Quantification of Drought Condition Using Drought Indices: A Review

Various drought indices have been developed to monitor drought conditions. Each index has typical characteristics that make it applicable to a specific environment. In this study, six popular drought indices, namely, precipitation condition index (PCI), temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), scaled drought condition index (SDCI), and temperature–vegetation dryness index (TVDI), have been used to monitor droughts in the Greater Changbai Mountains(GCM) in recent years. The spatial pattern and temporal trend of droughts in this area in the period 2001–2018 were explored by calculating these indices from multi-source remote sensing data. Significant spatial–temporal variations were identified. The results of a slope analysis along with the F-statistic test showed that up to 20% of the study area showed a significant increasing or decreasing trend in drought. It was found that some drought indices cannot be explained by meteorological observations because of the time lag between meteorological drought and vegetation response. The drought condition and its changing pattern differ from various land cover types and indices, but the relative drought situation of different landforms is consistent among all indices. This work provides a basic reference for reasonably choosing drought indices for monitoring drought in the GCM to gain a better understanding of the ecosystem conditions and environment.

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Study on the correlation between meteorological and agricultural drought, based on remotely sensed indices

10.5194/egusphere-egu2020-13925 ◽

2020 ◽

Author(s):

Ruja Mansorian ◽

Mohammad Zare ◽

Guy Schumann

Keyword(s):

Time Scales ◽

Vegetation Index ◽

Meteorological Drought ◽

Lag Time ◽

Irrigation Scheduling ◽

Agricultural Drought ◽

Standard Normal Distribution ◽

Drought Indices ◽

Landsat 8 ◽

Drought Condition

In this study, long-term time series of precipitation data were used for determining the drought condition using the standard precipitation index (SPI) for 3, 6 and 12 month time scales. The indicators were calculated with two methods: a) using a gamma distribution and transforming the probability of occurrence to standard normal distribution, b) using the non-parametric plotting position method. Then, the SPI values for two consequent years 2013-14 and 2014-15 were extracted from data to study on meteorological drought. The SPI index calculations showed that the first year had near normal, whereas the second year had extreme drought condition. In parallel, 34 Landsat 8 satellite images were downloaded during the indicated time period to determine normalized difference vegetation index (NDVI) and vegetation condition index (VCI) as agricultural drought indices. The mean values of VCI for each month were considered as representative value for drought condition of the area. When the agricultural and meteorological drought indices were determined, the correlation coefficient (r) were calculated for finding the relation between these types of droughts. the results show that the highest correlation between SPI-3,6 and 12-month time scales and VCI occurred in 4, 2 and 4 months lag time respectively, with corresponding r value of 0.67, 0.65 and 0.69. The best agreement between these indices with calculated lag time proves the hypothesis that agricultural drought occurs after meteorological drought. Therefore, the results could be applied by farmers to plan an appropriate irrigation scheduling for upcoming droughts, specially, in arid and semi-arid areas. It could be concluded that for having suitable planning in water scarcity condition, understanding the situation helps water planners have better insight about management polices to minimize the effects of this natural hazard on human. To sum up, finding a relation between different types of droughts is helpful for monitoring, predicting and detecting droughts to better prepare for drought phenomena and to minimize losses

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Mapping the Spatial and Temporal Variation of Agricultural and Metrological Drought Using Geospatial Techniques, Ethiopia

10.21203/rs.3.rs-70778/v1 ◽

2020 ◽

Author(s):

Abebe Senamaw ◽

Solomon Addisu ◽

K.V. Suryabhagavan

Keyword(s):

Temporal Variation ◽

Crop Yield ◽

Meteorological Drought ◽

Condition Index ◽

Agricultural Drought ◽

Spatial And Temporal Variation ◽

Drought Indices ◽

Drought Risk ◽

Drought Condition ◽

Gis And Remote Sensing

Abstract Background Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The objective of this study was to assess spatial and temporal variation of agricultural and metrological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI). To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as SPI and crop yield anomaly. The results revealed that the year 2009 and 2015 were drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r=0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map. ResultThe result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56%, 35% and 8% of study area were vulnerable to very severe, severe and moderate drought condition respectively. Conclusion In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. Thus besides mapping drought vulnerable areas, integrating socioeconomic data for better understand other vulnerable factors were recommended.

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2008 kurak yılının Termessos (Güllük Dağı) Milli Parkı (Antalya) vejetasyonuna etkisinin çeşitli kuraklık indeksleriyle incelenmesi (Various Drought Indices for Monitoring Drought Condition in Mount Güllük Termessos National Park)

SSRN Electronic Journal ◽

10.2139/ssrn.3394246 ◽

2015 ◽

Author(s):

Mehmet Ali Çelik ◽

Murat Karabulut

Keyword(s):

National Park ◽

Drought Indices ◽

Drought Condition

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Synergy of Satellite-Derived Drought Indices for Agricultural Drought Quantification and Yield Prediction

Advances in Environmental Engineering and Green Technologies - Spatial Information Science for Natural Resource Management ◽

10.4018/978-1-7998-5027-4.ch007 ◽

2020 ◽

pp. 122-148

Author(s):

