Sensitivity analysis of drought indices under substantially different agricultural systems in North and South Koreas

2020 ◽  
Author(s):  
Seonyoung Park ◽  
Jongmin Yeom ◽  
Jeongho Lee ◽  
Jaese Lee ◽  
Jungho Im ◽  
...  
Keyword(s):  
Soil Moisture ◽  
South Korea ◽  
Soil Water ◽  
Correlation Coefficient ◽  
Drought Index ◽  
Rice Yield ◽  
Rice Production ◽  
Drought Indices ◽  
Irrigation Canals ◽  
North And South

<p>Rice is a staple food in the North and South Koreas. Rice yield is closely related to water supply including irrigation, precipitation, and soil water. Drought typically occurs due to the lack of precipitation, and prolonged drought leads to the decrease of soil water, which results in plant water stress. Drought monitoring is crucial for agricultural mitigation because it enables us to estimate rice production in a timely manner. The purpose of this study is to suggest an optimal drought index for monitoring agricultural drought over North and South Koreas. Although North and South Koreas have similar climate conditions, they have different levels of infrastructure for agriculture such as irrigation facilities. In this study, nine satellite-based drought indices were used and evaluated based on in situ measurements at weather stations including Standardized Precipitation Index (SPI) and rice yield. Drought indices were calculated using the Global Land Data Assimilation System (GLDAS) soil moisture, Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). Since various drought indices have been developed with their own purpose, considering the characteristics of the study area under investigation, their applications for other regions are relatively limited. Thus, comparison of various drought indices is needed to identify an optimal drought index for a certain area. The measurable objectives of this research were to 1) compare the characteristics of drought depending on the properties of drought indices such as temperature, vegetation, precipitation, and soil moisture and 2) evaluate various drought indices using SPIs and rice yield data. The performance of the drought indices was evaluated using correlation coefficient values (R) for reference data (i.e., SPI and rice yield). As expected, drought indices including NDVI showed positive relationships with rice yield in both regions (averaged R=0.37). Meanwhile, temperature based drought indices showed negative relationships with rice yield in both regions because high temperature means high solar radiation, which is essential to rice production. While the correlation coefficient between precipitation based indices and rice yield was positive in North Korea (averaged R=0.34), it was negative in South Korea (averaged R=-0.26). The opposite pattern by area is because South Korea (117,457 irrigation Canals) has more artificial controls over agricultural land such as irrigation facilities and reservoirs than North Korea (51,400 irrigation Canals).</p>

scholarly journals Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

2010 ◽  
Vol 14 (2) ◽  
pp. 271-277 ◽  
Author(s):  
E. Peled ◽  
E. Dutra ◽  
P. Viterbo ◽  
A. Angert
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Technical Note ◽  
Temperate Climate ◽  
Drought Indices ◽  
Soil Drought ◽  
The Past ◽  
Analysis Technique ◽  
Global Soil ◽  
Warm Temperate

Abstract. In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis) technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

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.

The Ongoing Central European Drought Observed with GRACE Follow-On

2020 ◽  
Author(s):  
Eva Boergens ◽  
Andreas Güntner ◽  
Henryk Dobslaw ◽  
Christoph Dahle
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Surface Water ◽  
Central Europe ◽  
Drought Index ◽  
Water Mass ◽  
Water Storage ◽  
Drought Indices ◽  
Severe Drought ◽  
Data Set

