Assessment of the changes in the yields of millet crop under different scenarios of climate change using DSSAT model (original) (raw)
Related papers
2017
The seasonal effects of global warming and water shortages begin to be observed on agricultural production and forecast trends encourage studies on adaptation to climate change. In Niger, West Africa, farmers have always had to cope with irregularity and poor distribution of rainfall. In recent years, a variation in the frequency and duration of rainy season were observed, suddenly affecting a drop in agricultural productions with the resulting food crisis. Therefore, it is necessary to find measures to adapt to the climate variability. This study focus on the Tillaberi region (Niger) where pearl millet is one of the main agricultural product. In the last few years, variations in rainfall distribution and quantity have negatively influenced the yield of the millet crops. A climatic assessment of the region has been verified collecting information from both previous studies and satellite data. Two early improved varieties of pearl millet (SOSAT-C88 and HKP) drought resistant have bee...
Merit Research Journal of Agricultural Science and Soil Sciences, 2019
African agriculture of agricultural production in regions of the African continent with chronic water shortages depends upon understanding how major crops wheat and maize) and fluctuating rainfall). In the present study, a four 2018) was conducted in an African country (Tunisia) to determine how the wheat yield and nitrate leaching were affected by climate change in 2050. DSSAT model was used that the percentage = 28%) results showed that the used evaluating Furthermore, enhance wheat yield resistance to future climate change this study could be Tunisia with respect to climate change. Overall, the study can be used to implement the most appropriate strategy of soil and crop management to minimize effects of climate changes on wheat yield.
DSSAT modelling of conservation agriculture maize response to climate change in Malawi
Soil and Tillage Research, 2014
Adoption of conservation agriculture (CA) is increasingly being promoted as a way of adapting agricultural systems to increasing climate variability, especially for areas such as southern Africa where rainfall is projected to decrease. The DSSAT crop simulation models can be a valuable tool in evaluating the effects of CA which are viable both economically and environmentally. Our objectives were: (1) to evaluate the ability of DSSAT to predict continuous maize (Zea mays L.) yield for conventional tillage (CT) and CA systems as well as maize yield for a CA maize-cowpea (Vigna unguiculata) rotation on an Oxic rhodustalf (2) to use DSSAT to project weather effect of climate change on yield, economic returns and risk in CT and CA systems. The DSSAT model was calibrated using data from 2007-2008 season and validated against independent data sets of yield of 2008-2009 to 2011-2012 seasons. Simulations of maize yields were conducted on projected future weather data from 2010 to 2030 that was generated by RegCM4 using the A1B scenario. The DSSAT model calibration and validation showed that it could be used for decision-making to choose specific CA practices especially for no-till and crop residue retention. Long term simulations showed that maize-cowpea rotation gave 451 kg ha À1 and 1.62 kg mm À1 rain more maize grain yield and rain water productivity, respectively compared with CT. On the other hand, CT (3131-5023 kg ha À1 ) showed larger variation in yield than both CA systems (3863 kg ha À1 and 4905 kg ha À1 ). CT and CA systems gave 50% and 10% cumulative probability of obtaining yield below the minimum acceptable limit of 4000 kg ha À1 respectively suggesting that CA has lower probability of low yield than CT, thus could be preferred by risk-averse farmers in uncertain climatic conditions. Using similar reasoning, Mean-Gini Dominance analysis showed the dominancy of maize-cowpea rotation and indicated it as the most efficient management system. This study therefore suggests that CA, especially when all three principles are practiced by smallholders in the medium altitude of Lilongwe and similar areas, has the potential to adapt the maize based systems to climate change. Use of DSSAT simulation of the effects of CA was successful for no-till and crop residue retention, but poor for crop rotation. Refinement of crop rotation algorithm in DSSAT is recommended. ß
Environmental Science and Pollution Research, 2019
Climate change adversely affects food security all over the world, especially in developing countries where the increasing population is confronting food insecurity and malnutrition. Crop models can assist stakeholders for assessment of climate change in current and future agricultural production systems. The aim of this study was to use of system analysis approach through CSM-CERES-Millet model to quantify climate change and its impact on pearl millet under arid and semi-arid climatic conditions of Punjab, Pakistan. Calibration and evaluation of CERES-Millet were performed with the field observations for pearl millet hybrid 86M86. Mid-century (2040-2069) climate change scenarios for representative concentration pathway (RCP) 4.5 and RCP 8.5 were generated based on an ensemble of selected five general circulation models (GCMs). The model was calibrated with optimum treatment (15-cm plant spacing and 200 kg N ha −1) using field observations on phenology, growth and grain yield. Thereafter, pearl millet cultivar was evaluated with remaining treatments of plant spacing and nitrogen during 2015 and 2016 in Faisalabad and Layyah. The CERES-Millet model was calibrated very well and predicted the grain yield with 1.14% error. Model valuation results showed that there was a close agreement between the observed and simulated values of grain yield with RMSE ranging from 172 to 193 kg ha −1. The results of future climate scenarios revealed that there would be an increase in T min (2.8°C and 2.9°C, respectively, for the semi-arid and arid environment) and T max (2.5°C and 2.7°C, respectively, for the semi-arid and arid environment) under RCP4.5. For RCP8.5, there would be an increase of 4°C in T min for the semi-arid and arid environment and an increase of 3.7°C and 3.9°C in T max , respectively, for the semi-arid and arid environment. The impacts of climate changes showed that pearl millet yield would be reduced by 7 to 10% under RCPs 4.5 and 8.5 in Faisalabad and 10 to 13% in Layyah under RCP 4.5 and 8.5 for mid-century. So, CSM-CERES-Millet is a useful tool in assessing the climate change impacts.
