Flood risk influenced by the compound effect of storm surge and rainfall under climate change for low-lying coastal areas

Intensification of the East Asian summer monsoon lifecycle based on observation and CMIP6

This study examined various regression-based techniques and an artificial neural network used for streamflow forecasting during typhoons. A flow hydrograph was decomposed into two segments, rising and falling limbs, and the individual segments were modeled using statistical techniques. In addition, a conceptual rainfall-runoff model, namely the Public Works Research Institute (PWRI)-distributed hydrological model, and statistical models were compared. The study area was the Tsengwen Reservoir watershed in Southern Taiwan. The data used in this study comprised the observed watershed rainfalls, reservoir inflows, typhoon characteristics, and ground weather data. The forecast horizons ranged from 1 to 12źh. A series of assessments, including statistical analyses and simulations, was conducted. According to the improvements in errors, among single-segment statistical models, the multilayer perceptron achieved superior prediction accurary compared with the regression-based methods. However, the pace regression was the most favorable according to an evaluation of model complexity and accuracy. To examine the robustness of the results for forecast horizons varying from 1 to 12źh, statistical significance tests were performed for the single- and two-segment models. The prediction ability of the two-segment models was superior to that of the single-segment models. In addition, Typhoon Sinlaku in 2008 was considered in a comparison between the conceptual PWRI model output and that of the developed statistical models. The results showed that the PWRI model yielded the least favorable results. The four regressions and MLP ANN were modeled for river streamflow prediction.The OLS, pace, isotonic, and additive regression-based techniques were examined.The number of time-lagged input data according to a subset selection method was evaluated.The statistical significance tests were performed for single- and two-segment models.Comparisons between the conceptual PWRI model and the statistical models were made.

Comparing single- and two-segment statistical models with a conceptual rainfall-runoff model for river streamflow prediction during typhoons

Hydrologic ecosystem services are greatly affected by the changing climate. In this study, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was used to quantify hydrologic ecosystem services. Five general circulation models (GCMs) and two representative concentration pathways (RCPs) were selected to estimate hydrologic ecosystem services. The Local Indicators of Spatial Association (LISA) index was used to identify hydrologic ecosystem hotspots. The hotspots were used to evaluate the impact of climate change on the services. Results indicate that annual water yields vary from −17% to 8%, with significant intra-year fluctuation. Compared to baseline data, the CESM1-CAM5 predicts an increase of 45% in June, but HadGEM2-AO predicts a drop to only 12% in January. Sediment export results show a similar trend to water yield, with sediment export increasing significantly under RCP 8.5, and monthly sediment export increases concentrated from June and October. Nitrogen and phosphorous exports both show less significant changes but obvious intra-year variations. The CESM1-CAM5 predicts strong seasonal and spatial variation of the hydrologic ecosystem services. Our proposed approach successfully identifies annual and monthly hotspot spatial changes of hydrologic ecosystem services under climate change.

https://www.mdpi.com/2073-4441/11/4/867/pdf

Climate change impact on spatiotemporal hotspots of hydrologic ecosystem services: A case study of Chinan catchment, Taiwan

This study evaluated the overflow risk of the Tsengwen River under a climate change scenario by using bias-corrected dynamic downscaled data as inputs for a SOBEK model (Deltares, the Netherlands). The results showed that the simulated river flow rate at Yufeng Bridge (upstream), Erxi Bridge (midstream), and XinZong (1) (downstream) stations are at risk of exceeding the management plan’s flow rate for three projection periods (1979–2003, 2015–2039, 2075–2099). After validation with the geomorphic and hydrological data collected in this study, the frequency at which the flow rate exceeded the design flood was 2 in 88 events in the base period (1979–2003), 6 in 82 events in the near future (2015–2039), and 10 in 81 events at the end of the century (2075–2099).

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Estimating the Risk of River Flow under Climate Change in the Tsengwen River Basin

Funding information Ministry of Science and Technology, Grant/Award Number: MOST 107-2621-M865-001; Office of Science, Grant/Award Number: DE-SC0016605 Abstract The active phase of the East Asian summer monsoon (EASM) in Taiwan during May and June, known as Meiyu, produces substantial precipitation for water uses in all sectors of society. Following a companion study that analysed the historical increase in the Meiyu precipitation, the present study conducted model evaluation and diagnosis based on the EASM lifecycle over Taiwan. Higher and lower skill groups were identified from 17 Couple Model Intercomparison Project Phase 5 (CMIP5) models, with five models in each group. Despite the difference in model performance, both groups projected a substantial increase in the Meiyu precipitation over Taiwan. In the higher skill group, weak circulation changes and reduced low-level convergence point to a synoptically unfavourable condition for precipitation. In the lower skill group, intensified low-level southwesterly winds associated with a deepened upper level trough enhance moisture pooling. Thus, the projected increase in Meiyu precipitation will likely occur through the combined effects of (1) the extension of a strengthened North Pacific anticyclone enhancing southwesterlies; and (2) more systematically, the Clausius–Clapeyron relationship that increases precipitation intensity in a warmer climate. The overall increase in the Meiyu precipitation projected by climate models of variable performance supports the observed tendency toward more intense rainfall in Taiwan and puts its early June 2017 extreme precipitation events into perspective.

Projected increase of the East Asian summer monsoon (Meiyu) in Taiwan by climate models with variable performance

Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS), which has a conceptual, distributed rainfallrunoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 2003 (Present), 2015 2039 (Near-future), and 2075 2099 (Future), provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Ten extreme rainfall (top ten) events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 1.6 (Near-future/Present) and 0.9 2.2 (Future/Present), respectively. Additionally, we evaluated how these future discharges would affect the reservoir’s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam’s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir’s flood control capacity and was approximately 79.6 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

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Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM)

Lee-Yaw Lin

Papers

Projected increase of the East Asian summer monsoon (Meiyu) in Taiwan by climate models with variable performance

Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM)