Baseflow response to climate variability induced droughts in the Apalachicola–Chattahoochee–Flint River Basin, U.S.A.

Singh, Sarmistha; Srivastava, Puneet; Abebe, Asheber; Mitra, Subhasis

doi:10.1016/j.jhydrol.2015.06.068

Cited by 37 publications

(28 citation statements)

References 32 publications

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“…() and Singh et al . () carried out similar studies to what we propose, examining the combined effects of the ENSO, the AMO and the PDO on streamflow and baseflow in the ACF, respectively. Johnson et al .…”

Section: Introductionmentioning

confidence: 79%

“…For the ACF study area, Johnson et al (2013) and Singh et al (2015) carried out similar studies to what we propose, examining the combined effects of the ENSO, the AMO and the PDO on streamflow and baseflow in the ACF, respectively. Johnson et al (2013) found for the ACF that the positive AMO was associated with increased streamflow in the north of the study area while El Niño was associated with increased streamflow in the south; when indices were combined the alteration in streamflow had increased significance.…”

Section: Introductionmentioning

confidence: 99%

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Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Maleski

Martinez

2018

Intl Journal of Climatology

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Large‐scale patterns of ocean surface temperature can influence weather across the globe and understanding their interaction with the local climate can improve seasonal forecasting of local temperature and precipitation. Here we focus on the combined interactions of the El Niño‐Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) in the Alabama–Coosa–Tallapoosa (ACT) and Apalachicola–Chattahoochee–Flint (ACF) river basins of the southeastern United States. Nonparametric ranks‐sum tests of individual and coupled impacts of these teleconnections on the annual study area climate (1895–2009) found significant impacts. A positive AMO phase was associated with decreased precipitation and increased mean temperature while the negative AMO phase was associated with increased precipitation and decreased temperature. While an El Niño event generally increases regional precipitation, El Niño during a positive AMO or PDO phase resulted in precipitation below the long‐term average in our study area. Because of many instances of El Niño being shared between AMO and PDO phase, the effects of the PDO and AMO on El Niño could not be distinguished. La Niña was associated with negative precipitation and increased temperature. The effects of La Niña on the temperature and precipitation anomaly were significantly increased during positive AMO and PDO phases. The coupled impacts of the aforementioned teleconnections demonstrate the necessity of including the effects of the AMO and the PDO when using ENSO‐based forecasts. The significant shifts on the effects of teleconnections on area climate from AMO negative phase to AMO positive phase cast doubt on seasonal prediction for the study area based on the recent history (i.e. the use of the period 1950–2000 to predict seasonal climate since 2000).

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Section: Introductionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Maleski

Martinez

2018

Intl Journal of Climatology

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“…In this study the clusters are monthly or seasonal and there is no indication that the underlying correlations are different for different years. Monthly baseflow values fluctuate around the same value irrespective of year but the level tends to be different from month to month (Singh et al, ).…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Nonparametric and Parametric Statistical Procedures for Modeling and Prediction of Cluster‐Correlated Hydroclimatic Data

Singh

Abebe

Srivastava

2018

Water Resources Research

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Climate and hydrologic variables such as temperature, precipitation, streamflow, and baseflow generally do not follow Gaussian distribution due to the presence of outliers and heavy tails. Therefore, they are usually analyzed using the nonparametric Wilcoxon rank sum test rather than parametric methods like classical t tests and analysis of variance. Furthermore, in addition to having a non‐Gaussian distribution, these data exhibit monthly/seasonal variability, which leads to within month/season cluster correlation. In this study, a nonparametric procedure, called joint rank fit (JRFit), for analyzing cluster‐correlated data was implemented and compared against traditional methods such as restricted maximum likelihood, least absolute deviations, and rank‐based fit (a model‐based extension of Wilcoxon rank sum) for studying the coupled effect of the phases of El Niño–Southern Oscillation and Atlantic Multidecadal Oscillation on baseflow levels. The results from a large Monte Carlo simulation experiment showed that JRFit was more efficient than the other three methods for data with (i) high variability, (ii) outliers due to contamination, or (iii) strong monthly/seasonal correlation. The efficiency gain of JRFit was up to 50% compared to restricted maximum likelihood for heavy‐tailed and highly correlated data. Predictive performance evaluated using the mean absolute prediction error and mean prediction standard error from an out‐of‐sample cross‐validation study showed JRFit to be optimal for providing predictions of baseflow on the basis of the phases of El Niño–Southern Oscillation and Atlantic Multidecadal Oscillation. Thus, it is recommended that JRFit be implemented in hydroclimatic studies to provide powerful inference when there is evidence of clustering in the data.

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“…In addition, the problem of drought can occur at the regional or global scale. Being influenced by global climatic events containing ENSO (El Niño/Southern Oscillation) [1][2][3][4][5], PDO (Pacific Decadal Oscillation) [6][7][8][9][10][11], IOD (Indian Ocean Dipole) [12][13][14][15], and NAO (North Atlantic Oscillation) [16][17][18][19][20], drought can be quite complicated. Hence, the research on its spatiotemporal distribution and its responses to global climatic events are of critical significance for the assessment and early warning of drought disasters, as well as rational utilization of regional water resources.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events

Qiu

Wang

Xiao

2017

Water

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Abstract:The Xijiang River is a main branch of the Pearl River, the largest river in South China. Droughts in this area have seriously influenced local water resource utilization, and socio-economic development. The spatiotemporal distribution of droughts and its responses to global climatic events are of critical significance for the assessment and early warning of drought disasters. In this paper, the spatiotemporal patterns of droughts characterized by Rotated Empirical Orthogonal Function/Rotated Principal Components (REOF/RPC) in the Xijiang River Basin, China were evaluated using the Self-calibrated Palmer Drought Severity Index (Sc-PDSI). The drought responses to El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), India Ocean Dipole (IOD), and North Atlantic Oscillation (NAO) were analysed by Pearson correlation and multiple stepwise regression. The results showed that one year earlier NAO was the dominant factor impacting the droughts in the Xijiang Basin. Its contribution for the RPC2s of the annual, the first and second half years, winter, summer, autumn, and February were −0.556, −0.419, 0.597, −0.447, 0.542, 0.600, and −0.327, respectively. Besides the two adjacent Pacific and India oceans, the droughts seem be influenced by distant Atlantic climatic events. These results offer new reference insights into the early warning of droughts as well as the planning and management of water resources in the study area.

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Baseflow response to climate variability induced droughts in the Apalachicola–Chattahoochee–Flint River Basin, U.S.A.

Cited by 37 publications

References 32 publications

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Coupled impacts of ENSO AMO and PDO on temperature and precipitation in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins

Evaluation of Nonparametric and Parametric Statistical Procedures for Modeling and Prediction of Cluster‐Correlated Hydroclimatic Data

Spatiotemporal Distribution of Droughts in the Xijiang River Basin, China and Its Responses to Global Climatic Events

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