scholarly journals Concurrent wet and dry hydrological extremes at the global scale

Author(s):  
Paolo De Luca ◽  
Gabriele Messori ◽  
Robert L. Wilby ◽  
Maurizio Mazzoleni ◽  
Giuliano Di Baldassarre

Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman-Monteith model (sc_PDSI_pm) covering the period 1950–2014, at 2.5° horizontal resolution. We find that the land areas affected by extreme wet, dry and wet-dry events (i.e. geographically remote, yet temporally co-occurring wet or dry extremes) all display increasing trends with time, of which changes in dry and wet-dry episodes are significant (p-value

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1953 ◽  
Author(s):  
Seo ◽  
Lee

Drought is a complex phenomenon caused by lack of precipitation that affects water resources and human society. Groundwater drought is difficult to assess due to its complexity and the lack of spatio-temporal groundwater observations. In this study, we present an approach to evaluate groundwater drought based on relatively high spatial resolution groundwater storage change data. We developed an artificial neural network (ANN) that employed satellite data (Gravity Recovery and Climate Experiment (GRACE) and Tropical Rainfall Measuring Mission (TRMM)) as well as Global Land Data Assimilation System (GLDAS) models. The Standardized Groundwater Level Index (SGI) was calculated by normalizing ANN-predicted groundwater storage changes from 2003 to 2015 across South Korea. The ANN-predicted 25 km groundwater storage changes correlated well with both the in situ and the water balance equation (WBE)-estimated groundwater storage changes, with mean correlation coefficients of 0.87 and 0.64, respectively. The Standardized Precipitation–Evapotranspiration Index (SPEI), having an accumulation time of 1–6 months, and the Palmer Drought Severity Index (PDSI) were used to validate the SGI. The results showed that the SGI had a pattern similar to that of SPEI-1 and SPEI-2 (1- and 2-month accumulation periods, respectively), and PDSI. However, the SGI performance fluctuated slightly due to its relatively short study period (13 years) as compared to SPEI and PDSI (more than 30 years). The SGI, which was developed using a new approach in this study, captured the characteristics of groundwater drought, thus presenting a framework for the assessment of these characteristics.


2020 ◽  
Vol 11 (1) ◽  
pp. 251-266 ◽  
Author(s):  
Paolo De Luca ◽  
Gabriele Messori ◽  
Robert L. Wilby ◽  
Maurizio Mazzoleni ◽  
Giuliano Di Baldassarre

Abstract. Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global co-occurrence. We define these using the monthly self-calibrated Palmer Drought Severity Index based on the Penman–Monteith model (sc_PDSI_pm), covering the period 1950–2014, at 2.5∘ horizontal resolution. We find that the land areas affected by extreme wet, dry, and wet–dry events (i.e. geographically remote yet temporally co-occurring wet or dry extremes) are all increasing with time, the trends of which in dry and wet–dry episodes are significant (p value ≪ 0.01). The most geographically widespread wet–dry event was associated with the strong La Niña in 2010. This caused wet–dry anomalies across a land area of 21 million km2 with documented high-impact flooding and drought episodes spanning diverse regions. To further elucidate the interplay of wet and dry extremes at a grid cell scale, we introduce two new metrics: the wet–dry (WD) ratio and the extreme transition (ET) time intervals. The WD ratio measures the relative occurrence of wet or dry extremes, whereas ET quantifies the average separation time of hydrological extremes with opposite signs. The WD ratio shows that the incidence of wet extremes dominates over dry extremes in the USA, northern and southern South America, northern Europe, north Africa, western China, and most of Australia. Conversely, dry extremes are more prominent in most of the remaining regions. The median ET for wet to dry is ∼27 months, while the dry-to-wet median ET is 21 months. We also evaluate correlations between wet–dry hydrological extremes and leading modes of climate variability, namely the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO). We find that ENSO and PDO have a similar influence globally, with the former significantly impacting (p value < 0.05) a larger area (18.1 % of total sc_PDSI_pm area) compared to the latter (12.0 %), whereas the AMO shows an almost inverse pattern and significantly impacts the largest area overall (18.9 %). ENSO and PDO show the most significant correlations over northern South America, the central and western USA, the Middle East, eastern Russia, and eastern Australia. On the other hand, the AMO shows significant associations over Mexico, Brazil, central Africa, the Arabian Peninsula, China, and eastern Russia. Our analysis brings new insights on hydrological multi-hazards that are of relevance to governments and organizations with globally distributed interests. Specifically, the multi-hazard maps may be used to evaluate worst-case disaster scenarios considering the potential co-occurrence of wet and dry hydrological extremes.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Qian Wang ◽  
Yue Yang ◽  
Yangyang Liu ◽  
Linjing Tong ◽  
Qi-peng Zhang ◽  
...  

