scholarly journals Seasonal Drought Pattern Changes Due to Climate Variability: Case Study in Afghanistan

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1096 ◽  
Author(s):  
Ishanch Qutbudin ◽  
Mohammed Sanusi Shiru ◽  
Ahmad Sharafati ◽  
Kamal Ahmed ◽  
Nadhir Al-Ansari ◽  
...  
Keyword(s):  
Meteorological Drought ◽  
Research Unit ◽  
Trend Test ◽  
Drought Severity ◽  
Return Periods ◽  
Seasonal Drought ◽  
Growing Seasons ◽  
Drought Pattern ◽  
Cropping Seasons ◽  
Global Precipitation

We assessed the changes in meteorological drought severity and drought return periods during cropping seasons in Afghanistan for the period of 1901 to 2010. The droughts in the country were analyzed using the standardized precipitation evapotranspiration index (SPEI). Global Precipitation Climatology Center rainfall and Climate Research Unit temperature data both at 0.5° resolutions were used for this purpose. Seasonal drought return periods were estimated using the values of the SPEI fitted with the best distribution function. Trends in climatic variables and SPEI were assessed using modified Mann–Kendal trend test, which has the ability to remove the influence of long-term persistence on trend significance. The study revealed increases in drought severity and frequency in Afghanistan over the study period. Temperature, which increased up to 0.14 °C/decade, was the major factor influencing the decreasing trend in the SPEI values in the northwest and southwest of the country during rice- and corn-growing seasons, whereas increasing temperature and decreasing rainfall were the cause of a decrease in SPEI during wheat-growing season. We concluded that temperature plays a more significant role in decreasing the SPEI values and, therefore, more severe droughts in the future are expected due to global warming.

Analysis of Meteorological Drought Pattern During Different Climatic and Cropping Seasons in Bangladesh

2015 ◽  
Vol 51 (3) ◽  
pp. 794-806 ◽  
Author(s):  
Mahiuddin Alamgir ◽  
Shamsuddin Shahid ◽  
Manzul Kumar Hazarika ◽  
Syams Nashrrullah ◽  
Sobri Bin Harun ◽  
...  
Keyword(s):  
Meteorological Drought ◽  
Drought Pattern ◽  
Cropping Seasons

scholarly journals Developing Objective Operational Definitions for Monitoring Drought

2009 ◽  
Vol 48 (6) ◽  
pp. 1217-1229 ◽  
Author(s):  
Steven M. Quiring
Keyword(s):  
Water Conservation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Decision Makers ◽  
Drought Severity ◽  
Specific Method ◽  
The Standardized Precipitation Index ◽  
Spatially Variant ◽  
Objective Methodology

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

scholarly journals Seasonal drought prediction for semiarid northeastern Brazil: verification of six hydro-meteorological forecast products

2018 ◽  
Vol 22 (9) ◽  
pp. 5041-5056 ◽  
Author(s):  
José Miguel Delgado ◽  
Sebastian Voss ◽  
Gerd Bürger ◽  
Klaus Vormoor ◽  
Aline Murawski ◽  
...  
Keyword(s):  
Rainy Season ◽  
Meteorological Drought ◽  
Skill Score ◽  
Hydrological Drought ◽  
Northeastern Brazil ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará's research foundation for meteorology) and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation, (b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.

scholarly journals Seasonal Drought Induces Hydraulic Dysfunction, Not Carbohydrate Depletion, for Robinia Pseudoacacia in a Semi-humid Forest

2021 ◽  
Author(s):  
Qingyin Zhang ◽  
Xiaoxu Jia ◽  
Mingan Shao
Keyword(s):  
Drought Stress ◽  
Water Potential ◽  
Forest Decline ◽  
Robinia Pseudoacacia ◽  
Area Index ◽  
Drought Period ◽  
Humid Forest ◽  
Seasonal Drought ◽  
Growing Seasons ◽  
Hydraulic Failure

