scholarly journals Soil moisture and streamflow deficit anomaly index: an approach to quantify drought hazards by combining deficit and anomaly

2021 ◽  
Vol 21 (5) ◽  
pp. 1337-1354
Author(s):  
Eklavyya Popat ◽  
Petra Döll
Keyword(s):  
Soil Moisture ◽  
Water Supply ◽  
Hydrological Cycle ◽  
Well Being ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Risk ◽  
Spatial And Temporal Patterns ◽  
Drought Hazard ◽  
Anomaly Index

Abstract. Drought is understood as both a lack of water (i.e., a deficit compared to demand) and a temporal anomaly in one or more components of the hydrological cycle. Most drought indices, however, only consider the anomaly aspect, i.e., how unusual the condition is. In this paper, we present two drought hazard indices that reflect both the deficit and anomaly aspects. The soil moisture deficit anomaly index, SMDAI, is based on the drought severity index, DSI (Cammalleri et al., 2016), but is computed in a more straightforward way that does not require the definition of a mapping function. We propose a new indicator of drought hazard for water supply from rivers, the streamflow deficit anomaly index, QDAI, which takes into account the surface water demand of humans and freshwater biota. Both indices are computed and analyzed at the global scale, with a spatial resolution of roughly 50 km, for the period 1981–2010, using monthly time series of variables computed by the global water resources and the model WaterGAP 2.2d. We found that the SMDAI and QDAI values are broadly similar to values of purely anomaly-based indices. However, the deficit anomaly indices provide more differentiated spatial and temporal patterns that help to distinguish the degree and nature of the actual drought hazard to vegetation health or the water supply. QDAI can be made relevant for stakeholders with different perceptions about the importance of ecosystem protection, by adapting the approach for computing the amount of water that is required to remain in the river for the well-being of the river ecosystem. Both deficit anomaly indices are well suited for inclusion in local or global drought risk studies.

scholarly journals Soil moisture and streamflow deficit anomaly index: An approach to quantify drought hazards by combining deficit and anomaly

2020 ◽  
Author(s):  
Eklavyya Popat ◽  
Petra Döll
Keyword(s):  
Soil Moisture ◽  
Water Supply ◽  
Hydrological Cycle ◽  
Well Being ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Risk ◽  
Spatial And Temporal Patterns ◽  
Drought Hazard ◽  
Anomaly Index

Abstract. Drought is understood as both a lack of water (i.e., a deficit as compared to some requirement) and an anomaly in the condition of one or more components of the hydrological cycle. Most drought indices, however, only consider the anomaly aspect, i.e., how unusual the condition is. In this paper, we present two drought hazard indices that reflect both the deficit and anomaly aspects. The soil moisture deficit anomaly index, SMDAI, is based on the drought severity index, DSI, but is computed in a more straightforward way that does not require the definition of a mapping function. We propose a new indicator of drought hazard for water supply from rivers, the streamflow deficit anomaly index, QDAI, which takes into account the surface water demand of humans and freshwater biota. Both indices are computed and analyzed at the global scale, with a spatial resolution of roughly 50 km, for the period 1981–2010, using monthly time series of variables computed by the global water resources and the model WaterGAP2.2d. We found that the SMDAI and QDAI values are broadly similar to values of purely anomaly-based indices. However, the deficit anomaly indices provide more differentiated, spatial and temporal patterns that help to distinguish the degree of the actual drought hazard to vegetation health or the water supply. QDAI can be made relevant for stakeholders with different perceptions about the importance of ecosystem protection, by adopting the approach for computing the amount of water that is required to remain in the river for the well-being of the river ecosystem. Both deficit anomaly indices are well suited for inclusion in local or global drought risk studies.

scholarly journals A drought monitoring framework for data-scarce regions

2019 ◽  
Vol 22 (1) ◽  
pp. 170-185 ◽  
Author(s):  
Roberto A. Real-Rangel ◽  
Adrián Pedrozo-Acuña ◽  
J. Agustín Breña-Naranjo ◽  
Víctor H. Alcocer-Yamanaka
Keyword(s):  
Temporal Distribution ◽  
Probability Of Detection ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Drought Risk ◽  
Spatial And Temporal Patterns ◽  
Maize Production ◽  
Drought Hazard ◽  
Hydrological Variables

Abstract Drought monitoring is a critical activity for drought risk management; however, the lack of ground-based observations of climatological and hydrological variables in many regions of the world hinders an adequate follow-up and investigation of this phenomenon. This paper introduces a transparent framework for monitoring the spatio-temporal distribution of drought hazard based on uni- and multivariate standardized drought indices that use reanalysis datasets of hydrological variables available freely and globally. In the case study of the 2015–2017 East-Southwest drought in Mexico, the introduced framework successfully detected the spatial and temporal patterns of drought conditions, even in regions where a benchmark drought monitoring system failed to detect deficits. In addition, the ability of the introduced framework to detect drought impacts on the annual agricultural maize production in Mexico was evaluated using data of 1980–2018, yielding scores of the false alarm ratio =0.32, the probability of detection = 0.71, and the proportion correct = 0.68 for the analysis at the national scale. Currently, the framework provides a significant extension to the capabilities for national drought monitoring, and it is being used by the Mexican water authority in the decision-making process related to drought severity assessment.

