Crop Drought Research Articles

Application of Some Drought Stress Indices to Study Response of Durum Wheat Triticum durum to Different Levels of Water Depletion

A pot experiment was conducted to investigate the effect of five levels of soil water depletion from field capacity (30, 40, 50, 60, and 70%) on some growth, yield and yield components of durum wheat (Triticum durum L.) VAR-ACSAD/65, with testing ten stress and drought indices to indicate the suitable index that could be simply used to interpret drought stress conditions. Results indicated significant effect of soil water depletion levels on wheat plant height, tillers per plant, spikes per plant, spike length, and total chlorophyll content, increasing water depletion levels decreased all recorded data. The effect on spike numbers per plant; spike length; number of seeds per spike; 1000 seeds weight (gm); seed yield per plant; straw yield per plant; biological yield per plant and harvest index were negatively dependent on drought stress to the level of no seed yield under the highest water depletion level 70%. Drought indices could classify to three categories; unity to zero, zero to higher value, high values to lower values. The relationship between drought indices were either positive or negatively correlated to plant seed yield. All studied crop drought indices were suitable for studying crop drought cases. The wheat variety acsad/65 was sensitive to drought stress.

Mitigation of the effect of drought on growth and yield of pomegranates by foliar spraying of different sizes of selenium nanoparticles.

Drought is a very important environmental stressor, which has negative effects on the growth of trees, decreasing their yield. The role of different-sized selenium nanoparticles (Se-NPs) in the mitigation of environmental stresses such as drought in crops has not yet been investigated. Trees treated with Se-NPs displayed higher levels of photosynthetic pigments, a better nutrient status, better physical parameters (especially fruit cracking) and chemical parameters, a higher phenolic content, and higher concentrations of osmolytes, antioxidant enzymes, and abscisic acid than untreated trees under drought stress. Foliar spraying of 10 and 50 nm Se-NPs alleviated many of the deleterious effects of drought in pomegranate leaves and fruits and this was achieved by reducing stress-induced lipid peroxidation and H2 O2 content by enhancing the activity of antioxidant enzymes. Furthermore, the 10nm Se-NPs treatment produced more noticeable effects than the treatment with 50 nm Se-NPs. Results confirm the positive effects of nanoparticle spraying, especially the role of 10nm Se-NPs in the management of negative effects of drought not only for pomegranates but potentially also for other crops. © 2021 Society of Chemical Industry.

Low-energy heavy-ion-beam-induced mutation of novel high-yielding drought-tolerant Thai Jasmine rice

To respond to the global warming challenge to local agriculture, we applied a low-energy heavy ion beam as novel biotechnology to improve crop drought tolerance. Dehulled seeds of Thai Jasmine rice, Khao Dawk Mali 105 (KDML105), a popular Thai rice variety, were bombarded by a nitrogen ion beam with energy of tens-keV and fluences in an order of 1016 ions/cm2. The resulting mutagenized rice was obtained, selected, and further advanced until phenotypically stable. Mutagenized lines were screened for drought tolerance in the seedling and reproductive stages under an artificially created drought condition in comparison with KDML105 and the drought-tolerant reference variety, CT9993, using both subjective and quantitative parameters. We advanced the mutants up to M8 generation for stabilization and found a mutant line named HyKOS22, which displayed higher tolerance to the drought condition than KDML105 and CT9993 and produced a higher crop yield than KDML105. Genetic changes in HyKOS22 were confirmed by molecular biology analysis.

Capability of leaf water content and its threshold values in reflection of soil–plant water status in maize during prolonged drought

Leaves play an important role in plant growth and development through photosynthesis and transpiration. Many studies have explored the effects of short-term drought stress on leaf water status; however, few studies have focused on the leaf water content capacity as an indicator of soil–plant water status during prolonged droughts. The results of a field experiment with various irrigation regimes that was conducted during two consecutive maize growing seasons from 2013 to 2014, indicated that the water content of the first fully expanded leaf (LWCtop1) was representative of the soil–plant water status with the development of drought. LWCtop1 was closely linked to the water condition of other leaves and different plant parts in response to progressive water stress. LWCtop1 shared a quadratic relationship with the photosynthetic rate (Pn), and Pn peaked when LWCtop1 approached 84.11% and decreased to zero when LWCtop1 dropped to 68.26%. Moreover, three stages (slow-fast-slow) were observed as leaf water content responded to soil drying, and two important threshold values (minimum: 70.86 ± 0.80%, maximum: 84.58 ± 1.10%) of the leaf water content were determined. The results of this study may provide a physiological and ecological basis for the identification and monitoring of crop drought.

