Articles | Volume 18, issue 3
https://doi.org/10.5194/nhess-18-889-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-18-889-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Mar 2018
Research article |
| 20 Mar 2018
The effect of soil moisture anomalies on maize yield in Germany
UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Stephan Thober
UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Volker Meyer
UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
Luis Samaniego
UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany
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Cited
30 citations as recorded by crossref.
- Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields N. Vergopolan et al. 10.5194/hess-25-1827-2021
- A comparison of climate drivers’ impacts on silage maize yield shock in Germany F. Stainoh et al. 10.1007/s00704-024-05179-z
- Impact of drought on cereal crop yields in the Savanna Region of Nigeria O. Durowoju et al. 10.1080/19376812.2021.2024443
- Limited Potential of Irrigation to Prevent Potato Yield Losses in Germany Under Climatechange S. Egerer et al. 10.2139/ssrn.4045809
- Preface: Damage of natural hazards: assessment and mitigation H. Kreibich et al. 10.5194/nhess-19-551-2019
- Tillage erosion as an important driver of in‐field biomass patterns in an intensively used hummocky landscape L. Öttl et al. 10.1002/ldr.3968
- Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making B. Bartkowski & S. Bartke 10.3390/su10093179
- Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany M. Peichl et al. 10.5194/hess-25-6523-2021
- Heterogeneous impacts of excessive wetness on maize yields in China: Evidence from statistical yields and process-based crop models W. Liu et al. 10.1016/j.agrformet.2022.109205
- Development of an empirical model for sub-surface soil moisture estimation and variability assessment in a lesser Himalayan watershed S. Verma & M. Nema 10.1007/s40808-021-01316-z
- Machine learning reveals complex effects of climatic means and weather extremes on wheat yields during different plant developmental stages F. Schierhorn et al. 10.1007/s10584-021-03272-0
- Automatic Regionalization of Model Parameters for Hydrological Models M. Feigl et al. 10.1029/2022WR031966
- Machine learning in crop yield modelling: A powerful tool, but no surrogate for science G. Lischeid et al. 10.1016/j.agrformet.2021.108698
- Quantifying the impacts of compound extremes on agriculture I. Haqiqi et al. 10.5194/hess-25-551-2021
- High-resolution drought simulations and comparison to soil moisture observations in Germany F. Boeing et al. 10.5194/hess-26-5137-2022
- Winter wheat yield prediction using convolutional neural networks from environmental and phenological data A. Srivastava et al. 10.1038/s41598-022-06249-w
- Model-based reconstruction and projections of soil moisture anomalies and crop losses in Poland M. Piniewski et al. 10.1007/s00704-020-03106-6
- Impact of climate and weather extremes on soybean and wheat yield using machine learning approach M. Kumari et al. 10.1007/s00477-024-02759-3
- Comparison of process-based and statistical approaches for simulation and projections of rainfed crop yields M. Eini et al. 10.1016/j.agwat.2022.108107
- TPE-CatBoost: An adaptive model for soil moisture spatial estimation in the main maize-producing areas of China with multiple environment covariates J. Yu et al. 10.1016/j.jhydrol.2022.128465
- Maize yield reduction is more strongly related to soil moisture fluctuation than soil temperature change under biodegradable film vs plastic film mulching in a semi-arid region of northern China T. Yin et al. 10.1016/j.agwat.2023.108351
- The 2018–2020 Multi‐Year Drought Sets a New Benchmark in Europe O. Rakovec et al. 10.1029/2021EF002394
- Is the volatility of yields for major crops grown in Germany related to spatial diversification at county level? H. Ahrends et al. 10.1088/1748-9326/ad7613
- Modeling deficit irrigation water demand of maize and potato in Eastern Germany using ERA5-Land reanalysis climate time series O. Ogunsola et al. 10.1007/s00271-024-00939-1
- Evaluating the Hydrus-1D Model Optimized by Remote Sensing Data for Soil Moisture Simulations in the Maize Root Zone J. Yu et al. 10.3390/rs14236079
- Climate impacts on long-term silage maize yield in Germany M. Peichl et al. 10.1038/s41598-019-44126-1
- Soil-climate interactions enhance understanding of long-term crop yield stability W. Zhu et al. 10.1016/j.eja.2024.127386
- Changing patterns of soil water content and relationship with national wheat and maize production in Europe Z. Pinke et al. 10.1016/j.eja.2022.126579
- Seamless downscaling of the ESA CCI soil moisture data at the daily scale with MODIS land products W. Zhao et al. 10.1016/j.jhydrol.2021.126930
- Limited potential of irrigation to prevent potato yield losses in Germany under climate change S. Egerer et al. 10.1016/j.agsy.2023.103633
30 citations as recorded by crossref.
- Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields N. Vergopolan et al. 10.5194/hess-25-1827-2021
- A comparison of climate drivers’ impacts on silage maize yield shock in Germany F. Stainoh et al. 10.1007/s00704-024-05179-z
- Impact of drought on cereal crop yields in the Savanna Region of Nigeria O. Durowoju et al. 10.1080/19376812.2021.2024443
- Limited Potential of Irrigation to Prevent Potato Yield Losses in Germany Under Climatechange S. Egerer et al. 10.2139/ssrn.4045809
- Preface: Damage of natural hazards: assessment and mitigation H. Kreibich et al. 10.5194/nhess-19-551-2019
- Tillage erosion as an important driver of in‐field biomass patterns in an intensively used hummocky landscape L. Öttl et al. 10.1002/ldr.3968
- Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making B. Bartkowski & S. Bartke 10.3390/su10093179
- Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany M. Peichl et al. 10.5194/hess-25-6523-2021
- Heterogeneous impacts of excessive wetness on maize yields in China: Evidence from statistical yields and process-based crop models W. Liu et al. 10.1016/j.agrformet.2022.109205
- Development of an empirical model for sub-surface soil moisture estimation and variability assessment in a lesser Himalayan watershed S. Verma & M. Nema 10.1007/s40808-021-01316-z
- Machine learning reveals complex effects of climatic means and weather extremes on wheat yields during different plant developmental stages F. Schierhorn et al. 10.1007/s10584-021-03272-0
- Automatic Regionalization of Model Parameters for Hydrological Models M. Feigl et al. 10.1029/2022WR031966
- Machine learning in crop yield modelling: A powerful tool, but no surrogate for science G. Lischeid et al. 10.1016/j.agrformet.2021.108698
- Quantifying the impacts of compound extremes on agriculture I. Haqiqi et al. 10.5194/hess-25-551-2021
- High-resolution drought simulations and comparison to soil moisture observations in Germany F. Boeing et al. 10.5194/hess-26-5137-2022
- Winter wheat yield prediction using convolutional neural networks from environmental and phenological data A. Srivastava et al. 10.1038/s41598-022-06249-w
- Model-based reconstruction and projections of soil moisture anomalies and crop losses in Poland M. Piniewski et al. 10.1007/s00704-020-03106-6
- Impact of climate and weather extremes on soybean and wheat yield using machine learning approach M. Kumari et al. 10.1007/s00477-024-02759-3
- Comparison of process-based and statistical approaches for simulation and projections of rainfed crop yields M. Eini et al. 10.1016/j.agwat.2022.108107
- TPE-CatBoost: An adaptive model for soil moisture spatial estimation in the main maize-producing areas of China with multiple environment covariates J. Yu et al. 10.1016/j.jhydrol.2022.128465
- Maize yield reduction is more strongly related to soil moisture fluctuation than soil temperature change under biodegradable film vs plastic film mulching in a semi-arid region of northern China T. Yin et al. 10.1016/j.agwat.2023.108351
- The 2018–2020 Multi‐Year Drought Sets a New Benchmark in Europe O. Rakovec et al. 10.1029/2021EF002394
- Is the volatility of yields for major crops grown in Germany related to spatial diversification at county level? H. Ahrends et al. 10.1088/1748-9326/ad7613
- Modeling deficit irrigation water demand of maize and potato in Eastern Germany using ERA5-Land reanalysis climate time series O. Ogunsola et al. 10.1007/s00271-024-00939-1
- Evaluating the Hydrus-1D Model Optimized by Remote Sensing Data for Soil Moisture Simulations in the Maize Root Zone J. Yu et al. 10.3390/rs14236079
- Climate impacts on long-term silage maize yield in Germany M. Peichl et al. 10.1038/s41598-019-44126-1
- Soil-climate interactions enhance understanding of long-term crop yield stability W. Zhu et al. 10.1016/j.eja.2024.127386
- Changing patterns of soil water content and relationship with national wheat and maize production in Europe Z. Pinke et al. 10.1016/j.eja.2022.126579
- Seamless downscaling of the ESA CCI soil moisture data at the daily scale with MODIS land products W. Zhao et al. 10.1016/j.jhydrol.2021.126930
- Limited potential of irrigation to prevent potato yield losses in Germany under climate change S. Egerer et al. 10.1016/j.agsy.2023.103633
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Latest update: 12 Nov 2024
Short summary
Crop yields are routinely derived from meteorological variables, especially temperature. However, the primary water source for plant growth (soil moisture) is neglected. In this study, the predictability of maize yield is investigated using soil moisture or meteorological variables in Germany. The effects of soil moisture dominate those of temperature and are time-dependent. For example, comparatively moist soil conditions in June reduce crop yields, while in August they increase yields.
Crop yields are routinely derived from meteorological variables, especially temperature....
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