Drought Patterns Research Articles

Response of vegetation ecosystems to flash drought with solar-induced chlorophyll fluorescence over the Hai River Basin, China during 2001–2019

With global climate change, frequent flash droughts have critically impacted vegetation productivity. Based on the new definition on flash drought onset and duration, the temporal and spatial evolution patterns of the flash drought over the Hai River Basin (HRB) was analysed. Among the events, the flash drought in 2019 lasted for 40 days, from the day of the year (DOY) 120 to DOY160, which was the strongest and mainly concentrated in the south-eastern part of the basin. Solar-induced chlorophyll fluorescence (SIF) and vegetation indices were used to explore the responses of different vegetation types to this flash drought. Compared to forest and grassland, the SIF and SIFyield (SIF normalized by the absorbed photosynthetically active radiation (APAR)) values of cropland were more sensitive to water losses and replenishment. By analysing different radiation conditions which would affect SIF and photosynthesis, low radiation was found altering the linear relationship between fluorescence and photosynthesis. The flash drought event caused gross primary productivity (GPP) losses in 40% of the basin and the maximum loss reached 0.16 kg C m−2, indicating that the impact of this flash drought on vegetation productivity was quite serious. The results obtained in this work can be used to understand the mechanisms with which the vegetation photosynthetic capacity responds to flash droughts and to evaluate the impact of flash droughts on terrestrial ecosystems.

Spatiotemporal patterns of agricultural and meteorological droughts using SPI and MODIS-based estimates over a Brazilian semiarid region: study case of Upper Paraíba River basin

Drought is a very complex natural phenomenon that affects the water supply and consequently impacts agricultural and socioeconomic activities, causing social and political crises. The objective of this study is to spatiotemporally analyze meteorological and agricultural droughts based on multiple indices in the Upper Paraíba River basin for the 2001–2017 period. The agricultural droughts were analyzed using four drought indices (NDVI, LST, VSWI, and VHI) based on data from the MODIS sensor on the TERRA and AQUA satellites, while the meteorological droughts were characterized using the standardized precipitation index (SPI) at three different time scales based on TRMM rainfall data. The values of LST, NDVI, VHI, VSWI, and SPI revealed how much vegetation is influenced by rainfall variability in this semiarid region of Brazil. The estimated results of VSWI and VHI show the years with extremely wet and dry conditions from spatial and temporal perspectives. The relationship between estimated drought indices and observed relative humidity showed that VSWI (R2 = 0.78) was best fitted when compared to VHI (R2 = 0.46). Thus, it can be concluded that the VSWI index is better adapted because it presented more consistent results for the behavior of agricultural droughts when compared to the VHI. The results of the SPI analysis were used for the identification of the main drought events that affected the study basin. This combined technique of different drought indices easily produced an alternative method for comprehensive drought assessment.

Complex drought patterns robustly explain global yield loss for major crops

Multi-purpose crops as maize, rice, soybean, and wheat are key in the debate concerning food, land, water and energy security and sustainability. While strong evidence exists on the effects of climate variability on the production of these crops, so far multifaceted attributes of droughts—magnitude, frequency, duration, and timing—have been tackled mainly separately, for a limited part of the cropping season, or over small regions. Here, a more comprehensive assessment is provided on how droughts with their complex patterns—given by their compound attributes—are consistently related to negative impacts on crop yield on a global scale. Magnitude and frequency of both climate and yield variability are jointly analysed from 1981 to 2016 considering multiscale droughts, i.e., dry conditions occurring with different durations and timings along the whole farming season, through two analogous and standardized indicators enabling comparison among crops, countries, and years. Mainly winter wheat and then spring wheat, soybean and the main maize’s season reveal high susceptibility of yield under more complex drought patterns than previously assessed. The second maize’s season and rice present less marked and more uncertain results, respectively. Overall, southern and eastern Europe, the Americas and sub-Saharan Africa presents multi-crop susceptibility, with eastern Europe, Middle East and Central Asia appearing critical regions for the most vulnerable crop, which is wheat. Finally, yield losses for wheat and soybean clearly worsen when moving from moderate to extreme multiscale droughts.

