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Meteorological Drought. Research Paper No. 45, 1965, 58 p.
Abstract
Palmer Drought Index, Original Article
... We examine the relation between drought and corporate tax avoidance using the Palmer Drought Severity Index (hereafter PDSI) developed by Palmer (1965), which has been extensively used in the climatology literature and enables researchers to measure the magnitude, frequency, and duration of droughts. Using PDSI to measure the annual state-level drought intensity condition, we regress various tax avoidance measures on drought intensity after controlling for other known factors affecting a firm's tax strategy. ...
... We continue to document a strong negative relation between predicted values of our drought measures and tax avoidance, thus confirming our main findings. Second, we 3 Drought is scientifically defined as "an interval of time, generally of the order of months or years in duration, during which the actual moisture supply at a given place rather consistently falls short of the time climatically expected or climatically appropriate moisture supply" (Palmer, 1965). Williams et al. (2020) have reported that the U.S. is in the grips of a natural "megadrought" that began in year 2000 and is still continuing as a result of the climate crisis. ...
... This study's independent variable of interest is state-level drought conditions measured using the Palmer Drought Severity Index (hereafter PDSI) developed by Palmer (1965), which has been extensively used in the climatology literature and enables researchers to measure the magnitude, frequency, and duration of droughts. PDSI ranges from − 10 (dry) to + 10 (wet), where lower values of the index indicate more severe drought conditions. ...
Natural disaster events such as drought affect the broader economy and inflict adverse consequences for firms because of spill-over effects in an integrated economy. Contrary to the expectation that firms would engage in higher levels of corporate tax avoidance strategies when they experience a negative cash flow shock, we document consistent evidence that firms engage in less corporate tax avoidance when their headquarter states experience drought. Reduced tax avoidance is more pronounced among firms with higher CSR performance and among firms operating in states that experience a GDP decline. Collectively, the findings of our study demonstrate prosocial and ethical behavior of U.S. firms when they experience natural disaster events.
... 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. ...
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.
... 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. ...
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.
... Drought detection and classification rely on various established indices that link drought events with climate parameters (Zeybekoğlu and Aktürk 2021). The most commonly used methods to assess meteorological droughts include the Standardized Precipitation Index (SPI) (McKee et al. 1993), the Standardized Precipitation and Evapotranspiration Index (SPEI) (Vicente-Serrano et al. 2010), and the Palmer Drought Severity Index (PDSI) (Vicente-serrano et al. 2010;Palmer 1965). Drought research remains a crucial scientific field, aiming to mitigate its devastating effects and implement preventive measures. ...
... Among them, objective indicators are often used, but the subjective definition of drought makes it very difficult to construct a single and universal drought indicator. Most studies related to drought analysis and monitoring systems are conducted using one of the following: PDSI based on the drought balance equation soil moisture (Palmer 1965) and standard approach to precipitation index. It is based on a stochastic approach to precipitation. ...
In Algeria, one of the most alarming effects of climate change is drought. These periods of low rainfall have significant social and environmental implications, prompting investigations into management strategies, associated risks, and resulting crises. This study focuses on the Wadi Lakhdar watershed, a semi-arid region in northwestern Algeria, aiming to demonstrate the historical presence of drought and its impact on the environment and agriculture. To quantify long-term meteorological droughts and identify wet and dry periods from 1999 to 2021, we will utilize three drought indices: the Standardized Precipitation Index (SPI-12 months), the Standardized Precipitation and Evapotranspiration Index (SPEI-12 months), and the Palmer Drought Severity Index (PDSI-12 months). These indices are currently valuable tools for implementing various countermeasures, including drought early warning systems, monitoring, and contingency planning. Our analysis employing SPI, SPEI, and PDSI data will reveal distinct value ranges for wet years (1.01 to 2 for SPI, 0.64 to 1.28 for SPEI, and 1.35 to 2.68 for PDSI) and extremely dry years (− 1.07 to − 2.1 for SPI, − 0.68 to − 1.34 for SPEI, and − 1.43 to − 2.81 for PDSI). The wettest years were 2009, 2010, and 2013, while the driest years occurred in 2000, 2005, 2006, and 2007. Understanding drought characteristics is crucial for effective drought management. Drought indices provide a practical way to convert vast amounts of data into quantitative information for applications such as drought forecasting, communication of drought severity levels, and raising public awareness about the potential consequences of drought. This study’s social benefit lies in raising public awareness of these implications and anticipated consequences.
... Meteorological indices Palmer Drought Severity Index (Palmer, 1965), Standardised Precipitation Index (McKee et al., 1993), Crop-specific Drought Index (Meyer & Hubbard, 1995), NOAA Drought Index (Strommen et al., 1980), Rainfall Anomaly Index (Van Rooy, 1965), Reclamation Drought Index (Weghorst, 1996) Soil moisture indices Soil Moisture Anomaly (Bergman et al., 1988), Evapotranspiration Deficit Index and Soil Moisture Deficit Index (Narasimhan & Srinivasan, 2005) ...
... Palmer Hydrological Drought Severity Index (Palmer, 1965), Surface Water Supply Index (Shafer & Dezman, 1982), Standardized Water-level Index (Bhuiyan, 2004), Standardized Streamflow Index (Modarres, 2007), Standardized Reservoir Supply Index (Gusyev et al., 2015) Remote sensing indices Normalised Difference Vegetation Index (Tarpley et al., 1984), Vegetation Health Index (Kogan, 1990), Vegetation Condition Index (Liu & Kogan, 1996), Enhanced Vegetation Index (Huete et al., 2002) Composite or modelled indices* United States Drought Monitor (Svoboda et al., 2002), Combined Drought Indicator (Sepulcre-Canto et al., 2012), Global Integrated Drought Monitoring and Prediction System (Hao et al., 2014), New Zealand Drought Index (NIWA, 2017) Sources: Pourzand and Noy (2022). * All are used as indicators of droughts and are constructed by merging different types of indices. ...
This paper estimates the regional impact of drought, as defined by the New Zealand Drought Index (NZDI), on-farm income and profits across the main agricultural regions in New Zealand. We use farm micro-data (tax forms) from Statistics New Zealand's Longitudinal Business Database (LBD). The empirical strategy relies on region-specific panel-data models with fixed effects. We find that outcomes vary across regions and land uses. The main dairy regions (Waikato and Taranaki) have experienced significant positive impacts, likely resulting from drought-induced higher milk prices. In contrast, sheep/beef farms’ gross income and profit were negatively affected by droughts across most sheep/beef regions. Across all regions, the estimations also show that drought events do not have any observable persistent impact on farm income and profits, on average, past the first couple of years.
