scholarly journals Evaluation of bias-adjusted satellite precipitation estimations for extreme flood events in Langat river basin, Malaysia

2019 ◽  
Vol 51 (1) ◽  
pp. 105-126 ◽  
Author(s):  
Eugene Zhen Xiang Soo ◽  
Wan Zurina Wan Jaafar ◽  
Sai Hin Lai ◽  
Faridah Othman ◽  
Ahmed Elshafie ◽  
...  
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Monsoon Season ◽  
Rainfall Threshold ◽  
Careful Consideration ◽  
Northeast Monsoon ◽  
Satellite Precipitation ◽  
Extreme Floods ◽  
Extreme Flood ◽  
Langat River

Abstract Even though satellite precipitation products have received an increasing amount of attention in hydrology and meteorology, their estimations are prone to bias. This study investigates the three approaches of bias correction, i.e., linear scaling (LS), local intensity scaling (LOCI) and power transformation (PT), on the three advanced satellite precipitation products (SPPs), i.e., CMORPH, TRMM and PERSIANN over the Langat river basin, Malaysia by focusing on five selected extreme floods due to northeast monsoon season. Results found the LS scheme was able to match the mean precipitation of every SPP but does not correct standard deviation (SD) or coefficient of variation (CV) of the estimations regardless of extreme floods selected. For LOCI scheme, only TRMM and CMORPH estimations in certain floods have showed some improvement in their results. This might be due to the rainfall threshold set in correcting process. PT scheme was found to be the best method as it improved most of the statistical performances as well as the rainfall distribution of the floods. Sensitivity of the parameters used in the bias correction is also investigated. PT scheme is found to be least sensitive in correcting the daily SPPs compared to the other two schemes. However, careful consideration should be given for correcting the CMORPH and PERSIANN estimations.

Evaluation of satellite precipitation products for extreme flood events: case study in Peninsular Malaysia

2018 ◽  
Vol 10 (4) ◽  
pp. 871-892 ◽  
Author(s):  
Eugene Zhen Xiang Soo ◽  
Wan Zurina Wan Jaafar ◽  
Sai Hin Lai ◽  
Tanvir Islam ◽  
Prashant Srivastava
Keyword(s):  
Daily Rainfall ◽  
River Basins ◽  
Peninsular Malaysia ◽  
Careful Consideration ◽  
Northeast Monsoon ◽  
Flood Events ◽  
Satellite Precipitation ◽  
Thiessen Polygon ◽  
Extreme Flood ◽  
Kelantan River Basin

Abstract This study aimed at evaluating the three advanced satellite precipitation products (SPPs), i.e. CMORPH, TRMM 3B42V7 and PERSIANN, against the ground observation to evaluate their performance in detecting rain, capturing storms and rainfall pattern during 2014–2015 extreme flood events at three different river basins in Peninsular Malaysia (Kelantan, Langat and Johor river basins). Several spatial interpolation methods, including Arithmetic Mean, Thiessen Polygon, Inverse Distance Weighting, Ordinary Kriging and Spline were applied on the ground observations to transform the point-based precipitation into areal precipitation. Slight variations in the interpolated values were found, but overall it was comparable. Based on the daily rainfall data for the duration of 62 days, this study found that all SPPs performed with acceptable accuracy, as shown by the Kelantan river basin; however, these SPPs did not estimate accurately for Langat and Johor river basins. Overall, TRMM and CMORPH outperformed PERSIANN for the Langat and Johor river basins. In conclusion, all SPPs were capable of predicting heavy rainfall during the northeast monsoon and the level of accuracy is promising for the northern part of Peninsular Malaysia. However, as for the rest of the region, careful consideration should be given when applying the SPPs.

scholarly journals Precision of raw and bias-adjusted satellite precipitation estimations (TRMM, IMERG, CMORPH, and PERSIANN) over extreme flood events: case study in Langat river basin, Malaysia

2020 ◽  
Vol 11 (S1) ◽  
pp. 322-342 ◽  
Author(s):  
Eugene Zhen Xiang Soo ◽  
Wan Zurina Wan Jaafar ◽  
Sai Hin Lai ◽  
Faridah Othman ◽  
Ahmed Elshafie ◽  
...  
Keyword(s):  
River Basin ◽  
Random Errors ◽  
Satellite Precipitation ◽  
Extreme Flood ◽  
Langat River ◽  
Alternative Means ◽  
Local Intensity ◽  
Peak Streamflow ◽  
Intensity Scaling