Transpiration increases under high-temperature stress: Potential mechanisms, trade-offs and prospects for crop resilience in a warming world.

The frequency and intensity of high-temperature stress events are expected to increase as climate change intensifies. Concomitantly, an increase in evaporative demand, driven in part by global warming, is also taking place worldwide. Despite this, studies examining high-temperature stress impacts on plant productivity seldom consider this interaction to identify traits enhancing yield resilience towards climate change. Further, new evidence documents substantial increases in plant transpiration rate in response to high-temperature stress even under arid environments, which raise a trade-off between the need for latent cooling dictated by excessive temperatures and the need for water conservation dictated by increasing evaporative demand. However, the mechanisms behind those responses, and the potential to design the next generation of crops successfully navigating this trade-off, remain poorly investigated. Here, we review potential mechanisms underlying reported increases in transpiration rate under high-temperature stress, within the broader context of their impact on water conservation needed for crop drought tolerance. We outline three main contributors to this phenomenon, namely stomatal, cuticular and water viscosity-based mechanisms, and we outline research directions aiming at designing new varieties optimized for specific temperature and evaporative demand regimes to enhance crop productivity under a warmer and dryer climate.

Heterologous expression of fungal AcGDH alleviates ammonium toxicity and suppresses photorespiration, thereby improving drought tolerance in rice

Drought stress can significantly affect plant growth and agricultural productivity. Thus, it is essential to explore and identify the optimal genes for the improvement of crop drought tolerance. Here, a fungal NADP(H)-dependent glutamate dehydrogenase gene (AcGDH) was isolated from Aspergillus candidus, and heterologously expressed in rice. AcGDH has a high affinity for NH4+ and increases the ammonium assimilation in rice. AcGDH transgenic plants exhibited a tolerance to drought and alkali stresses, and their photorespiration was significantly suppressed. Our findings demonstrate that AcGDH alleviates ammonium toxicity and suppresses photorespiration by assimilating excess NH4+ and disturbing the delicate balance of carbon and nitrogen metabolism, thereby improving drought tolerance in rice. Moreover, AcGDH not only improved drought tolerance at the seedling stage but also increased the grain yield under drought stress. Thus, AcGDH is a promising candidate gene for maintaining rice grain yield, and offers an opportunity for improving crop yield under drought stress.

Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability

Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, ‘Cadeli’ and ‘Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to −0.96[−2.21,0.21] and −0.71[−1.97,0.49] units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of 0.33[0.16,0.68] for ‘Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes.

Overexpression of an aquaporin gene PvPIP2;9 improved biomass yield, protein content, drought tolerance and water use efficiency in switchgrass (Panicum virgatum L.)

AbstractSwitchgrass (Panicum virgatum L.) is a prime candidate for non‐grain‐based bioenergy feedstock production. Improved drought tolerance and higher water use efficiency (WUE) are important for its successful field establishment and production, especially on marginal lands. Aquaporins are key channels and regulators for water transportation and maintenance of cellular water status. In this study, the functional role of an aquaporin gene, PvPIP2;9, in switchgrass was studied. Expression of PvPIP2;9 was regulated by diurnal oscillation and osmotic stress. Constitutive over‐expressing PvPIP2;9 in switchgrass significantly improved its leaf length, plant height, aboveground biomass and biomass protein contents under both drought‐ and non‐stressed conditions, and also resulted in higher cellulose content in drought‐stressed transgenic than wild‐type plants. Under 21 days of drought treatment, transgenic plants showed less electrolyte leakage rates, but higher relative water contents, photochemical efficiencies, chlorophyll contents and WUE, indicating that PvPIP2;9 positively regulated plant drought tolerance. Moreover, expression patterns of all 14 switchgrass PIP2 subfamily genes were checked during the drought treatment, and the result showed that over‐expressing PvPIP2;9 also affected transcript levels of most other PIP2 genes. Together, this study showed that improved biomass yield, drought tolerance and higher WUE can be achieved by manipulating the expression of PvPIP2;9 and also suggested PIP2 subfamily genes were transcriptionally regulated in a coordinated manner, which can be used for potential targets for crop drought resistance breeding efforts.

