An Analysis of the Role of Tile-Drained Farmland Under Alternative Nitrogen Abatement Policies

Agricultural nitrogen is a major contributor to Gulf of Mexico hypoxia, and research has shown that agricultural subsurface tile drainage is a major carrier of nitrogen from croplands to streams and rivers. This study compares the results of abating nitrogen under a retired-land minimization policy with those of a new revenue-maximizing policy, paying particular attention to the role of tile-drained land. Findings reveal the retirement-minimizing policy resulted in more tile-drained land being retired and less being fertilizer-managed than was optimal under the net-return maximizing policy. Also, it led to a greater economic burden being shouldered by tile-drained land. Under both cases, tile drainage dominated the abatement process.abatement, ADAPT, drainage, hypoxia, nitrogen, Crop Production/Industries, Land Economics/Use,

Targeting Agricultural Drainage to Reduce Nitrogen Losses in a Minnesota Watershed

Agricultural nitrogen losses are the major contributor to nitrogen loads in the Mississippi River, and consequently, to the existence of a hypoxic, or dead, zone in the Gulf of Mexico. Focusing on two small agricultural watersheds in southeast Minnesota, simulation results from the Agricultural Drainage And Pesticide Management (ADAPT) model were combined with a linear-optimization model to evaluate the environmental and economic impact of alternative land-use policies for reducing nitrogen losses. Of particular importance was the studys explicit focus on agricultural subsurface (tile) drainage, which has been identified as the major pathway for agricultural nitrogen losses in the upper Midwest, and the use of drainage-focused abatement policies. Results indicate that tile-drained land plays a key role in nitrogen abatement, and that a combined policy of nutrient management on tile-drained land and retirement of non-drained land is a cost-effective means of achieving a 20- or 30-percent nitrogen-abatement goal. Results also indicate that although it is cost-effective to abate on tile-drained land, it is not cost-effective to undertake policies that plug or remove tile drains from the landscape, regardless of whether the land would be retired or kept in production. Therefore, results imply that although tile-drained land is a major source of nitrogen lost to waterways, it is not cost-effective to remove the land from production or to remove the drainage from the land. Because of its value to agricultural production, it is better to keep tile-drained land in production under nutrient management and focus retirement policies on relatively less-productive, non-drained acres.Environmental Economics and Policy, Land Economics/Use,

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

Forage Potential of Summer Annual Grain Legumes in the Southern Great Plains

Winter wheat (Triticum aestivum L.) and perennial warm-season grasses are the primary forage resources for grazing yearling stocker cattle (Bos taurus) in the US Southern Great Plains (SGP). However, low nutritive value of perennial grasses during mid to late summer limits high rates of growth by stocker cattle. In response, there has been a continued search for plant materials with the potential to provide forage high in crude protein (CP) and digestibility during August through September. A broad range of under-utilized legume species that are grown as grain crops in Africa, India, and South and Central America may have some capacity to serve as high quality pasture or harvested forage in the SGP. However, any crop selection must account for limitations related to unpredictable summer rainfall amounts and patterns, and the frequent occurrence of prolonged drought. Further, any selection should not create water deficits for following winter wheat, the primary forage and grain crop in the region. This article summarizes a small subset of the broad range of underutilized grain legumes (pulses) which exist worldwide and soybean [Glycine max (L.) Merr.] that may have capacity to serve as high quality forage for late-summer grazing. Bringing these crops into forage–stocker production systems could improve the overall system effectiveness, in addition to providing other ecosystem services (e.g., ground cover, grain crops)

ET mapping for agricultural water management: present status and challenges

Evapotranspiration (ET) is an essential component of the water balance. Remote sensing based agrometeorological models are presently most suited for estimating crop water use at both field and regional scales. Numerous ET algorithms have been developed to make use of remote sensing data acquired by sensors on airborne and satellite platforms. In this paper, a literature review was done to evaluate numerous commonly used remote sensing based algorithms for their ability to estimate regional ET accurately. The reported estimation accuracy varied from 67 to 97% for daily ET and above 94% for seasonal ET indicating that they have the potential to estimate regional ET accurately. However, there are opportunities to further improving these models for accurately estimating all energy balance components. The spatial and temporal remote sensing data from the existing set of earth observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation management purposes, especially at a field scale level (~10 to 200 ha). This will be constrained further if the thermal sensors on future Landsat satellites are abandoned. However, research opportunities exist to improve the spatial and temporal resolution of ET by developing algorithms to increase the spatial resolution of reflectance and surface temperature data derived from Landsat/ ASTER/MODIS images using same/other-sensor high resolution multi-spectral images