Abstract Although satellite precipitation products (SPPs) increasingly provide an alternative means to ground-based observations, these estimations exhibit large systematic and random errors which may cause large uncertainties in hydrologic modeling. Three approaches of bias correction (BC), i.e. linear scaling (LS), local intensity scaling (LOCI), and power transformation (PT), were applied on four SPPs (TRMM, IMERG, CMORPH, and PERSIANN) during 2014/2015 extreme floods in Langat river basin, and the performance in terms of rainfall and streamflow were investigated. The results show that the original TRMM had a potential to predict the peak streamflow although CMORPH show the best performance in general. After performing BC, it is found that the LS-IMERG and LOCI-TRMM show the best performance at both rainfall and streamflow analysis. Generally, it is indicated that the current SPP estimations are still imperfect for any hydrological applications. Cross validation of different datasets is required to avoid the calibration effects of datasets.

scholarly journals Quantifying Landscape Structure of the Kelantan River Basin Before and After a Major Flood Event Using Landscape Metrics

2021 ◽  
pp. 61-67
Author(s):  
H.Y. Abdul
Keyword(s):  
River Basin ◽  
Land Use Planning ◽  
Landscape Structure ◽  
Monsoon Season ◽  
Integrated Approach ◽  
Flood Event ◽  
Northeast Monsoon ◽  
Flood Events ◽  
Kelantan River Basin ◽  
The Impact

Over the years, flood is one of the natural hazards which occur all over the world and it is critical to be controlled through proper management. Flood in Kelantan is mainly caused by heavy rainfall brought by the Northeast monsoon starting from November to March every year. It is categorized as annual flood as it occurs every year during the Monsoon season. Severe flood events in Kelantan, Malaysia cause damage to both life and property every year and understanding landscape structure changes is very important for planners and decision makers for future land use planning and management. This research aims to quantify the landscape structure near to Kelantan River basin during the flood event using integrated approach of remote sensing (RS), geographic information system (GIS) technique and landscape ecological approach. As a result, this study provide new knowledge on landscape structure that contributes to understand the impact of flood events and provide the best ways to mitigate flooding for helping to protect biodiversity habitat and dwellers. As conclusions, this kind of study will give more benefits to various stakeholders such as Department of Irrigation and Drainage, Department of Environment, state government, fisherman and communities.

Holocene extreme paleofloods and their climatological context, Upper Colorado River Basin, USA

2020 ◽  
Vol 44 (5) ◽  
pp. 727-745
Author(s):  
Tao Liu ◽  
Lin Ji ◽  
Victor R Baker ◽  
Tessa M Harden ◽  
Michael L Cline
Keyword(s):  
River Basin ◽  
Colorado River ◽  
Meta Analysis ◽  
Flood Frequency ◽  
Colorado River Basin ◽  
Extreme Floods ◽  
Upper Colorado River Basin ◽  
Extreme Flood ◽  
Southwestern Usa ◽  
Extreme Flooding

Given its singular importance for water resources in the southwestern USA, the Upper Colorado River Basin (UCRB) is remarkable for the paucity of its conventional hydrological record of extreme flooding. Short-term record-based flood frequency analyses lead to very great aleatory uncertainties about infrequent extreme flood events and their climate-driven causal associations. This study uses paleoflood hydrology to examine a small portion of the underutilized, but very extensive natural record of Holocene extreme floods in the UCRB. We perform a meta-analysis of 82 extreme paleofloods from 18 slack water deposit sites in the UCRB to show linkages between Holocene climate patterns and extreme floods. The analysis demonstrates several clusters of extreme flood activity: 8040–7960, 4400–4300, 3600–3460, 2900–2740, 2390–1980, 1810–720, and 600–0 years BP. The extreme paleofloods were found to occur during both dry and wet periods in the paleoclimate record. When compared with independent paleoclimatic records across the Rocky Mountains and the southwestern USA, the observed temporal clustering pattern of UCRB extreme paleofloods shows associations with periods of abruptly intensified North Pacific-derived storms connected with enhanced variability of El Niño. This approach demonstrates the value of creating paleohydrological databases and comparing them with hydro-climatic proxies in order to identify natural patterns and to discover possible linkages to fundamental processes such as changes in climate.