The HD-Zip I transcription factor MdHB-7 regulates drought tolerance in transgenic apple (Malus domestica)

Drought severely restricts global crop yield and quality. These limitations may be partially addressed through genetic engineering to improve crop drought tolerance. The HD-Zip I transcription factors play important roles in the regulation of plant drought tolerance, but their specific functions in the regulation of apple drought response remain unclear. In this study, we found that MdHB-7 was expressed at different levels in a variety of apple tissues and was significantly induced by abscisic acid (ABA) and drought stress treatments. To investigate the functions of MdHB-7, we created transgenic apple plants that exhibited either MdHB-7 overexpression or RNAi-induced MdHB-7 suppression. Through drought stress treatments and phenotypic assessments, we found that MdHB-7 expression enhanced the drought tolerance of apple plants. Overexpression of MdHB-7 promoted endogenous ABA accumulation, stomatal closure, and reactive oxygen species (ROS) detoxification in response to drought, whereas suppression of MdHB-7 expression had the opposite effect. Our results lay a foundation for further research on the mechanisms by which HD-Zip I proteins promote drought tolerance.

Effects of irrigation regimes on yield and quality of upland rice and paddy rice and their interaction with nitrogen rates

The study of water-nitrogen (N) interaction to improve crop drought resistance and reduce environmental pollution has increasingly become a hot topic. However, the response of yield and quality of paddy rice and upland rice to N nutrition under different irrigation regimes is little known. Continuous flooding cultivation (CF, control) and bare-dry cultivation (BD) were used to cultivate paddy rice cultivar Yangjing 687 (japonica) and upland rice cultivar Zhonghan 3 (japonica), and 3 N application rates, 140 (low N, LN), 210 (normal N, NN) and 280 kg ha−1(high N, HN), were set for each irrigation regime. The results showed that under BD and CF irrigation regimes, the yield of paddy rice was the highest at NN, while that of upland rice was the highest at BD with NN and at CF with HN, breakdown viscosity was the highest and setback viscosity was the lowest for paddy rice at LN and for upland rice at NN. Increasing N application, the chalky kernels percentage and the chalkiness of upland rice increased first and then decreased, while that of paddy rice decreased under BD and increased under CF. Compared with CF, BD made the seed setting percentage and 1000-grain weight of upland rice and paddy rice different, and improved the appearance and nutritional quality of upland rice. The correlation between the cooking and nutritional quality and leaf N content of upland rice was lower than that of paddy rice. These results suggest that the yield and cooking quality of upland rice were high under BD with NN, and the paddy rice yield was high under BD with NN or CF with NN.

Analysis and Application of Drought Characteristics Based on Theory of Runs and Copulas in Yunnan, Southwest China.

Drought is a complex natural disaster phenomenon. It is of great significance to analyze the occurrence and development of drought events for drought prevention. In this study, two drought characteristic variables (the drought duration and severity) were extracted by using the Theory of Runs based on four drought indexes (i.e., the percentage of precipitation anomaly, the standardized precipitation index, the standardized precipitation evapotranspiration index and the improved comprehensive meteorological drought index). The joint distribution model of drought characteristic variables was built based on four types of Archimedean copulas. The joint cumulative probability and the joint return period of drought events were analyzed and the relationship between the drought characteristics and the actual crop drought reduction area was also studied. The results showed that: (1) The area of the slight drought and the extreme drought were both the zonal increasing distribution from northeast to southwest in Yunnan Province from 1960 to 2015. The area of the high frequency middle drought was mainly distributed in Huize and Zhanyi in Northeast Yunnan, Kunming in Central Yunnan and some areas of Southwest Yunnan, whereas the severe drought was mainly occurred in Deqin, Gongshan and Zhongdian in Northwest Yunnan; (2) The drought duration and severity were fitted the Weibull and Gamma distribution, respectively and the Frank copula function was the optimal joint distribution function. The Drought events were mostly short duration and high severity, long duration and low severity and short duration and low severity. The joint cumulative probability and joint return period were increased with the increase of drought duration and severity; (3) The error range between the theoretical return period and the actual was 0.1–0.4 a. The year of the agricultural disaster can be accurately reflected by the combined return period in Yunnan Province. The research can provide guidelines for the agricultural management in the drought area.

