Tropical Cyclone Hazard Research Articles

Increasing sequential tropical cyclone hazards along the US East and Gulf coasts

Two tropical cyclones (TCs) that make landfall close together can induce sequential hazards to coastal areas. Here we investigate the change in sequential TC hazards in the historical and future projected climates. We find that the chance of sequential TC hazards has been increasing over the past several decades at many US locations. Under the high (moderate) emission scenario, the chance of hazards from two TCs impacting the same location within 15 days may substantially increase, with the return period decreasing over the century from 10–92 years to ~1–2 (1–3) years along the US East and Gulf coasts, due to sea-level rise and storm climatology change. Climate change can also cause unprecedented compounding of extreme hazards at the regional level. A Katrina-like TC and a Harvey-like TC impacting the United States within 15 days of each other, which is non-existent in the control simulation for over 1,000 years, is projected to have an annual occurrence probability of more than 1% by the end of the century under the high emission scenario.

Tropical cyclone wind hazard assessment for Donghaitang wind farm (Zhejiang Province, China): Case study

Currently, offshore and coastal wind power resources are growing rapidly around the world, especially in China. However, systematic research on the hazard assessment of wind farms under tropical cyclone conditions remains lacking. This study simulated the wind field of tropical cyclones based on a parameterized tropical cyclone wind field model, and analyzed the characteristics of historical tropical cyclones in Donghaitang wind farm (Zhejiang, China). Four extreme tropical cyclone hazard factors including the maximum wind speed (Vmax), maximum duration of wind direction change (Tmax), maximum cumulative wind direction change (Δθmax) and maximum rate of change in wind direction (ΔDmax) were proposed and examined. Then a comprehensive hazard assessment model for wind farms based on the analytic hierarchy process was established, and the risk to the Donghaitang wind farm represented by tropical cyclones during 1949–2021 was evaluated. Results showed that the number and intensity of tropical cyclones made landfall near the coast of Donghaitang wind farm gradually increased with time, which results in a gradual increase in the composite tropical cyclone risk level of the Donghaitang wind farm with time. The numbers and risk levels of tropical cyclones traveling northwestward were much larger than those traveling northward or northeastward. Moreover, the average composite risk index for tropical cyclones passing to the left of the wind farm was 14.3% higher than that for tropical cyclones passing to the right. The large values of Vmax and ΔDmax are main reasons for the high risk of the wind farm, while the other two hazard factors (Tmax, Δθmax) proposed to account for the wind turbine backup power are also of great importance in the design, selection and operation stages of offshore wind turbines. The findings of this study could provide support for hazard assessment of offshore and coastal wind farms exposed to tropical cyclones, including macro site selection of wind farms and type selection of wind turbines.

Strong Relationship between Eye Radius and Radius of Maximum Wind of Tropical Cyclones

Abstract Estimation of the radius of maximum wind (RMW) of tropical cyclone (TC) is helpful for the disaster prevention and mitigation. If RMWs are estimated from infrared (IR) imagery taken by geostationary meteorological satellites, their estimation is available densely in time, regardless of the ocean basin. Kossin et al. showed that when TCs have clear eyes, the eye radii estimated from IR images have a high correlation with the RMW estimated from aircraft reconnaissance. The regression of the former onto that latter was shown to have a mean absolute error (MAE) of 4.7 km. We revisit the IR-based RMW estimation by using C-band synthetic aperture radar (SAR) sea surface wind estimates. The criteria for selecting clear-eye cases are simplified. The MAE of the Kossin et al. method is found to be smaller than previously suggested: 3.1 km when the proposed relation is used and 2.7 km when the regression is revised with the SAR-measured RMWs. We further propose an improvement of the IR-based method to estimate the eye radii. The resultant MAE is shown to be 1.7 km, which indicates that the IR-based RMW estimation is more accurate than has been suggested. A strong correlation between eyewall slope and eye size is confirmed. We also investigated cloud features in the eye that may be closely related to RMW and wind structure around RMW. Potential applications of highly accurate RMW estimation are discussed. Significance Statement The radius of maximum wind (RMW) of tropical cyclone (TC) is an important factor for TC intensity estimation and disaster prevention. A previous study suggested that the RMWs of TCs with clear eyes can be estimated from geostationary satellite images at a mean absolute error (MAE) of 4.7 km. Here we improved the method, reducing the MAE by more than one-half. Since the method does not require aircraft or satellite in low Earth orbit, it helps TC monitoring at high frequency. The method can also improve initialization of models used to predict TC hazards and further our physical understanding and the climatology of the wind structures near the centers of TCs.

