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Meteorological Drought. Research Paper No. 45, 1965, 58 p.

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Palmer Drought Index, Original Article

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... La combinación de altas temperaturas y condiciones de sequía aumentan el riesgo de incendios (Westerling et al., 2006;Aldersley et al., 2011;Abatzoglou et al., 2017;Turco et al., 2017;Holden et al., 2018). Alrededor del mundo, diversas investigaciones han constatado la asociación entre sequías e incendios a partir del estudio de las variadas características del régimen de incendios y variables meteorológicas como el índice de severidad de sequía de Palmer (Palmer, 1965;Westerling et al., 2003;Keeley, 2004;Collins et al., 2006;Preisler y Westerling, 2006;Xiao y Zhuang, 2007;Littell et al., 2016;Abatzoglou et al., 2017). ...
... El índice de severidad de sequía de Palmer (PDSI, por sus siglas en inglés) se basa en un modelo físico de balance hídrico; usa tanto la precipitación como la temperatura del aire superficial como entrada, y toma en cuenta la condición precedente (Palmer, 1965;Keyantash y Dracup, 2002). Este índice sirve para evaluar los períodos secos y húmedos, la variabilidad mensual y la tendencia de las sequías en una serie histórica de años (Ravelo et al., 2014). ...
... Los datos de extremos hídricos fueron adquiridos del Centro de Relevamiento y Evaluación de Recursos Agrícolas y Naturales (CREAN). El PDSI (Palmer, 1965) se calcula con datos mensuales de la evapotranspiración potencial y la precipitación, junto con información sobre la capacidad de retención del agua de los suelos. Tiene en cuenta la humedad recibida (precipitación), así como la humedad almacenada en el suelo, de manera que representa la posible pérdida de humedad a causa del efecto de la evapotranspiración. ...
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The climate in the province of Córdoba has suitable conditions for the occurrence of fires annually. The impact of current drought and preceding humidity conditions on fire activity was analyzed and modeled for the main eco-regions of the center of the country by using the Palmer Drought Severity Index (PDSI). A statistically significant relationship was observed between fires and droughts for the same season, while preceding weather conditions played a relatively minor role, depending on the region. A fire frequency map for the period 2001-2020 was created from the MODIS burned area product MCD64A1.The mountain region was the most affected in terms of burned area and the fire frequency ranged from 1 to 6 times. Furthermore, the models presented here estimated a positive response of fire occurrence to higher humidity conditions in the previous year. The Bañados del Río Dulce region had the highest fire occurrence and frequency, with sites burned up to 11 times. The models presented for the individual eco-regions are robust enough for developing a seasonal forecasting system to support fire management strategies.
... 2006-2100) experiments (Taylor et al., 2012). The Palmer Drought Severity Index (PDSI; Palmer, 1965) is adopted here to quantify drought as it has been widely used for operational drought monitoring and is increasingly used in studies assessing drought 85 under climate change (Cook et al., 2014(Cook et al., , 2015Dai, 2011Dai, , 2012Dai et al., 2018;Lehner et al., 2017;Liu et al., 2018;Sheffield et al., 2012;Swann et al., 2016;Trenberth et al., 2013). To maintain consistency between the calculated PDSI and the CMIP5 models, we calculate PDSI using direct hydrologic outputs (i.e., P, E, Q, ΔS) from the CMIP5 models (PDSI_CMIP5; see Methods). ...
... To maintain consistency between the calculated PDSI and the CMIP5 models, we calculate PDSI using direct hydrologic outputs (i.e., P, E, Q, ΔS) from the CMIP5 models (PDSI_CMIP5; see Methods). This procedure minimizes the uncertainty in PDSI estimates caused by uncertainties in the hydrologic 90 simulations embedded in the original PDSI algorithm (Palmer, 1965). The original PDSI using reference crop Penman-Monteith EP (PDSI_PM-RC), as extensively used previously (e.g., Cook et al., 2014Cook et al., , 2015Liu et al., 2018), and is also presented for comparison (the right stream shown in Figure (2006-2100) experiments (Taylor et al., 2012). ...
... The Palmer Drought Severity Index (PDSI) was used to quantify drought (Palmer, 1965). To minimize the impact of initial conditions on PDSI estimates, the first 40 years (1861-1900) are used for model spin-up with the analyses focused on the 1901-2100 period. ...
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Abstract. Anthropogenic warming is reported to increase global drought for the 21st century when calculated using offline drought indices. However, this contradicts observations of greening and little systematic change in runoff over the past few decades and climate projections of future greening with slight increases in global runoff for the coming century. This calls into question the drought projections based on offline drought indices. To resolve this paradox, here we calculate a widely-used conventional drought index (i.e., the Palmer Drought Severity Index, PDSI) using direct outputs from 16 CMIP5 models (PDSI_CMIP5) such that the hydrologic consistency between PDSI_CMIP5 and CMIP5 models is maintained. Results show that the global PDSI_CMIP5 remains generally unchanged as climate warms, demonstrating that CMIP5 models do not actually project a general increase in PDSI drought (more reflecting soil moisture/agricultural drought) under future warming. Further analyses indicate that the projected increase in PDSI drought reported previously is primarily due to ignoring the vegetation response to elevated atmospheric CO<sub>2</sub> concentration ([CO<sub>2</sub>]) in the offline calculations. On one hand, elevated [CO<sub>2</sub>] directly reduces stomatal opening; on the other hand, elevated [CO<sub>2</sub>] increases air temperature and thus vapor pressure deficit, which also causes partial stomatal closure. Finally, we show that the overestimation of PDSI drought can be avoided by directly using the relevant climate model outputs or by accounting for the effect of CO<sub>2</sub> on evapotranspiration. Our findings refute the common warming leads to drying perception and highlight the importance of elevated CO<sub>2</sub> in controlling future terrestrial hydrologic changes through vegetation responses.
... These 16 CMIP5 models were selected as they output all variables, including runoff, that are needed for the analysis performed herein. The Palmer Drought Severity Index (PDSI; Palmer, 1965) is adopted here to quantify drought as it has been widely used for operational drought monitoring and is increasingly used in studies assessing drought under climate change (Cook et al., 2014(Cook et al., , 2015Dai, 2011Dai, , 2012Dai et al., 2018;Lehner et al., 2017;Liu et al., 2018;Sheffield et al., 2012;Swann et al., 2016;Trenberth et al., 2014). To maintain consistency between the calculated PDSI and the CMIP5 models, we first calculate PDSI using direct hydrologic outputs (i.e., P , E, Q, S) from the CMIP5 models (PDSI_CMIP5; corresponds to the center column in Fig. 1; also see the Data and methods section). ...
... The PDSI was used to quantify drought (Palmer, 1965). To minimize the impact of initial conditions on PDSI estimates, the first 40 years (1861-1900) are used for model spin-up with the analyses focused on the 1901-2100 period. ...
... While this parameter is inevitably subject to uncertainties, Sheffield et al. (2012) demonstrated that the PDSI calculation is insensitive to AWC inputs. Detailed descriptions of PDSI can be found in Palmer (1965). A drought event is identified with negative PDSI values, with a more negative PDSI indicating a more severe drought, whereas moist events are associated with positive PDSI values. ...
Article
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Anthropogenic warming has been projected to increase global drought for the 21st century when calculated using traditional offline drought indices. However, this contradicts observations of the overall global greening and little systematic change in runoff over the past few decades and climate projections of future greening with slight increases in global runoff for the coming century. This calls into question the drought projections based on traditional offline drought indices. Here we calculate a widely used traditional drought index (i.e., the Palmer Drought Severity Index, PDSI) using direct outputs from 16 Coupled Model Intercomparison Project Phase 5 (CMIP5) models (PDSI_CMIP5) such that the hydrologic consistency between PDSI_CMIP5 and CMIP5 models is maintained. We find that the PDSI_CMIP5-depicted drought increases (in terms of drought severity, frequency, and extent) are much smaller than that reported when PDSI is calculated using the traditional offline approach that has been widely used in previous drought assessments under climate change. Further analyses indicate that the overestimation of PDSI drought increases reported previously using the PDSI is primarily due to ignoring the vegetation response to elevated atmospheric CO2 concentration ([CO2]) in the traditional offline calculations. Finally, we show that the overestimation of drought using the traditional PDSI approach can be minimized by accounting for the effect of CO2 on evapotranspiration.
... There have been great scientific efforts in developing and using drought indices to assess the drought condition and impacts for better decision making. The Palmer Drought Severity Index (PDSI) (Palmer, 1965) and its variations: the Palmer Z index (Palmer, 1965), Palmer Hydrologic Drought Index (PHDI) (Palmer, 1965), and Palmer Modified Drought Index (PMDI) (Heddinghaus and Sabol, 1991) have been extensively used for drought monitoring and related operational water management decision making. The Standardized Precipitation Index (SPI) developed by McKee et al. (1993) is based on a standardized transformation of the historical probability of precipitation, showing some advantages over PDSI, such as simple calculation, spatially invariant in interpretation, and flexible time scale (Guttman, 1998(Guttman, , 1999. ...
... There have been great scientific efforts in developing and using drought indices to assess the drought condition and impacts for better decision making. The Palmer Drought Severity Index (PDSI) (Palmer, 1965) and its variations: the Palmer Z index (Palmer, 1965), Palmer Hydrologic Drought Index (PHDI) (Palmer, 1965), and Palmer Modified Drought Index (PMDI) (Heddinghaus and Sabol, 1991) have been extensively used for drought monitoring and related operational water management decision making. The Standardized Precipitation Index (SPI) developed by McKee et al. (1993) is based on a standardized transformation of the historical probability of precipitation, showing some advantages over PDSI, such as simple calculation, spatially invariant in interpretation, and flexible time scale (Guttman, 1998(Guttman, , 1999. ...
... There have been great scientific efforts in developing and using drought indices to assess the drought condition and impacts for better decision making. The Palmer Drought Severity Index (PDSI) (Palmer, 1965) and its variations: the Palmer Z index (Palmer, 1965), Palmer Hydrologic Drought Index (PHDI) (Palmer, 1965), and Palmer Modified Drought Index (PMDI) (Heddinghaus and Sabol, 1991) have been extensively used for drought monitoring and related operational water management decision making. The Standardized Precipitation Index (SPI) developed by McKee et al. (1993) is based on a standardized transformation of the historical probability of precipitation, showing some advantages over PDSI, such as simple calculation, spatially invariant in interpretation, and flexible time scale (Guttman, 1998(Guttman, , 1999. ...
