Your search found 4 records
1 Gowda, P. H.; Ward, A. D.; White, D. A.; Baker, D. B.; Lyon, J. G. 1999. Using field scale models to predict peak flows on agricultural watersheds. Journal of the American Water Resources Association, 35(5):1223-1232.
Watersheds ; Runoff ; Hydrology ; Surface water ; Simulation models / USA / Ohio / Rock Creek Watershed
(Location: IWMI-HQ Call no: PER Record No: H025278)
2 Nangia, Vinay; Gowda, P. H.; Mulla, D. J.; Sands, G. R. 2008. Water quality modeling of fertilizer management impacts on nitrate losses in tile drains at the field scale. Journal of Environmental Quality, 37(2):296-307.
Water quality ; Simulation models ; Calibration ; Fertilizer application ; Nitrogen fertilizers ; Soyabeans ; Maize ; Subsurface drainage / USA / Gulf of Mexico / Mississippi River / Minnesota
(Location: IWMI HQ Call no: IWMI 631.8 G430 NAN Record No: H040829)
Nitrate losses from subsurface tile drained row cropland in the Upper Midwest U.S. contribute to hypoxia in the Gulf of Mexico. Strategies are needed to reduce nitrate losses to the Mississippi River. This paper evaluates the effect of fertilizer rate and timing on nitrate losses in two (East and West) commercial row crop fields located in south-central Minnesota. The Agricultural Drainage and Pesticide Transport (ADAPT) model was calibrated and validated for monthly subsurface tile drain flow and nitrate losses for a period of 1999–2003. Good agreement was found between observed and predicted tile drain flow and nitrate losses during the calibration period, with Nash-Sutcliff e modeling efficiencies of 0.75 and 0.56, respectively. Better agreements were observed for the validation period. The calibrated model was then used to evaluate the effects of rate and timing of fertilizer application on nitrate losses with a 50-yr climatic record (1954–2003). Significant reductions in nitrate losses were predicted by reducing fertilizer application rates and changing timing. A 13% reduction in nitrate losses was predicted when fall fertilizer application rate was reduced from 180 to 123 kg/ha. A further 9% reduction in nitrate losses can be achieved when switching from fall to spring application. Larger reductions in nitrate losses would require changes in fertilizer rate and timing, as well as other practices such as changing tile drain spacings and/or depths, fall cover cropping, or conversion of crop land to pasture.
3 Araya, A.; Prasad, P. V. V.; Gowda, P. H.; Afewerk, A.; Abadi, B.; Foster, A. J. 2019. Modeling irrigation and nitrogen management of wheat in northern Ethiopia. Agricultural Water Management, 216:264-272. [doi: https://doi.org/10.1016/j.agwat.2019.01.014]
Irrigation management ; Fertilizer application ; Nitrogen ; Crop production ; Wheat ; Crop yield ; Water productivity ; Soil chemicophysical properties ; Biomass ; Models ; Strategies / Ethiopia / Mekelle
(Location: IWMI HQ Call no: e-copy only Record No: H049197)
(1.10 MB)
Wheat (Triticum aestivum) is one of the most important staple food crops in Ethiopia. However, its production is limited by moisture and nutrient stresses. A field experiment was conducted in northern Ethiopia to: (i) evaluate the effects of irrigation and nitrogen (N) and phosphorus (P) fertilizer application rates on yield, biomass and irrigation water productivity (IWP) of wheat; (ii) calibrate and validate a crop model for simulating yield and biomass of wheat under different levels of nitrogen and irrigation applications; (iii) evaluate consecutive aboveground biomass accumulation as affected by different combinations of irrigation and N fertilizer rates. The Decision Support for Agro technology Transfer Cropping System Model (DSSAT-CSM) was calibrated and validated with experimental data. The calibrated and validated DSSAT-CSM was used to simulate wheat biomass, yield, and irrigation water productivity under rainfed and three irrigation scenarios: I0, rainfed; DI1, two irrigations from heading to flowering; DI2, four irrigations from heading to early grain filling; and DI3, six irrigations from heading to mid grain filling period in combination with nine N rates (0, 16, 32, 64, 80, 96, 112, 128 and 160 kg/ha). Simulation results showed that both irrigation and nitrogen applications positively affected wheat yield, biomass and IWP. Much of the increase in biomass and yield was due to increased N than to increased irrigation. Yield increased with increase in N application rates, however, at a diminishing rate yielding a curvilinear relationship. Four irrigation (DI2) starting from heading to early grain filling stage resulted in a yield similar to DI3, six irrigation applications from heading to mid grain filling stage. Simulations showed that two irrigation applications strategy (DI1) yielded relatively higher IWP (1.8 kg/m3 ) at the highest application rate of 160 kg N/ha. Further economic analysis would help to identify most efficient practices for wheat production in northern Ethiopia.
4 Araya, A.; Prasad, P.V.V.; Zambreski, Z.; Gowda, P.H.; Ciampitti, I. A.; Assefa, Y.; Girma, A. 2020. Spatial analysis of the impact of climate change factors and adaptation strategies on productivity of wheat in Ethiopia. Science of The Total Environment, 731:139094. (Online first) [doi: https://doi.org/10.1016/j.scitotenv.2020.139094]
Climate change adaptation ; Strategies ; Agricultural productivity ; Wheat ; Crop yield ; Crop modelling ; Fertilizers ; Nitrogen ; Carbon dioxide ; Irrigation ; Temperature ; Precipitation ; Rain ; Soil types ; Spatial analysis / Ethiopia
(Location: IWMI HQ Call no: e-copy only Record No: H049783)
(4.16 MB)
Wheat production is expected to be challenged by future climate change. However, it is unclear how wheat grown in diverse agroecologies will respond to climate change and adaptation management strategies. A geospatial simulation study was conducted to understand the impacts of climate change and adaptation management strategies on wheat (Triticum aestivum L.) production in Ethiopia. Simulation results showed that the average long-term baseline (1980–2005) wheat yield ranged from 1593 to 3356 kg/ha. This wheat yield range is within the national average (2100–2700 kg/ha) for this decade. In regions with cooler temperatures (<21 °C), mid-century temperatures and elevated CO2, along with increased N fertilizer slightly improved attainable yield levels above 3000 kg/ha. Whereas, in regions with heat and drought conditions wheat yield declined regardless the increase of N or CO2 levels. Wheat yield increased at a diminishing rate with increase in N fertilizer rate. However, N fertilizer did not increase yields under low rainfall conditions. Two to five irrigation per season contributed to yield improvement for low rainfall locations, while yield did not substantially improve for locations receiving adequate seasonal rainfall. Therefore, based on this study, improved N fertilizer application in combination with increased CO2 could improve wheat yield under future climate in most wheat producing regions (with adequate rainfall) of Ethiopia. Our results provide valuable information regarding impacts of climate change factors and adaptation strategies for producers, researchers, extension professionals and policy makers.
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