Development of an ENSO-based irrigation decision support tool for peanut production in the southeastern US

Paz, Joel O.; Fraisse, Clyde W.; Hatch, L. Upton; García, Axel García y; Guerra, Larry C.; Uryasev, O.; Bellow, J. G.; Jones, James W.; Hoogenboom, Gerrit

doi:10.1016/j.compag.2006.11.003

Cited by 44 publications

(22 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given that ENSO has a significant effect on the rainfall patterns in the southeastern USA, the Southeast Climate Consortium (SECC; www.SEClimate.org) was formed as an inter-and transdisciplinary programme to develop a system of seasonal climate forecasts (SCFs) and related crop management tools, with the intention of developing tools that can help farmers manage risks and opportunities related to inter-annual climate variability [23][24][25][26]. ENSO-based seasonal forecasts are a very recent development, since scientific understanding of the ENSO phenomenon, and thus the capacity to provide reasonably reliable forecasts, has really only begun to solidify in the last 15 years.…”

Section: Seasonal Adjustments In Georgia Usamentioning

confidence: 99%

Adaptation to climate change and climate variability: The importance of understanding agriculture as performance

Crane

Roncoli

Hoogenboom

2011

NJAS: Wageningen Journal of Life Sciences

Self Cite

187

102

View full text Add to dashboard Cite

a b s t r a c tMost climate change studies that address potential impacts and potential adaptation strategies are largely based on modelling technologies. While models are useful for visualizing potential future outcomes and evaluating options for potential adaptation, they do not adequately represent and integrate adaptive human agency. Richards' concept of 'agriculture as performance' is useful in counterbalancing the modelling approach to adaptation because it highlights how adaptive processes and technologies, whether short term or long term, are more than simple technical responses to biophysical conditions. Instead, adaptive processes are social phenomena whose significance and effects expand well beyond changing climate conditions. This examination of agriculture as performance in the context of climate adaptation draws on two different examples. The first example explores how technical aspects of climate adaptation in Mali are situated within the enactment of ethnic identities and political struggles between farmers and herders. The second example shows how farmers in southeastern United States approach climate variability and climate forecasts as risk management tools. There are substantial differences between approaching adaptation as a dynamic process that is socially embedded and approaching adaptation as a set of modelled responses to anticipated future conditions. It is unlikely that either is adequate to meet the challenges posed by the uncertainties associated with climate change. However, building a synergistic relationship between the two promises to be as difficult as it is necessary.

show abstract

Section: Seasonal Adjustments In Georgia Usamentioning

confidence: 99%

Adaptation to climate change and climate variability: The importance of understanding agriculture as performance

Crane

Roncoli

Hoogenboom

2011

NJAS: Wageningen Journal of Life Sciences

Self Cite

187

102

View full text Add to dashboard Cite

show abstract

“…Although the modified WGENR is not an empirical model among the 16 models evaluated, it was compared with other models because it has been used as a major solar radiation generator in the southeastern United States Fraisse et al 2006Fraisse et al , 2007Fraisse 2007;Garcia y Garcia et al 2007, 2010Paz et al 2007;Persson et al 2009aPersson et al ,b, 2010a. Equation (16) was added to the list of the models evaluated as an alternative to the Wu et al (2007) model [Eq.…”

Section: ) T-or P-based Modelsmentioning

confidence: 99%

“…Garcia y Garcia et al (2008) studied the effect of R g generated through the Weather Generator for Solar Radiation (WGENR) model, a stochastic R g generator originally developed by Hodges et al (1985) and later modified for the southeastern conditions by Garcia y Garcia and Hoogenboom (2005), on simulated yield of cotton, maize, and peanut at various locations in Georgia. The modified WGENR has been used as a principal solar radiation generator for crop modeling purposes in this region Fraisse et al 2006Fraisse et al , 2007Fraisse 2007;Garcia y Garcia et al 2007, 2010Paz et al 2007;Persson et al 2009aPersson et al ,b, 2010a.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Various Methods for Estimating Global Solar Radiation in the Southeastern United States

