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Vegetation makes an outstanding contribution to the stability of ecosystems and to a certain extent reflects the state of the terrestrial ecosystem. Drought conditions greatly affect the growth and development process of vegetation due to its remarkable stochasticity and complexity. Due to the complex coupling mechanism between vegetation and drought, the research on vegetation drought risk is still limited. In this work, we focus on Northwest China and use the improved vegetation health index (VHI) and other multi-source data. We selected indicator factors based on both hazard and vulnerability, and adopt three weight determination methods, namely entropy method, critic method, and coefficient of variation method, to construct the corresponding index model, and also to establish a vegetation drought risk assessment model to quantitatively evaluate the drought risk of vegetation in northwest China. Results show that the percentage of each drought category remarkably changed during the period encompassing 1981-2020, and the vegetation drought shows deterioration in more areas of northwest China. The vegetation drought risks derived from the three weight determination methods were generally consistent, but differed for a particular vegetation type. The overall spatial distribution pattern of vegetation drought risk in Northwest China is higher in the west and lower in the east, and the vegetation in southern Qinghai and northwestern Xinjiang presents higher drought risk. This study may be used as a tool to provide quantitative basis for vegetation protection and vegetation drought management., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Normalized Difference Vegetation Index (NDVI) has been extensively used in continuous and long-term drought monitoring over large-scale, but with late response to drought-related changes of photosynthesis. Instead, solar-induced chlorophyll fluorescence (SIF) is more closely related to photosynthesis and thus is proposed to track the impacts of drought on vegetation growth. However, the detailed difference between SIF and NDVI in responding to drought has not been thoroughly explored. Here we present continuous ground measurements of NDVI and SIF at 760nm over four plots of wheat with different intensities of drought (well-watered treatment, moderate drought, severe drought and extreme drought). The average values of seasonal SIF were significantly lower under severe drought and extreme drought, while NDVI means only showed significant reduction in extreme drought. In the seasonal patterns, daily SIF could clearly separate the difference of drought gradient, while the difference of daily NDVI was clearer in the end of the field campaign. Daily SIF also significantly and positively correlated with soil moisture, indicating that SIF could be considered as an estimator of soil moisture to detect the information about agricultural drought. Furthermore, in extreme drought plot, the correlation of SIF and soil moisture was higher than that of NDVI and soil moisture in a shorter time lag (<15-day) but weaker in a longer time lag (longer than 30-day). The relationships of growth parameters with SIF and NDVI were further analyzed, showing a saturation of NDVI and unsaturation of SIF at high values of leaf area index and relative water content. These results suggested that SIF is better fit in early drought monitoring, especially over closure canopy, while NDVI is more feasible when drought lasted over a long time scale. Our findings in the study might provide deep insight into the utility of SIF in drought monitoring., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEI G90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding why the adoption of counter measures against drought is important and direct farmers to choose drought-resistant crops.

