scholarly journals The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1375
Author(s):  
Adam Rus Nugroho ◽  
Ichiro Tamagawa ◽  
Morihiro Harada
Keyword(s):  
Flow Regime ◽  
Water Resource Management ◽  
River Flow ◽  
Southern Oscillation ◽  
Statistical Prediction ◽  
Climate Indices ◽  
Non Linear ◽  
Time Lagged ◽  
Time Variables ◽  
Statistical Prediction Model

Predicting the streamflow regimes using climate dynamics is important in water resource management. However, in Indonesia, there are few studies targeting climate indices and streamflow. A previous study found difficulty in developing a statistical prediction model for this relationship due to its non-linear nature. This study attempted to address that gap by applying multiple regression (MR) models using second- and third-order polynomial functions to show the non-linear relationship between climate and flow regime indices. First, a correlation analysis was performed to check the variable relationships. There was a good and significant correlation of El Niño Southern Oscillation (ENSO) with the flow regime indices. Secondly, MR models were developed with the same-time variables. The developed model showed that the Indian Ocean Dipole (IOD) had the effect of strongly increasing the high flow in La Niña phases. Finally, time-lagged MRs were developed aiming at forecasting. Lagged MR models with six-month leading climate indices demonstrated a relatively good correlation with the observed data (mostly R > 0.700) with moderate accuracy (root mean square error = 44–51%). It suggests that the forecasting of flow regime may be possible using ENSO and IOD indices.

scholarly journals Spatiotemporal Variations of Drought and Their Teleconnections with Large-Scale Climate Indices over the Poyang Lake Basin, China

2020 ◽  
Vol 12 (9) ◽  
pp. 3526 ◽  
Author(s):  
Weilin Liu ◽  
Shengnan Zhu ◽  
Yipeng Huang ◽  
Yifan Wan ◽  
Bin Wu ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Large Scale ◽  
Poyang Lake ◽  
Southern Oscillation ◽  
Trend Test ◽  
Climate Indices ◽  
Lake Basin ◽  
Spatiotemporal Variations ◽  
Poyang Lake Basin ◽  
Decadal Scale

The intensity and frequency of droughts in Poyang Lake Basin have been increasing due to global warming. To properly manage water resources and mitigate drought disasters, it is important to understand the long-term characteristics of drought and its possible link with large-scale climate indices. Based on the monthly meteorological data of 41 meteorological stations in Poyang Lake Basin from 1958 to 2017, the spatiotemporal variations of drought were investigated using the standardized precipitation evapotranspiration index (SPEI). Ensemble empirical mode decomposition (EEMD) methods and the modified Mann–Kendall (MMK) trend test were used to explore the spatiotemporal characteristics and trends of drought. Furthermore, to reveal possible links between drought variations and large-scale climate indices in Poyang Lake Basin, the relationships between SPEI and large-scale climate indices, such as North Atlantic Oscillation (NAO), El Niño–Southern Oscillation (ENSO), Arctic Oscillation (AO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO) were examined using cross-wavelet transform. The results showed that the SPEI in Poyang Lake Basin exhibited relatively stable quasi-periodic oscillation, with approximate quasi-3-year and quasi-6-year periods at the inter-annual scale and quasi-15-year and quasi-30-year periods at the inter-decadal scale from 1958 to 2017. Moreover, the Poyang Lake Basin experienced an insignificantly wetter trend as a whole at the annual and seasonal scales during the period of 1958–2017, except for spring, which had a drought trend. The special characteristics of the trend variations were markedly different in the basin. The areas in which drought was most likely to occur were mainly located in the Poyang Lake region, northwest and south of the basin, respectively. Furthermore, relationships between the drought and six climate indices showed that the drought exhibited a significant temporal correlation with five climate indices at restricted intervals, except for IOD. The dominant influences of the large-scale climate indices on the drought evolutions shifted in the Poyang Lake Basin during 1958–2017, from the NAO, Niño 3.4, and the Southern Oscillation Index (SOI) before the late 1960s and early 1970s, to the AO and PDO during the 1980s, then to the NAO, AO and SOI after the early 2000s. The NAO, AO and SOI exerted a significant influence on the drought events in the basin. The results of this study will benefit regional water resource management, agriculture production, and ecosystem protection in the Poyang Lake Basin.