Divergence of tropical cyclone hazard based on wind-weighted track distributions in the Coral Sea, over 50 years

Tropical cyclones (TCs) with genesis in the Coral Sea present significant hazards to coastal regions in their surroundings. In addition, the erratic nature of TC tracks is not well understood in this region. Therefore, this study grouped Coral Sea TC tracks over the last fifty years based on K-means clustering of the maximum wind-weighted centroids. This was done in order to extract valuable new cyclone power, track curvature and location related information from their historical track records and to predict their behaviour in the light of a changing climate. TC track variance and curvature (sinuosity) were assessed. Three well-defined clusters of TC tracks were identified, and the results showed differing predominant directions of TC movement by cluster. Track sinuosity was shown to increase from east to west. Only one cluster showed a statistically significant trend (decreasing) in TC frequency. The TC power dissipation index (PDI) was used to reveal that two of the clusters have diverging trends for PDI post-2004. Based on the location of cyclone maximum intensity, only one cluster showed a statistically significant trend (towards the equator). All these findings demonstrated a clear variance in between-cluster hazard and show that TC trends discovered for the southwest Pacific are not manifest or consistent across all clusters.

Centennial analysis in tropical cyclone-induced precipitation in Korea

Tropical cyclone (TC)-induced precipitation has undergone significant multidecadal changes over the last 117 years (1904–2020) on the Korean Peninsula, as determined through the analysis of affected TCs and surface-observed precipitation at ten stations in the Republic of Korea (hereafter Korea). Information on TCs that have affected Korea over a century was collected from the National Typhoon Center of the Korea Meteorological Administration (KMA). The information was cross-validated by referring to the International Best Track Archive for Climate Stewardship archive, while the information for 1904–1950 was cross-validated by also examining extreme weather reports in newspapers. A significant regime shift in the annual total heavy rainfall (confined to rain events ≥100 mm day−1), and its frequency associated with the affected TCs was found before and after 1979. The regime-shift signal is robust regardless of the methodology. Heavy rainfall from non-TC events, however, has presented a regime-shift increase since 1997. Based on a detailed review of historical documents describing instrument type, measuring method, altitude, and site location, this rainfall increase in regime-shift is likely a non-climatic signal coming from updates in measurement tools (i.e., the weather station automation project of KMA) during 1995–2000. However, increases in heavy rainfall of TC events in 1979 are comprehensively supported by the intensity and track changes in Korea affecting TC and changes in large-scale atmospheric and oceanic environments. The present results provide an earnest validation of TC records over the Korean Peninsula and confirm a regime-shift increase in TC hazards over Korea, thus providing grounds for further global analysis.

Exposure to precipitation from tropical cyclones has increased over the continental United States from 1948 to 2019

AbstractExtreme precipitation from tropical cyclones can generate large-scale inland flooding and cause substantial damage. Here, we quantify spatiotemporal changes in population risk and exposure to tropical cyclone precipitation in the continental eastern United States over the period 1948–2019 using high-resolution in-situ precipitation observations. We find significant increases in the magnitude and likelihood of these extreme events due to increased rainfall rates and reduced translation speeds of tropical cyclones over land. We then develop a social exposure index to quantify exposure and risk of tropical cyclone precipitation as a function of both physical risk and socio-economic activities. Increased social exposure is primarily due to the increased risk of tropical cyclone precipitation, but there are regional differences. We identify exposure hotspots in the south-eastern United States, where rapid population growth and economic development amplify societal exposure to tropical cyclone hazards. Our multi-scale evaluation framework can help identify locations that should be targeted for mitigation and adaptation activities to increase their climate resilience.

