within-canopy radiation parameters, productivity (yield and/or biomass), and plant height], soil characteristics, soil water content, and surface characteristics to the micrometeorology, water resources and agricultural engineering, and science community on broad spectrum of agro-ecosystems. The fundamental premise of the NEBFLUX project is to measure continuous and long-term (at least ten complete annual cycles for each surface) exchange of water vapor and energy fluxes. In addition to the scientific and research objectives, information dissemination to educate the general public and youth is another important objective and output of the network. This article describes the specific goals and objectives, basic principles, and operational characteristics of the NEBFLUX.

Crop Residue Cover Effects on Evaporation, Soil Water Content, and Yield of Deficit-Irrigated Corn in West-Central Nebraska

Competition for water is becoming more intense in many parts of the U.S., including west-central Nebraska. It is believed that reduced tillage, with more crop residue on the soil surface, conserves water, but the magnitude of water conservation is not clear. A study was initiated on the effect of residue on soil water content and corn yield at North Platte, Nebraska. The experiment was conducted in 2007 and 2008 on plots planted to field corn (Zea mays L.). In 2005 and 2006, soybean was grown on these plots. There were two treatments: residue-covered soil and bare soil. Bare-soil plots were created in April 2007. The residue plots were left untreated. In April 2008, bare-soil plots were recreated on the same plots as in 2007. The experiment consisted of eight plots (two treatments with four replications each). Each plot was 12.2 m × 12.2 m. During the growing season, soil water content was measured several times in each of the plots at six depths, down to a depth of 1.68 m, using a neutron probe. The corn crop was sprinkler-irrigated but purposely water-stressed, so that any water conservation in the residue-covered plots might translate into higher yields. In 2007, mean corn yield was 12.4 Mg ha-1 in the residue-covered plots, which was significantly (p = 0.0036) greater than the 10.8 Mg ha-1 in the bare-soil plots. Other research has shown that it takes 65 to 100 mm of irrigation water to grow this extra 1.6 Mg ha-1, which may be considered water conservation due to the residue. In 2008, the residue-covered soil held approximately 60 mm more water in the top 1.83 m compared to the bare soil toward the end of the growing season. In addition, mean corn yield was 11.7 Mg ha-1 in the residue-covered plots, which was significantly (p = 0.0165) greater than the 10.6 Mg ha-1 in the bare-soil plots. It would take 30 to 65 mm of irrigation water to produce this additional 1.1 Mg ha-1 of grain yield. Thus, the total amount of water conservation due to the residue was 90 to 125 mm in 2008. Water conservation of such a magnitude will help irrigators to reduce pumping cost. With deficit irrigation, water saved by evaporation is used for transpiration and greater yield, which may have even greater economic benefits. In addition, with these kinds of water conservation, more water would be available for competing needs.

Standardized ASCE Penman-Monteith: Impact of sum-of-hourly vs. 24-hour timestep computations at reference weather station sites

The standardized ASCE Penman-Monteith (ASCE-PM) model was used to estimate grass-reference evapotranspiration (ETo) over a range of climates at seven locations based on hourly and 24 h weather data. Hourly ETo computations were summed over 24 h periods and reported as sum-of-hourly (SOH). The SOH ASCE-PM ETo values (ETo,h,ASCE) were compared with the 24 h timestep ASCE-PM ETo values (ETo,d) and SOH ETo values using the FAO Paper 56 Penman-Monteith (FAO56-PM) method (ETo,h,FAO). The ETo,h,ASCE values were used as the basis for comparison. The ETo,d estimated higher than ETo,h,ASCE at all locations except one, and agreement between the computational timesteps was best in humid regions. The greatest differences between ETo,d and ETo,h,ASCE were in locations where strong, dry, hot winds cause advective increases in ETo. Three locations showed considerable signs of advection. Some of the differences between the timesteps was attributed to uncertainties in predicting soil heat flux and to the difficulty of ETo,d to effectively account for abrupt diurnal changes in wind speed, air temperature, and vapor pressure deficit. The ETo,h,FAO values correlated well with ETo,h,ASCE values (r2 > 0.997), but estimated lower than ETo,h,ASCE at all locations by 5% to 8%. This was due to the impact of higher surface resistance during daytime periods. Summing the ETo values over a weekly, monthly, or annual basis generally reduced the differences between ETo,d and ETo,h,ASCE. The differences suggest that using ETo,d rather than ETo,h,ASCE would result in underestimation or overestimation of ETo. Summing the ETo,d values over multiple days and longer periods for peak ETo months resulted in inconsistent differences between the two timesteps. The results suggest a potential improvement in accuracy when using the standardized ASCE-PM procedure applied hourly rather than daily. The hourly application helps to account for abrupt changes in atmospheric conditions on ETo estimation in advective and other environments when hourly climate data are available.

