Article
Geosciences, Multidisciplinary
Jean Moussa Kourouma, Emmanuel Eze, Emnet Negash, Darius Phiri, Royd Vinya, Atkilt Girma, Amanuel Zenebe
Summary: The study aimed to characterize agricultural drought in Ethiopia and understand its effects on crop yield using NDVI and VCI values. Results showed that VCI and NDVI data are useful for drought monitoring in Ethiopia, and that crops like maize, teff, and beans are more vulnerable to drought.
GEOMATICS NATURAL HAZARDS & RISK
(2021)
Article
Environmental Sciences
Simon Kloos, Ye Yuan, Mariapina Castelli, Annette Menzel
Summary: Droughts during the growing season in Central Europe are projected to increase, making area-wide monitoring of agricultural drought crucial. Research has shown that water is the primary limiting factor for vegetation growth in specific areas and during summer months, with temperature and vegetation health indices correlating with soil moisture and agricultural yield anomalies.
Article
Environmental Sciences
Guoyong Leng
Summary: The study found that drought has a probabilistic impact on US maize yield, with irrigation reducing yield loss risk. The diverse risk distribution patterns under different drought intensities emphasize the necessity of better representing drought effects at local scales.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Soo-Jin Lee, Nari Kim, Yangwon Lee
Summary: Various drought indices have been used for agricultural drought monitoring, but the Integrated Crop Drought Index (ICDI) developed in this study combines multiple factors including weather, hydrological, and vegetation factors to better express the dry/wet state of land surface and the health of vegetation. The ICDI showed higher positive correlations with corn yields compared to other drought indices, indicating its effectiveness in monitoring agricultural drought and its impact on crop yield.
Article
Meteorology & Atmospheric Sciences
Huawei Li, Yongping Li, Guohe Huang, Jie Sun
Summary: A copula-based bivariate probabilistic framework model was developed to assess the impacts of drought events on crop yield. The model was applied to Xinjiang Province in Northwestern China, revealing the varying sensitivity of wheat, maize, and cotton yield anomalies to different drought time-scales. Results enhance understanding of drought scales' impacts on crops and provide guidance for irrigation management.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2021)
Article
Chemistry, Analytical
Hoa Thi Pham, Joseph Awange, Michael Kuhn
Summary: Machine learning has played a crucial role in crop yield forecasting, but identifying critical features from datasets remains challenging. This study proposes a framework that compares feature selection, feature extraction, and their combination to enhance model performance, finding that the combined approach performs the best. The results emphasize the significant role of feature selection, feature extraction, and their combination with various machine learning algorithms in improving the accuracy of crop yield predictions.
Article
Remote Sensing
Tuyen V. Ha, Soner Uereyen, Claudia Kuenzer
Summary: This paper presents the first comprehensive analysis of agricultural and vegetative droughts in mainland Southeast Asia, using the Vegetation Condition Index (VCI) based on MODIS-based vegetation time-series data. The study reveals that central Myanmar experiences the most frequent droughts, while the Lower Mekong area suffers from both frequent and prolonged drought conditions. Recent severe droughts are predominantly observed in Cambodia, indicating a drying trend in this region. The findings provide valuable information for drought early warning management and agricultural planning.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Biodiversity Conservation
Cuiping Yang, Changhong Liu, Yuhui Gu, Yongqiang Wang, Xuguang Xing, Xiaoyi Ma
Summary: A comprehensive agricultural drought index (CADI) was developed using five commonly used binary copulas, considering evapotranspiration factors. It accurately reflected the integrated process of meteorological and agricultural drought occurrence and evolution. The correlation between CADI and yield anomalies in the North China Plain surpassed that of other indices, confirming its validity and reliability for drought monitoring. Droughts in the region have shown a decreasing trend over the past four decades, with severe droughts concentrated in winter.
ECOLOGICAL INDICATORS
(2023)
Article
Green & Sustainable Science & Technology
Abhishek Danodia, Anuradha Kushwaha, N. R. Patel
Summary: This study utilized an Analytical Hierarchy Process to define drought severity for rabi crops in the Bundelkhand region of India, creating a Combined Drought Index. The results indicated that the northern districts were more severely affected, with a significant correlation between crop yield and CDI. The integration of remote sensing data and expert advice through a geospatial platform shows promise for addressing drought risk in various crop ecosystems.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Agronomy
Ronnie J. Araneda-Cabrera, Maria Bermudez, Jeronimo Puertas
Summary: This study proposed a methodology to monitor the impact of drought on crops, using Mozambique as a case study, with PAA identified as a more accurate predictor of variability in crop yields.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Environmental Sciences
Wenguang Sun, David Fleisher, Dennis Timlin, Chittaranjan Ray, Zhuangji Wang, Sahila Beegum, Vangimalla Reddy
Summary: Extreme climate events including heat waves and droughts are projected to become more frequent under future climate change conditions. However, the mechanisms between soybean yields and climate factors, specifically involving variable rainfall and high heat episodes, are still unclear, particularly with respect to spatial trends in the United States (US) Midwest.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Vempi Satriya Adi Hendrawan, Wonsik Kim, Daisuke Komori
Summary: In this study, the crop yield response of major crops to different timescales of precipitation deficit was assessed. It was found that a significant portion of global harvested areas of maize, rice, soybean, and wheat were affected by drought at various timescales. The study also revealed that climate factors and water availability were important determinants of crop response to drought timescales.
Article
Agronomy
Siyang Cai, Depeng Zuo, Huixiao Wang, Zongxue Xu, GuoQing Wang, Hong Yang
Summary: Drought is a severe natural disaster in China, causing significant damage to the environment and socio-economy. Remote sensing technology is highly valuable for drought monitoring, compensating for limitations of ground-based techniques.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Biodiversity Conservation
Lidong Zou, Sen Cao, Zaichun Zhu, Arturo Sanchez-Azofeifa
Summary: The study revealed that Tropical Dry Forests (TDFs) are significantly affected by drought related to El Nin similar to o, with different responses to different ENSO phases across various sites. In the short term, the sensitivity of vegetation productivity to the El Nino warm phase varied among different locations.
ECOLOGICAL INDICATORS
(2021)
Article
Environmental Sciences
Vempi Satriya Adi Hendrawan, Wonsik Kim, Yoshiya Touge, Shi Ke, Daisuke Komori
Summary: This study compares different drought indices and finds that a drought index based on multiple precipitation datasets has a better correlation with crop yield anomalies. During the study period, approximately 23% of maize, 8% of rice, 30% of soybean, and 29% of wheat were significantly affected by drought, primarily due to medium to longer-term droughts. Rice is less affected by droughts as it is typically grown and irrigated in humid regions.
ENVIRONMENTAL RESEARCH LETTERS
(2022)