... To this end, several tools and mathematical models have been developed for the quantification of drought (Byun and Wilhite 1999;Mo 2008;Tan et al. 2015;Sarker et al. 2020;DİKİCİ and AKSEL 2021;Yisehak and Zenebe 2021;Mishra et al. 2022;Abdourahamane et al. 2022;Vicente-Serrano et al. 2022). Among the most well-known models, we can mention the most used: the Standardized Precipitation Index (SPI: McKee et al. (1993); Kebede et al. (2020); Sarker et al. (2020); Mishra et al. (2022)), the Standardized Precipitation Evapotranspiration Index (SPEI: Vicente-Serrano et al. (2010); Manh-Hung et al. (2020); Dahal et al. (2021)), the Effective Drought Index (EDI: Byun and Wilhite (1999); Ekhtiari and Dinpashoh (2019)), the Palmer Drought Severity Index (PDSI: Palmer (1965); Guttman (1998)), the Self-Calibrating Palmer Drought Severity Index (scPDSI: Wells et al. (2004); Zhang et al. (2019)), the Rainfall Anomaly Index (RAI: Huang et al. (2015); Sadiq et al. (2020); Raziei (2021)). The scPDSI is an improved version of PDSI which is the most widely used and recognized as successful if used operationally (Byun and Wilhite 1999), while SPI and EDI are among the most recommended for operational drought monitoring in many regions (Morid et al. 2006a;Hayes et al. 2011;Wambua et al. 2018). ...
... • The Self-Calibrating Palmer Drought Severity Index (scPDSI) constructed on the basis of CRU data at 0.5 • × 0.5 • spatial resolution. It was developed by Wells et al. (2004) as a variant on the original PDSI (Palmer 1965) introduced to help comparing results from different climate regimes. It is mostly used operationally and has shown best results in drought monitoring (Vicente-Serrano et al. 2010;Zhang et al. 2019;Silva et al. 2022). ...
In this paper, computation of the Effective Drought Index (EDI) is revisited and the performance of the derived model (mEDI) is compared to Standardized Precipitation Index (SPI) using Self-Calibrating Palmer Drought Severity Index (scPDSI) as the benchmark. Four monthly data sets over Central-Africa were used: precipitation from ten observation stations, gridded precipitation from Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit (CRU), and gridded scPDSI. Station data span the periods 1951–2005 and 1971–2013 for Cameroon and Democratic Republic of Congo (DRC), respectively, and 1950–2019 for all gridded data. SPI was computed based on gamma fitting function and EDI was revised so that mEDI uses monthly precipitation as input data and can quantify multi-scalar droughts. As results, the performances of both indices generally increase with the time scale (TS) and decrease as total annual precipitation increases. The mEDI model outperforms SPI for precipitation above 2288.91 mm/2444.02 mm at TS < 12-month, and below 3233.87 mm/2366.42 mm at 12-month TS, for GPCC/CRU data, while SPI performs better for precipitation out of these intervals, except at the particular TSs of 12, 24, 36 and 48 months where mEDI regains the advantage. At 15-month TS and over, both indices show substantially equal performances. If spatial average of precipitation is used as input for each of the four defined climatic zones, the performances of both indices are improved. SPI best describes drought on short TSs while on medium and long TSs (> 9-month TS), mEDI shows the best performance.
... Drought is a complex phenomenon (Van Loon, 2015;Wong et al., 2013;Yevjevich et al., 1983) that can potentially have catastrophic consequences at multiple levels, e.g., agriculture, water resources. The literature dealing with drought effects is considerable (Barker et al., 2016;Bonacci, 1993;Ferina et al., 2021;Hisdal, 2002;Li et al., 2021;Mishra and Singh, 2010;Morid et al., 2006;Palmer, 1965;Pandžić et al., 2020;Tadić et al., 2015;Van Lanen et al., 2013). In the context of climate change, the duration and intensity of drought are expected to be strongly influenced by increase in temperature (Dai, 2011). ...
... The Palmer Drought Index was developed for monitoring changes in soil water balance (Palmer, 1965). In the US, it is used as a standard to study meteorological drought. ...
Below-average precipitation and above-average air temperature are important factors in the occurrence and intensity of drought. In the context of global climate change, air temperature increase, as a key climatological parameter, has to be considered when calculating the drought index. We introduce a new method of drought analysis, relying on standardized values of precipitation and mean air temperatures for a certain period. The standardized value is calculated by subtracting the average value for each period from each measured value and dividing the obtained value by the standard deviation of the sample. Next, the New Drought Index (NDI) is calculated by subtracting the standardized temperature value from the standardized precipitation value. NDI values were determined for the monthly and annual precipitation time series and mean monthly and annual air temperatures measured at the stations Split-Marjan and Zagreb-Grič between 1948 and 2020. The NDI indicates that the risk of drought has intensified significantly in recent decades, which may be related to the effect of global warming.
... Dos de los principales índices climáticos más utilizados son el Standardized Precipitation Index (SPI) (McKee et al., 1993), que se basa únicamente en la precipitación, y el Palmer Drought Severity Index (PDSI) (Palmer, 1965), que se basa en la precipitación y la temperatura del aire. Por otro lado, algunos índices basados en la evapotranspiración potencial (PET) mostraron ser más útiles para cuantificar la severidad de la sequía. ...
En este trabajo se aborda el impacto de los períodos secos y húmedos en el rendimiento de cultivos de trigo y cebada, en el sudeste de la provincia de Buenos Aires. Para evaluar el grado de condición de sequía/humedad de cada período se utilizó el Índice Estandarizado de Precipitación y Evapotranspiración (SPEI). Por otro lado, se utilizaron datos de rendimiento de cultivo a nivel de partido de la Secretaría de Agricultura, Ganadería y Pesca de Argentina. Utilizando un modelo cuadrático, se analizó la relación SPEI-rendimiento para el período 2001-2023. A partir de un análisis multiescalar se determinó que el balance hídrico vertical entre la pre-siembra y el periodo crítico (mayo-octubre) es crucial para la productividad final de los cultivos de invierno en la zona de estudio. Se encontraron relaciones SPEI-rendimiento con coeficientes de correlación de 0.76 para trigo y de 0.68 para cebada con SPEI de dos meses antes de la cosecha. Finalmente, se observaron tanto para condiciones altas/extremas de sequía como de humedad impactos similares sobre el rendimiento de los cultivos analizados, con reducciones de entre 27% y 34%, con una mejor respuesta por parte de la cebada a condiciones extremas.
... package (R Core Team, 2021). We assessed rank-correlations of median nitrate anomalies for each cluster to the Palmer Drought Severity Index (PDSI), an integrated metric of drought (Palmer, 1965), using Spearman's ρ with the cor.test function in the R "stats" package (NOAA, 2023; R Core Team, 2021). We used a confidence level of 95% ( p = 0.05) to evaluate all statistical hypothesis tests. ...