RESPONSE OF SOYBEAN TO DEFICIT IRRIGATION IN THE SEMI-ARID ENVIRONMENT OF WEST-CENTRAL NEBRASKA

Several factors, including multi-year drought, declining aquifer levels, and new water regulations, are contributing to reduced availability of irrigation water in the semi-arid area of west-central Nebraska. Since many farmers in this area do not have enough water to meet the seasonal water requirements of crops like corn and soybean, maximizing yield produced per unit of water under deficit irrigation conditions is becoming increasingly important. This study was conducted to quantify the grain yield response of soybean [Glycine max (L.) Merr.] to deficit irrigation, and to determine which seasonal water variables correlated best to soybean grain yield under deficit irrigation. The study was conducted during 2002 at Curtis, and 2003 and 2004 at North Platte, Nebraska. Nine deficit irrigation treatments, including different irrigation amounts and timings, were studied in 2002 and 2003, and eight treatments were studied in 2004. Soybean grain yields across years and sites were best related to the seasonal ratio of the actual crop evapotranspiration and the crop evapotranspiration when soil water was not limiting (ETd/ETw), and to the seasonal ratio of actual crop transpiration and crop transpiration when soil water was not limiting (Td/Tw). Both of these seasonal ratios were linearly related to grain yield with R2 = 0.91 when combining data for all seasons. The crop water productivity (CWP) (yield per unit of seasonal ETd) linearly increased with both ETd/ETw (R2 = 0.72) and Td/Tw (R2 = 0.72), but was best correlated to the daily positive difference between the actual and the theoretical fraction of total available soil water in the root zone that can be depleted before crop water stress occurred, accumulated for the entire season (seasonal pdiff) (R2 = 0.77). A linear relationship between the cumulative ETw and fraction of season (function of days after emergence) was found. This relationship developed for a given location could be used to extrapolate seasonal ETw for in-season irrigation management. Poor correlation was found between CWP and other variables such as total irrigation, rain + irrigation, and total water. The results of this study can provide useful information for soybean irrigators to make better management decisions under deficit irrigation conditions.

Special issue on evapotranspiration measurement and modeling

Water availability for irrigation throughout the world has been reduced in recent years due to a combination of frequent droughts and competition for water resources among agricultural, industrial, and urban users. In addition, some major agricultural areas face moderate to significant reductions of rainfall, or changes in timing of stream flow due to changes in timing of snowmelt, as a result of global climate change. Under such conditions, sophisticated irrigation water management will be required to optimize water use efficiency and maintain sufficient levels of crop productivity and quality. A key factor to achieve these targets is the estimation of actual evapotranspiration (ET). Accurate determination of ET can be a viable tool in better utilization of water resources through well-designed irrigation management programs. Reliable estimates of ET are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. ET is commonly calculated using grass or alfalfareference evapotranspiration (ETo) multiplied by grass or alfalfa-reference-based crop-specific coefficients (Kc). The Penman–Monteith combination equation is widely accepted as the best-performing method for reference evapotranspiration estimates from a well-watered hypothetical grass or alfalfa surface having a fixed crop height, albedo, and surface canopy resistance. The Kc is basically the ratio of ET to ETo where ET can be measured using a lysimeter, soil water balance approach, eddy covariance method, Bowen ratio energy balance system, or surface renewal method. Advances over the last two to three decades in instrumentation, data acquisition systems, remote data access, and the off-the-shelf availability of aforementioned ET measurement tools have significantly enhanced our understanding of ET and its relation to microclimatic conditions. Advances also enabled the availability and affordability of data for practitioners for use in irrigation management. While the reference ET and Kc approach provides a simple and convenient way to estimate crop water requirements for a variety of crops and climatic conditions, a major uncertainty in this approach is that many Kc values reported in the literature are empirical and often not adapted to local conditions. This is due to the fact that ratios of ET to ETo depend on nonlinear interactions of soil, crop and atmospheric conditions, and irrigation management practices. This consideration is especially Communicated by R. Evans.