<p class="western">In the last three years Central Europe experienced an ongoing severe drought. With the data of the GRACE Follow-On (GRACE-FO) mission we are able to quantify the water deficit of these years. Since May 2018 GRACE-FO continues the observations of GRACE (2002-2017) allowing to compare the most recent drought with earlier droughts in 2003 and 2015.</p> <p class="western">In July 2019 the water mass deficit in Central Europe amounted to -154 Gt, which has been the largest deficit in the whole GRACE and GRACE-FO time series. In November 2018 the deficit reached -138 Gt and in June 2020 -147 Gt. Comparing these deficits to the mean annual water storage variation of 162 Gt shows the severity of the ongoing drought. With such a water mass deficit, a fast recovery within one year cannot be expected. In comparison to this, the droughts of 2003 with a deficit of -55 Gt and of 2015 with a deficit of -111 Gt were less severe.</p> <p class="western">The GRACE and GRACE-FO total water storage data set also allows for analysing spatio-temporal drought patterns. In 2018 the drought was centred in in the South-West of Germany and neighbouring countries while parts of Poland were hardly affected by the drought. In 2018 the drought reached its largest extent only in late autumn. However, the exact onset of drought is not determinable due to missing data between July and October. Both in 2019 and 2020 the centre of the drought is located further East and the months with the largest deficit were July and June, respectively. Also in the later years, the drought was more evenly spread out over the whole of Central Europe.</p> <p class="western">Additionally, we compared the GRACE and GRACE-FO data to an external soil moisture index and to surface water drought indices for Lake Constance and Lake Müritz. To this end, we derive a drought index from the GRACE and GRACE-FO mass anomalies. For the whole time series, the GRACE drought index shows a high congruency to the soil moisture drought index. Overall, the surface water drought index also fits well together with the GRACE drought index. However, the comparison reveals the influence of regional effects on surface waters not observable with GRACE and GRACE-FO.</p>

Assessment of the JULES model surface soil moisture using in-situ observations over the Brazilian North East semiarid region

2020 ◽  
Author(s):  
Marcelo Zeri ◽  
Karina Williams ◽  
Eleanor Blyth ◽  
Ana Paula Cunha ◽  
Toby Marthews ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Land Surface ◽  
Semiarid Region ◽  
Drought Indices ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Drought Risk ◽  
Rainfed Agriculture ◽  
North East

<p>Monitoring of soil water is essential to assess drought risk over rainfed agriculture. Soil water indicates the onset or progress of dry spells, the start of the rainy season and good periods for sowing or harvesting. Monitoring soil water over rainfed agriculture can be a valuable tool to support field activities and the knowledge of climate risks.</p><p>A network of soil moisture sensors was established over the Brazilian North East semiarid region in 2015 with measurements at 10 and 20 cm, together with rainfall and other variables in a subset of locations. The data are currently being used to assess the available water over the region in monthly bulletins and reports of potential impacts on yields.</p><p>In this work, we present a comparison of a dataset of observations from 2015 to 2019 with the soil water estimated by the JULES land surface model (the Joint UK Land Environment Simulator). Overall, the model captures the spatial and temporal variability observed in the measured data well, with an average correlation coefficient of 0.6 across the domain. The performance was compared for each station, resulting in a selection of locations with significant correlation.</p><p>Based on the regression results, we derive modelled soil moisture for the time span of the JULES run (1979 to 2016). The modeled data enabled the calculation of a standardized soil moisture anomaly (SSMA). The values of SSMA in the period were in agreement with the patterns of drought in the region, especially the recent long-term drought in the Brazilian semiarid region, with significant dry years in 2012, 2013 and 2015. Further analysis will focus on comparisons with other drought indices and measures of impacts on yields at the municipality level.</p>

scholarly journals Development and Evaluation of an Agricultural Drought Index by Harnessing Soil Moisture and Weather Data

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1375 ◽  
Author(s):  
Ali Ajaz ◽  
Saleh Taghvaeian ◽  
Kul Khand ◽  
Prasanna H. Gowda ◽  
Jerry E. Moorhead
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Drought Index ◽  
Root Zone ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Growth Stages

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.

scholarly journals A hybrid drought index for drought assessment in Wadi Shueib catchment area in Jordan

2020 ◽  
Vol 22 (4) ◽  
pp. 937-956
Author(s):  
Odai Al Balasmeh ◽  
Richa Babbar ◽  
Tapas Karmaker
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Drought Index ◽  
Agricultural Drought ◽  
Wavelet Coherence ◽  
Sunspot Activity ◽  
Drought Indices ◽  
Entropy Weight ◽  
Drought Assessment ◽  
Near Future

Abstract Wadi Shueib catchment in Jordan is a water stress area and climate change is creating a further deficiency in precipitation, streamflow, and soil moisture; which are a deterrent to agriculture production in the area. In order to analyze the drought-like situation in the area, a hybrid drought index (HDI) has been developed considering the combined effect of these three variables. Fuzzy analytical hierarchy process (F-AHP) and entropy weight methods were carried out to develop a hybrid drought index (HDI) which combines meteorological, hydrological, and agricultural drought indices based on precipitation, streamflow, and soil moisture data in the area. The wavelet transform (WT) with cross wavelet (XCT) and wavelet coherence (WTC) were applied to investigate the interaction and the relations between the HDI index, drought indices, and large-scale sunspot activity Niño3.4 index. The results show that HDI can easily capture the trend of the drought-like conditions in the area based on the available data. The trend analysis of HDI revealed an increasing trend in the drought incidences in the near future. The study can be used as an early alarm for drought in the area, which can be helpful in the decision-making process towards water resources planning and management in the future.