scholarly journals A Censored Shifted Mixture Distribution Mapping Method to Correct the Bias of Daily IMERG Satellite Precipitation Estimates

2019 ◽  
Vol 11 (11) ◽  
pp. 1345 ◽  
Author(s):  
Qiumei Ma ◽  
Lihua Xiong ◽  
Jun Xia ◽  
Bin Xiong ◽  
Han Yang ◽  
...  
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Hydrological Modeling ◽  
Extreme Values ◽  
Mixture Distribution ◽  
Satellite Precipitation ◽  
Gamma Distributions ◽  
Mapping Bias ◽  
Precipitation Estimates ◽  
Distribution Mapping

Satellite precipitation estimates (SPE) provide useful input for hydrological modeling. However, hydrological modeling is frequently hindered by large bias and errors in SPE, inducing the necessity for bias corrections. Traditional distribution mapping bias correction of daily precipitation commonly uses Bernoulli and gamma distributions to separately model the probability and intensities of precipitation and is insufficient towards extremes. This study developed an improved distribution mapping bias correction method, which established a censored shifted mixture distribution (CSMD) as a transfer function when mapping raw precipitation to the reference data. CSMD coupled the censored shifted statistical distribution to jointly model both the precipitation occurrence probability and intensity with a mixture of gamma and generalized Pareto distributions to enhance extreme-value modeling. The CSMD approach was applied to correct the up-to-date SPE of Integrated Multi-satelliE Retrievals for Global Precipitation Measurement (GPM) with near-real-time “Early” run (IMERG-E) over the Yangtze River basin. To verify the hydrological response of bias-corrected IMERG-E, the streamflow of the Wujiang River basin was simulated using Ge´nie Rural with 6 parameters (GR6J) and Coupled Routing Excess Storage (CREST) models. The results showed that the bias correction using both BerGam (traditional bias correction combining Bernoulli with gamma distributions) and the improved CSMD could reduce the systematic errors of IMERG-E. Furthermore, CSMD outperformed BerGam in correcting overall precipitation (with the median of mean absolute errors of 2.46 mm versus 2.81 mm for CSMD and BerGam respectively, and the median of modified Nash–Sutcliffe efficiency of 0.39 versus 0.29) and especially in extreme values for uniform format and particular attention paid to extremes. In addition, the hydrological effect that CSMD correction exerted on IMERG-E, driving GR6J and CREST rainfall-runoff modeling, outperformed that of the BerGam correction. This study provides a promising integrated distribution mapping framework to correct the biased daily SPE, contributing to more reliable hydrological forecasts by informing accurate precipitation forcing.

scholarly journals Adequacy of Near Real-Time Satellite Precipitation Products in Driving Flood Discharge Simulation in the Fuji River Basin, Japan

2021 ◽  
Vol 11 (3) ◽  
pp. 1087
Author(s):  
Li Zhou ◽  
Mohamed Rasmy ◽  
Kuniyoshi Takeuchi ◽  
Toshio Koike ◽  
Hemakanth Selvarajah ◽  
...  
Keyword(s):  
Real Time ◽  
River Basin ◽  
Bias Correction ◽  
Large Scale ◽  
River Flow ◽  
Hydrologic Model ◽  
Satellite Precipitation ◽  
Flood Discharge ◽  
Discharge Simulation ◽  
The Impact

Flood management is an important topic worldwide. Precipitation is the most crucial factor in reducing flood-related risks and damages. However, its adequate quality and sufficient quantity are not met in many parts of the world. Currently, near real-time satellite precipitation products (NRT SPPs) have great potential to supplement the gauge rainfall. However, NRT SPPs have several biases that require corrections before application. As a result, this study investigated two statistical bias correction methods with different parameters for the NRT SPPs and evaluated the adequacy of its application in the Fuji River basin. We employed Global Satellite Mapping of Precipitation (GSMaP)-NRT and Integrated Multi-satellitE Retrievals for GPM (IMERG)-Early for NRT SPPs as well as BTOP model (Block-wise use of the TOPMODEL (Topographic-based hydrologic model)) for flood runoff simulation. The results showed that the corrected SPPs by the 10-day ratio based bias correction method are consistent with the gauge data at the watershed scale. Compared with the original SPPs, the corrected SPPs improved the flood discharge simulation considerably. GSMaP-NRT and IMERG-Early have the potential for hourly river-flow simulation on a basin or large scale after bias correction. These findings can provide references for the applications of NRT SPPs in other basins for flood monitoring and early warning applications. It is necessary to investigate the impact of number of ground observation and their distribution patterns on bias correction and hydrological simulation efficiency, which is the future direction of this study.

