Quantification of the Impact of Temperature, CO2, and Rainfall Changes on Swedish Annual Crops Production Using the APSIM Model

Ongoing climate change is already affecting crop production patterns worldwide. Our aim was to investigate how increasing temperature and CO2 as well as changes in precipitation could affect potential yields for different historical pedoclimatic conditions at high latitudes (i.e., >55°). The APSIM crop model was used to simulate the productivity of four annual crops (barley, forage maize, oats, and spring wheat) over five sites in Sweden ranging between 55 and 64°N. A first set of simulations was run using site-specific daily weather data acquired between 1980 and 2005. A second set of simulations was then run using incremental changes in precipitation, temperature and CO2 levels, corresponding to a range of potential future climate scenarios. All simulation sets were compared in terms of production and risk of failure. Projected future trends showed that barley and oats will reach a maximum increase in yield with a 1°C increase in temperature compared to the 1980–2005 baseline. The optimum temperature for spring wheat was similar, except at the northernmost site (63.8°N), where the highest yield was obtained with a 4°C increase in temperature. Forage maize showed best performances for temperature increases of 2–3°C in all locations, except for the northernmost site, where the highest simulated yield was reached with a 5°C increase. Changes in temperatures and CO2 were the main factors explaining the changes in productivity, with ~89% of variance explained, whereas changes in precipitation explained ~11%. At the northernmost site, forage maize, oats and spring wheat showed decreasing risk of crop failure with increasing temperatures. The results of this modeling exercise suggest that the cultivation of annual crops in Sweden should, to some degree, benefit from the expected increase of temperature in the coming decades, provided that little to no water stress affects their growth and development. These results might be relevant to agriculture studies in regions of similar latitudes, especially the Nordic countries, and support the general assumption that climate change should have a positive impact on crop production at high latitudes.

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Integrated assessment of impact of water resources of important river basins in Eastern India under projected climate conditions

Global NEST Journal ◽

10.30955/gnj.001658 ◽

2015 ◽

Vol 17 (3) ◽

pp. 594-606 ◽

Cited By ~ 5

Keyword(s):

Climate Change ◽

Water Resources ◽

Catchment Area ◽

River Basins ◽

Weather Data ◽

Distributed Hydrological Model ◽

Eastern India ◽

Impact Of Climate Change ◽

Daily Weather Data ◽

The Impact

<div> <p>The impact of climate change on water resources through increased evaporation combined with regional changes in precipitation characteristics has the potential to affect mean runoff, frequency and intensity of floods and droughts, soil moisture and water supply for irrigation and hydroelectric power generation. The Ganga-Brahmaputra-Meghna (GBM) system is the largest in India with a catchment area of about 110Mha, which is more than 43% of the cumulative catchment area of all the major rivers in the country. The river Damodar is an important sub catchment of GBM basin and its three tributaries- the Bokaro, the Konar and the Barakar form one important tributary of the Bhagirathi-Hughli (a tributary of Ganga) in its lower reaches. The present study is an attempt to assess the impacts of climate change on water resources of the four important Eastern River Basins namely Damodar, Subarnarekha, Mahanadi and Ajoy, which have immense importance in industrial and agricultural scenarios in eastern India. A distributed hydrological model (HEC-HMS) has been used on the four river basins using HadRM2 daily weather data for the period from 2041 to 2060 to predict the impact of climate change on water resources of these river systems. </p> </div> <p> </p>

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Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria

The Journal of Agricultural Science ◽

10.1017/s0021859616000083 ◽

2016 ◽

Vol 154 (7) ◽

pp. 1153-1170 ◽

Cited By ~ 3

Author(s):

E. EBRAHIMI ◽

A. M. MANSCHADI ◽

R. W. NEUGSCHWANDTNER ◽

J EITZINGER ◽

S. THALER ◽

...

Keyword(s):

Climate Change ◽

Management Practices ◽

Crop Management ◽

Weather Data ◽

Climate Change Scenarios ◽

Management Scenarios ◽

Global Circulation Models ◽

Daily Weather Data ◽

Eastern Austria ◽

The Impact

SUMMARYClimate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.