Increasing Sequential Tropical Cyclone Hazards along the U.S. East and Gulf Coasts

Increasing Sequential Tropical Cyclone Hazards along the U.S. East and Gulf Coasts

Assessment of Tropical Cyclone Risk to Coral Reefs: Case Study for Australia

In this study, we attempt to expand tropical cyclone (TC) risk assessment methodology and build an understanding of TC risk to Australia’s natural environment by focusing on coral reefs. TCs are natural hazards known to have the potential to bring destruction due to associated gale-force winds, torrential rain, and storm surge. The focus of TC risk assessment studies has commonly centred around impacts on human livelihoods and infrastructure exposed to TC events. In our earlier study, we created a framework for assessing multi-hazard TC risk to the Australian population and infrastructure at the Local Government Area level. This methodology is used in this study with coral reefs as the focus. TC hazard, exposure, and vulnerability indices were created from selected coral-related datasets to calculate an overall TC risk index for the Ningaloo Reef (NR) and the Great Barrier Reef (GBR) regions. The obtained results demonstrate that the northern NR and the southern GBR had the highest risk values within the study area; however, limitations in data quality have meant that results are estimates at best. The study has shown the potential benefits of such a TC risk assessment framework that can be improved upon, as coral data collection becomes more readily available.

High-Resolution Hazard Assessment for Tropical Cyclone-Induced Wind and Precipitation: An Analytical Framework and Application

Intensified tropical cyclones (TCs) threaten the socioeconomic development of coastal cities. The coupling of strong wind and precipitation with the TC process usually amplifies the destructive effects of storms. Currently, an integrated analytical framework for TC hazard assessment at the city level that combines the joint statistical characteristics of multiple TC-induced hazards and local environmental features does not exist. In this study, we developed a novel hazard assessment framework with a high spatiotemporal resolution that includes a fine-tuned K-means algorithm for clustering TC tracks and a Copula model to depict the wind–precipitation joint probability distribution of different TC categories. High-resolution wind and precipitation data were used to conduct an empirical study in Shenzhen, a coastal megacity in Guangdong Province, China. The results show that the probabilities of TC-induced wind speed and precipitation exhibit significant spatial heterogeneity in Shenzhen, which can be explained by the characteristics of TC tracks and terrain environment factors. In general, the hazard intensity of TCs landing from the west side is higher than that from the east side, and the greatest TC intensity appears on the southeast coast of Shenzhen, implying that more disaster prevention efforts are needed. The proposed TC hazard assessment method provides a solid base for highly precise risk assessment at the city level.

Sensitivity of simulating Typhoon Haiyan (2013) using WRF: the role of cumulus convection, surface flux parameterizations, spectral nudging, and initial and boundary conditions

Abstract. Typhoon (TY) Haiyan was one of the most intense and highly destructive tropical cyclones (TCs) to affect the Philippines. As such, it is regarded as a baseline for extreme TC hazards. Improving the simulation of such TCs will not only improve the forecasting of intense TCs but will also be essential in understanding the potential sensitivity of future intense TCs with climate change. In this study, we investigate the effects of model configuration in simulating TY Haiyan using the Weather Research Forecasting (WRF) Model. Sensitivity experiments were conducted by systematically altering the choice of cumulus schemes, surface flux options, and spectral nudging. In addition to using the European Centre for Medium-Range Weather Forecasts Reanalysis fifth-generation (ERA5) single high-resolution realization as initial and boundary conditions, we also used 4 of the 10 lower-resolution ERA5 data assimilation system (EDA) ensemble members as initial and boundary conditions. Results indicate a high level of sensitivity to cumulus schemes, with a trade-off between using Kain–Fritsch and Tiedtke schemes that have not been mentioned in past studies of TCs in the Philippines. The Tiedtke scheme simulates the track better (with a lower mean direct positional error, DPE, of 33 km), while the Kain–Fritsch scheme produces stronger intensities (by 15 hPa minimum sea level pressure). Spectral nudging also resulted in a reduction in the mean DPE by 20 km, and varying the surface flux options resulted in the improvement of the simulated maximum sustained winds by up to 10 m s−1. Simulations using the EDA members initial and boundary conditions revealed low sensitivity to the initial and boundary conditions, having less spread than the simulations using different parameterization schemes. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in the track and intensity of simulating intense tropical cyclones.