The Complex and Spatially Diverse Patterns of Hydrological Droughts Across Europe

AbstractThis study presents a new data set of gauged streamflow (N = 3,224) for Europe spanning the period 1962–2017. The Monthly Streamflow of Europe Dataset (MSED) is freely available at http://msed.csic.es/. Based on this data set, changes in the characteristics of hydrological drought (i.e., frequency, duration, and severity) were assessed for different regions of Europe. Due to the density of the database, it is possible to delimit spatial patterns in hydrological droughts trend with the greatest detail available to date. Results reveal bidirectional changes in monthly streamflow, with negative changes predominating over central and southern Europe, while positive trends dominate over northern Europe. Temporally, two dominant patterns were noted. The first pattern corresponds to a consistent downward trend in all months, evident for southern Europe. A second pattern was noted over central and northern Europe and western France, with a predominant negative trend during warm months and a positive trend in cold months. For hydrological drought events, results suggest a positive trend toward more frequent and severe droughts in southern and central Europe and conversely a negative trend over northern Europe. This study emphasizes that hydrological droughts show complex spatial patterns across Europe over the past six decades, implying that hydrological drought behavior in Europe has a regional character. Accordingly it is challenging to adopt “efficient” strategies and policies to monitor and mitigate drought impacts at the continental level.

The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes

Abstract. The mid-summer drought, veranillo or canícula, is a phenomenon experienced in many areas, including Mexico, Central America, and the Caribbean. It generally is experienced as reduced rainfall in July–August, in the middle of the typical rainy season (May–September). Many past studies have attempted to quantify changes in mid-summer drought characteristics during the recent past or for future climate projections. To do this, objective definitions of a mid-summer drought's occurrence, strength, and duration have been developed by many researchers. In this effort we adopt a recent set of definitions and examine the impact of varying these on the characterization of mid-summer droughts and the detected changes over the past 4 decades. We find the selection of a minimum intensity threshold has a dramatic effect on the results of both the area considered as experiencing a mid-summer drought and the changes detected in the recent historical record. The intensity chosen can affect both the magnitude and direction of changes reported in the recent observed record. Further, we find that the typical mid-summer drought pattern may not be occurring during the time it has historically; whether examining past or future changes or developing improved seasonal forecasts, the non-stationarity of its timing should be accommodated.

Changes in drought characteristics based on rainfall pattern drought index and the CMIP6 multi-model ensemble

Drought monitoring and understanding of spatiotemporal patterns of drought characteristics are beneficial for sustainable agricultural water management at a regional scale. Changes in rainfall and drought patterns in future could impact decision-making in water resources allocation. The impacts of potential climate change on future meteorological droughts could be better analysed by utilizing an index that incorporates the number of rainy days information in addition to magnitude of rainfall to characterize the drought severity. In this study, we propose a bivariate copula-based multi-scalar rainfall pattern drought index (RPDI), a variant of the popular standardized precipitation index (SPI), and then the drought characteristics in India based on RPDI and SPI at different time scales (3-, 6- and 12-months) are analysed. When compared to RPDI, SPI underestimated drought severity and indicated low spatial heterogeneity of drought characteristics. The RPDI analysis identified changes in average drought severity and total number of drought events between two sample time slices (1920–1960 and 1961–2000) in the historical period. Future RPDI drought characteristics based on the coupled model intercomparison project phase 6 (CMIP6) multi-model ensemble under two emission scenarios known as shared socioeconomic pathways (SSPs): SSP126 and SSP245 are then computed. When drought characteristics in the near future (2020–2049) and far future (2070–2099) periods are compared with their baseline period (1985–2014) values, the results show that a significant declining trend is likely in the total number of drought events over the study region, while increases are projected in the maximum drought duration and maximum drought severity in future. Long-term drought characteristics extracted using 12-months scale RPDI, are likely to intensify in future under both scenarios. Considering the effects of erratic rainfall pattern on agricultural productivity, the RPDI drought monitoring framework could be utilized for efficient agricultural water management in future.

The Characteristics and Evaluation of Future Droughts across China through the CMIP6 Multi-Model Ensemble

Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China’s droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control.

