scholarly journals Estimation of Missing Rainfall Data Using GEP: Case Study of Raja River, Alor Setar, Kedah

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Nor Zaimah Che Ghani ◽  
Zorkeflee Abu Hasan ◽  
Lau Tze Liang
Keyword(s):  
Hydrological Modeling ◽  
Gene Expression Programming ◽  
Flood Management ◽  
Hydraulic Modeling ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Urban Flood ◽  
Rainfall Station ◽  
Study Gene Expression

Water resources and urban flood management require hydrologic and hydraulic modeling. However, incomplete precipitation data is often the issue during hydrological modeling exercise. In this study, gene expression programming (GEP) was utilised to correlate monthly precipitation data from a principal station with its neighbouring station located in Alor Setar, Kedah, Malaysia. GEP is an extension to genetic programming (GP), and can provide simple and efficient solution. The study illustrates the applications of GEP to determine the most suitable rainfall station to replace the principal rainfall station (station 6103047). This is to ensure that a reliable rainfall station can be made if the principal station malfunctioned. These were done by comparing principal station data with each individual neighbouring station. Result of the analysis reveals that the station 38 is the most compatible to the principal station where the value of R2 is 0.886.

scholarly journals The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai

2021 ◽  
Author(s):  
Kepeng Xu ◽  
Jiayi Fang ◽  
Yongqiang Fang ◽  
Qinke Sun ◽  
Chengbo Wu ◽  
...  
Keyword(s):  
Open Access ◽  
Critical Role ◽  
Flood Management ◽  
Hydraulic Modeling ◽  
Flood Mapping ◽  
Flood Inundation ◽  
Flood Simulation ◽  
Urban Flood ◽  
Digital Elevation ◽  
Flood Inundation Mapping

AbstractDigital Elevation Models (DEMs) play a critical role in hydrologic and hydraulic modeling. Flood inundation mapping is highly dependent on the accuracy of DEMs. Various vertical differences exist among open access DEMs as they use various observation satellites and algorithms. The problem is particularly acute in small, flat coastal cities. Thus, it is necessary to assess the differences of the input of DEMs in flood simulation and to reduce anomalous errors of DEMs. In this study, we first conducted urban flood simulation in the Huangpu River Basin in Shanghai by using the LISFLOOD-FP hydrodynamic model and six open-access DEMs (SRTM, MERIT, CoastalDEM, GDEM, NASADEM, and AW3D30), and analyzed the differences in the results of the flood inundation simulations. Then, we processed the DEMs by using two statistically based methods and compared the results with those using the original DEMs. The results show that: (1) the flood inundation mappings using the six original DEMs are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood management; and (2) the accuracy of a DEM corrected by the Dixon criterion for predicting inundation extent is improved, in addition to reducing errors in extreme water depths—this indicates that the corrected datasets have some performance improvement in the accuracy of flood simulation. A freely available, accurate, high-resolution DEM is needed to support robust flood mapping. Flood-related researchers, practitioners, and other stakeholders should pay attention to the uncertainty caused by DEM quality.

scholarly journals ANALYSIS OF TREND OF THE PRECIPITATION DATA: A CASE STUDY OF KANGRA DISTRICT, HIMACHAL PRADESH

2015 ◽  
Vol 3 (9) ◽  
pp. 87-95
Author(s):  
Arijit Ganguly ◽  
Ranjana Ray Chaudhuri ◽  
Prateek Sharma
Keyword(s):  
Flood Control ◽  
Rain Gauge ◽  
Himachal Pradesh ◽  
Flood Frequency ◽  
Negative Trend ◽  
Annual Rainfall ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Level Of Significance

