Calibrating and validating an inundation model with and without crowdsourced water depths and velocities

<p>Remote sensing and crowdsourcing data are new sensing methods that have the potential to improve significantly inundation modelling. That is especially true in data-scarce situations, for example when resources for acquiring sufficient traditional data are limited or when field conditions are not favourable. Crowdsourced water depths and velocities have been demonstrated to be useful for improving inundation models, ranging from the calibration of 1D models to data assimilation in 2D models. In this study, we aim to further evaluate how much the amount and type of crowdsourced data influence model calibration and validation, in comparison with data from traditional measurements. Further, we aim to assess the effects of combining both sources. For that, we developed a 2D inundation model of the Sontea-Fortuna area, a part of the Danube Delta in Romania. This is a wetland area, where data was collected during two 4-day field campaigns, using boat navigation together with the involved citizens. Citizens obtained thousands of images and videos that were converted into water depth and velocity data, while technicians collected ADCP data. We calibrated and validated the model using different combinations of data (e.g. all water depth data, half water depth and half water velocity). Results indicated that velocity data by themselves did not yield good calibration results, being better used in conjunction with water depths or by combining them into discharge. We also observed that calibration by crowdsourced water depths is comparable to the use of water depths from traditional measurements.</p>

A fully coupled spatially distributed hydrologic-hydrodynamic model for the Barotse Floodplain, Upper Zambezi

<p>Floodplains play important roles in global hydrological and biogeochemical cycles, and many socioeconomic activities also depend on water resources in floodplains. Although considered as critical for the formation and preservation of floodplains, hydrology in floodplains has been hard to characterise. In recent years the demand for an understanding of the hydrological and hydrodynamic processes for the Barotse floodplains is ever increasing especially with the advent of climate change/variability, and expected upstream developments. Yet, the multi-way interactions between river flows, wetland inundation, and groundwater are complex, and poorly understood, compromising studying these changes. Most hydrological and hydrodynamic models applied for large-scale hydrological and inundation modelling lack an advanced floodplain-groundwater feedback mechanism, and thus may over predict or under predict inundation extent, depth, and downstream river flow. This is because groundwater re-infiltration and evaporation from the floodplains over a longer time scale than the flood process are not accounted for.  Hence, the main objective of this current study is to show the very first attempt to a fully coupled model for the Barotse floodplain. The hypothesis is that a fully coupled model will result in larger groundwater dynamics, a slower rise of inundation, and possibly a longer recession tail. To test this hypothesis, we setup two experiments; (i) in the first experiment, WFLOW runs and feeds upstream flows into LISFLOOD. This is sort of the classic approach, and similar to earlier studies, and also does not necessarily require a time-step based coupling; (ii) in the second experiment, WFLOW runs and feeds into Lisflood_FP, and Lisflood_FP then returns water into the WFLOW model. This an experiment where we re-infiltrate water into wflow and by doing so, let groundwater levels adapt so that additional reinfiltrated water, decrease the amount of flood water, increase groundwater levels more during the wet season, and provide a higher recession tail downstream. Our model environment and experiments are available through https://github.com/Innochomba/barotse.</p>

