scholarly journals A global-scale relationship between crop yield anomaly and multiscalar drought index based on multiple precipitation data

2021 ◽  
Author(s):  
Vempi Satriya Adi Hendrawan ◽  
Wonsik Kim ◽  
Yoshiya Touge ◽  
Shi Ke ◽  
Daisuke Komori
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Input Data ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Global Scale ◽  
Data Set ◽  
Drought Impact ◽  
The Standardized Precipitation Index ◽  
Global Precipitation

Abstract Drought impact on crop production is well known as crop yield is strongly controlled by climate variation. Previous studies assessed the drought impact using a drought index based on a single input data set, while the variability of the drought index to the input data choice is notable. In this study, a drought index based on the Standardized Precipitation Index with multiple timescales using several global precipitation datasets was compared with the detrended anomaly based on the global dataset of historical yield for major crops over 1981-2016. Results show that the drought index based on the ensemble precipitation dataset correlates better with the crop yield anomaly than a single dataset. Based on the drought index using ensemble datasets, global crop areas significantly affected by drought during the study period were around 23, 8, 30, and 29% for maize, rice, soybean, and wheat, respectively, induced mainly by medium to longer drought timescale (5 – 12-months). This study indicates that most crops cultivated in dry regions were affected by droughts worldwide, while rice shows less correlation to drought as it is generally irrigated and cultivated in humid regions with less drought exposure. This study provides a valuable framework for data choices in drought index development and a better knowledge of the drought impact on agriculture using different timescales on a global scale towards understanding crop vulnerability to climate disruptions.

scholarly journals The GPCC Drought Index – a new, combined and gridded global drought index

2014 ◽  
Vol 6 (2) ◽  
pp. 285-295 ◽  
Author(s):  
M. Ziese ◽  
U. Schneider ◽  
A. Meyer-Christoffer ◽  
K. Schamm ◽  
J. Vido ◽  
...  
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Regular Grid ◽  
Data Set ◽  
Precipitation Climatology ◽  
Global Precipitation Climatology Centre ◽  
The Standardized Precipitation Index ◽  
Global Precipitation ◽  
Climate Prediction Center

Abstract. The Global Precipitation Climatology Centre Drought Index (GPCC-DI) provides estimations of water supply anomalies with respect to long-term statistics. It is a combination of the Standardized Precipitation Index with adaptations from Deutscher Wetterdienst (SPI-DWD) and the Standardized Precipitation Evapotranspiration Index (SPEI). Precipitation data were taken from the Global Precipitation Climatology Centre (GPCC) and temperature data from NOAA's Climate Prediction Center (CPC). The GPCC-DI is available with several accumulation periods of 1, 3, 6, 9, 12, 24 and 48 months for different applications. It is issued monthly starting in January 2013. Typically, it is released on the 10th day of the following month, depending on the availability of the input data. It is calculated on a regular grid with 1° spatial resolution. All accumulation periods are integrated into one netCDF file for each month. This data set is referenced by the doi:10.5676/DWD_GPCC/DI_M_100 and is available free of charge from the GPCC website ftp://ftp.dwd.de/pub/data/gpcc/html/gpcc_di_doi_download.html.

scholarly journals GPCC Drought Index – a new, combined, and gridded global drought index

2014 ◽  
Vol 7 (1) ◽  
pp. 243-270
Author(s):  
M. Ziese ◽  
U. Schneider ◽  
A. Meyer-Christoffer ◽  
K. Schamm ◽  
J. Vido ◽  
...  
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Regular Grid ◽  
Precipitation Climatology ◽  
Global Precipitation Climatology Centre ◽  
Precipitation Anomalies ◽  
The Standardized Precipitation Index ◽  
Global Precipitation ◽  
Climate Prediction Center

Abstract. The Global Precipitation Climatology Centre Drought Index (GPCC-DI) provides estimations of precipitation anomalies with respect to long term statistics. It is a combination of the Standardized Precipitation Index with adaptations from Deutscher Wetterdienst (SPI-DWD) and the Standardized Precipitation Evapotranspiration Index (SPEI). Precipitation data were taken from the Global Precipitation Climatology Centre (GPCC) and temperature data from NOAA's Climate Prediction Center (CPC). The GPCC-DI is available with several averaging periods of 1, 3, 6, 9, 12, 24 and 48 months for different applications. Since spring 2013, the GPCC-DI is calculated operationally and available back to January 2013. Typically it is released at the 10th day of the following month, depending on the availability of the input data. It is calculated on a~regular grid with 1° spatial resolution. All averaging periods are integrated into one netCDF-file for each month. This dataset can be referenced by the DOI:10.5676/DWD_GPCC/DI_M_100 and is available free of charge from the GPCC website ftp://ftp.dwd.de/pub/data/gpcc/html/gpcc_di_doi_download.html.

scholarly journals Using integrated meteorological and hydrological indices to assess drought characteristics in southern Taiwan