Groundwater-resource quality is assumed to be less responsive to drought compared to that of surface water due to relatively long transit times of recharge to drinking-supply wells. Here, we evidence dynamic perturbations in aquifer pressure dynamics during drought and subsequent recovery periods cause dramatic shifts in groundwater quality on a basin scale. We used a novel application of time-series clustering on annual nitrate anomalies at >450 public-supply wells (PSWs) across California's San Joaquin Valley during 2000-22 to group sub-populations of wells with similar water-quality responses to drought. Additionally , we statistically evaluated the direction and magnitude of multi-constituent water-quality changes across the San Joaquin Valley using a broader dataset of >3000 PSWs with data during two select hydrologic stress periods representing an extreme drought (2012-16) and subsequent recovery (2016-19). Results of time-series clustering and stress-period change analyses corroborate a predominant regional response to pumping stress characterized by increased concentrations of anthropogenic constituents (nitrate, total dissolved solids) and decreased concentrations of geogenic constituents (arsenic, fluoride), which largely reversed during recovery. Cluster analysis also identified a secondary, less commonly occurring group of PSWs where nitrate decreased during drought, but explanatory factor analysis was not able to discern hydrogeologic drivers for these two divergent response patterns. Long-term tracer data support the hypothesis that the predominant regional signal of nitrate increase during drought is caused by enhanced capture of modern-aged groundwater by PSWs during periods of pumping stress, which can drive rapid changes in water quality on seasonal and multiannual timescales. Pumping-induced migration of modern, oxic groundwater to depth during drought may affect geochemical conditions in deeper portions of regional aquifers controlling the mobility of geogenic contaminants over the long term.
... McMahon and Areas, 1982) stated that droughts occur over abnormally dry weather that is su ciently prolonged due to the lack of precipitation with its subsequent effects on hydrological imbalance, moisture de ciency and decrease of water resources availability during a period and over a spatial extent (Beran and Rodier, 1985). The most effective drought index is proposed by Palmer (1965) which takes into consideration not only precipitation effect but also moisture de ciency and solar irradiation factors. His method depends on precipitation, temperature data and local available water content of soil and thus it is more effective in agricultural drought assessments. ...
Global warming coupled climate change impacts show their end results in the form of extreme events including floods and droughts. Droughts are creeping phenomena and their prediction is more related to precipitation events and in many parts of the world droughts occurrences become temporally and spatially effective. In the literature, there is the concept of standard precipitation index (SPI) that provide classification of the drought based on the standard normal (Gaussian( probability distribution function (PDF) which is a product of the original time series record data PDF that may have various forms such as Gamma, Weibull, Log-Normal, Pearson, and like. As for SPI there are publications that are based on statistical standardization procedure whereas it should be probabilistic standardization methodology. On the other hand, many publications concentrate on conversion of the original PDF of the time series to Gamma PDF and then apply the normalization procedure. In this paper conversion of any PDF to Gamma PDF is noticed as misconception except in the case of original PDF confirms with Gamma PDF: It is well known that almost all hydro-meteorology time series have various PDF not abide with Gamma PDF: The mistakes of conversion to Gamma PDF prior to SPI is explained verbally and numerically and the genuine proper SPI procedure methodology is proposed in detail. The application of the proposed methodology is given for seven meteorology station records from seven internal climate zones of Türkiye.
... records of precipitation, temperature and the soil characteristics 34,35 . Therefore, PDSI measures soil moisture deficit and is more suitable for characterizing agricultural drought 36 . ...
Global warming accelerates water cycle, causing more droughts globally that challenge monitoring and forecasting. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to assess drought characteristics and response time of natural and economic systems at various timescales. However, existing SPEI datasets have coarse spatial or temporal resolution or limited spatial extent, restricting their ability to accurately identify the start or end dates or the extent of drought at the global scale. To narrow these gaps, we developed a global daily SPEI dataset (SPEI-GD), with a 0.25° spatial resolution from 1982 to 2021 at multiple timescales (5, 30, 90, 180 and 360 days), based on the precipitation from European Center for Medium Weather Forecasting Reanalysis V5 (ERA5) dataset and the potential evapotranspiration from Singer’s dataset. Compared to widely used SPEIbase dataset, the SPEI-GD can improve the spatial-temporal resolution and the accuracy of SPEI in areas where meteorological sites are lacking. The SPEI-GD significantly correlates with site-based SPEI and soil moisture. Our dataset solidly supports sub-seasonal and daily-scale global and regional drought research.
... The temperature record is from Bariloche (Servicio Meteorológico Nacional of Argentina; 41 • 09'S-71 • 15'W; period: 1931-2016), while the precipitation record is from Los Laureles (Dirección General de Aguas of Chile; 38 • 57'S, 72 • 12'W; period: 1947-2016). The Palmer Drought Severity Index (PDSI; Palmer, 1965) is a standardized measure of surface moisture conditions, ranging from about − 10 (dry) to + 10 (wet). The quarterly PDSI series for the study area period: 1957-2017) to evaluate the relationships between the Southern Annular Mode and the Araucaria tree-ring parameters. ...
Blue intensity (BI) has emerged as an inexpensive and relatively simple method for obtaining a proxy for relative wood density, and it has been successfully tested on several conifer species in Europe, North America, Asia and Australasia. Despite international efforts to promote the use of these methods worldwide, BI chronologies developed for native South American species have not yet been published. The possibility of developing BI chronologies in Araucaria araucana, an emblematic conifer of northern Patagonia, began to be explored some years ago. However, as it has been reported in other species, the wood anatomy of Araucaria presents several difficulties for obtaining robust BI common signals between samples. Therefore, we conducted this study to assess various methods for determining BI parameters based on the degree of common signal between trees in the chronology and their correlation with climatic factors. In this study, we demonstrated the feasibility of developing reliable BI chronologies from a site within the Araucaria range in Argentina by analysing the sensitivity to changes in the width of the measurement window. Although replicating measurements within the same core improved the classical statistic used to quantify the expressed population signal in a chronology (i.e. EPS), the results obtained here show that the chronologies developed using different methods were practically identical. Furthermore, our results revealed different climate signals expressed by both earlywood (EWBI) and latewood (LWBI) BI records, corresponding to the current spring and summer, respectively. In addition, soil water availability was significantly associated with wood density variation. Therefore, the climatic and environmental information provided by BI measurements in Araucaria complements what is already known from ring width (RW) and thus highlights its potential for use in future climate and ecological reconstructions.
... Various widely-used statistical drought indices (e.g., the Standardized Precipitation Index (SPI) 110 , the Standardized Precipitation Evapotranspiration Index (SPEI) 111 , and the Streamflow Drought Index (SDI) 112 ) use only one or two climatic variables. In contrast, the Palmer Drought Severity Index (PDSI) 113 requires more input data (e.g., ET, soil available water capacity, soil water content, and water yield) to drive a two-layer water balance model and evaluate the degree of soil moisture stress on a monthly time scale. The use of the PDSI facilitates comparisons across time and space and is capable of capturing extreme events because values are normalized by average moisture conditions 31,38,64,114 . ...
Droughts or floods are usually attributed to precipitation deficits or surpluses, both of which may become more frequent and severe under continued global warming. Concurring large-scale droughts in the Southwest and flooding in the Southeast of China in recent decades have attracted considerable attention, but their causes and interrelations are not well understood. Here, we examine spatiotemporal changes in hydrometeorological variables and investigate the mechanism underlying contrasting soil dryness/wetness patterns over a 54-year period (1965–2018) across a representative mega-watershed in South China—the West River Basin. We demonstrate that increasing rainfall intensity leads to severe drying upstream with decreases in soil water storage, water yield, and baseflow, versus increases therein downstream. Our study highlights a simultaneous occurrence of increased drought and flooding risks due to contrasting interactions between rainfall intensification and topography across the river basin, implying increasingly vulnerable water and food security under continued climate change.
