Spatial and Temporal Variation of Droughts in the Mongolian Plateau during 1959–2018 Based on the Gridded Self-Calibrating Palmer Drought Severity Index

Drought monitoring is challenging, but it is required for improving agricultural production, protecting the ecological environment, and reducing economic losses in drought-prone regions such as the Mongolian Plateau (MP). This study is a systematic analysis of the spatiotemporal changes in the characteristics of drought events (drought duration, severity, intensity, frequency, peak, and starting season) at the sub-regional scale between 1959 and 2018 based on the run theory and using the gridded self-calibrating Palmer Drought Severity Index (scPDSI) dataset. Principal component analysis and Varimax rotation and the Mann–Kendall trend and Sen’s slope were used for the sub-regional division and drought trend analysis, respectively. In addition, wavelet analysis was employed to analyze drought periodicity and determine the influence of large-scale climate indices on regional drought variation. The study results indicate clear differences in the spatial patterns of drought characteristics in the MP. The northern part suffered from droughts with longer duration and higher severity, whereas more drought events with shorter duration and less severity occurred in the southern part. Most of the MP experienced a relatively wet trend in 1996–2018 compared to the period of 1959–1995. The frequency of spring drought events showed an increasing trend in 1996–2018, unlike in 1959–1995. Some drought events simultaneously affected two or several sub-regions. The wavelet analysis results indicated that the drought periodicity in the MP was 10–64 months. The Arctic Oscillation (Pacific Decadal Oscillation) was significantly correlated with drought in the southern (northern) part.

Monitoring the evolution of drought conditions over Africa

Droughts have been found to have serious repercussions on humans, animals, and plants’ lives and they are likely to intensify under increasing global mean temperature. Monitoring drought conditions help in designing appropriate adaptations and mitigation strategies. This paper monitors the evolution of drought conditions in Africa over the past 30 years and the potential repercussions posed by this disaster event. We analyze and compare trends in surface temperatures, precipitation, soil moisture, Outgoing Longwave Radiation (OLR), and Palmer Drought Severity Index (PDSI). We use the NCEP/NCAR Reanalysis, the University of Delaware, the Climate Prediction Center (CPC), and the DAI PDSI gridded data for the period 1984-2014. Results from the NCEP/NCAR, University of Delaware, CPC, and the DAI PDSI gridded data show an increasingly warmer, drier, and less cloudy Sub-Saharan climate but with an intensification of the West African monsoon rainfall. Moreover, more than 80% of the continent shows strong evidence of droughts with an average increase in drought severity index. These conditions will likely have a negative effect on the agricultural sector which accounts for more than 70% of the Gross Domestic Product (GDP) of this region thereby posing a serious threat to regional food security. We recommend the research into and the development of new crop varieties that can tolerate higher temperatures and need less water. Additionally, our findings can also be used in Sub-Saharan Africa’s water management systems.

Evaluating the Performance of Palmer Drought Severity Index (PDSI) In Various Vegetation Regions of the Ethiopian Highlands

This paper focuses on the environment of Ethiopia, a country highly sensitive to droughts severely affecting vegetation. Vegetation monitoring of Ethiopian Highlands requires visualization of environmental parameters to assess droughts negatively influencing agricultural sustainable management of crops. Therefore, this study presented mapping of several climate and environmental variables including Palmer Drought Severity Index (PDSI). The data were visualized and interpreted alongside the topographic data to evaluate the environmental conditions for vegetation. The datasets included WorldClim and GEBCO and Digital Chart of the World (DCW). Research has threefold objectives: i) environmental mapping; ii) technical cartographic scripting; iii) data processing. Following variables were visualized on seven new maps: 1) topography; 2) soil moisture; 3) T °C minimum; 4) T °C maximum; 5) Wind speed; 6) Precipitation; 7) Palmer Drought Severity Index (PDSI). New high-resolution thematic environmental maps are presented and the utility of GMT for mapping multi-source datasets is described. With varying degrees of soil moisture (mean value of 15.0), min T°C (−1.8°C to 24°C), max T°C (14.4°C to 40.2°C) and wind speed (0.1 to 6.1 m/s), the maps demonstrate the variability of the PDSI fields over the country area (from −11.7 to 2.3) induced by the complex sum of these variables and intensified by the topographic effects notable over the Ethiopian Highlands which can be used for vegetation analysis. The paper presents seven new maps and contributes to the environmental studies of Ethiopia.