Environmental Economics eJournal, 2015
Achieving and maintaining global food security is challenged by changes in population, income, and climate, among other drivers. Assessing these challenges and possible solutions over the coming decades requires a rigorous multidisciplinary approach. To answer this challenge, the International Food Policy Research Institute (IFPRI) has developed a system of linked simulation models of global agriculture to do long-run scenario analysis of the effects of climate change and various adaptation strategies. This system includes the core International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT), which is linked to water models (global hydrology, water basin management, and water stress on crops) and crop simulation models.
Frontiers in Environmental Science
Introduction: The impact of climate change on food production in South Africa is likely to increase due to low rainfall and frequent droughts, resulting in food insecurity in the future. The use of well-calibrated and validated crop models with climate change data is important for assessing climate change impacts and developing adaptation strategies. In this study, the decision support system for agrotechnology transfer (DSSAT) crop model was used to predict yield using observed and projected climate data.Materials and Methods: Climate, soil, and crop management data were collected from wheat-growing study sites in Bethlehem, South Africa. The DSSAT wheat model (CROPSIM-CERES) used was already calibrated, and validated by Serage et al. (Evaluating Climate Change Adaptation Strategies for Disaster Risk Management: Case Study for Bethlehem Wheat Farmers, South Africa, 2017) using three wheat cultivar coefficients obtained from the cultivar adaptation experiment by the ARC-Small Grain ...
Wheat is one of the food security crops in Ethiopia which is critically sensitive to the impacts of climate change. However, the factors of climate change are very local; hence a local level and crop-specific understanding of the impact is extremely important. With this understanding, a study is conducted at Sinana district in Bale highlands to modeling the impacts of climate change on bread wheat production and analysis under future climate scenarios. Historical climate data (1984-2016), projected climate data downscaled using the ensemble of all GCMs, were analyzed to understand the local level climate change. The future climate is analyzed regarding of changes in annual rainfall, seasonal rainfall and monthly rainfall statistics using INSTAT v3.37 software analytical tools respectively. Observed agronomic and soil data were used to calibrate and validate the Crop model of Decision Support for Agrotechnology Transfer (DSSAT) model. The model was used to simulate the impact of future climate changes and variability in bread wheat yield of Madda walabu and Sofumer varieties at Sinana district in Bale highlands. The results revealed that climate change caused variability on bread wheat productivity in Sinana district within different time slices. There is a negative impact simulated at Robe area except in 2080's under RCP4.5 and 2050's and 2080's under RCP8.5 scenarios. Madda walabu yield is simulated to decreased up to-21.4% at Robe by 2050's under RCP4.5 scenario relative to the baseline due to climate change impacts. For Sofumer, an increase in grain yield from the baseline condition was 7.0 % and 11.6 % by near century (2030's) under both RCP4.5 and RCP8.5 scenarios respectively. Also, much yield reduction is experienced the 2050's and 2080's by 15.6 % and 27.0 % under RCP4.5. The decrease was expected by 21.9 % and 23.9 % in 2050's and 2080's under RCP8.5 respectively. Therefore; climate change had a severe impact that justifies the need for site-specific study. Therefore, future agricultural practices should benefit from agro weather advisory service for farming decision in study the area.
Evaluation of climate adaptation options for Sudano-Sahelian cropping systems
2014
In West Africa predictions of future changes in climate and especially rainfall are highly uncertain, and up to now no long-term analyses are available of the effects of climate on crop production. This study analyses long-term trends in climate variability at N'Tarla and Sikasso in southern Mali using a weather dataset from 1965 to 2005. Climatic variables and crop productivity were analysed using data from an experiment conducted from 1965 to 1993 at N'Tarla and from a crop yield database from ten cotton growing districts of southern Mali. Minimum daily air temperature increased on average by 0.05 • C per year during the period from 1965 to 2005 while maximum daily air temperature remained constant. Seasonal rainfall showed large inter-annual variability with no significant change over the 1965-2005 period. However, the total number of dry days within the growing season increased significantly at N'Tarla, indicating a change in rainfall distribution. Yields of cotton, sorghum and groundnut at the N'Tarla experiment varied (30%) without any clear trend over the years. There was a negative effect of maximum temperature, number of dry days and total seasonal rainfall on cotton yield. The variation in cotton yields was related to the rainfall distribution within the rainfall season, with dry spells and seasonal dry days being key determinants of crop yield. In the driest districts, maize yields were positively correlated with rainfall. Our study shows that cotton production in southern Mali is affected by climate change, in particular through changes in the rainfall distribution.
BIMP-EAGA Journal for Sustainable Tourism Development
Corn and peanut are major upland crops in Cagayan Valley. Emerging food and biofuel crops like sweet sorghum requires less water were recently introduced to increase the productivity in the rainfed ecosystem. However , little information is available on the potential productivity of these upland crops and analysis on the production constraints including climate change sensitivity. This study aimed to determine potential yield, yield gap, production constraints and clim ate change sensitivity of peanut, sweet sorghum and corn crops in Cagayan Valley through the use of Decision Support System for Agrotechnology Transfer (DSSAT) simulation modeling. Simulation results using DSSAT model showed highest potential yield of pean ut, corn and sweet sorghum is 2267 kg/ha when planted in October 15, 7,734 kg/ha when planted in June 15, and 6,570 kg/ha when planted in February 1 respectively, under rainfed condition. Under non stressed conditions, the highest obtainable yield is 4805 kg/ha when...