Typhoon complexity: Northwest Pacific tropical cyclone season complex systems analysis

The complex nature of tropical cyclones (TCs) has been recognized in a vast literature yet only few works perform complex systems diagnostics to understand their dynamics. This is especially important in order to study the effects of global warming on TC hazards. Here, such analysis is performed from a data-driven perspective using statistical and nonlinear dynamics diagnostics to the annual Accumulated Cyclonic Energy (ACE) data over the most active basin, the Northwest Pacific, from the years 1950 to 2021. The best quality data period, from 1984 to 2021, is also considered for a separate analysis in order to test the possible differences due to the data acquisition process. The following results are obtained: (i) The use of mobile windows shows a lack of trend. (ii) The closeness to a normal probability distribution indicates unpredictability, as confirmed by the return map and the autocorrelation function. As an explanation for such unpredictability, the ordering and ranking analyses reveal the presence of several processes governing the dynamics with fractal forcing dominating the larger ACE values. (iii) The Hurst exponent analysis shows a slight persistence for less than 3 years and a very slight antipersistence for longer periods of time suggesting the presence of negative feedback. (iv) Finally, the TC dynamical system dimensionality is studied. A discontinuity is inferred from a Katz fractal dimension value of 2.8, suggesting the system dynamics to be embedded by at least three independent variables, in agreement with statistical models for the TC season.

Reliability-based calibration of site-specific design typhoon wind and wave loads for wind turbine

The wind turbines (WTs) that are designed, constructed, and installed near the coastline of mainland China are faced with geographically varying tropical cyclone hazards; failure of WTs due to the tropical cyclone (TC) hazards has been observed in this considered region. The reliability-based Chinese design code calibration of WTs subjected to TC hazards for the considered region seems missing in the literature. In the present study, we calibrate the site-specific design TC wind and wave loads for designing offshore and onshore WTs located in the considered region for selected target reliability indices. The calibration considers the correlated TC wind speed and significant wave height during the passage of TC events. Also, the companion load factors by considering wind load and inertial wave load effects are calibrated. Moreover, the statistics of the responses of the onshore and offshore versions of the National Renewable Energy Laboratory 5 MW wind turbines are calculated using the software package FAST. The statistics of the responses are used in the reliability-based verification analysis by considering the calibrated design TC wind load and wave load requirements. The results indicated that using the calibrated geographically varying TC wind and wave loads is adequate and can be used to aid structural design code making.

Perception and Comprehension of the Hurricane Threats and Impacts Graphics

Effective tropical cyclone risk reduction is possible only if all relevant threats are considered and analyzed. Recently, weather organizations have expanded their forecast products to include more information about tropical cyclone hazards. Of these products, the Hurricane Threats and Impacts (HTI) graphics are gaining support. Although the HTI graphics have been operational since 2015, no user evaluations of their efficacy have been published. In an online experiment with 114 non-expert participants, we explored the effect of prior tropical cyclone experience and storm characteristics on HTI perceived ease of use, task completion time, and comprehension. Overall, perceived ease of use and comprehension scores were low across the experience groups. Completion times were similar across the groups and storms. The results suggest that the HTI graphics are misinterpreted by the public and may not be effective in communicating tropical cyclone hazards.

