A technical note on the influence of time-series length on the intensity-duration-frequency curves for Lazio Region

2020 ◽  
Author(s):  
B. Moccia ◽  
C. Mineo
Keyword(s):  
Time Series ◽  
Technical Note ◽  
Series Length ◽  
Lazio Region ◽  
Intensity Duration Frequency ◽  
Frequency Curves

scholarly journals Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

2019 ◽  
Vol 23 (10) ◽  
pp. 4323-4331 ◽  
Author(s):  
Wouter J. M. Knoben ◽  
Jim E. Freer ◽  
Ross A. Woods
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Ad Hoc ◽  
Model Performance ◽  
Technical Note ◽  
Mean Flow ◽  
Model Adequacy ◽  
Robust Model ◽  
The Mean ◽  
Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

Simulating reference rainfall scenarios for hydrological applications using a multifractal approach

2021 ◽  
Author(s):  
Arun Ramanathan ◽  
Pierre-Antoine Versini ◽  
Daniel Schertzer ◽  
Ioulia Tchiguirinskaia ◽  
Remi Perrin ◽  
...  
Keyword(s):  
Time Series ◽  
Moment Analysis ◽  
Specific Reference ◽  
Rainfall Time Series ◽  
Time Series Dataset ◽  
Hourly Rainfall ◽  
Spatial Dimensions ◽  
Multifractal Theory ◽  
Intensity Duration Frequency ◽  
Hydrological Applications

<p><strong>Abstract</strong></p><p>Hydrological applications such as flood design usually deal with and are driven by region-specific reference rainfall regulations, generally expressed as Intensity-Duration-Frequency (IDF) values. The meteorological module of hydro-meteorological models used in such applications should therefore be capable of simulating these reference rainfall scenarios. The multifractal cascade framework, since it incorporates physically realistic properties of rainfall processes such as non-homogeneity (intermittency), scale invariance, and extremal statistics, seems to be an appropriate choice for this purpose. Here we suggest a rather simple discrete-in-scale multifractal cascade based approach. Hourly rainfall time-series datasets (with lengths ranging from around 28 to 35 years) over six cities (Paris, Marseille, Strasbourg, Nantes, Lyon, and Lille) in France that are characterized by different climates and a six-minute rainfall time series dataset (with a length of around 15  years) over Paris were analyzed via spectral analysis and Trace Moment analysis to understand the scaling range over which the universal multifractal theory can be considered valid. Then the Double Trace Moment analysis was performed to estimate the universal multifractal parameters α,C<sub>1</sub> that are required by the multifractal cascade model for simulating rainfall. A renormalization technique that estimates suitable renormalization constants based on the IDF values of reference rainfall is used to simulate the reference rainfall scenarios. Although only purely temporal simulations are considered here, this approach could possibly be generalized to higher spatial dimensions as well.</p><p><strong>Keywords</strong></p><p>Multifractals, Non-linear geophysical systems, Cascade dynamics, Scaling, Hydrology, Stochastic rainfall simulations.</p>

Development of Rainfall Intensity-Duration-Frequency Curves Based on Dynamically Downscaled Climate Data: Arizona Case Study

2021 ◽  
Vol 26 (5) ◽  
pp. 05021005
Author(s):  
Amin Mohebbi ◽  
Simin Akbariyeh ◽  
Montasir Maruf ◽  
Ziyan Wu ◽  
Juan Carlos Acuna ◽  
...  
Keyword(s):  
Rainfall Intensity ◽  
Climate Data ◽  
Intensity Duration Frequency ◽  
Frequency Curves

scholarly journals Intensity-Duration-Frequency curves at the global scale

2018 ◽  
Author(s):  
Laurent Courty ◽  
Robert Wilby ◽  
John Hillier ◽  
Louise Slater
Keyword(s):  
Global Scale ◽  
Intensity Duration Frequency ◽  
Frequency Curves

scholarly journals Minimum time required to detect population trends: the need for long-term monitoring programs

2017 ◽  
Author(s):  
Easton R White
Keyword(s):  
Time Series ◽  
Statistical Power ◽  
Time Series Data ◽  
Conservation Status ◽  
Monitoring Program ◽  
Minimum Time ◽  
Series Data ◽  
Series Length ◽  
Time Required

Long-term time series are necessary to better understand population dynamics, assess species' conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. When is a population time series long enough to address a question of interest? We determine the minimum time series length required to detect significant increases or decreases in population abundance. To address this question, we use simulation methods and examine 878 populations of vertebrate species. Here we show that 15-20 years of continuous monitoring are required in order to achieve a high level of statistical power. For both simulations and the time series data, the minimum time required depends on trend strength, population variability, and temporal autocorrelation. These results point to the importance of sampling populations over long periods of time. We argue that statistical power needs to be considered in monitoring program design and evaluation. Time series less than 15-20 years are likely underpowered and potentially misleading.