... Although referred to as a meteorological drought index, the PDSI focuses on evapotranspiration, precipitation and soil moisture conditions (Yan et al., 2013). It uses a water balance model to determine moisture availability in the study region (Palmer, 1963). ...
This study examined the worsening severity of global droughts caused by climate change. However, the multiple definitions and varied range of drought indices pose challenges in effectively monitoring and assessing the prevalence and severity of droughts. This study aims to give a comprehensive overview of the various drought definitions found in the literature and how they have evolved based on their applications. Specifically, the focus was to shed light on the dynamic nature of drought characterization and offer insights into the factors that shaped its conceptualization over time. Within this context, this study explored three primary categories of drought indices: climatic, remote sensing, and composite. Each category was discussed in relation to its utility in specific fields, such as meteorological, agricultural, and hydrological drought assessments, along with an analysis of their strengths and limitations. Furthermore, this study presents modified meteorological drought indices that have been adapted to better monitor agricultural droughts. Additionally, the authors used geographic information systems to create a map showing the distribution of drought-related publications globally over the past decade. The findings showed that countries with arid and semi-arid climates are more actively involved in drought research, highlighting their particular interest and concern regarding the subject matter. The implications of this study emphasize the urgent need for immediate and coordinated efforts to address the escalating issue of droughts caused by climate change. By improving monitoring and assessment methods and focusing on tailored strategies in vulnerable regions, it is possible to mitigate the far-reaching consequences of drought and to build more resilient communities and ecosystems.
... However, monitoring drought may be more complex than monitoring flooding because there are four kinds of drought, specifically, meteorological, agricultural, hydrological, and socioeconomic drought (Mishra and Singh, 2010), and each drought is described by a different physical index. For example, meteorological drought is usually described by the Standardized Precipitation Index (McKee et al., 1993) or Palmer Drought Severity Index (Palmer, 1965) that is based on precipitation data. In contrast agricultural drought is based on soil water deficits that exert pressure on crop growth and is commonly measured by indices such as the Soil Moisture Index (Sridhar et al., 2008) and Soil Water Deficit Index (Martínez-Fernández et al., 2015), or a single vegetation index (VI) (Tucker, 1979), and a combination of the VI with other impact factors, such as surface temperature and evapotranspiration (e.g., Mu et al., 2013). ...
Climate change has critical adverse impacts on human society and poses severe challenges to global sustainable development. Information on essential climate variables (ECVs) that reflects the substantial changes that have occurred on Earth is critical for assessing the influence of climate change. Satellite remote sensing (SRS) technology has led to a new era of observations and provides multiscale information on ECVs that is independent of in situ measurements and model simulations. This enhances our understanding of climate change from space and supports policy-making in combating climate change. However, it remains challenging to remotely retrieve ECVs due to the complexity of the climate system. We provide an update on the studies on the role of SRS in climate change research, specifically in monitoring and quantifying ECVs in the atmosphere (greenhouse gases, clouds and aerosols), ocean (sea surface temperature, sea ice melt and sea level rise, ocean currents and mesoscale eddies, phytoplankton and ocean productivity), and terrestrial ecosystems (land use and land cover change and carbon flux, water resource and hydrological hazards, solar-induced chlorophyll fluorescence and terrestrial gross primary production). The benefits and challenges of applying SRS in climate change studies are also examined and discussed. This work will help us apply SRS and recommend future SRS studies to mitigate and adapt to global climate change.
... 1. A feasible definition of drought is needed to implement general actions in response to drought, and it may be necessary to adopt more than one definition depending on the economic, social, and environmental sectors impacted (Hayes, 1998 Index (Palmer, 1965), commonly used in the past, is being replaced or supplemented as a monitoring tool in many states. States now rely on multiple drought indices calibrated to various intensities of drought. ...
This study aimed to evaluate vegetation depletion in two distinct regions, the Brazilian
Amazon and Northern Namibia grassland, using remote sensing data and several vegetation
indices. The study utilized Sentinel-2 data with 10m spatial resolution and Qgis was used to
calculate the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index
(SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index
(GNDVI), Modified Soil Adjusted Vegetation Index (MSAVI), Albedo-NDVI and Carbon Delivery
Ratio (CDR).
The results from all the indices showed a negative trend towards vegetation depletion in both
regions, indicating a decline in vegetation health and productivity. This suggests that the
regions may be facing environmental challenges that require immediate attention to prevent
further degradation of the vegetation cover.
The Carbon Delivery Ratio (CDR) was used as a metric to evaluate the effectiveness of carbon
sequestration efforts in the two countries. The results showed a decline in CDR for both
countries, indicating a potential decrease in the effectiveness of carbon sequestration efforts
in the region. This highlights the importance of continued efforts to improve carbon
sequestration practices and reduce greenhouse gas emissions in the region.
However, the study would have benefited from the inclusion of ground truth data, such as
perception data from both countries, and the use of additional vegetation indices to provide
a more comprehensive assessment of vegetation health. This could further enhance the
accuracy of the results and provide more insights into the underlying factors contributing to
vegetation depletion in these regions.
Overall, this study demonstrates the usefulness of remote sensing and vegetation indices in
monitoring changes in vegetation over time. The results can inform decision-making
processes related to environmental conservation and management in these regions and serve
as a starting point for further research and analysis.
... The drought indices are used to monitor the drought events on multi-temporal scales (1-month, 2-month,…, n-month) by inculcating the values into a single numerical value. These indices are the Palmer Drought Severity Index (Palmer, 1965), the Z index (Palmer, 1968), the Crop Moisture Index (Dai, 2011;Palmer, 1968), the Standardized Precipitation Index (SPI) (McKee et al., 1995), the Reconnaissance Drought Index (Tsakiris & Vangelis, 2005), etc. However, The World Meteorological Organization (WMO) advises to use the SPI in all the national meteorological and hydrological services as it is considered to be the most efficient tool to assess the meteorological drought (Okpara & Tarhule, 2015). ...
... The drought indices are used to monitor the drought events on multi-temporal scales (1-month, 2-month,…, n-month) by inculcating the values into a single numerical value. These indices are the Palmer Drought Severity Index (Palmer, 1965), the Z index (Palmer, 1968), the Crop Moisture Index (Dai, 2011;Palmer, 1968), the Standardized Precipitation Index (SPI) (McKee et al., 1995), the Reconnaissance Drought Index (Tsakiris & Vangelis, 2005), etc. However, The World Meteorological Organization (WMO) advises to use the SPI in all the national meteorological and hydrological services as it is considered to be the most efficient tool to assess the meteorological drought (Okpara & Tarhule, 2015). ...
... There stands a range of drought indices such as Standardized Precipitation Index (SPI) (McKee et al., 1993), Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010b) and Palmer Drought Severity Index (PDSI) (Palmer, 1965). SPI considers precipitation changes only without consideration of impacts of other factors on occurrence of droughts such as air temperature, wind speed, evapotranspiration and soil moisture (Um et al., 2018). ...
