Uncertainty analysis in the detection of trends, cycles, and shifts in water resources time series

2019 ◽  
Vol 33 (8) ◽  
pp. 2629-2644 ◽  
Author(s):  
Marcelo Coelho ◽  
Cristovão Vicente Scapulatempo Fernandes ◽  
Daniel Henrique Marco Detzel
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Uncertainty Analysis ◽  
And Shifts

scholarly journals SARIMA Approach to Generating Synthetic Monthly Rainfall in the Sinú River Watershed in Colombia

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 602
Author(s):  
Luisa Martínez-Acosta ◽  
Juan Pablo Medrano-Barboza ◽  
Álvaro López-Ramos ◽  
John Freddy Remolina López ◽  
Álvaro Alberto López-Lambraño
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Autocorrelation Function ◽  
Information Criterion ◽  
Monthly Rainfall ◽  
Statistical Characteristics ◽  
Rainfall Time Series ◽  
River Watershed ◽  
Statistical Measures ◽  
Sarima Models

Seasonal Auto Regressive Integrative Moving Average models (SARIMA) were developed for monthly rainfall time series. Normality of the rainfall time series was achieved by using the Box Cox transformation. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF), and the minimum values of the Akaike Information Criterion (AIC). The result of the Ljung–Box statistical test shows the randomness and homogeneity of each model residuals. The performance and validation of the SARIMA models were evaluated based on various statistical measures, among these, the Student’s t-test. It is possible to obtain synthetic records that preserve the statistical characteristics of the historical record through the SARIMA models. Finally, the results obtained can be applied to various hydrological and water resources management studies. This will certainly assist policy and decision-makers to establish strategies, priorities, and the proper use of water resources in the Sinú river watershed.

scholarly journals Distinguishing Trends and Shifts from Memory in Climate Data

2018 ◽  
Vol 31 (23) ◽  
pp. 9519-9543 ◽  
Author(s):  
Claudie Beaulieu ◽  
Rebecca Killick
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Information Criterion ◽  
Steady Increase ◽  
Climate Data ◽  
Surface Warming ◽  
Abrupt Changes ◽  
Short Memory Process ◽  
The 1960S ◽  
And Shifts

The detection of climate change and its attribution to the corresponding underlying processes is challenging because signals such as trends and shifts are superposed on variability arising from the memory within the climate system. Statistical methods used to characterize change in time series must be flexible enough to distinguish these components. Here we propose an approach tailored to distinguish these different modes of change by fitting a series of models and selecting the most suitable one according to an information criterion. The models involve combinations of a constant mean or a trend superposed to a background of white noise with or without autocorrelation to characterize the memory, and are able to detect multiple changepoints in each model configuration. Through a simulation study on synthetic time series, the approach is shown to be effective in distinguishing abrupt changes from trends and memory by identifying the true number and timing of abrupt changes when they are present. Furthermore, the proposed method is better performing than two commonly used approaches for the detection of abrupt changes in climate time series. Using this approach, the so-called hiatus in recent global mean surface warming fails to be detected as a shift in the rate of temperature rise but is instead consistent with steady increase since the 1960s/1970s. Our method also supports the hypothesis that the Pacific decadal oscillation behaves as a short-memory process rather than forced mean shifts as previously suggested. These examples demonstrate the usefulness of the proposed approach for change detection and for avoiding the most pervasive types of mistake in the detection of climate change.

scholarly journals Paleo-hydrologic reconstruction of 400 years of past flows at a weekly time step for major rivers of Western Canada

2019 ◽  
Author(s):  
Andrew R. Slaughter ◽  
Saman Razavi
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Tree Ring ◽  
Flow Distribution ◽  
Future Climate Change ◽  
Western Canada ◽  
Tree Ring Chronology ◽  
Time Step ◽  
Water Resources Systems ◽  
Tree Ring Data

Abstract. The assumption of stationarity in water resources no longer holds, particularly within the context of future climate change. Plausible scenarios of flows that fluctuate outside the envelope of variability of the gauging data are required to assess the robustness of water resources systems to future conditions. This study presents a novel method of generating weekly-time-step flows based on tree-ring chronology data. Specifically, this method addresses two long-standing challenges with paleo-reconstruction: (1) the typically limited predictive power of tree-ring data at the annual and sub-annual scale, and (2) the inflated short-term persistence in tree-ring time series and improper use of prewhitening. Unlike the conventional approach, this method establishes relationships between tree-ring chronologies and naturalised flow at a biennial scale to preserve persistence properties and variability of hydrological time series. Biennial flow reconstructions are further disaggregated to weekly, according to the weekly flow distribution of reference two-year instrumental periods, identified as periods with broadly similar tree-ring properties to that of every two-year paleo-period. The Saskatchewan River Basin (SaskRB), a major river in Western Canada, is selected as a study area, and weekly flows in its four major tributaries are extended back to the year 1600. The study shows that the reconstructed flows properly preserve the statistical properties of the reference flows, particularly, short- to long-term persistence and the structure of variability across time scales. An ensemble approach is presented to represent the uncertainty inherent in the statistical relationships and disaggregation method. The ensemble of reconstructed weekly flows are publically available for download from https://doi.org/10.20383/101.0139 (Slaughter and Razavi, 2019).