Recent Hydrological Droughts in Brazil and Their Impact on Hydropower Generation

Brazil has endured the worst droughts in recorded history over the last decade, resulting in severe socioeconomic and environmental impacts. The country is heavily reliant on water resources, with 77.7% of water consumed for agriculture (irrigation and livestock), 9.7% for the industry, and 11.4% for human supply. Hydropower plants generate about 64% of all electricity consumed. The aim of this study was to improve the current state of knowledge regarding hydrological drought patterns in Brazil, hydrometeorological factors, and their effects on the country’s hydroelectric power plants. The results show that since the drought occurred in 2014/2015 over the Southeast region of Brazil, several basins were sharply impacted and remain in a critical condition until now. Following that event, other regions have experienced droughts, with critical rainfall deficit and high temperatures, causing a pronounced impact on water availability in many of the studied basins. Most of the hydropower plants end the 2020–2021 rainy season by operating at a fraction of their total capacity, and thus the country’s hydropower generation was under critical regime.

Examining spatiotemporal trends of drought in the conterminous United States using self-organizing maps

ABSTRACT Droughts are a natural, recurrent climate extreme that can inflict long-lasting devastation on natural ecosystems and socio-economic sectors. Unlike other natural hazards, drought onset is insidious and often affects a greater spatial extent over a prolonged temporal scale. In the United States the evolution of drought and its impacts are typically region-specific and intensified precipitation variability may obscure how drought may manifest. In this study, we examine the spatiotemporal trends of drought using self-organizing maps (SOM), competitive learning subset of artificial neural networks (ANN), requiring unsupervised training of inputs. We introduced monthly Palmer Drought Severity Index (PDSI) values to the SOM to identify existing clusters of wetting and drying patterns from 1895 to 2016. After training, we created cartographic visualizations of the SOM output and conducted a subsequent time-series analysis to link with the geographic patterns of drought. Over the last 40 years, precipitation intensified in the Northeast, Midwest, and upper Great Plains across several nodes. Across the majority of SOM patterns, we identified no significant changes of drying or wetting patterns over the last century for the greater part of the CONUS.

Drought Analysis Using Standardized Evapotranspiration and Aridity Index at Bilate Watershed: Sub-Basins of Ethiopian Rift Valley.

In Ethiopia, more prevalent drought happenings have been documented in the past century. The problem has gradually expanded from the north to the rest parts with deepened intensity. The study aimed to examine the magnitudes of spatiotemporal patterns of drought at the Bilate watershed from 1981 to 2016. Monthly rainfall and temperature data were used for the analysis. The Standardized Evapotranspiration Indexes (SPEI) at SPEI-03 and SPEI-12 timescales were applied to evaluate the drought patterns. Among different drought indices, the SPEI is the most valuable and preferred Index for drought studies. The SPEI method considers the role of temperature than other indices to compare drought in time and space. The Mann–Kendall test was used for trend analysis. Accordingly, the result revealed that 1988–2016 were years of continuous drought events in both timescales with (SPEI = −2.5 to −1.2) drought value. Drought severity and frequency were highly detected at Wulberag areas (SPEI: −2.5). Durame, Angacha, and Alaba experienced increasing drought trends (Z = −1.96−1.6) and Welayita Sodo is Z = −0.07−0.03. Bilate-Tena and Hossana area of the watershed were less affected by drought than other areas. Spatially, the drought occurrences were observed in all areas of the watershed with varying magnitude. In the SPEI-12 timescale, more frequent drought occurrences were observed than SPEI-03. It was found that severe drought was observed in 1987, 1993/94, 2000–2005, and 2010. Moreover, the watershed experienced an Aridity Index (AI) of 0.43 (43%) and was subjected to potential high evapotranspiration (PET). The highest PET was observed at Bilate-Tena, Angacha, Hosanna, Wulberag, Alaba, Welayita Sodo, and Durame (151.6, 119.6, 119.3, 140.8, 142, 127.5, and 125.7 mm/year, respectively. Hence, the finding of this study could initiate a further inquiry on drought risk management, early warning responses, and local scale planning.

