scholarly journals Impact of Climate Change on Crop Yield: A Case Study of Rainfed Corn in Central Illinois

2009 ◽  
Vol 48 (9) ◽  
pp. 1868-1881 ◽  
Author(s):  
Ximing Cai ◽  
Dingbao Wang ◽  
Romain Laurent
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Crop Yield ◽  
Climate Models ◽  
Regional Scale ◽  
Risk Estimate ◽  
Yield Reduction ◽  
Equal Weight ◽  
Corn Yield ◽  
Central Illinois

Abstract This paper assesses the effect of climate change on crop yield from a soil water balance perspective. The uncertainties of regional-scale climate models, local-scale climate variability, emissions scenarios, and crop growth models are combined to explore the possible range of climate change effects on rainfed corn yield in central Illinois in 2055. The results show that a drier and warmer summer during the corn growth season and wetter and warmer precrop and postcrop seasons will likely occur. Greater temperature and precipitation variability may lead to more variable soil moisture and crop yield, and larger soil moisture deficit and crop yield reduction are likely to occur more frequently. The increased water stress is likely to be most pronounced during the flowering and yield formation stages. The expected rainfed corn yield in 2055 is likely to decline by 23%–34%, and the probability that the yield may not reach 50% of the potential yield ranges from 32% to 70% if no adaptation measures are instituted. Among the multiple uncertainty sources, the greenhouse gas emissions projection may have the strongest effect on the risk estimate of crop yield reduction. The effects from the various uncertainties can be offset to some degree when the uncertainties are considered jointly. An ensemble of GCMs with an equal weight may overestimate the risk of soil moisture deficits and crop yield reduction in comparison with an ensemble of GCMs with different weight determined by the root-mean-square error minimization method. The risk estimate presented in this paper implies that climate change adaptation is needed to avoid reduced corn yields and the resulting profit losses in central Illinois.

Usage of soil moisture models in agronomic research

1996 ◽  
Vol 76 (3) ◽  
pp. 285-295 ◽  
Author(s):  
O. O. Akinremi ◽  
S. M. McGinn
Keyword(s):  
Soil Moisture ◽  
Grain Yield ◽  
Water Use ◽  
Crop Yield ◽  
Drought Index ◽  
Regional Scale ◽  
Irrigation Scheduling ◽  
Water Model ◽  
Yield Reduction ◽  
Efficiency Coefficient

Soil moisture controls many important processes in the soil-plant system and the extent of these processes cannot be quantified without knowing moisture status of the root zone. Of agronomic importance these include, seedling emergence, evapotranspiration, mineralization of the soil organic fraction, surface runoff, leaching and crop yield. Many models have been developed to simulate these processes based on algorithms of varying degrees of complexity that describe the dynamic nature of soil moisture at different temporal and spatial scales. This paper reviews the direct applications of soil moisture models in agronomy from the field to regional scale and for daily to seasonal time steps. At every level of detail, the lack of model validation beyond the region where it was developed is the main limitation to the application of soil moisture models in agronomy. At the field scale, models have been used for irrigation scheduling to ensure efficient utilization of irrigation water and maximize crop yields. Models are also used to estimate crop yield based on the growing season water use. The water use of crops is converted to biomass accumulation and grain yield using a water-use efficiency coefficient and a harvest index. Other empirical equations are available that relate cumulative crop water use directly to grain yield. On a regional scale, in a study of drought climatology on the Canadian prairie, we coupled a soil water model, the Versatile Soil Moisture Budget, with the Palmer Drought Index model to improve the modelling of soil moisture. This was found to improve the relationship of the Palmer drought index to wheat yield reduction resulting from drought. Key words: Soil moisture, modelling, water-use, evapotranspiration, aridity index, Canadian prairies

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals Meteorological, soil moisture, surface water, and groundwater data from the St Denis National Wildlife Area, Saskatchewan, Canada

2018 ◽  
Author(s):  
Edward K. P. Bam ◽  
Rosa Brannen ◽  
Sujata Budhathoki ◽  
Andrew M. Ireson ◽  
Chris Spence ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Surface Water ◽  
Climate Models ◽  
Multiple Scales ◽  
Full Range ◽  
Research Network ◽  
Groundwater Levels ◽  
Groundwater Availability ◽  
Surface Water And Groundwater

