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 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 Drought Monitoring for Washington State: Indicators and Applications

2011 ◽  
Vol 12 (1) ◽  
pp. 66-83 ◽  
Author(s):  
Shraddhanand Shukla ◽  
Anne C. Steinemann ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Standardized Precipitation Index ◽  
Land Surface Model ◽  
Washington State ◽  
Drought Monitoring ◽  
Surface Model ◽  
Drought Conditions ◽  
The Standardized Precipitation Index

Abstract A drought monitoring system (DMS) can help to detect and characterize drought conditions and reduce adverse drought impacts. The authors evaluate how a DMS for Washington State, based on a land surface model (LSM), would perform. The LSM represents current soil moisture (SM), snow water equivalent (SWE), and runoff over the state. The DMS incorporates the standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture percentile (SMP) taken from the LSM. Four historical drought events (1976–77, 1987–89, 2000–01, and 2004–05) are constructed using DMS indicators of SPI/SRI-3, SPI/SRI-6, SPI/SRI-12, SPI/SRI-24, SPI/SRI-36, and SMP, with monthly updates, in each of the state’s 62 Water Resource Inventory Areas (WRIAs). The authors also compare drought triggers based on DMS indicators with the evolution of drought conditions and management decisions during the four droughts. The results show that the DMS would have detected the onset and recovery of drought conditions, in many cases, up to four months before state declarations.

scholarly journals A Nonparametric Multivariate Multi-Index Drought Monitoring Framework

2014 ◽  
Vol 15 (1) ◽  
pp. 89-101 ◽  
Author(s):  
Zengchao Hao ◽  
Amir AghaKouchak
Keyword(s):  
Soil Moisture ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Multi Index ◽  
Additional Information ◽  
Indicator Variables ◽  
Monitoring Framework ◽  
Drought Mitigation ◽  
The Standardized Precipitation Index

Abstract Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, drought monitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDM and provides additional information and insights into drought monitoring.

scholarly journals Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2592 ◽  
Author(s):  
María del Pilar Jiménez-Donaire ◽  
Juan Vicente Giráldez ◽  
Tom Vanwalleghem
Keyword(s):  
Soil Moisture ◽  
Soil Depth ◽  
Standardized Precipitation Index ◽  
Early Warning Systems ◽  
Agricultural Drought ◽  
Annual Precipitation ◽  
Drought Indices ◽  
Climate Data ◽  
Management Tools ◽  
The Standardized Precipitation Index

The early and accurate detection of drought episodes is crucial for managing agricultural yield losses and planning adequate policy responses. This study aimed to evaluate the potential of two novel indices, static and dynamic plant water stress, for drought detection and yield prediction. The study was conducted in SW Spain (Córdoba province), covering a 13-year period (2001–2014). The calculation of static and dynamic drought indices was derived from previous ecohydrological work but using a probabilistic simulation of soil moisture content, based on a bucket-type soil water balance, and measured climate data. The results show that both indices satisfactorily detected drought periods occurring in 2005, 2006 and 2012. Both their frequency and length correlated well with annual precipitation, declining exponentially and increasing linearly, respectively. Static and dynamic drought stresses were shown to be highly sensitive to soil depth and annual precipitation, with a complex response, as stress can either increase or decrease as a function of soil depth, depending on the annual precipitation. Finally, the results show that both static and dynamic drought stresses outperform traditional indicators such as the Standardized Precipitation Index (SPI)-3 as predictors of crop yield, and the R2 values are around 0.70, compared to 0.40 for the latter. The results from this study highlight the potential of these new indicators for agricultural drought monitoring and management (e.g., as early warning systems, insurance schemes or water management tools).

scholarly journals Assessment of SMADI and SWDI agricultural drought indices using remotely sensed root zone soil moisture

2018 ◽  
Vol 380 ◽  
pp. 55-66
Author(s):  
Miriam Pablos ◽  
Ángel González-Zamora ◽  
Nilda Sánchez ◽  
José Martínez-Fernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Water Deficit ◽  
Surface Soil ◽  
Root Zone ◽  
Soil Layer ◽  
Statistical Correlation ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Moisture Index

Abstract. The increasing frequency of drought events has expanded the research interest in drought monitoring. In this regard, remote sensing is a useful tool to globally mapping the agricultural drought. While this type of drought is directly linked to the availability of root zone soil moisture (RZSM) for plants growth, current satellite soil moisture observations only characterize the water content of the surface soil layer (0–5 cm). In this study, two soil moisture-based agricultural drought indices were obtained at a weekly rate from June 2010 to December 2016, using RZSM estimations at 1 km from the Soil Moisture and Ocean Salinity (SMOS) satellite, instead of surface soil moisture (SSM). The RZSM was estimated by applying the Soil Water Index (SWI) model to the SMOS SSM. The Soil Moisture Agricultural Drought Index (SMADI) and the Soil Water Deficit Index (SWDI) were assessed over the Castilla y León region (Spain) at 1 km spatial resolution. They were compared with the Atmospheric Water Deficit (AWD) and the Crop Moisture Index (CMI), both computed at different weather stations distributed over the study area. The level of agreement was analyzed through statistical correlation. Results showed that the use of RZSM does not influence the characterization of drought, both for SMADI and SWDI.

Drought planning and management: experience in the Seyhan River Basin, Turkey

Water Policy ◽  
2016 ◽  
Vol 18 (S2) ◽  
pp. 177-209 ◽  
Author(s):  
Ismail Kaan Tuncok
Keyword(s):  
River Basin ◽  
Eastern Mediterranean ◽  
Methodological Approach ◽  
Standardized Precipitation Index ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Drought Planning ◽  
Planning And Management ◽  
Drought Conditions ◽  
The Standardized Precipitation Index

The focus of this study was to integrate drought planning and management into local and regional decision-making processes in the Seyhan River Basin, which is the second-largest basin after the Nile in the Eastern Mediterranean and agriculturally one of the most productive regions in Turkey and Europe. The methodological approach consisted of two steps: Step 1 – review and analyse historical data sets to evaluate and characterize water resources and drought-driven elements; Step 2 – evaluate drought indices to characterize drought conditions through use of the Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index. Historical and future expected drought periods were identified in the context of hydrologic, meteorologic and agricultural drought conditions.

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 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.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

scholarly journals Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin

2005 ◽  
Vol 9 (5) ◽  
pp. 523-533 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
J. I. López-Moreno
Keyword(s):  
Time Scales ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Long Time ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Different Time Scales

Abstract. At present, the Standardized Precipitation Index (SPI) is the most widely used drought index to provide good estimations about the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI in comparison with other indices is the fact that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. It is widely accepted that SPI time scales affect different sub-systems in the hydrological cycle due to the fact that the response of the different water usable sources to precipitation shortages can be very different. The long time scales of SPI are related to hydrological droughts (river flows and reservoir storages). Nevertheless, few analyses empirically verify these statements or the usefulness of the SPI time scales to monitor drought. In this paper, the SPI at different time scales is compared with surface hydrological variables in a big closed basin located in the central Spanish Pyrenees. We provide evidence about the way in which the longer (>12 months) SPI time scales may not be useful for drought quantification in this area. In general, the surface flows respond to short SPI time scales whereas the reservoir storages respond to longer time scales (7–10 months). Nevertheless, important seasonal differences can be identified in the SPI-usable water sources relationships. This suggests that it is necessary to test the drought indices and time scales in relation to their usefulness for monitoring different drought types under different environmental conditions and water demand situations.

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