In this study, we proposed a new integrated remote sensing drought monitoring indices, i.e. Multiple Remote Sensing Drought Index integrated by Principal Component Analysis (PSDI), Multiple Remote Sensing Drought Index integrated by multiple linear regression (MRSDI) and Multiple Remote Sensing drought index integrated by gradient boosting method (GBMDI), based on the Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Soil Moisture Condition Index (SMCI). The monitoring performance of PSDI, MRSDI and GBMDI was compared and verified based on the real-world observed droughts during 2002 to 2016. We also evidenced drought monitoring performance of the PSDI MRSDI and GBMDI by comparison between PSDI, MRSDI, GBMDI and SPEI, SPI and PDSI based on the in situ observed meteorological data. We found that the spatiotemporal characteristics of droughts monitored by the PSDI, MRSDI and GBMDI were generally in good agreement with those by the SPI and SPEI. The GBMDI performs better than PSDI and MRSDI in describing drought processes and spatial patterns of droughts of different drought intensities. Comparison between the real-world observed drought-affected croplands and those monitored by PSDI, MRSDI and GBMDI indicated better drought monitoring performance of GBMDI than PSDI and MRSDI in monitoring droughts across widespread drought-affected regions. Besides, the trend of GBMDI is in good agreement with standardized crop yield. Therefore GBMDI should be the first choice in drought monitoring practice. The GBMDI developed in this study can help to provide an alternative drought monitoring index for large-scale drought monitoring across China and also in other regions of the globe.
... Various indices are developed and suggested for drought assessment, e.g. Standardized Precipitation Index (McKee et al. 1993), Palmer Drought Severity Index (Palmer 1965), Standardized Streamflow Index (Shukla and Wood 2008), Percent of Normal Precipitation Index (Werick et al. 1994), Regional Drought Area Index (Fleig et al. 2011) andStandardized Precipitation Evapotranspiration Index (Vicente-Serrano et al. 2010). Every index defines specific characteristics. ...
Depletion of water resources and soil moisture leading to drought is a global concern and the effective assessment and monitoring using a drought model has become essential. A detailed account of frequency, run length, and temporal trend of the drought events are presented in the study from 1981 to 2019 at the 1-, 3-, 6-, 9-, 12-, and 24-month timescale using the Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index. SPI recorded more drought months in the extreme category with 14 months at Gubbi station for example, while SPEI showed only 5 months. SPEI showed longer drought length in moderate and severe categories for agricultural and hydrological drought. At 1-month timescale, both the indices reported extreme drought events where Tiptur station in May 2016 (-4.75) and Chikanayakanahalli station in March 1992 (-2.76) were the worst-case scenarios. The study aims at providing practical results to facilitate decision-makers for drought risk management.
... 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. ...
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.
... From these data we extracted the gridcells covering 60 • N-40 • N by 10 • W-30 • E. For relative soil moisture availability, we use data from the Old World Drought Atlas (OWDA; Cook et al., 2015). The OWDA is a tree-ringbased reconstruction of annually resolved June-August (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) values (Palmer, 1965;van der Schrier et al., 2011van der Schrier et al., , 2013) resolved on a 0.5 • × 0.5 • grid across Europe. For obvious reasons, the spatial and temporal extent of both reconstructions is limited by the distribution and length of the tree-ring chronologies available for reconstruction. ...
Although variations in building activity are a useful indicator of societal well-being and demographic development, historical datasets for larger regions and longer periods are still rare. Here, we present 54,045 annually precise dendrochronological felling dates from historical construction timber from across most of Europe between 1250 and 1699 CE to infer variations in building activity. We use geostatistical techniques to compare spatiotemporal dynamics in past European building activity against independent demographic, economic, social and climatic data. We show that the felling dates capture major geographical patterns of demographic trends, especially in regions with dense data coverage. A particularly strong negative association is found between grain prices and the number of felling dates. In addition, a significant positive association is found between the number of felling dates and mining activity. These strong associations, with well-known macro-economic indicators from pre-industrial Europe, corroborate the use of felling dates as an independent source for exploring large-scale fluctuations of societal well-being and demographic development. Three prominent examples are the building boom in the Hanseatic League region of northeastern Germany during the 13th century, the onset of the Late Medieval Crisis in much of Europe c. 1300, and the cessation of building activity in large parts of central Europe during armed conflicts such as the Thirty Years’ War (1618–1648 CE). Despite new insights gained from our European-wide felling date inventory, further studies are needed to investigate changes in construction activity of high versus low status buildings, and of urban versus rural buildings, and to compare those results with a variety of historical documentary sources and natural proxy archives.
... 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. ...
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.
... 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). ...
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.
Southeast Asia and Australia have historically suffered significant losses due to droughts. Understanding these droughts can serve as a foundation for mitigation strategies aimed at reducing the damages they cause. Meteorological drought indices, such as the Standardized Precipitation Index (SPI), offer a valuable method for quantifying drought severity and frequency. This study employs monthly precipitation data from GPM_3IMERGM (0.1° x 0.1°) spanning 2000-2021 to calculate SPI for Southeast Asia and Australia across different time scales: 3 months (SPI-3), 6 months (SPI-6), and 12 months (SPI-12). These indices measure drought frequency and intensity, providing parameters for the multiscale Drought Hazard Index (DHI) to identify areas at risk during specific periods. Our analysis indicates that as drought periods lengthen, DHI intensity in each grid generally decreases. A distinct DHI pattern emerges in the tropical rainforest climate zone (Af) in Southeast Asia, while the Mediterranean climate (Csb) in southwestern and southeastern Australia exhibits the largest proportion of extreme hazard across all drought periods. Overall, the 3-month period presents the highest drought hazard in both Southeast Asia and Australia.
تهدف هذه الدراسة إلى تحديد الفترات الجافة والرطبة لسلسلة بيانات الأمطار في محطة طبرق الواقعة شمال شرق ليبيا، واُستخدمت قرائن الجفاف المناخي التي تعتمد على عنصرالتساقط وهي المؤشر المعياري للتساقط (SPI) وطريقة العشريات لـ(جبس وماهر) والنسبة المئوية للتساقط، ومعامل شدة الجفاف، واتفقت نتائج المؤشرات أن السنوات الجافة بلغت نسبتها 53.3%، وأطولها الفترة الممتدة فيما بين 1999- 2004، وكانت سنة 1999 أشدّ السنوات جفافاً، وبلغت نسبة السنوات الرطبة 46.3% من مدة الرصد، وأظهرت النتائج أن هناك سلسلة متتالية لسنوات رطبة تعقبها سنوات جافة كما في الفترة الممتدة بين 2005-2013، وهذا ما يعكس المناخ شبه الجاف في منطقة طبرق.
Agricultural drought is one of the most critical effects of climate change. This work proposes a machine learning based approach for agricultural drought monitoring that integrates seven standard remote sensing indices computed from Sentinel-2 multispectral imagery, agricultural drought damage percentage assessed in situ and six meteo-climatic variables, including Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index. We applied the approach to 117 agricultural fields in Italy, using a multinomial logistic regression model to classify the fields into zero-risk, medium-risk, and high-risk drought damage classes. The overall performances of the proposed classification model, summarized by an F1 score equal to 0.61, are not particularly encouraging as the model struggles to distinguish between medium-risk damage and high-risk damage classes. Nonetheless, the model shows promising results in identifying fields with zero drought damage and could be applied to reduce the time and cost of in situ measurements by excluding fields with no damage from the ground data collection.
