scholarly journals Effect of Climate Change on Maize Yield in the Growing Season: A Case Study of the Songliao Plain Maize Belt

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2108 ◽  
Author(s):  
Ari Guna ◽  
Jiquan Zhang ◽  
Siqin Tong ◽  
Yongbin Bao ◽  
Aru Han ◽  
...  
Keyword(s):  
Global Warming ◽  
Coupled Model ◽  
Growing Season ◽  
Maize Yield ◽  
Climate Data ◽  
Yield Data ◽  
Increasing Temperature ◽  
Songliao Plain ◽  
The Relationship

Based on the 1965–2017 climate data of 18 meteorological stations in the Songliao Plain maize belt, the Coupled Model Intercomparision Project (CMIP5) data, and the 1998–2017 maize yield data, the drought change characteristics in the study area were analyzed by using the standardized precipitation evapotranspiration index (SPEI) and the Mann–Kendall mutation test; furthermore, the relationship between meteorological factors, drought index, and maize climate yield was determined. Finally, the maize climate yields under 1.5 °C and 2.0 °C global warming scenarios were predicted. The results revealed that: (1) from 1965 to 2017, the study area experienced increasing temperature, decreasing precipitation, and intensifying drought trends; (2) the yield of the study area showed a downward trend from 1998 to 2017. Furthermore, the climate yield was negatively correlated with temperature, positively correlated with precipitation, and positively correlated with SPEI-1 and SPEI-3; and (3) under the 1.5 °C and the 2.0 °C global warming scenarios, the temperature and the precipitation increased in the maize growing season. Furthermore, under the studied global warming scenarios, the yield changes predicted by multiple regression were −7.7% and −15.9%, respectively, and the yield changes predicted by one-variable regression were −12.2% and −21.8%, respectively.

scholarly journals Identifying maize yield and precipitation gaps in Uganda

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Terence Epule Epule ◽  
Driss Dhiba ◽  
Daniel Etongo ◽  
Changhui Peng ◽  
Laurent Lepage
Keyword(s):  
Cropping Systems ◽  
Growing Season ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
World Bank Group ◽  
Precipitation Data ◽  
Yield Data ◽  
Yield Gaps ◽  
Maize Yields ◽  
Growing Season Precipitation

AbstractIn sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.

Impact of global warming on meteorological drought: a case study of the Songliao Plain, China

2021 ◽  
Author(s):  
Guna Ari ◽  
Yongbin Bao ◽  
Hanfu Asi ◽  
Jiquan Zhang ◽  
Li Na ◽  
...  
Keyword(s):  
Global Warming ◽  
Meteorological Drought ◽  
Songliao Plain

scholarly journals Evaluating the Yield Response of Maize (Zea mays L.) and Rice (Oryza sativa L.) to Future Climate Variability in The Gambia

2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei
Keyword(s):  
Climate Variability ◽  
Rice Yield ◽  
Oryza Sativa L ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
Negative Effects ◽  
Yield Data ◽  
Maize Cultivars

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.

scholarly journals Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India

Forecasting ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 59-84 ◽  
Author(s):  
Alen Shrestha ◽  
Md Mafuzur Rahaman ◽  
Ajay Kalra ◽  
Rohit Jogineedi ◽  
Pankaj Maheshwari
Keyword(s):  
Coupled Model ◽  
Severity Index ◽  
Extreme Drought ◽  
Drought Severity ◽  
Climate Data ◽  
Drought Forecasting ◽  
Drought Duration ◽  
Intercomparison Project ◽  
Near Future

This study forecasts and assesses drought situations in various regions of India (the Araveli region, the Bundelkhand region, and the Kansabati river basin) based on seven simulated climates in the near future (2015–2044). The self-calibrating Palmer Drought Severity Index (scPDSI) was used based on its fairness in identifying drought conditions that account for the temperature as well. Gridded temperature and rainfall data of spatial resolution of 1 km were used to bias correct the multi-model ensemble mean of the Global Climatic Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) project. Equidistant quantile-based mapping was adopted to remove the bias in the rainfall and temperature data, which were corrected on a monthly scale. The outcome of the forecast suggests multiple severe-to-extreme drought events of appreciable durations, mostly after the 2030s, under most climate scenarios in all the three study areas. The severe-to-extreme drought duration was found to last at least 20 to 30 months in the near future in all three study areas. A high-resolution drought index was developed and proven to be a key to assessing the drought situation.