Article
Drought is a devastating natural hazard posing great threats to agriculture. Identifying the spatial pattern of agricultural sensitivity to drought can provide scientific information for decision-makers to prepare droughts, allocate resources, and mitigate impacts. Here, we use long-term state- and county-level crop data for the 10 major crops: corn grain, soybeans, hay, spring wheat, winter wheat, cotton, corn silage, sorghum, barley, and rice in the United States from 1950 to 2016. First, we perform a correlation analysis between crop yield anomalies and two drought indices (Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI)) to identify the sub-seasonal pattern of agricultural sensitivity to drought stress. SPEI performs better than SPI. For most crops, the sensitivity to drought increases in the early period, peaks at the critical months, and then declines. July is the most critical month for crop growth for most crops. Among all crops, soybean and corn grain are most sensitive to drought. Second, we develop an Agriculture Drought Sensitivity Index (ADSI) to quantitatively measure the sensitivity of agriculture to drought stress based on the statistical relationship between the ten major crops and SPEI. We demonstrate that there exists a very strong spatial correspondence between higher sensitivity to drought and the lower percentage of acres irrigated, and vice versa. Also, for those regions with limited irrigation, the sensitivity is higher in arid/semi-arid regions and lower in humid regions in summer. Third, given the importance of irrigation, an analysis of covariance (ANCOVA) shows that the irrigated crop yields have much higher long-run mean yields than non-irrigated crop yields. Fourth, to investigate how irrigation affects drought sensitivity, a panel data regression model shows that the responses of crop growth to drought are non-linear for all crops. Non-irrigated crops are more sensitive to droughts than the irrigated crops, particularly in severe drought conditions. This provides quantitative incentive to use irrigation as an important adaptation and coping strategy to mitigate the drought impacts on agriculture in the US.
... Palmer Drought Severity Index (PDSI) is another widely used drought indicator for monitoring hydrological droughts and has been increasingly used for assessing the impacts of climate change Cook et al., 2014;Dai, 2011bDai, , 2013Dai et al., 2018;Liu et al., 2018;Palmer, 1965;Sheffield et al., 2012). Originally created by W.C. Palmer in 1965, PDSI was calibrated with data for nine climatic regions in the U.S. and has been successfully applied to monitoring and analyzing droughts over the Great Plain regions, in the central U.S. (Guttman et al., 1992). ...
... In a subsequent study, Wells et al. (2004) improved the calibration scheme of PDSI and introduced a so-call selfcalibrated PDSI, which allows PDSI to be calibrated with local conditions and consequently greatly enhanced the suitability of the index for drought quantification in other regions beyond the Great Plains. Compared with other drought indices that are purely based on past statistics of particular climatic/hydrological variable/s of interest, the calculation of PDSI relies on all components of the surface water balance and accounts for the antecedent conditions (Dai, 2011a;Palmer, 1965). This implies a stronger physical basis of PDSI than other statistical drought indices in capturing hydrological variability and changes over land (Dai, 2011a). ...
... Two versions of PDSI are calculated, including (i) the traditional PDSI, where the water balance components are estimated based on the original PDSI two-layer bucket water balance model (PDSI original ), and (ii) PDSI with improved hydrological modeling, where the water balance components are directly obtained from the ISIMIP GHM outputs (PDSI ISIMIP ). For PDSI original , the self-calibrated PDSI algorithm as per Palmer (1965) and Wells et al. (2004) was used (see Wells et al., 2004 for algorithm details). For PDSI ISIMIP , direct hydrological outputs (i.e., Q, ET and soil moisture) from the ISIMIP GHMs were used to replace the simplified two-layer bucket model embedded in the original PDSI model and the normalization scheme of self-calibrated PDSI is adopted to calculate the PDSI index. ...
Article
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With the ongoing climate warming, changes in drought and the adverse effects on water resources, food production and ecosystem functioning have been key research topics of ever-increasing interest. The Palmer Drought Severity Index (PDSI) is among the most widely used indicators for drought monitoring and research. However, the two-layer bucket water balance model embedded in the original PDSI model has been criticized for being over-simplified to accurately quantify the surface water balance and therefore raising uncertainties in the subsequent PDSI estimates (PDSIoriginal). Here we improve the water balance calculations in the PDSI model by using direct hydrological outputs from physically-based, more sophisticated global hydrological models (GHMs) participated in the Inter-Sectoral Impact Model Inter-Comparison Project (ISIMIP). Validation results show that the estimated runoff (Q) and evapotranspiration (ET) from ISIMIP GHMs perform much better than those from the original PDSI two-layer bucket model in capturing the long-term trend and monthly variabilities of Q and ET, especially in cold regions and relatively dry areas, using observed Q (at 2191 catchments) and an independent satellite-based ET product (the Global Land Evaporation Amsterdam Model, GLEAM; over the entire terrestrial environment) as the reference. In addition, the new PDSI estimates with improved hydrological modeling (PDSIISIMIP) exhibit a significantly stronger correlation with observed Q than PDSIoriginal in nearly all studied catchments, suggesting that PDSIISIMIP is superior to PDSIoriginal in capturing hydrological droughts. We further compare the long-term PDSI trends and changes in drought using PDSIoriginal and PDSIISIMIP under both historical climate (1900-2005) and future climate change scenarios (2006-2099). We find that PDSIoriginal and the PDSIoriginal-identified land areas under drought generally show a larger trend than those based on PDSIISIMIP. For future climate change scenarios, the PDSIoriginal-projected increasing trend of land proportion under drought is about two times larger than that assessed with PDSIISIMIP, implying that PDSIoriginal may largely overestimate future drought increases, as commonly done in existing studies. In this light, our approach of directly using hydrological outputs from physically-based, more sophisticated GHMs provide an effective, yet relatively simple approach to reduce uncertainties in PDSI estimates thereby achieving a better prediction of drought changes under warming.
... water conservation measures, drought-tolerant crops) (Ramezani et al., 2019). The performance of NBS needs to be assessed by estimating drought risks before and after implementing NBS, which is commonly measured based on indicators (Tables S3 and S4), for example, the Palmer Drought Severity Index (PDSI) (Palmer, 1965) or the Standardized Precipitation Index (SPI) (McKee et al., 1993), among others (Heim Jr, 2002;Mishra and Singh, 2010). PDSI estimates soil water demand and supply using a water balance formula and only precipitation and temperature data to reproduce soil moisture fluctuations. ...
... It goes then one step forward in characterizing drought impacts, compared to the SPI precipitation anomaly detection. However, water balance estimates require the input of an additional meteorological parameter, which is the air temperature (Palmer, 1965). Again, this additional requirement was a difficulty for its application in poorly gauged areas, which has been largely overcome Meta-analysis of data from sixty-nine field measurements in coastal habitats globally. ...
Article
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To bring to fruition the capability of nature-based solutions (NBS) in mitigating hydro-meteorological risks (HMRs) and facilitate their widespread uptake require a consolidated knowledge-base related to their monitoring methods, efficiency, functioning and the ecosystem services they provide. We attempt to fill this knowledge gap by reviewing and compiling the existing scientific literature on methods, including ground-based measurements (e.g. gauging stations, wireless sensor network) and remote sensing observations (e.g. from topographic LiDAR, multispectral and radar sensors) that have been used and/or can be relevant to monitor the performance of NBS against five HMRs: floods, droughts, heatwaves, landslides, and storm surges and coastal erosion. These can allow the mapping of the risks and impacts of the specific hydro-meteorological events. We found that the selection and application of monitoring methods mostly rely on the particular NBS being monitored, resource availability (e.g. time, budget, space) and type of HMRs. No standalone method currently exists that can allow monitoring the performance of NBS in its broadest view. However, equipments, tools and technologies developed for other purposes, such as for ground-based measurements and atmospheric observations, can be applied to accurately monitor the performance of NBS to mitigate HMRs. We also focused on the capabilities of passive and active remote sensing, pointing out their associated opportunities and difficulties for NBS monitoring application. We conclude that the advancement in airborne and satellite-based remote sensing technology has signified a leap in the systematic monitoring of NBS performance, as well as provided a robust way for the spatial and temporal comparison of NBS intervention versus its absence. This improved performance measurement can support the evaluation of existing uncertainty and scepticism in selecting NBS over the artificially built concrete structures or grey approaches by addressing the questions of performance precariousness. Remote sensing technical developments, however, take time to shift toward a state of operational readiness for monitoring the progress of NBS in place (e.g. green NBS growth rate, their changes and effectiveness through time). More research is required to develop a holistic approach, which could routinely and continually monitor the performance of NBS over a large scale of intervention. This performance evaluation could increase the ecological and socio-economic benefits of NBS, and also create high levels of their acceptance and confidence by overcoming potential scepticism of NBS implementations.
... Traditionally, the meteorological drought analysis is carried out using in-situ precipitation information (Zuo et al., 2019). Palmer Drought Severity Index (PDSI) (Palmer, 1965) is used as a meteorological drought index, and it measures the departure of the moisture supply based on the supply-and-demand concept of the water balance equation. The PDSI is calculated by accounting precipitation and temperature data, as well as the local available water content of the soil. ...
... The PDSI is calculated by accounting precipitation and temperature data, as well as the local available water content of the soil. Several limitations of PDSI (Palmer, 1965;Mishra and Singh, 2010) are addressed through self-calibrating PDSI(sPDSI) (Wells et al., 2004). There are limited studies that incorporated re Chawla et al. ...
Article
Water resources are critical to the sustainability of life on Earth. With a growing population and climate change, it is imperative to assess the security of these resources. Over the past five decades, satellite remote sensing has become indispensable in understanding the Earth and atmospheric processes. Satellite sensors have the capability of providing data at global scales, which is economical compared to the ground or airborne sensor acquisitions. The science community made significant advances over recent years with the help of satellite remote sensing. In view of these efforts, the current review aims to present a comprehensive review of the role of remote sensing in assessing water security. This review highlights the role of remote sensing applications to assess water quality, quantity, and hydroclimatic extreme events that play an important role in improving water security. Four water quality parameters, namely, chlorophyll-a, turbidity and Total Suspended Solids (TSS), Secchi Disk Depth (SDD), and Colored Dissolved Organic Matter (CDOM), are considered. Under water quantity assessment, we review three aspects, streamflow estimation, terrestrial water storage, and reservoir operations. Remote sensing applications in quantifying floods and droughts extremes are reviewed in this work. We present how satellite sensor information acquired from different spectral bands, including optical, thermal, and microwave ranges, along with gravity field measurements, have contributed towards the applications in the above areas. We also assess the role of physical models, empirical models, and data assimilation strategies, among others, in the above areas. Finally, possible future research pathways needed to address the issues faced by the science community are discussed. This work is the second of the two-part review series, wherein the first part deals with the applications of satellite remote sensing for agriculture management.
... Numerous drought indices have been developed to characterize various types of water availability conditions and determine the impact of climate on a variety of vegetation types; example include the Palmer Drought Severity Index (PDSI) (Palmer, 1965), Standardized Precipitation Index (SPI) (McKee et al., 1993) and SPEI. The PDSI, the most common drought index, is calculated based on a water balance model and related variables, such as precipitation, temperature, soil moisture and streamflow to evaluate the supply and demand of soil moisture on a weekly or monthly time scale (Palmer, 1965). ...
... Numerous drought indices have been developed to characterize various types of water availability conditions and determine the impact of climate on a variety of vegetation types; example include the Palmer Drought Severity Index (PDSI) (Palmer, 1965), Standardized Precipitation Index (SPI) (McKee et al., 1993) and SPEI. The PDSI, the most common drought index, is calculated based on a water balance model and related variables, such as precipitation, temperature, soil moisture and streamflow to evaluate the supply and demand of soil moisture on a weekly or monthly time scale (Palmer, 1965). The primary limitation of the PDSI is the relatively limited (single) time scale, strong influence of the calibration period, and spatial comparability problems (Wells et al., 2004). ...