Estimating tropical cyclone-induced wind, waves, and surge: A general methodology based on representative tracks

Tropical Cyclones (TCs) are singular storms causing intense wind, large waves, extreme water levels, and heavy rainfall. TCs prove every year to be one of the most destructive natural phenomena worldwide. The quantitative assessment of the hazards resulting from TCs (i.e., flooding and extreme winds) is challenging since satellite data are only available for recent decades, whereas older historical observations are incomplete and less accurate. In addition, long-term prediction through numerical weather forecasting is still limited. This often results in large uncertainties in the definition of TC hazards associated with events with longer return periods or in areas infrequently impacted by TCs. Even when this information is available, for example through statistical sampling of synthetic TC tracks, the numerical modelling of the associated hazards for all the different TC conditions can lead to computational costs which are often infeasible. Several methodologies that overcome the issues of accuracy and computational efficiency currently exist, but these are not generically applicable, and they tend to focus on specific areas only, for example where TCs typically make landfall. The main contribution of this paper is a novel methodology for the estimation and analysis of TC hydro-meteorological conditions and induced hazards. The method is generically applicable and maximizes accuracy while accounting for computational efficiency. Our approach identifies a smaller but representative set of TC tracks (RTCs) that preserves the information about extremes and the frequency of events of the larger population. The method is successfully applied and validated in a case study in the Bay of Bengal, using a set of synthetic TC tracks representing 1000 years of TC climate. For the best-performing configuration, the required number of scenarios and associated computational costs were reduced by 90% while maintaining accuracy in the simulated offshore storm surges, significant wave height, and windspeeds typically within 10% of the prediction based on the original full set of scenarios. This method is globally applicable and greatly improves the efficiency of TC-related hazard estimation, making it particularly valuable for areas with limited historical data.

Impact of Tropical Cyclone Avoidance on Fishing Vessel Activity over Coastal China Based on Automatic Identification System Data during 2013–2018

Tropical cyclones (TCs) may cause severe impacts on the activities of coastal fishing vessels. Due to the unavailability or unacceptability of detailed Automatic Identification System (AIS) data that are capable of differentiating fishing activity from navigation, as well as the lack of detailed models and observation data of TC winds, few studies have provided quantitative and reliable assessment of the impacts of TCs on fishing activities. In this study, we modeled snapshots for the TC winds of 52 TCs over the Northwest Pacific (NWP) basin from 2013 to 2018, as well as daily fishing hours and daily hours of presence (hereafter “vessel hours”) of fishing vessels. Based on these data, the spatiotemporal pattern of fishing vessel activity over offshore China was first analyzed and mapped. Then, a TC wind hazard index and absolute and relative impact indices were proposed to assess the impact of the 52 TCs on fishing and vessel hours. Their relationship was then fitted with the cumulative distribution function (CDF) of the log-normal distribution. The results show that in the 2013−2018 period, the most active fishing areas were located in the South China Sea. In each instance, an increase was first observed in the initial several years; then a decrease followed in the yearly total fishing hours per vessel in the remaining years. The relative impact index was significantly correlated to the TC wind hazard index proposed in this study. Based on the quantitative relationship between the specified TC hazard index and the impact indices, it is possible to implement a pre-cyclone rapid loss assessment due to TC avoidance in the future.

A Simple Model for Predicting the Tropical Cyclone Radius of Maximum Wind from Outer Size

Abstract The radius of maximum wind (Rmax) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However, Rmax is an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predicting Rmax from the radius of 34-kt (1 kt ≈ 0.51 m s−1) wind (R17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed, R17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimating Rmax. The model reproduces the observed statistical increase in Rmax with latitude and demonstrates that this increase is driven by the increase in R17.5 ms with latitude. Overall, the model offers a simple and fast first-order prediction of Rmax that can be used operationally and in risk models. Significance Statement If we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.