2019 ◽  
Vol 50 (3) ◽  
pp. 901-914 ◽  
Author(s):  
Hsin-Fu Yeh
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Drought Indices ◽  
Trend Test ◽  
Integrated Analysis ◽  
Drought Assessment ◽  
Southern Taiwan ◽  
The Standardized Precipitation Index

Abstract Numerous drought index assessment methods have been developed to investigate droughts. This study proposes a more comprehensive assessment method integrating two drought indices. The Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) are employed to establish an integrated drought assessment method to study the trends and characteristics of droughts in southern Taiwan. The overall SPI and SDI values and the spatial and temporal distributions of droughts within a given year (November to October) revealed consistent general trends. Major droughts occurred in the periods of 1979–1980, 1992–1993, 1994–1995, and 2001–2003. According to the results of the Mann–Kendall trend test and the Theil–Sen estimator analysis, the streamflow data from the Sandimen gauging station in the Ailiao River Basin showed a 30% decrease, suggesting increasing aridity between 1964 and 2003. Hence, in terms of water resources management, special attention should be given to the Ailiao River Basin. The integrated analysis showed different types of droughts occurring in different seasons, and the results are in good agreement with the climatic characteristics of southern Taiwan. This study suggests that droughts cannot be explained fully by the application of a single drought index. Integrated analysis using multiple indices is required.

Building Drought Index Based on AMSR-E Data - A Case Study in Hilly Area of Central Sichuan Basin

2013 ◽  
Vol 781-784 ◽  
pp. 2292-2295
Author(s):  
Qiong Lian Chen ◽  
Jing Wen Xu ◽  
Shao Wei Shi ◽  
Xin Li ◽  
Peng Wang
Keyword(s):  
Correlation Analysis ◽  
Sichuan Basin ◽  
Drought Index ◽  
Daily Precipitation ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Ratio Method ◽  
Hilly Area ◽  
Central Sichuan Basin ◽  
The Standardized Precipitation Index

Sichuan Hilly Area is selected as the study area. This paper uses ten brightness temperature AMSR-E data during 2006-2010. It constructs 8 preferred drought index by using the polarization ratio method (Polarization Rations, PR). This paper makes Pearson correlation analysis by using the 8 preferred drought index and the soil moisture of study area. Meanwhile, Linear regression and correlation analysis with the Daily precipitation and the standardized precipitation index SPI are also made. The results show: for example, in December 2009, drought index DI74, DI92, DI96 were basically consistent with the spatial distribution. Drought degree has an increasing trend from southeast to northwest regional gradually. And with the drought conditions in hilly area of actual and daily precipitation, SPI correlation between interannual and Sichuan are proper. So the drought index is more suitable for drought study in hilly area of central Sichuan Basin.

scholarly journals Drought Monitoring Utility using Satellite-Based Precipitation Products over the Xiang River Basin in China

2019 ◽  
Vol 11 (12) ◽  
pp. 1483 ◽  
Author(s):  
Qian Zhu ◽  
Yulin Luo ◽  
Dongyang Zhou ◽  
Yue-Ping Xu ◽  
Guoqing Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Drought Monitoring ◽  
In Situ Observations ◽  
Remote Sensing Techniques ◽  
Xiang River ◽  
The Standardized Precipitation Index

Drought is a natural hazard disaster that can deeply affect environments, economies, and societies around the world. Therefore, accurate monitoring of patterns in drought is important. Precipitation is the key variable to define the drought index. However, the spare and uneven distribution of rain gauges limit the access of long-term and reliable in situ observations. Remote sensing techniques enrich the precipitation data at different temporal–spatial resolutions. In this study, the climate prediction center morphing (CMORPH) technique (CMORPH-CRT), the tropical rainfall measuring mission (TRMM) multi-satellite precipitation analysis (TRMM 3B42V7), and the integrated multi-satellite retrievals for global precipitation measurement (IMERG V05) were evaluated and compared with in situ observations for the drought monitoring in the Xiang River Basin, a humid region in China. A widely-used drought index, the standardized precipitation index (SPI), was chosen to evaluate the drought monitoring utility. The atmospheric water deficit (AWD) was used for comparison of the drought estimation with SPI. The results were as follows: (1) IMERG V05 precipitation products showed the highest accuracy against grid-based precipitation, followed by CMORPH-CRT, which performed better than TRMM 3B42V7; (2) IMERG V05 showed the best performance in SPI-1 (one-month SPI) estimations compared with CMORPH-CRT and TRMM 3B42V7; (3) SPI-1 was more suitable for drought monitoring than AWD in the Xiang River Basin, because its high R-values and low root mean square error (RMSE) compared with the corresponding index based on in situ observations; (4) drought conditions in 2015 were apparently more severe than that in 2016 and 2017, with the driest area mainly distributed in the southwest part of the Xiang River Basin.

