Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects
Abstract
:1. Introduction
2. Results
2.1. Types of Droughts
2.1.1. Meteorological Drought
2.1.2. Agricultural Drought
2.1.3. Hydrological Drought
2.1.4. Socio-Economic Drought
2.1.5. Ecological Drought
2.1.6. Groundwater Drought
2.1.7. Flash Drought
3. Socio-Economic and Environmental Impacts of Drought
3.1. Socio-Economic Impacts of Drought
- The most severe effects of the drought appeared to be economical, with significant effects on household income.
- Food insecurity and poor sanitation, spreading of more diseases lead to losses of life, result in the nation’s economic decline.
- Increasing joblessness rate due to the reduction in crop yields and the failure of business-related activities; less employment in the agriculture sector or other jobs in rural areas.
- The temporary dispersion of family members moving to the regions with economic opportunities, subpopulation, and urban enlargement might result in pollution and increasing criminal activity.
- Less water and de-vegetation of the landscape drive livestock to the lower number, when there might be many disasters that supplement droughts, such as soil erosion, wildfires, and heatwaves. All this affects both public health and wealth.
3.2. Environmental Impacts of Droughts
4. Drought’s Causes and Their Characteristics
4.1. Natural Causes of Drought
4.2. Artificial Causes of Drought
4.3. Drought Characteristics
5. Drought Indicators
6. Drought Indices and Their Effectiveness in Monitoring Drought
7. Discussion
7.1. Drought Risk Management and Mitigation
7.2. Preparedness
7.3. Mitigation Strategies
7.4. Reaction and Response
8. Recommendation and Future Directions
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Drought Index | Type of Drought | Parameters | Characteristics | Advances | Limitations | References Number in Manuscript for Each Index |
---|---|---|---|---|---|---|
CDI | Composite or modelled | Modelled, precipitation, satellite | Composed of three warning levels (watch, warning, and alert) by integrating three drought indicators: SPI, soil moisture and remotely sensed vegetation data. | The combination of remotely sensed and surface data make the spatial coverage to be good at a high resolution. | Difficult replication and not available for regions outside of Europe. | [122] |
CMI | Meteorology | Precipitation, temperature | It can determine any deficit by subtracting the difference between PET and moisture, it is intended to be suited to drought impacts on agriculture. | Respond quickly to rapidly changing conditions, the output is weighted, therefore it can compare different climate regions. | It was developed specifically for regions that produce grain in the United States of America, it may illustrate not a reliable sense of recovery from long-term drought incidents. | [78] |
CZI | Meteorology | Precipitation | Is used to determine wet and dry periods | Missing data are allowed, it can characterize bot wet and dry incidents, simple calculation. | Shorter timescales may be less well represented. | [80] |
DI | Meteorology | Precipitation | Simple calculation, it provides an accurate statistical measurement of precipitation. | It can be used in meteorological, agricultural, and hydrological drought. | A single input data | [116,117] |
EDDI | Agriculture | Temperature, humidity, wind speed, and net radiation | Thirst of the atmosphere | Focusing on evaporative demand. Can provide added value to other drought indicators, flash drought detection, and early warning. | Not directly measure on the ground conditions, not a drought predictor | [89] |
eRDI | Monthly Precipitation and temperature. | Inclusion of effective precipitation and PET | It is highly recommended to assess drought in hyper arid and arid regions. | Similar to RDI | [94,95] | |
ESI | Remote sensing | Satellite, potential evapotranspiration | It can use geostationary satellites to compare evapotranspiration to potential evapotranspiration. | Very high resolution with a spatial coverage of any region. | The results can be contaminated and affected by cloud cover. | [89] |
PSDI | Meteorology | Precipitation and temperature | It considers moisture from precipitation and moisture stored in the soil. | Applied around the world, its code and output are readily available, the ability to use soil data and total water balance makes it to be robust in identifying drought. | Requirement of serial complete data, complexity of computation. | [77] |
RDI | Meteorology | Monthly Precipitation and temperature. | It can define drought duration, severity and predict the start and the end of drought periods, and incorporation of evaporation. | The incorporation of PET provides a better representation of the full water balance of the specific region, it can better indicate the severity of drought, it can be computed at several time steps. | The calculations of PET can be subjected to errors when using temperature only to create the estimate. For rapid developing droughts, reaction is not quickly enough at monthly timescales. | [95,111,116] |
RAI | Meteorology | Precipitation | Utilizes normalized precipitation values depend on station history record of a given location. | Simple calculation, with a single input data, the analysis can be done based on annual, seasonal, and monthly timescales. | Serial complete dataset with estimates of missing values is required | [81,99] |
SPI | Meteorology | Precipitation | Easy calculations | SPI data can be compared between regions with different climate conditions. | A single input data | [75,86,88,91,99,100,103,107,108,112,114,116,117,118] |
SPEI | Meteorology | Precipitation and temperature | Multi-scalar index, Various methods of calculation. | Inclusion of PET allows it to account for the impact of temperature on a drought situation. | Require a long data record at least for 30 years. | [19,76,86,87,91,98,102,104,105,107,108,109,110,113,117,118,121] |
SPAEI | Hydro-meteorological | Precipitation and temperature | It can provide more insight in detecting the severe and extreme drought characteristics. | Inclusion of actual evapotranspiration. | It was first developed for India | [106] |
SDI | Hydrology | Streamflow | Investigation of dry and wet periods and severity of drought with an output related to that of SPI. | Easy to use and readily available program, missing data are allowed, Provision of more accurate results. | A single input data | [114] |
SRI | Hydrology | Runoff | Calculations similar to that of SPI. | It can investigate hydrological drought at various timescales and compare meteorological drought simultaneously at the same timescales. | A single input data | [117] |
PN | Meteorology | Precipitation | Simple calculations, can be computed at annual, seasonal, monthly, weekly, and daily timescales. | Quicky and easy to compute with basic mathematics. | It is very difficult to compare different climate regimes, especially those characterized by wet and dry seasons. | [99] |
VCI | Assess drought that affect agriculture | AVHRR satellite data | Focus on the impact of drought on vegetation and provide reliable information the characteristics of drought such as onset, duration, and severity by noticing vegetation changes and compering them with historical values. | High resolution and good spatial coverage. | Potential for cloud contamination and short period of record. | [93,109] |
TCI | Assess drought of vegetation in the conditions where agricultural impacts are the major concern. | AVHRR satellite data | It used to determine stress on vegetation provoked by temperature and extreme wetness, | High resolution and good spatial coverage. | Potential for cloud contamination short period of record. | [93] |
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Ndayiragije, J.M.; Li, F. Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects. Climate 2022, 10, 125. https://doi.org/10.3390/cli10090125
Ndayiragije JM, Li F. Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects. Climate. 2022; 10(9):125. https://doi.org/10.3390/cli10090125
Chicago/Turabian StyleNdayiragije, Jean Marie, and Fan Li. 2022. "Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects" Climate 10, no. 9: 125. https://doi.org/10.3390/cli10090125
APA StyleNdayiragije, J. M., & Li, F. (2022). Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects. Climate, 10(9), 125. https://doi.org/10.3390/cli10090125