Groundwater Drought Index Research Articles

Monthly and Seasonal Drought Characterization Using GRACE-Based Groundwater Drought Index and Its Link to Teleconnections across South Indian River Basins

Traditional drought monitoring is based on observed data from both meteorological and hydrological stations. Due to the scarcity of station observation data, it is difficult to obtain accurate drought distribution characteristics, and also tedious to replicate the large-scale information of drought. Thus, Gravity Recovery and Climate Experiment (GRACE) data are utilized in monitoring and characterizing regional droughts where ground station data is limited. In this study, we analyzed and assessed the drought characteristics utilizing the GRACE Groundwater Drought Index (GGDI) over four major river basins in India during the period of 2003–2016. The spatial distribution, temporal evolution of drought, and trend characteristics were analyzed using GGDI. Then, the relationship between GGDI and climate factors were evaluated by the method of wavelet coherence. The results indicate the following points: GRACE’s quantitative results were consistent and robust for drought assessment; out of the four basins, severe drought was noticed in the Cauvery river basin between 2012 and 2015, with severity of −27 and duration of 42 months; other than Godavari river basin, the remaining three basins displayed significant negative trends at monthly and seasonal scales; the wavelet coherence method revealed that climate factors had a substantial effect on GGDI, and the impact of Southern Oscillation Index (SOI) on drought was significantly high, followed by Sea Surface Temperature (SST) Index (namely, NINO3.4) and Multivariate El Niño–Southern Oscillation Index (MEI) in all the basins. This study provides reliable and robust quantitative result of GRACE water storage variations that shares new insights for further drought investigation.

Drought characterization using the Combined Terrestrial Evapotranspiration Index over the Indus, Ganga and Brahmaputra river basins

Drought is a recurring natural disaster, which significantly affects the economy and environment of diverse geographical area worldwide. Therefore, it is imperative to develop a new technique that enables comprehensive identification and monitoring of drought over a large spatial extent. In this study, a new drought index called Combined Terrestrial Evapotranspiration Index (CTEI) is developed by using a combination of Gravity Recovery and Climate Experiment (GRACE) data and meteorological parameters, i.e. precipitation (P) and potential evapotranspiration (PET) over the Indus, Ganga, and the Brahmaputra (IGB) river basins. Further, the results of CTEI are compared with pre-existing drought indices, which highlighted good correlation with GRACE Groundwater Drought Index (GGDI) (ρ = 0.88), Water storage deficit index (WSDI) (ρ = 0.96), Combined Climatologic Deviation Index (CCDI) (ρ = 0.97) and Standardized Precipitation-Evapotranspiration Index (SPEI) (ρ = 0.49). It also compared with In-situ Groundwater Drought Index (IGDI) derived by groundwater observation wells. The mean annual CTEI exhibited a strong correlation with IGDI (0.49 to 0.77) and climatic parameters (P, PET, and land surface temperature). Outcomes illustrated a significant potential of CTEI index and extended the utility of GRACE derived Terrestrial Water Storage observations for drought characterization as well as quantification of its severity.

Development of a new integrated hydrological drought index (SRGI) and its application in the Heihe River Basin, China

In the context of climate change, hydrological processes between surface water and groundwater become increasingly complex, which may aggravate the risk of hydrological drought. As the complexity of factors influencing drought increases, traditional univariate drought indices are likely to be insufficient for accurate drought analysis. Therefore, it is important to develop an appropriate index combining surface water and groundwater for comprehensive monitoring of hydrological drought, and to understand the process of drought propagation to reduce the impact of droughts. This study develops the standardized runoff groundwater drought index (SRGI), which is a multi-variable model based on a combination of the standardized groundwater level drought index (SGI) and the standardized runoff drought index (SRI). The cross-wavelet transforms and correlation coefficient methods are used to reveal the linkages and propagation characteristics between meteorological and hydrological drought. The results indicate that (1) the generalized extreme value (GEV) distribution is generally suitable for the SGI calculation in the midstream of the Heihe River Basin (HHRB); (2) the SRGI, combining the advantages of the SRI and SGI, can detect droughts more accurately and timely than univariate drought indices, and it demonstrates a drought warning capability to some extent; (3) the lag time of the SRI/SRGI responding to the SPI notably varied with seasons, the longer in spring and winter and the shorter in summer and autumn. Additionally, the propagation time from the SRI to the SPI is shorter than that from the SRGI to the SPI in spring and autumn, the opposite is true in summer. (4) Positive correlations exist between the SRI/SRGI and the SPI during the period 1986–2010, which are relatively stable over longer periods, but ambiguous over shorter periods.