Article
Vegetation is a crucial component of terrestrial ecosystems, and its changes are driven mainly by a combination of climate change and human activities. This paper aims to reveal the relationship between vegetation and climate change by using the normalized difference vegetation index (NDVI) and standardized precipitation evapo-transpiration index (SPEI), and to find the cause of vegetation change by performing residual analysis on the Loess Plateau during the period from 2000 to 2016. The results showed that the NDVI on the Loess Plateau exhibited an increase of 0.086 per decade, and an increasing trend was observed across 94.86% of the total area. The relationship between the NDVI and SPEI was mainly positive, and the correlation increased as the time scale of the SPEI lengthened, indicating that long-term water availability was the major climate factor affecting vegetation growth. Residual analysis indicated that climate change was responsible for 45.78% of NDVI variation, while human activities were responsible for 54.22%. In areas with degraded vegetation, the relative roles of climate change and human activities were 28.11% and 72.89%, respectively. In addition, the relative role of climate change increased with an increase in the time scales, implying that the long-term NDVI trend was more sensitive to climate change then the short-term trend. The results of this study are expected to enhance our understanding of vegetation changes under climate change and human activities and provide a scientific basis for future ecological restoration in arid regions.
... The 10th percentile of wettest and driest years in the rescaled reconstruction were tabulated for comparison with the instrumental record and used to calculate the extreme value capture (EVC) for pluvial and drought conditions independently to identify potential bias in the reconstruction (McCarroll et al., 2015). Drought frequency was examined in the context of categories described by Palmer (1965): moderate (PMDI À2.0 to À2.9), severe (PMDI À3.0 to À3.9), and extreme (PMDI À4.0), where "[PMDI] of À4.0 spells economic disaster in any region in which the established economy is significantly dependent on the vagaries of weather for its moisture supply" (Palmer, 1965: 45). Pluvials were interpreted with respect to the comparable categories of moderate (PMDI 2.0 to 2.9), severe (PMDI 3.0 to 3.9), and extreme (PMDI ! ...
... The Years are classified as moderate (PMDI +2.0 to 2.9), severe (PMDI +3.0 to 3.9), and extreme (PMDI ! 4.0 or -4.0) (Palmer, 1965). Driftless Oaks reconstruction and LBDA exhibited stronger correlations during the 1950s through the 1970s, while the LBDA was the superior time series after that period because it directly incorporated instrumental measurements ( Figure 10a). ...
Article
New and updated multi-century tree-ring chronologies from living oak trees, remnants, and archeological beams from across the Driftless Area of southwest Wisconsin and northeast Iowa, USA, were developed to fill a spatial gap in the network of available tree-ring chronologies. We produced a robust 303-year summer drought reconstruction (June–August Palmer’s Modified Drought Index (PMDI): r ² = 0.45) that identified clusters of extreme droughts and pluvials (PMDI ≤ –4.0 or ≥ 4.0) in the early 1700s and more even distributions of drought conditions, with the exception of the post 1930s period when drought became relatively infrequent. Compared to the Living Blended Drought Atlas (LBDA) and the North American Drought Atlas (NADA), our reconstruction more accurately represented moderate moisture conditions across the Driftless Area, the NADA and LBDA more closely represented extreme pluvials, and our reconstruction and the LBDA better represented extreme drought years. The three reconstructions largely captured the same high-frequency variability in drought conditions and differed most at low frequencies. Significant correlations were identified between our reconstruction and corn ( r = 0.30, n = 91, p = 0.002) and soybean ( r = 0.25, n = 81, p = 0.012) yields, with the strength of the correlations increasing over recent decades suggesting a tighter coupling of interannual climate variability and crop productivity in the region. Superposed epoch analyses indicated significantly wetter conditions in the Driftless Area two years after major volcanic eruptions. In the context of long-term climatic variability, the Driftless Oaks drought reconstruction demonstrated that drought and pluvial conditions more extreme than those experienced during the instrumental record have occurred in the past.
... Droughts are a potentially expensive hazard, with significant and widespread impacts that affect many economic and social sectors. To monitor drought and to assess its impact, several drought indices have been developed (Palmer, 1965;Tarpley et al., 1984;McKee et al., 1993;Wu et al., 2001;Lyon, 2004;Narasimhan and Srinivasan, 2005;Nalbantis and Tsakiris, 2008;Vicente-Serrano and Lopez-Moreno, 2010;Anderson et al., 2011;Woli et al., 2012;Hao and AghaKouchak, 2013;Beguería et al., 2014). The standardized precipitation index (SPI) was developed by Thomas B. McKee in 1993(McKee et al., 1993, and in 2009 the WMO recommended that the SPI, which is calculated only from precipitation, should be the main meteorological drought index used to monitor the evolution of drought conditions (Hayes et al., 2011). ...
... Another widely used index is the weighted average of the precipitation index (WAP) (Lu, 2009), which has been shown to perform better than the SPI, on which it is based, as it is more flexible and can be applied over different timescales (Lu et al., 2014). The Palmer drought severity index (PDSI) was originally developed for North American conditions by the U.S. Weather Bureau in 1965 (Palmer, 1965;Alley, 1984) and is one of the most widely used drought indices worldwide. The standardized precipitation and evapotranspiration index (SPEI) takes into account both precipitation and potential evapotranspiration, so that, unlike the SPI (on which it is based), it captures the impact of increasing temperatures on water demand (Vicente-Serrano and Lopez-Moreno, 2010). ...
Article
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Maize is one of China's most important crops and is profoundly sensitive to drought. Using weather and county‐level maize yield data, the drought risk for maize in China was estimated for the period 1971–2010. The results show that drought risk has increased in China over the last 40 years, and that areas experiencing moderate to high drought risk have expanded, particularly in Northeast China. The main reasons for the observed changes are increased drought hazard associated with climate change, and increased exposure of maize to drought due to an expanded production area. Drought risk over all of China increased by 55% in the 2000s compared to the 1970s. While around 93% of the increase in drought risk in the maize production regions is due to increased drought exposure, 7% is attributable to climate change. In Northeast China alone, drought risk increased by 129% from the 1970s to the 2000s, which is the sum of an 86% increase caused by greater drought exposure, associated with expansion of the production area, and a 14% increase driven by climate change. The results indicate that the drought hazard has increased by around 13%, and drought risk has increased by 110% for each 1°C rise in annual mean temperature in Northeast China over the past 40 years. Maize yield losses have increased by around 4% per 1°C increase in annual mean temperature in this region. The sensitivity of maize to drought means that climate change is likely to have significant negative impact on future maize productivity, and China's export and import of maize is likely to be affected. The drought risk had increased by 55% in 2000s compared to the 1970s for the whole China. 7% of the increased drought risk in the maize production regions was caused by climate change. Maize yield loss rate amounted to 19.4% for county‐level yield in drought years during 2001–2010, and it increased by 4.0% per 1°C warming in Northeast China. The increasing drought risk of maize from 1970s to 2000s in China.
... 干旱指数目前广泛使用的有十几种, 影响力比较 大的包括1965年Palmer [30] 创建的PDSI指数、1993年 ...
... McKee等人 [31] 提出的SPI指数, 以及2010年Vicente-Ser-rano等人 [29] 提出的SPEI指数. PDSI指数是一种物理化 的干旱指数, 基于计算两层土壤水平衡状况, 与SPEI指 数、SPI指数这类统计干旱指数不同, Palmer [30] 提出了 气候适宜态(climatically appropriate for existing conditions)的概念. 标准化降雨指数SPI由降雨在不同时间尺 度上的累计和计算而来 [31] . ...
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In the summer and autumn of 2019, the extreme drought in the middle and lower reaches of the Yangtze River lasted for half a year, which had a serious impact on local agricultural production and ecological environment. At present, the estimation of drought degree mainly depends on the monitoring of precipitation, evapotranspiration, runoff and soil moisture. The GRACE/GRACE-FO gravity satellite captures and captures global changes in the Earth's gravity field, Collect information on changes in surface water, soil moisture and groundwater storage to track drought events on a global scale. Although great achievements have been made in observing global and regional land water storage changes using GRACE and GRACE-FO satellites, there are still few studies on monitoring drought using gravity satellites. Therefore, based on GRACE/GRACE-FOM Based on satellite observation data, the drought intensity and its spatial and temporal distribution in the middle and lower reaches of the Yangtze River in the summer and autumn of 2019 were studied by estimating GRACE-DSI. The results showed that: (1) GRACE-DSI well reflected the occurrence and development of persistent drought in the middle and lower reaches of the Yangtze River in the summer and autumn of 2019, and the extreme drought area was located in Lake North-east, northern Jiangxi, southern Anhui and other regions; (2) The regional average GRACE-DSI index of Hubei, Jiangxi, Anhui and Hunan provinces is in the best agreement with the 6-month SPEI-Z time series, and the correlation is 0.84, which indicates that GRACE-DSI can reflect the long-term accumulation effect of drought; (3) Passing ratio Compared with the monitoring of two extreme drought events in the middle and lower reaches of the Yangtze River in spring and summer of 2011 and in summer and autumn of 2019, it shows that GRACE-FO has the same drought monitoring capability as the two groups of gravity satellites before and after GRACE. In the future, with the continuous improvement of the spatial and temporal resolution of gravity satellite observations, GRACE-DSI will be able to be more accurate, faster and more accurate. Rapid detection of hydrological extreme drought events
... Meteorological drought occurs rapidly, while hydrological drought occurs after a meteorological drought (Wilhite 2000). Drought indices such as PDSI (Palmer 1965), standardized evapotranspiration index (Vicente-Serrano et al. 2010) and standardized precipitation index (Mckee et al. 1993) are used extensively for monitoring the meteorological droughts over the world. Sims et al. (2002) studied the relationship between SPI with the soil moisture, which can determine the available water for plants and agriculture. ...
... The SPEI is presented by Vicente-serrano et al. (2011) and it has been used in numerous studies; also calculation method involves the equilibrium of the climate and considers the role of the temperature in the drought evaluation. Previously, the palmer drought severity index (PDSI) uses the readily available temperature and precipitation data to estimate relative dryness (Palmer 1965). It is a standardized index that spans − 10 (dry)-+ 10 (wet) (Vicente-serrano et al. 2010). ...
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With respect to the necessity of comprehensive studies on drought and also high damages that caused by drought, this research studied the meteorological and hydrological droughts. In this study, Lighvan, Navroud and Seqez basins with different climates were selected. We used monthly data of stream flow, precipitation and evaporation from 1992 to 2016 for the study of drought phenomena. The aim at this study is to analyze the SPI and SPEI for determination of dry and wet meteorological periods and use of the SSI for the exploration of hydrological drought. The analysis of drought characteristics such as intensity and duration in three areas with different climates shows that the climate change has a major impact on the characteristics of the droughts. The relations between the duration and severity of drought have been more accurate in the period of 9 months in the Navroud watershed basin. The most significant events are SPI-9 with the duration of 57 months and the severity of 34.7, SPEI-9 with the duration of 34 months and the severity of 28.09 and SSI-9 with the duration of 41 months and the severity of 30.2. According to the obtained equations in different time periods, it was resulted that the highest accuracy was observed in the relationship between the meteorological and hydrological drought characteristics in the watershed basin of Seqez for a period of 6 months. The results show that in all three basins, the correlation between the meteorological and hydrological drought is significant at the level of 99%. Results show that hydrological and meteorological droughts in Navroud and Lighvan basins have a significant correlation with 48-month periods and in the Seqez basin with 12- and 24-month periods, and the relations between hydrological droughts and meteorological droughts were obtained using the nonlinear linear models (polynomial, exponential and logarithmic). The good R ² between the duration and severity of SPI-9 and SSI-9 is 0.8 and 0.92, respectively, for polynomial equations. The maximum determination coefficient of duration and severity of SPEI-9 and SSI-9 is 0.72 and 0.82, respectively, using polynomial equation. The application of several indices indicating different components of the hydrological cycle integrates many factors that affect and trigger droughts, and thus can help in providing a wider realization of the characteristics of droughts on various water sections.