This paper presented a valuable framework for evaluating the impacts of droughts (single factor) on grassland ecosystems. This framework was defined as the quantitative magnitude of drought impact that unacceptable short-term and long-term effects on ecosystems may experience relative to the reference standard. Long-term effects on ecosystems may occur relative to the reference standard. Net primary productivity (NPP) was selected as the response indicator of drought to assess the quantitative impact of drought on Inner Mongolia grassland based on the Standardized Precipitation Index (SPI) and BIOME-BGC model. The framework consists of six main steps: 1) clearly defining drought scenarios, such as moderate, severe and extreme drought; 2) selecting an appropriate indicator of drought impact; 3) selecting an appropriate ecosystem model and verifying its capabilities, calibrating the bias and assessing the uncertainty; 4) assigning a level of unacceptable impact of drought on the indicator; 5) determining the response of the indicator to drought and normal weather state under global-change; and 6) investigating the unacceptable impact of drought at different spatial scales. We found NPP losses assessed using the new framework were more sensitive to drought and had higher precision than the long-term average method. Moreover, the total and average losses of NPP are different in different grassland types during the drought years from 1961-2009. NPP loss was significantly increased along a gradient of increasing drought levels. Meanwhile, NPP loss variation under the same drought level was different in different grassland types. The operational framework was particularly suited for integrative assessing the effects of different drought events and long-term droughts at multiple spatial scales, which provided essential insights for sciences and societies that must develop coping strategies for ecosystems for such events., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Background: Drought is considered the main environmental factor restricting apple production and thus the development of the apple industry. Rootstocks play an important role in enhancing the drought tolerance of apple plants. Studies of the physiology have demonstrated that 'ZC9-3' is a strong drought-resistant rootstock, whereas 'Jizhen-2' is a weak drought-resistant rootstock. However, the metabolites in these two apple rootstock varieties that respond to drought stress have not yet been characterized, and the molecular mechanisms underlying their responses to drought stress remain unclear. Results: In this study, the physiological and molecular mechanisms underlying differences in the drought resistance of 'Jizhen-2' (drought-sensitive) and 'ZC9-3' (drought-resistant) apple rootstocks were explored. Under drought stress, the relative water content of the leaves was maintained at higher levels in 'ZC9-3' than in 'Jizhen-2', and the photosynthetic, antioxidant, and osmoregulatory capacities of 'ZC9-3' were stronger than those of 'Jizhen-2'. Metabolome analysis revealed a total of 95 and 156 differentially accumulated metabolites in 'Jizhen-2' and 'ZC9-3' under drought stress, respectively. The up-regulated metabolites in the two cultivars were mainly amino acids and derivatives. Transcriptome analysis revealed that there were more differentially expressed genes and transcription factors in 'ZC9-3' than in 'Jizhen-2' throughout the drought treatment. Metabolomic and transcriptomic analysis revealed that amino acid biosynthesis pathways play key roles in mediating drought resistance in apple rootstocks. A total of 13 metabolites, including L-α-aminoadipate, L-homoserine, L-threonine, L-isoleucine, L-valine, L-leucine, (2S)-2-isopropylmalate, anthranilate, L-tryptophan, L-phenylalanine, L-tyrosine, L-glutamate, and L-proline, play an important role in the difference in drought resistance between 'ZC9-3' and 'Jizhen-2'. In addition, 13 genes encoding O-acetylserine-(thiol)-lyase, S-adenosylmethionine synthetase, ketol-acid isomeroreductase, dihydroxyacid dehydratase, isopropylmalate isomerase, branched-chain aminotransferase, pyruvate kinase, 3-dehydroquinate dehydratase/shikimate 5-dehydrogenase, N-acetylglutamate-5-P-reductase, and pyrroline-5-carboxylate synthetase positively regulate the response of 'ZC9-3' to drought stress. Conclusions: This study enhances our understanding of the response of apple rootstocks to drought stress at the physiological, metabolic, and transcriptional levels and provides key insights that will aid the cultivation of drought-resistant apple rootstock cultivars. Especially, it identifies key metabolites and genes underlying the drought resistance of apple rootstocks. [ABSTRACT FROM AUTHOR]

Agricultural drought differs from meteorological, hydrological, and socioeconomic drought, being closely related to soil water availability in the root zone, specifically for crop and crop growth stage. In previous studies, several soil moisture indices ( e.g., the soil moisture index, soil water deficit index) based on soil water availability have been developed for agricultural drought monitoring. However, when developing these indices, it was generally assumed that soil water availability to crops was equal throughout the root zone, and the effects of root distribution and crop growth stage on soil water uptake were ignored. This article aims to incorporate root distribution into a soil moisture-based index and to evaluate the performance of the improved soil moisture index for agricultural drought monitoring. The Huang-Huai-Hai Plain of China was used as the study area. Overall, soil moisture indices were significantly correlated with the crop moisture index ( CMI), and the improved root-weighted soil moisture index ( RSMI) was more closely related to the CMI than averaged soil moisture indices. The RSMI correctly identified most of the observed drought events and performed well in the detection of drought levels. Furthermore, the RSMI had a better performance than averaged soil moisture indices when compared to crop yield. In conclusion, soil moisture indices could improve agricultural drought monitoring by incorporating root distribution. [ABSTRACT FROM AUTHOR]