scholarly journals Analysis of drought characteristics for improved understanding of a water resource system

2014 ◽  
Vol 364 ◽  
pp. 404-409 ◽  
Author(s):  
A. T. Lennard ◽  
N. Macdonald ◽  
J. Hooke
Keyword(s):  
Resource Management ◽  
Water Supply ◽  
Water Resource ◽  
Water Resource Management ◽  
Drought Indices ◽  
Drought Severity ◽  
Small Scale ◽  
Water Resource System ◽  
Drought Characteristics ◽  
Standardised Precipitation Index

Abstract. Droughts are a reoccurring feature of the UK climate; recent drought events (2004–2006 and 2010–2012) have highlighted the UK’s continued vulnerability to this hazard. There is a need for further understanding of extreme events, particularly from a water resource perspective. A number of drought indices are available, which can help to improve our understanding of drought characteristics such as frequency, severity and duration. However, at present little of this is applied to water resource management in the water supply sector. Improved understanding of drought characteristics using indices can inform water resource management plans and enhance future drought resilience. This study applies the standardised precipitation index (SPI) to a series of rainfall records (1962–2012) across the water supply region of a single utility provider. Key droughts within this period are analysed to develop an understanding of the meteorological characteristics that lead to, exist during and terminate drought events. The results of this analysis highlight how drought severity and duration can vary across a small-scale water supply region, indicating that the spatial coherence of drought events cannot be assumed.

Flash Drought Characteristics by Different Severities in Humid Subtropical Basins: A Case Study in the Gan River Basin, China

2021 ◽  
pp. 1-44
Author(s):  
Yuqing Zhang ◽  
Qinglong You ◽  
Guangxiong Mao ◽  
Changchun Chen ◽  
Xin Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Vapour Pressure Deficit ◽  
Severity Index ◽  
Drought Severity ◽  
Rapid Decline ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Period ◽  
Drought Intensity

AbstractIt is essential to assess flash drought risk based on a reliable flash drought intensity (severity) index incorporating comprehensive information of the rapid decline (“flash”) in soil moisture towards drought conditions and soil moisture thresholds belonging to the “drought” category. In this study, we used the Gan River Basin as an example to define a flash drought intensity index that can be calculated for individual time steps (pentads) during a flash drought period over a given grid (or station). The severity of a complete flash drought event is the sum of the intensity values during the flash drought. We explored the spatial and temporal characteristics of flash droughts with different grades based on their respective severities. The results show that decreases in total cloud cover, precipitation, and relative humidity, as well as increases in 500 hPa geopotential height, convective inhibition, temperature, vapour pressure deficit, and wind speed can create favorable conditions for the occurrence of flash droughts. Although flash droughts are relatively frequent in the central and southern parts of the basin, the severity is relatively high in the northern part of the basin due to longer duration. Flash drought severity shows a slightly downward trend due to decreases in frequency, duration, and intensity from 1961 to 2018. Extreme and exceptional flash droughts decrease significantly while moderate and severe flash droughts trend slightly upward. Flash drought severity appears to be more affected by the interaction between duration and intensity as the grade increases from mild to severe. The frequency and duration of flash droughts are higher in July to October. The southern part of the basin is more prone to moderate and severe flash droughts, while the northern parts of the basin are more vulnerable to extreme and exceptional flash droughts due to longer durations and greater severities than other parts. Moderate, severe, extreme, and exceptional flash droughts occurred approximately every 3-6, 5-15, 10-50, and 30-200 year intervals, respectively, based on the copula analysis.

Drought

Geography ◽  
2020 ◽  
Author(s):  
Woonsup Choi
Keyword(s):  
Soil Moisture ◽  
Atmospheric Circulation ◽  
Agricultural Drought ◽  
Subsurface Water ◽  
Drought Indices ◽  
Human Society ◽  
Atmospheric Conditions ◽  
Spatial And Temporal Patterns ◽  
Circulation Anomalies ◽  
Atmospheric Circulation Anomalies