... Our compilation of tree-ring based hydroclimate reconstructions, extending back to 1000 CE, includes 24 reconstructions of precipitation, 11 reconstructions of streamflow, 6 reconstructions of the Palmer Drought Severity Index (PDSI; Palmer, 1965;van der Schrier et al., 2011), 3 reconstructions of moisture availability/balance, 1 reconstruction of the Standardized Precipitation Index (SPI; McKee et al., 1993), and 1 reconstruction of Palmer Hydrological Drought Index (PHDI) (Karl, 1986). Precipitation is the most easily available metric as it is directly derived from meteorological station data, although it does not fully reflect the complex hydrological systems. ...
... PDSI integrates precipitation and temperature to estimate relative dryness ranging from À10 (very dry) to þ10 (very wet) (Palmer, 1965;Dai et al., 2004;Wells et al., 2004;van der Schrier et al., 2011). It tracks long-term changes in physiological drought, relative to the mean conditions in a given region, as it combines a physical water balance model with temperature and thus considers potential evapotranspiration (Hobbins et al., 2008). ...
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To place recent hydroclimate changes, including drought occurrences, in a long-term historical context, tree-ring records serve as an important natural archive. Here, we evaluate 46 millennium-long tree-ring based hydroclimate reconstructions for their Data Homogeneity, Sample Replication, Growth Coherence, Chronology Development, and Climate Signal based on criteria published by Esper et al. (2016) to assess tree-ring based temperature reconstructions. The compilation of 46 individually calibrated site reconstructions includes 37 different tree species and stem from North America (n = 29), Asia (n = 10); Europe (n = 5), northern Africa (n = 1) and southern South America (n = 1). For each criterion, the individual reconstructions were ranked in four groups, and results showed that no reconstruction scores highest or lowest for all analyzed parameters. We find no geographical differences in the overall ranking, but reconstructions from arid and semi-arid environments tend to score highest. A strong and stable hydroclimate signal is found to be of greater importance than a long calibration period. The most challenging trade-off identified is between high continuous sample replications, as well as a well-mixed age class distribution over time, and a good internal growth coherence. Unlike temperature reconstructions, a high proportion of the hydroclimate reconstructions are produced using individual series detrending methods removing centennial-scale variability. By providing a quantitative and objective evaluation of all available tree-ring based hydroclimate reconstructions we hope to boost future improvements in the development of such records and provide practical guidance to secondary users of these reconstructions.
... Drought-a slow-evolving phenomenon-is among the costliest natural disasters 27 , directly affecting water resources, agriculture, socioeconomic development and ecosystem health and often linked with armed conflicts 28 . Substantial literature exists on the study of droughts using indices such as the standardized precipitation index (SPI) 29 , Palmer drought severity index 30 , soil moisture drought index (SMI) 31,32 and standardized runoff index (SRI) 33 . These conventional indices have been used in monitoring and projecting 32,34 meteorological, agricultural and hydrological droughts 35 . ...
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Terrestrial water storage (TWS) modulates the hydrological cycle and is a key determinant of water availability and an indicator of drought. While historical TWS variations have been increasingly studied, future changes in TWS and the linkages to droughts remain unexamined. Here, using ensemble hydrological simulations, we show that climate change could reduce TWS in many regions, especially those in the Southern Hemisphere. Strong inter-ensemble agreement indicates high confidence in the projected changes that are driven primarily by climate forcing rather than land and water management activities. Declines in TWS translate to increases in future droughts. By the late twenty-first century, the global land area and population in extreme-to-exceptional TWS drought could more than double, each increasing from 3% during 1976–2005 to 7% and 8%, respectively. Our findings highlight the importance of climate change mitigation to avoid adverse TWS impacts and increased droughts, and the need for improved water resource management and adaptation. Projections of terrestrial water storage (TWS)—the sum of all continental water—are key to water resource and drought estimates. A hydrological model ensemble predicts climate warming will more than double the land area and population exposed to extreme TWS drought by the late twenty-first century.
... Drought can be effectively monitored using drought indices integrated with weather factors such as rainfall, temperature and evapotranspiration. The most frequently used drought indices include the Palmer Drought Severity Index (PDSI) [10], Percent of Normal Precipitation, deciles [11], SPI (Standardized Precipitation Index) [12] and the Standardized Precipitation Evapotranspiration Index (SPEI) [13]. Among these, the SPI only uses precipitation as input and can be obtained for flexible time scales that can be used to monitor meteorological, agricultural or hydrological drought depending on a user's interests [2,14]. ...
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Drought is the costliest disaster around the world and in China as well. Northeastern China is one of China’s most important major grain producing areas. Frequent droughts have harmed the agriculture of this region and further threatened national food security. Therefore, the timely and effective monitoring of drought is extremely important. In this study, the passive microwave remote sensing soil moisture data, i.e., the SMOS soil moisture (SMOS-SM) product, was compared to several in situ meteorological indices through Pearson correlation analysis to assess the performance of SMOS-SM in monitoring drought in northeastern China. Then, maps based on SMOS-SM and in situ indices were created for July from 2010 to 2015 to identify the spatial pattern of drought distributions. Our results showed that the SMOS-SM product had relatively high correlation with in situ indices, especially SPI and SPEI values of a nine-month scale for the growing season. The drought patterns shown on maps generated from SPI-9, SPEI-9 and sc-PDSI were also successfully captured using the SMOS-SM product. We found that the SMOS-SM product effectively monitored drought patterns in northeastern China, and this capacity would be enhanced when field capacity information became available.
... In order to understand drought, which is considered to be one of the most severe natural disasters, many drought indices are commonly used to quantify and assess drought characteristics, such as the Precipitation Anomaly (PA), Composite Index (CI), Aridity Index (AI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), and Standardized Precipitation Evapotranspiration Index (SPEI) [36][37][38][39][40][41]. Among these, SPEI can be used for multi time scales and take into account both precipitation and temperature in assessing drought conditions. ...
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The Horn of Africa (HOA) is one of the most drought-prone regions in the world with many arid and semiarid areas, and even some extremely arid areas. Primarily affected by the marine continental climate systems, this zone is really sensitive to global warming. Drought is the main type of natural disaster affecting this region, which triggers famine, civil conflict, and even deterioration of food security. The present study examined changes in droughts in the HOA during 1979–2019 based on Standardized Precipitation Evapotranspiration Index (SPEI). Results show that frequency, duration, and intensity of droughts exhibited an increasing trend over the past decades. Moreover, in October to December (called locate “short rains”) 2016 and March to May (called locate “long rains”) 2017, the HOA experienced the most severe drought. Based on Generalized Extreme Value (GEV) fitting, the 2016/2017 SPEI index corresponds to a drought that occurs every 250 years in the observational records. However, considering the precipitation in short rains of 2016 (long rains of 2017) was only 27.1% (11.8%) less than normal, it is hard to explain the formation of this extreme drought only from precipitation anomalies. Further statistical result shows that the evaporation in 2016/2017 corresponds to a 1-in-131 years event in the observed records. The abnormally high temperature (1.02 °C higher than normal) as well as the greatest potential evaporation since 1979 are the more important causes for the formation of drought. Thus, the extreme drought in 2016/2017, probably caused by the combined effect of dry condition and high temperature simultaneously, and the latter, played a leading role. In other words, droughts can be exacerbated by the co-occurrence of extreme high temperature. With continuous warming caused by anthropogenic activities in the next decades, the Horn of Africa may be a hotspot of the compound droughts and, therefore, it is especially important to considering the combined impacts from less precipitation and high temperature when predicting the future drought trend and making adaptation measures.
... Thus, there is no one universal drought index that can be used to satisfy all needs of researchers; after all, different drought indexes are only suitable for specific drought types. To precisely and visually identify drought occurrence and magnitude, many quantitative definitions of drought indexes have been proposed (Palmer, 1965;Bhalme and Mooley, 1980;McKee et al., 1993). In this study, the SPI and SRI were used to assess the risk of meteorological and hydrological droughts, respectively. ...
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China, with its fragile environment and ecosystems, is vulnerable to climate change. Continuous changes in climatic conditions have altered precipitation patterns in most regions of China. Droughts become more frequent and severe in the Xi River basin in South China. It is expected that rapid urbanization and climate change will continue to aggravate water stress in this region. There is an urgent need to develop sustainable water management strategies in face of growing water demand and changing water availability. Projection of future climate change impacts on drought conditions has thus become imperative to support improved decision-making in sustainable water management. In this study, we assessed the risk of extreme droughts under future climate projections in the Xi River basin. The variable infiltration capacity (VIC) model was applied to simulate the hydrological processes of the basin under a multitude of future climate scenarios from CMIP5. Based on the precipitation and runoff series obtained from the VIC model, a comprehensive analysis with respect to the major characteristics of meteorological and hydrological droughts had been carried out. This study is of practical and theoretical importance to both policymakers and scholars. First, this study may be a readily available reference work for policymakers when taking consideration of building drought mitigation plans into future water management practices. Second, the findings in this study may provide some valuable insights into the inherent connection between climatic and hydrological changes under a changing climate. Recognition of the connection and interrelation may contribute to the improvement of climatic and hydrological models in practices.
... Rainfall data required for the study were collected from India Meteorological Department (IMD) and Indian Water Portal for a period of 115 years for all 8 districts under 2 CACZs of Odisha. Palmer, 1965), the Rainfall Anomaly Index (RAI; Van Rooy, 1965), the Rainfall deciles (Gibbs and Maher, 1967), the National Rainfall Index (RI; Gommes and Petrassi, 1994), and the Standardized Precipitation Index (SPI; McKee et al., 1993). Among these indices, SPI is widely used for assessment of meteorological drought in many countries of the world. ...
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Drought is a recurring phenomenon in Indian agriculture. Every year, vast amount of crop areas are affected by drought in most parts of India causing heavy economic loss to the country. Drought forecasting and its mitigation measures are very important for boosting agricultural production, especially in rainfed areas. In this paper standardized precipitation index (SPI) was used to assess meteorological drought for 8 coastal districts coming under two coastal agro-climatic zones (CACZs) of Odisha. Monthly rainfall data of 115 years (1901-2015) for all 8 districts of Odisha were analyzed using SPI on 1, 3, 6, 9, and 12-month time scale. Results indicate that mild drought events have the highest frequencies of occurrence followed by moderate drought events for all time scales under analysis for different CACZs. Severe and extreme drought frequencies are comparatively lesser than mild and moderate drought frequencies. SPI analysis considering all the time scales shows that the frequency of occurrence of mild, moderate, severe and extreme droughts varies from 32.0% to 42.5%, 6.16% to 11.2%, 1.88% to 5.22% and 1.08% to 3.50%, respectively across all the districts in CACZs of Odisha. It was observed that 7 out of 8 districts (except Puri) had more number of drought years varying from 59 to 63 years (out of 115 years) in June, whereas all the 8 districts had more number of wet years in August varying from 59 to 67 years. The excess rainwater in August should be harvested for use in crops in subsequent months.