Abstract. Long-term meteorological, soil moisture, surface water, and groundwater data provide information on past climate change, most notably information that can be used to analyze past changes in precipitation and groundwater availability in a region. These data are also valuable to test, calibrate and validate hydrological and climate models. CCRN (Changing Cold Regions Network) is a collaborative research network that brought together a team of over 40 experts from 8 universities and 4 federal government agencies in Canada for 5 years (2013–18) through the Climate Change and Atmospheric Research (CCAR) Initiative of the Natural Sciences and Engineering Research Council of Canada (NSERC). The working group aimed to integrate existing and new data with improved predictive and observational tools to understand, diagnose and predict interactions amongst the cryospheric, ecological, hydrological, and climatic components of the changing Earth system at multiple scales, with a geographic focus on the rapidly changing cold interior of Western Canada. The St Denis National Wildlife Area database contains data for the prairie research site, St Denis National Wildlife Research Area, and includes atmosphere, soil, and groundwater. The meteorological measurements are observed every 5 seconds, and half-hourly averages (or totals) are logged. Soil moisture data comprise volumetric water content, soil temperature, electrical conductivity and matric potential for probes installed at depths of 5 cm, 20 cm, 50 cm, 100 cm, 200 cm and 300 cm in all soil profiles. Additional data on snow surveys, pond and groundwater levels, and water isotope isotopes collected on an intermittent basis between 1968 and 2018 are also presented including information on the dates and ground elevations (datum) used to construct hydraulic heads. The metadata table provides location information, information about the full range of measurements carried out on each parameter and GPS locations that are relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.20383/101.0115.

scholarly journals PEMANFAATAN MODEL PROYEKSI IKLIM DAN SIMULASI TANAMAN DALAM PENGUATAN ADAPTASI SISTEM PERTANIAN PADI TERHADAP PENURUNAN PRODUKTIVITAS AKIBAT PERUBAHAN IKLIM: STUDI KASUS DI KABUPATEN SUMEDANG, JAWA BARAT

2016 ◽  
Vol 23 (2) ◽  
pp. 159
Author(s):  
Candradijaya A
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Rice Yield ◽  
Local Level ◽  
Irrigation Scheduling ◽  
Yield Reduction ◽  
Planting Time ◽  
Near Future ◽  
Far Future

Despite the well-documented model-simulated adverse climate change impact on rice yields reported elsewhere, interventions to address the issue seem to be still limited, particularly at local level. This links to the uncertainty that entails to climate projection and its likely future impact, which varies across regions and climate models. The study analyzes climate change-induced rice yield reduction and the adequacy of current adaptations, to cope with a large range of impact under various climate models. Seventeen General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) climate change with scenarios of RCP8.5 and RCP4.5, combined with CROPWAT model for near-future (2011-2040) and far-future (2041-2070) projections. The study was conducted in November-December 2013, in Ujungjaya Subdistrict, the District of Sumedang. The output confirms yield reduction to occur in the near-future, to the extent variable across the GCMs. At the highest estimation, rice yield decreases by 32.00% and 31.81%, in comparison to baseline, for near-future under RCP8.5 and RCP4.5, respectively. The reduction extends, with a slightly higher degree, to the far-future. The reduction is sensitive to variation in farming practices of the local farmers, in particular that in planting time and irrigation scheduling. The shifting of planting time to better match rainfall pattern reduces the rice yield by 12.95% for rainfed and 14.07% for the irrigated farming. Meanwhile, improved irrigation scheduling reduces the yield reduction by 16.16%. The findings provide valuable inputs for relevant authorities to understand the climate change-induced rice yield reduction, and to formalate intervention strategies for spesific-location adaptation.

A COMPARISON OF SOME TILLAGE METHODS FOR CORN ON BROOKSTON CLAY SOIL

1957 ◽  
Vol 37 (2) ◽  
pp. 113-119
Author(s):  
E. F. Bolton ◽  
J. W. Aylesworth
Keyword(s):  
Soil Moisture ◽  
Crop Yield ◽  
Clay Soil ◽  
Corn Yield ◽  
Corn Production ◽  
Moisture Supply ◽  
Second Year ◽  
Tillage Method ◽  
Tillage Methods

Methods of mulch-planting were compared with mouldboard-ploughing methods for corn production at Woodslee during 1953, 1954 and 1955. The tillage treatments were established in second-year alfalfa sod on Brookston clay soil. On the basis of corn yield the conventional ploughing treatments were greatly superior to any mulch-plant method tested during the three years. Soil moisture studies indicated that the effect of the intercrop on the soil moisture supply was the major factor influencing crop yield, but moisture alone did not account entirely for the differences obtained in crop yield. The plough-plant method produced as good corn yields as spring ploughing in 1953 but somewhat less in 1954 and 1955. The results would suggest that an adaptation of the plough-plant method may have possible application as a tillage method for corn on the finer textured soils of southwestern Ontario.

scholarly journals Soil moisture regimes in Mexico in a global 1.5°C warming scenario

2019 ◽  
Vol 11 (4) ◽  
pp. 465-482 ◽  
Author(s):  
Jesus David Gomez Diaz ◽  
Alejandro I. Monterroso ◽  
Patricia Ruiz ◽  
Lizeth M. Lechuga ◽  
Ana Cecilia Conde Álvarez ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Regional Scale ◽  
Moisture Regime ◽  
Monthly Precipitation ◽  
Climate Change Scenarios ◽  
Content Type ◽  
Warming Scenario ◽  
Moisture Regimes ◽  
Gfdl Model

