Search Results (12)

This study aims to assess a spillway’s capacity to manage the highest possible fluctuations in water levels, the probable maximum flood (PMF). The PMF values have experienced alterations throughout the last six decades since the initial design and construction of the Kaeng Krachan Dam, one of Thailand’s major dams. The study also conducted an assessment of the greatest levels of rainfall for different timeframes, known as probable maximum precipitation (PMP). This was achieved by simulating the movement of rainstorms into the reservoir area near the dam. Afterwards, a thorough examination was carried out on several time periods related to anticipated flood volumes, PMF, and the spillway’s capability. The research entailed a comprehensive analysis of rainfall occurrences spanning 65 years, encompassing a total of 190 storm events, to present the top 10 highest recorded levels of rainfall in the southern and western regions of Thailand. This information is of utmost significance in assessing the potential maximum rainfall in the study area. The results reveal that the highest PMP observed over a three-day period was 429.20–726.40 mm, which is slightly different from the results obtained using storm transposition method (513.90–869.76 mm). Results of PMF and base flow were 4677.00 and 86.80 cms, respectively. The results of the examination of the estimated maximum flood volumes and their comparison with previous studies show that the maximum flow rates per unit area are within reasonable and consistent boundaries. The current spillway has the capability to manage flood flows with a frequency of up to 10,000 years. Nevertheless, while examining the potential PMF, it has been concluded that the existing spillway’s capacity is insufficient to adequately handle the highest water level in the reservoir, therefore preventing it from exceeding the designated maximum water level. Full article

Extreme rainfall and floods have increased in frequency and severity in recent years, due to climate change and urbanization. Consequently, interest in estimating the probable maximum precipitation (PMP) has been burgeoning. The World Meteorological Organization (WMO) recommends two types of methods for calculating the PMP: hydrometeorological and statistical methods. This study proposes a modified Hershfield’s nomograph method and assesses the changes in PMP values based on the two representative concentration pathway (RCP4.5 and RCP8.5) scenarios in South Korea. To achieve the intended objective, five techniques were employed to compute statistical PMPs (SPMPs). Moreover, the most suitable statistical method was selected by comparing the calculated SPMP with the hydrometeorological PMP (HPMP), by applying statistical criteria. Accordingly, SPMPs from the five methods were compared with the HPMPs for the historical period of 2020 and the future period of 2100 for RCP 4.5 and 8.5 scenarios, respectively. The results confirmed that the SPMPs from the modified Hershfield’s nomograph showed the smallest MAE (mean absolute error), MAPE (mean absolute percentage error), and RMSE (root mean square error), which are the best results compared with the HPMP with an average SPMP/HPMP ratio of 0.988 for the 2020 historical period. In addition, Hershfield’s method with varying $K_M$ exhibits the worst results for both RCP scenarios, with SPMP/HPMP ratios of 0.377 for RCP4.5 and 0.304 for RCP8.5, respectively. On the contrary, the modified Hershfield’s nomograph was the most appropriate method for estimating the future SPMPs: the average ratios were 0.878 and 0.726 for the 2100 future period under the RCP 4.5 and 8.5 scenarios, respectively, in South Korea. Full article

Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m³/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam. Full article

Changes in flood loads and reservoir levels, produced by climate change (CC), represent an increasing concern for dam safety managers and downstream populations, highlighting the need to define adaptation strategies based on the dam failure risk management framework. Currently, thousands of dams worldwide, varying in use, age, and maintenance, may represent a threat to downstream cities in the case of structural failure. Several studies relate the failure of dams to several issues in the spillway, which may be even more vulnerable in CC conditions. This study provides a review of dam safety threats due to CC and approaches for the design/redesign of the spillway to cope with CC. A general four-stage methodology is proposed: data gathering and hydro-climatic, hydrological, and hydraulic analyses. Afterward, this methodology is applied to the spillway design for the Sube y Baja dam in Ecuador. The Probable Maximum Precipitation (PMP) increases around 20% considering CC under the Representative Concentration Pathway 8.5. Such an increment derived a 25% increase in the spillway maximum flow. These results show that the non-stationary hydrological regimes related to CC require a revision of engineering design criteria for hydraulic structures in general, and call for a consensus on design variables under CC. Full article

