Monitoring multiscale drought using remote sensing in a Mediterranean arid region.

2021 ◽  
Author(s):  
Hadri Abdessamad ◽  
Saidi Mohamed El Mehdi ◽  
Boudhar Abdelghani
Keyword(s):  
Remote Sensing ◽  
Time Scale ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Severity ◽  
Landsat Images ◽  
Entire Study ◽  
Vegetation Activity ◽  
The Standardized Precipitation Index ◽  
Entire Study Area

<p>During the last few decades, the frequency of drought has significantly increased in Morocco especially for arid and semi-arid regions, leading to a rising of several environmental and economic issues. In this work, we analyse the spatial and temporal relationship between vegetation activity and drought severity at different moments of the year, across an arid area in the western Haouz plain in Morocco. Our approach is based on the use of a set of more than thirty satellite Landsat images data acquired for the period from 2008 to 2017, combined with the Standardized Precipitation Index (SPI) at different time scales and Standardized water-level Index (SWI). The Mann-Kendall and Sen’s slopes methods were used to estimate SPI trends and the Pearson correlation between NDVI and SPI were calculated to assess the sensitivity of vegetation types to drought. Results demonstrated that SPI experienced an overall upward trend in the Chichaoua-Mejjate region, except for 3-months time scale SPI in summer. The vegetation activity is largely controlled by the drought with clear differences between seasons and timesclaes at which drought is assessed. Positives correlations between the NDVI and SPI are dominant across the entire study area except in June when almost half of correlations is negative. More than 80% of the study domain exhibit a correlation exceeding 0.4 for SPI3 and SPI6 in March. Importantly, this study stresses that the irrigation status of land can introduce some uncertainties on the remote sensing drought monitoring. A weak correlation between the SPI and the SWI was observed at different time-scale. The fluctuations of the piezometric levels are strongly affected by the anthropogenic overexploitation of aquifers and proliferation of irrigated plots.</p>

scholarly journals Relationship between meteorological and hydrological droughts in the upstream regions of the Lancang–Mekong River

2021 ◽  
Author(s):  
Jiqiu Li ◽  
Yinfei Wang ◽  
Yungang Li ◽  
Wenting Ming ◽  
Yunshu Long ◽  
...  
Keyword(s):  
Time Scale ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Mekong River ◽  
Propagation Time ◽  
Wet Season ◽  
Evolution Characteristics ◽  
The Standardized Precipitation Index ◽  
The Relationship

Abstract Information on the relationship between meteorological drought (MD) and hydrological drought (HD) can serve as the basis for early warning and mitigation of HD. In this study, the standardized precipitation index and standardized streamflow index were applied to characterize MD and HD, respectively, and the evolution characteristics of MD and HD were assessed in the upstream regions of the Lancang–Mekong River (ULMR) from 1961 to 2015. Furthermore, the relationship between MD and HD was investigated using the Pearson correlation and wavelet analysis. The results revealed that (1) there was no significant change in the annual precipitation and streamflow; however, the ULMR experienced successive alternations of wet and dry episodes; (2) the average duration and magnitude of MD and HD increased with an increase in the time scale, while the duration and magnitude of MD lengthened and amplified in HD; (3) MD more likely propagated to HD as the time scale increased, and the propagation time exhibited marked seasonality, which was shorter in the wet season and longer in the dry season; and (4) there was a positive correlation between MD and HD; these two types of drought exhibited similar resonance frequency and phase-shift characteristics, and HD lagged behind MD.

scholarly journals A Hybrid Precipitation Index Inspired by the SPI, PDSI, and MCDI. Part I: Development of the Index

2020 ◽  
Vol 21 (9) ◽  
pp. 1945-1976 ◽  
Author(s):  
Dudley B. Chelton ◽  
Craig M. Risien
Keyword(s):  
Time Scale ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Precipitation Index ◽  
Drought Severity ◽  
Fading Memory ◽  
Hybrid Index ◽  
Weighted Averages ◽  
The Standardized Precipitation Index ◽  
Exponentially Weighted

AbstractThe filtering properties of the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and the model calibrated drought index (MCDI) are investigated to determine their relations to past, present, and future precipitation anomalies in regions with a wide diversity of precipitation characteristics. All three indices can be closely approximated by weighted averages of precipitation, but with different weighting. The SPI is well represented by one-sided, uniformly weighted averages; the MCDI is well represented by one-sided, exponentially weighted averages; and the PDSI is well represented by two-sided, exponentially weighted averages with much higher weighting of past and present precipitation than future precipitation. Detailed analyses identify interpretational complications and other undesirable features in the SPI and PDSI. In addition, the PDSI and MCDI are each restricted to single regionally specific “intrinsic” time scales that can significantly differ between the two indices. Inspired by the strengths of the SPI, PDSI, and MCDI, a hybrid index is developed that consists of exponentially weighted averages of past and present precipitation that are implicit in the PDSI and MCDI. The explicit specification of the exponential weighting allows users to control the time scale of the hybrid index to investigate precipitation variability on any time scale of interest. This advantage over the PDSI and MCDI is analogous to the controllability of the time scale of the SPI, but the exponentially fading memory is more physical than the uniform weighting of past and present precipitation in the SPI.

