scholarly journals Assessment of spatiotemporal characteristics of agro-meteorological drought events based on comparing Standardized Soil Moisture Index, Standardized Precipitation Index and Multivariate Standardized Drought Index

2020 ◽  
Vol 11 (S1) ◽  
pp. 1-17 ◽  
Author(s):  
Muhammad Imran Khan ◽  
Xingye Zhu ◽  
Muhammad Arshad ◽  
Muhammad Zaman ◽  
Yasir Niaz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Moisture Index ◽  
Drought Characteristics ◽  
Soil Moisture Index ◽  
The Impact ◽  
Standardized Drought Index

Abstract Drought indices that compute drought events by their statistical properties are essential stratagems for the estimation of the impact of drought events on a region. This research presents a quantitative investigation of drought events by analyzing drought characteristics, considering agro-meteorological aspects in the Heilongjiang Province of China during 1980 to 2015. To examine these aspects, the Standardized Soil Moisture Index (SSI), Standardized Precipitation Index (SPI), and Multivariate Standardized Drought Index (MSDI) were used to evaluate the drought characteristics. The results showed that almost half of the extreme and exceptional drought events occurred during 1990–92 and 2004–05. The spatiotemporal analysis of drought characteristics assisted in the estimation of the annual drought frequency (ADF, 1.20–2.70), long-term mean drought duration (MDD, 5–11 months), mean drought severity (MDS, −0.9 to −2.9), and mild conditions of mean drought intensity (MDI, −0.2 to −0.80) over the study area. The results obtained by MSDI reveal the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. The results of this study provide valuable information and can prove to be a reference framework to guide agricultural production in the region.

scholarly journals A Non-Stationary and Probabilistic Approach for Drought Characterization Using Trivariate and Pairwise Copula Construction (PCC) Model

2021 ◽  
Author(s):  
Soumyashree Dixit ◽  
K V Jayakumar
Keyword(s):  
Drought Index ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Climate Indices ◽  
Copula Model ◽  
Reconnaissance Drought Index ◽  
Drought Characteristics ◽  
Recurrence Intervals

Abstract Under the variable climatic conditions, the conventional Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) are inadequate for predicting extreme drought characteristics. So in the present study, two indices namely, Non-stationary Standardized Precipitation Index (NSPI) and Non-stationary Reconnaissance Drought Index (NRDI) are developed by fitting non-stationary gamma (for precipitation series) and lognormal (for initial values,δ0) distributions. The Generalized Additive Model in Location, Scale and Shape (GAMLSS) framework, with time varying location parameters considering the external covariates, is used to fit the non-stationary distributions. This includes various large scale climate indices namely Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) as external covariates for the non-stationary drought assessment. The performances of stationary and non-stationary models are compared based on the Akaika Information Criterion (AIC). Additionally, the drought characteristics are evaluated using Run theory analysis for both stationary and non-stationary drought indices. The study also concentrated on the trivariate copula as well as the Pairwise Copula Construction (PCC) models to estimate the drought recurrence intervals. The comparison of two copula models revealed that the PCC model performed better than the trivariate Student’s t copula model. The recurrence intervals arrived at for the drought events are different for trivariate copula model and PCC model. The area taken for the study is the Upper and Lower sub basins of the Godavari River basin. This study shows that non-stationary drought indices will be helpful in the accurate estimate of the drought characteristics under the changing climatic scenario.

scholarly journals Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

2021 ◽  
Vol 13 (4) ◽  
pp. 2066
Author(s):  
Jin Hyuck Kim ◽  
Jang Hyun Sung ◽  
Eun-Sung Chung ◽  
Sang Ug Kim ◽  
Minwoo Son ◽  
...  
Keyword(s):  
General Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Coupled Model ◽  
Meteorological Drought ◽  
General Circulation Models ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Drought Period ◽  
Drought Characteristics

Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.

scholarly journals The Assessment of Climate Change Impact on Meteorological Draught Susceptability on Sampean Watershed

