Limited water supply in many parts of the United States, including the Mid-south and Mississippi in particular, is a serious problem in agriculture (USGS, 2007). The aquifer level under the alluvial soil to the immediate east of the Mississippi River (Mississippi River Alluvial Aquifer) has been declining (YMD, 2007). A declining water supply has possibly been made worse due to the droughts of 2006 and 2007. Additionally, policies in the future may further restrict usage of water for irrigating crops. Also, the recent interest in alternative fuels may create different crop mixes in the Delta region creating different water demands on the alluvial aquifer. Therefore, a method of evaluating the water needs of different crops and the value of water to each crop similar to Banerjee et al. (2007) would provide agricultural producers with valuable information.

Policymakers also need better tools to devise programs and policies to deal with such water shortages. A model is proposed to estimate irrigation water demand and hence estimate water value through crop acreage committed to irrigation. This model combines a land allocation model with actual water use data for each crop. The land allocation model is based on a portfolio type analysis that not only combines measures of risks and returns, but also allows for agronomic and other influences.

The overall objective of this study is to develop a method of precisely forecasting agricultural water demand for irrigating corn and cotton in Mississippi. In particular, the following steps let us fulfill the basic objective of developing such a forecasting method:

   1. Develop an econometric model of crop irrigated acreage allocation based on expected prices, expected yields, expected crop returns, variances and covariances of crop returns, and total irrigated acres by crop.

   2. Employ the acreage forecasts from the estimated econometric model to the relevant actual water use data in Mississippi to estimate water demand by crop, and compare and contrast the forecast results from this econometric approach against those from the traditional/engineering approach that uses the initial crop distribution to forecast water demand.

   Steps 1 and 2 allow a precise estimation of crop irrigated acreage a year in advance, thus enabling us to calculate the value of water saved in terms of irrigated acreage. 

   3. From the above water demand estimates for the econometric and engineering approaches, use simulated forecasting scenarios to determine responsiveness of the econometric approach vis-à-vis the engineering approach to certain economic and institutional variables, and calculate “slippage” – a measure to distinguish between the two approaches. The value of water saved by differing the crop mix allows the calculation of the value per acre-inch of water on a crop-by-crop basis. Calculation of “slippage” (one minus the ratio of the econometric change to the physical change in total water demand) enables us to visualize this difference as in related literature (Tareen, 2001; Banerjee, 2007).

Data for this study was primarily obtained from U. S. Department of Agriculture – National Agricultural Statistics Service (USDA-NASS) (2007) (data on state planted and irrigated acres by crop, and yields by crop), Commodity Research Bureau (data on futures prices by crop), U. S. Department of Agriculture – Economic Research Service (USDA-ERS) (2007) (data on variable costs by crop), and Yazoo Mississippi Delta (YMD) Joint Water Management District (2007) (data on water use by crop). A time series for Mississippi starting in 1984 and ending in 2003 was chosen for the sample. Years 2004 and 2005 were chosen for out-of-sample forecasts. Latest irrigated acreage data available were only until 2005 for comparison.

Preliminary results show, assuming there was a 50,000 acres policy-induced decrease in irrigation in 2006 over 2005, the differences between the physical and econometric models would result in an increase of water savings of around 24%, as measured by “slippage,” by shifting water out of irrigation from other crops (e.g., rice and soybeans) into corn and cotton. [The same for a policy-induced 33,000-acre reduction (FRDPA, 2001) in a study on the Flint River Basin in Georgia was between 19% and 24%, depending on if acres were reduced simultaneously with prices, like in the current study, or sequentially (Banerjee et al., 2007).] With higher prices resulting in a major shift in acres from cotton and other crops to corn in 2007, this percentage savings of water is presumed to be more pronounced for a study using current commodity prices. 

A physical/engineering model would not consider any changes in economic or institutional conditions. Hence it would not account for changes in crop mix over time due to economic or institutional changes. Our model takes into account such changes and reallocates irrigated acres in the new economic or institutional regime by accounting for substitution and expansion effects.  

Thus, with the successful introduction and implementation of the proposed model, farmers will have a better and more scientific method of anticipating water demand and value for their crops not only in the wake of a short supply due to natural causes, but also due to government policy that restricts water use. Policymakers will have a more precise method to calibrate acreage reduction programs to meet targeted levels for reductions in agricultural water use.

References

Banerjee, S.B., I.Y. Tareen, L.F. Gunter, J. Bramblett, and M.E. Wetzstein. “Forecasting Irrigation Water Demand: A Case Study on the Flint River Basin in Georgia.” Journal of Agricultural and Applied Economics 39,3(December 2007):641-655.

Commodity Research Bureau (CRB), CRB InfoTech CD – Futures, 2007.

Flint River Drought Protection Act (FRDPA). House Resolution 17, Georgia General Assembly, 2001.

United States Department of Agriculture – Economic Research Service (USDA-ERS). “Briefing Room Farm Income and Costs: Commodity Costs and Returns.” Website: http://www.ers.usda.gov/briefing/farmincome/costsandreturns.htm (accessed Oct 1, 2007).

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United States Department of Agriculture – National Agricultural Statistics Service (USDA-NASS). Website: http://www.usda.gov/nass/ (accessed Oct 1, 2007).

United States Geological Survey (USGS). Website: http://ms.water.usgs.gov/ms_proj/eric/delta/index.html (accessed Oct 1, 2007).

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Yazoo Mississippi Delta (YMD) Joint Water Management District. Website: http://www.ymd.org/ (accessed Oct 1, 2007).