scholarly journals Frequency analysis of extreme floods in a highly developed river basin

2016 ◽  
Author(s):  
Tomohiro Tanaka ◽  
Yasuto Tachikawa ◽  
Yutaka Ichikawa ◽  
Kazuaki Yorozu
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
River Discharge ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Discharge Data ◽  
Extreme Floods ◽  
Extreme Flood ◽  
Flood Peaks ◽  
Gauging Station

Abstract. Design flood, river discharge with a particular return period, is fundamental to determine the scale of flood control facilities. In addition, considering a changing climate, not only frequencies of river discharge at design level but those of devastating flooding are also crucial. Characteristics of river discharge during extreme floods largely differ from those during others because of upstream dam operation and/or river overflow; however, flood frequency analysis (FFA) from past discharge data is difficult to represent such impact because river basins rarely experience floods over the design level after river improvement and dam construction. To account for the above impact on extreme flood frequencies, this study presented a rainfall-based flood frequency model (RFFM) that derives flood frequencies from probabilistic rainfall modelling that empirically represents probabilistic structure of rainfall intensity over a catchment by directly using observed spatial-temporal rainfall profiles. The RFFM was applied to the Yodo River basin, Japan and demonstrated that flood frequency estimations by the RFFM well represent past flood frequencies at the Hirakata gauging station. Furthermore, the RFFM showed that return periods of large flood peaks are estimated at extremely large values, reflecting decrease of discharge by the inundation in an upstream area of the gauging station. On the other hand, FFA from past discharge data did not represent this impact because it has not experienced such huge flood peaks in an observation period. This study demonstrated the importance of the RFFM for flood frequency estimations, including those exceeding the design level.

scholarly journals Watershed Sustainability Index for Langat UNESCO HELP River Basin, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 187
Author(s):  
Rahmah Elfithri ◽  
Mazlin Mokhtar ◽  
Mat Pauzi Abdullah ◽  
Mohd Raihan Taha ◽  
Mohd Ekhwan Toriman ◽  
...  
Keyword(s):  
River Basin ◽  
Catchment Area ◽  
Economic Conditions ◽  
Environmental Condition ◽  
Sustainability Index ◽  
State Response ◽  
Maximum Value ◽  
Langat River ◽  
Basin Hydrology ◽  
Pressure State

The study on Watershed Sustainability Index (WSI) has been conducted to analyst the environmental condition in the area incorporating ecological baseline and socio-economic conditions. WSI is an integrated indicator based on basin Hydrology, Environment, Life and Policy (HELP) state condition. It is suitable to be applied in the Langat River Basin in Malaysia which has similar catchment area (up to 2,350 km2) and is one of the UNESCO HELP River Basin since 2004. The WSI analysis which uses a pressure–state–response function based on basin HELP Indicator was done for Langat River Basin by using relevant available 5 years data for the period of 2009 to 2013. It is found that Langat River Basin is having WSI value of 0.68 which falls under the category of medium sustainability (between 0.5-0.8). Based on the maximum value (i.e. 1) or high sustainability (i.e. WSI value more than 0.8) it can be said that Langat is in the good side in term of sustainability. Few management aspects need to be improved and maintained well to be more sustainable. The assessment provides Langat River Basin with more information that is crucial in managing the basin through the adoption of UNESCO’s HELP Framework.   

scholarly journals Projection of Hydro-Climatic Extreme Events under Climate Change in Yom and Nan River Basins, Thailand

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 665
Author(s):  
Chanchai Petpongpan ◽  
Chaiwat Ekkawatpanit ◽  
Supattra Visessri ◽  
Duangrudee Kositgittiwong
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Extreme Events ◽  
River Basins ◽  
Annual Rainfall ◽  
Extreme Floods ◽  
Extreme Flood ◽  
Rcp 8.5 ◽  
Near Future ◽  
Far Future

Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.

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