Estimating millet production for famine early warning: an application of crop simulation modelling using satellite and ground-based data in Burkina Faso

Thornton, Philip K.; Bowen, W. T.; Ravelo, Andrés C.; Wilkens, Paul W.; Farmer, G. Thomas; Brock, John C.; Brink, Jim

doi:10.1016/s0168-1923(96)02348-9

Cited by 88 publications

(42 citation statements)

References 4 publications

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“…Phasic development is quantified according to the plant's physiological age. The input data required to run the model include daily weather information (maximum and minimum temperatures, rainfall, and solar radiation); soil characterization data (data by soil layer for extractable phosphorus and nitrogen and soil water content); a set of genetic coefficients characterizing the wheat variety being grown; and crop management information, such as emerged plant population, row spacing, seeding depth, and fertilizer and irrigation schedules (Thornton et al 1997). The soil data were obtained from the US Soil Conservation Service (SCS; now known as the Natural Resources Conservation Service) and were selected to represent the dominant local soils of each of the 10 representative areas.…”

Section: Wheat Crop Model (Ceres-wheat)mentioning

confidence: 99%

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Sensitivity of winter wheat yields in the Midwestern United States to future changes in climate, climate variability, and CO2 fertilization

Southworth

Pfeifer²,

Habeck³

et al. 2002

Clim. Res.

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This research investigates the potential impacts of climate change on winter wheat Triticum aestiuum L. production, looking at changes both in the mean climate and in climate variability, under conditions of elevated atmospheric CO 2 concentrations. The study region is comprised of the 5 states of Indiana, Illinois, Ohio, Michigan, and Wisconsin in the US. This analysis was conducted for the period 2050-59 for 10 representative farm locations in the 5 states for 6 future climate scenarios using the crop growth model CERES-Wheat. Wheat is currently the most widely grown crop in the world, with approximately 250 million ha planted each year. This region, while not a critical area for winter wheat production under current climate, is in a marginal area that could become a more important production region under a warmer climate. As such, the impacts of climate change on wheat growth are of great significance both regionally and globally. With future atmospheric CO 2 concentrations of 555 ppmv, wheat yields increased 60 to 100% above current yields across the central and northern areas of the study region when modeled for 2050-59 climate change scenarios. In the southern areas of the study region, small increases (0.1 to 20%) and small decreases (-0.1 to -15%) were found. These decreases in yield were more frequent under climate conditions associated with the more extreme Hadley Center greenhouse gas run (HadCM2-GHG, representing a 1% increase in greenhouse gases per year) and for the doubled climate variability analyses. Across all sites, earlier planting dates (September 2 is optimal) performed best; yields decreased as planting was delayed. These results have implications for spring-planted crops. CO 2 fertilization effects also are found to be significant for wheat, representing an average yield increase greater than 20% under future climate scenarios, with greater benefits occurring under more moderate future climate scenarios. Without the effects of CO 2 fertilization in the model, many of the southern locations had greater decreases in yields. The overall climate change impact across the study area resulted in large increases in yields with only a few locations exhibiting decreases, and those decreases occurring only under the more extreme climate scenarios. KEY WORDS: Midwestern United States · Winter wheat · Carbon dioxide · HadCM2 model · CERES-Wheat · Climate variabilityResale or republication not permitted without written consent of the publisher Clim Res 22: 73-86, 2002 Johnston 1995, IPCC 1995). Climate influences crop growth and yields directly through impacts on phenology, photosynthesis, and other physiological processes. Indirect effects relate to nutrient availability, weeds, pests and diseases, and ability of farmers to work in the field (field days). These effects will be modified by moisture availability and temperature ranges (Olesen et al. 2000).With respect to agriculture, changes in solar radiation, temperature, and precipitation will produce changes in crop yields, crop mix, cr...

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Section: Wheat Crop Model (Ceres-wheat)mentioning

confidence: 99%

“…The DSSAT itself is a shell that allows the user to organize and manipulate data and to run crop models in various ways and analyze their outputs (Hoogenboom et al 1995, Thornton et al 1997. DSSAT version 3.5 was used in this analysis.…”

Section: Wheat Crop Model (Ceres-wheat)mentioning

confidence: 99%

Sensitivity of winter wheat yields in the Midwestern United States to future changes in climate, climate variability, and CO2 fertilization

Southworth

Pfeifer²,

Habeck³

et al. 2002

Clim. Res.

