Download or read book Detecting the Effect of Dust and Other Climate Variables on Crop Yields Using Diagnostic Statistical Crop Models written by Alexis Hoffman and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Food security and agriculture productivity assessments require a strong understanding of how climate and other drivers influence regional crop yields. While the effects of temperature, precipitation, and carbon dioxide are relatively well-understood, the effect of dust on crop yields has yet to be thoroughly investigated. This line of inquiry is warranted because many areas of the world with frequent dust storms and high dust loadings are often food insecure, and because wind erosion is prevalent in the High Plains of the United States, a major crop-producing area. Existing research suggests that the effect of dust on yields should be largely negative, but until now this has not been investigated on a regional scale. A major hindrance to understanding the effect of dust on crop yields is insufficient data and inadequate methods of analysis. In this dissertation, we developed data and analysis methods for three distinct projects to determine whether dust affects regional crop yields. In the first project, we validated the use of random forest, a machine learning technique, as a diagnostic crop model that can be used to assess the impact of individual climate predictors on yields. Because we motivated this research with food security concerns, we analyzed climate signals in the crop yield record of sub-Saharan Africa from 1962-2014. From this work, we determined that random forest could function as a statistical crop model, but the data quality and resolution inhibited the ability to detect the effect of dust on yields in this area of the world. In our second line of inquiry, we shifted the focus to the central region of the United States for its high quality and high resolution data, as well as its importance as a major crop-producing region of the world. Because these data had higher temporal resolution, we could explore individual phases of the growing season. We developed crop-specific algorithms to compute the planting date, establishment phase, critical window, and grain filling phase to investigate yield responses to phase-specific climate predictors. Using these data, the random forest identified distinct phase-specific responses for important climate predictors. Finally, we computed dust metrics from three different data sources and merged them with climate and yield data in the central region of the United States to estimate the impact of dust on yields. Over the entire central US region, we found that including dust as a predictor in each crop model did not improve yield predictions for the region as a whole. However, when crop models were applied to individual states, we found several instances in which dust weakly reduced yields. Although these state-specific results were encouraging, we presented them cautiously because the yield responses could be an artifact of either partitioning the data or a true yield response that is obscured when data was spatially aggregated. While the results were largely inconclusive, we have advanced the capabilities of statistical crop modeling, developed data sets that can be used to move the science forward, and revealed new questions that merit further research.
Download or read book Improving Modeling Tools to Assess Climate Change Effects on Crop Response written by Jerry L. Hatfield and published by John Wiley & Sons. This book was released on 2020-01-22 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crop model intercomparison and improvement are required to advance understanding of the impact of future climate change on crop growth and yield. The initial efforts undertaken in the Agriculture Model Intercomparison and Improvement Project (AgMIP) led to several observations where crop models were not adequately simulating growth and development. These studies revealed where enhanced efforts should be undertaken in experimental data to quantify the carbon dioxide × temperature × water interactions in plant growth and yield. International leaders in this area held a symposium at the 2013 ASA, CSSA, and SSSA Annual Meeting to discuss this topic. This volume in the Advances in Agricultural Systems Modeling series presents experimental observations across crops and simulation modeling outcomes and addresses future challenges in improving crop simulation models. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.
Download or read book Prediction of Crop Yields Under a Changing Climate written by Godfrey Shem Juma and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The impact of increasing climate variability on crop yield is now evident. Predicting the potential effects of climate change on crops prompts the use of statistical models to measure how the crop responds to climate variables. This chapter examines the usage of regression analysis in predicting crop yield under a changing climate. Data quality control is explained and application of descriptive statistics, correlation analysis and contingency tables discussed. Methodological aspects of crop yield modeling and prediction using climate variables are described. Estimation of yield via a multilinear regression approach is outlined and an overview of statistical model verification introduced. The study recommends the usage of regression models in estimating crop yield in consideration of many other externalities that can contribute to yield change.