A sharp drop in groundwater level as a result of indiscriminate extraction over a long period of time leads to the drying up of groundwater flows, which is called the phenomenon of groundwater drought. In this regard, this research aims to investigate the process of change and reduction of groundwater level, which is characterised by the phenomenon of groundwater drought. Based on this, the Groundwater Resource Index (GRI) was used to evaluate the drought condition of groundwater and analyse its spatial and temporal patterns based on groundwater level data of 21 observation wells between 1993 and 2019. ArcGIS software was used to create zone maps. The results of the research show that certain areas of the study area have experienced moderate to severe drought since 2001. In addition, the GRI zonation maps show that the southern and south-eastern regions of the aquifer have been more sensitive to drought than other parts of the aquifer during the defined period. The spatio-temporal pattern of groundwater drought in the aquifer shows that after a period of moderate drought from 2001 to 2003, the condition of the aquifer improved slightly, and generally stable conditions were established from 2001 to 2010, but since 2011, the occurrence of drought has intensified and the aquifer has been in severe to very severe drought conditions. These conditions highlight the need for careful attention and implementation of management measures. One of the study's recommendations is to use satellite data on groundwater levels to assess the progress of the drought, and compare it with the findings of this study.
Global drylands, covering over 40% of Earth's land surface, are important among worldwide ecoregions and support large human and livestock populations. However, these ecologically sensitive ecoregions are undergoing a rapid transformation resulting from climate change, socioeconomic and political factors, increases in population, and ever-growing demands for goods and services. Managing Soil Drought addresses basic processes and provides specific case studies throughout covering the protection, restoration, and sustainable management goals of global drylands under changing and harsh climatic conditions, including fragile and vulnerable ecosystems. The book is written by numerous researchers, academicians, practitioners, advocates, land managers, and policymakers involved in bringing about transformation in these regions important to human and nature. It includes information on basic strategies for sustainable management of global drylands aimed at improving water use efficiency through choosing appropriate species, developing new varieties, using organic and inorganic amendments, and scaling up innovative farming systems. This volume in the Advances in Soil Sciences series is an essential read for development organizations and policymakers involved in improving crop productivity and sustainability in drought-prone regions; students, researchers, and academicians interested in sustainable management of water resources; and those involved in emerging concepts of regenerative agriculture, agroecology, and conservation agriculture.
As known, Algeria is a dry country that belongs to the arid-semi-arid climate (Smadhi et al., 2022). These vast interior spaces are characterized by a dry and cold climate in winter, and hot and dry in summer (Bachir et al., 2022). A deficient and irregularly distributed rainfall characterizes the climatic conditions that exert a very strong influence on agricultural growth (Bachir et al., 2016). They are an obstacle to the adoption of intensive agricultural practices without irrigation (Bachir et al., 2021). A judicious use of water in the main sectors of agriculture, industry and drinking water supply, should be based on the knowledge of its hydrochemical status (Hosseinifard and Mirzaei, 2015). The latter is a function of the mineralization acquisition process and pollution (Sayeh et al., 2022). Many factors are involved in the chemistry of water, such as climate, geology, the presence of a sea, and human action (Peters and Maybeck, 2000). Thus, it is prudent to link the changes in the chemical character of waters to natural conditions and anthropogenic activities. Due to their location on the surface, surface waters are relatively less loaded with minerals than ground waters, which are subject to geochemical, natural processes resulting from water-rock interactions. Numerous research studies have elucidated these geochemical reactions through case studies (Gupta et al., 2008; Al-Ahmadi and El-Fiky, 2009; Senthilkumar and Elango, 2013; Barbieri et al., 2017; Yi et al., 2017). Several approaches were used to assess water geochemistry. By using the determination of chemical facies or factors approach, it is possible to identify, the mixing processes of waters (Selvakumar et al., 2017), the recharge zones (Dragon and Gorski, 2015) or the chemical evolution of waters due to the human activities which impact in a direct or indirect way in the modification of hydrochemical behaviour (Eloïse, 2017). Geochemical indicators are widely discussed in the literature and have used the following parameters: Saturation and Chloro-alkalines indices, Gibbs diagram and some characteristic ion ratios. Human, through diverse activities, participates in a direct or indirect way in the modification of hydrochemical behavior.
Algeria, as well as developing countries, has reoriented the concept of food security through institutional and administrative measures and policies aimed at improving the access of populations to abundant and healthy food. Thus, it is the availability of food, the accessibility to this food, the proper use, and the stability and safety of supplies (Amrani, 2021). Ambitious public policies put in place in terms of irrigation, energy and infrastructure development, also associated with the emergence of local economic dynamics, have allowed an extraordinary development of agriculture, especially in the Saharan regions, thus aiming to modernize agriculture with the purpose of increasing and stabilizing agricultural and food production (Bencharif, 2018). Benefiting from these incentives, in favor of Saharan agricultural projects, the increasing aggregation of the population in urban centers and, subsequently, the growth of consumer markets, stimulate the economic development of the entire region (Kouzmine et al., 2009).
Drought is a natural disaster with severe global agricultural and economic impacts. Accurate drought indices are needed for improved assessment and monitoring; however, most existing drought indices poorly represent agricultural drought due to complex interactions among meteorological factors, crop and soil conditions. Here, we compute an integrated drought condition index (IDCI) based on the 3-month standardized precipitation evapotranspiration index (SPEI3), vegetation cover index (VCI) and soil moisture condition index (SMCI). We apply the IDCI to monitoring agricultural drought in Xinjiang, China. After regional evaluations with soil moisture, precipitation and air temperature observations, as well as with the scaled crop yields index, the IDCI was used to describe spatiotemporal changes in regional drought in Xinjiang during 2000–2018, revealing adverse impacts on crop yield (beet, wheat and vegetables). The IDCI is strongly correlated with observed soil moisture and performs better than SMCI, VCI or SPEI3, demonstrating that the IDCI is suitable for agricultural drought monitoring. The most severe drought occurred in the spring to autumn of 2008. Droughts before 2008 were more serious than those after 2008, in terms of both severity and frequency. Droughts in northern, southern and eastern Xinjiang, as well as in the Tianshan Mountains, were generally increasing before 2008 and then weakened after 2008.
Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA‐GPP) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA‐GPP relationship (RWA‐GPP) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near‐infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance–light‐use efficiency GPP. We found that the 3‐ and 7‐year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17‐ and 40‐year time scales (7.28% and 8.23%). The long‐term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA‐GPP and RWA‐GPP with different source products: In high‐latitude regions, RWA‐GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid‐low latitudes. Forests had weak RWA‐GPP at all time scales, shrublands showed negative RWA‐GPP at long time scales, and grassland (GL) showed a positive RWA‐GPP at short time scales. Globally, the EWA‐GPP, whether positive or negative, enhanced significantly at 3‐, 7‐, and 17‐year time scales. For arid and humid zones, the semi‐arid and sub‐humid zones experienced a faster increase in the positive EWA‐GPP, whereas the humid zones experienced a faster increase in the negative EWA‐GPP. At the ecosystem types, the positive EWA‐GPP at a 3‐year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA‐GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA‐GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change.