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Impact of Annual Weather Fluctuations on Wine Production in Germany

Journal of Wine Economics ◽

10.1017/jwe.2017.47 ◽

2017 ◽

Vol 12 (4) ◽

pp. 436-445 ◽

Cited By ~ 4

Author(s):

Britta Niklas

Keyword(s):

Positive Impact ◽

Weather Data ◽

Total Output ◽

Wine Quality ◽

Wine Production ◽

Daily Weather Data ◽

Weather Stations ◽

The Impact ◽

The Empirical Analysis ◽

Quality Categories

AbstractThis paper analyzes the impact of annual weather fluctuations on the total output of wine and on the share of output of different wine-quality categories in Germany, using a set of wine data from all thirteen German wine regions and daily weather data taken from regional weather stations. The empirical analysis suggests that rising average temperatures have a significantly positive impact on the total output of wine as well as on the output shares of wine in higher-quality categories. The number of freezing days appears to be detrimental to overall production; precipitation during the growing season impairs higher-quality wines in particular. (JEL Classifications: Q21, Q13)

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Projection of Climate Change Influences on U.S. West Nile Virus Vectors

Earth Interactions ◽

10.1175/ei-d-15-0008.1 ◽

2015 ◽

Vol 19 (18) ◽

pp. 1-18 ◽

Cited By ~ 12

Author(s):

Heidi E. Brown ◽

Alex Young ◽

Joceline Lega ◽

Theodore G. Andreadis ◽

Jessica Schurich ◽

...

Keyword(s):

Climate Change ◽

West Nile Virus ◽

Simulation Model ◽

Disease Risk ◽

Weather Data ◽

Effect Of Temperature ◽

West Nile ◽

Virus Vectors ◽

Daily Weather Data ◽

The Impact

Abstract While estimates of the impact of climate change on health are necessary for health care planners and climate change policy makers, models to produce quantitative estimates remain scarce. This study describes a freely available dynamic simulation model parameterized for three West Nile virus vectors, which provides an effective tool for studying vectorborne disease risk due to climate change. The Dynamic Mosquito Simulation Model is parameterized with species-specific temperature-dependent development and mortality rates. Using downscaled daily weather data, this study estimates mosquito population dynamics under current and projected future climate scenarios for multiple locations across the country. Trends in mosquito abundance were variable by location; however, an extension of the vector activity periods, and by extension disease risk, was almost uniformly observed. Importantly, midsummer decreases in abundance may be offset by shorter extrinsic incubation periods, resulting in a greater proportion of infective mosquitoes. Quantitative descriptions of the effect of temperature on the virus and mosquito are critical to developing models of future disease risk.

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Downscaling climate change scenarios for apple pest and disease modeling in Switzerland

Earth System Dynamics Discussions ◽

10.5194/esdd-2-493-2011 ◽

2011 ◽

Vol 2 (2) ◽

pp. 493-529 ◽

Cited By ~ 3

Author(s):

M. Hirschi ◽

S. Stoeckli ◽

M. Dubrovsky ◽

C. Spirig ◽

P. Calanca ◽

...

Keyword(s):

Climate Change ◽

Fire Blight ◽

Codling Moth ◽

Weather Data ◽

Climate Change Scenarios ◽

Climate Conditions ◽

Pests And Diseases ◽

Daily Weather Data ◽

The Future ◽

The Impact

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously not affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology depending on actual weather conditions and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1 % on average today to over 60 % in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g., insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.

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Comparison of five wheat simulation models In southern Alberta

Canadian Journal of Plant Science ◽

10.4141/cjps95-010 ◽

1995 ◽

Vol 75 (1) ◽

pp. 61-68 ◽

Cited By ~ 31

Author(s):

A. Touré ◽

D. J. Major ◽

C. W. Lindwall

Keyword(s):

Climate Change ◽

Global Warming ◽

Spring Wheat ◽

Crop Production ◽

Wheat Yield ◽

Simulation Models ◽

Epic Model ◽

Impact Of Climate Change ◽

Long Term Experiment ◽

The Impact

Increasing concentrations of greenhouse gases are expected to result in global warming which will affect crop production. Crop modelling is a useful tool for assessing the impact of climate change on crop production. The objective of this study was to select an appropriate model for climate change studies. Five simulation models, EPIC, CERES, Century, Sinclair and Stewart, were assessed using data from a long-term experiment begun in 1911 on a clay loam (Dark Brown Chernozem) soil at Lethbridge, AB. Yields predicted by the five models were compared with actual spring wheat yields in continuous wheat, fallow-wheat and fallow-wheat-wheat rotations. The EPIC model gave the best simulation results over all rotations and the most accurate predictions of mean yields during droughts. It was concluded that the EPIC model had the greatest potential for assessing the impact of climate change on wheat yield. The Stewart model was the most accurate for unfertilized continuous wheat and fallow-wheat. The Sinclair model was most accurate for fertilized fallow-wheat and CERES was the most accurate model for fertilized continuous wheat. The Century model simulated average yield accurately but did not account for year-to-year variability. Key words: Global warming, crop simulation, spring wheat yields