Variable upper and lower crop water stress index baselines for corn and soybean

Upper and lower crop water stress index (CWSI) baselines adaptable to different environments and times of day are needed to facilitate irrigation scheduling with infrared thermometers. The objective of this study was to develop dynamic upper and lower CWSI baselines for corn and soybean. Ten-minute averages of canopy temperatures from corn and soybean plots at four levels of soil water depletion were measured at North Platte, Nebraska, during the 2004 growing season. Other variables such as solar radiation (Rs), air temperature (Ta), relative humidity (RH), wind speed (u), and plant canopy height (h) were also measured. Daily soil water depletions from the research plots were estimated using a soil water balance approach with a computer model that used soil, crop, weather, and irrigation data as input. Using this information, empirical equations to estimate the upper and lower CWSI baselines were developed for both crops. The lower baselines for both crops were functions of h, vapor pressure deficit (VPD), Rs, and u. The upper baselines did not depend on VPD, but were a function of Rs and u for soybean, and Rs, h, and u for corn. By taking into account all the variables that significantly affected the baselines, it should be possible to apply them at different locations and times of day. The new baselines developed in this study should facilitate the application of the CWSI method as a practical tool for irrigation scheduling of corn and soybean.

Artificial Neural Network Model as a Data Analysis Tool in Precision Farming

Spatial variation in landscape and soil properties combined with temporal variations in weather can result in yield patterns that change annually within a field. The complexity of interactions between a number of yield-limiting factors makes it difficult to accurately attribute yield losses to conditions that occur within a field. In this research, a back-propagation neural network (BPNN) model was developed to predict the spatial distribution of soybean yields and to understand the causes of yield variability. First, we developed a BPNN model by relating soybean yield to topography, soil, weather, and site factors and evaluated model predictions for the same field for independent years. We also explored the potential use of BPNN for predicting yields in independent fields. Finally, we evaluated the ability of the BPNN to attribute yield losses due to soybean cyst nematodes (SCN), soil pH, and weeds. A total of 14 input datasets with combinations of four controlling factors (topographic, soil fertility, weather, and site) were used. For each objective, data from fields in Iowa were used for training the BPNN, while a portion of the data was withheld to verify the accuracy of yield predictions. All BPNN models had fully connected feed-forward architecture with a back-propagation weight adjustment algorithm. When tested for a particular field, the BPNN captured the major patterns of yield variability in independent years; the root mean square error of prediction (RMSEP) was 14.2% of actual yield. When the BPNN was trained with inputs from five fields, the RMSEP at test sites was 11.2% of actual yield. When the BPNN was used to attribute yield losses to soil pH, SCN, and weed populations, standard errors were 92, 262, and 171 kg ha-1, respectively. The technique showed that the BPNN could predict spatial yield variability with an RMSEP of about 14%.

Soil Water Extraction Patterns and Crop, Irrigation, and Evapotranspiration Water Use Efficiency of Maize under Full and Limited Irrigation and Rainfed Settings