scholarly journals Reliability of meteorological drought indices for predicting soil moisture droughts

2016 ◽  
Author(s):  
Devanmini Halwatura ◽  
Neil McIntyre ◽  
Alex M. Lechner ◽  
Sven Arnold
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Pressure ◽  
Meteorological Drought ◽  
Water Model ◽  
Water Retention Curve ◽  
Drought Indices ◽  
Drought Duration ◽  
Eastern Australia ◽  
Shallow Soils

Abstract. Meteorological drought indices based on precipitation and/or evaporation are commonly used to detect the presence, severity and duration of soil moisture droughts. However, it is debatable whether droughts can be adequately characterised using only precipitation and/evaporation, or whether more physical based methods using soil water deficits and pressures is necessary. To address this question, the performances of two commonly used meteorological drought indices, the Standard Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI), are evaluated against soil moisture droughts identified using a physically based soil water model. Our analysis is based on three sites in Eastern Australia, each representing specific soil-climate conditions. Drought duration and severity were estimated using SPI and RDI and soil water pressure data were simulated with Hydrus-1D. The performance of the two drought indices was measured in terms of their correlation with simulated monthly minimum soil water pressures, and their ability to estimate the frequency with which the simulated pressure drops below threshold values. There was a significant correlation between the two drought indices (SPI and RDI) and the monthly minimum soil water pressure. Failure rate (FR) and false alarm rate (FAR) of drought indices detect soil moisture drought reasonably well (FR and FAR is <50 %) for both drought indices (SPI and RDI) and soil depths (5 cm and 30 cm) (except Melbourne). Overall SPI performs better (except shallow soils in Bourke) than RDI. However an uncertainty of the FR and FAR in the soil water retention curve is always higher than the uncertainties of drought indices. The complexity and the uncertainty in the model encourage to use the simple drought indices, however the model provide physically relevant soil water pressure values which are species specific for plants.

scholarly journals Development and application of a short- /long-term composited drought index in the upper Huaihe River basin, China

2015 ◽  
Vol 369 ◽  
pp. 103-108
Author(s):  
M. Yu ◽  
Q. Li ◽  
G. Lu ◽  
H. Wang ◽  
P. Li
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Drought Index ◽  
The Self ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Short Term

Abstract. Accurate and reliable drought monitoring is of primary importance for drought mitigation and reduction of social-ecological vulnerability. The aim of the paper was to propose a short-term/long-term composited drought index (CDI) which could be widely used for drought monitoring and early warning in China. In the study, the upper Huaihe River basin above the Xixian gauge station, which has been hit by severe droughts frequently in recent decades, was selected as the case study site. The short-term CDI was developed by the Principle Component Analysis of the self-calibrating Palmer Drought Severity Index (sc-PDSI), the 1- and 3-month Standardized Precipitation Evapotranspiration Index (SPEI), Z Index (ZIND), the Soil Moisture Index (SMI) with the long-term CDI being formulated by use of the self-calibrating Palmer Hydrology Drought Index (sc-PHDI), the 6-, 12-, 18- and 24-month SPEI, the Standardized Streamflow Index (SSI), the SMI. The sc-PDSI, the PHDI, the ZIND, the SPEI on a monthly time scale were calculated based on the monthly air temperature and precipitation, and the monthly SMI and SSI were computed based on the simulated soil moisture and runoff by the distributed Xinanjiang model. The thresholds of the short-term/long-term CDI were determined according to frequency statistics of different drought indices. Finally, the feasibility of the two CDIs was investigated against the scPDSI, the SPEI and the historical drought records. The results revealed that the short-term/long-term CDI could capture the onset, severity, persistence of drought events very well with the former being better at identifying the dynamic evolution of drought condition while the latter better at judging the changing trend of drought over a long time period.

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