... Wildfire was simulated using Base Fire (v3.1 Scheller and Domingo, 2017), calibrated against records of wildfires in the region compiled by the Wisconsin Department of Natural Resources (Miranda et al., 2012) using the RCP 2.6 climate projection. The probability of fire ignitions was modified for the other two climate scenarios after year 2050 compared to RCP 2.6 and in inverse proportion to the (modest) change in the average Palmer Drought Severity Index (PDSI, Palmer, 1965), estimated from temperature and precipitation values in the climate projections. Cohort damage caused by microburst wind events was simulated using Base Wind (v2.2 Scheller and Domingo, 2011), parameterized based on data in Rich et al. (2007). ...
Article
Forest managers have been wrestling with questions of how best to prepare today’s forests for a future climate that may be quite different from the climate under which they were established. We used the LANDIS forest landscape model to conduct a factorial simulation experiment to assess the landscape-wide effects of alternative cutting and planting practices in northern Wisconsin (USA) under three climate change scenarios simulated for 300 years to allow demographic legacies to be overcome by the experimental treatments. Our objective was to assess the relative ability of actionable components of silvicultural strategies to maintain productivity and economical and ecological values of forests under future climates compared to a “business as usual” (BAU) silviculture scenario representing current sustained yield practices. We found that the general effect of climate change was to increase the biomass of all species (CO2 fertilization and increased growing season), although the most cold-adapted species eventually declined under warming climate scenarios. Two alternative silvicultural strategies produced clearly different outcomes compared to the BAU scenario. Total landscape tree biomass was least under BAU, reflecting its high biomass removal rates, and greatest under the most aggressive climate-adapted silviculture strategy coupled with a high CO2 climate scenario due to increased growth and relatively high removal rates. Harvested outputs responded to both climate and silvicultural strategy, with the high CO2 scenario reducing biomass available for harvesting compared to a moderate CO2 scenario, except under the aggressive climate-adapted strategy. Our study suggests that creative silvicultural practices can be developed (and tested) to maintain productive and ecologically healthy forests under future climate conditions.
... Drought is one of the deadliest natural calamities that affect mankind the most. Reference [1] defined drought as an interval of time generally in order of months or year during which the actual moisture supply in a place fall short of the climatically expected. Reference [2] defined drought as a natural hazard, that results from deficiency of precipitation from normal, which when extended over a considerable period of time, is unable to meet the demand for human activities and environment. ...
... The ET response to warming is a key component of these uncertainties. Earlier drought assessments with the Palmer Drought Severity Index 16 , a metric that relies on temperature-based potential ET, pointed to a substantial increase in aridity since the 1970s 17,18 . However, this was shown to be overestimated by using a modified version of the index that also accounts for available energy, air humidity and wind speed when computing potential ET 19 . ...
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Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1 °C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.
... totals of daily rainfall amounts from land-and GoM-sourced events were 334 averaged spatially using the seasonal total from all five stations to create a seasonal spa-335 tial average time series. This time series was correlated with gridded data sets of sum-336 mer average SSTs, PDSI(Palmer, 1965), and 850-mb heights(Figure 14, 15).337 Both sources show connections and teleconnections to these large-scale variables 338 through this analysis, though the patterns for each source differ. ...
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Summer rainfall in the southeast Prairie Pothole Region (SEPPR) is an important part of a vital wetland ecosystem that various species use as their habitat. We examine sources and pathways for summer rainfall moisture, large-scale features inuencing moisture delivery, and large-scale connections related to summer moisture using the HYSPLIT model. Analysis of HYSPLIT back trajectories shows that land is the primary moisture source for summer rainfall events indicating moisture recycling plays an important role in precipitation generation. The Great Plains Low Level Jet/Maya Express is the most prominent moisture pathway. It impacts events sourced by land and the Gulf of Mexico (GoM), the secondary moisture source. There is a coupling between land, atmosphere, and ocean conveyed by large-scale climate connections between rainfall events and sea surface temperature (SST), Palmer Drought Severity Index (PDSI), and 850-mb heights. Land-sourced events have a connection to the northern Paci c and northwest Atlantic Oceans, soil moisture over the central U.S., and low-pressure systems over the SEPPR. GoM-sourced events share the connection to soil moisture over the central U.S. but also show connections to SSTs in the north Pacific and Atlantic Oceans and the GoM, soil moisture in northern Mexico, and 850-mb heights in the eastern Pacific Ocean. Both types of events show connections to high 850-mb heights in the Caribbean which may reflect a connection to the Bermuda High. These insights into moisture sources and pathways can improve skill in SEPPR summer rainfall predictions and benefit natural resource managers in the region.
... Rainfall data required for the study were collected from India Meteorological Department (IMD) and Indian Water Portal for a period of 115 years for all 8 districts under 2 CACZs of Odisha. Palmer, 1965), the Rainfall Anomaly Index (RAI; Van Rooy, 1965), the Rainfall deciles (Gibbs and Maher, 1967), the National Rainfall Index (RI; Gommes and Petrassi, 1994), and the Standardized Precipitation Index (SPI; McKee et al., 1993). Among these indices, SPI is widely used for assessment of meteorological drought in many countries of the world. ...
Article
Full-text available
Drought is a recurring phenomenon in Indian agriculture. Every year, vast amount of crop areas are affected by drought in most parts of India causing heavy economic loss to the country. Drought forecasting and its mitigation measures are very important for boosting agricultural production, especially in rainfed areas. In this paper standardized precipitation index (SPI) was used to assess meteorological drought for 8 coastal districts coming under two coastal agro-climatic zones (CACZs) of Odisha. Monthly rainfall data of 115 years (1901-2015) for all 8 districts of Odisha were analyzed using SPI on 1, 3, 6, 9, and 12-month time scale. Results indicate that mild drought events have the highest frequencies of occurrence followed by moderate drought events for all time scales under analysis for different CACZs. Severe and extreme drought frequencies are comparatively lesser than mild and moderate drought frequencies. SPI analysis considering all the time scales shows that the frequency of occurrence of mild, moderate, severe and extreme droughts varies from 32.0% to 42.5%, 6.16% to 11.2%, 1.88% to 5.22% and 1.08% to 3.50%, respectively across all the districts in CACZs of Odisha. It was observed that 7 out of 8 districts (except Puri) had more number of drought years varying from 59 to 63 years (out of 115 years) in June, whereas all the 8 districts had more number of wet years in August varying from 59 to 67 years. The excess rainwater in August should be harvested for use in crops in subsequent months.
... The AED intensification during dry periods can increase levels of vegetation stress Hartmann et al., 2018;A.P. Williams et al., 2013), higher evaporation rates from soil (Teuling et al., 2013) and water bodies (Friedrich et al., 2018), and accelerate hydrological drought downstream. Some drought indices like the Palmer Drought Severity Index (PDSI) (Palmer, 1965), the Reconnaissance drought index (RDI) (Tsakiris et al., 2007), the Standardized Moisture Anomaly Index (SZI) (B. Zhang, AghaKouchak, et al., 2019;B. ...
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The standardized precipitation evapotranspiration index (SPEI) is one of the well-established drought metrics worldwide. It is simply computed using precipitation and atmospheric evaporative demand (AED) data. Although AED is considered a key driver of drought variability worldwide, it could have less impact on drought in specific regions and for particular times as a function of the magnitude of precipitation. Specifically, the influence of the AED might overestimate drought severity during both normal and humid periods, resulting in “false alarms” about drought impacts on physical and human environments. Here, we provided a global characterization of the sensitivity of the SPEI to changes of the AED. Results demonstrate that the contribution of AED to drought severity is largely impacted by the spatial and temporal variability of precipitation. Specifically, the impact of AED on drought severity was more pronounced during periods of low precipitation, compared to wet periods. Interestingly, drought severity in humid regions (as revealed by SPEI) also showed low sensitivity to AED under drier conditions. These results highlight the skill of SPEI in identifying the role of AED in drought evolution, especially in arid and semiarid regions whose climate is characterized typically by low precipitation. This advantage was also evident for humid environments, where SPEI did not overestimate drought severity due to the increased AED. These findings highlight the broader applicability of SPEI to accurately characterize drought severity worldwide.
... In this paper, we describe new multi-century tree-ring chronologies at four old-growth eastern hemlock forests in northern Michigan. With each of these datasets, we evaluate their suitability for recording regional climate parameters by comparing interannual ring growth with monthly temperature and Palmer Drought Severity Index (PDSI, a measure of dryness (Palmer 1965)). ...
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Availability of high-quality primary ecological datasets like tree-ring growth is critical to the progress of ecological sciences. The International Tree-Ring Databank (ITRDB) is the premier public archive for interannual records of tree-ring growth (i.e., "chronologies"); however, there is currently a dearth of available chronologies that extend into the 21st century. In Michigan, none of the available records for eastern hemlock extends past 1983. Unfortunately, this reduces the availability of these chronologies for study of recent ecological and climatological change or for their integration with new environmental measuring technologies. In this paper, we fill part of this gap for northern Michigan and examine how our datasets can inform long-term studies of ecology-climate interactions in the Midwest region. We present multi-century Tsuga canadensis (L.) Carrière (eastern hem-lock) tree-ring growth records for four sites in the Upper Peninsula of Michigan, U.S.A., covering the periods 1708-2015, 1754-2015, 1794-2015, and 1857-1995. We explore potential applications of these datasets by examining basic correlations between interannual growth on the one hand and regional temperature and Palmer Drought Severity Index (PDSI, an estimate of dryness) values on the other. At all four sites, growth is negatively correlated with previous summer and current spring temperature , while growth is positively correlated with previous summer PDSI at three of the four sites.
... The standardized precipitation index (SPI; McKee et al., 1993) and the standardized precipitation evapotranspiration index (SPEI; Vicente-Serrano et al., 2010) are often used for meteorological drought analysis. Soil moisture indicators such as the soil moisture-based drought severity index (Cammalleri et al., 2016) or the Palmer drought severity index (Palmer, 1965) characterize drought impacts in terms of plant water stress. Hydrological indicators, such as flow percentiles or the standardized run-off index (Shukla and Wood, 2008), are used to quantify the volume of water deficit in rivers and reservoirs (Hisdal et al., 2004;Cammalleri et al., 2017) or to monitor whether a required ecological flow or a minimum flow regime is maintained. ...
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Droughts have deep, widespread and underestimated impacts on societies, ecosystems, and economies. They incur costs that are borne disproportionately by the most vulnerable people. The extensive impacts of drought are consistently underreported even though they span large areas, cascade through systems and scales, and linger through time, affecting millions of people and contributing to food insecurity, poverty, and inequality. Climate change is increasing temperatures and disrupting rainfall patterns, increasing the frequency, severity, and duration of droughts in many regions across the globe. As we move towards a 2˚C warmer world, urgent action is required to better understand and more effectively manage drought risk to reduce the devastating toll on human lives and livelihoods, and ecosystems. The GAR Special Report on Drought 2021 explores the systemic nature of drought and its impacts on achievement of the Sendai Framework for Disaster Risk Reduction, the SDGs and human and ecosystems health and wellbeing.