scholarly journals Night-Time Light Remote Sensing Mapping: Construction and Analysis of Ethnic Minority Development Index

2021 ◽  
Vol 13 (11) ◽  
pp. 2129
Author(s):  
Fei Zhao ◽  
Lu Song ◽  
Zhiyan Peng ◽  
Jianqin Yang ◽  
Guize Luan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Ethnic Group ◽  
Ethnic Groups ◽  
Ethnic Minorities ◽  
Population Data ◽  
Night Time ◽  
Entire Study ◽  
Development Index ◽  
Remote Sensing Mapping ◽  
Entire Study Area

Using toponym data, population data, and night-time light data, we visualized the development index of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups on ArcGIS as well as the distribution of 25 ethnic minorities in the study area. First, we extracted the toponym data of 25 ethnic minorities in the study area, combined with night-time light data and the population proportion data of each ethnic group, then we obtained the development index of each ethnic group in the study area. We compared the development indexes of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups with higher development indexes. The results show that the Yi nationality’s development index was the highest, reaching 28.86 (with two decimal places), and the Dai nationality’s development index was the lowest (15.22). The areas with the highest minority development index were concentrated in the core area of the minority development, and the size varied with the minority’s distance. According to the distribution of ethnic minorities, we found that the Yi ethnic group was distributed in almost the entire study area, while other ethnic minorities had obvious geographical distribution characteristics, and there were multiple ethnic minorities living together. This research is of great significance to the cultural protection of ethnic minorities, the development of ethnic minorities, and the remote sensing mapping of lights at night.

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

Water ◽  
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.

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 Long-Term, Gridded Standardized Precipitation Index for Hawai‘i

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 109
Author(s):  
Matthew P. Lucas ◽  
Clay Trauernicht ◽  
Abby G. Frazier ◽  
Tomoaki Miura
Keyword(s):  
High Spatial Resolution ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Drought Severity ◽  
Spatially Explicit ◽  
Historical Period ◽  
The Standardized Precipitation Index ◽  
Climatic Information

Spatially explicit, wall-to-wall rainfall data provide foundational climatic information but alone are inadequate for characterizing meteorological, hydrological, agricultural, or ecological drought. The Standardized Precipitation Index (SPI) is one of the most widely used indicators of drought and defines localized conditions of both drought and excess rainfall based on period-specific (e.g., 1-month, 6-month, 12-month) accumulated precipitation relative to multi-year averages. A 93-year (1920–2012), high-resolution (250 m) gridded dataset of monthly rainfall available for the State of Hawai‘i was used to derive gridded, monthly SPI values for 1-, 3-, 6-, 9-, 12-, 24-, 36-, 48-, and 60-month intervals. Gridded SPI data were validated against independent, station-based calculations of SPI provided by the National Weather Service. The gridded SPI product was also compared with the U.S. Drought Monitor during the overlapping period. This SPI product provides several advantages over currently available drought indices for Hawai‘i in that it has statewide coverage over a long historical period at high spatial resolution to capture fine-scale climatic gradients and monitor changes in local drought severity.

scholarly journals An Intercomparison of Drought Indicators Based on Thermal Remote Sensing and NLDAS-2 Simulations with U.S. Drought Monitor Classifications

2013 ◽  
Vol 14 (4) ◽  
pp. 1035-1056 ◽  
Author(s):  
Martha C. Anderson ◽  
Christopher Hain ◽  
Jason Otkin ◽  
Xiwu Zhan ◽  
Kingtse Mo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Standardized Precipitation Index ◽  
Fast Response ◽  
Rapid Onset ◽  
Cold Season ◽  
Stress Index ◽  
Drought Severity ◽  
Thermal Remote Sensing ◽  
Temporal Correlations ◽  
The North

Abstract Comparison of multiple hydrologic indicators, derived from independent data sources and modeling approaches, may improve confidence in signals of emerging drought, particularly during periods of rapid onset. This paper compares the evaporative stress index (ESI)—a diagnostic fast-response indicator describing evapotranspiration (ET) deficits derived within a thermal remote sensing energy balance framework—with prognostic estimates of soil moisture (SM), ET, and runoff anomalies generated with the North American Land Data Assimilation System (NLDAS). Widely used empirical indices based on thermal remote sensing [vegetation health index (VHI)] and precipitation percentiles [standardized precipitation index (SPI)] were also included to assess relative performance. Spatial and temporal correlations computed between indices over the contiguous United States were compared with historical drought classifications recorded in the U.S. Drought Monitor (USDM). Based on correlation results, improved forms for the ESI were identified, incorporating a Penman–Monteith reference ET scaling flux and implementing a temporal smoothing algorithm at the pixel level. Of all indices evaluated, anomalies in the NLDAS ensemble-averaged SM provided the highest correlations with USDM drought classes, while the ESI yielded the best performance of the remote sensing indices. The VHI provided reasonable correlations, except under conditions of energy-limited vegetation growth during the cold season and at high latitudes. Change indices computed from ESI and SM time series agree well, and in combination offer a good indicator of change in drought severity class in the USDM, often preceding USDM class deterioration by several weeks. Results suggest that a merged ESI–SM change indicator may provide valuable early warning of rapidly evolving “flash drought” conditions.