Dipti Ladli ◽

Kanhaiya Lal ◽

Kiran Jalem ◽

Avinash Kumar Ranjan

Keyword(s):

Condition Index ◽

District Level ◽

Drought Indices ◽

Yield Prediction ◽

Drought Condition ◽

Yield Model ◽

Yield Data ◽

Moderate Drought ◽

Vegetation Health Index ◽

Paddy Yield

The present study was conducted over Jharkhand state (India) for assessing the drought condition and corresponding yield of paddy (district-level) during Kharif 2018. Vegetation drought indices, namely Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), and vegetation indices (VI) anomaly, were derived from different VI (i.e., NDVI, EVI) to assess the paddy health condition during drought year (2018) and non-drought year (2017). Later, the correlation between the DES-based yield data and derived drought indices (for the year 2017) were made to develop the district-level paddy yield model for the drought year 2018. The key results of the study shown that VCI derived from EVI data was found to be more reasonable to depict the drought condition, wherein ~21% area was under severe drought condition, 43% area under moderate drought condition, and 36% area under no drought condition. In addition, the yield prediction model derived from VCI (EVI-based) was found to be promising for predicting the paddy yield for Kharif 2018 with fair R2 of 0.53.

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Mapping the spatial and temporal variation of agricultural and meteorological drought using geospatial techniques, Ethiopia

ENVIRONMENTAL SYSTEMS RESEARCH ◽

10.1186/s40068-020-00204-2 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Abebe Senamaw ◽

Solomon Addisu ◽

K. V. Suryabhagavan

Keyword(s):

Temporal Variation ◽

Crop Yield ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Precipitation Index ◽

Agricultural Drought ◽

Spatial And Temporal Variation ◽

Drought Indices ◽

Drought Risk ◽

Drought Condition

Abstract Background Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The aim of this study was to assess spatial and temporal variation of agricultural and meteorological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI) from the year 2000 to 2016. To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as standardized precipitation index (SPI) and crop yield anomaly. Results The results revealed that the year 2009 and 2015 was drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r = 0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map. The result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56% and 35% of the study area were vulnerable to very severe, severe and moderate drought condition respectively. Conclusions In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. There was also no year without drought in many parts of the study area. Thus besides mapping drought vulnerable areas, integrating socio-economic data for better understand other vulnerable factors were recommended.

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Practical tool for drought characteristics calculation

10.5194/egusphere-egu21-14328 ◽

2021 ◽

Author(s):

Mahyar Mottaghi Zadeh ◽

Maral Habibi

Keyword(s):

Quantitative Description ◽

Geographical Location ◽

Drought Indices ◽

Drought Severity ◽

Drought Condition ◽

Development Environment ◽

Drought Duration ◽

Software Application ◽

Drought Characteristics ◽

Drought Conditions

There are many ways to identify and monitor drought conditions. Scarcely are tools that calculate drought characteristics, The "SDF Calculator" works to bring monitoring tools to the public so they can assess drought conditions, this tool is used to assess and identify drought and its intensity.Drought severity refers to the absolute sum of consecutive SDI values below a given threshold level while drought duration is the number of consecutive months that SDI is below that threshold, and drought frequency is a number of months with drought condition (means SPI < -0.5 or any given threshold that is desire, the threshold of drought index is a value that an index faces to drought condition. In every index, this value can be changed. For example, in many indices, the threshold of drought starts from zero or less zero. In other words, when the value of an index is calculating then all the values located in the drought classes, refer to the severity of the drought.Droughts and exceptionally wet periods are regional phenomena, which are considered as major environmental extremes, especially in semiarid regions of the world. The development of severity-duration-frequency (SDF) relationships of droughts and wet periods is important in hydrological and climatic plannings in any country.In this study, we aimed to offer a novel software model to be used for a quantitative description of droughts and wet periods to provide an overview of drought intensity and analyzing their severity, frequency, and duration. In addition, we have been able to develop a state-of-the-art bespoke software application, so the users are able to analyze drought based on the regional thresholds. While most of the analysis applications have used programming languages such as R or Python, due to the lack of software libraries in the .NET development environment, we have managed to offer our development environment based on .NET Core and C# programming language. The software application accepts inputs from various file formats or APIs, processes the data, and demonstrates the outcome in different graphs and maps depending on the geographical location of study areas. The outputs are not only can be exported as different formats to be used in big data applications but also might be exposed as web APIs to be used in live applications.&#160;&#160;Keywords: Drought characteristics, SDF Calculator, API, Standardized Drought Indices (SDI)

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DEVELOPMENT OF STREAMFLOW DROUGHT INDICES IN THE MORAVA RIVER BASIN

Proceedings of the XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management ◽

10.15407/uhmi.conference.01.14 ◽

2020 ◽

Author(s):

Ondrej Ledvinka ◽

◽

Pavel Coufal ◽

Keyword(s):

Time Series ◽

Kendall Test ◽

Drought Indices ◽

Drought Period ◽

Left Hand ◽

Low Flows ◽

Current Period ◽

Catchment Size ◽

Morava River ◽

The Stability

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.

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