... Our paleoclimate proxy is the Monsoon Asia Drought Atlas version 2 (MADA v2) (Cook, 2015), built upon the original MADA of Cook et al. (2010). The MADA is a gridded data set of the Palmer Drought Severity Index (PDSI) (Palmer, 1965) over the Asian monsoon region. Each grid cell contains an annual time series of the mean June-July-August PDSI, reconstructed from tree rings, and calibrated with the instrumental data set of Dai et al. (2004). ...
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Plain Language Summary Ten of the world's biggest rivers are located entirely within the Asian Monsoon region. They provide water, energy, and food for 1.7 billion people. To manage these critical resources, we need a better understanding of river discharge—how does it change over a long time? Are there common variation patterns among rivers? To answer these questions, we use information derived from tree rings to reconstruct average annual river discharge history at 62 gauges in 16 Asian countries. Our reconstruction reveals the riparian footprint of megadroughts and large volcanic eruptions over the past eight centuries. We show that simultaneous droughts and pluvials have often occurred at adjacent river basins in the past, because Asian rivers share common influences from the Pacific, Indian, and Atlantic Oceans. We also show how these oceanic teleconnections change over space and time. Our findings can inform big decisions made on water‐dependent infrastructure, thus benefiting the riparian people of the Asian Monsoon region.
... As the causes of drought are extremely complex, with many influential factors, drought events are often monitored and evaluated by establishing drought indicators . To objectively quantify the intensity, duration, and spatial range of drought, drought indices are calculated using climate variables for research, such as the Palmer Drought Severity Index (PDSI) (Palmer, 1965), Standardized Precipitation Index (SPI) (McKee et al., 1993), and Standardized Precipitation Evapotranspiration Index (SPEI) , etc. Among these, SPEI integrates the timescale variation of SPI and the sensitivity of PDSI to the change in evapotranspiration demand, and it has obvious advantages in dry and wet analysis under the background of warming (Potop et al., 2012). ...
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As one of the extreme climate events, the frequency and intensity of drought’s change significantly affect the growth of regional vegetation. Drought events have occurred frequently in the Vegetation Region of Northwest China (VRNWC) in the past 20 years, but the spatiotemporal characteristics of drought lack discussion in VRNWC. Additionally, the response mechanism of vegetation activities to drought is unclear. In this study, the Theil-Sen median trend and Mann-Kendall test correlation analysis were combined to analyse the spatiotemporal characteristics of drought in VRNWC based on the Standardized Precipitation Evapotranspiration Index (SPEI) from 2000 to 2019. Morlet wavelet and Hurst (H) exponent were used to analyse the future prediction of drought in VRNWC. The effects of drought on vegetation change were further analysed using the Normalized Difference Vegetation Index (NDVI). The results showed that from 2000 to 2019, the SPEI in VRNWC increased at the rate of 0.0113/ a, and the drought slowed down, mainly distributed in northeastern Shaanxi, southern Gansu, southern Qilian Mountains, and western Xinjiang. However, there was extreme drought in the northwest of the Tarim Basin in 2007 and severe drought in the northern Qaidam Basin in 2014. In the past 20 years, the occurrence frequency, duration and percentage of drought grade of slight drought, moderate drought, and severe drought showed a downward trend. The VRNWC gradually developed to a wetting trend, but the overall frequency of slight drought was the highest, and the frequency of extreme drought was the lowest, while severe drought was mainly concentrated in the Qinghai Plateau. The drought in VRNWC had a periodicity of about 8a. Further, SPEI_Hurst indicated that the drought in the study area will probably increase in the future. Drought in VRNWC significantly impacted vegetation, and 72.36% of the regional SPEI was positively correlated with the NDVI. This study provides a theoretical basis and data support for ecological management and future ecological restoration in vegetation regions.
... Since there is no absolute quantitative measure of drought, various drought indices have been developed and typically used to indicate one or two types of drought (Zargar et al., 2011). Drought indices can be categorized into two groups: one is station-based indices such as Palmer Drought Severity Index (Palmer, 1965) and the other is satellite-based indices using satellite data and products such as Vegetation Condition Index (Kogan, 1990) and Scaled Drought Condition Index (Rhee et al., 2010). Station-based drought indices have limited spatial coverage due to the sparse distribution of stations. ...
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Drought forecasting is crucial to minimize the damage to food security and water resources caused by drought. Satellite-based drought research has been conducted since 1980s, which includes drought monitoring, assessment, and prediction. Unlike numerous studies on drought monitoring and assessment for the past few decades, satellite-based drought forecasting has gained popularity in recent years. For successful drought forecasting, it is necessary to carefully identify the relationships between drought factors and drought conditions by drought type and lead time. This paper aims to provide an overview of recent research trends and challenges for satellite-based drought forecasts focusing on lead times. Based on the recent literature survey during the past decade, the satellite-based drought forecasting studies were divided into three groups by lead time (i.e., short-term, sub-seasonal, and seasonal) and reviewed with the characteristics of the predictors (i.e., drought factors) and predictands (i.e., drought indices). Then, three major challenges-difficulty in model generalization, model resolution and feature selection, and saturation of forecasting skill improvement-were discussed, which led to provide several future research directions of satellite-based drought forecasting.
... To evaluate risk and formulate of alleviation measures for droughts, it is necessary to identify the severity of drought events. Therefore, many drought indicators were developed in the past to describe the characteristics of different drought types (Palmer, 1965;Shafer and Dezman, 1982;McKee et al., 1993;Tsakiris and Vangelis, 2005;Nalbantis, 2008;Nalbantis and Tsakiris, 2009;Sharma and Panu, 2010;Bloomfield and Marchant, 2013;Mu et al., 2013;Liu et al., 2017). Table 1 compares the most commonly used drought indices. ...
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In recent years, Taiwan has been facing severe water shortages due to extreme drought. In addition, changes in rainfall patterns have resulted in an increasingly notable drought phenomenon, which affects the management and utilization of water resources. Therefore, this work examines basins in Central Taiwan. Long-term records from 13 rainfall and 17 groundwater stations were selected. The Standardized Precipitation Index (SPI) and Standardized Groundwater Level Index (SGI) were used to analyze the drought characteristics of this region. The rainfall and groundwater level data from basins in Central Taiwan were analyzed in this study. The results show that the year 2015 experienced extreme drought conditions due to a correlation with SPI and SGI signals. In addition, with regard to groundwater drought, more drought events occurred in the Da'an River basin; however, the duration and intensity of these events were relatively low, in contrast to those of the Wu River basin. Finally, the correlation between SPI and SGI was observed to vary in different basins, but a certain degree of correlation was observed in all basins. The results show that drought intensity increases with longer drought durations. Moreover, severe droughts caused by rainfall tend to occur at a greater frequency than those caused by groundwater.
... In the past decades, the use of monitoring technology and various indices have been proposed as methods for measuring dryness and wetness, and their advantages and drawbacks have been reviewed by Zhang and Zhou (2015). Examples of meteorological drought indices include the Precipitation Anomaly (PA), Composite Index (CI), Aridity Index (AI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), and Standardized Precipitation Evapotranspiration Index (SPEI) (Palmer, 1965;Hayes et al., 1999;McKee et al., 1993;Vicente-Serrano et al., 2010a. Compared to other indices, the SPEI has several advantages, including its consideration of the collective influence of both precipitation and potential evaporation, flexibility of multitime scales, and identification of more extreme events (Sun et al., 2016). ...
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Central Asia (CA) is one of the most drought-prone regions in the world with complex climate regimes, it is extremely vulnerable to water scarcity. Many studies on drought in CA, as a whole, have been carried out, whereas there is a lack of studies on the drying and wetting trends of different climatic zones within CA. In this study, CA was divided into three different climatic zones based on the Köppen climate classification method, precipitation climatology, and aridity index. These were the temperate continental (Df), dry arid desert (BW), and Mediterranean continental (Ds) climatic zones. The regional drying and wetting trends during the years 1961–2015 were investigated using the monthly gridded Standardized Precipitation Evapotranspiration Index (SPEI). The empirical orthogonal function (EOF) was applied to analyze spatial and temporal variation patterns. EOF mode 1 (EOF1) analysis found increasingly wet conditions throughout CA over the duration of the study, and EOF mode 2 (EOF2) analysis found a contrast between northern and southern CA: as Df became drier and BW and Ds became wetter. EOF mode 3 (EOF3) analysis found a western and eastern inverse phase distribution. The SPEI displayed a decreasing trend from 1961 to 1974 for CA as a whole, before increasing from 1975 to 2015, with a particularly significant increase over the first seven years of that period. On a regional scale, the BW and Ds zones experienced a wetting trend due to increased precipitation during 1961–2015, but the Df zone experienced a drying trend due to reduced evapotranspiration and an increasing temperature, particularly from 1961 to 1978. Thus, the spatio-temporal patterns in dryness and wetness across CA can be categorized according to climatic regions.
... Usually, the drought-prone areas are delineated based on rainfall intensity, rainfall periodicity, groundwater potential, and agricultural production [4]. The water balance technique is one such logical approach used for drought-prone area delineation [5]. Several drought indices such as Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Surface Water Supply Index (SWSI), Foley Drought Index (FDI), Effective Drought Index (EDI), Rainfall Deciles-based Drought Index (RDDI), China Z-Index (CZI) etc. have been developed to integrate various hydro-climatological parameters like rainfall, temperature, evapotranspiration, soil moisture, runoff, etc. for accurate identification of drought-affected/prone areas and drought severity [6]. ...
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Assessing spatial variability of drought-prone areas is important for disaster preparedness and impact management. This study applied state-of-the-art geographically weighted regression hybridized with kriging method (GWRKrig) to map the spatial variability of drought-prone areas in the northwest of Iran based on the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Rainfall and evapotranspiration data from 47 synoptic stations over 20 years were used to generate SPI and SPEI, and topographical (altitude) data were used for GWRKrig. The results obtained using GWRKrig were compared with that of standalone GWR, regression kriging (RegKrig), and ordinary kriging (Krig) methods. The GWRKrig method emerged as a promising tool for spatial interpolation of drought indices based on performance evaluation measures, namely, the root mean squared error (RMSE) and coefficient of determination (R2). The SPEI-based drought intensity interpolated via GWRKrig revealed relatively precise spatial variability of drought zones. The method proposed in this study would assist in the accurate delineation of drought-prone areas, which is the foremost venture in the planning hierarchy of drought management schemes and their implementation.
... Palmer [4] compiled drought definitions by many authors (e.g., [5][6][7][8][9][10][11]) and proposed a definition that drought is a phenomenon that depends on the effects of relatively prolonged and abnormal moisture deficiency. However, various definitions of drought existed in the early 1980s based on differences in region, needs, and disciplinary approach. ...
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South Asian countries have been experiencing frequent drought incidents recently, and due to this reason, many scientific studies have been carried out to explore drought in South Asia. In this context, we review scientific studies related to drought in South Asia. The study initially identifies the importance of drought-related studies and discusses drought types for South Asian regions. The representative examples of drought events, severity, frequency, and duration in South Asian countries are identified. The Standardized Precipitation Index (SPI) was mostly adopted in South Asian countries to quantify and monitor droughts. Nevertheless, the absence of drought quantification studies in Bhutan and the Maldives is of great concern. Future studies to generate a combined drought severity map for the South Asian region are required. Moreover, the drought prediction and projection in the regions is rarely studied. Furthermore, the teleconnection between drought and large-scale atmospheric circulations in the South Asia has not been discussed in detail in most of the scientific literature. Therefore, as a take-home message, there is an urgent need for scientific studies related to drought quantification for some regions in South Asia, prediction and projection of drought for an individual country (or as a region), and drought teleconnection to atmospheric circulation.
... Palmer [4] compiled drought definitions by many authors (e.g., [5][6][7][8][9][10][11]) and proposed a definition that drought is a phenomenon that depends on the effects of relatively prolonged and abnormal moisture deficiency. However, various definitions of drought existed in the early 1980s based on differences in region, needs, and disciplinary approach. ...
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South Asian countries experience frequent drought incidents recently, and due to this reason, many scientific studies were carried to explore the drought in South Asia. In this context, we review scientific studies related to drought in South Asia. The study initially identifies the importance of drought-related studies and discusses drought types for South Asian regions. The representative examples of drought events, severity, frequency, and duration in South Asian countries are identified. The Standardized Precipitation Index (SPI) was mostly adopted in South Asian countries to quantify and monitor droughts. Nevertheless, the absence of drought quantifi-cation studies in Bhutan and Maldives is of great concern. Future studies to generate a combined drought severity map for the South Asian region are required. Moreover, the drought prediction and projection in the regions is rarely studied. Further, the teleconnection between drought and large-scale atmospheric circulations in the South Asian area has not been discussed in detail in the most scientific literature. Therefore, as a take-home message, there is an urgent need for scientific studies related to drought quantification for some regions in South Asia, prediction and projection of drought for an individual country (or as a region), and drought teleconnection to atmospheric circulation.
... Desde la década de 1960 se han implementado diferentes índices de sequía, que presentan una serie de ventajas e inconvenientes bajo distintas condiciones climáticas (Mishra &y Singh, 2011;Marcos, 2001). Entre ellos se pueden destacar el Palmer Drouhgt Severity Index (PDSI) (Palmer, 1965), Standardized Precipitation Index (SPI) (Mckee et al., 1993) o Índice Estandarizado de Sequía Pluviométrica (IESP) (Pita,2000). Sin duda, el SPI es el más utilizado en el ámbito científico, debido a que únicamente requiere datos de precipitación, la simplicidad de su cálculo respecto a otros índices, y la comparabilidad entre unas regiones y otras al ser un índice adimensional (Santos et al., 2010;He et al., 2015). ...
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A partir de un total de 92 series de precipitación mensual de la base de datos de la Agencia Estatal de Meteorología (AEMET) se ha realizado un análisis exhaustivo de sequías en el marco espacial de la Demarcación Hidrográfica del Segura (DHS) y Mancomunidad de los Canales del Taibilla (MCT), organismos encargados de la planificación de los recursos hídricos, y del abastecimiento de agua potable, respectivamente, de gran parte del sureste de España. El objetivo principal de este estudio es la regionalización de los patrones temporales de sequía a partir del Standarized Precipitation Index (SPI), con escala de 12 meses (SPI12), para evaluar las sequías hidrológicas. El periodo seleccionado es 1968–2017. La regionalización se ha realizado a partir del Análisis de Componentes Principales (ACP), a través del cual se han obtenido 4 regiones homogéneas. A partir de estas regiones se ha identificado el porcentaje de área afectada por sequías de diferente severidad, y la frecuencia de ocurrencia de sequías (basado en el método Kernel Ocurrence Rate Estimation-KORE). Se observa un incremento de la frecuencia de ocurrencia de sequías y del área afectada por las mismas en prácticamente todas las regiones, lo que conlleva importantes repercusiones territoriales, sociales y económicas en un ámbito territorial semiárido que presenta un déficit hídrico destacado.
... recently evoked interest beyond the scientific community ( Leuzinger et al., 2005). The current common drought monitoring indices include the SPI (Standardized Precipitation Index), PDSI (Palmer Drought Severity Index), ISDI (Integrated Surface Drought Index), SPEI (Standardized Precipitation Evapotranspiration Index), TCI (Temperature Condition Index), VCI (Vegetation Condition Index) and the VHI (Vegetation Health Index) ( Rhee et al., 2010;Banimahd and Khalili, 2013;Wu et al., 2013;Hu et al., 2014); the SPEI ( Vicente-Serrano et al., 2010;Wang et al., 2014); the SPI ( McKee et al., 1993) and the PDSI ( Palmer, 1965) are the three most widely used drought indices. The results of using the SPI are comparable in space and time ( Guttman, 1998;Hayes et al., 1999), and their multi-scale characteristics can identify different types of droughts. ...
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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.
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Understanding how drivers of ecological disturbance operate across scales is important in an era of increasing disturbance activity. Severe and extensive Dendroctonus bark beetle outbreaks across western North America have left in their wake dominance by shade‐tolerant and commonly late‐seral trees such as subalpine fir (Abies lasiocarpa), which can foster resilience of forest cover. However, subalpine fir decline (SFD) is a poorly understood phenomenon that has killed trees across millions of hectares in western North America with unknown consequences for future forest resilience. How different factors (e.g., climate, topography, host‐tree characteristics, and abundance) govern SFD presence and severity across spatial scales from individual trees to a subcontinental scale has not been explored in a single framework. Here, we combine broad‐scale geospatial data on SFD occurrence, stand‐scale field data on SFD severity, and fine‐scale individual tree data on mortality to test the relative importance of factors related to SFD across spatial scales spanning >10 orders of magnitude (<1 m to >10 M hectares). At the broadest scale (subcontinental, ~25 M ha), annual areal extent of SFD over time increased sharply with antecedent drought. At regional‐ (~6 M ha) and stand‐ (0.1–0.25 ha) scales, the occurrence and severity of SFD were spatially associated with more mesic topographic positions and greater host‐tree abundance. Finally, at the individual tree‐ and tree‐neighborhood‐ (<1 m) scale, the probability of mortality increased for larger trees and trees closer to dead conspecific neighbors. The positive temporal association of SFD with drought at broad scales versus the positive spatial association of SFD with mesic sites at fine scales suggests strong importance of local biotic processes in mediating drought‐driven forest decline and highlights the need for understanding multi‐scale drivers of ecological disturbance.
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Drought is an obscure climatic state that has socioeconomic repercussions on power generation, agricultural production, forestry, tourism and construction. In this study, an Ensemble Empirical Mode Decomposition (EEMD) based Time Dependent Intrinsic Correlation (TDIC) analysis was conducted to assess the impacts of Indian Ocean Dipole(IOD) and El Niño-Southern Oscillation (ENSO) to drought events of Peninsular region in India. Standardized Precipitation Index (SPI) at three different time scales (SPI-3, SPI-6 and SPI-12) are considered for analysis. The teleconnections IOD and ENSO on the three indices are evaluated independently using TDIC method and the detection and attribution was made from the obtained correlation plots. From the detailed analysis, short term drought (SPI-3) is found to have better correlation with both IOD and ENSO. It is also interpreted that high frequency modes of SPI-3 have more association to IOD while low frequency modes show more correlation to ENSO. Thereby, IOD experiences a lagged influence on ENSO relation to rainfall. The IMF3 and IMF7 of SPI-12 also show positive association that can be added to existing data for efficient prediction of drought events. Similarly, for ENSO IMF1, IMF6 and IMF7 of SPI-6 and IMF6 and IMF7 of SPI-12 can also be used for determining the drought accurately.
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In this study, Standardized Precipitation Index (SPI) derived from parametric and nonparametric methods using 0.25∘ gridded rainfall data from 1901 to 2013 (113 years) generated by India Meteorological Department (IMD) was compared for understanding drought conditions over the Indian region. The parametric SPI was computed using a three-parameter Gamma distribution function, whereas nonparametric SPI was computed using Gringorten, Weibull, and Hazen plotting positions, on a 4-month cumulative rainfall data of June–September (SPI-4) representing the southwest monsoon season. Nonnormality is a major concern if equal-sized intervals are drawn for interpretation, and SPI being a normalized index wherein classes are standard deviations from normal, its impact on drought assessment needs to be understood. Accordingly, in our study, normality tests were performed using the Shapiro-Wilk method on SPI derived from both parametric and nonparametric methods. The SPI showed 100% of grid cells conforming to normality in the case of nonparametric methods, whereas in the case of parametric approach it was only 80%. The remaining 20% of nonnormality in parametric SPI is spread over montane, tropical wet, and semi-arid regions of India. Furthermore, differences in the estimation of dryness are observed in the range of 1.0 to 2.5% between nonparametric and parametric SPI for the drought years considered this study. The quantile analysis on all grid cells for the drought year 2002 showed an important fact that at 0.025 quantile only 2.6% of grid cells are in the extremely dry condition as per parametric SPI, whereas in the case of nonparametric SPI it is 6.9%. For the drought year 1939 in grid cells where normality is not followed in parametric SPI, Cohen’s kappa (κ = 0.15) under extreme dryness category indicates large disagreements between parametric and nonparametric SPI. The temporal analysis of Cohen’s kappa computed for each grid cell over drought years shows that in 22.5% of cases the drought category between nonparametric and parametric SPI is not in perfect agreement. Hence, the nonparametric SPI can better categorize the drought classes, representing well the extent of dryness and normality conditions, it is highly recommended for drought assessment over India.
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Groundwater is an essential part of the hydrological cycle. The ultimate source of the groundwater is precipitation that occurs over the surface of the earth. Stress condition in groundwater reflects the vulnerability of drought events. In areas with ample soil moisture and without irrigation facilities, groundwater abstraction eventually leads to a decrease in agricultural yield. For the assessment of groundwater fluctuations, hydrological drought indices play a significant role in drought conditions. In Upper Bhima sub-basin, maximum area is under scarcity zone and partly under assured rainfall zone (Western part) and partly in transition zone I & II (Western part) with average annual rainfall of 690 mm. In the present study, standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and standardized water level index (SWI) is used to assess meteorological and hydrological drought conditions respectively. As SWI reflects aquifer stress, it is also used to understand groundwater decline and recharge in the present study region. SPI and SPEI are estimated by using precipitation and temperature data for yearly aggregated time scale, while SWI is obtained by normalising groundwater level data. Precipitation and temperature data are obtained from gridded reanalysis data product of NCEP-CFSR (spatial resolution approx. 38 km) for the period of 2002-2014. Groundwater level data is obtained from Central Ground Water Board for the period of 2002-2016. Spatio-temporal map of SPI, SPEI and SWI has been generated. No direct linear relationship has been observed between SPI and SWI; and between rainfall and SWI over the region. Hence, topography, aquifer properties, soil type and lithology may affect groundwater fluctuation in the region.