Drought is a natural disaster that has plagued human society throughout history. However, the meaning of drought varies by perspective and academic discipline, and the cause of drought is difficult to pinpoint. Despite the variation in its meaning, drought generally refers to the condition of an abnormally low amount of water for a given climate. Here the water can be precipitation, streamflow, soil moisture, groundwater, reservoir storage, and the like, but the lack of precipitation is a precursor for other types of drought. The lack of precipitation is often associated with anomalous atmospheric conditions such as atmospheric-circulation anomalies, higher-than-normal temperatures, and lower-than-normal relative humidity. Sea surface temperature anomalies may lead to sustained atmospheric-circulation anomalies. Drought defined as a lack of precipitation is often called meteorological or climatological drought. Other drought types can be classified within the context of the affected sectors, such as agricultural, hydrological, and socioeconomic drought. Agricultural drought generally refers to a lack of soil moisture, and hydrological drought refers to a lack of surface and subsurface water (e.g., streamflow and groundwater). Socioeconomic drought hampers human activities such as industry or water supply. As meteorological drought persists, other types of drought can follow. Such definitions of drought are regarded as conceptual definitions, but operational definitions are also necessary for quantitative understanding and management of drought events. Operational definitions use quantitative indices to identify the occurrence and characteristics of drought events such as onset, duration, termination, and deficit volume of drought. Much of existing drought research concerns developing, revising, and applying drought indices to investigate spatial and temporal patterns of drought at various geographical scales. Drought research has progressed along several directions, such as causes of drought, characteristics of drought events, impacts, and mitigation. Each of these directions is represented by the works cited in this article.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
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.

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 Agricultural biomass monitoring on watersheds based on remotely sensed data

2015 ◽  
Vol 72 (12) ◽  
pp. 2212-2220 ◽  
Author(s):  
János Tamás ◽  
Attila Nagy ◽  
János Fehér
Keyword(s):  
Spectral Data ◽  
River Basin ◽  
Yield Loss ◽  
Agricultural Land ◽  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Remotely Sensed ◽  
Drought Indices ◽  
Drought Risk ◽  
Drought Period

There is a close quality relationship between the harmful levels of all three drought indicator groups (meteorological, hydrological and agricultural). However, the numerical scale of the relationships between them is unclear and the conversion of indicators is unsolved. Different areas or an area with different forms of drought cannot be compared. For example, from the evaluation of meteorological drought using the standardized precipitation index (SPI) values of a river basin, it cannot be stated how many tonnes of maize will be lost during a given drought period. A reliable estimated rate of yield loss would be very important information for the planned interventions (i.e. by farmers or river basin management organisations) in terms of time and cost. The aim of our research project was to develop a process which could provide information for estimating relevant drought indexes and drought related yield losses more effectively from remotely sensed spectral data and to determine the congruency of data derived from spectral data and from field measurements. The paper discusses a new calculation method, which provides early information on physical implementation of drought risk levels. The elaborated method provides improvement in setting up a complex drought monitoring system, which could assist hydrologists, meteorologists and farmers to predict and more precisely quantify the yield loss and the role of vegetation in the hydrological cycle. The results also allow the conversion of different-purpose drought indices, such as meteorological, agricultural and hydrological ones, as well as allow more water-saving agricultural land use alternatives to be planned in the river basins.

scholarly journals Drought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium)

2021 ◽  
Vol 21 (1) ◽  
pp. 39-51
Author(s):  
Buruk Kitachew Wossenyeleh ◽  
Kaleb Asnake Worku ◽  
Boud Verbeiren ◽  
Marijke Huysmans
Keyword(s):  
Hydrological Cycle ◽  
Groundwater Resources ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Severity ◽  
Threshold Method ◽  
Groundwater System ◽  
Variable Threshold ◽  
Groundwater Drought ◽  
Temporary Decrease

Abstract. Drought can be described as a temporary decrease in water availability over a significant period that affects both surface and groundwater resources. Droughts propagate through the hydrological cycle and may impact vulnerable ecosystems. This paper investigates drought propagation in the hydrological cycle, focusing on assessing its impact on a groundwater-fed wetland ecosystem. Meteorological drought indices were used to analyze meteorological drought severity. Moreover, a method for assessing groundwater drought and its propagation in the aquifer was developed and applied. Groundwater drought was analyzed using the variable threshold method. Furthermore, meteorological drought and groundwater drought on recharge were compared to investigate drought propagation in the hydrological cycle. This research is carried out in the Doode Bemde wetland in central Belgium. The results of this research show that droughts are attenuated in the groundwater system. The number and severity of drought events on groundwater discharge were smaller than for groundwater recharge. However, the onset of both drought events occurred at the same time, indicating a quick response of the groundwater system to hydrological stresses. In addition, drought propagation in the hydrological cycle indicated that not all meteorological droughts result in groundwater drought. Furthermore, this drought propagation effect was observed in the wetland.

scholarly journals Twenty-First Century Drought Analysis Across China using CMIP6 Under Climate Change

2021 ◽  
Author(s):  
Gengxi Zhang ◽  
Thian Yew Gan ◽  
Xiaoling Su
Keyword(s):  
Soil Moisture ◽  
General Circulation ◽  
Coupled Model ◽  
Severity Index ◽  
General Circulation Models ◽  
Mitigation Strategies ◽  
Drought Indices ◽  
Drought Severity ◽  
Moisture Index ◽  
Arid Northwestern China

Abstract Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices (the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)). Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the 21st century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in humid regions. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices are crucial in project representative future droughts and meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact.

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