Browsing by Author "Bobert, J."

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    Simulation of water productivity for Maize under drip irrigation
    (Tropentag, 2011) Festo, R.; Bobert, J.; Mahoo, H.; Kashaigili, J.
    Water has become increasingly scarce in most of the countries in the world. To use the available water efficiently in crop production, agricultural water productivity (WP) need to be improved. Drip irrigation systems and deficit irrigation practices are the most ef- ficient methods in improving WP. Availability of soil-water-crop simulation and climatic models can also help in the efforts to improve WP. A study was conducted in Morogoro using CROPWAT model to simulate water productivity of maize under drip irrigation by supplying different water deficits. A completely randomised block design was used with three replications and four treatments. The treatments were T1, T2, T3 and T4 represen- ting 60, 40, 20, 0 percent deficit of ETC (crop evapo-transpiration) respectively. Biomass accumulation (at 45 and 75 days after planting; DAP), grain yield and harvest index we- re determined for each treatment and experimental yield reductions were calculated. The CROPWAT simulation was done for each water deficit level and yield reductions were recorded. A comparison was made between experimental and simulated yield reductions. The mean biomass production between the treatments at 45 DAP were not significant dif- ferent (p < 0.05). At 75 DAP mean biomass production (0.684, 0.728, 1.049, 1.378 kg m-2 for T1, T2, T3 and T4 respectively) were highly significant different (p < 0.05). The mean grain yield between treatments, mean water productivity (1.67, 2.2, 1.78, 1.72 kg m-3 for T1, T2, T3 and T4 respectively) and harvest index values were significant different (p < 0.01). Experimental and CROPWAT simulated yield reductions were not significant different (p < 0.01) at all stages for all the treatments. The CROPWAT model adequately simulated the experimental yield response to water for maize (maize water productivity).
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    Using soil-vegetation-atmosphere models and down scaled global climate scenarios to assess the impact of climate change in Morogoro region, Tanzania
    (Tropentag, 2010) Bobert, J.; Dietrich, O.; Dietz, J.; Festo, R.; Kashaigili, J.; Sieber, S.; Tscherning, K.
    ReACCT (Resilient Agro-landscapes to Climate Change in Tanzania) aims at assessing the regional impacts of climate change on agriculture and environment in the Morogoro region of Tanzania and at designing adaptation strategies and practices for small-scale agriculture and land use. The sub-project crop-soil modelling concentrates on model based estimations of climate change impacts on current land use systems and practices. At three research sites, distri- buted over the project region and with distinct climates, field trials are conducted to assess the yield potential of widely-used maize and sorghum varieties. The data obtained from the study are used to calibrate multiple soil-vegetation-atmosphere models ranging from rather simple to process-oriented models, which are able to simulate the bio-geophysical interactions between climate, soil and vegetation. These models are sensitive to changes concerning soil hydrology, nutrient cycling, and crop response to assess combined clima- te change and management effects on crop production, water resources and soil fertility. Combined with downscaled global climate scenarios, these models evaluate the best mana- gement practices for future climatic conditions. In another approach tested at sites at the Sokoine University in Morogoro the effects of including trees into the farming systems are investigated. Here the maize and sorghum varieties taken into account are cultivated at one site under standard conditions, whereas at the second site the plants are shaded by native Acacia trees. The effects of the shading on growth and development are measured in situ as well as the water use of trees and crops to quantify water competition between the plants. The interrelationship of these processes is modelled using the Water, Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) model, which has been developed at the World Agroforestry Centre.