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Naturally growing vegetation often suffers from the effects of drought. There exists a vast number of drought indices (DI’s) to assess the impact of drought on the growth of crops and naturally occurring vegetation. However, assessing the fitness of these indices for large areas with variable vegetation cover is often problematic because of the absence of adequate spatial information. In this study, we compared six DI’s to NDVI (the normalized difference vegetation index), a common indicator of vegetation occurrence and health based on satellite-acquired reflectance data. The study area covers an aridity gradient from forests to deserts along a 2,400-km-long section across the Inner Mongolia Autonomous Region of China. On an annual timescale, standardized precipitation index (SPI) was the most appropriate in assessing drought in steppes and deserts. On a seasonal timescale, the self-calibrated Palmer drought severity index (scPDSI) displayed the greatest sensitivity during the summer, but not during the other seasons. On a monthly timescale, scPDSI demonstrated the greatest sensitivity to the various vegetation zones (i.e., forests, steppes, and deserts) in June and July. Further analysis indicated that summer drought had a lag-effect on vegetation growth, which varied from one to six months according to the specific vegetation cover. The mixed response of DI’s to NDVI and the lag-effect in transitional vegetation on annual, seasonal, and monthly timescales were ascribed to differences in DI definition and the dominant plant species within the transitional cover. The current study has the potential to inform the drafting of selection criteria of DI’s for the study of drought-related impact on naturally growing vegetation at timescales from month to year.
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Beaver dams are gaining popularity as a low‐tech, low‐cost strategy to build climate resiliency at the landscape scale. They slow and store water that can be accessed by riparian vegetation during dry periods, effectively protecting riparian ecosystems from droughts. Whether or not this protection extends to wildfire has been discussed anecdotally but has not been examined in a scientific context. We used remotely sensed Normalized Difference Vegetation Index (NDVI) data to compare riparian vegetation greenness in areas with and without beaver damming during wildfire. We include data from five large wildfires of varying burn severity and dominant landcover settings in the western USA in our analysis. We found that beaver‐dammed riparian corridors are relatively unaffected by wildfire when compared to similar riparian corridors without beaver damming. On average, the decrease in NDVI during fire in areas without beaver is 3.05 times as large as it is in areas with beaver. However, plant greenness rebounded in the year after wildfire regardless of beaver activity. Thus, we conclude that while beaver activity does not necessarily play a role in riparian vegetation post‐fire resilience, it does play a significant role in riparian vegetation fire resistance and refugia creation.
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Long‐term ecosystem studies are valuable for understanding integrated ecosystem response to global changes in atmospheric deposition and climate. We examined trends for a 35‐year period (1982/83 to 2017/18) in concentrations of a range of solutes in precipitation and stream water from nine headwater catchments spanning elevation and surficial geology gradients at the Turkey Lakes Watershed in northeastern Ontario, Canada. Average annual water year (WY, October to September) concentrations in precipitation significantly declined over the period for sulphate (SO42−), nitrate (NO3−), and chloride (Cl−), while calcium (Ca2+) and potassium (K+) concentrations increased, resulting in a significant pH increase from 4.2 to 5.7. Trends in stream chemistry through time are generally consistent with expectations associated with acidification recovery. Concentration of many stream water solutes (SO42−, Cl−, calcium [Ca2+], magnesium [Mg2+], and NH4+ generally decreased, while others (silica [SiO2], and dissolved organic carbon [DOC]) generally increased. Increases were also observed for alkalinity (6 of 9 catchments), acid neutralizing capacity ([ANC]; 6 of 9 catchments) and pH (8 of 9 catchments), while conductivity declined (6 of 9 catchments). Variability in trends among catchments are associated with differences in surficial geology and wetland cover. While absolute solute concentrations were generally lower at bedrock dominated high‐elevation catchments compared to till dominated lower elevation catchments, the rate of change of concentration was often greater for high elevation catchments. This study confirms continued, but non‐linear stream chemistry recovery from acidification, particularly at the less buffered high and moderate elevation sites. The heterogeneity of responses among catchments highlights our incomplete understanding of the relative importance of different mechanisms influencing stream chemistry and the consequences for downstream ecosystems. This article is protected by copyright. All rights reserved.
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Drought has become a major challenge in many Sub-Saharan Africa countries. This study aimed to investigate the precipitation trends and drought incidents in the semi-closed Raya graben in Ethiopia. Monthly precipitation records of nine meteorological stations for the years 1980–2016 were studied. The spatio-temporal drought conditions were analysed using Man-Kendall and Standardized Precipitation Index (SPI) techniques. A decreasing trend of precipitation was observed during the spring season (March−May) (p < 0.01). Many meteorological drought years were identified since 1980, occurring at varying temporal frequencies. Similarly, agricultural drought was occurring continuously for 1−5 years at an interval of five years. Our results also showed major hydrological droughts that persisted for 2−4 years occurring at an interval of five years. Almost all stations experienced an average intensity of moderate and above drought conditions during their agricultural and hydrological drought periods. Drought risk increased with the growing frequency of extreme drought events occurring every 14 months. Spatially, the southern and eastern parts were found to be more vulnerable to frequent, intense and longer drought conditions as compared to the western graben escarpment. Therefore, building adaptive capacity to climate change and extreme events is recommended to reduce the consequences of drought incidents in the Raya graben and northern Ethiopia.
Chapter
The chapter consists of a description of the method of drought assessment by the PDSI, processing of remote sensing imagery and derivation of the NDVI and assessment of drought impact on yields of spring barley (Hordeum vulgare L.), winter wheat (Triticum aestivum L.) and maize (Zea mays L.). Hectare yields of the cereals were detrended for each district using the second degree polynomial function. For identification of relationships between PDSI and NDVI and drought impact on vegetation vigor was used correlation analysis.
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Droughts are responsible for severe vegetation loss and declining agricultural yields. As future climate change projections imply an increased risk of extreme events, the occurrence of droughts is potentially accelerating in the future. The influence of climate change on drought events in a Danish agricultural catchment under the emission scenario RCP8.5 are evaluated by three different drought indices covering soil moisture, groundwater and streamflow deficits. The indices are based on results from a hydrological model forced by downscaled climate outputs from 16 Euro-CORDEX climate models (GCM-RCMs), while considering uncertainties among climate model projections. The hydrological model demonstrated a satisfactory ability in modelling historical drought characteristics. The results from the future projections showed that the intensity and frequency of droughts increased towards the end of the century. The spatial patterns of changes in drought were found to be highly dependent on the climate model results, index formulations and assumptions, as well as the hydrogeological properties of the catchment. Groundwater based irrigation in the agricultural areas effectively mitigates soil moisture drought, leading to lower future uncertainty of the ensemble mean (higher model agreement) for soil moisture droughts at irrigated locations. This is obtained at the cost of lower groundwater levels in both reference and future periods resulting in larger uncertainties on the simulated groundwater droughts, because of the addition of irrigation uncertainty. While the joint impact of greater groundwater abstraction and changing dynamics of precipitation and groundwater recharge also leads to larger streamflow variability between model combinations (standard deviation) under RCP8.5 for the downstream discharge station.
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The climate history of the Alxa desert of northwestern China must be sought both in recent instrumental records (dating from 1960) and in high‐resolution proxy data. Climate proxies are scarce in desert areas; however, long‐lived desert shrubs can offer one such proxy. We have used shrub‐ring data from Zygophyllum xanthoxylum, collected in the central Alxa desert, to reconstruct the Self‐calibrating Palmer Drought Severity Index (scPDSI) for the period 1880–2015. The data covers the May–July growth season. When we compared the history constructed from the shrub‐ring data with the instrumental data collected 1960–2015, we found that the reconstructed history explained 41% of the variance in scPDSI data (40% after adjusting for loss of degrees of freedom). The reconstructed history shows that this region has experienced six persistent droughts and four seasons wetter than usual during the period under study. Of note is a severe drought event in 1920s that affected much of northern China (as noted in contemporary documents). The droughts and wet seasons identified in our reconstruction are consistent with reports from other researchers who have studied the climate history or the region. Our study suggests that it is feasible to reconstruct climate history using shrub‐ring data from long‐lived desert shrubs. This article is protected by copyright. All rights reserved.
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Changing climates and severe weather events can affect population viability. Individuals need to buffer such negative fitness consequences through physiological plasticity. Whether certain life-history strategies are more conducive to surviving changing climates is unknown, but theory predicts that strategies prioritizing maintenance and survival over current reproduction should be better able to withstand such change. We tested this hypothesis in a meta-population of garter snakes having naturally occurring variation in life-history strategies. We tested whether slow pace-of-life (POL) animals, that prioritize survival over reproduction, are more resilient than fast POL animals as measured by several physiological biomarkers. From 2006 to 2019, which included two multi-year droughts, baseline and stress-induced reactivity of plasma corticosterone and glucose varied annually with directionalities consistent with life-history theory. Slow POL animals exhibited higher baseline corticosterone and lower baseline glucose, relative to fast POL animals. These patterns were also observed in stress-induced measures; thus, reactivity was equivalent between ecotypes. However, in drought years, measures of corticosterone did not differ between different life histories. Immune cell distribution showed annual variation independent of drought or life history. These persistent physiological patterns form a backdrop to several extirpations of fast POL populations, suggesting a limited physiological toolkit to surviving periods of extreme drought.
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Drought-induced pumpage has precipitated dramatic groundwater-level declines in California’s Central Valley over the past 30 years, but the impacts of aquifer overdraft on water quality are poorly understood. This study coupled over 160,000 measurements of nitrate from ∼6,000 public-supply wells with a 30-year reconstruction of groundwater levels throughout the Central Valley to evaluate dynamic relations between aquifer exploitation and resource quality. We find that long-term rates of groundwater-level decline and water-quality degradation in critically overdrafted basins accelerate by respective factors of 2–3 and 3–5 during drought, followed by brief reversals during wetter periods. Episodic water-quality degradation can occur during drought where increased pumpage draws shallow, contaminated groundwater down to depth zones tapped by long-screened production wells. These data show, for the first time, a direct linkage between climate-mediated aquifer pumpage and groundwater quality on a regional scale.
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Abstract Droughts cause extreme anomalies in tropical forest growth, but the direction and magnitude of tropical forests in response to droughts are still widely debated. Here, we used four satellite‐based canopy growth proxies (CGPs), including three optical and one passive microwave, and in situ fluxes observations from eddy covariance (EC) measurements for a retrospective investigation of the impacts of historical droughts on tropical forest growth from a statistical point of view. Results indicate two opposite directions in drought‐related canopy dynamics across pantropical forests. The canopy of tropical forests with higher CGPs is more vulnerable to drought stress and recovers faster in the post‐drought recovery period. In contrast, the canopy of tropical forests with lower CGPs increases during the drought period and declines in the subsequent recovery period, which is beyond general expectation. In situ measurements from eddy‐covariance flux towers showed that forests with higher gross primary production and latent heat flux decreased photosynthesis and evapotranspiration during the drought period but increased photosynthesis and evapotranspiration faster during the post‐drought recovery period, supporting the findings from satellite observations. Our statistical analysis against climatic factors predicts that higher‐CGPs tress with probably taller and bigger canopies are more responsive to shortage of water availability caused by drought; while lower‐CGPs tress with shorter and smaller canopies are more responsive to sunlight availability and tend to increase their canopy leaves and enhance photosynthesis in sunnier days during the drought period. Our results highlight the differences in tropical forests in responding to drought stress, which are worth incorporated in Earth system models for time‐series evaluations.
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