scholarly journals Aggressive incidents in psychiatric hospitals on heat days

BJPsych Open ◽  
2021 ◽  
Vol 7 (4) ◽  
Author(s):  
Frank Eisele ◽  
Erich Flammer ◽  
Tilman Steinert ◽  
Hans Knoblauch
Keyword(s):  
Global Warming ◽  
Dose Response ◽  
Aggressive Behaviour ◽  
Psychiatric Patients ◽  
Psychiatric Hospitals ◽  
Patient Treatment ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Increasing Temperature ◽  
The Relationship

This study explores the relationship between temperature and the number of aggressive incidents and coercive interventions in the years 2007–2019 in six psychiatric hospitals in the south of the Germany with a total of 1007 beds. The number of aggressive incidents among 164 435 admissions was significantly higher on ‘heat days’ (≥30°C). Furthermore, there was a dose–response relationship between the number of aggressive incidents and increasing temperature. In contrast, the number of coercive interventions was not related to temperature. Considering the background of global warming, rising temperature could result in more frequent aggressive behaviour during in-patient treatment of psychiatric patients.

scholarly journals Robustly forecasting maize yields in Tanzania based on climatic predictors

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rahel Laudien ◽  
Bernhard Schauberger ◽  
David Makowski ◽  
Christoph Gornott
Keyword(s):  
Agricultural Development ◽  
Mean Squared Error ◽  
Global Climate ◽  
National Level ◽  
Maize Yield ◽  
Weather Data ◽  
Efficiency Coefficient ◽  
Climate Data ◽  
Yield Data ◽  
Out Of Sample

AbstractSeasonal yield forecasts are important to support agricultural development programs and can contribute to improved food security in developing countries. Despite their importance, no operational forecasting system on sub-national level is yet in place in Tanzania. We develop a statistical maize yield forecast based on regional yield statistics in Tanzania and climatic predictors, covering the period 2009–2019. We forecast both yield anomalies and absolute yields at the sub-national scale about 6 weeks before the harvest. The forecasted yield anomalies (absolute yields) have a median Nash–Sutcliffe efficiency coefficient of 0.72 (0.79) in the out-of-sample cross validation, which corresponds to a median root mean squared error of 0.13 t/ha for absolute yields. In addition, we perform an out-of-sample variable selection and produce completely independent yield forecasts for the harvest year 2019. Our study is potentially applicable to other countries with short time series of yield data and inaccessible or low quality weather data due to the usage of only global climate data and a strict and transparent assessment of the forecasting skill.

scholarly journals How Climate Change Affects Extremes in Maize and Wheat Yield in Two Cropping Regions

2015 ◽  
Vol 28 (12) ◽  
pp. 4653-4687 ◽  
Author(s):  
Caroline C. Ummenhofer ◽  
Hong Xu ◽  
Tracy E. Twine ◽  
Evan H. Girvetz ◽  
Heather R. McCarthy ◽  
...  
Keyword(s):  
Climate Model ◽  
Wheat Yield ◽  
Coupled Model ◽  
Growing Season ◽  
Maize Yield ◽  
First Century ◽  
Southeastern Australia ◽  
Marginal Areas ◽  
Twenty First Century ◽  
Yield Responses