Spatiotemporal Rainfall Variability and Drought Assessment during Past Five Decades in South Korea Using SPI and SPEI

About 41% of the earth is drought-affected, which has impacted nearly 2 billion people, and it is expected that more than 90% of terrestrial areas will be degraded by 2050. To evade and mitigate the harmful impacts of drought, it is necessary to study the rainfall variability and assess the drought trend at a global and regional level. This study utilized 70 meteorological stations in South Korea to evaluate the rainfall variability, drought, and its trend during the past five decades using the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI). Rainfall data normality was assessed with mean, standard deviation, skewness, and kurtosis. The highest amount of rainfall was observed in the months of June, July, and August. The SPI and SPEI 12-month results revealed that 1982, 1988, 2008, 2015, and 2017 were dry years throughout the country, while from 2013 to 2017 mixed drought events were observed for the 6-month time series. The Mann-Kendall trend test was applied to the 1- and 12-month time series, and the results revealed that the months of January, March, April, May, June, and August had a significant negative trend, which means drought is increasing in these months, while the months of September, October, and December had a significant positive trend, which means wetter conditions prevailed in these months during the study period. It was observed in the 12-month time series that only two met stations had a significant negative trend, while only one had a significant positive trend. It was found that January and March were the driest months, and October was the wettest month. The detected drought events in this research are consistent with ENSO events. We have observed differences in drought characteristics (duration and frequency) for both indices. Climatic data revealed that South Korea has faced drought conditions (rainfall deficit) due to a shortened monsoon season. This study can provide guidance on water management strategies under the changing pattern of drought in South Korea.

Drought Assessment Based on Fused Satellite and Station Precipitation Data: An Example from the Chengbi River Basin, China

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought.

Patterns of Past and Future Droughts in Permanent Lowland Rivers

The problem of droughts is acute due to climate change. The study aims to assess the temporal and spatial drought patterns in Lithuanian lowland rivers in the past and to project these phenomena according to climate scenarios and models. Drought analysis was based on Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI) and Streamflow Drought Index (SDI). To evaluate the past patterns, the hydrometeorological data of 17 rivers were used from 1961–2020. Future drought changes were analyzed in 2021–2100 according to the selected RCPs (Representative Concentration Pathways) using the hydrological model HBV. There were different patterns of droughts in three hydrological regions of Lithuania (Western, Central and Southeastern). The Southeastern region was more prone to extreme summer hydrological droughts, and they had a shorter accumulation period compared to the other two regions. SPI and RDI indices showed that the number of dry months and the minimum value of the index increased, extending the accumulation period. The highest correlation was recorded between RDI-12/SPI-12 and SDI-12. The amplitude between extremely wet and dry values of river runoff will increase according to RCP8.5. The projections indicated that hydrological drought intensity in the Central region is expected to increase under both analyzed RCPs.

Peat fire risk assessment in Central Kalimantan, Indonesia using the Standardized Precipitation Index (SPI)

Decreased rainfall and drought due to the long dry season affecting peat fires in Indonesia. This condition causes a decrease in the groundwater level and peat drought, bringing a dry conditions of peat that are suitable for fires. Our prolonged studies revealed a close relationship between precipitation, groundwater levels, and peat fires. This paper aims to assess the risk of peat fires by applying the Standardized Precipitation Index (SPI). We used 18-year daily rainfall data (2000–2017), 16-year hotspot data (2002–2017), and 8-year groundwater level data (2010–2017). Our results showed the strong correlation (r = -0.61) between SPI-1 (short term) and the number of fires. The combination of low rainfall. the peat fire occurrences will increase significantly following less SPI-1 value and decreased groundwater levels during the peak of the dry season. A prolonged dry season followed by less rainfall in the normal rainy season will encourage high-intensity peat fires, bring the important of the using of drought patterns for a better risk assessment of future peat fire occurrences.