Abstract Quantitatively assessing the impacts of drought on grassland has significant implications to understand the degradation mechanism and prevention degraded grassland. In this study, we analyzed the relationship between grassland drought and grassland Net Primary Productivity (NPP) based on the self-calibrated Palmer Drought Severity Index (scPDSI) from 1982 to 2008. The results showed that the global grassland scPDSI value had a slightly increasing trend with the rate of 0.0119 per year (R2 = 0.195), indicating that the global grassland drought lighter to some extent during study period. Moreover, the correlation coefficient between annual grassland NPP and scPDSI was from −0.83 to 0.92. The grassland NPP decreased under mild drought from 1992 to 1996. Additionally, the correlation coefficient between scPDSI and NPP for each grassland type was: Closed Shrublands > Non-woody grassland > Savannas > Open Shrublands > Woody Savannas, indicating that drought had difference influences on the different grassland types. Our results might provide the underlying insights needed to be guide for the effects of extreme weather events on grassland NPP.


2018 ◽  
Vol 7 (7) ◽  
pp. 286 ◽  
Author(s):  
Hok Fok ◽  
Qing He

The monitoring of hydrological extremes requires water level measurement. Owing to the decreasing number of continuous operating hydrological stations globally, remote sensing indices have been advocated for water level reconstruction recently. Nevertheless, the feasibility of gravimetrically derived terrestrial water storage (TWS) and its corresponding index for water level reconstruction have not been investigated. This paper aims to construct a correlative relationship between observed water level and basin-averaged Gravity Recovery and Climate Experiment (GRACE) TWS and its Drought Severity Index (GRACE-DSI), for the Yangtze river basin on a monthly temporal scale. The results are subsequently compared against traditional remote sensing, Palmer’s Drought Severity Index (PDSI), and El Niño Southern Oscillation (ENSO) indices. Comparison of the water level reconstructed from GRACE TWS and its index, and that of remote sensing against observed water level reveals a Pearson Correlation Coefficient (PCC) above 0.90 and below 0.84, with a Root-Mean-Squares Error (RMSE) of 0.88–1.46 m, and 1.41–1.88 m and a Nash-Sutcliffe model efficiency coefficient (NSE) above 0.81 and below 0.70, respectively. The ENSO-reconstructed water levels are comparable to those based on remote sensing, whereas the PDSI-reconstructed water level shows a similar performance to that of GRACE TWS. The water level predicted at the location of another station also exhibits a similar performance. It is anticipated that the basin-averaged, remotely-sensed hydrological variables and their standardized forms (e.g., GRACE TWS and GRACE-DSI) are viable alternatives for reconstructing water levels for large river basins affected by the hydrological extremes under ENSO influence.