Utilizing GRACE-based groundwater drought index for drought characterization and teleconnection factors analysis in the North China Plain

Traditional drought monitoring methods rely on ground station data, which are difficult to reflect large-scale dynamic drought information. Thus, Gravity Recovery and Climate Experiment (GRACE) gravity satellite technology is applied to monitor and estimate drought, which can provide new data sources and measurement instruments for drought investigation. In this study, the GRACE groundwater drought index (GGDI) was utilized as a metric for assessing drought. The temporal evolution, spatial distribution and trend characteristics of drought were comprehensively identified in the North China Plain (NCP) from 2003 to 2015. Subsequently, the links between GGDI and teleconnection factors were clarified using cross wavelet transform technology. The results indicated that: (1) the quantitative results of GRACE were reliable and robust for drought evaluation; (2) the most serious drought event occurred from August 2013 to September 2014, with an average GGDI value of −1.36; (3) the monthly and seasonal droughts were increasing based on the modified Mann-Kendall (MMK) trend test method; and (4) the cross wavelet transform revealed that teleconnection factors had significant influences on drought evolution, and El Niño-Southern Oscillation (ENSO) had the strongest impact on drought in the NCP. This study sheds new insights into drought monitoring by using GRACE gravity satellite, which can be applied in other regions as well.

Drought Detection of Regional Nonparametric Standardized Groundwater Index

Groundwater drought index characterizes hydrological drought, aquifer characteristics and human disturbance in the hydrological system. For drought management, the values of standardized groundwater index (SGI) at local and regional scales are usually determined in a specific site and regional area. The SGI in the studied area is influenced mainly by precipitation, hydrogeology, and human disturbance occurring in the high-usage pumping area. The underlying signals of SGI at local and regional scales can therefore be identified using data clustering and decomposition analysis e.g. empirical orthogonal functions (EOFs). Using cluster analysis, the three primary SGI clusters of the investigated aquifer are identified to be situated at the proximal fan, mid-fan, and distal fan areas. With EOF, the meteorological drought pattern and the trend of long-term pumping in the aquifer are also identified. Specifically, the meteorological drought pattern is mainly from the proximal fan, while the over-pumping signal is from the coastal area of the distal fan. The regional SGI integrated with EOF is a useful and direct way for detecting and quantifying groundwater drought. The proposed method for identifying drought signals and sustainable zone for water supply is a substantial step toward an effective regional groundwater resource planning.

Global Assessment of Groundwater Sustainability Based On Storage Anomalies

AbstractThe world's largest aquifers are a fundamental source of freshwater used for agricultural irrigation and to meet human water needs. Therefore, their stored volume of groundwater is linked with water security, which becomes more relevant during periods of drought. This work focuses on understanding large‐scale groundwater changes, where we introduce an approach to evaluate groundwater sustainability at a global scale. We employ a groundwater drought index to assess performance metrics (reliability, resilience, vulnerability, and a combined sustainability index) for the largest and most productive global aquifers. Spatiotemporal changes in total water storage are derived from remote sensing observations of gravity anomalies, from which the groundwater drought index is inferred. The results reveal a complex relationship between the indicators, while considering monthly variability in groundwater storage. Combining the drought and sustainability indexes, as presented in this work, constitutes a measure for quantifying groundwater sustainability. This framework integrates changes in groundwater resources due to human influences and climate changes, thus opening a path to assess progress toward sustainable use and water security.

GRACE Groundwater Drought Index: Evaluation of California Central Valley groundwater drought

Quantitative approaches to assess the complexity of groundwater drought are hindered by the lack of direct observations of groundwater over space and time. Here, we present an approach to evaluate groundwater drought occurrence based on observations from NASA's Gravity Recovery and Climate Experiment (GRACE) satellite mission. Normalized GRACE-derived groundwater storage deviations are shown to quantify groundwater storage deficits during the GRACE record, which we define as the GRACE Groundwater Drought Index (GGDI). As a case study, GGDI is applied over the Central Valley of California, a regional aquifer undergoing intensive human activities and subject to significant drought periods during the GRACE record. Relations between GGDI and other hydrological drought indices highlight our ability to capture drought delays unique to groundwater drought. Further, GGDI captures characteristics of groundwater drought that occur as a result of complex human activities and natural changes, thus presenting a framework to assess multi-driver groundwater drought characteristics.

