Resilience-oriented modeling and co-optimization for coupled power and water distribution systems

The interdependencies between the power distribution system (PDS) and water distribution system (WDS) are well-acknowledged in resilience analysis. Such interdependencies can hinder the post-disruption service restoration of both systems, and prolong the overall recovery process. Aimed at handling these issues, this paper proposes a resilience-oriented modeling and co-optimization method for coupled power and water (CPW) systems. The model integrates critical features of modern CPW systems, such as microgrids and distributed generations for power and water treatment plants, pumps, and tanks, for the water side. The interdependencies are extracted and formulated from mutual demand aspects. Further, a multiobjective optimization is presented to simultaneously reduce the loss of power load (LOPL) and loss of water load (LOWL). Finally, the method is tested on a coupled 33-bus power and 25-node water system and the result demonstrates the effectiveness of the proposed model and algorithm.Singapore-ETH Centre for Global Environmental SustainabilitySubmitted/Accepted versionThis work was supported by Future Resilient Systems, Singapore-ETH Centre through the National Research Foundation of Singapore under Its Campus for Research Excellence and Technological Enterprise program

High wavenumber coherent structures in low re apg-boundary-layer transition flow—a numerical study

This paper presents a numerical study of high wavenumber coherent structure evolution in boundary layer transition flow using recently-developed high order Combined compact difference schemes with non-uniform grids in the wall-normal direction for efficient simulation of such flows. The study focuses on a simulation of an Adverse-Pressure-Gradient (APG) boundary layer transition induced by broadband disturbance corresponding to the experiment of Borodulin et al. (Journal of Turbulence, 2006, 7, pp. 1–30). The results support the experimental observation that although the coherent structures seen during transition to turbulence have asymmetric shapes and occur in a random pattern, their local evolutional behaviors are quite similar. Further calculated local wavelet spectra of these coherent structures are also very similar. The wavelet spectrum of the streamwise disturbance velocity demonstrates high wavenumber clusters at the tip and the rear parts of the Λ-vortex. Both parts are imbedded at the primary Λ-vortex stage and spatially coincide with the spike region and high shear layer. The tip part is associated with the later first ring-like vortex, while the rear part with the remainder of the Λ-vortex. These observations help to shed light on the generation of turbulence, which is dominated by high wavenumber coherent structures.Published versio

Assessment of future changes in Southeast Asian precipitation using the NASA Earth Exchange Global Daily Downscaled Projections data set

Extreme precipitation and associated flooding cause severe damage to society and the environment. Future climate projections suggest an intensification of precipitation extremes in many regions. However, there is an increasing need for climate change impact assessment at higher spatial resolution, particularly for regions with complex geography such as Southeast Asia (SEA). In this study, we analysed the NASA Earth Exchange 0.25° resolution daily precipitation projections from an ensemble of 20 climate models under two emission scenarios RCP4.5 and RCP8.5. The variability in future precipitation projections is analysed and quantified for six geographical subregions, two climatological regions (wet and dry), and the low-elevation coastal zones in SEA. Various aspects of precipitation structure are studied using indices that characterize precipitation amount, number of heavy precipitation days, extreme precipitation amount, and maximum daily precipitation at annual and seasonal scales. The results show substantial increases in mean and extreme precipitation in many parts of SEA by the end of the 21st century under both emission scenarios, thus increasing the region's vulnerability to precipitation-driven hazards. The projected centennial increase in total annual precipitation relative to the baseline period of 1970–1999 when averaged over all land grid cells is about 15% under RCP8.5 scenario, with larger values (∼20%) over mainland SEA and Philippines and smaller values (∼6%) in Java island. The projected changes in extreme precipitation are stronger compared to the total annual precipitation under both emission scenarios. The New Guinea and Java regions show the largest and smallest increases in annual maximum daily precipitation, with ensemble mean values of 30 and 17%, respectively, under RCP8.5 scenario. The results also reveal large inter-model spread in projected changes, particularly during boreal winter and summer months.Accepted versio

Evaluation of GPM IMERG rainfall estimates in Singapore and assessing spatial sampling errors in ground reference

