AquaCrop Model Validation for Simulating Biomass and Water Productivity Under Climate Change for Potatoes

AquaCrop Model Validation for Simulating Biomass and Water Productivity Under Climate Change for Potatoes

Effective crop development modelling is essential for crop management, water resource planning, assessing climate change's influence on agricultural production, and yield prediction. Validation and simulation of the measured data indicated that AquaCrop software is an effective and reliable program for designing pressurized irrigation systems to increase water application efficiency, system performance and the future prediction. The AquaCrop model was evaluated through a solid-set sprinkler and surface drip irrigation systems at 100%, 80%, and 60% of evapotranspiration (ETo) for the potato crop. The AquaCrop model has shown better performance to simulate potato growth and predicting crop variables under various water systems. The surface drip-irrigation system's at 80% of ETo (48.00, 8.05 ton ha-1) Yield had a substantial impact on the yield of potato and water productivity (WP), matching the yield of potatoes that was irrigated with solid-set sprinklers at 100% of ETo (37.39, 7.19 ton ha-1), with 20% water savings. Attributes of potatoes (canopy cover, biomass, potato crop factor (Kc), and water productivity) were affected by increasing water deficit. The simulated of AquaCrop model was a little higher than observed at 80% of ETo treatment, but still has a similar deviation, and it was slightly lower than seen for 60% of ETo treatment at the mid-season. The AquaCrop model predicted the yield of potatoes and biomass correctly when irrigation is adequate. The results indicated that there may be some changes in AquaCrop model simulation operations over future years based on the climate and irrigation method.