scholarly journals Statistical–Dynamical Seasonal Forecast for Tropical Cyclones Affecting New York State

2015 ◽  
Vol 30 (2) ◽  
pp. 295-307 ◽  
Author(s):  
Hye-Mi Kim ◽  
Edmund K. M. Chang ◽  
Minghua Zhang
Keyword(s):  
New York ◽  
Prediction Model ◽  
Tropical Cyclones ◽  
Southern Oscillation ◽  
New York State ◽  
Statistical Prediction ◽  
Annual Number ◽  
York State ◽  
Hybrid Prediction ◽  
Statistical Prediction Model

Abstract This study attempts, for the first time, to predict the annual number of tropical cyclones (TCs) affecting New York State (NYS), as part of the effort of the New York State Resiliency Institute for Storms and Emergencies (RISE). A pure statistical prediction model and a statistical–dynamical hybrid prediction model have been developed based on the understanding of the physical mechanism between NYS TCs and associated large-scale climate variability. During the cold phase of El Niño–Southern Oscillation, significant circulation anomalies in the Atlantic Ocean provide favorable conditions for more recurving TCs into NYS. The pure statistical prediction model uses the sea surface temperature (SST) over the equatorial Pacific Ocean from the previous months. Cross validation shows that the correlation between the observed and predicted numbers of NYS TCs is 0.56 for the June 1979–2013 forecasts. Forecasts of the probability of one or more TCs impacting NYS have a Brier skill score of 0.35 compared to climatology. The statistical–dynamical hybrid prediction model uses Climate Forecast System, version 2, SST predictions, which are statistically downscaled to forecast the number of NYS TCs based on a stepwise regression model. Results indicate that the initial seasonal prediction for NYS TCs can be issued in February using the hybrid model, with an update in June using the pure statistical prediction model. Based on the statistical model, for 2014, the predicted number of TCs passing through NYS is 0.33 and the probability of one or more tropical cyclones crossing NYS is 30%, which are both below average and in agreement with the actual activity (0 NYS TCs).

scholarly journals Identifying ENSO Influences on Rainfall with Classification Models: Implications for Water Resource Management of Sri Lanka

2018 ◽  
Author(s):  
Thushara De Silva M. ◽  
George Hornberger
Keyword(s):  
Resource Management ◽  
Sri Lanka ◽  
Water Resource ◽  
Water Resource Management ◽  
Southern Oscillation ◽  
Classification Tree ◽  
Management Decision ◽  
Climate Indices ◽  
Climate Conditions ◽  
Kelani River

Abstract. Seasonal to annual forecasts of precipitation patterns are very important for water infrastructure management. In particular, such forecasts can be used to inform decisions about the operation of multipurpose reservoir systems in the face of changing climate conditions. Success in making useful forecasts often is achieved by considering climate teleconnections such as the El-Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) as related to sea surface temperature variations. We present a statistical analysis to explore the utility of using rainfall relationships in Sri Lanka with ENSO and IOD to predict rainfall to Mahaweli and Kelani, river basins of the country. Forecasting of rainfall as classes; flood, drought and normal are helpful for the water resource management decision making. Results of these models give better accuracy than a prediction of absolute values. Quadratic discrimination analysis (QDA) and classification tree models are used to identify the patterns of rainfall classes with respect to ENSO and IOD indices. Ensemble modeling tool Random Forest is also used to predict the rainfall classes as drought and not drought with higher skill. These models can be used to forecast the areal rainfall using predicted climate indices. Results from these models are not very accurate; however, the patterns recognized are useful input to the water resources management and adaptation the climate variability of agriculture and energy sectors.

