scholarly journals Frequently used drought indices reflect different drought conditions on global scale

2017 ◽  
Author(s):  
Niko Wanders ◽  
Anne F. Van Loon ◽  
Henny A. J. Van Lanen
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Hydrological Cycle ◽  
Meteorological Drought ◽  
Global Scale ◽  
Drought Indices ◽  
Drought Impacts ◽  
Drought Conditions ◽  
Suitable Index ◽  
Degraded Ecosystems

Abstract. Drought is an abnormal and prolonged deficit in available water. Possible drought impacts are crop losses, famine, fatalities, power blackouts and degraded ecosystems. These severe socio-economic and environmental impacts show the need to carefully monitor drought conditions using a suitable index. Our objective is to provide an intercomparison of frequently used physical drought indices to show to which degree they are interchangeable for monitoring drought in precipitation, soil moisture, groundwater and streamflow. Physical indices are commonly introduced to predict drought impacts, because appropriate drought impact indices are still missing. Correlations (R) between frequently used indices for different drought types were calculated at the global scale. We have made the index timeseries available to the community for future studies. Precipitation drought indices show low to intermediate correlations (ranging from R = 0.1 to 0.75), soil moisture drought indices show an even lower similarity (R = 0.25). Indices for streamflow drought show the highest correlation (R = 0.5 to 0.95). Additionally, meteorological drought indices do not capture the soil moisture drought correctly (R = 0.0 to 0.6) nor streamflow drought (R = 0.0 to 0.7). These findings have implications for drought monitoring systems: (i) for each drought type, a different index should carefully be identified; (ii) drought indices that are designed to monitor the same drought type show large discrepancies in their anomalies and hence drought detection; (iii) there is no single superior physical drought index that is capable of accurately capturing the diverse set of drought impacts in all parts of the hydrological cycle.

scholarly journals Development and Evaluation of an Agricultural Drought Index by Harnessing Soil Moisture and Weather Data

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1375 ◽  
Author(s):  
Ali Ajaz ◽  
Saleh Taghvaeian ◽  
Kul Khand ◽  
Prasanna H. Gowda ◽  
Jerry E. Moorhead
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Drought Index ◽  
Root Zone ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Growth Stages

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.

scholarly journals Exploring Drought Conditions in the Three River Headwaters Region from 2002 to 2011 Using Multiple Drought Indices

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 190 ◽  
Author(s):  
Keyi Wang ◽  
Tiejian Li ◽  
Jiahua Wei
Keyword(s):  
Comparative Study ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Condition Index ◽  
Drought Indices ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Drought Conditions ◽  
The Comparative Study

The Three River Headwaters Region (TRHR) has great uncertainty on drought conditions under climate change. The aim of this study is to compare the drought conditions detected by multiple drought indices across the TRHR. We applied four single drought indices, i.e., Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), and Vegetation Condition Index (VCI), and two combined drought indices, i.e., Combined Meteorological Drought Index (CMDI) and Combined Vegetation drought index (CVDI), to explore the drought conditions across the TRHR. Three in situ drought indices, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Non-Parametric Index (SNPI) were used to evaluate the performances of multiple drought indices. The results include various drought conditions detected by multiple drought indices, as well as a comparative study among different drought indices. Through the comparative study, we found that PCI was a desirable single index to monitor meteorological drought. TCI was suitable for monitoring agricultural/vegetation drought. SMCI and VCI should be avoided for monitoring drought in this region. CMDI was an appropriate meteorological drought index, and CVDI was a promising indicator in monitoring agricultural/vegetation drought.

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

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.

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

2011 ◽  
Vol 24 (8) ◽  
pp. 2025-2044 ◽  
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.

Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

2021 ◽  
Author(s):  
Dimmie Hendriks ◽  
Pieter Hazenberg ◽  
Jonas Gotte ◽  
Patricia Trambauer ◽  
Arjen Haag ◽  
...  
Keyword(s):  
Drought Index ◽  
Agricultural Drought ◽  
Data Sources ◽  
Drought Indices ◽  
Next Generation ◽  
Hazard Indices ◽  
Local Data ◽  
Drought Impacts ◽  
Drought Hazard ◽  
Impact Data

<p>An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.</p><p>Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.</p><p>The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.</p><p>We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.</p>

scholarly journals Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

2010 ◽  
Vol 14 (2) ◽  
pp. 271-277 ◽  
Author(s):  
E. Peled ◽  
E. Dutra ◽  
P. Viterbo ◽  
A. Angert
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Technical Note ◽  
Temperate Climate ◽  
Drought Indices ◽  
Soil Drought ◽  
The Past ◽  
Analysis Technique ◽  
Global Soil ◽  
Warm Temperate

Abstract. In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis) technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

scholarly journals Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3393
Author(s):  
Seon Woo Kim ◽  
Donghwi Jung ◽  
Yun-Jae Choung
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Drought Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Index Estimation ◽  
Cumulative Precipitation

Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiple linear regression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.

scholarly journals Assessment of spatiotemporal characteristics of agro-meteorological drought events based on comparing Standardized Soil Moisture Index, Standardized Precipitation Index and Multivariate Standardized Drought Index

2020 ◽  
Vol 11 (S1) ◽  
pp. 1-17 ◽  
Author(s):  
Muhammad Imran Khan ◽  
Xingye Zhu ◽  
Muhammad Arshad ◽  
Muhammad Zaman ◽  
Yasir Niaz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Moisture Index ◽  
Drought Characteristics ◽  
Soil Moisture Index ◽  
The Impact ◽  
Standardized Drought Index

Abstract Drought indices that compute drought events by their statistical properties are essential stratagems for the estimation of the impact of drought events on a region. This research presents a quantitative investigation of drought events by analyzing drought characteristics, considering agro-meteorological aspects in the Heilongjiang Province of China during 1980 to 2015. To examine these aspects, the Standardized Soil Moisture Index (SSI), Standardized Precipitation Index (SPI), and Multivariate Standardized Drought Index (MSDI) were used to evaluate the drought characteristics. The results showed that almost half of the extreme and exceptional drought events occurred during 1990–92 and 2004–05. The spatiotemporal analysis of drought characteristics assisted in the estimation of the annual drought frequency (ADF, 1.20–2.70), long-term mean drought duration (MDD, 5–11 months), mean drought severity (MDS, −0.9 to −2.9), and mild conditions of mean drought intensity (MDI, −0.2 to −0.80) over the study area. The results obtained by MSDI reveal the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. The results of this study provide valuable information and can prove to be a reference framework to guide agricultural production in the region.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

Can multi-scalar meteorological drought indices detect soil moisture droughts? A study of Indian regions

2021 ◽  
Author(s):  
Prabir Kumar Das ◽  
Sk Mohinuddin ◽  
Subrata Midya ◽  
Dilip Kumar Das ◽  
Richa Sharma ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Meteorological Drought ◽  
Drought Indices
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