Fall Waterfowl Use of Bridgeport Reservoir, Mono County, California

Aerial surveys from 2003 to 2019 documented the abundance of waterfowl at Bridgeport Reservoir in Mono County, California, from September through mid-November. Waterfowl totals at Bridgeport Reservoir averaged 33,106 ± 4050 (standard error) in the fall. Annual peak counts averaged 10,474 ± 1349, ranging from a low of 2583 in 2014 to the highest single-day count of 23,150 in 2005. Bridgeport Reservoir is a man-made water body in the intermountain West that waterfowl use primarily a mid-migration stopover site, with peak numbers occurring in September. The dominant waterfowl species, the Northern Shoveler (Spatula clypeata), Gadwall (Mareca strepera), Mallard (Anas platyrhynchos), Northern Pintail (A. acuta), and Green-winged Teal (A. crecca), showed both unimodal and bimodal migration chronologies. Regional drought, as indicated by the Palmer drought severity index, combined with a downward trend in waterfowl numbers explained 61.4% of annual variation in fall waterfowl totals. These data may allow future assessment of change in waterfowl abundance at Bridgeport Reservoir in the context of local or regional conditions, and as influenced by climate change.

Analysis of the Influencing Factors of Drought Events Based on GRACE Data under Different Climatic Conditions: A Case Study in Mainland China

The occurrence of droughts has become more frequent, and their intensity has increased in mainland China. With the aim of better understanding the influence of climate background on drought events in this region, we analyzed the role of the drought-related factors and extreme climate in the formation of droughts by investigating the relationship between the drought severity index (denoted as GRACE-DSI) based on the terrestrial water storage changes (TWSCs) derived from Gravity Recovery and Climate Experiment (GRACE) time-variable gravity fields and drought-related factors/extreme climate. The results show that GRACE-DSI was consistent with the self-calibrating Palmer Drought Severity Index in mainland China, especially for the subtropical monsoon climate, with a correlation of 0.72. Precipitation (PPT) and evapotranspiration (ET) are the main factors causing drought events. However, they play different roles under different climate settings. The regions under temperate monsoon climate and subtropical monsoon climate were more impacted by PPT, while ET played a leading role in the regions under temperate continental climate and plateau mountain climate. Moreover, El Niño–Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) events mainly caused abnormalities in PPT and ET by affecting the strength of monsoons (East Asian and Indian monsoon) and regional highs (Subtropical High, Siberian High, Central Asian High, etc.). As a result, the various affected regions were prone to droughts during ENSO or NAO events, which disturbed the normal operation of atmospheric circulation in different ways. The results of this study are valuable in the efforts to understand the formation mechanism of drought events in mainland China.

Analyzing Trend and Pattern of Agricultural Drought: A Case Study of Karnali and Sudurpashchim Provinces

A drought is a period of time when an area or region experiences below-normal precipitation, with characteristics and impacts that can vary from region to region. Agricultural Drought analyzes and reflects the extent of the soil moisture and morphology of crop. Deficient rainfall in the winter of 2008 resulted in a severe drop in crop production right across the country. So, there is a necessity of assessment of drought events to make informed and timely decisions. The main focus of our study is to monitor the agricultural drought in Karnali and Sudurpashchim provinces of Nepal. The condition of drought in Karnali and Sudurpashchim provinces from 2001- 2020 were analysed with the help of Drought Severity Index. MODIS NDVI (MOD13) and MODIS ET-PET (MOD16) datasets were used to monitor and analyze the trend and pattern of agricultural drought scenario. Both datasets were then normalized for DSI calculation and the DSI result was used to monitor and to analyze the trend and pattern in the agricultural drought scenario. Further, trend and pattern analyses were performed in terms of landcover, ecological zones, and the variation of DSI. After completion of this project, we can conclude that the Maximum dryness was found in March, it might be due to less NDVI and increase in evapotranspiration rate and maximum wetness in November. Agricultural area experienced more drought variation than other landcover zones

Global drought monitoring with drought severity index (DSI) using Google Earth Engine

Unlike 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.