Changing spectral patterns of long‐term drought propensity in Iran through reliability–resilience–vulnerability‐based Drought Management Index

AbstractThis study aims to investigate the change in spectral patterns of droughts in Iran based on the concepts of reliability, resilience, and vulnerability (RRV) in the context of time. To achieve this goal, RRV values were first estimated based on monthly gridded soil moisture data for a period of 64 years (1955–2018) for the framework of Iran's political borders. The pairwise comparison of the values of the three variables RRV indicates a positive relationship between reliability–resilience and a negative relationship between reliability–vulnerability and resilience–vulnerability. In order to obtain the Joint Probability Distribution between reliability–vulnerability, Drought Management Index (DMI) for all the gridded points within Iran's political borders were calculated by fitting the Gaussian copula. According to this index, drought is an unfavourable climatic phenomenon that is associated with increased Vulnerability and decreased Reliability. The temporal and spatial changes of this index indicate that DMI values are always high for the south, east and centre of Iran and low for the western and northern half. To study the change in spectral patterns of droughts in Iran, the 64‐year period studied (1955–2018) was divided into two equal periods of 32 years. Then, using spectral analysis through Fourier transform method, the first three periodicities related to each period that had the highest powers were extracted. Finally, their periodicity was compared. The results indicated that the drought periodicities in the north‐west, north‐east, west, south‐west, and south of Iran have become longer, that is, their nature has been changed from shorter periodicities to longer ones. This change of nature in their first three periodicities has been sometimes from 2–10 years to 2–15 years, from 2–10 years to 3–30 years, and from 3–8 years to 8–15 years. However, the periodicities of droughts in the eastern, south‐eastern, and central Iran has changed from longer periodicities to shorter ones. It has been changed from 3–15 years to 2–6 years, from 3–15 years to 2–3 years, and from 3–30 years to 3–15 years.

Spatio-temporal pattern of ecological droughts and their impacts on health of vegetation in Northwestern China

The ecological implications of drought have been widely discussed in recent years. Ecological drought was thus proposed as a new drought type to describe the impact of drought on ecosystems. The current study used an innovative drought index, called the standardized ecological water deficit index (SEWDI), to monitor terrestrial ecological drought in Northwestern China, which is an ecologically fragile region. Droughts and their characteristics, including drought affected area, drought severity, drought duration, drought frequency, and drought orientation, were extracted using a spatial and temporal identification method based on SEWDI at a three-month timescale. To investigate the variation in dominant factors determining vegetation health, the contributions of moisture and thermal conditions during different ecological drought events were determined using a gradient boosting regression model. The main results indicated that (1) the spatial and temporal identification method successfully identified the spatio-temporal patterns of ecological drought; (2) a total of 184 ecological drought events during 1982–2020 were identified, of which 56.6% occurred prior to the 21st century. Drought events in the 21st century always exhibit larger affected areas, longer durations, a higher frequency, and greater severity, and migrated westward; and (3) in all ecological drought events, vegetation health dominated by thermal conditions accounted for 42.7% and 48.2% before and during the 21st century, respectively. This illustrated that vegetation has experienced more severe thermal stress during the 21st century.

The increasing contribution of potential evapotranspiration to severe droughts in the Yellow River basin

Under global warming, droughts have become more severe and more frequent. In this context, it is widely accepted that both water supply (e.g., precipitation, PRE) and demand (e.g., potential evapotranspiration, PET) should be considered in drought assessments due to increasing evapotranspiration. China’s Yellow River basin is located mainly in arid and semi-arid regions that suffer severe droughts. Analyzing the temporal and spatial patterns of droughts in this area and exploring the relative effects of supply and demand on drought occurrence and variations are thus necessary to adapt to increased droughts. Here, we compared three kinds of drought indices, including the standardized precipitation evapotranspiration index (SPEI), the standardized precipitation index (SPI), and the standardized evapotranspiration deficit Index (SEDI), and used SPEI to identify droughts in the Yellow River basin during the six decades from 1956 to 2016. We identified droughts and described drought dynamics based on drought duration, intensity, frequency, and spatial extent. We then evaluated the relative contributions of PRE and PET to droughts of varying severity and long-term trend, as well as the relationships between ocean signals and droughts. Our results show that most of the basin has undergone progressively drier conditions since the 1950 s. This increased drought occurrence has manifested as longer, more frequent droughts affecting a larger spatial extent. PRE was the dominant driver (64%) of drought occurrence in an area of ∼ 86% of the basin, whereas PET was the main driver (55%) in the remaining 14% of the basin. However, changes in PET contributed more than PRE to drought variation, i.e., long-term SPEI trends, in about ∼ 60% of the area. And effects of PET increased during severer droughts due to the intensive interaction between soil moisture and atmospheric water demand in highly arid conditions. Physically, droughts were closely related to several ocean signals, such as the Multivariate ENSO Index (MEI), the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation index (AMO), and the Arctic Oscillation index (AO), at different time scales. Understandings of drought dynamics, their physical mechanisms, and the effects of PRE and PET on droughts of varying severity are essential for water resource management, especially in arid regions.