Estimation of the Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) are regulatory requirements in many jurisdictions that are used in the design of dams and assessment of existing infrastructure. The recently available British Columbia MetPortal provides regionally consistent PMP and precipitation frequency estimates across the province of British Columbia (BC). This paper proposes an approach to process and apply this data for the estimation of the PMF for watersheds across British Columbia. Guidelines are presented for selection of transposition points applicable to a watershed, and algorithms are developed for processing the geospatial probable maximum storm and precipitation frequency data. The algorithms developed are generic to multiple software and programming environments, and could also be applied in other regions where spatially and temporally intact PMP estimates are available. A detailed description of data sources and development of PMF scenario inputs is provided, as well as details of important sensitivity analyses. The methodology is applied to estimate the PMF for the Cheakamus Basin north of Squamish British Columbia. The application of the MetPortal PMP and precipitation frequency estimates, when used with a consistent PMF development methodology as proposed in this paper, will help improve the consistency of PMF estimates for watersheds across the province, offering a welcome improvement for dam owners and regulators. Full article

The focus of this research is to develop a general method for estimation of rain intensity for application in various geographical regions. In a world with a changing climate, a high importance is attributed to the potential threats caused by increased temperature and rainfall intensity levels. The rainfall intensity climate is here interpreted by a combination of cloud physical factors affecting rain intensity and further developed by the use of climate data and rain intensity statistics. A formula was developed that estimates extreme rainfall and the frequency of these extremes with durations in the intervals of 5 min to 24 h. The obtained estimates are compared in this article with results from statistical methods for the extreme value analysis of measurements. The comparison shows about 90% of the explained variance. The coefficients in the formula are connected with climatological predictors based on the climatological norms of temperature and rainfall. Rain intensity maps over Sweden were produced using the developed formula. Examples of the function of the formula are also given for six European countries. The application of the formula in connection with the probable maximum precipitation (PMP) is presented, where the return period of extreme rainfall is a key factor. The formula is tested with an assumed increased warming of the atmosphere of 1 to 5 °C, and the result indicates an increase of 5.9% of the rainfall amount per each warming degree in intense rainfall. Full article

Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern. Full article

For public safety, especially for people who dwell in the valley that is located downstream of a dam site, as well as the protection of economic and environmental resources, risk management programs are urgently required all over the world. Despite the high safety standards of dams because of improved engineering and excellent construction in recent times, a zero-risk guarantee is not possible, and accidents can happen, triggered by natural hazards, human actions, or just because the dam is aging. In addition to that is the impact of potential climate change, which may not have been taken into account in the original design. A flood risk management program, which is essential for protecting downstream dam areas, is required. Part of this program is to prepare an inundation map to simulate the impact of dam failure on the downstream areas. The Baysh dam has crucial importance both to protect the downstream areas against flooding, to provide drinking water to cities in the surrounding areas, and to use the excess water for irrigation of the agricultural areas located downstream of the dam. Recently, the Kingdom of Saudi Arabia (KSA) was affected by extraordinary rainstorm events causing many problems in many different areas. One of these events happened along the basin of the Baysh dam, which raised the alarm to the decision makers and to the public to take suitable action before dam failure occurs. The current study deals with a flood risk analysis of Wadi Baysh using an integration of hydrologic and hydraulic models. A detailed field investigation of the dam site and the downstream areas down to the Red Sea coast has been undertaken. Three scenarios were applied to check the dam and the reservoir functionality; the first scenario at 100- and 200-year return period rainfall events, the second scenario according to the Probable Maximum Precipitation (PMP), and the third scenario if the dam fails. Our findings indicated that the Baysh dam and reservoir at 100- and 200-year rainfall events are adequate, however, at the PMP the water will spill out from the spillway at ~8900 m³/s causing flooding to the downstream areas; thus, a well-designed channel along the downstream wadi portion up to the Red Sea coast is required. However, at dam failure, the inundation model indicated that a vast area of the section downstream of the dam will be utterly devastated, causing a significant loss of lives and destruction of urban areas and agricultural lands. Eventually, an effective warning system and flood hazard management system are imperative. Full article