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

scholarly journals Transformation of the Flow Regime of a Large Allochthonous River in Central Europe—An Example of the Vistula River in Poland

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 507 ◽  
Author(s):  
Dariusz Wrzesiński ◽  
Leszek Sobkowiak
Keyword(s):  
Flow Regime ◽  
Annual Cycle ◽  
River Flow ◽  
Hydrological Cycle ◽  
Temporal Structure ◽  
Flow Characteristics ◽  
Point Of View ◽  
Theoretical Point ◽  
Vistula River ◽  
Basin Water

Identification of river flow regime and its possible changes caused by natural factors or human activity is one of major issues in modern hydrology. In such studies different approaches and different indicators can be used. The aim of this study is to determine changes in flow regime of the largest river in Poland—the Vistula, using new, more objectified coefficients and indices, based on data recorded in 22 gauges on the Vistula mainstream and 38 gauges on its tributaries in the multi-year period 1971–2010. The paper consists of three main parts: in the first part, in order to recognize changes in the flow regime characteristics along the Vistula, data from gauges located on the river mainstream were analyzed with the help of the theory of entropy. In the second part gauging stations on the Vistula mainstream and its tributaries were grouped; values of the newly introduced pentadic Pardé’s coefficient of flow (discharge) (PPC) were taken as the grouping criterion. In the third part of the study a novel method of determining river regime characteristics was applied: through the recognition of the temporal structure of hydrological phenomena and their changes in the annual cycle sequences of hydrological periods (characteristic phases of the hydrological cycle) on the Vistula River mainstream and its tributaries were identified and their occurrence in the yearly cycle was discussed. Based on the detected changes of the 73-pentad Pardé’s coefficients of flow four main types of rivers were distinguished. Transformation of the flow regime was reflected in the identified different sequences of hydrological periods in the average annual cycle. It was found that while transformation of the Vistula River regime occurred along its whole course, the most frequent changes were detected in its upper, mountainous reaches, under the influence of the flow characteristics of its tributaries. This allowed the Vistula to be considered the allochthonous river. These findings are interesting not only from a theoretical point of view, but they also can be valuable to stakeholders in the field of the Vistula River basin water management and hydrological forecasting, including flood protection, which has recently become a matter of growing concern due to the observed effects of climate change and human impact.

scholarly journals Historical drought patterns over Canada and their teleconnections with large-scale climate signals

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Kendall Test ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Data Sets ◽  
Canadian Prairies ◽  
Agriculture Industry ◽  
Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

Evidence of river flow regulation loss over time in the Magdalena river basin 

2021 ◽  
Author(s):  
Diver E. Marín ◽  
Juan F. Salazar ◽  
José A. Posada-Marín
Keyword(s):  
Climate Change ◽  
Environmental Change ◽  
River Basin ◽  
River Flow ◽  
Southern Oscillation ◽  
Scaling Theory ◽  
Scaling Properties ◽  
Low Flows ◽  
High Flows ◽  
Magdalena River

<p>Some of the main problems in hydrological sciences are related to how and why river flows change as a result of environmental change, and what are the corresponding implications for society. This has been described as the Panta Rhei context, which refers to the challenge of understanding and quantifying hydrological dynamics in a changing environment, i.e. under the influence of non-stationary effects. The river flow regime in a basin is the result of a complex aggregation process that has been studied by the scaling theory, which allows river basins to be classified as regulated or unregulated and to identify a critical threshold between these states. Regulation is defined here as the basin’s capacity to either dampen high flows or to enhance low flows. This capacity depends on how basins store and release water through time, which in turn depends on many processes that are highly dynamic and sensitive to environmental change. Here we focus on the Magdalena river basin in northwestern South America, which is the main basin for water and energy security in Colombia, and at the same time, it has been identified as one of the most vulnerable regions to be affected by climate change. Building upon some of our previous studies, here we use data analysis to study the evolution of regulation in the Magdalena basin for 1992-2015 based on the scaling theory for extreme flows. In contrast to most previous studies, here we focus on the scaling properties of events rather than on long term averages. We discuss possible relations between changes in the scaling properties and environmental factors such as climate variability, climate change, and land use/land cover change, as well as the potential implications for water security in the country. Our results show that, during the last few decades, the Magdalena river basin has maintained its capacity to regulate low flows (i.e. amplification) whereas it has been losing its capacity to regulate high flows (i.e. dampening), which could be associated with the occurrence of the extremes phases of  El Niño Southern Oscillation (ENSO) and anthropogenic effects, mainly deforestation. These results provide foundations for using the scaling laws as empirical tools for understanding temporal changes of hydrological regulation and simultaneously generate useful scientific evidence that allows stakeholders to take decisions related to water management in the Magdalena river basin in the context of environmental change.</p>

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