Stomatal limitations to photosynthesis and their critical Water conditions in different growth stages of maize under water stress

Stomata are the channels by which plants exchange water vapor and carbon dioxide with the environment. Clarifying the change from stomatal limitations (SL) to non-stomatal limitations (NSL) of photosynthesis and their critical conditions is vital for accurately recognizing the degree of crop drought and formulating countermeasures. A field experiment was carried out from 2013 to 2015 to study the critical water conditions when maize photosynthesis changed from being limited by SL to NSL in different leaf positions under different degrees of water stress in different growth stages (3rd leaf stage, 7th leaf stage and jointing stage). Our results indicated that photosynthesis of maize leaves at different positions changed from being determined by SL to NSL under different water stress levels at different growth stages; moreover, maize photosynthesis changed from being directed by SL to NSL in the first fully expanded leaf at the top before the changes occurred in the third leaf. The effect of water stress during different growth stages on the maize leaf water content (LWC) at which photosynthesis changed from being limited by SL to NSL was not distinct. The changing point of SL at different leaf positions was closely related to the LWC, and the LWC at the changing point of SL was different at different leaf positions, which indicated that the change in SL is mainly determined by the leaf position and LWC, and its occurrence showed a decreasing trend from plant top to bottom. The LWC at which the SL transformation point occurred in the first fully expanded leaf at the top (75.5 % ± 1.5 %–75.7 % ± 1.3 %) was higher than that at which the change occurred in the third leaf at the top (73.2 % ± 1.1 %–73.4 % ± 1.6 %). The phenomenon of photosynthesis changing from being limited by SL to NSL occurred first in the first fully expanded leaf at the top; additionally, the LWC of the first fully expanded leaf at the top was the best indicator in maize under water stress and could be used as the critical condition marking the transformation of maize damage from water stress to damage from plant physiological and ecological stress. These results could provide a basis for the identification of crop drought disasters and their classification and provide a methodological reference for the identification and monitoring of drought in other crops.

Unique miRNAs and their targets in tomato leaf responding to combined drought and heat stress

BackgroundBoth drought and heat stress are serious global problems, leading to agricultural production loss. MicroRNAs (miRNAs) play important roles in plant species responding to individual drought and heat stress. However, the miRNAs and mRNAs in association with combined drought and heat in crops like tomato remains unclear.ResultsWe studied the crosstalk of miRNAs and their target genes in tomato plants grown under simultaneous drought and heat stress that frequently happen in field conditions. In total, 335 known miRNAs representing 55 miRNA families and 430 potential novel miRNAs were identified in Solanum lycopersicum L. using small RNA deep sequencing. Through expression analysis, miRNAs in association with drought, heat and the combination of these were investigated. In total, 61, 74 and 37 miRNAs were differentially regulated for combination (of both stresses) vs control, combination vs drought and combination vs heat, respectively. Target genes with different expression levels were found using degradome sequencing, which were mainly involved in transcription factor activity, sequence-specific DNA binding, transcription, regulation of transcription, nucleus, DNA binding etc. The quantitative real-time polymerase chain reaction (qRT-PCR) results confirmed the accuracy of sequencing.ConclusionsOur study serves as valuable knowledge on how crop adapted to combined drought and heat stress by regulating miRNAs and mRNAs, which provide information for crop improvement to deal with future climate changes.