2021 ◽  
Vol 9 (4) ◽  
pp. 146
Author(s):  
Masita Ratih ◽  
Gusfan Halik ◽  
Retno Utami Agung Wiyono
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Precipitation Index ◽  
Climate Change Scenarios ◽  
Change Impact ◽  
The Standardized Precipitation Index ◽  
The Impact

Drought disasters that occur in the Sampean watershed from time to time have increased, both the intensity of events and the area affected by drought. The general objective of this research is to develop an assessment method for the impact of climate chan ge on vulnerability to drought disasters based on atmospheric circulation data. The specific objectives of this study are to model rainfall predictions based on atmospheric circulation data, predict rainfall in various climate change scenarios (Intergovernm ental Panel on Climate Change, IPCC – AR5), and assess vulnerability to drought disasters using a meteorological approach. The Standardized Precipitation Index (SPI) is one way to analyze the drought index in an area which was developed previous researcher. The Standardized Precipitation Index (SPI) is designed to quantitatively determine the rainfall deficit with various time scales. The advantage of the Standardized Precipitation Index (SPI) is that it is enough to use monthly rainfall data to compare drou ght levels between regions even with different climate types. To facilitate the presentation of the data base on the identification of d rought susceptibility, we need a system that can assist in building, storing, managing and displaying geographically ref erenced information in the form of spatial mapping. This research facilitates monitoring of the area of drought-prone areas, predicts drought levels, prevents future drought disasters, and prepares plans for rebuilding drought-prone areas in the Sampean watershed.

Evaluating the Utility of Drought Indices as Soil Moisture Proxies for Drought Monitoring and Land–Atmosphere Interactions

2020 ◽  
Vol 21 (9) ◽  
pp. 2157-2175
Author(s):  
Shanshui Yuan ◽  
Steven M. Quiring ◽  
Chen Zhao
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Soil Layer ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Moisture Index ◽  
Drought Conditions ◽  
Crop Moisture Index ◽  
The Standardized Precipitation Index ◽  
The Relationship

AbstractThere are a variety of metrics that are used to monitor drought conditions, including soil moisture and drought indices. This study examines the relationship between in situ soil moisture, NLDAS-2 soil moisture, and four drought indices: the standardized precipitation index, the standardized precipitation evapotranspiration index, the crop moisture index, and the Palmer Z index. We evaluate how well drought indices and the modeled soil moisture represent the intensity, variability, and persistence of the observed soil moisture in the southern Great Plains. We also apply the drought indices to evaluate land–atmosphere interactions and compare the results with soil moisture. The results show that the SPI, SPEI, and Z index have higher correlations with 0–10-cm soil moisture, while the CMI is more strongly correlated with 0–100-cm soil moisture. All the drought indices tend to overestimate the area affected by moderate to extreme drought conditions. Significant drying trends from 2003 to 2017 are evident in SPEI, Z index, and CMI, and they agree with those in the observed soil moisture. The CMI captures the intra- and interannual variability of 0–100-cm soil moisture better than the other drought indices. The persistence of CMI is longer than that of 0–10-cm soil moisture and shorter than that of 0–100-cm soil moisture. Model-derived soil moisture does not outperform the CMI in the 0–100-cm soil layer. The Z index and CMI are better drought indices to use as a proxy for soil moisture when examining land–atmosphere interactions while the SPI is not recommended. Soil type and climate affect the relationship between drought indices and observed soil moisture.

scholarly journals Multivariate drought risk analysis based on copula functions: a case study

2020 ◽  
Vol 20 (6) ◽  
pp. 2375-2388
Author(s):  
Mohammadreza Seyedabadi ◽  
Mohammadreza Kavianpour ◽  
Saber Moazami
Keyword(s):  
Return Period ◽  
Drought Index ◽  
Human Life ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Drought Risk ◽  
Severe Drought ◽  
Copula Functions ◽  
Drought Characteristics ◽  
Multiple Variables

