Reconnaissance Drought Index Based Evaluation of Meteorological Drought Characteristics in Bundelkhand

Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.

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Analysis of meteorological droughts in the Lake’s Region of Ethiopian Rift Valley using reconnaissance drought index (RDI)

Geoenvironmental Disasters ◽

10.1186/s40677-021-00183-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yimer Mohammed ◽

Asnake Yimam

Keyword(s):

Rift Valley ◽

Drought Index ◽

Meteorological Drought ◽

Extreme Drought ◽

Trend Test ◽

Ethiopian Rift ◽

Negative Effects ◽

Reconnaissance Drought Index ◽

Spatio Temporal ◽

Temperature Records

AbstractThis study investigated the intensity, trend and spatio-temporal variability of meteorological drought in the Lakes’ Region of Ethiopian Rift Valley using monthly rainfall and maximum and minimum temperature records for the period 1986–2019. Reconnaissance Drought Index (RDI) was employed to generate the intensity of drought at 3 and 12-months timescale. Mann-Kendall trend test was used to determine the trend of the changes in the RDI time series. The spatial extent of droughts has been interpolated by inverse distance weighted (IDW) method using the spatial analyst tool of ArcGIS. Results indicated the occurrence of different intensity and trend signals across seasons and over space in the study area. A total of 33 extreme drought months were observed in all stations during summer with varying intensity (− 2.01 at Halaba to − 3.52 at Wolaita) and 168 extreme drought months at annual timescale ranging from − 2.10 at Hawassa to − 4.51 at Wolaita. The intensity of drought events observed in Wolaita in 1986 at all timescales (RDI value of − 3.19, − 3.52 and − 4.51 for spring, summer and annual respectively) were very extraordinary and devastating. Drought magnitude showed increasing signal at 6 out of 10 stations, although statistically significant at only two stations (Arsi Negelle at all timescale and Butajira at spring and annual timescale). However, the spatial patterns of drought events didn’t exhibit clear pattern rather more localized distribution and variability. The frequency of drought incidence became intense in the study area from 2008 onwards at all timescales compared to the 1990s and 2000s.The increasing tendency of drought in recent years might be the manifestation of borderless global warming. The empirical evidences showed that drought events and their negative effects are highly localized in the study area and provide useful information for local-scale planning for drought management and response.

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A Non-Stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model

10.21203/rs.3.rs-382218/v1 ◽

2021 ◽

Author(s):

Soumyashree Dixit ◽

K V Jayakumar

Keyword(s):

Drought Index ◽

Southern Oscillation ◽

Standardized Precipitation Index ◽

Precipitation Index ◽

Drought Indices ◽

Climate Indices ◽

Copula Model ◽

Reconnaissance Drought Index ◽

Drought Characteristics ◽

Recurrence Intervals

Abstract Under the variable climatic conditions, the conventional Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) are inadequate for predicting extreme drought characteristics. So in the present study, two indices namely, Non-stationary Standardized Precipitation Index (NSPI) and Non-stationary Reconnaissance Drought Index (NRDI) are developed by fitting non-stationary gamma (for precipitation series) and lognormal (for initial values,δ0) distributions. The Generalized Additive Model in Location, Scale and Shape (GAMLSS) framework, with time varying location parameters considering the external covariates, is used to fit the non-stationary distributions. This includes various large scale climate indices namely Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) as external covariates for the non-stationary drought assessment. The performances of stationary and non-stationary models are compared based on the Akaika Information Criterion (AIC). Additionally, the drought characteristics are evaluated using Run theory analysis for both stationary and non-stationary drought indices. The study also concentrated on the trivariate copula as well as the Pairwise Copula Construction (PCC) models to estimate the drought recurrence intervals. The comparison of two copula models revealed that the PCC model performed better than the trivariate Student’s t copula model. The recurrence intervals arrived at for the drought events are different for trivariate copula model and PCC model. The area taken for the study is the Upper and Lower sub basins of the Godavari River basin. This study shows that non-stationary drought indices will be helpful in the accurate estimate of the drought characteristics under the changing climatic scenario.

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Climate Variability Impact on the Spatiotemporal Characteristics of Drought and Aridityin Arid and Semi-Arid Regions

Water Resources Management ◽

10.1007/s11269-019-02397-3 ◽

2019 ◽

Vol 33 (15) ◽

pp. 5015-5033 ◽

Cited By ~ 3

Author(s):

Ruqayah Mohammed ◽

Miklas Scholz

Keyword(s):

Climate Variability ◽

Drought Index ◽

Potential Evapotranspiration ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Drought Indices ◽

Homogeneity Test ◽

Climate Data ◽

Reconnaissance Drought Index ◽

Semi Arid

AbstractInvestigating the spatiotemporal distribution of climate data and their impact on the allocation of the regional aridity and meteorological drought, particularly in semi-arid and arid climate, it is critical to evaluate the climate variability effect and propose sufficient adaptation strategies. The coefficient of variation, precipitation concentration index and anomaly index were used to evaluate the climate variability, while the Mann-Kendall and Sen’s slope were applied for trend analysis, together with homogeneity tests. The aridity was evaluated using the alpha form of the reconnaissance drought index (Mohammed & Scholz, Water Resour Manag 31(1):531–538, 2017c), whereas drought episodes were predicted by applying three of the commonly used meteorological drought indices, which are the standardised reconnaissance drought index, standardized precipitation index and standardized precipitation evapotranspiration index. The Upper Zab River Basin (UZRB), which is located in the northern part of Iraq and covers a high range of climate variability, has been considered as an illustrative basin for arid and semi-arid climatic conditions. There were general increasing trends in average temperature and potential evapotranspiration and decreasing trends in precipitation from the upstream to the downstream of the UZRB. The long-term analysis of climate data indicates that the number of dry years has temporally risen and the basin has experienced succeeding years of drought, particularly after 1994/1995. There was a potential link between drought, aridity and climate variability. Pettitt’s, SNHT, Buishand’s and von Neumann’s homogeneity test results demonstrated that there is an evident alteration in the mean of the drought and aridity between the pre- and post-alteration point (1994).

