Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed

Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% to 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.

Download Full-text

An Extended Model in Estimating Consistent Quantiles for Intensity-Duration-Frequency Curves

10.5194/egusphere-egu21-7562 ◽

2021 ◽

Author(s):

Felix Fauer ◽

Jana Ulrich ◽

Oscar E. Jurado ◽

Uwe Ulbrich ◽

Henning W. Rust

Keyword(s):

Extreme Value ◽

Data Availability ◽

Extreme Value Statistics ◽

Statistical Characteristics ◽

Exceedance Probability ◽

Extended Model ◽

Adequate Model ◽

Extreme Precipitation Events ◽

Idf Curves ◽

Intensity Duration Frequency

Intensity-Duration-Frequency (IDF) curves describe the main statistical characteristics of extreme precipitation events. Providing information on the exceedance probability or return period of certain precipitation intensities for a range of durations, IDF curves are an important tool for the design of hydrological structures.Although the Generalized-Extreme-Value (GEV) distribution is an adequate model for annual precipitation maxima of a certain duration, the core problem of extreme value statistics remains: the limited data availability. Hence, it is reasonable to use a model that can describe all durations simultaneously. This reduces the total number of parameters and a more efficient usage of data is achieved. The idea of implementing a duration dependence directly into the parameters of the extreme value distribution and therefore obtaining a single distribution for a range of durations was proposed by Koutsoyiannis et al. (1998). However, while the use of the GEV is justified by a strong theoretical basis, only empirical models exist for the dependence of the parameters on duration.In this study, we compare different models regarding the dependence of the GEV parameters on duration with the aim of finding a model for a wide duration range (1 min - 5 days). We use a combination of existing model features, especially curvature for small durations and multi-scaling for all durations, and extend them by a new feature that allows flattening of the IDF curves for long durations. Using the quantile score in a cross-validation setting, we provide detailed information on the duration and probability ranges for which specific features or a systematic combination of features lead to improved modeling skill.Our results show that allowing curvature or multi-scaling improves the model only for very short or long durations, respectively, but leads to disadvantages in modeling the other duration ranges. In contrast, allowing flattening of the IDF curves leads to an improvement for medium durations between 1 hour and 1 day without affecting other duration regimes.

Download Full-text

Model evaluation of high-resolution urban climate simulations: using the WRF/Noah LSM/SLUCM model (Version 3.7.1) as a case study

Geoscientific Model Development ◽

10.5194/gmd-12-4571-2019 ◽

2019 ◽

Vol 12 (11) ◽

pp. 4571-4584 ◽

Cited By ~ 2

Author(s):

Zhiqiang Li ◽

Yulun Zhou ◽

Bingcheng Wan ◽

Hopun Chung ◽

Bo Huang ◽

...

Keyword(s):

High Resolution ◽

Model Evaluation ◽

Urban Climate ◽

Simulation Models ◽

Climate Simulation ◽

Model Uncertainties ◽

Temporal Dimension ◽

Climate Simulations ◽

Hong Kong Sar

Abstract. The veracity of urban climate simulation models should be systematically evaluated to demonstrate the trustworthiness of these models against possible model uncertainties. However, existing studies paid insufficient attention to model evaluation; most studies only provided some simple comparison lines between modelled variables and their corresponding observed ones on the temporal dimension. Challenges remain since such simple comparisons cannot concretely prove that the simulation of urban climate behaviours is reliable. Studies without systematic model evaluations, being ambiguous or arbitrary to some extent, may lead to some seemingly new but scientifically misleading findings. To tackle these challenges, this article proposes a methodological framework for the model evaluation of high-resolution urban climate simulations and demonstrates its effectiveness with a case study in the area of Shenzhen and Hong Kong SAR, China. It is intended to (again) remind urban climate modellers of the necessity of conducting systematic model evaluations with urban-scale climatology modelling and reduce these ambiguous or arbitrary modelling practices.