This study provides a method for analyzing the drought-vulnerability index (DVI) from a multidimensional perspective that includes biophysical and social aspects, considering the Intergovernmental Panel on Climate Change’s (IPCC) assessment. The proposed method generates the “exposure index (EI)”, “sensitivity index (SI)”, and “adaptive capacity index (ACI)” components of the proposed DVI using nine sub-indicators and 29 proxy variables. By using it throughout all of Turkey’s provinces, the performance of the developed index was evaluated. In this study, the decision matrices were built utilizing expert knowledge, and the weights of the indicators and variables were obtained by using the Analytical Hierarchy Process (AHP) technique. Moreover, the values of these four indices were classified as “very high, high, moderate, low, and very low,” and their geographical distribution across the country was drawn, as well as relevant patterns retrieved. The study’s major results show that 17 of the 81 provinces are classified as “very high,” 16 as “high,” 15 as “moderate,” 17 as “low,” and the remaining 16 as “very low” drought vulnerable. Another significant result is that the majority of people in the country’s south, center, and southeast rely on agriculture and are thus more vulnerable to drought due to socioeconomic underdevelopment in those regions.
Iran experienced increasing droughts in recent years. Since droughts have devastating effects on the economy and irreparable impacts on the environment, knowing the factors affecting droughts can effectively help their early warning and loss reduction. The present study used Palmer Drought Severity Index (sc-PDSI) and large-scale atmospheric indices (ENSO, IOD) to examine how various factors affected drought (precipitation, temperature, evapotranspiration, VPD, NDVI) in eight regions of Iran from 1981 to 2020. Results revealed that the northwest and southeast of Iran experienced longer duration and more severe droughts in the last 40 years. There is an increase in annual total precipitation and average daily temperature in all regions of Iran. The vegetation cover has changed slightly; however, its density has increased on the Caspian Sea shores due to increased rainfall. Correlation analysis revealed ENSO as Iran’s primary driver of droughts, while the IOD affects sc-PDSI only in the central plateau. Besides, the ENSO significantly affects the vegetation changes in Iran. General trends in precipitation, temperature, evapotranspiration, VPD, NDVI, and sc-PDSI indicate northwest Iran as most prone to drought.
Fire is a critical driver of giant sequoia (Sequoiadendron giganteum [Lindl.] Buchholz) regeneration. However, fire suppression combined with the effects of increased temperature and severe drought have resulted in fires of an intensity and size outside of the historical norm. As a result, recent mega-fires have killed a significant portion of the world’s sequoia population (13 to 19%), and uncertainty surrounds whether severely affected groves will be able to recover naturally, potentially leading to a loss of grove area. To assess the likelihood of natural recovery, we collected spatially explicit data assessing mortality, crown condition, and regeneration within four giant sequoia groves that were severely impacted by the SQF- (2020) and KNP-Complex (2021) fires within Sequoia and Kings Canyon national parks. In total, we surveyed 5.9 ha for seedlings and assessed the crown condition of 1140 trees. To inform management, we used a statistical methodology that robustly quantifies the uncertainty in inherently ‘noisy’ seedling data and takes advantage of readily available remote sensing metrics that would make our findings applicable to other burned groves. A loss of giant sequoia grove area would be a consequence of giant sequoia tree mortality followed by a failure of natural regeneration. We found that areas that experienced high severity fire (above ~800 RdNBR) are at substantial risk for loss of grove area, with tree mortality rapidly increasing and giant sequoia seedling density simultaneously decreasing with fire severity. Such high severity areas comprised 17.8, 142.0, 14.6, 1.6 hectares and ~90%, ~14%, ~53%, and ~27% of Board Camp, Redwood Mountain, Suwanee, and New Oriole Lake groves, respectively. In all sampling areas, we found that seedling densities fell far below the average density measured after prescribed fires, where seedling numbers were almost certainly adequate to maintain giant sequoia populations and postfire conditions were more in keeping with historical norms. Importantly, spatial pattern is also important in assessing risk of grove loss, and in two groves, Suwanee and New Oriole Lake, the high severity patches were not always contiguous, potentially making some areas more resilient to regeneration failure due to the proximity of surviving trees.
A new multiscale Standardized Precipitation Evapotranspiration Index (SPEI) dataset is provided for a reference period (1960–1999) and two future time horizons (2040–2079) and (2060–2099). The historical forcing is based on combined climate observations and reanalysis (WATer and global CHange Forcing Dataset), and the future projections are fed by the Fast Track experiment of the Inter-Sectoral Impact Model Intercomparison Project under representative concentration pathways (RCPs) 4.5 and 8.5 and by an additional Earth system model (CMCC-CESM) forced by RCP 8.5. To calculate the potential evapotranspiration (PET) input to the SPEI, the Hargreaves–Samani and Thornthwaite equations were adopted. This ensemble considers uncertainty due to different climate models, development pathways, and input formulations. The SPEI is provided for accumulation periods of potential moisture deficit from 1 to 18 months starting in each month of the year, with a focus on the within-period variability, excluding long-term warming effects on PET. In addition to supporting drought analyses, this dataset is also useful for assessing wetter-than-normal conditions spanning one or more months. The SPEI was calculated using the SPEIbase package.
Dataset:https://doi.org/10.25424/cmcc-mfd5-t060 (accessed on 3 February 2023).
Dataset License: The dataset is made available under license CC-BY.
Selection of forage and habitats is driven by nutritional needs of individuals. Some species may sacrifice nutritional quality of forage for the mother in favor of safety of offspring (risk-averse strategy), immediately following parturition. We studied diet quality and forage selection by bighorn sheep before and following parturition to determine how nutritional demands associated with rearing offspring influenced forage acquisition. We used desert bighorn sheep, Ovis canadensis nelsoni, to investigate that potential tradeoff. We captured and radio-collared female bighorn sheep from 2016 to 2018. We used vaginal implant transmitters (VIT)s in pregnant females to identify parturition and to capture and radio-collar neonates to monitor survival of young. We collected fecal samples throughout the breeding season and throughout the year to understand diet quality and composition throughout those temporal periods. We determined diet quality and composition for pre-parturient females, females provisioning offspring, females that lost offspring, and non-pregnant individuals using fecal nitrogen and DNA metabarcoding analyses. Additionally, we compared the diet quality and composition of offspring and adult females during the spring, as well as summer and winter months. Our results indicated differences in diet quality between individuals provisioning offspring and those whose offspring had died. Females that were provisioning dependent young had lower quality diets than those that lost their offspring. Diet composition among those groups was also markedly different; females that had lost an offspring had a more diverse diet than did females with dependent young. Diet quality differed among seasons, wherein offspring and adult females had higher quality diets during the spring months, with decreasing quality as the year progressed. Diet diversity was similar across seasons, although spring months tended to be most diverse. Our results support tradeoffs associated with risk-averse strategies made by adult females associated with parturition. Nutritional quality of forage was linked to provisioning status, indicating that females were trading diet quality for safety of offspring, but those females whose offspring had died selected high quality forages. Those results help explain habitat selection observed in mountain ungulates around parturition and provide further insight into the evolutionary processes and adaptive significance exhibited by those specialized artiodactyls.