Abstract BackgroundShifts in rainfall patterns that are associated with climate change are likely to cause widespread forest decline in regions where droughts are predicted to increase in duration and severity. However, causes of forest decline and their physiological mechanisms remain unclear, particularly the roles of carbon metabolism and xylem function. To explore the response of hydraulic architecture and non-structural carbohydrates (NSC) traits under seasonal drought, we conducted a manipulation experiment in a Robinia pseudoacacia plantation in 2015 and 2016 in Loess Plateau of China. Sap-flow, leaf area index, water potential, non-structural carbohydrate concentrations, and hydraulics in different organs were measured. ResultsThe mean pre-dawn and midday leaf water potential after two growing seasons of drought stress was significantly lower (-2.2 MPa and -2.7 MPa, respectively) than those of control trees (-1.5 MPa and -2.0 MPa, respectively). Drought stress accelerated the loss of conductivity, and promoted the formation of narrow hydraulic safety margins, which indicated that hydraulic failure could be a good predictor of “physiological drought” in trees when subjected to two growing seasons of drought. Both sugar and starch concentrations in stems and roots were similar in all trees throughout the drought period, which indicated that trees maintained good coordination between carbon supply and demand when confronted with two growing seasons of drought.ConclusionsOur results emphasized that hydraulic failure plays the predominant role in causing tree death during highly intense drought, while whether "carbon starvation" occurs during tree mortality remains to be tested in longer (multi-year) but less intense drought.

scholarly journals Modeling, prediction and trend assessment of drought in Iran using standardized precipitation index

2018 ◽  
Vol 10 (1) ◽  
pp. 181-196 ◽  
Author(s):  
Mehdi Bahrami ◽  
Samira Bazrkar ◽  
Abdol Rassoul Zarei
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Occurrence Frequency ◽  
Natural Phenomenon ◽  
Drought Severity ◽  
Data Series ◽  
Climate Data ◽  
Seasonal Drought

Abstract Drought as an exigent natural phenomenon, with high frequency in arid and semi-arid regions, leads to enormous damage to agriculture, economy, and environment. In this study, the seasonal Standardized Precipitation Index (SPI) drought index and time series models were employed to model and predict seasonal drought using climate data of 38 Iranian synoptic stations during 1967–2014. In order to model and predict seasonal drought ITSM (Interactive Time Series Modeling) statistical software was used. According to the calculated seasonal SPI, within the study area, drought severity classes 4 and 3 had the greatest occurrence frequency, while classes 6 and 7 had the least occurrence frequency. Results indicated that the best fitted models were Moving-Average or MA (5) Innovations and MA (5) Hannan-Rissenen, with 60.53 and 15.79 percentage, respectively. On the other hand, results of the prediction as well, indicated that drought class 4 with the highest percentages, was the most abundant class over the study area and drought class 7 was the least frequent class. According to results of trend analysis, without attention to significance of them, observed seasonal SPI data series (1967–2014), in 84.21% of synoptic stations had a negative trend, but this percentage changes to 86.84% when studying the combination of observed and predicted simultaneously (1967–2019).

scholarly journals Elucidating Diverse Drought Characteristics from Two Meteorological Drought Indices (SPI and SPEI) in China

2020 ◽  
Vol 21 (7) ◽  
pp. 1513-1530 ◽  
Author(s):  
Lingcheng Li ◽  
Dunxian She ◽  
Hui Zheng ◽  
Peirong Lin ◽  
Zong-Liang Yang
Keyword(s):  
Clustering Algorithm ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Three Dimensional ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Severity ◽  
Severe Drought ◽  
Small Areas ◽  
Drought Characteristics

AbstractThis study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

Spatial analysis of return periods of hydrological drought of Nile River Basin

2020 ◽  
Author(s):  
Gizaw Mengistu Tsidu
Keyword(s):  
River Basin ◽  
Water Resource ◽  
Return Period ◽  
Arrival Time ◽  
Population Increase ◽  
Drought Severity ◽  
Nile River ◽  
Return Periods ◽  
The Mean ◽  
Nile River Basin

