Drainage design coefficients for eastern United States

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Abstract

The development of drainage simulation models has made it possible to quantitatively describe the performance of drainage systems, including the effects of design parameters on yields. While this was a primary goal of drainage researchers 40 years ago, it is no longer sufficient. Currently, the effect of drainage on nutrient loads and surface water quality is of equal or greater importance to production goals. Limited field data and modeling results indicate that nitrogen (N) loss in drainage water is proportional to subsurface drainage intensity (DI). This implies that the drainage system should be tailored to soil and site conditions, such that the DI is as small as possible. While simulation models can be used to determine drain depth and spacing required to maximize yields or profits for a specific site, the modeling expertise and/or the extensive data required are often not available. Simple approaches are still needed for estimating drain spacing and depth. The Hooghoudt equation has been used for many years for this purpose. Its application requires knowledge of the design drainage rate, which has not been defined for many locations in the US.

A simulation study was conducted to determine the drain spacing corresponding to predicted maximum economic return for corn production on four soils at 10 locations in eastern United States. The drainage intensity (cm/day) corresponding to the optimum drain spacing was defined as the design drainage rate (DDR). DDR varied with growing season rainfall and ranged from an average (across the four soils) of 0.58 cm/day at Toledo, OH to 1.61 cm/day at Baton Rouge, LA. Variation of DDR among the four soils was least for the low rainfall locations and highest where growing season rainfall was high. The regression equation, DDR = 0.004P  1.1, may be used to estimate DDR (cm/day) in terms of growing season rainfall, P (mm). These results were obtained for a drain depth of 1 m and surface depressional storage of 2 cm. Additional research is needed to test the relationships, and/or develop new equations, for additional drain depths and surface storages.

Introduction

This paper was prepared as a contribution to a special issue of Agricultural Water Management honoring former editors Jan van Schilfgaarde, Herman Bouwer and Jans Wesseling. All three were pioneers in the development and application of the theory of agricultural drainage. At the time of their most active work in drainage, there were two primary objectives in drainage research. One was to mathematically describe the performance of drainage systems in terms of soil properties, drainage design parameters (drain depth, spacing, and characteristics of the drain), site parameters, and weather conditions. The second was to quantitatively relate the design of agricultural drainage systems to crop yields and profits. The honorees made significant contributions to the first of the objectives and were instrumental in designing and promoting research strategies to achieve the second. For example, van Schilfgaarde (1965) developed analytical methods to use long-term weather data to predict the frequency of high water table conditions and to thereby design systems on a probabilistic basis of risk. This was a precursor to the drainage simulation models, such as SWATRE (Feddes et al., 1978) and DRAINMOD (Skaggs, 1978), that were developed later to predict the performance of drainage systems and the effects of drainage design on yields and profits. The models may be used to simulate the effect of drainage system design on soil water status and crop yields for long periods of climatological record (e.g., 50 years), providing a basis for selecting a design to maximize yields or profits on either an average or a recurrence interval basis (Skaggs and Chescheir, 1999).

As researchers developed methods to optimize drainage system designs, the objectives changed. Now the environmental impacts of drainage systems are as important, and in some cases more important, than agricultural production goals. Drainage has traditionally been viewed positively as an agricultural production practice that has dramatically increased yields and profits on previously marginal lands. However, there is currently great concern about its environmental impacts. Drainage has resulted in the loss of over 50% of the wetlands in the continental US. Current federal and state laws prohibit the drainage of wetlands. While there is scientific evidence that subsurface drainage reduces surface runoff (Robinson and Rycroft, 1999), and the loss of sediment and phosphorus to surface waters (Bottcher et al., 1981, Gilliam et al., 1999), there are still legitimate concerns about the impacts of drainage on water quality. There is strong evidence that artificial drainage increases nitrogen (N) losses to surface waters (Baker et al., 1975, Gilliam et al., 1999, Dinnes et al., 2002). In the US, nitrogen losses to surface waters are of great concern on a national scale. Scientists have concluded that large areas of hypoxia in the northern Gulf of Mexico are due to excessive N derived primarily from agricultural runoff via the Mississippi River (Rabalais et al., 1996, Rabalais et al., 1999, Turner and Rabalais, 1994, Sen Gupta et al., 1996).

Methods are needed to design drainage systems to address both agricultural production goals and environmental impacts. This paper briefly reviews the effect of drainage design on N losses to surface waters. There is evidence that such losses can be reduced by minimizing subsurface drainage intensity as much as possible. It is possible to use current simulation models, with detailed input data on soil properties, climate, crop, and site parameters, to tailor the design of a drainage system to maximize agricultural returns for a specific site (Skaggs and Chescheir, 1999). However, the required modeling expertise and/or input data are often not available, and simple, easy to use methods are needed. One such method is to use the steady state Hooghoudt equation (Raats and van der Ploeg, 2005) to determine drain depth and spacing in terms of the soil hydraulic properties and a design drainage rate, which depends on crop and other factors, including climate. The Hooghoudt equation has been applied for drainage design in both irrigated and arid areas for over 50 years (Luthin, 1978). This approach ignores most of the processes and interactions considered in simulation models, but it can be easily used to estimate drainage design parameters. The main obstacle to its application is the lack of appropriate design drainage rates (referred to herein as DDR) for different crops and locations. This paper presents results of a DRAINMOD simulation analysis to estimate DDR values for corn (Zea mays) production in the eastern United States.

Section snippets

Effect of drainage intensity on nitrogen loss in drainage water

Most of the drainage research in the US is currently directed at the reduction of nutrient losses, specifically nitrogen and phosphorus, to surface waters. Nitrogen in the nitrate form (NO3-N) is mobile in the soil water and moves with subsurface drainage to surface outlets. There is evidence that NO3-N losses from drained lands increase with drainage intensity (DI). That is, NO3-N losses tend to increase as the spacing between drains decreases and as the drain depth increases. For example,

A simple approach

Based on results shown in Fig. 1, a simple approach for reducing NO3-N losses to surface waters is to minimize drainage intensity as much as practical. That is, the drainage system should be designed to remove only the minimum amount of water necessary for producing the crop, not more. Existing simulation models can be used to determine depth and spacing for such designs. While this approach requires detailed information on soil properties, weather data and crop related inputs, it can be used

Methods

DRAINMOD (Skaggs, 1978) was used to simulate hydrology and predict annual crop yields for continuous corn production at 11 locations in the eastern United States. A summary of the locations and key climatic data is given in Table 1. The first six locations in Table 1 are in the North Central region of the USA where subsurface drainage is used on about 20 million ha of agricultural land. The other five locations are scattered throughout the eastern half of the USA. Simulations were conducted for

Results and discussion

Predicted 50-year average relative corn yields for each of the four soils at Urbana, Illinois are plotted as a function of drain spacing in Fig. 4. The relative yield is defined as the ratio of actual yield, as affected by soil water factors, to the potential yield. The potential yield is the average yield that would be obtained if soil water stresses are eliminated; that is, the yield that would be obtained if the crop is planted on time and there are no stresses due to either excessive or

Summary

Artificial or improved drainage is required for crop production on large areas of some of the world's most productive soils. Drainage systems should be designed to fit the soil, crop and climatological requirements for each site. Simulation models can be used to tailor drainage system designs for specific soil properties and site characteristics, but simpler methods are needed for cases where modeling expertise and/or model inputs are not available. This paper develops design drainage rates

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