2 (April 1999) The Ohio State University Press. Submitted: 9/9/97. Revised ...... The National Water WPII Association, Dublin, Ohio. Kittl
Chansheng He
Assessing Regional Crop Irrigation Requirements and Streamflow Availability for Irrigation Development in Saginaw Bay, Michigan Spatial and temporal variability of soil, crorJ, and climate significantly affects the estimates of regional irrigation requirements. This paper incorporates soil association data and multiple-station, multiple-year climate data into four simulation models, CERES-MAIZE, SOYGRO, BEANGRO, and YIELD to account for the spatial and temporal variability of the input parameters in estimating the evapotranspiration rates and irrigation requirements of corn, drybean, soybean, and sugarbeet production in the Saginaw Bay basin, Michigan. The Thiessen method was used to delineate the spatial coverage of the weather stations in the study watershed. The results of the simulated crop irrigation requirements at the soil association level were multiplied by the weights of each soil association area to derive regional irrigation requirements. The availability of streamflow at different exceedence probabilities was evaluated to detennine the maximum irrigation area the stream is able to sustain without causing water quality degradation. Through a case study of the Saginaw Bay irrigation development, this paper demonstrates that the spatial mul temporal variability of soil, crop, and climate can be well represented in the simulation models to provide more realistic simulation results in sulJJWrf of irrigation decision making.
Water resource planners dealing with irrigation development often face the following questions: How much water is needed for irrigation supply? Where does the water come from? What crops should be irrigated? Which crop fields are suitable for irrigation? Addressing such questions involves establishing the relevant parameters of irrigation water requirements, availability of dependable sources of water, optimal crop mix, and spatial distribution of irrigable crop fields. This paper develops a framework for integrating crop simulation models and water balance equations with geographic information systems (GIS) to address this class of water resource problems through a case study of the The author acknowledgl'S the Michigan State University Institute of WaiN Hewareh and tlw USDA Natural HPsouree ConsPrvatiou Serviee for providing partial llnaneial support to this study. He also thanks the anonymous reviewl•rs for their constructive commPnts on this paper.
Clumsheng He is assistant professor of geography. Westem Michigan University. Geographical Analysis, Vol. 31, No. 2 (April 1999) The Ohio State University Press Submitted: 9/9/97. Revised version accepted: 10/20/98.
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Geographical Analysis
Soils Land Use Management
Economic Info.
Fll Hey Pipestmw-Kingsville-Sangatuck-Wixmn Metamnra-Binnnt-l't>wanw Tappan-LIIidt•au:y is ddilu·d ;IS tlw r.\tio of tht• \'olnmt• of irrigation w.ltt•r used to nH·t·t tilt' irrigation n••tnin·nwnl'\ of an irri)4.11t•tl aH•a to tlw \'olumt' of water tlt•lin-rt•d to tlw an·a (jt'll'H'll, Bnrnmn. ami Allc·n JHUO; Doon•nhos and Pruitt 1077).
C. Management Information. Management inputs to the simulation models include crop varieties, planting and harvesting dates, plant population, irrigation efficiency, and fertilizer applications. These data were acquired from the Michigan State University Cooperative Extension Service (LeCureux 1990) and the Saginaw Valley Bean and Beet Research Farm (Christenson, Horny, and Fleischmann 1989). The management input parameters are summarized in Table 2. In simulating irrigated crop production, automatic irrigation with an efficiency of 75 percent was assumed, that is, irrigation water was immediately provided to crops whenever there was a need. The 2.'5 percent loss of irrigation water includes leaching and miscellaneous losses such as return flow. The four crops considered in the study are assumed to be pest and disease frt>e. D. Model Ollt]mts. The model outputs used in this study include daily and seasonal ET rates, the irrigation water requirement, irrigation date, plantextractable soil water, the above-ground biomass, and crop yields.
3. Spatial and Temporal Variability of lllpllt Parameters The spatial and temporal variability of input parameters to the simulation models significantly affects the estimates of crop ET and irrigation water requirements. Exclusion of the spatial variability in calculating ET could lead to errors with a standard deviation of 40 percent at the regional scale (IIashimi, Garcia, and Fontane 1995). This paper incorporates the spatial and temporal variability of input parameters by using the soil association data and multipleyear, multiple-station climatic data. PC ARC/INFO was used to delineate the spatial variability of climatic data (temperature and precipitation), and soil associations. There are five weather stations and twelve soil associations in the study area (Figures 3 and 4). Four ( Bad Axe, Caro, Saginaw Consumer Power, and Sandusky) of the five weather stations are located either within or adjacent to the study area and were used to compute the irrigation water requirements of corn, soybeans, and drybeans. Simulations were separately run based on the daily climatic data from each of these four weather stations for each of the twelve soil associations in the Cass River Watershed to account for both the spatial and temporal variation of the climate and soil in order to obtain more realistic estimates of crop ET rates and irrigation requirements. Delineation of the spatial coverage for each of the Bad Axe, Cnro, Saginaw Consumer Power, and Sandusky weather stations was done in PC Arc/Info using the Thiessen method based on the locations of these stations (Bras 1990) (Figure 4). The Thiessen polygons were then intersected with the soil association file in PC Arc/Info to determine the proximity of each of the twelve soil associations to those polygons and the percentage of each soil association area in
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178
Geographical Analysis
TABLE ;j SinmlatPd An•ragt• Irrigation \VatPr 1\eqnin•mt·nts (mm) of Com, Dryllf'ans, and SovhPans forthr~ht·ans
·------·--
·----~----
JIll~
Au~
Jn•w
)Ilk
Au~
jllllt'
jllh
:\u~
!J(i 1>2 1>.5 H2 H-l 79
60 .54 .5:)
I 17 12 2(i
92 117
HI> f))
)Of)
\),')
0 16 II Hi 0 12
10.5 106 105 110 10:3
66 63 SH 63
)),')
.56
()
10.'5 10:3 10-l JOH
,')f)
--~---------
10.51-I\JHO
ublishing Company. Chow, V. T., D. R. Maidment, and L. W. Mays (191lll). Applied Hydrology. New York: McGraw-Hill Book Company. Christenson, D. R, P. Horny, and D. Fleischmann (1989). "Saginaw Valley Bean and Beet Hesl'arch Fann and Related Bean and Beet Research Report." Michigan State University Agricultural Experiment Station, East Lansing. Doorenhos, J .. and A. H. Kassam. (1979). "Yield Response to Water." FAO Irrigation and Drainage Paper 33, Home. Doorenbos, J., and W. 0. Pruitt (1977). "Guidelines for Predicting Crop Water Requirements." FAO Irrigation and Drainage Paper 24, Rmne. Fulcher, G. W., S. A. Miller, and R. Van Til {191l6). "Effects of Consumptive Water Uses on Drought Flows in the Hiver Haisin." Michigan Department of Natural Resources, Lansing. Giese, G. L., and R. H. M