Purpose This study aims to present the climate change effect on soil moisture regimes in Mexico in a global 1.5°C warming scenario. Design/methodology/approach The soil moisture regimes were determined using the Newhall simulation model with the database of mean monthly precipitation and temperature at a scale of 1: 250,000 for the current scenario and with the climate change scenarios associated with a mean global temperature increase of 1.5°C, considering two Representative Concentration Pathways, 4.5 and 8.5 W/m2 and three general models of atmospheric circulation, namely, GFDL, HADGEM and MPI. The different vegetation types of the country were related to the soil moisture regimes for current conditions and for climate change. Findings According to the HADGEM and MPI models, almost the entire country is predicted to undergo a considerable increase in soil moisture deficit, and part of the areas of each moisture regime will shift to the next drier regime. The GFDL model also predicts this trend but at smaller proportions. Originality/value The changes in soil moisture at the regional scale that reveal the impacts of climate change and indicate where these changes will occur are important elements of the knowledge concerning the vulnerability of soils to climate change. New cartography is available in Mexico.

scholarly journals The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale

2018 ◽  
Vol 99 (11) ◽  
pp. 2341-2359 ◽  
Author(s):  
M. J. Roberts ◽  
P. L. Vidale ◽  
C. Senior ◽  
H. T. Hewitt ◽  
C. Bates ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Regional Scale ◽  
Coupled Model ◽  
Convective Precipitation ◽  
Climate Simulation ◽  
Intergovernmental Panel

AbstractThe time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain of processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms).

Large contribution from anthropogenic warming to an emerging North American megadrought

Science ◽  
2020 ◽  
Vol 368 (6488) ◽  
pp. 314-318 ◽  
Author(s):  
A. Park Williams ◽  
Edward R. Cook ◽  
Jason E. Smerdon ◽  
Benjamin I. Cook ◽  
John T. Abatzoglou ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
North America ◽  
Relative Humidity ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Drought Severity ◽  
Large Contribution ◽  
Moderate Drought

Severe and persistent 21st-century drought in southwestern North America (SWNA) motivates comparisons to medieval megadroughts and questions about the role of anthropogenic climate change. We use hydrological modeling and new 1200-year tree-ring reconstructions of summer soil moisture to demonstrate that the 2000–2018 SWNA drought was the second driest 19-year period since 800 CE, exceeded only by a late-1500s megadrought. The megadrought-like trajectory of 2000–2018 soil moisture was driven by natural variability superimposed on drying due to anthropogenic warming. Anthropogenic trends in temperature, relative humidity, and precipitation estimated from 31 climate models account for 46% (model interquartiles of 34 to 103%) of the 2000–2018 drought severity, pushing an otherwise moderate drought onto a trajectory comparable to the worst SWNA megadroughts since 800 CE.

scholarly journals Varying soil moisture-atmosphere feedbacks explain divergent temperature extremes and precipitation projections in Central Europe

2018 ◽  
Author(s):  
Martha M. Vogel ◽  
Jakob Zscheischler ◽  
Sonia I. Seneviratne
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Central Europe ◽  
Climate Models ◽  
Global Climate ◽  
Summer Precipitation ◽  
Global Climate Models ◽  
Temperature Extremes ◽  
Extreme Temperatures

Abstract. The frequency and intensity of climate extremes is expected to increase in many regions due to anthropogenic climate change. In Central Europe extreme temperatures are projected to change more strongly than global mean temperatures and soil moisture-temperature feedbacks significantly contribute to this regional amplification. Because of their strong societal, ecological and economic impacts, robust projections of temperature extremes are needed. Unfortunately, in current model projections, temperature extremes in Central Europe are prone to large uncertainties. In order to understand and potentially reduce uncertainties of extreme temperatures projections in Europe, we analyze global climate models from the CMIP5 ensemble for the business-as-usual high-emission scenario (RCP8.5). We find a divergent behavior in long-term projections of summer precipitation until the end of the 21st century, resulting in a trimodal distribution of precipitation (wet, dry and very dry). All model groups show distinct characteristics for summer latent heat flux, top soil moisture, and temperatures on the hottest day of the year (TXx), whereas for net radiation and large-scale circulation no clear trimodal behavior is detectable. This suggests that different land-atmosphere coupling strengths may be able to explain the uncertainties in temperature extremes. Constraining the full model ensemble with observed present-day correlations between summer precipitation and TXx excludes most of the very dry and dry models. In particular, the very dry models tend to overestimate the negative coupling between precipitation and TXx, resulting in a too strong warming. This is particularly relevant for global warming levels above 2 °C. The analysis allows for the first time to substantially reduce uncertainties in the projected changes of TXx in global climate models. Our results suggest that long-term temperature changes in TXx in Central Europe are about 20 % lower than projected by the multi-model median of the full ensemble. In addition, mean summer precipitation is found to be more likely to stay close to present-day levels. These results are highly relevant for improving estimates of regional climate-change impacts including heat stress, water supply and crop failure for Central Europe.

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

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