2020 ◽  
Vol 79 (3) ◽  
pp. 193-206 ◽  
Author(s):  
ZJ Suriano ◽  
DJ Leathers ◽  
AE Benjamin

Previous investigations have documented relationships between global-scale forcings and Northeast United States moisture conditions, yet the physical pathways from global-scale forcing to sub-regional moisture deficit or surplus are not well understood. This research uses eigenvector-based regionalization to confirm the existence of sub-regional moisture environments within the Northeast. Synoptic classification is used to derive daily weather types that impact these moisture environments, and evaluate the relationship between global and synoptic scales. The Palmer Drought Severity Index (PDSI) regionalization identifies 3 sub-regions across the Northeast with homogeneous moisture conditions including New England, the Eastern Great Lakes, and Mid-Atlantic Regions. All 3 regions’ PDSI conditions are predominantly associated with variations in precipitation, rather than thermal characteristics. The frequency of key precipitation-associated synoptic types can inform PDSI variability in the regions, where drier conditions are observed during growing seasons with a reduced frequency of precipitation-inducing synoptic types and an enhanced frequency of dry synoptic types. Variations in the frequencies of these synoptic types are partially explained by the phase of the various teleconnection patterns. In the case of the New England region, 14% of the variance in PDSI is explained by the frequency of synoptic type D2, and 12% of the variance in D2 is explained by variations in the Summer Atmospheric Drought Index. The New England region became significantly wetter (positive PDSI) from 1950 to 2016. This study suggests a partial cause of this trend is the increased and decreased frequencies of wet and dry synoptic types, respectively, both related to the phase of the Summer Atmospheric Drought Index.


Author(s):  
Ramla Khan ◽  
Hammad Gilani

AbstractUnlike most disasters, drought does not appear abruptly. It slowly builds over time due to the changes in different environmental and climatological factors. It is one of the deadly disasters that has plagued almost every region of the globe since early civilization. Droughts are scientifically being studied with the help of either simple or composite indices. At 500-m spatial resolution, this study presents global scale drought severity index (DSI), a composite index using Moderate Resolution Imaging Spectroradiometer (MODIS), 8-day temporal resolution evapotranspiration (ET), potential evapotranspiration (PET), and normalized difference vegetation index (NDVI). This index is mainly used to identify meteorological droughts and also has proven reliable for studying agriculture droughts. In this study, Google Earth Engine (GEE), a cloud-based geospatial data computational platform, is used for drought mapping and monitoring from 2001 to 2019. For annual DSI spatial maps, the statistical median is computed ranging from − 1 to + 1, which means drought struck or dry regions have values closer to negative, and wet zones have values near to positive. For the validity of DSI results, the findings are compared with available records of droughts struck in previous years. This study declares that continent-wise, Australia, Africa, and Asia have the most extreme and frequent drought events while South America and North America come a close second. Europe is the least affected by this particular weather event when compared to other continents.


2019 ◽  
Vol 4 (3) ◽  
pp. 608
Author(s):  
Suyastri Suyastri ◽  
Irvan Medison ◽  
Deddy Herman ◽  
Russilawati Russilawati