Modeling Groundwater Levels on the Calera Aquifer Region in Central Mexico Using ModFlow

A conceptual model for the Calera Aquifer has been created to represent the aquifer system beneath the Calera Aquifer Region (CAR) in the State of Zacatecas, Mexico. The CAR area was uniformly partitioned into a 500 X 500 m grid generating a high resolution model that represented the natural boundaries of the aquifer. A computer model was calibrated and validated to verify output from the model corresponding to situations that matched the historical aquifer performance. Predicted groundwater levels were compared with measured data collected from nine observation wells between 1954 and 2004 to evaluate model performance. The main objective of this study was to develop and evaluate a groundwater modeling system using ModFlow-2000 for the CAR. Performance statistics indicated that the model performed well in simulating historic groundwater levels in the central part of the CAR where irrigated agriculture was concentrated. Results evaluation yielded average coefficients of determination of 0.81 and 0.67 and root mean square error values lower than 25.1 m and 25.9 m for the calibration and validation processes, respectively. These results are indicative of a good agreement between predicted and observed groundwater levels. However, further improvements in the conceptual model may be needed to improve predictions in other parts of the CAR for evaluating alternative groundwater management strategies

Assessment of Alternative Agricultural Land Use Options for Extending the Availability of the Ogallala Aquifer in the Northern High Plains of Texas

The Ogallala Aquifer has experienced a continuous decline in water levels due to decades of irrigation pumping with minimal recharge. Corn is one of the major irrigated crops in the semi-arid Northern High Plains (NHP) of Texas. Selection of less water-intensive crops may provide opportunities for groundwater conservation. Modeling the long-term hydrologic impacts of alternative crops can be a time-saving and cost-effective alternative to field-based experiments. A newly developed management allowed depletion (MAD) irrigation scheduling algorithm for Soil and Water Assessment Tool (SWAT) was used in this study. The impacts of irrigated farming, dryland farming, and continuous fallow on water conservation were evaluated. Results indicated that simulated irrigation, evapotranspiration, and crop yield were representative of the measured data. Approximately 19%, 21%, and 32% reductions in annual groundwater uses were associated with irrigated soybean, sunflower, and sorghum, respectively, as compared to irrigated corn. On average, annual soil water depletion was more than 52 mm for dryland farming scenarios. In contrast, only 18 mm of soil water was lost to evaporation annually, for the long-term continuous fallow simulation. The fallow scenario also showed 31 mm of percolation for aquifer recharge

Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains

Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate regional evapotranspiration (ET) maps would provide valuable information on actual crop water use. In this study, METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration), a remote sensing based ET algorithm, was evaluated for mapping ET in the THP. Two Landsat 5 Thematic Mapper images acquired on 27 June (DOY 178) and 29 July (DOY 210) 2005 were used for this purpose. The performance of the ET model was evaluated by comparing the predicted daily ET with values derived from soil moisture budget at four commercial agricultural fields. Daily ET estimates resulted with a prediction error of 12.7±8.1% (mean bias error ± root mean square error) on DOY 178 and -4.7±9.4% on DOY 210 when compared with ET derived from measured soil moisture through the soil water balance. These results are good considering the prevailing advective conditions in the THP. METRIC have the potential to be used for mapping regional ET in the THP region. However, more evaluation is needed under different agroclimatological conditions

Radiometer Footprint Model to Estimate Sunlit and Shaded Components for Row Crops

Th is article describes a geometric model for computing the relative proportion of sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil appearing in a circular or elliptical radiometer footprint for row crops, where the crop rows were modeled as continuous ellipses. Th e model was validated using digital photographs of row crops, where each component was determined by supervised classification. Root mean squared errors (RMSE) between modeled and observed components were 35, 49, 29, and 44% of observed means for sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil, respectively. Mean bias errors (MBE) were, respectively, –5.6, 16.6, –4.0, and –0.5% of observed means. Th e continuous ellipse model was compared to the commonly used clumping index model, where the latter estimates total vegetation and total soil, but does not resolve these into their sunlit or shaded components and does not account for radiometer footprint shape dimensions. Th e continuous ellipse model resulted in RMSE for vegetation and soil of 22 and 19%, respectively, whereas the clumping index model resulted in respective RMSE of 37 and 31%. Th e continuous ellipse model had MBE of 3.3 and –2.6% for vegetation and soil, respectively, which was slightly greater than the respective MBE of –1.5 and 1.4% for clumping index model. Given the model sensitivity and uncertainty of leaf area index (LAI), the RMSE and MBE resulting from the continuous ellipse model would not be expected to be less than 20% of the observed means, and model performance was therefore deemed reasonable in this study