Download or read book Impacts of Climate Change and Agricultural Managements on Major Global Cereal Crops written by Xuhui Wang and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Croplands accounts for one-fifth of global land surface, providing calories for human beings and altering the global biogeochemical cycle and land surface energy balance. The response of croplands to climate change and intensifying human managements is of critical importance to food security and sustainability of the environment. The present manuscript of thesis utilizes various types of data sources (yield statistics, long-term agrometeorological observations, field warming experiments, data-driven global datasets, gridded historical climate dataset and projected climate change) and also modelling approaches (statistical model vs. process model). It presents a series of detection and attribution studies exploring how crop phenology and crop yield respond to climate change and some management practices at regional and global scales, according to data availability. In Chapter 2, a statistical model is constructed with prefecture-level yield statistics and historical climate observations over Northeast China. There are asymmetrical impacts of daytime and nighttime temperatures on maize yield. Maize yield increased by 10.0±7.7% in response to a 1 oC increase of daily minimum temperature (Tmin) averaged in the growing season, but decreased by 13.4±7.1% in response to a 1 oC warming of daily maximum temperature (Tmax). There is a large spatial variation in the yield response to Tmax, which can be partly explained by the spatial gradient of growing season mean temperature (R=-0.67, P0.01). The response of yield to precipitation is also dependent on moisture conditions. In spite of detection of significant impacts of climate change on yield variations, a large portion of the variations is not explained by climatic variables, highlighting the urgent research need to clearly attribute crop yield variations to change in climate and management practices. Chapter 3 presents the development of a Bayes-based optimization algorithm that is used to optimize key parameters controlling phenological development in ORCHIDEE-crop model for discriminating effects of managements from those of climate change on rice growth duration (LGP). The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends, but with dependency on rice types. Climate trends have shortened LGP of early rice (-2.0±5.0 day/decade), lengthened LGP of late rice (1.1±5.4 day/decade) and have little impacts on LGP of single rice (-0.4±5.4 day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate-change-induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management is predominant driver of LGP change for early and single rice. This chapter demonstrated the capability of the optimized crop model to represent complex regional variations of LGP. Future studies should better document observational errors and management practices in order to reduce large uncertainties that exist in attribution of LGP change and to facilitate further data-model integration. In Chapter 4, a harmonized data set of field warming experiments at 48 sites across the globe for the four most-widely-grown crops (wheat, maize, rice and soybean) is combined with an ensemble of gridded global crop models to produce emergent constrained estimates of the responses of crop yield to changes in temperature (ST). The new constraining framework integrates evidences from field warming experiments and global crop modeling shows with 95% probability that warmer temperatures would reduce yields for maize (-7.1±2.8% K-1), rice (-5.6±2.0% K-1) and soybean (-10.6±5.8% K-1). For wheat, ST was less negative and only 89% likely to be negative (-2.9±2.3% K-1). The field-observation based constraints from the results of the warming experiments reduced uncertainties associated with modeled ST by 12-54% for the four crops.
Download or read book Making Climate Forecasts Matter written by National Research Council and published by National Academies Press. This book was released on 1999-05-27 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: El Nino has been with us for centuries, but now we can forcast it, and thus can prepare far in advance for the extreme climatic events it brings. The emerging ability to forecast climate may be of tremendous value to humanity if we learn how to use the information well. How does society cope with seasonal-to-interannual climatic variations? How have climate forecasts been usedâ€"and how useful have they been? What kinds of forecast information are needed? Who is likely to benefit from forecasting skill? What are the benefits of better forecasting? This book reviews what we know about these and other questions and identifies research directions toward more useful seasonal-to-interannual climate forecasts. In approaching their recommendations, the panel explores: Vulnerability of human activities to climate. State of the science of climate forecasting. How societies coevolved with their climates and cope with variations in climate. How climate information should be disseminated to achieve the best response. How we can use forecasting to better manage the human consequences of climate change.
Download or read book Crop weather Models and Their Use in Yield Assessments written by Wolfgang Baier and published by . This book was released on 1977 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Overzicht van de technieken die momenteel aangewend worden voor het simuleren en analyseren van de reacties van het gewas op het klimaat. Speciale aandacht wordt gegeven aan het gebruik van empirisch-statistische opbrengst-schattingsmodellen voor tarwe
Download or read book Modeling Framework to Evaluate the Impacts of Climate Change on Crop Productivity Over a Diverse Region written by Ali Ismaeel and published by . This book was released on 2021 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crop productivity is an essential component of food security which is affected by multiple biotic and abiotic parameters, including climate variations. Previous studies have reported variable impacts of climate change on crop productivity depending upon the climatic parameter analyzed or the study region's characteristics. The negative impacts of climate change on crop productivity can be eased by adopting efficient strategies and making the cropping system more resilient towards extreme events. Process-based crop models provide a unique opportunity to study the complex interactions of physiological conditions and agronomic practices from a local to regional scale. Previous large-scale crop model studies have used spatially aggregated biophysical, climatic, and crop management conditions to provide generalized climate change assessments of crop production. The exclusion of regional cropland diversity remains a persistent flaw in large- scale crop model studies that may mislead adaptation strategies at the local scale. This research aims to design a modeling framework to evaluate climate change impacts on crop productivity over a diverse region. Three aspects of the regional cropland diversity were focused on in this research: (a) existing climate-cropland nexus, (b) spatial variability of cropping system, and (c) spatiotemporal variations of crop management activities. Time-series data from satellite remote sensing were the primary input