<p><em>Tingkat keparahan CAP adalah poin penting pengambilan keputusan perawatan pasien. Beberapa metode telah digunakan untuk menilai tingkat keparahan pneumonia seperti Pneumonia Severity Index (PSI), CURB-65, SMART-COP dan Expanded CURB-65. Metode tersebut memiliki kelebihan dan kekurangan. Expanded CURB 65 diusulkan menjadi metode yang lebih akurat untuk mengevaluasi keparahan pneumonia dan memprediksi kematian pasien CAP. Tujuan penelitian ini memprediksi keakuratan Expanded CURB  65 dibandingkan CURB 65 dan PSI. Penelitian kohort prospektif pada pasien CAP yang dirawat di RSUP Dr. M.Djamil Padang dari April sampai Oktober 2019. Tingkat keparahan CAP pada pasien dinilai menggunakan PSI, CURB 65, Expanded CURB 65, kemudian hasilnya dievaluasi berdasarkan keparahan. Data dianalisis menggunakan regresi logistik dengan CI 95% dan nilai p &lt;0,05 dianggap signifikan. Hasil penelitian pada 90 pasien sebagian besar laki-laki usia 53 tahun dengan komorbiditas terbanyak keganasan. Uji Pearson Chi aquare menunjukkan tidak ada hubungan antara tingkat keparahan berdasarkan CURB 65 dan luaran pengobatan (CI 95%, nilai p = 0,104). Sementara, PSI dan Expanded CURB 65 memiliki hubungan yang signifikan antara tingkat keparahan dan luaran (CI 95%, p=0,081 dan CI 95%, p= 0,046, masing-masing). Analisis multivariat menemukan Expanded CURB 65 lebih akurat dalam memprediksi luaran pasien CAP rawat inap (kappa =0,108 dan AUC=0,422).</em></p><p><em><br /></em></p><p><em><em>Severity of CAP is very important for site care decision inpatients. Several methods have been used to assess the severity of pneumonia such as Pneumonia Severity Index (PSI), CURB-65, SMART-COP and Expanded CURB-65. Those methods have advantages and disadvantages. Expanded CURB 65 is proposed to be more accurate method for evaluating pneumonia severity and predicting mortality in CAP. The aim of this study was to investigate the accuracy of Expanded CURB 65 compare to CURB 65 and PSI. Cohort prospective study was conducted for CAP patients who were hospitalized at RSUP Dr. M.Djamil Padang from April to October 2019. Patients was assesed for severity using PSI, CURB 65, Expanded CURB 65, then we evaluated it’s outcome. The data were analyzed by logistic regression with CI 95% and p value &lt;0,05 considered as statistically significant. We found 90 patients that predominantly males with an average age of 53 years, and the most common comorbidity is malignancy. There was no relationship between pneumonia severity by CURB 65 and outcome (CI 95%, p=0.104). PSI and Expanded CURB 65 had significant relationship between severity and outcome (CI 95%, p=0.081and CI 95%, p=0.046, respectively). Multivariate analysis showed the expanded CURB 65 was more accurate for predicting the outcome of CAP inpatients (kappa=0.108 and AUC= 0.422).</em></em></p>


2021 ◽  
Vol 206 ◽  
pp. 103187
Author(s):  
Matteo Tomei ◽  
Lorenzo Baraldi ◽  
Simone Calderara ◽  
Simone Bronzin ◽  
Rita Cucchiara

2021 ◽  
Author(s):  
Sinta Berliana S. ◽  
Indah Susanti ◽  
Bambang Siswanto ◽  
Amalia Nurlatifah ◽  
Hidayatul Latifah ◽  
...  

2010 ◽  
Vol 19 (1) ◽  
pp. 14 ◽  
Author(s):  
Katarzyna Grala ◽  
William H. Cooke

Forests constitute a large percentage of the total land area in Mississippi and are a vital element of the state economy. Although wildfire occurrences have been considerably reduced since the 1920s, there are still ~4000 wildfires each year in Mississippi burning over 24 000 ha (60 000 acres). This study focusses on recent history and various characteristics of Mississippi wildfires to provide better understanding of spatial and temporal characteristics of wildfires in the state. Geographic information systems and Mississippi Forestry Commission wildfire occurrence data were used to examine relationships between climatic and anthropogenic factors, the incidence, burned area, wildfire cause, and socioeconomic factors. The analysis indicated that wildfires are more frequent in southern Mississippi, in counties covered mostly by pine forest, and are most prominent in the winter–spring season. Proximity to roads and cities were two anthropogenic factors that had the most statistically significant correlation with wildfire occurrence and size. In addition, the validity of the Palmer Drought Severity Index as a measure of fire activity was tested for climatic districts in Mississippi. Analysis indicated that drought influences fire numbers and size during summer and fall (autumn). The strongest relationship between the Palmer Drought Severity Index and burned area was found for the southern climatic districts for the summer–fall season.


Sign in / Sign up

Export Citation Format

Share Document