التفاصيل البيبلوغرافية
| العنوان: |
A NOVEL ROBUST META-MODEL FRAMEWORKFOR PREDICTING CROP YIELD PROBABILITY DISTRIBUTIONS USING MULTISOURCE DATA. |
| Alternate Title: |
НОВА НАДІЙНА СТРУКТУРА МЕТАМОДЕЛІ ДЛЯ ПРОГНОЗУВАННЯ РОЗПОДІЛУ ЙМОВІРНОСТІ ВРОЖАЙНОСТІ З ВИКОРИСТАННЯМ ДАНИХ ІЗ БАГАТЬОХ ДЖЕРЕЛ. (Ukrainian) |
| المؤلفون: |
ERMOLIEVA, T., HAVLIK, P., LESSA-DERCI-AUGUSTYNCZIK, A., BOERE, E., FRANK, S., KAHIL, T., WANG, G., BALKOVIC, J., SKALSKY, R., FOLBERTH, C., KOMENDANTOVA, N., KNOPOV, P. S. |
| المصدر: |
Cybernetics & Systems Analysis / Kibernetiki i Sistemnyj Analiz; 2023, Issue 5, p180-195, 16p |
| مصطلحات موضوعية: |
CROP yields, DISTRIBUTION (Probability theory), AGRICULTURAL productivity, HEAT waves (Meteorology), LAND use |
| مستخلص: |
There is an urgent need to better understand and predict crop yield responses toweather disturbances, in particular, of extreme nature, such as heavy precipitation events, droughts, and heat waves, to improve future crop production projections under weather variability, extreme events, and climate change. In this paper, we develop quantile regressionmodels for estimating crop yield probability distributions depending on monthly temperature andprecipitation values and soil quality characteristics, which can be made available for different climate change projections. Crop yields, historical and those simulated by the EPIC model, areanalyzed and distinguished according to their levels, i.e., mean and critical quantiles. Then, the crop yield quantiles are approximated by fitting separate quantile-based regression models. Thedeveloped statistical crop yield meta-model enables the analysis of crop yields and respectiveprobabilities of their occurrence as a function of the exogenous parameters such as temperatureand precipitation and endogenous, in general, decision-dependent parameters (such as soil characteristics), which can be altered by land use practices. Statistical and machine learningmodels can be used as reduced form scenario generators (meta-models) of stochastic events(scenarios), as a submodel of more complex models, e.g., Integrated Assessment model (IAM) GLOBIOM. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