___

  • Attia S and Gobin C (2020). Climate change effects on Belgian households: a case study of a nearly zero energy building. Energies, 13(20): 5357.
  • Borus DJ (2017). Impacts of climate change on the potato (Solanum tuberosum L.) productivity in Tasmania, Australia and Kenya. PhD Thesis. University of Sydney pp. 206.
  • DeTar WR, Browne GT, Phene CJ and Sanden BL (1996). Real-time irrigation scheduling of potatoes with sprinkler and subsurface drip systems. In Proceeding International Conference on Evapotranspiration and Irrigation Scheduling, eds. CR Camp, EJ Sadler, and RE Yoder (pp. 812-824).
  • Dewedar O, Plauborg F, El-Shafie A and Marwa A (2021) Response of potato biomass and tuber yield under future climate change scenarios in Egypt. Journal of Water and Land Development. 49(IV-VI): 139-150.
  • Eldredge EP, Shock CC and Saunders LD (2002). Early and late harvest potato cultivar response to drip irrigation. In XXVI International Horticultural Congress: Potatoes, Healthy Food for Humanity: International Developments in Breeding, 619 (pp. 233-239).
  • El-Shaer HM, Rosenzweig C, Iglesias A, Eid MH and Hillel D (1997). Impact of climate change on possible scenarios for Egyptian agriculture in the future. Mitigation and Adaptation Strategies for Global Change, 1(3): 233-250.
  • Fabeiro CM, de Santa Olalla FM and De Juan JA (2001). Yield and size of deficit irrigated potatoes. Agricultural Water Management, 48(3): 255-266.‏
  • Fang H, Baret F, Plummer S and Schaepman-Strub G (2019). An overview of global leaf area index (LAI): Methods, products, validation, and applications. Reviews of Geophysics, 57(3): 739-799.
  • García-Vila M and Fereres E (2012). Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level. European Journal of Agronomy, 36(1): 21-31.‏
  • Gee GN and Bauder JW (1986) Particle Size Distribution. In: Klute, A., Ed., Methods of Soil Analysis Part 1. Physical and Mineralogical Methods, 2nd Edition, Agronomy Society of America/Soil Science Society of America, Madison, Wisconsin, 383-411.
  • Heng LK, Hsiao TC, Evett S, Howell T and Steduto P (2009). Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agronomy Journal, 101: 488-498.
  • Howell TA (2001). Enhancing water uses efficiency in irrigated agriculture. Agronomy Journal, 93: 281-289.
  • Hsiao TC (2000). Sensitivity of growth of tubers vs. leaves to water stress: Biophysical analysis and relation to water transport. Journal of Experimental Botany, 51: 1595-1616.
  • Hsiao TC (2007). AquaCrop–Model parameterization and testing for maize. In ASA-CSSA-SSSA International Annual Meetings (November 4-8, 2007). ASA-CSSA-SSSA.
  • Ibrahim A, Csúr-Varga A, Jolánkai M, Mansour H and Hamed A (2018). Monitoring some quality attributes of different wheat varieties by infrared technology. Agricultural Engineering International CIGR Journal, 20: 201-210.
  • IP and Gitlin HM (1975). Irrigation efficiencies of surface, sprinkler and drip irrigation. Proceedings Second World Congress, International Water Resources Association, New Delhi: 191-199.
  • Kaur A, Singh KB, Gupta RK, Alataway A, Dewidar AZ and Mattar MA (2022). Interactive effects of nitrogen application and irrigation on water use, growth and tuber yield of potato under subsurface drip irrigation. Agronomy, 13(1): 11.
  • Kemanian AR, Stockle CO, Huggins DR and Viega LM (2007). A simple method to estimate harvest index in grain crops. Field Crops Research, 103: 208-216.
  • King BA, Stark JC and Neibling H (2020). Potato irrigation management. In Potato Production Systems (pp. 417-446). Springer, Cham.
  • Klute A (1986). Water Retention: Laboratory Methods, in Klute, A. (ed.): Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods. ASA and SSSA, Madison, WI, USA, pp. 635-662.
  • Loague K and Green RE (1991). Statistical and graphical methods for evaluating solute transport models: overview and application. Journal of Contaminat Hydrology, 7: 51-73.
  • Luck J, Asaduzzaman M, Banerjee S, Bhattacharya I, Coughland K, Chakraborty A, Debnath G C, De Boer R F, Dhutta S, Griffiths W, Hossain D, Huda S, Jagannathan R, Khan S , O'leary G, Miah M G, Shana A, Spooner- Hart R (2012). The effects of climate change on potato production and potato late blight in the Asia-Pacific Region. APN Science Bulletin, 2: 28-33.
  • Malhi GS, Kaur M and Kaushik P (2021). Impact of climate change on agriculture and its mitigation strategies: review. Sustainability, 13(3): 1318.
  • Mansour HA, Abdallah EF, Gaballah MS and Gyuricza C (2015a). Impact of bubbler discharge and irrigation water quantity on 1-hydraulic performance evaluation and maize biomass yield. International Journal Geomate, 9, 1538-1544.
  • Mansour HA, Abdel-Hady M, Eldardiry EI and Bralts VF (2015b). Performance of automatic control different localized irrigation systems and lateral lengths for emitters clogging and maize (Zea mays L.) growth and yield. Intenational Journal Geomate, 9, 1545-1552.
  • Mansour HA, Abd-Elmabod SK and Engel BA (2019a). Adaptation of modeling to the irrigation system and water management for corn growth and yield. Plant Archives, 19 (Suppl. S1), 644-651.
  • Mansour HA, El-Hady MA, Bralts VF and Engel BA (2016). Performance automation controller of drip irrigation system and saline water for wheat yield and water productivity in Egypt. Journal of Irrigation and Drainage Engineering, 142, 05016005.
  • Mansour HA, Hu J, Ren H, Kheiry AN and Abd-Elmabod SK (2019b). Influence of using automatic irrigation system and organicfertilizer treatments on faba bean water productivity. Intenational Journal Geomate, 17: 256-265.
  • Mengistu TG, Nigussie TA, Haile A and Seid A (2021). Evaluating the performance of aquacrop model in simulating the productivity of potato (Solanum tuberosum L.) crop under various water levels at Debre Birhan, Amhara Regional State, Ethiopia. Culture, 5(4), 674-687.‏
  • Molden DJ, Sakthivadivel R and Habib Z (2001). Basin-level use and productivity of water: Examples from South Asia. Research Report 49, International Water Management Institute, Colombo, Sri Lanka.
  • Moriasi DN, Arnold JG, Liew MWV, Bingner RL, Harmel RD and Veith TL (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50: 885-900.
  • Nourani V, Rouzegari N, Molajou A and Baghanam AH (2020). An integrated simulation-optimization framework to optimize the reservoir operation adapted to climate change scenarios. Journal of Hydrology. 587: 125018, 1-19.
  • Pontius R, Thontteh O and Chen H (2008). Components of information for multiple resolution comparisons between maps that share a real variable. Environmental Ecological Statistics, 15: 111-142.
  • Raes D, Steduto P, Hsiao TC and Fereres E (2009). AquaCrop-The FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal, 101: 438-447.
  • Rahimikhoob H, Sohrabi T and Delshad M (2021). Simulating crop response to nitrogen-deficiency stress using the critical Nitrogen concentration concept and the AquaCrop semi-quantitative approach. Scientia Horticulturae, 285, 110194.
  • Razzaghi F, Zhou Z, Andersen MN and Plauborg F (2017). Simulation of potato yield in temperate condition by the AquaCrop model. Agricultural Water Management, 191: 113-123.
  • Rebecca B (2004). Soil Survey Methods Manual. Soil Survey Investigations Report. No 42 Natural Resources Conservation Services.
  • Salemi H, Mohd-Soom MA, Lee TS, Mousavi SF and Ganji A (2011) Application of AquaCrop model in deficit irrigation management of winter wheat in arid region. African Journal of Agricultural Research. 610: 2204-2215.
  • Shaw B, Thomas TH and Cooke DT (2002). Responses of potato (Beta vulgaris L.) to drought and nutrient deficiency stress. Plant Growth Regulation, 37: 77-83.
  • Steduto P (2003). Biomass water-productivity. Comparing the growth engines of crop models. FAO expert consultation on crop water productivity under deficient water supply, Rome.
  • Strıčevıć R, Trbıć G, Vujadınovıć M, Cupać, R, Đurovıć, N and Ćosıć M 2017. Impact of climate change on potato yield grown in different climatic zone in Bosnia and Herzegovina. In VIII International Scientific Agriculture Symposium, Agrosym (pp. 596-601).