Long-term (1900-2100) Hydrometeorological and Snow Water Equivalent reconstructions in the French Southern Alps (Mercantour Natural Parc).

2021 ◽  
Author(s):  
Thibault Mathevet ◽  
Cyril Thébault ◽  
Jérôme Mansons ◽  
Matthieu Le Lay ◽  
Audrey Valery ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Water Resources ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Hydrological Regime ◽  
Southern Alps ◽  
Snow Line ◽  
Snow Water

<p>The aim of this communication is to present a study on climate variability and change on snow water equivalent (SWE) and streamflow over the 1900-2100 period in a mediteranean and moutainuous area.  It is based on SWE and streamflow observations, past reconstructions (1900-2018) and future GIEC scenarii (up to 2100) of some snow courses and hydrological stations situated within the French Southern Alps (Mercantour Natural Parc). This has been conducted by EDF (French hydropower company) and Mercantour Natural Parc.</p><p>This issue became particularly important since a decade, especially in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production or impacts on mountainous ecosystems (fauna and flora). As a water resources manager in French mountainuous regions, EDF developed and managed a large hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurements of a hundred of snow courses within the French Alps. EDF have been operating an automatic SWE sensors network, complementary to historical snow course network. Based on numerous SWE observations time-series and snow modelization (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2018 period. These reconstructions have been extented to 1900 using 20 CR (20<sup>th</sup> century reanalyses by NOAA) reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii (+4.5 W/m² and + 8.5 W/m² hypotheses). In the scope of this study, Mercantour Natural Parc is particularly interested by snow scenarii in the future and its impacts on their local flora and fauna.</p><p>Considering observations within Durance watershed and Mercantour region, this communication focuses on: (1) long term (1900-2018) analyses of variability and trend of hydrometeorological and snow variables (total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length, streamflow regimes) , (2) long term variability of snow and hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii.</p><p>Comparing old period (1950-1984) to recent period (1984-2018), quantitative results within these regions roughly shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season duration by 15 days. Characterization of the increase of snow line height and SWE reduction are particularly important at a local and watershed scale. Then, this communication focuses on impacts on long-term time scales (2050, 2100). This long term change of snow dynamics within moutainuous regions both impacts (1) water resources management, (2) snow resorts and artificial snow production developments or (3) ecosystems dynamics.Connected to the evolution of snow seasonality, the impacts on hydrological regime and some streamflow signatures allow to characterize the possible evolution of water resources in this mediteranean and moutianuous region This study allowed to provide some local quantitative scenarii.</p>

scholarly journals Impact of Climate Variabilities and Human Activities on Surface Water Extents in Reservoirs of Yongding River Basin, China, from 1985 to 2016 Based on Landsat Observations and Time Series Analysis

2019 ◽  
Vol 11 (5) ◽  
pp. 560 ◽  
Author(s):  
Mingli Wang ◽  
Longjiang Du ◽  
Yinghai Ke ◽  
Maoyi Huang ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Water Resources ◽  
River Basin ◽  
Change Point ◽  
Human Activities ◽  
Reservoir Water ◽  
Change Period ◽  
Statistical Time ◽  
Yongding River

Yongding River is the largest river flowing through Beijing, the capital city of China. In recent years, Yongding River Basin (YDRB) has witnessed increasing human impacts on water resources, posing serious challenges in hydrological and ecological health. In this study, remote sensing techniques and statistical time series approaches for hydrological studies were combined to characterize the dynamics and driving factors of reservoir water extents in YDRB during 1985–2016. First, 107 Landsat 4, 5, 7 and 8 images were used to extract surface water extents in YDRB during 1985–2016 using a combination of water indices and Otsu threshold algorithm. Significant positive correlation was found between water extents and the annual inflow for the two biggest reservoirs, the downstream Guanting and upstream Cetian reservoirs, proving their representativeness of surface water availability in this basin. Then, statistical time series approaches including trend-free pre-whitening Mann-Kendall trend test, Pettit change-point test and double mass curve method, which are frequently used in hydrological studies, were adopted to quantify the trend of reservoir water extents dynamics and the relative contributions of climate variability and human activities. Results showed that the water extents in both reservoirs exhibited significant downward trend with change point occurring in 2001 and 2005 for Guanting and Cetian, respectively. About 74%~75% of the shrinkage during the post-change period can be attributed to human activities, among which GDP, population, electricity power production, raw coal production, steel and crude iron production, value of agriculture output, and urban area were the major human drivers. Hydrological connectivity between the upstream Cetian and downstream Guanting reservoirs declined during the post-change period. Since 2012, water extents in both reservoirs recovered as a result of various governmental water management policies including the South-to-North Water Diversion Project. The methodology presented in this study can be used for analyzing the dynamics and driving mechanism of surface water resources, especially for un-gauged or poorly-gauged watersheds.