Woli

Paz

2012

Journal of Applied Meteorology and Climatology

View full text Add to dashboard Cite

Global solar radiation R g is an important input for crop models to simulate crop responses. Because the scarcity of long and continuous records of R g is a serious limitation in many countries, R g is estimated using models. For crop-model application, empirical R g models that use commonly measured meteorological variables, such as temperature and precipitation, are generally preferred. Although a large number of models of this kind exist, few have been evaluated for conditions in the United States. This study evaluated the performances of 16 empirical, temperature-and/or precipitation-based R g models for the southeastern United States. By taking into account spatial distribution and data availability, 30 locations in the region were selected and their daily weather data spanning eight years obtained. One-half of the data was used for calibrating the models, and the other half was used for evaluation. For each model, location-specific parameter values were estimated through regressions. Models were evaluated for each location using the root-meansquare error and the modeling efficiency as goodness-of-fit measures. Among the models that use temperature or precipitation as the input variable, the Mavromatis model showed the best performance. The piecewise linear regression-based Wu et al. model (WP) performed best not only among the models that use both temperature and precipitation but also among the 16 models evaluated, mainly because it has separate relationships for low and high radiation levels. The modeling efficiency of WP was from ;5% to more than 100% greater than those of the other models, depending on models and locations.

show abstract

“…soils parameters). Dynamic crop models are becoming important decision support systems for monitoring crops and for assessing the impact of soils, management decisions, weather and climate change on crops (Paz et al, 2007;Semenov and DoblasReyes, 2007;Challinor and Wheeler, 2008). In fact, the simulation of crop parameters under different conditions, scenarios and stresses are key outcomes from crop models.…”

Section: Dynamic Crop Modelsmentioning

confidence: 99%

Application of crop modelling to portuguese viticulture: implementation and added-values for strategic planning

Costa

Fraga

Malheiro

et al. 2015

Ciência Téc. Vitiv.

View full text Add to dashboard Cite

SUMMARYGrapevine (Vitis vinifera L.) is a very important crop in Portugal, where the viticultural sector plays a central role in the national economy. The present study provides a review of most relevant research on grapevine modelling, giving particular emphasis to its past and future applicability to Portuguese conditions. A brief overview of the national sector, as well as of the prevailing physical and biological environments and viticultural practices is provided. Further, the terroir concept is discussed in view of the main controlling factors of grapevine development. Several crop models, either statistical or dynamic, that have reliably simulated grapevine/vineyard parameters, such as phenology, yield and quality, are referred. Statistical models are based on statistically significant relationships between a number of predictors and a given grapevine parameter. Dynamic crop models simulate plant growth and development and holistically integrate crop phenotype, soil profiles, weather and climate data and management practices in their simulations. Dynamic crop models are then becoming important decision support systems in viticulture. Additionally, they allow testing the effects of soils, management decisions and weather on crops. However, only a few dynamic models can properly simulate grapevine performance. Several studies also apply crop models under future conditions to assess the detrimental climate change impacts on grapevines. These crop models can be either applied to real-time monitoring and short-range predictions or to develop long-term climate change projections for the Portuguese viticulture. These studies will represent important added-values for the competitiveness and future sustainability of the winemaking sector in Portugal. RESUMOA videira (Vitis vinifera L.) é uma cultura de grande relevo em Portugal, onde o sector vitivinícola desempenha um papel central na economia nacional. O presente estudo fornece uma revisão de pesquisas mais relevantes sobre a modelação da videira, dando especial ênfase à sua aplicabilidade às condições específicas portuguesas. É dada uma visão sucinta do sector nacional, bem como das condições físicas, biológicas e práticas vitivinícolas predominantes. O conceito de terroir é discutido tendo em conta os principais fatores condicionantes do desenvolvimento da videira. São referidos vários modelos de culturas, estatísticos e dinâmicos, que têm simulado com sucesso as características da videira/vinha, fenologia, produtividade e qualidade. Os modelos estatísticos são baseados em relações estatisticamente significativas entre um número de preditores e uma determinada característica da videira. Os modelos dinâmicos simulam o crescimento e desenvolvimento da planta de forma holística, integrando nas suas simulações o fenótipo da cultura, perfis de solo, dados meteorológicos e práticas culturais. Por este motivo, os modelos dinâmicos estão a tornar-se importantes sistemas de apoio à decisão em viticultura. Além disso, permitem prever os efeitos do solo, das práticas cul...

show abstract

Development of an ENSO-based irrigation decision support tool for peanut production in the southeastern US

Cited by 44 publications

References 10 publications

Adaptation to climate change and climate variability: The importance of understanding agriculture as performance

Adaptation to climate change and climate variability: The importance of understanding agriculture as performance

Evaluation of Various Methods for Estimating Global Solar Radiation in the Southeastern United States

Application of crop modelling to portuguese viticulture: implementation and added-values for strategic planning

Contact Info

Product

Resources

About