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

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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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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Monitoring Droughts in the Greater Changbai Mountains Using Multiple Remote Sensing-Based Drought Indices

Remote Sensing ◽

10.3390/rs12030530 ◽

2020 ◽

Vol 12 (3) ◽

pp. 530 ◽

Cited By ~ 5

Author(s):

Yang Han ◽

Ziying Li ◽

Chang Huang ◽

Yuyu Zhou ◽

Shengwei Zong ◽

...

Keyword(s):

Remote Sensing ◽

Time Lag ◽

Remote Sensing Data ◽

Meteorological Drought ◽

Condition Index ◽

Temporal Variations ◽

Changbai Mountains ◽

Drought Indices ◽

Drought Condition ◽

Meteorological Observations

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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ANALISIS KETERKAITAN ANTARA KEKERINGAN METEOROLOGIS DENGAN INDEKS VEGETASI TERSTANDARISASI DI PULAU LOMBOK

Jurnal Sains & Teknologi Modifikasi Cuaca ◽

10.29122/jstmc.v22i2.4437 ◽

2021 ◽

Vol 22 (2) ◽

pp. 41-49

Author(s):

Siti Najma Nindya Utami ◽

Rista Hernandi Virgianto ◽

Dzikrullah Akbar

Keyword(s):

Vegetation Index ◽

Meteorological Drought ◽

Agricultural Drought ◽

Maximum Temperature ◽

Drought Indices ◽

Drought Risk ◽

Observation Data ◽

Standardized Precipitation Evapotranspiration Index ◽

Length Of The Day ◽

Lombok Island

Intisari Kekeringan merupakan bencana kompleks yang dapat menyebabkan kerugian masyarakat di berbagai sektor. Salah satu wilayah yang berisiko tinggi mengalami kekeringan adalah Pulau Lombok. Wilayah ini memiliki lahan yang berisiko terkena kekeringan seluas 405.985 ha. Tingkat keparahan kekeringan meteorologis dapat diukur dengan Standardized Precipitation Evapotranspiration Index (SPEI). Salah satu karakteristik kekeringan adalah kondisi vegetasi tanaman yang buruk, oleh karena itu Standardized Vegetation Index (SVI) digunakan sebagai acuan dalam monitoring kekeringan agrikultural. Penelitian ini bertujuan untuk mengetahui hubungan antara SPEI dengan SVI untuk setiap pos hujan di Pulau Lombok tahun 2001-2018. Penelitian ini menggunakan data bulanan tahun 2001-2018 yang meliputi data observasi curah hujan, suhu maksimum, suhu minimum, penginderaan jauh Normalized Differences Vegetation Index (NDVI) dengan resolusi 0,05°, model FLDAS kecepatan angin yang juga didapatkan dengan resolusi 0,5°, lama penyinaran matahari, lintang, dan elevasi. Metode yang digunakan yaitu menghitung indeks kekeringan SPEI dan SVI, kemudian menghitung korelasi dan signifikansi untuk kedua indeks kekeringan tersebut. Hasilnya menunjukkan bahwa SPEI1 lebih tinggi berkorelasi dengan SVI+1 dengan kategori cukup kuat. Untuk SPEI3, SPEI6, dan SPEI12 berkorelasi cukup kuat hingga kuat dengan SVI0. Hal ini menunjukkan bahwa kekeringan jangka panjang akan langsung mempengaruhi kekeringan agrikultural atau kekeringan vegetasi saat itu juga. Nilai korelasi yang lebih tinggi untuk setiap indeks tersebar di pos hujan yang terletak di tengah-tengah Pulau Lombok, karena pengaruh kondisi geografis dan demografis Abstract Drought is a complex disaster because it can cause loss to society in various sectors. One of the high-risk areas of drought is Lombok Island. This area has 405,985 ha of drought risk. The severity of meteorological drought can be measured by the Standardized Precipitation Evapotranspiration Index (SPEI). One of the characteristics of drought is the poor condition of plant vegetation, therefore the Standardized Vegetation Index (SVI) is used as a reference in monitoring agricultural drought. This study aims to determine the relationship of SPEI with SVI for each rainfall post in Lombok Island from 2001-2018. This study uses monthly data from 2001-2018, including observation data of rainfall, maximum temperature, minimum temperature, remote sensing Normalized Differences Vegetation Index (NDVI) 0.05 °, FLDAS model of wind speed 0.5 °, length of the day, latitude, and elevation. The use method is to calculate SPEI and SVI, then calculate the correlation and significance for the two drought indices. The result shows that SPEI1 is higher in correlation with SVI+1, which is in a strong enough category. For SPEI3, SPEI6, and SPEI12, the correlation is strong enough to strong with SVI0. This suggests that long-term drought will directly affect agricultural drought or immediate vegetation drought. The higher correlation values ??for each index are spread over the rain posts located in the middle of Lombok Island because geographic and demographic conditions influence them.