scholarly journals Design Values for Precipitation and Floods from M5 Values

2000 ◽  
Vol 31 (4-5) ◽  
pp. 357-372 ◽  
Author(s):  
Jonas Elíasson
Keyword(s):  
Natural Resource ◽  
Return Period ◽  
Coefficient Of Variation ◽  
Statistical Distribution ◽  
Engineering Research ◽  
Design Values ◽  
Intensity Duration Frequency ◽  
Two Parameters ◽  
The University ◽  
Frequency Curves

The M5 method, originally proposed by the Natural Resource Council in UK, is used for estimating precipitation in Iceland. In this method the M5 (24-hour precipitation with 5-year return period) is used as an index variable. Instead of the usual approach in estimating regional values of the coefficient of variation another coefficient, Ci is used. The M5 and the Ci define together a generalised distribution that can be utilised to estimate the statistical distribution of precipitation anywhere in the country. M5 maps have been prepared for this purpose by the Engineering Research Institute of the University of Iceland. Methods have been devised to derive PMP values from the M5 values. This paper describes the method and gives examples of calculation. It is also shown that the same CDF applies for the observations of shorter duration precipitation available in Iceland. By applying the principle of identical statistical distribution for standardised annual maxima of any duration, IDF (Intensity – Duration – Frequency) curves have been derived. This allows the IDF – values to be calculated on basis of M5 and Ci, which are the two-parameters that define the generalised precipitation distribution.

scholarly journals Minimum time required to detect population trends: the need for long-term monitoring programs

2018 ◽  
Author(s):  
Easton R White
Keyword(s):  
Time Series ◽  
Statistical Power ◽  
Conservation Status ◽  
Species Conservation ◽  
Population Data ◽  
Iucn Red List ◽  
Series Length ◽  
Large Variability ◽  
Monitoring Programs

Long-term time series are necessary to better understand population dynamics, assess species' conservation status, and make management decisions. However, population data are often expensive, requiring a lot of time and resources. What is the minimum population time series length required to detect significant trends in abundance? I first present an overview of the theory and past work that has tried to address this question. As a test of these approaches, I then examine 822 populations of vertebrate species. I show that 72% of time series required at least 10 years of continuous monitoring in order to achieve a high level of statistical power. However, the large variability between populations casts doubt on commonly used simple rules of thumb, like those employed by the IUCN Red List. I argue that statistical power needs to be considered more often in monitoring programs. Short time series are likely under-powered and potentially misleading.

scholarly journals Technical Note: Using wavelet analyses on water depth time series to detect glacial influence in high-mountain hydrosystems

2013 ◽  
Vol 10 (4) ◽  
pp. 4369-4395 ◽  
Author(s):  
S. Cauvy-Fraunié ◽  
T. Condom ◽  
A. Rabatel ◽  
M. Villacis ◽  
D. Jacobsen ◽  
...  
Keyword(s):  
Time Series ◽  
Water Depth ◽  
Water Pressure ◽  
Methodological Approach ◽  
Technical Note ◽  
High Mountain ◽  
Tropical Andes ◽  
Glacial Meltwater ◽  
Depth Measurement ◽  
Wavelet Analyses

Abstract. Worldwide, the rapid shrinking of glaciers in response to ongoing climate change is currently modifying the glacial meltwater contribution to hydrosystems in glacierized catchments. Assessing the contribution of glacier run-off to stream discharge is therefore of critical importance to evaluate potential impact of glacier retreat on water quality and aquatic biota. This task has challenged both glacier hydrologists and ecologists over the last 20 yr due to both structural and functional complexity of the glacier-stream system interface. Here we propose a new methodological approach based on wavelet analyses on water depth time series to determine the glacial influence in glacierized catchments. We performed water depth measurement using water pressure loggers over ten months in 15 stream sites in two glacier-fed catchments in the Ecuadorian Andes (> 4000 m). We determined the global wavelet spectrum of each time series and defined the Wavelet Glacier Signal (WGS) as the ratio between the global wavelet power spectrum value at a 24 h-scale and its corresponding significance value. To test the relevance of the WGS we compared it with the percentage of the glacier cover in the catchments, a metric of glacier influence often used in the literature. We then tested whether one month data could be sufficient to reliably determine the glacial influence. As expected we found that the WGS of glacier-fed streams decreased downstream with the increasing of non-glacial tributaries. We also found that the WGS and the percentage of the glacier cover in the catchment were significantly positively correlated and that one month data was sufficient to identify and compare the glacial influence between two sites, provided that the water level time series were acquired over the same period. Furthermore, we found that our method permits to detect glacial signal in supposedly non-glacial sites, thereby evidencing glacial meltwater infiltrations. While we specifically focused on the tropical Andes in this paper, our approach to determine glacier influence would be applicable to temperate and arctic glacierized catchments. The WGS therefore appears as a powerful and cost effective tool to better understand the hydrological links between glaciers and hydrosystems and assess the consequences of rapid glacier melting.

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