The current study is carried out to determine the potential trend of rainfall and assess its significance in Kangra district of Himachal Pradesh. Rainfall is a key characteristic of any watershed which plays a significant role in flood frequency, flood control studies and water planning and management. In this case study,mean monthly rainfall has been analysed to determine the variability in magnitude over the period 1950-2005.  Trend in mean monthly precipitation data and mean seasonal trends are analysed using Mann-Kendall test and Sen’s slope estimation for the data period 1950-2005. Analysis of monthly trend in precipitation shows negative trend for the months of July, August, September and October in all the rain gauge stations. However, the falling trend is significant for the month of August for Dharamshala(0.05 level of significance). Interestingly the month of June shows rising trend of rainfall in all the stations, however, at Dharamshala the trend is significant (0.01 level of significance). The winter rainfall in the month of January and February record decreasing trend, with DeraGobipur and Kangra recording significant decreasing trend for the month of January at 0.01 level of significance and 0.05 level of significance respectively. Trend analysis for annual rainfall data shows significant negative trend for Dharamshala.

scholarly journals Investigation of impact of climate change on small catchments using different climate models and statistical approaches

2021 ◽  
Author(s):  
A. Guven ◽  
A. Pala ◽  
M. Sheikhvaisi
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Gene Expression Programming ◽  
Monthly Precipitation ◽  
Global Circulation Models ◽  
Systems Model

Abstract The use of a statistical downscaling technique is needed to investigate the hydrological consequences of climate change on the local hydropower capacity. Global Circulation Models (GCMs) are crucial tools used in various simulations for potential climate change effects, including precipitation and temperature. Statistical downscaling methods comprise the improvement of relations between the large-scale climatic parameters and the local variables. This study presents the trend analysis of the observed variables compared to the statistically downscaled emission scenarios that are adopted from the Canadian Second Generation Earth Systems Model (CanESM2) in the basin of Göksu River which is located in Turkey. The key purpose of the research is to evaluate both the predicted monthly precipitation and the projections of GCMs within the three simulated scenarios of RCP2.6, RCP4.5, and RCP8.5 by Gene Expression Programming (GEP). In addition, the findings of statistical downscaling of monthly mean precipitation will be compared to the Linear Regression model (LR). The R-value is 0.827 and 0.755 for precipitation of the GEP model for the periods of calibrating and validation. In comparison with the LR model for the validation and calibration periods (1971–2005), the results of the GEP model prove its applicability in projecting the data of the monthly mean rainfall. Generally, in the simulated periods of 2021–2100, the mentioned scenarios forecast a decline in the monthly mean precipitation in the basin. Moreover, the scenario of RCP8.5 projects more suitably for the case study than expected under the scenarios of the RCP4.5 and RCP2.6. The mean statistically downscaled CanESM2 model was compared with the trend analysis of the areal mean precipitation (PM) over the case study area, and the trend was shown decreasing. However, the RCP 8.5 scenario has the more quasi-asymptotic for trend.

scholarly journals Determination Towards Decision of Public Response in Flood Situation: Case Study in Urban Flood Prone Area in Central Region in Thailand

2014 ◽  
pp. 77-94 ◽  
Author(s):  
I-soon Raungratanaamporn
Keyword(s):  
Disaster Management ◽  
Urban Areas ◽  
Public Involvement ◽  
Flood Management ◽  
Response Effort ◽  
Community Members ◽  
Management Activity ◽  
Urban Flood ◽  
Factors Influencing

Public involvement has become a crucial part in increasing the efficiency of disaster management activities nowadays. In particular, collaboration between civil society and municipalities emerge in disaster situations because uncertainties in personal perception compel them to do so more than their own willingness to involved in disaster management activity. Since this appears to have occurred as a response to the 2011 flood situation in Thailand, the question is how a successful was this collaboration? The aim of this research is to identify factors influencing people’s involvement in disaster management activity. The two study objectivesare as follows: (1) to elucidate the characteristics of flood responses in the selected case study, and (2) to measure the level of involvement of community members in flood-prone urban areas during the flood situation in 2011. This study area is located in PakKretMunicipality, NonthaburiProvince, which is considered as one area that was successful in its flood management efforts during the 2011 flood situation. This research utilized a questionnaire survey, which adopts and extends concepts relevant to willingness to pay for and take part in disaster management activities. Fivefactors were applied to the investigation: (1) Respondents’ information; (2) Decision of respondents to take action, classified by flood inundation level; (3) Perception towards stakeholders in flood management activities; (4) Factors influencing respondents to become involved in flood management activity; and (5) Current preparation and response effort. The study found that external groups such as central and local government, community leaders and members have to take responsibility as first-tier respondents in disaster situations. In the case of collaboration, community members are willing to help government sector as volunteers, and the three most influentialfactors which led community members to become involved in disaster management activity are level of severity, duration of disaster, and expectation to avoid escalation of the situation.

