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

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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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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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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The impact of drought on the productivity of two rainfed crops in Spain

10.5194/nhess-2019-1 ◽

2019 ◽

Author(s):

Marina Peña-Gallardo ◽

Sergio Martín Vicente-Serrano ◽

Fernando Domínguez-Castro ◽

Santiago Beguería

Keyword(s):

Crop Yield ◽

Crop Yields ◽

Spatial Scales ◽

Standardized Precipitation Index ◽

Yield Response ◽

Drought Indices ◽

Economic Sectors ◽

Yield Data ◽

Agriculture Sector ◽

The Impact

Abstract. Drought events are of great importance in most Mediterranean climate regions because of the diverse and costly impacts they have in various economic sectors and on the environment. The effects of this natural hazard on rainfed crops are particularly evident. In this study the impacts of drought on two representative rainfed crops in Spain (wheat and barley) were assessed. As the agriculture sector is vulnerable to climate, it is especially important to identify the most appropriate tools for monitoring the impact of the weather on crops, and particularly the impact of drought. Drought indices are the most effective tool for that purpose. Various drought indices have been used to assess the influence of drought on crop yields in Spain, including the standardized precipitation and evapotranspiration index (SPEI), the standardized precipitation index (SPI), the Palmer drought indices (PDSI, Z-Index, PHDI, PMDI), and the standardized Palmer drought index (SPDI). Two sets of crop yield data at different spatial scales and temporal periods were used in the analysis. The results showed that drought indices calculated at different time scales (SPI, SPEI) most closely correlated with crop yield. The results also suggested that different patterns of yield response to drought occurred depending on the region, period of the year, and the drought time scale. The differing responses across the country were related to season and the magnitude of various climate variables.

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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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The impact of drought on the productivity of two rainfed crops in Spain

Natural Hazards and Earth System Science ◽

10.5194/nhess-19-1215-2019 ◽

2019 ◽

Vol 19 (6) ◽

pp. 1215-1234 ◽

Cited By ~ 15

Author(s):

Marina Peña-Gallardo ◽

Sergio Martín Vicente-Serrano ◽

Fernando Domínguez-Castro ◽

Santiago Beguería

Keyword(s):

Crop Yield ◽

Drought Index ◽

Crop Yields ◽

Spatial Scales ◽

Standardized Precipitation Index ◽

Yield Response ◽

Drought Indices ◽

Drought Severity ◽

Yield Data ◽

The Impact

Abstract. Drought events are of great importance in most Mediterranean climate regions because of the diverse and costly impacts they have in various economic sectors and on the environment. The effects of this natural hazard on rainfed crops are particularly evident. In this study the impacts of drought on two representative rainfed crops in Spain (wheat and barley) were assessed. As the agriculture sector is vulnerable to climate, it is especially important to identify the most appropriate tools for monitoring the impact of the weather on crops, and particularly the impact of drought. Drought indices are the most effective tool for that purpose. Various drought indices have been used to assess the influence of drought on crop yields in Spain, including the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI), the Palmer drought indices (Palmer Drought Severity Index, PDSI; Palmer Z Index, Z Index; Palmer Hydrological Drought Index, PHDI; Palmer Modified Drought Index, PMDI), and the Standardized Palmer Drought Index (SPDI). Two sets of crop yield data at different spatial scales and temporal periods were used in the analysis. The results showed that drought indices calculated at different timescales (SPI, SPEI) most closely correlated with crop yield. The results also suggested that different patterns of yield response to drought occurred depending on the region, period of the year, and the drought timescale. The differing responses across the country were related to season and the magnitude of various climate variables.

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Earth Observation Data for Agricultural Drought Monitoring in the Pannonian Basin

10.5194/egusphere-egu2020-16916 ◽

2020 ◽

Author(s):

Laura Crocetti ◽

Milan Fischer ◽

Matthias Forkel ◽

Aleš Grlj ◽

Wai-Tim Ng ◽

...

Keyword(s):