Drought indicators-based integrated assessment of drought vulnerability: a case study of Bundelkhand droughts in central India

Decision makers face multifaceted challenge in characterizing drought climatology for appropriate water resources-related drought management strategies. This paper focuses on understanding and quantifying the drought vulnerability of Bearma basin in the Bundelkhand region of central India, which is one of the prominent climate extremes that the region is affected by frequently. Regular drought conditions have been prevailing in the region in the last decade with continuous drought from 2004 to 2007. An integrated approach using multiple indicators has been developed to spatially identify the vulnerable regions. The Bearma basin has been selected as a pilot basin to develop a methodology for integrated drought vulnerability assessment adopting spatially and temporally varying drought characteristics represented by drought indicators. The temporally varying indicators include standardized precipitation index (SPI), surface water drought index and groundwater drought index. The spatial information of the indicators was categorized in layers prepared in the spatial domain using a geographic information system, and integrated values of weights of various indicators have been computed on a 50 × 50 m grid scale. The SPI has been applied to quantify monthly precipitation deficit anomalies on multiple time scales (1, 3, 6 and 12 months). The drought characteristics including frequency, duration and intensity and magnitude have been calculated with the estimated SPI. The multiple indicator approach has been used for arriving at the drought vulnerable zones. The highly vulnerable areas are located in the southern and northern regions of the Bearma basin. It has been observed that more than 26 % of the basin lies in the highly and critically vulnerable classes and consequently has greater drought-related negative impacts. Results show that the proposed method is highly effective in representing assessments of drought vulnerability.

Groundwater Drought Analysis of Sagar District in Bundelkhand Using Groundwater Drought Index (GDI)

Groundwater Drought Analysis of Sagar District in Bundelkhand Using Groundwater Drought Index (GDI)

Assessment of drought characteristics for Dhasan basin in Bundelkhand region

Drought monitoring is an important aspect for assessing and forecasting the drought risk for an area. The various types of drought including the meteorological drought and groundwater drought have been analysed using the appropriate drought indicators for Dhasan basin. This has helped in understanding the spatio-temporal variation of droughts including duration, severity and also helped to capture the progression and withdrawal of droughts during various months of the identified drought years. Based on the Effective Drought Index (EDI), four major drought events have been identified during 1981–82, 1988–89, 2002–03 and 2007–08. The drought severity assessment based on the EDI, indicates that the maximum drought severity of-33.49 had occurred during September 2006 and May 2008 and it was of longest duration (21 months) in the area under Banda rain gauging station. An increasing trend of meteorological drought severity has been observed for all the rain gauging stations in Dhasan basin. Hydrological drought characteristics have been evaluated using Groundwater Drought Index (GDI), which indicates that the groundwater drought severity is increasing gradually in the study area. During August 2002, about 0.78 sq. km. area was under severe drought whereas, during November 2002 about 46.01 sq. km. of the area was under severe drought and only 0.62 sq. km. area was under extreme drought conditions.

Comprehensive evaluation of the changing drought characteristics in Bundelkhand region of Central India

The evaluation of meteorological and hydrological drought characteristics including the dry spell analysis for planning of supplemental irrigation has been carried out for Bearma basin in Bundelkhand region of Central India. The Bundelkhand region has been under a spell of recurrent droughts. In the last decade, widespread droughts were felt during 2002–2003 and 2007–2008. The drought frequency varies between 1 in 3 years in Rehli and Deori and 1 in 5 years in Hatta. Rehli and Deori blocks falling in Sagar district have been identified to be drought prone. The meteorological drought characteristics evaluated by standardized precipitation index (SPI) indicated that drought severity has increased greatly with the drought intensity varying between −1.22 in Deori and −0.97 in Rehli. The streamflow drought characteristics have been evaluated using streamflow drought index (SDI), whereas the groundwater drought characteristics evaluated by groundwater drought index (GDI). The maximum groundwater drought intensity is observed in Rehli (−0.44). Two critical dry spells (CDS) of 14–18 days invariably occur during the principal rainy months of July and August, for which provision of life-saving supplementary irrigation is essential for the rain-fed agriculture. A drought management plan (DMP) has been developed, based on basin relevant drought indicators and drought triggers, designed and fined tuned to actual drought conditions in the basin. Based on the supply and demand scenario during droughts, an appropriate drought response plan linked to prevailing drought levels has been developed, to effectively manage the scarce water resources during persistent drought scenario. Results of the study are quite promising and the concept of DMP can be replicated to other basins in the region taking into account the basin relevant indicators as necessary.

Evaluation of a model-based groundwater drought indicator in the conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.