Molecular bases for drought tolerance in common vetch: designing new molecular breeding tools

BackgroundCommon vetch (Vicia sativa L.) is a forage grain legume of high protein content and high nitrogen fixation, relevant in sustainable agriculture systems. Drought is the main limiting factor of this crop yield. Genetic resources collections are essential to provide genetic variability for breeding. The analysis of drought associated parameters has allowed us to identify drought tolerant and sensitive ecotypes in a vetch core collection.ResultsTo understand the mechanisms involved in drought response we analysed transcriptomic differences between tolerant and sensitive accessions. Polymorphic variants (SNPs and SSRs) in these differential expressed genes (DEGs) have also been analysed for the design of drought-associated markers. A total of 1332 transcripts were commonly deregulated in both genotypes under drought. To know the drought adaptive response, we also analysed DEGs between accessions. A total of 2646 transcripts are DEG between sensitive and tolerant ecotypes, in watered and drought conditions, including important genes involved in redox homeostasis, cell wall modifications and stress-response. The integration of this functional and genetic information will contribute to understand the molecular mechanisms of drought response and the adaptive mechanisms of drought tolerance in common vetch. The identification of polymorphic variants in these DEGs has also been screened for the design of drought-associated markers that could be used in future breeding program strategies.ConclusionsOur studies shed light for the first time in common vetch about the genes and pathways associated with drought tolerance. In addition, we identify over 100 potential drought associated polymorphism, as SNPs or SSRs, which are differently present in drought and tolerant genotypes. The use of these molecular markers for trait prediction would enable the development of genomic tools for future engineering strategies by screening of germplasm crop collections for traits related with crop drought resilience, adaptability or yield in vetch.

Evaluation of a combined drought indicator and its potential for agricultural drought prediction in southern Spain

Abstract. Drought prediction is crucial, especially where the rainfall regime is irregular, such as in Mediterranean countries. A new combined drought indicator (CDI) integrating rainfall, soil moisture and vegetation dynamics is proposed. Standardized precipitation index (SPI) is used for evaluating rainfall trends. A bucket-type soil moisture model is employed for keeping track of soil moisture and calculating anomalies, and, finally, satellite-based normalized difference vegetation index (NDVI) data are used for monitoring vegetation response. The proposed CDI has four levels, at increasing degrees of severity: watch, warning, alert type I and alert type II. This CDI was thus applied over the period 2003–2013 to five study sites, representative of the main grain-growing areas of SW Spain. The performance of the CDI levels was assessed by comparison with observed crop damage data. Observations show a good match between crop damage and the CDI. Important crop drought events in 2004–2005 and 2011–2012, distinguished by crop damage in between 70 % and 95 % of the total insured area, were correctly predicted by the proposed CDI in all five areas.

Drought Analysis Based on the Information Diffusion and Fractal Technology: A Case Study of Winter Wheat in China

HighlightsThere is no good correlation between meteorological drought and crop drought.The data series of meteorological drought and crop drought at the same time have fractal characteristics.Fractal theory can be used to predict the next drought year.Abstract.Drought is one of the natural disasters of global concern. Drought forecasting is an important tool for drought management. Uncertainty is a major challenge in drought forecasting. In order to provide a short-term effective drought prediction, this study provides a new point into drought prediction from the timing-prediction perspective. The key part of this essay lies in its fractal theoretical framework guided by the self-similarity principle, which fully considers the complexity, disorder and regularity of agricultural drought. At the same time, information diffusion theory is used to polish the raw data, especially some data about winter wheat in Zhengzhou in China. The results as follows: 1) the change trend of drought in the study region is consistent with the past; 2) the time of meteorological drought, summer maize does not necessarily lead to drought, but most timing prediction work is consistent, they have shared the similar cyclical changing-laws; and 3) the occurring time of the next drought calculated is consistent with the actual observation results. Therefore, the method established in this study is effective, and it can provide some reference for the prediction of agricultural drought outbreak time. Keywords: Crop drought, Fractal theory, Information diffusion, Meteorological drought, Winter wheat.