Abstract Drought is asserted as a natural disaster that encompasses vast territories for a long time and affects human life. Indicators are powerful tools for understanding this phenomenon. However, in order to get more information about the drought, multivariate indices were introduced for simultaneous evaluation of multiple variables. In this study, a combined drought index (CDI) based on three drought indices, the Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Standardized Water-level Index (SWI), is defined. Then, the Entropy method is used to determine the weight of each indicator. Among the calculated weights, SDI and SPI had the highest and lowest weight, respectively. The CDI is utilized to identify drought characteristics, such as duration and severity. In addition, the joint distribution function of drought characteristics is formed by copula functions and consequently the probability of different droughts is calculated. For the study area, data and information from eight regions located in Golestan province in the northern part of Iran are used to evaluate the performance of the proposed index. Four categories of drought were defined and their return period calculated. The shortest return period of severe drought was observed in the east and then in the west. In the south and center, the return period of severe drought was longer. Over the course of 30 years, all parts of the province experienced all drought categories.

scholarly journals A modified drought index for WMO RA VI

2011 ◽  
Vol 6 (1) ◽  
pp. 275-279 ◽  
Author(s):  
S. Pietzsch ◽  
P. Bissolli
Keyword(s):  
Arid Regions ◽  
Drought Index ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
The Internet ◽  
Precipitation Data ◽  
Heterogeneous Region ◽  
The Individual ◽  
Standardized Drought Index

Abstract. Drought is a phenomenon which can cause large economical impact even in Europe. To assess the magnitude and the spatial extension of drought events, it is important to have a standardized drought index which is applicable for a large climatically heterogeneous region like Europe or the WMO RA VI Region (Europe and the Middle East). Such an index should describe the drought phenomenon adequately, but it should also be derivable from meteorological quantities which are easily and timely available in whole Europe. In a first investigation, some candidates for drought indices were chosen, compared and assessed for applicability in whole Europe. The most appropriate one seems to be the widely known Standardized Precipitation Index (SPI) which is a standardized and handy measurement of drought for any location and requires nothing but precipitation data. However, it has turned out that for some places in the RA VI Region, notably in arid regions in summer, the SPI does not always provide reasonable or easily interpretable results. For that reason, some modifications of the SPI have been tried out and tested statistically. It seems that the gamma distribution of precipitation which is used for computation of the SPI is in fact the most appropriate one and other distributions have not improved the results substantially. On the other hand a so called zero correction, which sets very small precipitation totals to dry values, only dependent on the precipitation distribution, but independent on the individual location delivers more reasonable results. Maps of the new modified drought index and its anomalies from the climate normal are produced quasi-operationally and distributed via the Internet each month. The drought monitoring is part of the monitoring programme of the WMO RA VI Pilot Regional Climate Centre on Climate Monitoring (RCC-CM) hosted by the German Meteorological Service (Deutscher Wetterdienst, DWD), and the maps can be found on its present RCC-CM platform (http://www.dwd.de/rcc-cm).

scholarly journals Long-term trends in agricultural droughts over Netherlands and Germany: how extreme was the year 2018?

2021 ◽  
Author(s):  
Yafei Huang ◽  
Jonas Weis ◽  
Harry Vereecken ◽  
Harrie-Jan Hendricks Franssen
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Potential Evapotranspiration ◽  
Sandy Loam ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Moisture Index

