A Proxy Record of Drought Severity for the Southwestern Canadian Plains

Water is a critical natural resource that sustains the productivity of many economic sectors, whether directly or indirectly. Climate change alongside rapid growth and development are a threat to water sustainability and regional productivity. In this paper, we develop an extension to the economic input-output model to assess the impact of water supply disruptions to regional economies. The model utilizes the inoperability variable, which measures the extent to which an infrastructure system or economic sector is unable to deliver its intended output. While the inoperability concept has been utilized in previous applications, this paper offers extensions that capture the time-varying nature of inoperability as the sectors recover from a disruptive event, such as drought. The model extension is capable of inserting inoperability adjustments within the drought timeline to capture time-varying likelihoods and severities, as well as the dependencies of various economic sectors on water. The model was applied to case studies of severe drought in two regions: (1) the state of Massachusetts (MA) and (2) the US National Capital Region (NCR). These regions were selected to contrast drought resilience between a mixed urban–rural region (MA) and a highly urban region (NCR). These regions also have comparable overall gross domestic products despite significant differences in the distribution and share of the economic sectors comprising each region. The results of the case studies indicate that in both regions, the utility and real estate sectors suffer the largest economic loss; nonetheless, results also identify region-specific sectors that incur significant losses. For the NCR, three sectors in the top 10 ranking of highest economic losses are government-related, whereas in the MA, four sectors in the top 10 are manufacturing sectors. Furthermore, the accommodation sector has also been included in the NCR case intuitively because of the high concentration of museums and famous landmarks. In contrast, the Wholesale Trade sector was among the sectors with the highest economic losses in the MA case study because of its large geographic size conducive for warehouses used as nodes for large-scale supply chain networks. Future modeling extensions could potentially include analysis of water demand and supply management strategies that can enhance regional resilience against droughts. Other regional case studies can also be pursued in future efforts to analyze various categories of drought severity beyond the case studies featured in this paper.

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Analysis of wet and dry season by using the Palmer Drought Severity Index (PDSI) over Java Island

10.1063/5.0041843 ◽

2021 ◽

Author(s):

Sinta Berliana S. ◽

Indah Susanti ◽

Bambang Siswanto ◽

Amalia Nurlatifah ◽

Hidayatul Latifah ◽

...

Keyword(s):

Palmer Drought Severity Index ◽

Severity Index ◽

Dry Season ◽

Drought Severity ◽

Drought Severity Index

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Persistence and spatial–temporal variability of drought severity in Iran

Environmental Science and Pollution Research ◽

10.1007/s11356-021-14100-4 ◽

2021 ◽

Author(s):

Zahra Noorisameleh ◽

William A. Gough ◽

M. Monirul Qader Mirza

Keyword(s):

Temporal Variability ◽

Drought Severity

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Drought severity classification based on threshold level method and drought effects on NPP

Theoretical and Applied Climatology ◽

10.1007/s00704-020-03348-4 ◽

2020 ◽

Vol 142 (1-2) ◽

pp. 675-686

Author(s):

Jianzhu Li ◽

Keke Zhou ◽

Fulong Chen

Keyword(s):

Threshold Level ◽

Drought Severity ◽

Severity Classification ◽

Level Method ◽

Drought Effects

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Projection of Future Drought Characteristics under Multiple Drought Indices

Water ◽

10.3390/w13091238 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1238

Author(s):

Muhammad Imran Khan ◽

Xingye Zhu ◽

Xiaoping Jiang ◽

Qaisar Saddique ◽

Muhammad Saifullah ◽

...

Keyword(s):

Series Data ◽

Natural Phenomenon ◽

Drought Indices ◽

Drought Severity ◽

Severe Drought ◽

Drought Analysis ◽

Songhua River ◽

Drought Intensity ◽

Drought Characteristics ◽

Rcp 8.5

Drought is a natural phenomenon caused by the variability of climate. This study was conducted in the Songhua River Basin of China. The drought events were estimated by using the Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI) which are based on precipitation (P) and potential evapotranspiration (PET) data. Furthermore, drought characteristics were identified for the assessment of drought trends in the study area. Short term (3 months) and long term (12 months) projected meteorological droughts were identified by using these drought indices. Future climate precipitation and temperature time series data (2021–2099) of various Representative Concentration Pathways (RCPs) were estimated by using outputs of the Global Circulation Model downscaled with a statistical methodology. The results showed that RCP 4.5 have a greater number of moderate drought events as compared to RCP 2.6 and RCP 8.5. Moreover, it was also noted that RCP 8.5 (40 events) and RCP 4.5 (38 events) showed a higher number of severe droughts on 12-month drought analysis in the study area. A severe drought conditions projected between 2073 and 2076 with drought severity (DS-1.66) and drought intensity (DI-0.42) while extreme drying trends were projected between 2097 and 2099 with drought severity (DS-1.85) and drought intensity (DI-0.62). It was also observed that Precipitation Decile predicted a greater number of years under deficit conditions under RCP 2.6. Overall results revealed that more severe droughts are expected to occur during the late phase (2050–2099) by using RDI and SPI. A comparative analysis of 3- and 12-month drying trends showed that RDI is prevailing during the 12-month drought analysis while almost both drought indices (RDI and SPI) indicated same behavior of drought identification at 3-month drought analysis between 2021 and 2099 in the research area. The results of study will help to evaluate the risk of future drought in the study area and be beneficial for the researcher to make an appropriate mitigation strategy.

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Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽

10.3390/w13010082 ◽

2021 ◽

Vol 13 (1) ◽

pp. 82

Author(s):

Omolola M. Adisa ◽

Muthoni Masinde ◽

Joel O. Botai

Keyword(s):

South Africa ◽

South African ◽

Correlation Coefficient ◽

Pearson Correlation ◽

Standardized Precipitation Index ◽

Drought Monitoring ◽

Drought Indices ◽

Drought Severity ◽

Pearson Correlation Coefficient ◽

Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

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Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)

Remote Sensing ◽

10.3390/rs13091618 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1618

Author(s):

Melakeneh G. Gedefaw ◽

Hatim M. E. Geli ◽

Temesgen Alemayehu Abera

Keyword(s):

Time Series ◽

New Mexico ◽

Trend Analysis ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Rangeland Management ◽

Environmental Benefits ◽

Drought Severity ◽

Assessment Framework ◽

Rangeland Degradation

Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.

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