Machine Learning-Based Crop Drought Mapping System by UAV Remote Sensing RGB Imagery

Water stress has adverse effects on crop growth and yield, where its monitoring plays a vital role in precision crop management. This paper aims at initially exploiting the potentials of UAV aerial RGB image in crop water stress assessment by developing a simple but effective supervised learning system. Various techniques are seamlessly integrated into the system including vegetation segmentation, feature engineering, Bayesian optimization and Support Vector Machine (SVM) classifier. In particular, wheat pixels are first segmented from soil background by using the classical vegetation index thresholding. Rather than performing pixel-wise classification, pixel squares of appropriate dimension are defined as samples, from which various features for pure vegetation pixels are extracted including spectral and color index (CI) features. SVM with Bayesian optimization is adopted as the classifier. To validate the developed system, a Unmanned Aerial Vehicle (UAV) survey is performed to collect high-resolution atop canopy RGB imageries by using DJI S1000 for the experimental wheat fields of Gucheng town, Heibei Province, China. Two levels of soil moisture were designed after seedling establishment for wheat plots by using intelligent irrigation and rain shelter, where field measurements were to obtain ground soil water ratio for each wheat plot. Comparative experiments by three-fold cross-validation demonstrate that pixel-wise classification, with a high computation load, can only achieve an accuracy of 82.8% with poor F1 score of 71.7%; however, the developed system can achieve an accuracy of 89.9% with F1 score of 87.7% by using only spectral intensities, and the accuracy can be further improved to 92.8% with F1 score of 91.5% by fusing both spectral intensities and CI features. Future work is focused on incorporating more spectral information and advanced feature extraction algorithms to further improve the performance.

Transcription factors as molecular switches to regulate drought adaptation in maize.

Here, we reviewed major transcription factors of maize that confer drought stress tolerance, and their target genes and involved signaling pathway. Transcription factors in maize can be promising candidates for improving comprehensive resistance of multiple environmental stimuli. Adverse environmental stress is the main influencing factor affecting plant growth and reproduction, which poses tremendous threats to sustainable agriculture development and crops productivity worldwide. Among various abiotic stress factors, drought is the most vital adversity with the characteristics of frequent occurrences, long duration, and globality. Maize (Zea mays L.) is a major source of food supply for human being and livestock and recently for biofuel. Maize is the crop that is highly susceptible to drought stress. Drought stress tolerance in plants is quite complex, and it is not ideal to improve crop drought tolerance through a single resistant gene. Transcription factors participate in the regulation of plant growth and development, morphogenesis, and various environmental stress responses via regulating the expression level of their target stress-responsive genes independently or cross talk with other transcription factors, thereby the comprehensive resistance of multiple stresses in crops is improved. This review aims to summarize the major drought-tolerant transcription factors in maize and their regulatory network. With the continuous identification of maize transcription factors, more will be demonstrated to confer drought tolerance either in maize or other crops. It is expected that the transcription factors will greatly enrich the functional gene resources and will be a benefit to drought-tolerant maize cultivars breeding.

A Quantitative Analysis of Socio-Economic Determinants Influencing Crop Drought Vulnerability in Sub-Saharan Africa

Drought events have significant impacts on agricultural production in Sub-Saharan Africa (SSA), as agricultural production in most of the countries relies on precipitation. Socio-economic factors have a tremendous influence on whether a farmer or a nation can adapt to these climate stressors. This study aims to examine the extent to which these factors affect maize vulnerability to drought in SSA. To differentiate sensitive regions from resilient ones, we defined a crop drought vulnerability index (CDVI) calculated by comparing recorded yield with expected yield simulated by the Environmental Policy Integrated Climate (EPIC) model during 1990–2012. We then assessed the relationship between CDVI and potential socio-economic variables using regression techniques and identified the influencing variables. The results show that the level of fertilizer use is a highly influential factor on vulnerability. Additionally, countries with higher food production index and better infrastructure are more resilient to drought. The role of the government effectiveness variable was less apparent across the SSA countries due to being generally stationary. Improving adaptations to drought through investing in infrastructure, improving fertilizer distribution, and fostering economic development would contribute to drought resilience.

Drought Monitoring Based on Ground and Satellite Data

Droughts on the territory of Russia and their impact on the crop productivity are briefly described. Drought risk maps and the current and future drought indices are discussed. The Russian drought monitoring system based on the ground information is considered. The possibility of using satellite data for the operational drought monitoring is assessed. The results of the evaluation of the crop state and droughts based on surface and satellite data are given.