Optimal estimation of irrigation schedule - An example of quantifying human interferences to hydrologic processes

Advances in Water Resources

Volumn 30, Issue 8, 2007, Pages 1844-1857

  Wang, Dingbao ^a   Cai, Ximing ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Data assimilation; Evapotranspiration; Genetic algorithm; Human interferences; Irrigation; Uncertainties

Indexed keywords

COMPUTER SIMULATION; EVAPOTRANSPIRATION; GENETIC ALGORITHMS; HYDROLOGY; KALMAN FILTERS; MATHEMATICAL MODELS; OPTIMIZATION; SCHEDULING; WATER MANAGEMENT;

DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; HUMAN INTERFERENCE; WATER AVAILABILITY ASSESSMENT; WATER USE;

IRRIGATION;

COMPUTER SIMULATION; EVAPOTRANSPIRATION; GENETIC ALGORITHMS; HYDROLOGY; IRRIGATION; KALMAN FILTERS; MATHEMATICAL MODELS; OPTIMIZATION; SCHEDULING; WATER MANAGEMENT;

ANTHROPOGENIC EFFECT; EVAPOTRANSPIRATION; GENETIC ALGORITHM; HYDROLOGICAL CYCLE; IRRIGATION; KALMAN FILTER; UNCERTAINTY ANALYSIS; WATER AVAILABILITY; WATER USE;

EID: 34248217009     PISSN: 03091708     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advwatres.2007.02.006     Document Type: Article

References (38)