A Multivariate Scaling System Is Essential to Characterize the Tropical Cyclones' Risk

AbstractThe current Tropical Cyclones (TCs) scaling system, Saffir‐Simpson Hurricane Wind Scale (SSHWS), characterizes the hazardousness of these events solely based on wind speed. This is despite the fact that TCs are classic examples of compound hazards during which multiple hazard drivers that are wind, storm surge, and intense rainfall interact and yield in impacts greater than the sum of individuals. Studies have shown that people's decision to evacuate is highly related to the estimated SSHWS category. Thus, the current SSHWS ‐based classification of TCs yields an underestimation of the hazardousness of TCs and so may misguide the threatened communities. Here, we propose a new scaling system that uses Copulas for categorizing TCs based on the likelihood of a given set of severity for rainfall, surge, and wind speed. We use a variety of data sources to obtain the timing and intensity of wind speed, rainfall along the track, and the associated maximum surge for 102 TCs that have made landfall in the United States' Atlantic and Gulf coasts between 1979 and 2020. Comparing the outputs of our scaling system with official damage reporting for the costliest TCs in the history of the United States, we show that the proposed approach significantly improves TC hazard communication and can be useful for informing decision makers and emergency responders.

Projecting the Impacts of a Changing Climate: Tropical Cyclones and Flooding.

There is clear evidence that the earth's climate is changing, largely from anthropogenic causes. Flooding and tropical cyclones have clear impacts on human health in the United States at present, and projections of their health impacts in the future will help inform climate policy, yet to date there have been few quantitative climate health impact projections. Despite a wealth of studies characterizing health impacts of floods and tropical cyclones, many are better suited for qualitative, rather than quantitative, projections of climate change health impacts. However, a growing number have features that will facilitate their use in quantitative projections, features we highlight here. Further, while it can be difficult to project how exposures to flood and tropical cyclone hazards will change in the future, climate science continues to advance in its capabilities to capture changes in these exposures, including capturing regional variation. Developments in climate epidemiology and climate science are opening new possibilities in projecting the health impacts of floods and tropical cyclones under a changing climate.

Accomplishments of NOAA’s Airborne Hurricane Field Program and a Broader Future Approach to Forecast Improvement

Abstract Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and Gulfstream IV-SP (G-IV) Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions toward improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the next generation of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.

Temporal analysis for multi-hazard risk assessment of rice cultivation in coastal areas: a case study of Soc Trang, Vietnam

Rice is an important human crop and rice cultivation is threatened due to natural disasters, leading to negative effects on national and global food security. Natural disasters, such as tropical cyclones and saline intrusion, have dramatic influences in coastal regions. To investigate possible impacts of these disasters on rice cultivation, it needs an efficient tool to assess potential disaster impacts and a risk index is highly applicable. Therefore, this study aims at establishing a risk assessment of rice production in coastal areas under the effects of tropical cyclones and saline intrusion. We adopted the risk definition introduced by [1] in which risk is a function of hazard, exposure and, vulnerability. Multiple hazards of tropical cyclones and saline intrusion were indicated by their frequency and severity at some critical levels of 25%, 50% and, >50% rice yield reduction. Each hazard was weighted by its damage to rice yield. The exposure and vulnerability of rice crops are evaluated at different growing phases. The tropical cyclone hazard index was ranked high and very high in the wet season while the salinity hazard index was ranked very high in the dry season. Due to the combined effects of tropical cyclones and salinity, rice crop is highly susceptible during the reproduction phase and at the panicle initiation stage particularly. Based on the cropping calendar of My Xuyen, the period of October-November was the very high vulnerability period since it had the largest rice cultivable area and rice crops were at the reproduction phase. This result shows that rice crops are at high risk in October and November. Noticeably, saline intrusion reaches the highest level in April and May, but no risk is at this period because of no rice crop cultivated. This can reflect a measure to reduce risk by adjusting the cropping calendar.