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Irrigation Scheduling Impact Assessment MODel (ISIAMOD): a Decision Tool for Irrigation Scheduling


Affiliations
1 Department of Agricultural Engineering, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
 

This paper presents a process-based simulation known as Irrigation Scheduling Impact Assessment MODel (ISIAMOD). It was developed to simulate crop growth&yield, soil water balance and water management response indices to define the impact of irrigation scheduling decisions. ISIAMOD was calibrated and validated using data from field experiments on the irrigated maize crop conducted in an irrigation scheme located in south western Tanzania. The model adequately simulates crop biomass yield, grain yield, seasonal evapotranspiration and average soil moisture content in the crop effective ischolar_maining depth. Some unique features of this model make it a major improvement over the existing crop-soil simulation models.

Keywords

Simulation Model, Irrigation Scheduling, Water Management, Crop Water Productivity, ISIAMOD
User

  • Allen RG, Pereira LS, Raes D and Smith M (1998) Crop evapotranspiration: guideline for computing crop water requirements. FAO Irrigation & Drainage paper. 56, pp: 300.

  • Antonopoulos VZ (1997) Simulation of soil moisture dynamics in irrigated cotton in semi-arid climates. Agr. Water Manage. 34, 233-246.

  • Arora VK and Gajri PR (1996) Performance of simplified water balance models under maize in a semiarid subtropical environment. Agr. Water Manage. 31, 57-64.

  • Arora VK, Prihar SS and Gajri PR (1987) Synthesis of a simplified water use simulation model for predicting wheat yield. Water Resour. Res. 23, 903-910.

  • Belman C, Wesseling JG and Feddes RA (1983) Simulation of the water balance of a cropped soil: SWATRE. J. Hydrol. 63, 271-286.

  • Boote KJ and Jones JW (1988) Application of, and limitation to, crop growth simulation models to fit crops and cropping systems to semi-arid environment. In: Drought Res. Priorities for the Dry Land Tropics. Bindinger FR & Johansen C (ed.), ICRISAT, Patenchens, India. pp: 63-75.

  • Campbell GS and Diaz R (1988) Simplified soil-water balance models to predict crop transpiration. In: Drought Research Priorities for the Dryland Tropics, Bindinger FR & Johansen C (Ed.), Parancheru, A.P. 502324, India: ICRISAT, pp.15-25.

  • Cavero J, Farre I, Debaeke P and Faci JM (2000) Simulation of maize yield under water stress with the EPICphase and CROPWAT models. Agronomy J. 92, 679-690.

  • Hargreaves GH and Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl. Eng. Agr. 1(2), 96-99.

  • Igbadun HE, Mahoo HF, Tarimo AKPR and Salim BA (2006a) Performance of two temperature-based reference evapotranspiration models in the mkoji subcatchment in tanzania. Agr. Eng. Int. CIGR E J., Manuscript LW 05 008. Vol. VIII. April, 2006. ISSN Number 1682-1130.

  • Igbadun HE, Mahoo HF, Tarimo AKPR and Salim BA (2006b) Crop water productivity of an irrigated maize crop in Mkoji sub-catchment of the Great Ruaha River Basin, Tanzania. Agr. Water Manage. 85, 141-150.

  • Jones CA and Kiniry JR (1986) CERES-Maize: A simulation model of maize growth and development. Texas A & M Univ. Press, College Station, Texas, pp: 150

  • Mahdian MH and Gallichand J (1995) Validation of the SUBSTOR model for simulating soil water content. Trans. Am. Soc. Agr. Eng (ASAE). 38, 513-520.

  • McCown RL, Hammer GL, Hargreaves JNG, Holzworth DP and Freebairn DN (1996) APSIM: A novel software system for model development, model testing, and simulation in agricultural research. Agr. Sys. 50, 255-271.

  • Michael AM (1999) Irrigation theory and practice. Reprint. Vikas Publ. House PVT Ltd. New Delhi. pp: 520.