We evaluated the Integrated Multi-satellite Retrievals for GPM (IMERG) V06B Early and Final Run products using data from a dense gauge network in Singapore as ground reference (GR). The evaluation is carried out at monthly, daily, and hourly scales, and conditioned on different seasons and rainfall intensities. Further, different spatial configurations and densities of the gauge networks (3-17 gauges per IMERG cell) used here allowed us to examine spatial sampling errors (SSE) in the GR. The results revealed a probability of detection of 0.95 (0.65), critical success index of 0.69 (0.35), and a correlation of 0.60 (0.41) for the daily (hourly) scale. Results also indicate an overestimation of rainy days (hours) by IMERG compared to GR, leading to a false alarm ratio of 0.29 (0.57) at daily (hourly) scales. Analysis of probability distributions and conditional error metrics showed overestimation of lighter (0.2-4 mm/d) and moderate (4-8 mm/d) rainfall by IMERG, but better performance for heavier rainfall (≥32 mm/d). The seasonal analysis showed improved performance of IMERG during November-February compared to June-September months. The hourly analysis further revealed large discrepancies in diurnal cycles during June-September. The SSE are studied in a Monte Carlo framework consisting of several synthetic networks with varying spatial configurations and densities. The effect of SSE on IMERG evaluation results is characterized following the error variance separation approach. For the gauge networks studied here, the contribution of SSE variance to IMERG daily error variance ranges from 4-24% depending on gauge spatial configuration, and is as large as 36% during inter-monsoon months when rainfall is highly convective in nature.National Research Foundation (NRF)Accepted versionThe authors appreciate the partial support from the Singapore ETH Centre Future Resilience Systems projec

Fitting parametric tropical cyclone-induced rainfall model for tropical cyclones landfalling onto the Northern Vietnam coast

Tropical cyclones (TCs) can cause major flooding individually or collectively due to wind, storm surges and rainfall. This study applies the parametric rainfall climatology and persistence (R-CLIPER) model to analyse the axisymmetric component of 14 TC rainfall events in Northern Vietnam with the observed rainfall dataset from the Global Precipitation Mission from 2001 to 2021. The R-CLIPER model uses two inputs from TC track information: the maximum wind speed and radial distance from the TC centre. Four parameters represent the axisymmetric profile of rainfall rates: T0, Tm, rm, and re. T0 and Tm describe the rainfall intensity at the TC centre, and the maximum intensity which is located at radial distance rm from the centre, respectively. The fall-off from the maximum is exponential with a characteristic distance re. The R-CLIPER model generally assumes linear relationships between the four parameters and a normalised maximum wind speed (U). We adopt the operational coefficients by the National Hurricane Center (NHC) for the Western Pacific region as the initial setting. The observed TC rainfall profiles are further used to fit the parameters using the least-square method. Performance of the R-CLIPER with the initial and fitted settings for predicting the observed 14 rainfall profiles is assessed. T0 and Tm are found to be better represented by logarithm relationships with U, and rm by an exponential relationship, based on their improved R2 values over the R-CLIPER with NHC coefficients for the 14 historical TC events. At 0.1-degree resolution, the equitable threat score demonstrated significant improvement, almost six times at the 100 mm rainfall threshold. Improved root mean square error and bias are also seen for the cumulative rainfall volume and the averaged rainfall intensity. For instance, the bias has reduced by around 50% with the new relationships of the parameters and U in most cases

Assessment of flood risk exposure for the Foshan-Zhongshan region in Guangdong province, China

Floods have caused 20% of the worldwide economic losses resulting from catastrophe events over 2008 to 2018. In China, the annual flood economic losses have exceeded CNY 100 billion from 1990 to 2010, which is equivalent to 1% to 3% of China’s Gross Domestic Product (GDP). This paper presents a rainfall-runoff model coupled with an inundation estimation to assess the flood risk for a basin within the Foshan-Zhongshan area of the Pearl River Delta (PRD) region in China. A Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model was constructed for the crisscrossing river network in the study basin where the West and North Rivers meet, using publicly accessible meteorological, hydrological and topographical datasets. The developed model was used to analyze two recent flood events, that in July 2017 with large upstream river inflows, and in June 2018 with high local rainfall. Results were further used to develop the needed river rating curves within the basin. Two synthetic events that consider more severe meteorological and hydrological conditions were also analyzed. These results demonstrate the capability of the proposed model for quick assessment of potential flood inundation and the GDP exposure at risk within the economically important PRD region.Nanyang Technological UniversityPublished versionSupport from the Institute of Catastrophe Risk Management (ICRM), Nanyang Technological University and Axis Reinsurance is gratefully acknowledged

Assessment of Flood Risk Exposure for the Foshan-Zhongshan Region in Guangdong Province, China

Floods have caused 20% of the worldwide economic losses resulting from catastrophe events over 2008 to 2018. In China, the annual flood economic losses have exceeded CNY 100 billion from 1990 to 2010, which is equivalent to 1% to 3% of China’s Gross Domestic Product (GDP). This paper presents a rainfall-runoff model coupled with an inundation estimation to assess the flood risk for a basin within the Foshan-Zhongshan area of the Pearl River Delta (PRD) region in China. A Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model was constructed for the crisscrossing river network in the study basin where the West and North Rivers meet, using publicly accessible meteorological, hydrological and topographical datasets. The developed model was used to analyze two recent flood events, that in July 2017 with large upstream river inflows, and in June 2018 with high local rainfall. Results were further used to develop the needed river rating curves within the basin. Two synthetic events that consider more severe meteorological and hydrological conditions were also analyzed. These results demonstrate the capability of the proposed model for quick assessment of potential flood inundation and the GDP exposure at risk within the economically important PRD region