The effects of full and limited irrigation and rainfed maize production practices on soil water extraction and water use efficiencies were investigated in 2009 and 2010 under center-pivot irrigation near Clay Center, Nebraska. Four irrigation regimes (fully irrigated treatment (FIT), 75% FIT, 60% FIT, and 50% FIT) and a rainfed treatment were implemented. The crop water use efficiency (CWUE, or crop water productivity), irrigation water use efficiency (IWUE), and evapotranspiration water use efficiency (ETWUE) were used to evaluate the water productivity performance of each treatment. The seasonal rainfall amounts in 2009 and 2010, respectively, were 426 mm (18% below normal) and 563 mm (9% above normal). Irrigation regime impacted soil water extraction pattern, which increased with irrigation amounts. In general, the soil water extraction decreased with soil depth, and the water extraction from the top soil (0-0.30 m) accounted for the largest portion of the seasonal total water extraction as 39%, 42%, 48%, 48%, and 51% of the total extraction under rainfed, 50% FIT, 60% FIT, 75% FIT, and FIT, respectively. The rainfed treatment extracted more water from the 0.60-0.90 m and 0.90-1.2 m layers (19% and 17% of the total, respectively) than all other treatments. In general, the deepest soil layer (1.5-1.8 m) contributed about 5% to 8% to the seasonal total water extraction. The efficiency values for the same treatments varied between the years due to their dependency on the seasonal water supply, water supply impact on water extraction, climatic conditions, and their impact on yield. The CWUE increased with irrigation from 1.89 kg m-3 for the rainfed treatment to 2.58 kg m-3 for the 60% FIT in 2009 and from 2.03 kg m-3 for the rainfed treatment to 2.44 kg m-3 for the FIT in 2010. The CWUE was strongly correlated to actual crop evapotranspiration (ETa) (R2 = 0.99 in both years), irrigation amounts (R2 = 0.97 in both years), and grain yield (R2 = 0.95 in 2009 and R2 = 0.99 in 2010). The IWUE and ETWUE decreased with ETa and the irrigation amounts in 2009, while they showed the opposite trend in 2010. The IWUE ranged between 3.63 kg m-3 for FIT and 5.9 kg m-3 for 50% FIT in 2009 and between 2.52 kg m-3 for 50% FIT and 3.24 kg m-3 for 75% FIT in 2010. On average, 60% FIT resulted in the largest IWUE of 4.33 kg m-3. The measured ETWUE varied from 4.65 kg m-3 for FIT to 6.09 kg m-3 for 50% FIT in 2009 and from 5.94 kg m-3 for 50% FIT to 6.73 kg m-3 for FIT in 2010. The 60% FIT and 75% FIT had similar or greater CWUE and ETWUE than the FIT in both years. The ETWUE was usually greatest when the ETa was about 580 mm in 2009 and 634 mm in 2010, indicating that in these experimental, climate, and management conditions, the maximum ETWUE and crop water productivity can be obtained at ETa values smaller than those for the fully irrigated treatment. The 60% and 75% FIT treatments were very comparable to the fully irrigated treatment in terms of productivity performance and are viable supplemental irrigation strategies for increasing crop water productivity of maize while using (withdrawal) 40% or 25% less irrigation water under these experimental, soil and crop management, and climatic conditions.

Large-scale on-farm implementation of soil moisture-based irrigation management strategies for increasing maize water productivity

Irrigated maize is produced on about 3.5 Mha in the U.S. Great Plains and western Corn Belt. Most irrigation water comes from groundwater. Persistent drought and increased competition for water resources threaten long-term viability of groundwater resources, which motivated our research to develop strategies to increase water productivity without noticeable reduction in maize yield. Results from previous research at the University of Nebraska-Lincoln (UNL) experiment stations in 2005 and 2006 found that it was possible to substantially reduce irrigation amounts and increase irrigation water use efficiency (IWUE) and crop water use efficiency (CWUE) (or crop water productivity) with little or no reduction in yield using an irrigation regime that applies less water during growth stages that are less sensitive to water stress. Our hypothesis was that a soil moisture-based irrigation management approach in research fields would give similar results in large production-scale, center-pivot irrigated fields in Nebraska. To test this hypothesis, IWUE, CWUE, and grain yields were compared in extensive on-farm research located at eight locations over two years (16 site-years), representing more than 600 ha of irrigated maize area. In each site-year, two contiguous center-pivot irrigated maize fields with similar topography, soil properties, and crop management practices received different irrigation regimes: one was managed by UNL researchers, and the other was managed by the farmer at each site. Irrigation management in farmer-managed fields relied on the farmers’ traditional visual observations and personal expertise, whereas irrigation timing in the UNL-managed fields was based on pre-determined soil water depletion thresholds measured using soil moisture sensors, as well as crop phenology predicted by a crop simulation model using a combination of real-time (in-season) and historical weather data. The soil moisture-based irrigation regime resulted in greater soil water depletion, which decreased irrigation requirements and enabled more timely irrigation management in the UNL-managed fields in both years (34% and 32% less irrigation application compared with farmer-managed fields in 2007 and 2008, respectively). The average actual crop evapotranspiration (ETC) for the UNL- and farmer-managed fields for all sites in 2007 was 487 and 504 mm, respectively. In 2008, the average UNL and average farmer-managed field had seasonal ETC of 511 and 548 mm, respectively. Thus, when the average of all sites is considered, the UNL-managed fields had 3% and 7% less ETC than the farmer-managed fields in 2007 and 2008, respectively, although the percentage was much higher for some of the farmer-managed fields. In both years, differences in grain yield between the UNL and farmer-managed fields were not statistically significant (p = 0.75). On-farm implementation of irrigation management strategies resulted in a 38% and 30% increase in IWUE in the UNL-managed fields in 2007 and 2008, respectively. On average, the CWUE value for the UNL-managed fields was 4% higher than those in the farmer-managed fields in both years. Reduction in irrigation water withdrawal in UNL-managed fields resulted in