  • Panda RK, Behera SK and Kashyap PS (2004) Effective management of irrigation water for maize under stress conditions. Agr. Water Manage. 66, 181- 203.

  • Pandey RK, Maranville JW and Admou A (2000) Deficit irrigation and nitrogen effects on maize in a sahelian environment I. Grain yield and yield components. Agr. Water Manage. 46, 1-13.

  • Plauborg F, Andersen MN, Heidmann T and Olesen JE (1996) MARKVAND: an irrigation scheduling system for use under limited irrigation capacity in a temperate humid climate. In: Irrigation Scheduling from Theory to Practice. Water Reports 8. FAO-ICIDCIID, Rome. pp: 177-184.

  • Raes D, Lemmens H, van Aelst P, Vandebulcke M and Smith M (1986) Irrigation scheduling information system (IRSIS). Ref. Manual No.3, Lab. Land Manage. K. U. Leuven, Belgium. pp: 119.

  • Saxton KE (1989) User manual for SPAW- A soil plant atmosphere water model. USDA-SEA-AR, Pullman, WA. pp: 90.

  • Sharpley A and Williams JR (1990) EPIC: Erosion, productivity impact calculator: 1. Model documentation. Technical Bull. 1768, USDA. pp: 145.

  • Smith M (1992) CROPWAT: A computer program for irrigation planning and management. FAO Irrigation & Drainage Paper 46. FAO, Rome. pp: 89.

  • Stockle CO and Nelson R (1996) Cropping system simulation model. User’s manual. Biol. Sys. Eng. Dept. Washington State Univ., Pullman WA 99164-6120, pp: 165.

  • SWMRG-FAO (2003) Comprehensive assessment of water resources of mkoji sub catchment, its current uses and productivity. FAO- Netherlands Partnership Programme, Water & Food Security. IWRM for the Vulnerable Group. PR26935. pp: 50.

  • Van Dam, Huygen JC, Wesseling J, Feddes JG, Kabat RA, van Waslum P, Groenendjik PEV, PP and van Diepen CA (1997) Theory of SWAP version 2.0: Simulation of water flow and plant growth in the soilwater- atmosphere-plant environment. Technical Document 45. The Netherlands: Wageningen Agr. Univ. & DLO Winand Staring Centre. pp: 90.

  • Williams JR, Jones CA, Kiniry JR and Spanel DA (1989) The EPIC crop growth model. Trans. Am. Soc. Agr. Eng. 32, 497-513.

  • Yang HS, Dobermann AJ, Lindquist L, Walker DT, Arkebauer TJ and Cassman KG (2004) Hybrid-maizea maize simulation model that combines two crop modelling approaches. Field Crops Res. 87, 131-154.

  • Zhang Y, Yu Q Liu C, Jiang J and Zhang X (2004) Estimation of winter wheat evapotranspiration under water stress with to semi-empirical approach. Agronomy J. 96, 159-168.


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  • Irrigation Scheduling Impact Assessment MODel (ISIAMOD): a Decision Tool for Irrigation Scheduling

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Authors

Henry. E. Igbadun
Department of Agricultural Engineering, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria

Abstract


This paper presents a process-based simulation known as Irrigation Scheduling Impact Assessment MODel (ISIAMOD). It was developed to simulate crop growth&yield, soil water balance and water management response indices to define the impact of irrigation scheduling decisions. ISIAMOD was calibrated and validated using data from field experiments on the irrigated maize crop conducted in an irrigation scheme located in south western Tanzania. The model adequately simulates crop biomass yield, grain yield, seasonal evapotranspiration and average soil moisture content in the crop effective ischolar_maining depth. Some unique features of this model make it a major improvement over the existing crop-soil simulation models.

Keywords


Simulation Model, Irrigation Scheduling, Water Management, Crop Water Productivity, ISIAMOD

References





DOI: https://doi.org/10.17485/ijst%2F2012%2Fv5i8%2F30520