scholarly journals Glacier recession and water resources in Peru’s Cordillera Blanca

2012 ◽  
Vol 58 (207) ◽  
pp. 134-150 ◽  
Author(s):  
Michel Baraer ◽  
Bryan G. Mark ◽  
Jeffrey M. McKenzie ◽  
Thomas Condom ◽  
Jeffrey Bury ◽  
...  
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Hydrologic Model ◽  
Dry Season ◽  
Glacier Retreat ◽  
Cordillera Blanca ◽  
Tropical Glaciers ◽  
Daily Discharge ◽  
Synthetic Time Series ◽  
Nonparametric Statistical

AbstractThe tropical glaciers of the Cordillera Blanca, Peru, are rapidly retreating, resulting in complex impacts on the hydrology of the upper Río Santa watershed. The effect of this retreat on water resources is evaluated by analyzing historical and recent time series of daily discharge at nine measurement points. Using the Mann-Kendall nonparametric statistical test, the significance of trends in three hydrograph parameters was studied. Results are interpreted using synthetic time series generated from a hydrologic model that calculates hydrographs based on glacier retreat sequences. The results suggest that seven of the nine study watersheds have probably crossed a critical transition point, and now exhibit decreasing dry-season discharge. Our results suggest also that once the glaciers completely melt, annual discharge will be lower than present by 2-30% depending on the watershed. The retreat influence on discharge will be more pronounced during the dry season than at other periods of the year. At La Balsa, which measures discharge from the upper Río Santa, the glacier retreat could lead to a decrease in dry-season average discharge of 30%.

Time Series Methods In Water Resources Engineering

1984 ◽  
Vol 4 (2) ◽  
pp. 77-79
Author(s):  
Maria Mimikou ◽  
Th. Xanthopoulos
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Water Resources Engineering

Topographic and hydrogeologic controls of groundwater dynamics in generalized hydrologic landscapes with a humid climate

2020 ◽  
Author(s):  
Ezra Haaf ◽  
Alireza Kavousi ◽  
Thomas Reimann ◽  
Markus Giese ◽  
Roland Barthel
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Water Flow ◽  
Groundwater Level ◽  
Flow Model ◽  
Sensitivity Study ◽  
Groundwater Dynamics ◽  
Global Sensitivity ◽  
Surface Water Flow ◽  
Hydrogeological Properties

<p>The study investigates how topographic and hydrogeological properties influence groundwater dynamics. Using the concept of the fundamental hydrologic landscape (FHL; Winter, 2001), the impact of slope angle, wavelength and amplitude, as well as boundary conditions and hydraulic conductivity on groundwater dynamics is systematically assessed. This type of global sensitivity study has been done for stream flow (e.g. Carlier et al., 2019) or within groundwater focusing solely on groundwater flow and fractions of regional versus local recharge at steady state (e.g. Gleeson and Manning, 2008). In contrast, we study the influence of controls on groundwater level dynamics by using transient models. The coupled, physically based Groundwater and Surface-Water Flow simulator GSFLOW (Markstrom et al., 2008) is employed, to run a set of simulations for a FHL, where topographic and hydrogeological properties are varied across a range of possible value. The model is run at a daily time-step with climate data obtained from a measuring station in Southern Germany. Subsequently, groundwater level time series are read from the model domain across the set of simulations. These time series are decomposed into amplitude, magnitude, timing, flashiness and inter-annual variability by using dynamics indices (Heudorfer et al., 2019). Sensitivity of groundwater dynamics to the different topographic and hydrogeological controls is discussed and contrasted with the results from a prior empirical study (Haaf et al., under review). This type of global sensitivity study may aid understanding hypothesis testing of climate change impacts on groundwater level dynamics.</p><p> </p><p>Carlier C, Wirth SB, Cochand F, Hunkeler D, Brunner P. 2019. Exploring Geological and Topographical Controls on Low Flows with Hydrogeological Models. Groundwater, 57: 48-62. DOI: 10.1111/gwat.12845.<br>Gleeson T, Manning AH. 2008. Regional groundwater flow in mountainous terrain: Three-dimensional simulations of topographic and hydrogeologic controls. Water Resources Research, 44. DOI:10.1029/2008wr006848.<br>Haaf E, Giese M, Heudorfer B, Stahl K, Barthel R. Physiographic and climatic controls on groundwater dynamics on the regional scale. (under review).<br>Heudorfer B, Haaf E, Stahl K, Barthel R. 2019. Index-Based Characterization and Quantification of Groundwater Dynamics. Water Resources Research, 55: 5575-5592. DOI: 10.1029/2018wr024418.<br>Markstrom SL, Niswonger RG, Regan RS, Prudic DE, Barlow, PM. 2008. GSFLOW-Coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005): U.S. Geological Survey Techniques and Methods 6-D1, 240 p.<br>Winter TC. 2001. The concept of hydrologic landscapes. Journal of the American Water Resources Association, 37: 335-349. DOI: DOI 10.1111/j.1752-1688.2001.tb00973.x.</p>