Probabilistic storm surge hazard using a steady-state surge model for the Pearl River Delta Region, China

Storm surges caused by tropical cyclones (TCs) are one of the costliest threats to coastal communities in southern China. Numerical surge models remain computationally challenging when used to simulate the large number of TC events required for probabilistic hazard assessments at regional scale. The present study demonstrates the applicability of a simple 1D steady-state storm surge representation for such regional scale hazard assessment. The surge setups from wind shear stress and barometric pressure difference are calculated with the meteorological forcing derived from parametric wind models and TC track information. Being computationally efficient, the surge model results do not require further empirical coefficients derived from correlation against observed data as compared to the previous statistical and semi-empirical surge estimations. Using the Pearl River Delta (PRD) region in China as a case study, the root-mean-square errors between the estimated and reported peak storm surges along the PRD coastline are 0.37 m and 0.45 m using two different TC best track inputs, respectively, covering 118 observed surge records from 39 historical TC events. Probabilistic surge hazard maps are further developed for the PRD coastline using the two TC best track datasets covering 1951-2018 as inputs. The mean surge heights along the coastline are in the range of 1.5-3.2 m and 2.0-3.5 m under 100-year and 200-year return periods, respectively. Areas in the west and near the estuary outlet are more prone to higher surge levels due to more frequent TCs affecting the areas historically. Differences in TC characteristics exist between the two best track datasets, which gives rise to localised difference in surge heights along the PRD coastline. The maximum differences in the 100-year and 200-year return period surge levels from the two best track datasets are 0.51 m and 0.64 m, respectively.Accepted versionThis research work is partially supported by the China-Singapore International Joint Research Institute (Project No. 205-A017020)

Cluster analysis of monthly precipitation over the western maritime continent under climate change

Changes in climate because of global warming during the 20th and 21st centuries have a direct impact on the hydrological cycle as driven by precipitation. However, studying precipitation over the Western Maritime Continent (WMC) is a great challenge, as the WMC has a complex topography and weather system. Understanding changes in precipitation patterns and their groupings is an important aspect of planning mitigation measures to minimize flood and drought risk as well as of understanding the redistribution of precipitation arising from climate change. This paper employs Ward’s hierarchical clustering on regional climate model (RCM)-simulated monthly precipitation gridded data over 42 approximately evenly distributed grid stations from the years 2030 to 2060. The aim was to investigate spatial and temporal groupings over the four major landmasses in the WMC and to compare these with historical precipitation groupings. The results showed that the four large-scale islands of Java, Sumatra, Peninsular Malaysia and Borneo would experience a significant spatial redistribution of precipitation over the years 2030 to 2060, as compared to historical patterns from 1980 to 2005. The spatial groups were also compared for two future forcing scenarios, representative concentration pathways (RCPs) 4.5 and 8.5, and different groupings over the Borneo region were observed.Published versio

Seasonal and Interannual Variability of Wet and Dry Spells over Two Urban Regions in the Western Maritime Continent

Daily rainfall data from two urban regions in Southeast Asia are analyzed to study seasonal and interannual variability of wet and dry spells. The analysis is carried out using 35 years of data from Singapore and 23 years of data from Jakarta. The frequency distribution of wet (dry) spells and their relative contribution to the total number of wet (dry) days and to the total rainfall are studied using 15 statistical indicators. At the annual scale, Singapore has a greater number of wet spells and a larger mean wet spell length compared to Jakarta. However, both cities have equal probability of extreme wet spells. Seasonal-scale analysis shows that Singapore is drier (wetter) than Jakarta during boreal winter (summer). The probability of extreme wet spells is lower (higher) for Singapore than Jakarta during boreal winter (summer). The results show a stronger contrast between Singapore and Jakarta during boreal summer. The study also examined the time series of Singapore wet and dry spell indicators for the presence of interannual trends. The results indicate statistically significant upward trends for a majority of wet spell indicators. The wet day percentage and mean wet spell length are increasing at 2.0% decade−1 and 0.18 days decade−1, respectively. Analysis of dynamic and thermodynamic variables from ERA-Interim during the study period indicates a strengthening of low-level convergence and vertical motion and an increase in specific humidity and atmospheric instability (convective available potential energy), which explain the increasing trends observed in Singapore wet spell indicators.MOE (Min. of Education, S’pore)Published versio