for the intended methodology. The machine learning algorithms to unearth hidden patterns in multitemporal data and GIS (Geographical Information System) capabilities to handle extensive geospatial data were employed to achieve the research objectives. The Indus River (IR) basin that stretches over four international territories of the developing world and fall under arid and semi-arid climatic zones was the focus of this research. The outcomes of the first research objective revealed variable existing cropland trends in the region. The climate-cropland nexus analysis pointed out that actual evapotranspiration and evaporative stress index are the primary climate-related parameters that control the IR's cropland trends. The proposed novel approach of mapping the cropping system revealed that wheat-cotton and wheat-rice are the two most crucial crop rotations in the region. The overall accuracy of identifying seasonal primary crop type was 88±3% when assessed against field observations using the error matrix. The remote sensing-based yield of wheat and rice was estimated with an accuracy of achieving the coefficient of determination (R2) values of 0.75 and 0.68, respectively. The spatiotemporal detection of crop types and their productivity levels were used to assess the diverse crop management practices in the region. A gridded model approach in the GIS was adopted to integrate cropland diversity in a crop model for future climate impact assessment on crop productivity. The crop model was calibrated and validated against reported wheat and rice yield by achieving a value of R2 and NSE (Nash-Sutcliffe Efficiency) ≥ 0.50. Future yield simulations revealed that wheat yield might decrease in highly productive regions but improve productivity in various other regions. Similarly, rice yield might severely decrease in southern parts but might increase in the IR basin's northern parts. The overall impact of carbon fertilization was positive on crop water use efficiency; yet a rise in temperature and severe rainfall reduction was the leading cause of a decline in crop productivity in various parts of the study region. Different adaptation and mitigation strategies to overcome projected yield losses for regional food security are also discussed in this dissertation.
Download or read book The Use of Statistical Climate crop Models for Simulating Yield to Project the Impacts of CO2 Induced Climate Change written by Wayne L. Decker and published by . This book was released on 1988 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Aggregation of Gridded Emulated Rainfed Crop Yield Projections at the National Or Regional Level written by Elodie Blanc and published by . This book was released on 2017 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: To estimate the impact of climate change on yields, researchers traditionally use process-based models or statistical models. To benefit from the capabilities of processed-based models while preserving the application simplicity of statistical models, Blanc and Sultan (2015) and Blanc (2017) provide an ensemble of statistical tools emulating crops yields from global gridded crop models at the grid cell level using a simple set of environmental variables. This paper and companion code provide a tool for researcher to use those statistical emulators and estimate crop yields of rainfed maize, rice, soybean and wheat at the regional level. Crop yields estimates for various regional delineations can then simply be used as input into a variety of numerical equilibrium models and other analyses. JEL codes: Q19, Q54. Keywords: Crop Yields; Crop Model; Statistical Model; Climate Change.
Download or read book Assessing and Modeling Crop Yield and Soil Carbon in Smallholder Fields in Africa and Central America written by Lin Liu and published by . This book was released on 2020 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on developing and testing agricultural tools for smallholder agricultural producers remains limited , despite the fact that new tools designed to improve agronomic management and resilience of cropping systems are becoming increasingly available also in developing countries. The overarching goal of this dissertation was to evaluate the efficacy of agricultural technologies, like process-based crop simulation models, to improve food production forecasts and crop yields in smallholder fields in low-income countries (Chapter 1). Chapter 2 presents the development and the validation of a new maize yield forecasting system for the Government of Tanzania. In this study, a field-based survey was integrated with a process-based crop model, Systems Approach to Land Use Sustainability (SALUS) to provide accurate and timely maize yield forecasts for small fields in Tanzania. In spite of a wide range of maize growing conditions, the method developed in the chapter has shown to provide reliable forecasts across three districts in Tanzania 14-77 days prior to crop harvest. Chapter 3 investigates how climate impact assessment differs when using the averaged value simulated with each climate model from the Coordinated Regional Climate Downscaling Experiment (CORDEX) program, versus one simulated value with one single delta-method projected climate based on average changes in climatic variables. This analysis was performed using SALUS-simulated grain yield, Soil Organic Caron (SOC) and soil inorganic Nitrogen (N) for 60 sites from Chapter 2. The simulated climate impact on soil N and SOC using the delta-method climate was close to the average simulated impact using each climate model, but the adverse impact on grain yield was projected to be lower.Chapter 4 focuses on agronomic management that could increase the yield of yam while improving soil fertility in Ghana. In this study, I first parameterized yam in the SALUS model using field experiment data from three N and phosphorous (P) fertilizer treatments combined with two yam cropping in two distinct agroecological zones in Ghana for two years. The calibrated and validated SALUS-Yam model was used to assess the impact of four management treatments: continuous unfertilized rainfed yam (control), pigeonpea-yam rotation, yam with 3 Mg/ha pigeonpea residue incorporated, and yam with 23-23 kg/ha N-P2O5 fertilizer added. The results showed that incorporating pigeonpea residues into yam fields produced the highest yam tuber yield and reduced SOC compared to the other treatments. This work also confirmed that yam cultivation in Ghana was mostly limited by lack of nutrients (N, P or both), as opposed to drought.Chapter 5 presents within-field variability of smallholder fields. From field observations in Tanzania, maize-based fields across more than 60 sites in three districts in Tanzania contained considerable variability in plant density (median CV 20-30%) and grain yield (median CV 30-36%). Grain yield variability was correlated with in-season vegetation indices, particularly the green chlorophyll vegetation index. The coefficient of variation of normalized difference vegetation index became smaller as the spatial resolution became coarser. The analysis was performed using images of distinct spatial resolutions for smallholder yam and pigeonpea fields in Ghana, and bean growing areas in Honduras. Lessons from the research projects and recommendations on using agricultural technologies for international agricultural development are outlined in Chapter 6.
