Journal of Irrigation and Drainage Engineering

The impact of irrigation on groundwater quality is influenced by climate, topography, geology, soils, geohydrology, crops, and agricultural practices. Since the early 1950s, the irrigated crop acreage in the Corn Belt and Lake States has increased markedly. Irrigation in these regions is concentrated in areas underlain by sandy soils with low moisture‐holding capacities, where supplemental moisture and relatively heavy applications of agrichemicals are needed to achieve economically viable crop yields. Due to the high hydraulic conductivities and low attenuation capacities of sandy soils, shallow aquifers underlying these areas are particularly susceptible to contamination with nitrates and stable, soluble pesticides. Present and potential problems associated with irrigation in these states are illustrated by available case studies from the Central Sand Plain of Wisconsin.

Irrigated agriculture in the humid region has resulted in more intensive management including crop production and the associated increase in fertilizer and pesticide use. Multiple cropping in most of the southeast (Alabama, Florida, Georgia, and South Carolina) and Delta (Arkansas, Louisiana, and Mississippi) states increases the demand for water and agricultural chemicals. Pesticide usage in the 48 states and the District of Columbia totaled 299,829,159 kg of active ingredient (AI) by 1982. Agricultural chemicals may percolate to aquifers in some soils and geologic formations resulting in groundwater contamination. Groundwater fluctuations are related to irrigation. Groundwater quality data are used to show the trend in quality related to irrigated agriculture and cropping systems. Areas with specific groundwater problems such as salt‐water intrusion and pesticide levels are identified. A total of 17 pesticides have been reported in groundwater in the United States and four of these were found in the southeast and Delta states. Data show that less that 1% of wells sampled in the southeast and Delta states had nitrate concentrations exceeding 10 mg/L (drinking water standard). Degradation of surface water quality relative to irrigation is discussed.

The northeastern and Appalachian states have a diverse array of geology, soils, and climate. Irrigation is concentrated in a few states, with the largest irrigation area in the Coastal Plain soils. Most of these soils are sandy and very susceptible to leaching. The groundwater recharge area in the Coastal Plain is directly above the aquifer. Most of the increase in irrigation has been to irrigate corn in Delaware, Maryland, and Virginia. Groundwater studies have been conducted in Delaware, Maryland, and New York in irrigated regions. Nitrate and aldicarb leaching has occurred on‐Long Island, New York, where potatoes are grown. Poultry manure is the largest source of nitrate contamination of the water table aquifer on the Delmarva Peninsula in Maryland. Both pesticide and nitrate leaching under irrigation have been studied in Delaware. A total water management system that can be used for both drainage and subsurface irrigation has been developed in North Carolina. The system will increase crop yields and has the potential for reducing nitrates by water table control.

The Groundwater Loading Effects of Agricultural Management Systems (GLEAMS) model was applied to estimate the effects of: (1) Soil; (2) planting date; (3) irrigation level; and (4) pesticide characteristic on pesticide leaching below the root zone of representative coarse‐grained soils. Climate/application/pesticide‐characteristic interactions are shown to significantly affect pesticide losses, whereas irrigation practice has little effect. Persistent and mobile compounds exhibit the highest losses.

Geostationary Operational Environmental Satellite (GOES) visible and thermal infrared data, in conjunction with the Griffith‐Woodley method, are used to estimate the rainfall in Florida. Both the life history techniques (LHT) and streamline techniques (SLT) of the Griffith‐Woodley method are studied. The results show that the satellite data are useful for estimating both the volume and areal distribution of rainfall, which are very difficult to assess using the conventional rain‐gauge method. The satellite rainfall estimation is well correlated with the gauge rainfall measurement. The coefficients of determination $(\mathrm{r2}⊐)$ range from 0.76 to 0.82 in the LHT and from 0.56 to 0.60 in the SLT. The paired t‐test is able to differentiate the performance difference between the LHT and SLT, and the rainfall estimated by the LHT was significantly higher than that by the SLT. The LHT appears to be more suitable for estimating rainfall under Florida conditions, mainly because of the rainfall increment rate between the satellite estimation and gauge measurements is near 1.0 in the LHT but not in the SLT. A further study is strongly recommended concerning the possibility of improving the SLT application.

The analysis quantified the energy required to deliver pressure head for the area irrigated by an end gun. The energy actually used to apply water to the corner while the end gun was on and the extra energy used while the end gun was off were estimated. With the end gun off there is increased application of water under the lateral. Energy use associated with this increased application was estimated. The pressure head cost ratio (with end gun/without end gun) was in direct proportion to the capacity ratio (end gun/total system). The values ranged from a cost ratio of 1.73 for a capacity ratio of 0.05 to 3.69 for a capacity ratio of 0.20. Speed modification and flow‐pressure regulation with the end gun off were also considered. Energy reduction was not significant for these modifications.

An irrigation scheduling model for a center‐pivot irrigation machine was developed to maximize returns in humid areas. A corn growth‐ and yieldsimulation model was incorporated to predict the end‐of‐season yield. The irrigation decision process for an irrigation machine was defined and formulated mathematically into a model that sequentially optimizes the irrigation schedule. The problem of optimal scheduling of an irrigation machine was divided into a singlefield problem and a multifield problem. Each problem was formulated as a decision‐tree problem and was solved using tree enumeration techniques. The model was coded into a computer program written in PASCAL that uses the corn simulation model (written in FORTRAN) as a subroutine. The model can aid in making the daily irrigation decision and the allocation of limited water resources when irrigating different fields under the same center‐pivot machine.

Application and results of a short‐range irrigation‐scheduling model for center‐pivot machines are described. The irrigation‐decision model sequentially optimizes the irrigation schedule to maximize net return from a center‐pivot irrigation machine. Application of the model was done by using field experiments conducted in previous years and by conducting an initial field experiment. Afterthe‐fact simulation of the irrigation‐decision process using the optimal model was done for the field experiments conducted in previous years, and the results were compared with the actual field results. In the field experiment, the optimal scheduling model was compared with a conventional irrigation‐scheduling method. The net return from corn under a simulated center‐pivot system was increased by 7.8% over the conventional scheduling method and 10.1% over no irrigation. It was concluded that the model can aid the daily irrigation decision and the allocation of limited water supplies among competing crops under the same irrigation machine.