In this study, future probable maximum precipitations (PMPs) based on future meteorological variables produced from three regional climate models (RCMs) of 50-km spatial resolution provided by Coordinated Regional Climate Downscaling Experiment (CORDEX) are projected. In order to estimate future PMPs, the hydro-meteorological method is applied. The key future meteorological variable used to analyze the rate of change of future PMPs is the dew-point temperature. Future 12-h persistence 100-year return period extreme dew-point temperatures obtained from future daily dew-point temperature time series by using the scale-invariance method are applied to estimate future PMPs. As a result of estimating future PMPs using several RCMs and representative concentration pathways (RCPs) scenarios, the spatial distribution of future PMPs is expected to be similar to that of the present, but PMPs tend to increase in the future. In addition, it can be seen that the difference in PMPs estimated from various RCMs and RCP scenarios is getting bigger in the future. Especially after 2070, the difference has increased even more. In the short term, it is proposed to establish climate change adaptation policies with an 18% increase in PMPs, which is the ensemble average in the future year 2050. Full article

Probable Maximum Precipitation (PMP) is an essential prerequisite in designing dams, spillways, and reservoirs in order to minimize the risk of overtopping infrastructure collapse, especially under today’s changing climate. This study investigates conventional PMP estimation approach by using both scarce in-situ observations and mainstream satellite precipitation products in the Dadu River basin, where plenty of reservoirs and dams are being built. The satellite data include Climate Prediction Center (CPC) MORPHing algorithm (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Tropic Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7. The evaluation of satellite products shows that CMORPH and 3B42V7 agree well with gauge-based dataset for the period of 1998–2013 at both the grid and basin scales, also capturing the extreme precipitation events, with high Correlation Coefficients (CC) in terms of 0.68 and 0.71, respectively. Also, CMORPH and 3B42V7 show better performance for the magnitude and spatial distribution of 24-h PMP in such complex terrains. PERSIANN-CDR shows an overestimation in the upstream and an underestimation in the downstream. As among the first studies of satellite precipitation-based PMP estimation, this work sheds lights on the suitability of satellite precipitation in PMP estimation and could provide a reference for future extended spatially-distributed PMP estimation in vast ungauged regions. Full article

The Multiplicative Discrete Random Cascade (MDRC) class of model is used to temporally disaggregate rainfall volumes through multiplying the volumes by random weights, which is repeated through multiple disaggregation levels. The model development involves the identification of probability density functions from which to sample the weights. The parameters of the probability density functions are known to be dependent on the rainfall volume. This paper characterises the volume dependency over the scarcely observed extreme ranges of rainfall, introducing the concept of volume-bounded MDRC models. Probable maximum precipitation (PMP) estimates are used to define theoretically-based points and asymptotes to which the observation-based estimates of the MDRC model parameters are extrapolated. Alternative models are tested using a case study of rainfall data from Brisbane, Australia covering the period 1908 to 2015. The results show that moving from a baseline model with constant parameters to incorporating the volume dependency of the parameters is essential for acceptable performance in terms of the frequency and magnitude of modelled extremes. As well as providing better estimates of parameters at each disaggregation level, the volume dependency provides an in-built bias correction when moving from one level to the next. A further, relatively small performance gain is obtained by extrapolating the observed dependency to the theoretically-based bounds. The volume dependency of the parameters is found to be reasonably time-scaleable, providing opportunity for advances in the generalisation of MDRC models. Sensitivity analysis shows that the subjectivities and uncertainties in the modelling procedure have mixed effects on the performance. A principal uncertainty, to which the results are sensitive, is the PMP estimate. Therefore, in applications of the bounded approach, the PMP should ideally be described by a probability distribution function. Full article

Extreme precipitation events have been extensively applied to the design of social infra structures. Thus, a method to more scientifically estimate the extreme event is required. This paper suggests a method to estimate the extreme precipitation in Korea using a regional climate model. First, several historical extreme events are identified and the most extreme event of Typhoon Rusa (2002) is selected. Second, the selected event is reconstructed through the Weather Research and Forecasting (WRF) model, one of the Regional Climate Models (RCMs). Third, the reconstructed event is maximized by adjusting initial and boundary conditions. Finally, the Probable Maximum Precipitation (PMP) is obtained. The WRF could successfully simulate the observed precipitation in terms of spatial and temporal distribution (R² = 0.81). The combination of the WRF Single-Moment (WSM 6-class graupel scheme (of microphysics), the Betts-Miller-Janjic scheme (of cumulus parameterization) and the Mellor-Yamada-Janjic Turbulent Kinetic Energy (TKE) scheme (of planetary boundary layer) was determined to be the best combination to reconstruct Typhoon Rusa. The estimated PMP (RCM_PMP) was compared with the existing PMP. The RCM_PMP was generally in good agreement with the PMP. The suggested methodology is expected to provide assessments of the existing PMP and to provide a new alternative for estimating PMP. Full article