Download or read book The Regional Impacts of Climate Change written by Intergovernmental Panel on Climate Change. Working Group II. and published by Cambridge University Press. This book was released on 1998 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cambridge, UK : Cambridge University Press, 1998.
Download or read book A Review and Evaluation of Weather crop Yield Models written by Joanne M. Geigel and published by . This book was released on 1984 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Global Climate Change Impacts in the United States written by U.S. Global Change Research Program and published by Cambridge University Press. This book was released on 2009-08-24 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizes the science of climate change and impacts on the United States, for the public and policymakers.
Download or read book Shock Waves written by Stephane Hallegatte and published by World Bank Publications. This book was released on 2015-11-23 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ending poverty and stabilizing climate change will be two unprecedented global achievements and two major steps toward sustainable development. But the two objectives cannot be considered in isolation: they need to be jointly tackled through an integrated strategy. This report brings together those two objectives and explores how they can more easily be achieved if considered together. It examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win†? situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.
Download or read book The impact of disasters and crises on agriculture and food security 2021 written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2021-03-17 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: On top of a decade of exacerbated disaster loss, exceptional global heat, retreating ice and rising sea levels, humanity and our food security face a range of new and unprecedented hazards, such as megafires, extreme weather events, desert locust swarms of magnitudes previously unseen, and the COVID-19 pandemic. Agriculture underpins the livelihoods of over 2.5 billion people – most of them in low-income developing countries – and remains a key driver of development. At no other point in history has agriculture been faced with such an array of familiar and unfamiliar risks, interacting in a hyperconnected world and a precipitously changing landscape. And agriculture continues to absorb a disproportionate share of the damage and loss wrought by disasters. Their growing frequency and intensity, along with the systemic nature of risk, are upending people’s lives, devastating livelihoods, and jeopardizing our entire food system. This report makes a powerful case for investing in resilience and disaster risk reduction – especially data gathering and analysis for evidence informed action – to ensure agriculture’s crucial role in achieving the future we want.
Download or read book Climate Change and Food Security written by David B. Lobell and published by Springer Science & Business Media. This book was released on 2009-12-21 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Roughly a billion people around the world continue to live in state of chronic hunger and food insecurity. Unfortunately, efforts to improve their livelihoods must now unfold in the context of a rapidly changing climate, in which warming temperatures and changing rainfall regimes could threaten the basic productivity of the agricultural systems on which most of the world’s poor directly depend. But whether climate change represents a minor impediment or an existential threat to development is an area of substantial controversy, with different conclusions wrought from different methodologies and based on different data. This book aims to resolve some of the controversy by exploring and comparing the different methodologies and data that scientists use to understand climate’s effects on food security. In explains the nature of the climate threat, the ways in which crops and farmers might respond, and the potential role for public and private investment to help agriculture adapt to a warmer world. This broader understanding should prove useful to both scientists charged with quantifying climate threats, and policy-makers responsible for crucial decisions about how to respond. The book is especially suitable as a companion to an interdisciplinary undergraduate or graduate level class.
Download or read book Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation written by Intergovernmental Panel on Climate Change and published by Cambridge University Press. This book was released on 2012-05-28 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extreme weather and climate events, interacting with exposed and vulnerable human and natural systems, can lead to disasters. This Special Report explores the social as well as physical dimensions of weather- and climate-related disasters, considering opportunities for managing risks at local to international scales. SREX was approved and accepted by the Intergovernmental Panel on Climate Change (IPCC) on 18 November 2011 in Kampala, Uganda.