Drought and wetness events have become common due to global warming, warranting the need for continuous analysis and monitoring of drought and wet events to safeguard people’s livelihoods. In this study, the Standardized Precipitation Evapotranspiration Index (SPEI) was utilized to analyze the spatiotemporal characteristics of drought and wetness events in the coastal Savannah agroecological zone from 1981 to 2021. Climate data from 14 locations across the zone were used to characterize drought and wetness events at the 3 and 12 month timescales. Except for September 1995 and November 2002, when changepoints occurred, the results revealed the homogeneous nature of temperature and rainfall in the zone. More drought events were observed in the dry and minor seasons, while the wet season had more wetness events under both the SPEI-3 and SPEI-12 timescales. The results also showed that, while moderate-to-severe drought events were common for most years, extreme drought events were more typical in the 1980s and 1990s than in the 2000s under both the SPEI-3 and SPEI-12. Furthermore, the 2000s saw more moderate-to-severe wetness events than the 1980s and 1990s, while the greatest number of extreme wetness events occurred in 1987, followed by 1997 and 2021 under the SPEI-3, and a few moderate-to-extreme wetness events occurred in 1987, 1991, 1997–1998, 2012–2013, 2018, and 2020–2021 under the SPEI-12. Under the SPEI-12, only extreme drought events showed a significant positive trend with a small magnitude of change. On the spatial scale, drought and wetness events occurred more frequently in the Central and Volta regions than in the Greater Accra region; however, the intensity and duration of the events were stronger and lasted longer in the Greater Accra and Central regions than in the Volta region. The regular monitoring of drought and wetness events is required to protect the livelihoods of people in the zone.
Wetlands are important environmental resources that are vulnerable to droughts and floods. Studying drought-flood events and their driving factors is essential for wetland resource planning and management. However, climate change and human activities present dynamic challenges that traditional approaches are unable to simulate dynamically in a rapidly changing environment. This makes quantitative analysis difficult. Our research focused on the innovative use of the data stream model, namely online bagging of Hoeffding adaptive trees, to quantify drought and flood drivers in response to climate change and human activity. The proposed approach was applied to a river-lake system, the Dongting Lake wetland. The frequency and duration characteristics of drought-flood events were analyzed. In addition, the cyclical changes of droughts and floods were analyzed by wavelet analysis. Then, drought-flood indicators as well as climatic and hydrological factors were entered into a dynamic data stream model for quantitative calculations. The results showed that the water conservancy projects largely reduced flood events while aggravating droughts. The frequency of floods decreased by 4.91% and the frequency of droughts increased by 6.81% following the construction of the Gezhouba Hydro-project and the Three Gorges Dam. Precipitation and Sankou streamflow were two dominant factors in the Dongting Lake drought and flood events, both of which had a feature importance value of approximately 0.3. This research showed how the data stream model can be used in a changing environment and the applicability of the conclusions reached through real-world instances. Moreover, these quantitative outputs can help in the sustainable utilization of Dongting Lake wetland resources.
The South Asian region is prone to extreme weather annually resulting in loss of lives and damage to the properties. While some people have attributed the cause of such events to the global warming and climate change, the fact is that the anomalous weather is a result of the changes in the three-dimensional structures of the atmosphere. While predicting the extreme weather events at precise location, intensity and lead time have been a challenge to the Meteorologists due to the limit of the deterministic forecasts, our observation system should be able to sense the changes in the structure of the atmosphere and the numerical weather prediction models should be able to provide accurate solutions to the future state of the atmosphere with usable skills. Accurate prediction of the extreme weather events requires observations of 3-dimensional structure of atmosphere at good temporal and spatial resolutions, applications of numerical models at cloud-resolving scale, and high-performance computing resources. The observations are required several times a day on routine basis from different sources such as satellites, radars, aircrafts, radiosonde balloons, automatic weather stations, surface meteorological observatories over land, and ocean from ships, and buoys. A review of the challenges faced by the Meteorologists in predicting the extreme weather events over the South Asian region is presented in this article.KeywordsExtreme weatherSouth AsiaStormPredictionModelingNWP
Drought monitoring systems are real‐time information systems focused on drought severity data. They are useful for determining the drought onset and development and defining the spatial extent of drought at any time. Effective drought monitoring requires databases with high spatial and temporal resolution and large spatial and temporal coverage. Recent reanalysis datasets meet these requirements and offer an excellent alternative to observational data. In addition, reanalysis data allow better quantification of some variables that affect drought severity and are more seldom observed. This study presents a global drought dataset and a monitoring system based on the Standardized Precipitation Evapotranspiration Index (SPEI) and ERA5 reanalysis data. Computation of the atmospheric evaporative demand for the SPEI follows the FAO‐56 Penman‐Monteith equation. The system is updated weekly, providing near real‐time information at a 0.5° spatial resolution and global coverage. It also contains a historical dataset with the values of the SPEI at different time scales since January 1979. The drought monitoring system includes the assessment of drought severity for dominant crop‐growing areas. A comparison between SPEI computed from the ERA5 and CRU datasets shows generally good spatial and temporal agreement, albeit with some important differences originating mainly from the different spatial patterns of SPEI anomalies, as well as from employing long‐term climate trends for different regions worldwide. The results show that the ERA5 dataset offers robust results and supports its use for drought monitoring. The new system and dataset are publicly available at the link https://global‐drought‐crops.csic.es/ .
Paddlefish, Polyodon spathula (Walbaum), provide an important snagging and bowfishing fishery below Gavins Point Dam in South Dakota. During 2009-2020, snagging catch rates of paddlefish decreased below Gavins Point Dam to presumed “normal” lower pre-2004 levels, while bowfishing catch (harvest) rates significantly increased during 2000-2020. Because Paddlefish are highly migratory, both local (i.e., monthly gauge height, precipitation, and air temperature near Gavins Point Dam) and remote (difference in Mississippi and Missouri River discharge near their confluence) environmental conditions were used to explain variation in snagging catch rates and bowfishing harvest rates. Snagging catch rates were related to October gauge height, whereby deeper water in October led to decreased catch rates below Gavins Point Dam. Bowfishing harvest rates increased significantly after a 2016 regulation change moved the season from July 1 – July 31 to June 1 – June 30, likely because water clarity was greater in June than July. Mean annual air temperature and precipitation explained variation in bowfishing harvest rates prior to the 2016 regulation change. Our findings, the first to examine both snagging and bowfishing fisheries below Gavins Point Dam, suggest that local abiotic factors are likely more important than remote discharge for explaining variation in snagging catch rates and bowfishing harvest rates in the channelized Missouri River.
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.
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.
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