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Downscaling climate change scenarios for apple pest and disease modeling in Switzerland

Earth System Dynamics ◽

10.5194/esd-3-33-2012 ◽

2012 ◽

Vol 3 (1) ◽

pp. 33-47 ◽

Cited By ~ 26

Author(s):

M. Hirschi ◽

S. Stoeckli ◽

M. Dubrovsky ◽

C. Spirig ◽

P. Calanca ◽

...

Keyword(s):

Climate Change ◽

Fire Blight ◽

Codling Moth ◽

Weather Data ◽

Climate Change Scenarios ◽

Climate Conditions ◽

Pests And Diseases ◽

Daily Weather Data ◽

The Future ◽

The Impact

Abstract. As a consequence of current and projected climate change in temperate regions of Europe, agricultural pests and diseases are expected to occur more frequently and possibly to extend to previously non-affected regions. Given their economic and ecological relevance, detailed forecasting tools for various pests and diseases have been developed, which model their phenology, depending on actual weather conditions, and suggest management decisions on that basis. Assessing the future risk of pest-related damages requires future weather data at high temporal and spatial resolution. Here, we use a combined stochastic weather generator and re-sampling procedure for producing site-specific hourly weather series representing present and future (1980–2009 and 2045–2074 time periods) climate conditions in Switzerland. The climate change scenarios originate from the ENSEMBLES multi-model projections and provide probabilistic information on future regional changes in temperature and precipitation. Hourly weather series are produced by first generating daily weather data for these climate scenarios and then using a nearest neighbor re-sampling approach for creating realistic diurnal cycles. These hourly weather series are then used for modeling the impact of climate change on important life phases of the codling moth and on the number of predicted infection days of fire blight. Codling moth (Cydia pomonella) and fire blight (Erwinia amylovora) are two major pest and disease threats to apple, one of the most important commercial and rural crops across Europe. Results for the codling moth indicate a shift in the occurrence and duration of life phases relevant for pest control. In southern Switzerland, a 3rd generation per season occurs only very rarely under today's climate conditions but is projected to become normal in the 2045–2074 time period. While the potential risk for a 3rd generation is also significantly increasing in northern Switzerland (for most stations from roughly 1% on average today to over 60% in the future for the median climate change signal of the multi-model projections), the actual risk will critically depend on the pace of the adaptation of the codling moth with respect to the critical photoperiod. To control this additional generation, an intensification and prolongation of control measures (e.g. insecticides) will be required, implying an increasing risk of pesticide resistances. For fire blight, the projected changes in infection days are less certain due to uncertainties in the leaf wetness approximation and the simulation of the blooming period. Two compensating effects are projected, warmer temperatures favoring infections are balanced by a temperature-induced advancement of the blooming period, leading to no significant change in the number of infection days under future climate conditions for most stations.

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A Preliminary Life Cycle Analysis of Bioethanol Production Using Seawater in a Coastal Biorefinery Setting

10.20944/preprints202108.0020.v2 ◽

2021 ◽

Author(s):

Abdelrahman S. Zaky ◽

Claudia E. Carter ◽

Fanran Meng ◽

Christopher E. French

Keyword(s):