Spatiotemporal patterns of future meteorological drought in the Yellow River Basin based on SPEI under RCP scenarios

PurposeThe purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway (RCP) scenarios.Design/methodology/approachDelta method is used to process the future climate data of the global climate models, then analyzed the spatiotemporal variation trend of drought in the Yellow River Basin based on standardized precipitation evaporation index (SPEI) under four RCP scenarios.FindingsThis research was funded by the National Natural Science Foundation of China (41901239), Soft Science Research Project of Henan Province (212400410077, 192400410085), the National Key Research and Development Program of China (2016YFA0602703), China Postdoctoral Science Foundation (2018M640670) and the special fund of top talents in Henan Agricultural University (30501031).Originality/valueThis study can provide support for future meteorological drought management and prevention in the Yellow River Basin and provide a theoretical basis for water resources management.

Analysis of spatiotemporal variations of drought and its correlations with remote sensing-based indices via wavelet analysis and clustering methods

Abstract Beside in situ observations, satellite-based products can provide an ideal data source for spatiotemporal monitoring of drought. In this study, the spatiotemporal pattern of drought was investigated for the northwest part of Iran using ground- and satellite-based datasets. First, the Standardized Precipitation Index series were calculated via precipitation data of 29 sites located in the selected area and the CPC Merged Analysis of Precipitation satellite. The Maximal Overlap Discrete Wavelet Transform (MODWT) was used for obtaining the temporal features of time series, and further decomposition was performed using Ensemble Empirical Mode Decomposition (EEMD) to have more stationary time series. Then, multiscale zoning was done based on subseries energy values via two clustering methods, namely the self-organizing map and K-means. The results showed that the MODWT–EEMD–K-means method successfully identified homogenous drought areas. On the other hand, correlation between the satellite sensor data (i.e. the Normalized Difference Vegetation Index, the Vegetation Condition Index, the Vegetation Healthy Index, and the Temperature Condition Index) was evaluated. The possible links between central stations of clusters and satellite-based indices were assessed via the wavelet coherence method. The results revealed that all applied satellite-based indices had significant statistical correlations with the ground-based drought index within a certain period.

Is Drought Increasing in Maine and Hurting Wild Blueberry Production?

A few severe drought events occurred in the Northeast (NE) USA in recent decades and caused significant economic losses, but the temporal pattern of drought incidents and their impacts on agricultural systems have not been well assessed. Here, we analyzed historical changes and patterns of drought using a drought index (standardized precipitation-evapotranspiration index (SPEI)), and assessed drought impacts on remotely sensed vegetation indices (enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI)) and production (yield) of the wild blueberry fields in Maine, USA. We also analyzed the impact of short- and long-term water conditions of the growing season on the wild blueberry vegetation condition and production. No significant changes in the SPEI were found in the past 71 years, despite a significant warming pattern. There was also a significant relationship between the relatively long-term SPEI and the vegetation indices (EVI and NDVI), but not the short-term SPEI (one year). This suggests that the crop vigor of wild blueberries is probably determined by water conditions over a relatively long term. There were also significant relationships between 1-year water conditions (SPEI) and yield for a non-irrigated field, and between 4-year-average SPEI and the yield of all fields in Maine. The vegetation indices (EVI and NDVI) are not good predictors of wild blueberry yield, possibly because wild blueberry yield does not only depend on crop vigor, but also on other important variables such as pollination. We also compared an irrigated and a non-irrigated wild blueberry field at the same location (Deblois, Maine) where we found that irrigation decoupled the relationship between the SPEI and NDVI or EVI.