scholarly journals Simulation-optimization framework in urban flood management for historic and climate change scenarios

2021 ◽  
Author(s):  
R. Madhuri ◽  
Y. S. L. Sarath Raja ◽  
K. Srinivasa Raju
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Simulation Optimization ◽  
Flood Management ◽  
Hydraulic Modeling ◽  
Optimization Approach ◽  
Climate Change Scenarios ◽  
Urban Flood ◽  
Optimization Framework ◽  
Runoff Reduction

Abstract A simulation-optimization framework is established by integrating Hydrologic Engineering Center Hydraulic Modeling System (HEC-HMS) for computation of runoff, siting tool EPA System for Urban Storm-water Treatment and Analysis INtegration (EPA-SUSTAIN) for placement of Best Management Practices (BMPs), and Binary Linear Integer Programming (BLIP) for runoff reduction. The framework is applied to an urban catchment, namely Greater Hyderabad Municipal Corporation (GHMC). The rainfall-runoff analysis was conducted for extreme rainfalls for historic (2016) and future events in 2050 and 2064 under Representative Concentration Pathways (RCPs) 6.0 and 8.5. The simulation-optimization approach in the historic scenario yielded 495,607 BMPs occupying 76.99 km2 resulting in runoff reduction of 21.54 mm (198.76–177.22 mm). Achieved runoff reduction is 38.72 (428.35–389.63 mm) and 55.03 (602.65–547.62 mm), respectively, for RCPs 6.0 and 8.5, which could meet the water demands of GHMC for 10.33 and 11.53 days. Impacts of 10 different BMP configurations of varying costs (10–70%) and pollutant load reductions (0–3%) on runoff reduction are accomplished as part of sensitivity analysis.

Urban flood hazard analysis in present and future climate after statistical downscaling: a case study in Ha Tinh city, Vietnam

2021 ◽  
Vol 18 (4) ◽  
pp. 257-274
Author(s):  
T. T. A. Le ◽  
N. T. Lan-Anh ◽  
V. Daskali ◽  
B. Verbist ◽  
K. C. Vu ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
Flood Hazard ◽  
Hazard Analysis ◽  
Future Climate ◽  
Urban Flood

scholarly journals Decision Support for the (Inter-)Basin Management of Water Resources Using Integrated Hydro-Economic Modeling

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Gerald Norbert Souza da Silva ◽  
Márcia Maria Guedes Alcoforado de Moraes
Keyword(s):  
Decision Support ◽  
Water Resources ◽  
Water Allocation ◽  
Hydrological Modeling ◽  
Well Being ◽  
Water Transfer ◽  
Economic Modeling ◽  
Trade Offs ◽  
Study Results

The development of adequate modeling at the basin level to establish public policies has an important role in managing water resources. Hydro-economic models can measure the economic effects of structural and non-structural measures, land and water management, ecosystem services and development needs. Motivated by the need of improving water allocation using economic criteria, in this study, a Spatial Decision Support System (SDSS) with a hydro-economic optimization model (HEAL system) was developed and used for the identification and analysis of an optimal economic allocation of water resources in a case study: the sub-middle basin of the São Francisco River in Brazil. The developed SDSS (HEAL system) made the economically optimum allocation available to analyze water allocation conflicts and trade-offs. With the aim of providing a tool for integrated economic-hydrological modeling, not only for researchers but also for decision-makers and stakeholders, the HEAL system can support decision-making on the design of regulatory and economic management instruments in practice. The case study results showed, for example, that the marginal benefit function obtained for inter-basin water transfer, can contribute for supporting the design of water pricing and water transfer decisions, during periods of water scarcity, for the well-being in both basins.

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