Your search found 2 records
1 Mustafa, S. M. T.; Vanuytrecht, E.; Huysmans, M. 2017. Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh. Agricultural Water Management, 191:124-137. [doi: https://doi.org/10.1016/j.agwat.2017.06.011]
Irrigation management ; Water deficit ; Soil fertility ; Soil management ; Soil texture ; Water productivity ; Models ; Crop yield ; Wheat ; Irrigation scheduling ; Soil water content ; Soil types ; Meteorological observations ; Drought ; Precipitation ; Strategies / Bangladesh / Dhaka / Mymensigh / Rajshahi / Rangpur
(Location: IWMI HQ Call no: e-copy only Record No: H048223)
(2.35 MB)
Proper utilization of water resources is very important in agro-based and drought-prone Bangladesh. Sustainable use of water resources in agriculture requires irrigation schedules based on local environmental conditions, soil type and water availability. In this study, the water productivity model AquaCrop was used to simulate different water and fertilizer management strategies in a drought prone area of Bangladesh to obtain management recommendations. First, the Standardised Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were determined to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere, which confirm that meteorological drought is occurring frequently in the study area. Also, the AquaCrop model was successfully calibrated and validated for wheat in the area, which was confirmed by the several statistical indicators, and could be used to design water and fertilizer management strategies. Simulations identified stem elongation (jointing) to booting and flowering stage as the most water sensitive stages for wheat. Deficit irrigation during the most water sensitive stages could increase the interannual yield stability and the grain yield compared to rainfed conditions for different soil fertility levels on loamy and sandy soils by 21–136% and 11–71%, respectively, while it could increase water productivity compared to full irrigation strategies. Deficit irrigation resulted in grain yields almost equal to yields under full irrigation and could at the same time save 121–197 mm of water per growing season. Specifically, we suggest two irrigation applications: one at the stem elongation (jointing) to booting stage and another at the flowering stage for loamy soils; and one at the end of seedling development to the beginning of crown root initiation stage and another at the flowering stage for sandy soils. Given the water scarcity in the region, instead of optimal fertility levels, moderate fertility levels are recommended that result in 60% of the potential biomass production for loamy soils and in 50% for sandy soils in combination with the suggested deficit irrigation strategies.
2 Alvar-Beltran, J.; Soldan, R.; Vanuytrecht, E.; Heureux, A.; Shrestha, Nirman; Manzanas, R.; Pant, K. P.; Franceschini, G. 2023. An FAO model comparison: Python Agroecological Zoning (PyAEZ) and AquaCrop to assess climate change impacts on crop yields in Nepal. Environmental Development, 47:100882. [doi: https://doi.org/10.1016/j.envdev.2023.100882]
Crop modelling ; Agroecological zones ; Climate change ; Crop yield ; Maize ; Rice ; Wheat ; Irrigation management ; Rainfed farming ; Water productivity ; Soil texture ; Temperature ; River basins ; FAO / Nepal / Koshi River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H052082)
(9.28 MB)
To identify the most effective agricultural transformation and adaptation measures, the Food and Agriculture Organization (FAO) calls for action to produce robust crop suitability assessments. We developed a novel approach to assess the inputs and outputs of two FAO tools (AEZ and AquaCrop). We use Nepal as a case study, a country offering a myriad of ecoclimatic conditions for multiple crops. Our work provides further evidence of climate change impacts on rice, maize and wheat yields along the different agroclimatic zones of Nepal, equally under rainfed and irrigated conditions for future climate scenarios. The findings of bias-adjusted regional climate models (RCMs) shows increasing temperatures and precipitation; whereas the outputs of agroecological/crop models show effective adaptation of C3 crops to a CO2 enriched environment. In sum, this supports the climate-crop modelling user community, extension workers and government agencies with guidance’s to overcome uncertainties associated with the application of these tools.
Powered by DB/Text WebPublisher, from