FLOOD MODELLING OF BADENG RIVER USING HEC-RAS IN SINGOJURUH SUB DISTRICT, BANYUWANGI REGENCY, EAST JAVA, INDONESIA

The flood disaster is a severe threat in Indonesia due to the enormous impacts on environmental degradation, social and economic sectors. One flood event due to the overflow is the Badeng River's flooding in 2018 at Singojuruh Subdistrict, Banyuwangi Regency. The flood had a detrimental impact on the local community, especially on agricultural land and residential. Anticipatory steps need to be taken to minimize losses due to flooding in the future. Inundation modelling in this research is purposed to predict flood hazards. Hence it can have appropriate anticipatory steps in the future. The software used to model the inundation in this study was the HEC-RAS Program. Data needed in this study are river geometry, manning coefficient, and maximum daily rainfall from the year 2010 until 2019. The research e stages in this study consist of (1) Calculation of watershed morphometry, (2) Calculation of average regional rainfall, (3) Calculation of rainfall plan, (4) Rain Data Suitability Test, (5) Calculation of Rain Intensity, (6) Calculation of Flood Discharge Plan, (7) Geometry Modelling, (8) Extraction of Manning Coefficient, and (9) Inundation Simulation. The results of the Gama 1 method's peak discharge plan showed an increase in each return period. The area with the highest level of susceptibility around the Badeng River occurs in Alasmalang Village, Singojuruh Subdistrict. This area has the smallest river storage capacity than other river crossings. Hence it has the most significant potential for flooding.Keywords: inundation modelling, flood, HEC-RAS, Badeng RiverBencana banjir menjadi ancaman serius bagi negara Indonesia karena memberikan dampak yang besar terhadap kerusakan lingkungan, sosial maupun ekonomi. Salah satu kejadiannya adalah banjir yang terjadi akibat luapan sungai Badeng pada tahun 2018 di Kecamatan Singojuruh, Kabupaten Banyuwangi. Kejadian Banjir tersebut memberikan dampak yang merugikan bagi masyarakat setempat, terutama pada lahan pertanian dan permukiman. Langkah antisipasi perlu dilakukan untuk meminimalisir kerugian akibat bencana banjir di masa mendatang. Pemodelan genangan dalam penelitian ini dibuat bertujuan untuk memprediksi bahaya banjir, sehingga dapat dilakukan langkah antisipasi yang tepat. Software yang digunakan untuk memodelkan genangan dalam penelitian ini adalah Program HEC-RAS. Data yang dibutuhkan berupa data geometri sungai, koefisien manning dan curah hujan harian maksimum selama periode tahun 2010 sampai 2019. Beberapa tahapan dalam penelitian ini meliputi (1) Perhitungan morfometri DAS, (2) Perhitungan hujan rerata wilayah, (3) Perhitungan curah hujan rencana, (4) Uji Kesesuaian Data Hujan, (5) Perhitungan Intensitas Hujan, (6) Perhitungan Debit banjir rencana, (7) Pemodelan geometri, (8) Ekstraksi angka kekasaran manning, dan (9) Simulasi Genangan. Hasil perhitungan debit puncak rencana metode Gama 1 menunjukkan peningkatan pada setiap periode ulang. Daerah yang mempunyai tingkat kerawanan paling besar adalah areal sekitar Sungai Badeng yang berada di Desa Alasmalang Kecamatan Singojuruh. Daerah ini memiliki kapasitas tampung sungai yang paling kecil daripada penampang sungai yang lainnya, sehingga memiliki potensi terjadinya banjir paling besar. Kata kunci: pemodelan genangan, banjir, HEC-RAS, Sungai Badeng

A rapid flood inundation model in the floodplain area due to an extreme rainfall event

Extreme rainfall in East Jakarta on February 19, 2021 caused flooding in a number of subdistricts. The research was conducted in the central part of Kali Sunter, which flows through three subdistricts, namely Cipinang Melayu, Cipinang Muara, and Pondok Bambu. The purpose of the study was to do flood hazard modeling and analyze the characteristics of flood-affected areas based on land use and topography. Inundation and flood hazard maps is done by: calculating the flood discharge using the SCS-CN method, flood inundation modelling using HEC-RAS, and analyzing the characteristics of the inundated area. This combination is effective for rapid modeling during extreme rainfall events. Based on the research, the distribution of the highest flood hazard area is in RW 004 Cipinang Melayu, with the widest inundation affecting small and medium-sized houses. The characteristics of the affected area are that there is green and empty land which reduces the potential for water to inundate buildings or other land uses. Buildings located in low-hazard housing areas tend to be more organized and relatively medium to large in size. While the types of housing in the Cipinang Melayu with a high level of danger tend to be dense and small to medium in size, but the majority have two floors as a form of flood adaptation.

Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations

Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval. PTHA provides scientific guidance for tsunami risk analysis and risk management, including coastal planning and early warning. Explicit computation of site-specific PTHA, with an adequate discretization of source scenarios combined with high-resolution numerical inundation modelling, has been out of reach with existing models and computing capabilities, with tens to hundreds of thousands of moderately intensive numerical simulations being required for exhaustive uncertainty quantification. In recent years, more efficient GPU-based High-Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have now made local long-term hazard assessment feasible. A workflow has been developed with three main stages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundation simulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunami propagation and inundation model using a system of nested topo-bathymetric grids, and 3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, for tsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of the PTHA as implemented for High-Performance Computing applications, including preliminary simulations carried out on intermediate scale GPU clusters. We show how the local hazard analysis conducted here produces a more fine-grained assessment than is possible with a regional assessment. However, the new local PTHA indicates somewhat lower probabilities of exceedance for higher maximum inundation heights than the available regional PTHA. The local hazard analysis takes into account small-scale tsunami inundation features and non-linearity which the regional-scale assessment does not incorporate. However, the deterministic inundation simulations neglect some uncertainties stemming from the simplified source treatment and tsunami modelling that are embedded in the regional stochastic approach to inundation height estimation. Further research is needed to quantify the uncertainty associated with numerical inundation modelling and to properly propagate it onto the hazard results, to fully exploit the potential of site-specific hazard assessment based on massive simulations.