Abstract Downscaled climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were used to force a dynamic vegetation agricultural model (Agro-IBIS) and simulate yield responses to historical climate and two future emissions scenarios for maize in the U.S. Midwest and wheat in southeastern Australia. In addition to mean changes in yield, the frequency of high- and low-yield years was related to changing local hydroclimatic conditions. Particular emphasis was on the seasonal cycle of climatic variables during extreme-yield years and links to crop growth. While historically high (low) yields in Iowa tend to occur during years with anomalous wet (dry) growing season, this is exacerbated in the future. By the end of the twenty-first century, the multimodel mean (MMM) of growing season temperatures in Iowa is projected to increase by more than 5°C, and maize yield is projected to decrease by 18%. For southeastern Australia, the frequency of low-yield years rises dramatically in the twenty-first century because of significant projected drying during the growing season. By the late twenty-first century, MMM growing season precipitation in southeastern Australia is projected to decrease by 15%, temperatures are projected to increase by 2.8°–4.5°C, and wheat yields are projected to decline by 70%. Results highlight the sensitivity of yield projections to the nature of hydroclimatic changes. Where future changes are uncertain, the sign of the yield change simulated by Agro-IBIS is uncertain as well. In contrast, broad agreement in projected drying over southern Australia across models is reflected in consistent yield decreases for the twenty-first century. Climatic changes of the order projected can be expected to pose serious challenges for continued staple grain production in some current centers of production, especially in marginal areas.

scholarly journals Climate change extreme and seasonal toxic metal occurrence in Romanian freshwaters in the last two decades—case study and critical review

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Andreea Maria Iordache ◽  
Constantin Nechita ◽  
Cezara Voica ◽  
Tomáš Pluháček ◽  
Kevin A. Schug
Keyword(s):  
Climatic Factors ◽  
Toxic Metal ◽  
Strong Relationship ◽  
Mitigation Strategies ◽  
River Ecosystem ◽  
Climate Data ◽  
Elemental Concentrations ◽  
Metal Levels ◽  
The Relationship

AbstractThe relationship between metal levels in the Olt River ecosystem in southern Romania (measured during 2018‒2019, with 1064 sediment and water samples) and daily climate data were explored to assess the need for targeted source identification and mitigation strategies. In 2018, there was a strong relationship between the sediment Pb, As, Cd, and Hg contents and temperature (r > 0.8, p < 0.001). Mercury in sediments had a positive correlation with precipitation, and Hg in the water correlated with minimum temperature in May 2018 (p < 0.01). In July 2019, heavy metals were positively correlated with precipitation and negatively correlated with temperature. According to nonsymmetrical correspondence analysis, the four climate parameters analyzed were linearly correlated with the frequency of metal detection (p < 0.001) in both years. The statistical analysis showed strong relationships between heavy metal levels and climatic factors and attributed the discrepancies in elemental concentrations between 2018 and 2019 to climate warming.

scholarly journals The Effect of Climate Variability on Maize Production in the Ejura-Sekyedumase Municipality, Ghana

Climate ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 145
Author(s):  
Godwin P. Cudjoe ◽  
Phillip Antwi-Agyei ◽  
Benjamin A. Gyampoh
Keyword(s):  
Climate Variability ◽  
Maize Yield ◽  
Climatic Conditions ◽  
Chi Square ◽  
Maize Production ◽  
Change Dynamics ◽  
The Right ◽  
Increasing Temperature ◽  
The Impact ◽  
The Relationship

Agriculture is one of the sectors most susceptible to changes in climatic conditions. The impact is even stronger in Africa, where rain-fed agriculture is vital for daily subsistence, but where adaptive capacity is low. It is therefore crucial to increase the understanding of the actual climate change dynamics on agricultural productivity. This study examined the effects of changes in climatic variables such as rainfall and temperature on maize production in the Ejura-Sekyedumase Municipality, Ghana. Regression, chi-square and trend analyses were used to establish the relationship between climate variables (rainfall and temperature) and maize yield in the study area. This was supplemented with participatory household interviews with 120 farmers to understand the perception of farmers on rainfall and temperature patterns. The results from the study respondents and trend analysis show that rainfall is shorter in terms of duration and less predictable, whilst temperature has increased. The findings suggest that the general relationship between rainfall, temperature and maize yield is such that maize yield increased with increasing rainfall of the right amount and distribution pattern and decreased with increasing temperature. The study concludes that climate variability and/or change is evident in the study area and its effect on maize yield is severe.

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