Download Full-text

Estimating IDF-Relations consistently using a duration-dependent GEV with spatial covariates

10.5194/egusphere-egu2020-18724 ◽

2020 ◽

Author(s):

Jana Ulrich ◽

Madlen Peter ◽

Oscar E. Jurado ◽

Henning W. Rust

Keyword(s):

Extreme Precipitation ◽

Probability Distributions ◽

Skill Score ◽

Exceedance Probability ◽

Ungauged Sites ◽

Extreme Precipitation Events ◽

One Step ◽

Idf Curves ◽

Intensity Duration Frequency ◽

A Site

Intensity-Duration-Frequency (IDF) Curves are a popular tool in Hydrology for estimating the properties of extreme precipitation events. They describe the relationship between rainfall intensity and duration for a given non-exceedance probability (or frequency). For a site where precipitation measurements are available, these curves can be estimated consistently over durations using a duration-dependent GEV (d-GEV, after Koutsoyiannis et al. 1998). In this approach, the probability distributions are modeled simultaneously for all durations.Additionally, we integrate covariates to describe the spatial variability of the d-GEV parameters so that we can model the distribution of extreme precipitation for a range of durations and locations in one step. Thus IDF Curves can be estimated even at ungauged sites. Further advantages are parameter reduction and more efficient use of the available data. We use the Quantile Skill Score to investigate under which conditions this method leads to an improved estimate compared to the single-site approach and to evaluate the performance at ungauged sites.

Download Full-text

Review for ‘Model evaluation of high-resolution urban climate simulations: using WRF ARW/LSM/SLUCM model as a case study’ by Zhiqiang Li et al.

10.5194/gmd-2018-220-rc2 ◽

2018 ◽

Author(s):

Anonymous

Keyword(s):

High Resolution ◽

Model Evaluation ◽

Urban Climate ◽

Climate Simulations

Download Full-text

Model evaluation of high-resolution urban climate simulations: using WRF ARW/LSM/SLUCM model as a case study

10.5194/gmd-2018-220 ◽

2018 ◽

Author(s):

Zhiqiang Li ◽

Yulun Zhou ◽

Bingcheng Wan ◽

Bo Huang ◽

Biao Liu ◽

...

Keyword(s):

High Resolution ◽

Model Evaluation ◽

Urban Climate ◽

Simulation Models ◽

Climate Simulation ◽

Model Uncertainties ◽

Temporal Dimension ◽

New Findings ◽

Climate Simulations

Abstract. The veracity of urban climate simulation models should be systematically evaluated to demonstrate the trustworthiness of these models against possible model uncertainties. However, existing studies paid insufficient attention to the model evaluation; most studies only provided some simple comparison lines between modelled variables and their corresponding observed ones on the temporal dimension. Challenges remain since such simple comparisons cannot concretely prove that the simulation of urban climate behaviors is reliable. Studies without systematic model evaluations are ambiguous or arbitrary to some extent, which may still lead to some seemingly new findings, but these findings may be scientifically misleading. To tackle these challenges, this article proposes a methodological framework for the model evaluation of high-resolution urban climate simulations and demonstrates its effectiveness with a case study in the fast-urbanizing city of Shenzhen, China. It is intended to remind (again) urban climate modelers of the necessity of conducting systematic model evaluations in urban-scale climatology modelling and reduce these ambiguous or arbitrary modelling practices.

Download Full-text

Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas

Journal of Hydrometeorology ◽

10.1175/jhm-d-19-0055.1 ◽

2019 ◽

Vol 20 (12) ◽

pp. 2331-2346 ◽

Cited By ~ 3

Author(s):

Zhangshuan Hou ◽

Huiying Ren ◽

Ning Sun ◽

Mark S. Wigmosta ◽

Ying Liu ◽

...

Keyword(s):

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Time Windows ◽

Gas Emissions ◽

Spatial Continuity ◽

Infrastructure Design ◽

Climate Simulations ◽

Spatially Distributed ◽

Numerical Grid ◽

Intensity Duration Frequency

Abstract Downscaled high-resolution climate simulations were used to provide inputs to the physics-based Distributed Hydrology Soil Vegetation Model (DHSVM), which accounts for the combined effects of snowmelt and rainfall processes, to determine spatially distributed available water for runoff (AWR). After quasi-stationary time windows were identified based on model outputs extracted for two different mountainous field sites in Colorado and California, intensity–duration–frequency (IDF) curves for precipitation and AWR were generated and evaluated at each numerical grid to provide guidance on hydrological infrastructure design. Impacts of snowmelt are found to be spatially variable due to spatial heterogeneity associated with topography according to geostatistical analyses. AWR extremes have stronger spatial continuity compared to precipitation. Snowmelt impacts on AWR are more pronounced at the wet California site than at the semiarid Colorado site. The sensitivities of AWR and precipitation IDFs to increasing greenhouse gas emissions are found to be localized and spatially variable. In subregions with significant snowfall, snowmelt can result in an AWR (e.g., 6-h 100-yr events) that is 70% higher than precipitation. For comparison, future greenhouse gas emissions may increase 6-h 100-yr precipitation and AWR by up to 50% and 80%, respectively, toward the end of this century.

Download Full-text