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ASSESSMENT AND MONITORING OF AGRICULTURAL DROUGHTS IN MAHARASHTRA USING METEOROLOGICAL AND REMOTE SENSING BASED INDICES

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-5-253-2018 ◽

2018 ◽

Vol IV-5 ◽

pp. 253-264 ◽

Cited By ~ 1

Author(s):

P. V. Aswathi ◽

B. R. Nikam ◽

A. Chouksey ◽

S. P. Aggarwal

Keyword(s):

Remote Sensing ◽

Meteorological Drought ◽

Condition Index ◽

Agricultural Drought ◽

Drought Indices ◽

Drought Assessment ◽

Sparse Vegetation ◽

Vegetation Health Index ◽

Agricultural Yield ◽

Remote Sensing Methods

Abstract. Drought is a recurring climatic event characterized by slow onset, a gradual increase in its intensity, and persistence for a long period depending upon the availability of water. Droughts, broadly classified into meteorological, hydrological and agricultural drought, which are interconnected to each other. India, being an agriculture based economy depends primarily on agriculture production for its economic development and stability. The occurrence of agriculture drought affects the agricultural yield, which affects the regional economy to a larger extent. In present study, agricultural and meteorological drought in Maharashtra state was monitored using traditional as well as remote sensing methods. The meteorological drought assessment and characterization is done using two standard meteorological drought indices viz. standard precipitation index (SPI) and effective drought index (EDI). The severity and persistency of meteorological drought were studied using SPI for the period 1901 to 2015. However, accuracy of SPI in detection of sub-monthly drought is limited. Therefore, sub-monthly drought is effectively monitored using EDI. The monthly and sub-monthly drought mapped using SPI and EDI, respectively were then compared and assessed. It was concluded that EDI serves as a better indicator to monitor sub-monthly droughts. The agricultural drought monitoring was carried out using the remote sensing based indices such as vegetation condition index (VCI), temperature condition index (TCI), vegetation health index (VHI), shortwave angle slope index (SASI) and the index which maps the agricultural drought in a better way was identified. The area under drought as calculated by various agricultural drought indices compared with that of the EDI, it was found that the results of SASI matched with results of EDI. SASI denotes different values for the dry and wet soil and for the healthy and sparse vegetation. SASI monitors the agricultural drought better as compared to other indices used in this study.

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Different Agricultural Responses to Extreme Drought Events in Neighboring Counties of South and North Korea

Remote Sensing ◽

10.3390/rs11151773 ◽

2019 ◽

Vol 11 (15) ◽

pp. 1773 ◽

Cited By ~ 4

Author(s):

Jae-Hyun Ryu ◽

Kyung-Soo Han ◽

Yang-Won Lee ◽

No-Wook Park ◽

Sungwook Hong ◽

...

Keyword(s):

North Korea ◽

Drought Index ◽

Management Practices ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Condition Index ◽

Agricultural Management ◽

Agricultural Drought ◽

Extreme Drought ◽

Drought Indices

Satellite-based remote sensing techniques have been widely used to monitor droughts spanning large areas. Various agricultural drought indices have been developed to assess the intensity of agricultural drought and to detect damaged crop areas. However, to better understand the responses of agricultural drought to meteorological drought, agricultural management practices should be taken into consideration. This study aims to evaluate the responses to drought under different forms of agricultural management for the extreme drought that occurred on the Korean Peninsula in 2014 and 2015. The 3-month standardized precipitation index (SPI3) and the 3-month vegetation health index (VHI3) were selected as a meteorological drought index and an agricultural drought index, respectively. VHI3, which comprises the 3-month temperature condition index (TCI3) and the 3-month vegetation condition index (VCI3), differed significantly in the study area during the extreme drought. VCI3 had a different response to the lack of precipitation in South and North Korea because it was affected by irrigation. However, the time series of TCI3 were similar in South and North Korea. These results meant that each drought index has different characteristics and should be utilized with caution. Our results are expected to help comprehend the responses of the agricultural drought index on meteorological drought depending on agricultural management.