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“…CROPGROPeanut performed well in recent experiments in northern Benin (Adomou et al, 2005) and Ghana (Naab et al, 2004) taking into account disease damage. For an experiment at Tara, Niger, CERES-Millet substantially over predicted LAI, biomass, grain yield and soil water Fechter et al (Fechter et al, 1991), Fechter (1993, Mbabaliye and Wojtkowski (1994), Wafula (1995), Soler et al (2008) Fertilizer management Maize (Dry and wet Nigeria), maize (Malawi) Jagtap (1999), Thornton et al (1997), MacCarthy et al (2012; Adamou et al (2012), Irrigation and water management Wheat (Egypt), Wheat (Zimbabwe), Millet under Zaï Kamel et al (1995), Macrobert and Savage (1998);Fatondji et al (2012). Climate change and variability Maize (Zimbabwe) Muchena and Iglesia (1995), Phillips et al (1998) …”

Section: Dssat (Ceres and Cropgro)mentioning

confidence: 99%

“…Jagtap et al (1999) describe decision applications in a more subhumid environment in Nigeria. Thornton et al (1997) developed a prototype GIS-based, real-time yield forecasting system for Burkina Faso that uses CERESMillet and satellite-derived precipitation estimates combined with historic weather data series. CROPGROPeanut performed well in recent experiments in northern Benin (Adomou et al, 2005) and Ghana (Naab et al, 2004) taking into account disease damage.…”

Section: Dssat (Ceres and Cropgro)mentioning

confidence: 99%

Soil water crop modeling for decision support in millet-based systems in the Sahel: a challenge

Gérard¹,

Bielders²

2014

Afr. J. Agric. Res.

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Food insecurity in the Sahelian environment was extensively shown to be a result of low soil fertility and high climate risks. But decisions and recommendations made from the great wealth of research have little been adopted by farmers. Soil water crop models (SWCM) can assist researchers and development actors in this environment if they can appropriately deal with the constraints and mainly farmers' agricultural development goals. We reviewed the Sahelian agricultural constraints and farmer management practices with an emphasis on Niger and pearl millet. Significant results derived from research works to improve crop productivity are presented and analyzed with regard to the main agricultural constraints. Potential and currently used SWCMs are presented and compared for relevance for use in such a particular environment for decision support (DS). This shows that crop modeling in millet-based agricultural system of the Sahel should be addressed with an integrated approach that can handle the multiple and usually connected agricultural constraints of the region: low soil fertility and spatial variability, time and space rainfall variability. Recommendations were made regarding the relevant and minimum aspects that SWCM should take into account for a successful and reliable use for DS in the complex Sahelian environment.

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“…At the same time, land surface moisture is a significant component of the hydrologic cycle [2] with important feedback to the atmosphere [3]. Monitoring surface moisture to detect drought is a challenging subject, and due to a generally insufficient number of conventional ground based climate observation sites in the region, the development of reliable Early Warning Systems (EWS) exploiting the capabilities of Earth Observation (EO) data for this purpose, has been an important topic for decades [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Relation between Seasonally Detrended Shortwave Infrared Reflectance Data and Land Surface Moisture in Semi‑Arid Sahel

et al. 2013

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Abstract:In the Sudano-Sahelian areas of Africa droughts can have serious impacts on natural resources, and therefore land surface moisture is an important factor. Insufficient conventional sites for monitoring land surface moisture make the use of Earth Observation data for this purpose a key issue. In this study we explored the potential of using reflectance data in the Red, Near Infrared (NIR), and Shortwave Infrared (SWIR) spectral regions for detecting short term variations in land surface moisture in the Sahel, by analyzing data from three test sites and observations from the geostationary Meteosat Second Generation (MSG) satellite. We focused on responses in surface reflectance to soil-and surface moisture for bare soil and early to mid-growing season. A method for implementing detrended time series of the Shortwave Infrared Water Stress Index (SIWSI) is examined for detecting variations in vegetation moisture status, and is compared to detrended time series of the Normalized Difference Vegetation Index (NDVI). It was found OPEN ACCESSRemote Sens. 2013, 5 2899 that when plant available water is low, the SIWSI anomalies increase over time, while the NDVI anomalies decrease over time, but less systematically. Therefore SIWSI may carry important complementary information to NDVI in terms of vegetation water status, and can provide this information with the unique combination of temporal and spatial resolution from optical geostationary observations over Sahel. However, the relation between SIWSI anomalies and periods of water stress were not found to be sufficiently robust to be used for water stress detection.

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Estimating millet production for famine early warning: an application of crop simulation modelling using satellite and ground-based data in Burkina Faso

Cited by 88 publications

References 4 publications

Sensitivity of winter wheat yields in the Midwestern United States to future changes in climate, climate variability, and CO2 fertilization

Sensitivity of winter wheat yields in the Midwestern United States to future changes in climate, climate variability, and CO2 fertilization

Soil water crop modeling for decision support in millet-based systems in the Sahel: a challenge

Relation between Seasonally Detrended Shortwave Infrared Reflectance Data and Land Surface Moisture in Semi‑Arid Sahel

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