Machine Learning ◽

Soil Moisture ◽

Pannonian Basin ◽

Spatial Scales ◽

European Space Agency ◽

Earth Observation ◽

Machine Learning Algorithms ◽

Agricultural Drought ◽

Drought Monitoring ◽

Observation Data

The Pannonian Basin is a region in the southeastern part of Central Europe that is heavily used for agricultural purposes. It is geomorphological defined as the plain area that is surrounded by the Alps in the west, the Dinaric Alps in the Southwest, and the Carpathian mountains in the North, East and Southeast. In recent decades, the Pannonian Basin has experienced several drought episodes, leading to severe impacts on the environment, society, and economy. Ongoing human-induced climate change, characterised by increasing temperature and potential evapotranspiration as well as changes in precipitation distribution will further exacerbate the frequency and intensity of extreme events. Therefore, it is important to monitor, model, and forecast droughts and their impact on the environment for a better adaption to the changing weather and climate extremes. The increasing availability of long-term Earth observation (EO) data with high-resolution, combined with the progress in machine learning algorithms and artificial intelligence, are expected to improve the drought monitoring and impact prediction capacities.Here, we assess novel EO-based products with respect to drought processes in the Pannonian Basin. To identify meteorological and agricultural drought, the Standardized Precipitation-Evapotranspiration Index was computed from the ERA5 meteorological reanalysis and compared with drought indicators based on EO time series of soil moisture and vegetation like the Soil Water Index or the Normalized Difference Vegetation Index. We suggest that at resolution representing the ERA5 reanalysis (~0.25&#176;) or coarser, both meteorological as well as EO data can identify drought events similarly well. However, at finer spatial scales (e.g. 1 km) the variability of biophysical properties between fields cannot be represented by meteorological data but can be captured by EO data. Furthermore, we analyse historical drought events and how they occur in different EO datasets. It is planned to enhance the forecasting of agricultural drought and estimating drought impacts on agriculture through exploiting the potential of EO soil moisture and vegetation data in a data-driven machine learning framework.This study is funded by the DryPan project of the European Space Agency (https://www.eodc.eu/esa-drypan/).

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Global-scale drought risk assessment for agricultural systems

10.5194/nhess-2019-255 ◽

2019 ◽

Cited By ~ 1

Author(s):

Isabel Meza ◽

Stefan Siebert ◽

Petra Döll ◽

Jürgen Kusche ◽

Claudia Herbert ◽

...

Keyword(s):

Spatial Scales ◽

Global Scale ◽

Drought Indices ◽

Drought Risk ◽

Agricultural Systems ◽

Coping Capacity ◽

Climate Conditions ◽

Hazard Exposure ◽

Social Ecological ◽

The Impact

Abstract. Droughts continue to affect ecosystems, communities, and entire economies. Agriculture bears much of the impact, and in many countries it is the most heavily affected sector. Over the past decades, efforts have been made to assess drought risk at different spatial scales. Here, we present for the first time an integrated assessment of drought risk for both irrigated and rain-fed agricultural systems at the global scale. Composite hazard indicators were calculated for irrigated and rain-fed systems separately using different drought indices based on historical climate conditions (1980–2016). Exposure was analyzed for irrigated and non-irrigated crops. Vulnerability was assessed through a social-ecological systems perspective, using social-ecological susceptibility and lack of coping capacity indicators that were weighted by drought experts from around the world. The analysis shows that drought risk of rain-fed and irrigated agricultural systems displays heterogeneous pattern at the global level with higher risk for southeastern Europe, as well as northern and southern Africa. By providing information on the drivers and spatial patterns of drought risk in all dimensions of hazard, exposure, and vulnerability, the presented analysis can support the identification of tailored measures to reduce drought risk and increase the resilience of agricultural systems.

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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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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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The Impacts of Climate-Induced Agricultural Drought on Four Cereal Crops: A Case Study in Bako Tibe District, Oromia National Regional State, Ethiopia

Caraka Tani Journal of Sustainable Agriculture ◽

10.20961/carakatani.v35i1.35749 ◽

2020 ◽

Vol 35 (1) ◽

pp. 135

Author(s):

Terefa Adunya ◽

Fedhasa Chalchisa Benti

Keyword(s):

Crop Yields ◽

Pearson Correlation ◽

Agricultural Drought ◽

Extreme Weather Events ◽

Coefficient Of Determination ◽

Cereal Crops ◽

Drought Indices ◽

Trend Test ◽

Small Scale ◽

The Impact

Increasing temperature and altered precipitation patterns lead to the extreme weather events such as drought and flood, which severely affects the agricultural production. This study was aimed to assess the impact of climate change-induced agricultural drought on four cereal crops in Bako Tibe District. Time-series climate and crop yield data, recorded from 1989 to 2018, were acquired from NASA’s data portal and Bako Research Institute. The changes in temperature and precipitation were analyzed using Mann Kendall trend test. The agricultural drought index was analyzed using R-software. The correlation between the selected yield crops and drought indices were evaluated using Pearson correlation coefficient. The results show that trends of seasonal and annual maximum and minimum temperatures were significantly increased (P<0.05). However, seasonal and annual precipitations were insignificantly decreased (P>0.05). Moderate to severe agricultural drought intensities happened four times in the last three decades. These drought spells spatially covered about 36% of the total area of the district. Crop yields and drought indices were significantly correlated at p-values; 0.0034, 0.043, 0.003 and 0.001 for teff, wheat, barley and maize, respectively. The coefficient of determination (R2) values of crop yields were 28.3%, 30.9%, 28.5% and 34.6% for teff, wheat, barley and maize, correspondingly. The study clearly suggests that the increase in temperature and decrease in precipitation enhanced the frequency and intensity of drought events and these impacted the selected crop yields during the past three decades. The map-based results could be used as guides for governmental and non-governmental organizations concerning on drought impact mitigation activities in the district by encouraging farmers to adopt appropriate agricultural technologies, drought tolerant crop varieties and small scale irrigation.

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