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Monitoring and Assessment of Drought Focused on Its Impact on Sorghum Yield over Sudan by Using Meteorological Drought Indices for the Period 2001–2011

Remote Sensing ◽

10.3390/rs10081231 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1231 ◽

Cited By ~ 7

Author(s):

Khalid. Elhag ◽

Wanchang Zhang

Keyword(s):

Natural Disaster ◽

Crop Yield ◽

Spatial Scales ◽

Meteorological Drought ◽

Agricultural Drought ◽

Drought Indices ◽

Observation Data ◽

High Resolution Satellite Images ◽

Trmm Precipitation ◽

The Impact

Currently, the high-resolution satellite images in near real-time have gained more popularity for natural disaster detection due to the unavailability and difficulty of acquiring frequent ground observation data over a wide region. In Sudan, the occurrence of drought events is a predominant natural disaster that causes substantial damages to crop production. Therefore, monitoring drought and measuring its impact on the agricultural sector remain major concerns of policymakers. The current study focused on assessing and analyzing drought characteristics based on two meteorological drought indices, namely the Standardized Precipitation Index (SPI) and the Drought Severity Index (DSI), and inferred the impact of drought on sorghum productivity in Sudan from 2001 to 2011. To identify the wet and dry areas, the deviations of tropical rainfall measuring mission (TRMM) precipitation products from the long-term mean from 2001 to 2011 were computed and mapped at a seasonal scale (July–October). Our findings indicated that the dry condition fluctuated over the whole of Sudan at various temporal and spatial scales. The DSI results showed that both the Kordofan and Darfur regions were affected by drought in the period 2001–2005, whereas most regions were affected by drought from 2008 to 2011. The spatial correlation between DSI, SPI-3, and TRMM precipitation products illustrated a significant positive correlation in agricultural lands and negative correlation in mountainous areas. The relationship between DSI and the Standardized variable of crop yield (St. Y) for sorghum yield was also investigated over two main agricultural regions (Central and Eastern regions) for the period 2001–2011, which revealed a good agreement between them, and a huge drop of sorghum yield also occurred in 2008–2011, corresponding to extreme drought indicated by DSI. The present study indicated that DSI can be used for agricultural drought monitoring and served as an alternative indicator for the estimation of crop yield over Sudan in some levels.

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The Alpine Drought Observatory

10.5194/egusphere-egu2020-16052 ◽

2020 ◽

Author(s):

Felix Greifeneder ◽

Emilie Crouzat ◽

Mario Fosatti ◽

Gregor Gregoric ◽

Klaus Haslinger ◽

...

Keyword(s):

Case Studies ◽

Meteorological Drought ◽

Hydrological Drought ◽

Agricultural Drought ◽

Drought Indices ◽

Drought Risk ◽

Alpine Regions ◽

The Alps ◽

Set Up ◽

Available Information

Water scarcity and related conflicts are becoming a worrying topic in Alpine regions. Moreover, lowland regions far beyond the Alps suffer from missing water from the Alps. Thus, countries are urged to act on this topic with common strategies. To support this cause, the Interreg Alpine-Space project, Alpine Drought Observatory (ADO), aims to set up a virtual observatory for the monitoring of drought in the entire Alpine region and beyond this, to derive recommendations for improved risk preparedness and efficiency of drought management.The ADO itself will be a transnational alpine-wide operational system with a web-interface (e.g. WebGIS, periodic reports) to access data and specific impact-oriented indices for monitoring droughts and their impacts. It will provide optimized observations and forecasts for mountainous areas, which could be integrated in existing EU-level monitoring systems (e.g. European Drought Observatory). Monitoring will be based on a fusion of existing approaches (e.g. meteorological drought indices, hydrological drought indices), and newly available information (e.g. remote sensing of snow and soil moisture), to provide an optimized set of drought indices and a common drought classification. One of the further project activities will be the collection and recording of specific drought impacts. This knowledge will help to relate meteo-hydrological indices to concrete, real world effects and thus significantly enhance their applicability for drought monitoring and management.The ADO will be tested in six case studies in all alpine countries with local partners. The case studies represent different drought issues such as agricultural drought, hydrological drought or drought impact on ecosystems. Out of the case studies, guidelines for an improved drought risk management will be developed. Findings will be upscaled to recommendations for drought governance policies for the Alps. Main beneficiaries of project findings are institutions with decision-making capacities in the field of water management, energy production, and agriculture.

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Commonly Used Drought Indices as Indicators of Soil Moisture in China

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0076.1 ◽

2015 ◽

Vol 16 (3) ◽

pp. 1397-1408 ◽

Cited By ~ 43

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.

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Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1767.1 ◽

2009 ◽

Vol 48 (1) ◽

pp. 77-88 ◽

Cited By ~ 10

Author(s):

Bradfield Lyon ◽

Lareef Zubair ◽

Vidhura Ralapanawe ◽

Zeenas Yahiya

Keyword(s):

Sri Lanka ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

Drought Indices ◽

Drought Risk ◽

Mitigation And Adaptation ◽

Wide Range ◽

Drought Relief ◽

Drought Indicators ◽

The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

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