Studi Analisa Kekeringan Metode Standardized Precipitation Index (SPI) dan Palmer Drought Severity Index (PDSI) di DAS Kemuning Kabupaten Sampang

Kekeringan ialah bencana alam yang terjadi secara perlahan dan berdampak buruk untuk kelangsungan hidup penduduk Kabupaten Sampang. Mengingat hal tersebut, perlu dilakukan analisa indeks kekeringan serta pemetaan sebarannya sebagai upaya mitigasi bencana kekeringan. Studi ini bertujuan untuk mengetahui tingkat keparahan kekeringan dengan metode Standardized Precipitation Index (SPI) dan Palmer Drought Severity Index (PDSI), serta kesesuaiannya dengan data Southern Oscillation Index (SOI) yang mampu mempresentasikan kejadian El Nino Southern Oscillation (ENSO). Setelah itu, Indeks kekeringan yang lebih sesuai dengan pola SOI dipetakan dengan metode Inverse Distance Weighting (IDW) untuk mengetahui sebaran kekeringan. Metode SPI menghasilkan indeks kekeringan terparah di bulan April 2004 sebesar -3,651 pada periode defisit 1 bulanan. Metode PDSI menghasilkan indeks kekeringan terparah di bulan September 2001 sebesar - 20,628. Berdasarkan hasil analisa rerata PDSI periode 1998-2017, diketahui bahwa bencana kekeringan umumnya bermula sejak bulan Juli dan berakhir di bulan Oktober, sedangkan puncak kekeringan terjadi pada bulan September. Metode PDSI juga memiliki kesesuaian sebesar 60% terhadap nilai SOI berdasarkan penggambaran grafik surplus dan defisit indeks rerata tahunan, lebih baik daripada metode SPI yang hanya bernilai 53%. Penggambaran peta sebaran kekeringan berdasarkan indeks kekeringan PDSI menunjukkan bahwa Kecamatan Sampang, Torjun, dan Camplong perlu diprioritaskan dalam upaya mitigasi bencana kekeringan di masa mendatang karena memiliki potensi bencana kekeringan lebih besar jika dibandingan kecamatan lainnya.

The Association between Palmer Drought Severity Index Data and Tuberculosis-Like Lesions Occurrence in Mediterranean Hunted Wild Boars

In the Iberian Peninsula, the prevalence of tuberculosis differs for each region and for different wild disease hosts and the region affected by a Mediterranean climate will be the most affected. The Mediterranean Iberic regions have a favourable ecosystem for the development of Mycobacterium tuberculosis complex agents, where habitat, population dynamics, and climate (especially drought) are important factors affecting the high prevalence of tuberculosis in the wild boar population. Our objective was to study the association between the Palmer Drought Severity Index (PDSI) and the occurrence of tuberculosis-like lesions (TBL) in wild boar during nine hunting seasons (2008/09 to 2016/17) in Idanha-a-Nova County. To this end, statistical analysis revealed a significant association (p < 0.05) between the occurrence of TBL in wild boar in Idanha-a-Nova County and the analysed risk factor—previous season with periods of drought—which indicated that, when one season experiences some periods of drought, the probability of TBL occurrence in wild boars was 1.2 (OR = 1.2) times higher in the next hunting season than when there were no periods of drought. Therefore, our study contributes to the discovery of a positive effect of periods of drought on the transmission of tuberculosis in Iberian wildlife.