Climate Change ◽

Life Cycle ◽

Crop Production ◽

Positive Impact ◽

Bioethanol Production ◽

Water Depletion ◽

Coastal Seawater ◽

Impact Reduction ◽

Marine Biomass ◽

The Impact

Bioethanol has many environmental and practical benefits as a transportation fuel. It is one of the best alternatives to replace fossil fuels due to its liquid nature which is similar to petrol and diesel fuels traditionally used in transportation. In addition, bioethanol production technology has the capacity for negative carbon emissions which is vital for solving the current global warming dilemma. However, conventional bioethanol production takes place based on an inland site and relies on freshwater and edible crops (or land suitable for edible crop production) for production, which has led to the food vs fuel debate. Establishing a coastal marine biorefinery (CMB) system for bioethanol production that is based on coastal sites and relies on marine resources (seawater, marine biomass and marine yeast) could be the ultimate solution. In this paper, we aim to evaluate the environmental impact of using seawater for bioethanol production at coastal locations as a step towards the evaluation of a CMB system. Hence, a life cycle assessment for bioethanol production was conducted using the proposed scenario named Coastal-Seawater and compared to the conventional scenario, named Inland-Freshwater (IF). The impact of each scenario in relation to climate change, water depletion, land use and fossil depletion was studied for comparison. The coastal-seawater scenario demonstrated an improvement upon the conventional scenario in all the selected impact categories. In particular, the use of seawater in the process had a significant effect on water depletion showing an impact reduction of 31.2%. Furthermore, reductions are demonstrated in natural land transformation, climate change and fossil depletion of 5.5%, 3.5% and 4.2% respectively. This indicates the positive impact of using seawater and coastal locations for bioethanol production and encourages research to investigate the CMB system.

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IMPACT OF CLIMATE CHANGE ON CHINA’S RICE PRODUCTION — AN EMPIRICAL ESTIMATION BASED ON PANEL DATA (1979–2011) FROM CHINA’S MAIN RICE-PRODUCING AREAS

The Singapore Economic Review ◽

10.1142/s0217590817400240 ◽

2018 ◽

Vol 63 (03) ◽

pp. 535-553 ◽

Cited By ~ 3

Author(s):

DAN WANG ◽

YU HAO ◽

JIANPEI WANG

Keyword(s):

Climate Change ◽

Panel Data ◽

Temperature Difference ◽

Rice Production ◽

Weather Data ◽

Impact Of Climate Change ◽

Positive Effects ◽

Daily Weather Data ◽

Maximum Temperatures ◽

The Impact

Climate change is attracting increasing attention from the international community. To assess the impact of climate change on China’s rice production, this paper re-organizes the main rice-producing areas by adding up the annual production of the provincial level regions between 1979 and 2011, utilizes Cobb–Douglas function using daily weather data over the whole growing season. Our analysis of the panel data shows that minimum temperatures (Tmin), maximum temperatures (Tmax), temperature difference (TD) and precipitation (RP) are the four key climate determinants of rice production in China. Among these, temperature difference is surprisingly significant and all except maximum temperatures have positive effects. However, because the actual minimum temperatures and precipitation in China’s main rice-producing areas declined while the maximum temperatures and the temperature difference increased during our sample period, climate change has actually provided a negative contribution to the increase in China’s rice production.

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Evaluating and Adapting Climate Change Impacts on Rice Production in Indonesia: A Case Study of the Keduang Subwatershed, Central Java

Environments ◽

10.3390/environments8110117 ◽

2021 ◽

Vol 8 (11) ◽

pp. 117

Author(s):

Andrianto Ansari ◽

Yu-Pin Lin ◽

Huu-Sheng Lur

Keyword(s):

Climate Change ◽

Rice Yield ◽

Rice Production ◽

Calibration Coefficient ◽

Weather Data ◽

Climate Change Scenarios ◽

Impact Of Climate Change ◽

Central Java ◽

Daily Weather Data ◽

The Impact

Predicting the effect of climate change on rice yield is crucial as global food demand rapidly increases with the human population. This study combined simulated daily weather data (MarkSim) and the CERES-Rice crop model from the Decision Support System for Agrotechnology Transfer (DSSAT) software to predict rice production for three planting seasons under four climate change scenarios (RCPs 2.6, 4.5, 6.0, and 8.5) for the years 2021 to 2050 in the Keduang subwatershed, Wonogiri Regency, Central Java, Indonesia. The CERES-Rice model was calibrated and validated for the local rice cultivar (Ciherang) with historical data using GenCalc software. The model evaluation indicated good performance with both calibration (coefficient of determination (R2) = 0.89, Nash–Sutcliffe efficiency (NSE) = 0.88) and validation (R2 = 0.87, NSE = 0.76). Our results suggest that the predicted changing rainfall patterns, rising temperature, and intensifying solar radiation under climate change can reduce the rice yield in all three growing seasons. Under RCP 8.5, the impact on rice yield in the second dry season may decrease by up to 11.77% in the 2050s. Relevant strategies associated with policies based on the results were provided for decision makers. Furthermore, to adapt the impact of climate change on rice production, a dynamic cropping calendar, modernization of irrigation systems, and integrated plant nutrient management should be developed for farming practices based on our results in the study area. Our study is not only the first assessment of the impact of climate change on the study site but also provides solutions under projected rice shortages that threaten regional food security.

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