Optimizing the management of complex water resources systems taking into account the long-term persistence in streamflow

2020 ◽  
Author(s):  
Amaury Tilmant ◽  
Vahid Espanmanesh
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Optimization Techniques ◽  
Irrigated Agriculture ◽  
Water Resources Systems ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Operating Policies ◽  
Dual Dynamic Programming

<p>The operation of multireservoir systems is a challenging decision-making problem due to (i) multiple, often conflicting, objectives (e.g. hydropower generation versus irrigated agriculture), (ii) stochastic variables (e.g. inflows, water demands, commodity prices), (iii) nonlinear relationships, (e.g. hydropower production function) and (iv) trade-offs between immediate and future consequences. Properly capturing the properties of the hydrologic processes responsible for the inflows is of paramount importance to enhance the performance of water resources systems. This becomes all the more relevant since low-frequency climate signals, which affect the hydrology in numerous regions around the globe, has increased in recent years. If traditional time series models generally fail to reproduce this regime-like behavior, so are the optimization models that are used to support multireservoir operation. Hidden Markov Model (HMM) is a class of hydrological models that can accommodate both overdispersion and serial dependence in historical time series, two essential hydrological properties that must be captured when modeling a system where the climate is switching between different states (e.g., dry, normal, wet). In terms of reservoir operation, Stochastic Dual Dynamic Programming (SDDP) is one of the few optimization techniques that can accomodate both system and hydrologic complexity. In SDDP, the hydrologic uncertainty is often captured by a multi-site periodic autoregressive (MPAR) model. However, MPAR models are unable to represent the long-term persistence of the streamflow process found in some regions, which may lead to suboptimal reservoir operating policies. We present an extension of the SDDP algorithm that can handle the long-term persistence and provide reservoir operating policies that explicitly capture regime shifts. To achieve this, the state-space vector now includes a climate variable whose transition is governed by a HMM. The Senegal River Basin (SRB), whose flow regime is characterized by multiyear dry/wet periods, is used as a case study.</p>

scholarly journals The Influence of European Climate Variability Mechanism on Air Temperatures in Romania

2014 ◽  
Vol 8 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Nicoleta Ionac ◽  
Monica Matei
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Large Scale ◽  
Empirical Orthogonal Functions ◽  
Spatial And Temporal Variability ◽  
Orthogonal Functions ◽  
Mean Values ◽  
European Climate ◽  
Air Temperatures ◽  
And Shifts

Abstract The present paper investigates on the spatial and temporal variability of maximum and minimum air-temperatures in Romania and their connection to the European climate variability. The European climate variability is expressed by large scale parameters, which are roughly represented by the geopotential height at 500 hPa (H500) and air temperature at 850 hPa (T850). The Romanian data are represented by the time series at 22 weather stations, evenly distributed over the entire country’s territory. The period that was taken into account was 1961-2010, for the summer and winter seasons. The method of empirical orthogonal functions (EOF) has been used, in order to analyze the connection between the temperature variability in Romania and the same variability at a larger scale, by taking into consideration the atmosphere circulation. The time series associated to the first two EOF patterns of local temperatures and large-scale anomalies were considered with regard to trends and shifts in their mean values. The non- Mann-Kendall and Pettitt parametric tests were used in this respect. The results showed a strong correlation between T850 parameter and minimum and maximum air temperatures in Romania. Also, the ample variance expressed by the first EOF configurations suggests a connection between local and large scale climate variability.

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