scholarly journals Evaluation of temporal drought variation and projection in a tropical river basin of Kerala

2020 ◽  
Vol 11 (S1) ◽  
pp. 115-132 ◽  
Author(s):  
M. A. Jincy Rose ◽  
N. R. Chithra
Keyword(s):  
River Basin ◽  
Standardized Precipitation Index ◽  
Drought Severity ◽  
Climate Projections ◽  
Severe Drought ◽  
Tropical River ◽  
The Past ◽  
Drought Conditions ◽  
The Future ◽  
The Standardized Precipitation Index

Abstract Temperature is an indispensable parameter of climate that triggers evapotranspiration and has vital importance in aggravating drought severity. This paper analyses the existence and persistence of drought conditions which are said to prevail in a tropical river basin which was once perennial. Past observed data and future climate projections of precipitation and temperature were used for this purpose. The assessment and projection of this study employ the Standardized Precipitation Evapotranspiration Index (SPEI) compared with that of the Standardized Precipitation Index (SPI). The results indicate the existence of drought in the past and the drought conditions that may persist in the future according to RCP 4.5 and 8.5 scenarios. The past drought years identified in the study were compared with the drought declared years in the state and were found to be matching. The evaluation of the future scenarios unveils the occurrence of drought in the basin ranging from mild to extreme conditions. It has been noted that the number of moderate and severe drought months has increased based on SPEI compared to SPI, indicating the importance of temperature in drought studies. The study can be considered as a plausible scientific remark helpful in risk management and application decisions.

Drought Monitoring of Southwestern China Using Insufficient GRACE Data for the Long-Term Mean Reference Frame under Global Change

2018 ◽  
Vol 31 (17) ◽  
pp. 6897-6911 ◽  
Author(s):  
Chuanpeng Zhao ◽  
Yaohuan Huang ◽  
Zhonghua Li ◽  
Mingxing Chen
Keyword(s):  
Reference Frame ◽  
Annual Cycle ◽  
Time Scale ◽  
Water Cycle ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Drought Monitoring ◽  
Drought Severity ◽  
Global Changes

Global changes, such as human activities and climate change, increase the odds of worsening drought. The Gravity Recovery and Climate Experiment (GRACE) satellite provides an opportunity to monitor drought levels by the total amount of water, instead of using a small finite set of water cycle elements or indirect indicators. The potential gap lies in the insufficient size of the GRACE record. The database does not meet the requirements of a stationary annual cycle calculated over a relatively long period as recommended by the IPCC, and the disturbance from long-term global changes is often not considered. In this work, a GRACE-based modulated water deficit (GRACE-MWD) process for drought monitoring under the modulated annual cycle (MAC) reference frame in southwest China was proposed. GRACE-MWD achieved a higher ratio of agreement with the standardized precipitation evapotranspiration index at a time scale of 3 months (SPEI03): it ranged from 0.48 to 0.84, while the GRACE-based drought severity index (GRACE-DSI) ranged from 0.48 to 0.68. Compared with remote sensing datasets widely used in drought monitoring, GRACE-MWD data are less affected by seasonality from land-cover categories, which benefit from the MAC reference frame. The ratio-of-agreement metric for the study area showed that GRACE-MWD had a time scale between 7 and 11 months in reference to SPEI and the standardized precipitation index (SPI). The stability of the MAC reference frame to GRACE-MWD was further discussed when GRACE records were extended and was more stable than that of the stationary annual cycle. GRACE-MWD meets global changes via an adaptive reference frame, which is worthy of generalizing to global applications.

Building Drought Index Based on AMSR-E Data - A Case Study in Hilly Area of Central Sichuan Basin

2013 ◽  
Vol 781-784 ◽  
pp. 2292-2295
Author(s):  
Qiong Lian Chen ◽  
Jing Wen Xu ◽  
Shao Wei Shi ◽  
Xin Li ◽  
Peng Wang
Keyword(s):  
Correlation Analysis ◽  
Sichuan Basin ◽  
Drought Index ◽  
Daily Precipitation ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Ratio Method ◽  
Hilly Area ◽  
Central Sichuan Basin ◽  
The Standardized Precipitation Index

Sichuan Hilly Area is selected as the study area. This paper uses ten brightness temperature AMSR-E data during 2006-2010. It constructs 8 preferred drought index by using the polarization ratio method (Polarization Rations, PR). This paper makes Pearson correlation analysis by using the 8 preferred drought index and the soil moisture of study area. Meanwhile, Linear regression and correlation analysis with the Daily precipitation and the standardized precipitation index SPI are also made. The results show: for example, in December 2009, drought index DI74, DI92, DI96 were basically consistent with the spatial distribution. Drought degree has an increasing trend from southeast to northwest regional gradually. And with the drought conditions in hilly area of actual and daily precipitation, SPI correlation between interannual and Sichuan are proper. So the drought index is more suitable for drought study in hilly area of central Sichuan Basin.

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