<p>The Nile River Basin has been vital source of water to Riparian countries in both upper and lower catchments of the Basin. However, the states in the lower catchment namely Sudan and Egypt have exploited this resource without significant competition from countries in the upper catchments in the past. Recently, due to population increase in the basin and climate change, there are some initiatives by Riparian States such as Ethiopia to use this vital water resource (e.g., for energy generation). Therefore, it is important to understand recurrent drought characteristics and its potential impacts on the water resource in the basin. Drought events in the Nile Basin have been extracted using run theory based on the Standardized Precipitation Evapotranspiration Index (SPEI) accumulated on the time scale of 12 months using CRU rainfall and evapotranspiration data, which covers the period 1901–2018. The drought events are characterized by four variables: duration, severity. Intensity and Inter-arrival time. The mean duration and severity of drought during the last 118 years over the Basin are generally short and moderate over upper catchments. Conversely, the mean duration various from 4 to 8 months and up to 14 months over the middle and lower catchments of the Basin respectively while the mean drought severity increases from -2 at upper catchment to -7 at lower catchment. Gamma, Weibull, Gamma and Exponential functions are then selected to describe the marginal distribution of severity, duration, intensity and inter-arrival time, respectively. The Gumbel–Hougaard Copula was used to construct the joint distribution of duration, severity, intensity and/or inter-arrival time. The results indicate that the return period is dependent on the location within the basin, variable type and the combination of variables. For extreme droughts with severity index of -10 and duration of 14 months, return periods are longer than 40 years over south parts of the Basin and it barely exceeds 25 years over northern parts of the Basin. Generally, the short return period is mainly distributed in lower catchments of the Basin. This study on the identification of spatial distributions of drought return periods across the Basin is therefore important for drought mitigation and strategic planning on the water resource.</p>

scholarly journals Efficiency of some meteorological drought indices in different time scales, case study: wadi Louza basin (NW-Algeria)

2016 ◽  
Vol 31 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Fayçal Djellouli ◽  
Abderrazak Bouanani ◽  
Kamila Baba-Hamed
Keyword(s):  
Meteorological Drought ◽  
Water Shortage ◽  
Operational Definition ◽  
Climatic Conditions ◽  
Drought Indices ◽  
Drought Severity ◽  
Time Step ◽  
Standardised Precipitation Index ◽  
Ground Conditions

AbstractDrought is an insidious hazard of nature in many parts of the world. It originates from persistent shortage of precipitation over a specific region for a specific period of time and has a conceptual and operational definition. Drought impact on some activity, group, or environmental sector depends on the extent of water shortage and ground conditions. Algeria and especially the western region has experienced several periods of drought over the last century, since 1975 to the present day. The most recent drought in 1981, 1989, 1990, 1992, 1994 and 1999 was characterized by its intensity and spatial extent. Drought is identified using various drought indices (meteorological, hydrological and agricultural). In this research, we focus on the meteorological drought, to assess the reliability of these indices under changing climatic conditions. Data was recorded for the period of 1980–2009 at wadi Louza catchment (NW-Algeria). For describing and monitoring drought severity periods, we calculated the correlation between both meteorological drought indices: Standardised Precipitation Index (SPI) and Effective Drought Index (EDI). The results show that the watershed of wadi Louza has experienced a severe meteorological drought. The correlation between meteorological drought indices was good for all time steps and the best was found for 9-month time step. The obtained results may provide some scientific support for fighting against droughts.

scholarly journals A New Global 0.5° Gridded Dataset (1901–2006) of a Multiscalar Drought Index: Comparison with Current Drought Index Datasets Based on the Palmer Drought Severity Index

2010 ◽  
Vol 11 (4) ◽  
pp. 1033-1043 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
S. Beguería ◽  
J. I. López-Moreno ◽  
M. Angulo ◽  
A. El Kenawy
Keyword(s):  
Spatial Resolution ◽  
Drought Index ◽  
Palmer Drought Severity Index ◽  
National Research Council ◽  
Severity Index ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Drought Severity ◽  
Spatial And Temporal Variability ◽  
Drought Severity Index

Abstract A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI). The presented dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained using the Climatic Research Unit (CRU) TS3.0 dataset at a spatial resolution of 0.5°. The advantages of the new dataset are that (i) it improves the spatial resolution of the unique global drought dataset at a global scale; (ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI; and, in particular, (iii) it enables the identification of various drought types, given the multiscalar character of the SPEI. The dataset is freely available on the Web page of the Spanish National Research Council (CSIC) in three different formats [network Common Data Form (netCDF), binary raster, and plain text].

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