Various studies have been performed on drought hazard assessment at the national or regional scales, but few studies to date at the global scale, especially on global agriculture. In this paper, we utilized an agricultural drought hazard index (DHI), based on both drought severity and drought occurrence rate, derived from 3-month scale Standardized Precipitation Index (SPI) and the phenology data of main crops (rice, maize, wheat, barley, sorghum and soybean) to assess the agricultural drought hazard grades of the world during 1980-2008. The results indicated that area percentages of high and very high agricultural drought hazard zones were approximately 23.57 and 27.19% of the total agricultural area in the world. Moreover, those zones mostly were distributed in central United States, southeastern South America, most of Europe, southwestern Russia, both southern Congo and Nigeria, east-central and southwest China, Southeast Asia and eastern Australia, and most of those areas were also located in semi-humid or humid climate zones. In addition, some regions above were also found to be the very high agricultural drought hazard zones for the main crops: East-central and southwest China for wheat, maize, rice and soybean; Europe for wheat, maize and barley; Southeast Asia for rice; both central United States and southeastern South America for wheat, maize, soybean and sorghum. [ABSTRACT FROM AUTHOR]

ABSTRACT Drought is a major natural hazard that can have devastating impacts on regional agriculture, water resources and the environment. To assess the variability and pattern of drought characteristics in the Huang-Huai-Hai ( HHH) Plain, the daily Standardized Precipitation Evapotranspiration Index ( SPEI) is developed based on daily meteorological data in this study. The daily SPEI data are used, including Annual Total Drought Severity ( ATDS), Annual Total Drought Duration ( ATDD) and Annual Drought Frequency ( ADF), which were calculated from 1981 to 2010 at 28 meteorological stations. We used the indices ( ATDS, ATDD and ADF), Hovmöller diagrams and the reliable no parameter statistical methods of the Mann-Kendall test to assess the variability and pattern of drought characteristics for the period from 1981 to 2010 in the HHH plain. The results suggested that severe drought occurred in the 1980s, the late 1990s and the early 2000s, severe drought events occurred in 1981, 1986, 1997 and 2002. Decreasing trends for both ATDS and ATDD were found, and the drought situation did not worsen under global warming during the past 30 years, and the drought situation is alleviating in the entire HHH plain. The northeast and southwest regions of the HHH plain have suffered from more severe drought, and the north region is prone to drought. The results of the study can provide a scientific understanding for the adoption of countermeasures of regional defence against drought and also may serve as a reference point for drought hazard vulnerability analysis. [ABSTRACT FROM AUTHOR]

To identify the world's severely drought-prone areas, given that the corresponding ground area for a 0.5-degree grid in different latitudes is different, we proposed a more precise spherical area-based statistical method. The corresponding ground area per 0.5-degree grid is obtained by integral calculation in latitude and longitude directions. The analysis of the drought based on the global Standardized Precipitation Evapotranspiration Index dataset from 1902 to 2008, where global, Northern Hemisphere, Southern Hemisphere, and major crop-planting regions from six continents are treated as statistical units. The interannual variability characteristics of the severe drought area for each statistical unit are investigated. To study the spatial distribution characteristics of the global frequency of severe drought, the drought frequency was calculated based on drought events identified by continuous drought months on a grid level. Six major crops (wheat, maize, rice, soybean, barley, and sorghum) were chosen to study the impact of drought events on agriculture. The results suggested that severe droughts in global, Northern Hemisphere, and Southern Hemisphere areas have indicated a downward trend since 1990, but an upward trend overall in all continents except Oceania. The identified drought-prone areas show a patchy distribution and frequently drought-prone areas (with 10–20% occurrence probability of drought) were distributed in regions surrounding chronically drought-prone areas (with more than 20% probability). Global chronically drought-prone areas have increased significantly, from 16.19% in 1902–1949 to 41.09% in 1950–2008. Chronically drought-prone areas of agriculture are located in the center of southern Europe, South America, and eastern Asia. [ABSTRACT FROM AUTHOR]