Development of a Coastal Drought Index Using Salinity Data

2017 ◽  
Vol 98 (4) ◽  
pp. 753-766 ◽  
Author(s):  
Paul A. Conrads ◽  
Lisa S. Darby
Keyword(s):  
South Carolina ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Aquatic Communities ◽  
Groundwater Levels ◽  
Salinity Data ◽  
Negative Impacts ◽  
The Standardized Precipitation Index ◽  
Coastal Salinity

Abstract A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.

scholarly journals Flash Drought Response to Precipitation and Atmospheric Evaporative Demand in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 165
Author(s):  
Iván Noguera ◽  
Fernando Domínguez-Castro ◽  
Sergio M. Vicente-Serrano
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Rapid Decline ◽  
Spatial And Temporal Patterns ◽  
Evaporative Demand ◽  
Main Driver ◽  
The Standardized Precipitation Index ◽  
High Degree

Flash drought is the result of strong precipitation deficits and/or anomalous increases in atmospheric evaporative demand (AED), which triggers a rapid decline in soil moisture and stresses vegetation over short periods of time. However, little is known about the role of precipitation and AED in the development of flash droughts. For this paper, we compared the standardized precipitation index (SPI) based on precipitation, the evaporative demand drought index (EDDI) based on AED, and the standardized evaporation precipitation index (SPEI) based on the differences between precipitation and AED as flash drought indicators for mainland Spain and the Balearic Islands for 1961–2018. The results show large differences in the spatial and temporal patterns of flash droughts between indices. In general, there was a high degree of consistency between the flash drought patterns identified by the SPI and SPEI, with the exception of southern Spain in the summer. The EDDI showed notable spatial and temporal differences from the SPI in winter and summer, while it exhibited great coherence with the SPEI in summer. We also examined the sensitivity of the SPEI to AED in each month of the year to explain its contribution to the possible development of flash droughts. Our findings showed that precipitation is the main driver of flash droughts in Spain, although AED can play a key role in the development of these during periods of low precipitation, especially in the driest areas and in summer.

scholarly journals Daily standardized precipitation index with multiple time scale for monitoring water deficit across the mainland China from 1961 to 2018

2021 ◽  
Author(s):  
Qianfeng Wang ◽  
Rongrong Zhang ◽  
Yanping Qu ◽  
Jingyu Zeng ◽  
Xiaoping Wu ◽  
...  
Keyword(s):  
Standardized Precipitation Index ◽  
Social Economy ◽  
Mainland China ◽  
Precipitation Index ◽  
Agricultural Drought ◽  
Multiple Time ◽  
Data Set ◽  
Drought Assessment ◽  
Multi Scale ◽  
The Standardized Precipitation Index

Abstract. With the increasing shortage of water resources, drought has become one of the hot issues in the world. The standardized precipitation index (SPI) is one of the widely used drought assessment indicators because of its simple and effective calculation method, but it can only assess drought events more than one month. We developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI and meet the needs of drought types at different time scales. Taking three typical stations in Henan, Yunnan and Fujian Province as examples, the drought events identified by SPI with different scales were consistent with the historical drought events recorded. Meanwhile, we took the 3-month scale SPI of soil and agricultural drought as an example, and analyzed the characteristics of drought events in 484 stations in Chinese mainland. The results showed that most of the drought events the mainland China did not increase significantly, and some parts of the northwestern Xinjiang and Northeast China showed signs of gradual relief. In short, our daily SPI data set is freely available to the public on the website https://doi.org/10.6084/m9.figshare.14135144, and can effectively capture drought events of different scales. It can also meet the needs of drought research in different fields such as meteorology, hydrology, agriculture, social economy, etc.

scholarly journals Drought Analysis in Europe and in the Mediterranean Basin Using the Standardized Precipitation Index

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1043 ◽  
Author(s):  
Tommaso Caloiero ◽  
Simone Veltri ◽  
Paola Caloiero ◽  
Francesco Frustaci
Keyword(s):  
Mediterranean Basin ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Large Area ◽  
Full Data ◽  
Data Set ◽  
Global Precipitation Climatology Centre ◽  
The Mediterranean ◽  
The Standardized Precipitation Index ◽  
The Mediterranean Basin

In this study, drought events over a large area of the Northern Hemisphere, including continental Europe, Ireland, the United Kingdom, and the Mediterranean basin, were analyzed using the Standardized Precipitation Index (SPI) at various times scales (3, 6, 12, and 24 months). To this purpose, the Global Precipitation Climatology Centre (GPCC) Full Data Monthly Product Version 2018 data set, with spatial resolutions of 0.5° longitude/latitude and for the period 1951–2016, has been used. First, the temporal evolution of the percentage of grid points, falling within the severe and extreme drought categories, has been evaluated. Then, a trend analysis has been performed at a seasonal scale, considering the autumn-winter and the spring-summer periods, and at an annual scale. The results of this paper highlight that the Mediterranean basin and North Africa are the most consistently vulnerable areas showing a general reduction in SPI values especially for the long time scale.

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