Abstract. Droughts can have important impacts on environment and economy like in the year 2018 in parts of Europe. Droughts can be analyzed in terms of meteorological drought, agricultural drought, hydrological drought and social-economic drought. In this paper, we focus on meteorological and agricultural drought and analyzed drought trends for the period 1965–2019 and assessed how extreme the drought year 2018 was in Germany and the Netherlands. The analysis was made on the basis of the following drought indices: standardized precipitation index (SPI), standardized soil moisture index (SSI), potential precipitation deficit (PPD) and ET deficit. SPI and SSI were computed at two time scales, the period April-September and a 12-months period. In order to analyze drought trends and the ranking of the year 2018, HYDRUS 1-D simulations were carried out for 31 sites with long-term meteorological observations and soil moisture, potential evapotranspiration (ET) and actual ET were determined for five soil types (clay, silt, loam, sandy loam and loamy sand). The results show that the year 2018 was severely dry, which was especially related to the highest potential ET in the time series 1965–2019, for most of the sites. For around half of the 31 sites the year 2018 had the lowest SSI, and largest PPD and ET-deficit in the 1965–2019 time series, followed by 1976 and 2003. The trend analysis reveals that meteorological drought (SPI) hardly shows significant trends over 1965–2019 over the studied domain, but agricultural droughts (SSI) are increasing, at several sites significantly, and at even more sites PPD and ET deficit show significant trends. The increasing droughts over Germany and Netherlands are mainly driven by increasing potential ET and increasing vegetation water demand.

scholarly journals Comparison of Pálfai’s drought index and the Normalised Precipitation Index in the North Great Plain region

2015 ◽  
pp. 59-64
Author(s):  
Bernadett Gálya ◽  
Attila Nagy ◽  
Lajos Blaskó ◽  
Boglárka Dályai ◽  
János Tamás
Keyword(s):  
Agricultural Production ◽  
Drought Index ◽  
Crop Yields ◽  
Regional Scale ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Soil Conditions ◽  
Climate Conditions ◽  
Drought Assessment ◽  
The Impact

Agriculture has always been an important role in economy, food supplies, sustainability of society and creation of job opportunities in Hungary. Our country has resource-related strength of agriculture, because we have more than 4.5 million ha for agricultural production. Agricultural production can be influenced by several factors, including climate, hydrology, soil conditions and antropogenic impacts. Climate determines the quality and quantity of the crop yields. The climate conditions in Hungary are variable and it shows spatial and temporal extremes. As a result of this, drought have become more frequent in our country (2003, 2007, 2009, 2012), which is reflected in the decline in yields as well. In the present study, Pálfai's Drought Index (PAI) and the Standardized Precipitation Index (SPI) were compared 2003–2012 in Debrecen. The temperature and precipitation data were calculated from data provided by a local meteorological station to work out PAI, while the SPI-3 index values were downloaded from the database of the European Drought Observatory. This allowed to drought assessment in a local and regional scale. Our study was supplemented with SPI-3, soil moisture anomalies, PAI and yields of wheat (Triticum aestivum L.) and maize (Zea mays L.) to evaluating the impact of drought on agriculture.

scholarly journals EVALUATION OF THE SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI) AND PRECIPITATION-BASED DROUGHT INDICES IN ARGENTINA

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 53-58
Author(s):  
M. M. Salvia ◽  
N. Sánchez ◽  
M. Piles ◽  
A. Gonzalez-Zamora ◽  
J. Martínez-Fernández
Keyword(s):  
Soil Moisture ◽  
Gross Domestic Product ◽  
Surface Temperature ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Agricultural Exports ◽  
Hydric Stress ◽  
The Standardized Precipitation Index

Abstract. Agricultural drought is one of the most critical hazards with regard to intensity, severity, frequency, spatial extension and impact on livelihoods. This is especially true for Argentina, where agricultural exports can represent up to 10% of gross domestic product (GDP), and where drought events for 2018 led to a decrease of nearly 0.5% of GDP. In this work, we investigate the applicability of the Soil Moisture Agricultural Drought Index (SMADI) for detection of droughts in Argentina, and compare its performance with the use of two well-known precipitation-based indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation- Evaporation Index (SPEI). SMADI includes satellite-based information of soil moisture, surface temperature and vegetation greenness, and was designed to capture the hydric stress on the soil-vegetation ensemble. Results indicate that SMADI has greater capabilities for agricultural drought detection than SPI and SPEI: it was able to recognize more than 83% of the registered emergencies, correctly classifying 75% of them as extreme droughts, and outperforming SPI and SPEI in all the analyzed metrics.

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

2019 ◽  
Vol 19 (6) ◽  
pp. 1215-1234 ◽  
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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