1. Bastiaanssen W.G.M., Menenti M., Feddes R.A., and Holtslag A.A.M. A remote sensing surface energy balance algorithm for land - SEBAL. J Hydrol 213 (1998) 198-212
2. Bastiaanssen W.G.M., Noordman E.J.M., Pelgrum H., Davids G., Thoreson B.P., and Allen R.G. SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. J Irrig Drain Eng 131 1 (2005) 85-93
3. Bowman AJ, Kimpel BC. Irrigation practices in Illinois. Illinois State Water Survey Research Report/118, 1991.
4. Cahill A.T., Ungaro F., Parlange M.B., Mata M., and Nielsen D.R. Combined spatial and Kalman filter estimation of optimal soil hydraulic properties. Water Resour Res 35 4 (1999) 1079-1088
5. Cai X., McKinney D.C., and Rosegrant M.W. Sustainability analysis for irrigation water management in the Aral Sea region. Agric Syst 76 (2003) 1043-1066
6. Calsyn DE. Soil survey of Mason County, Illinois. Soil Report/146, Illinois Agriculture Experiment Station, 1995.
7. Drecourt J.P., Madsen H., and Rosbjerg D. Bias aware Kalman filters: comparison and improvements. Adv Water Resour 29 5 (2006) 707-718
8. Eppstein M.J., and Dougherty D. Simultaneous estimation of transmissivity values and zonation. Water Resour Res 32 11 (1996) 3321-3336
9. Evensen G. Sequential data assimilation with a non-linear quasi-geostrophic model using Mote Carlo methods to forecast error statistics. J Geophys Res 99 C5 (1994) 10143-10162
10. Feddes R.A., Menenti M., Kabat P., and Bastiaanssen W.G.M. Is large-scale modeling of unsaturated flow with areal average evaporation and surface soil moisture as estimated from remote sensing feasible?. J Hydrol 143 (1993) 125-152
11. Ferraresi M., Todini E., and Vignoli R. A solution to the inverse problem in groundwater hydrology based on Kalman filtering. J Hydrol 175 (1996) 67-581
12. Gelb A. Applied optimal estimation (1974), MIT Press, Cambridge
13. Goldberg D.E. Genetic algorithms in search, optimization, and machine learning (1989), Addison-Wesley, Boston
14. Gusev Y.M., and Nasonova O.N. An experience of modeling heat and water exchange at the land surface on a large river basin scale. J Hydrol 233 (2000) 1-18
15. Hupet F., Trought M.C.T., Greven M., Green S.R., and Clothier B.E. Data requirements for identifying macroscopic water stress parameters: a study on grapevines. Water Resour Res (2005) 41;W06008 10.1029/2004WR003609
16. Illinois Water and Climate Summary. Available from http://www.sws.uiuc.edu//warm/climate.asp.
17. Ines A.V.M., and Droogers P. Inverse modelling in estimating soil hydraulic functions: a genetic algorithm approach. Hydrol Earth Syst Sci 6 (2002) 49-65
18. Ines A.V.M., Honda K., Gupta A.D., Droogers P., and Clemente R.S. Combining remote sensing-simulation modeling and genetic algorithm to explore water management options in irrigated agriculture. Agric Water Manage 83 3 (2006) 221-232
19. Jhorar R.K., Bastiaanssen W.G.M., Feddes R.A., and van Dam J.C. Inversely estimating soil hydraulic functions using evapotranspiration fluxes. J Hydrol 258 (2002) 198-213
20. Kalman R.E. A new approach to linear filtering and prediction problems. Trans AMSE J Basic Eng 82 (1960) 35-44
21. Katul G.G., Wendroth O., Parlange M.B., Puente C.E., Folegatti M.V., and Nielsen D.R. Estimation of in situ hydraulic conductivity function from nonlinear filtering theory. Water Resour Res 29 4 (1993) 1063-1070
22. Knaapen M.A.F., and Hulscher S.J.M.H. Use of a genetic algorithm to improve predictions of alternate bar dynamics. Water Resour Res 39 9 (2003) 123 10.1029/2002WR001793
23. Leng C.H., and Yeh H.D. Aquifer parameter identification using the extended Kalman filter. Water Resour Res 39 3 (2003) 1062 10.1029/2001WR000840
24. Mohamed Y.A., van den Hurk B.J.J.M., and savenije H.H.G. Bastiaanssen WGM. Impact of the Sudd wetland on the Nile hydroclimatology. Water Resour Res 41 (2005) W08420 10.1029/2004WR003792
25. Moradkhani H., Sorooshian S., Gupta H.V., and Houser P.R. Dual state-parameter estimation of hydrological models using ensemble Kalman filter. Adv Water Resour 28 (2005) 135-147
26. National Research Council. Estimating water use in the United States: A new paradigm for the National Water Use Information Program (2002), National Academy Press, Washington, DC
27. Olioso A., Inoue Y., Ortega-Farias S., Demarty J., Wigeron J.P., Braud I., et al. Future directions for advanced evapotranspiration modeling: Assimilation of remote sensing data into crop simulation models and SVAT models. Irrig Drain Syst 19 (2005) 377-412
28. Ozdogan M., and Salvucci G.D. Irrigation-induced changes in potential evapotranspiration in southeastern Turkey: test and application of Bouchet's complementary hypothesis. Water Resour Res 40 (2004) W04301 10.1029/2003WR002822
29. Sun N. Inverse problems in groundwater modeling (1994), Kluwer Academic Publishers, Netherlands
30. Tietje O., and Tapkenhinrichs M. Evaluation of pedo-transfer functions. Soil Sci Soc Am J 57 (1993) 1088-1095
31. Van Dam JC, Huygen J, Wesseling JG, Feddes RA, Kabat P, Van Walsum PEV, Groenendijk P, Van Diepen CA. Theory of SWAP, version 2.0. Technique Document 45, Wageningen Agricultural University and DLO Winand Staring Centre, 1997.
32. Van Genuchten M.T. A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am Proc 44 (1980) 892-898
33. Vrugt I.A., Diks C.G.H., Gupta H.V., Bouten W., and Verstraten J.M. Improved treatment of uncertainty in hydrologic modeling: combining the strengths of global optimization and data assimilation. Water Resour Res 41 (2005) W01017
34. Water and Atmospheric Resources Monitoring Program, Illinois Climate Network, Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820, 2005.
35. Wehrmann HA, Westcott NE, Scoot RW. Operation of rain gauge and groundwater monitoring networks for the Imperial Valley Water Authority, year ten: September 2001-August 2002. Contract Report 2004-01, Illinois State Water Survey, Groundwater Section, 2004.
36. Wösten J.H.M., Lilly A., Nemes A., and Bas C.L. Development and use of a database of hydraulic properties of European soils. Geoderma 90 (1999) 169-185
37. Zehe E., and Blöschl G. Predictability of hydrologic response at the plot and catchment scales: role of initial conditions. Water Resour Res 40 (2004) W10202 10.1029/2003WR002869
38. Zhang Y., Pinder G.F., and Herrera G.S. Least cost design of groundwater quality monitoring networks. Water Resour Res 41 (2005) W08412 10.1029/2005WR003936