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Evaluation of Drought Characteristics Using the Reconnaissance Drought Index (RDI) over Parambikulam Aliyar Basin of Tamil Nadu

International Journal of Environment and Climate Change ◽

10.9734/ijecc/2020/v10i930246 ◽

2020 ◽

pp. 201-208

Author(s):

V. Guhan ◽

V. Geethalakshmi ◽

S. Panneerselvam ◽

A. Raviraj ◽

A. Lakshmanan ◽

...

Keyword(s):

Tamil Nadu ◽

Drought Index ◽

Potential Evapotranspiration ◽

Meteorological Data ◽

The Other ◽

Severe Drought ◽

Reconnaissance Drought Index ◽

Weather Forecasts ◽

Drought Characteristics ◽

Investigation Period

Drought tends to be a creeping phenomenon occurs gradually with the deficiency in rainfall further extending its impact on sectors which are dependent on water. The drought characteristics were analysed in Parambikulam Aliyar Project (PAP) basin based on the European Centre for Medium range Weather Forecasts Interim Reanalysis (ERA-Interim) gridded data with resolution of 0.125° ×0.125° during 1981-2017. Reconnaissance Drought Index (RDI) was applied for monitoring the drought. The variables used in RDI are rainfall and potential evapotranspiration (ETo), the required meteorological data were taken from the ERA Interim dataset and ETo was calculated using Penman-Monteith method. RDI indicated that 41% of the time had drought condition over 37 years. Two years (1982 and 2012) faced severe drought across all the parts of the PAP basin and the highest number of mild drought events were observed than the other drought conditions in PAP basin. Results showed that Plain areas in PAP basin experienced maximum number of drought events compared to the other areas in PAP basin during the investigation period.

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Different Drought Legacies of Rain-Fed and Irrigated Croplands in a Typical Russian Agricultural Region

Remote Sensing ◽

10.3390/rs12111700 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1700

Author(s):

Yuanhuizi He ◽

Fang Chen ◽

Huicong Jia ◽

Lei Wang ◽

Valery G. Bondur

Keyword(s):

Surface Temperature ◽

Drought Index ◽

Growth Period ◽

Meteorological Drought ◽

Agricultural Drought ◽

Drought Monitoring ◽

Growth Stages ◽

Drought Conditions ◽

Irrigated Lands ◽

Meteorological Droughts

Droughts are one of the primary natural disasters that affect agricultural economies, as well as the fire hazards of territories. Monitoring and researching droughts is of great importance for agricultural disaster prevention and reduction. The research significance of investigating the hysteresis of agricultural to meteorological droughts is to provide an important reference for agricultural drought monitoring and early warnings. Remote sensing drought monitoring indices can be employed for rapid and accurate drought monitoring at regional scales. In this paper, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and the surface temperature product are used as the data sources. Calculating the temperature vegetation drought index (TVDI) and constructing a comprehensive drought disaster index (CDDI) based on the crop growth period allowed drought conditions and spatiotemporal evolution patterns in the Volgograd region in 2010 and 2012 to be effectively monitored. The causes of the drought were then analyzed based on the sensitivity of a drought to meteorological factors in rain-fed and irrigated lands. Finally, the lag time of agricultural to meteorological droughts and the hysteresis in different growth periods were analyzed using statistical analyses. The research shows that (1) the main drought patterns in 2010 were spring droughts from April to May and summer droughts from June to August, and the primary drought patterns in 2012 were spring droughts from April to June, with an affected area that reached 3.33% during the growth period; (2) local drought conditions are dominated by the average surface temperature factor. Rain-fed lands are sensitive to the temperature and are therefore prone to summer droughts. Irrigated lands are more sensitive to water shortages in the spring and less sensitive to extremely high temperature conditions; (3) there is a certain lag between meteorological and agricultural droughts during the different growth stages. The strongest lag relationship was found in the planting stage and the weakest one was found in the dormancy stage. Therefore, the meteorological drought index in the growth period has a better predictive ability for agricultural droughts during the appropriately selected growth stages.

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Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

Journal of Climate ◽

10.1175/2010jcli3812.1 ◽

2011 ◽

Vol 24 (8) ◽

pp. 2025-2044 ◽

Cited By ~ 249

Author(s):

Martha C. Anderson ◽

Christopher Hain ◽

Brian Wardlow ◽

Agustin Pimstein ◽

John R. Mecikalski ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Drought Index ◽

Temporal Correlation ◽

Meteorological Drought ◽

Rainfall Data ◽

Added Value ◽

Stress Index ◽

Drought Indices ◽

Shallow Water Table

Abstract The reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

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