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Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 35962

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Dr. Raffaele Albano

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Guest Editor

School of Engineering, University of Basilicata, Potenza, Italy
Interests: floods; water resource management; soil moisture; hydrology; artificial intelligence; GIS; geomorphic method; DEM; geospatial analysis
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Prof. Dr. Jan Franklin Adamowski

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Guest Editor

Faculty of Agricultural and Environmental Sciences, Department of Bioresource Engineering, McGill University, Montréal, QC H3A 0G4, Canada
Interests: water resources modeling; integrated, collaborative and adaptive water resources management
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Special Issue Information

Dear Colleagues,

This inter-Journal (IJGI/Water) Special Issue seeks to promote new and innovative studies, experiences, and models, in an effort to improve water resources management through the implementation of new algorithms, measurement systems, and Earth observation (EO) data. Challenges posed by contemporary issues such as climate change, population pressure, and increasingly complex social interactions have led to increased usage of geo-information in different phases of water resources management. Real-time access to data and the use of high-resolution spatial information provided by EO-based applications and environmental monitoring techniques have several advantages over traditional fieldwork expeditions. These include safety, the obtention of a synoptic view of the region of interest, data availability extending back several years and, in many cases, cost savings. Fortunately, the advent of new and more powerful sensors (e.g., UAVs, SAR, Lidar, GPS, citizen) provides an opportunity to image, assess, and quantify water resources management more comprehensively than ever before. Concurrently, the power of computers and newly developed algorithms has grown sharply (e.g., machine learning and system dynamic models, image classification and change detection); in particular, the integrated use of recent algorithms and EO monitoring techniques provides scientists and engineers with valuable spatial information to study hydrologic–hydraulic processes operating at different spatiotemporal scales in data-scarce environments. These studies target the monitoring and forecasting of natural risks (e.g., floods, droughts, extreme rainfall events). By providing managers and emergency officials with access to a wealth of time-continuous information for assessment and analysis of small- to large-scale natural hazards around the globe, such studies inform and improve management and emergency responses.

Contributions are solicited that address the challenge of updating and re-inventing the way water resources management and both high resource- and data-intensive processes are carried out. This Special Issue is dedicated to multi(cross/inter/trans)-disciplinary contributions with an operational user-oriented perspective, especially those focused on demonstrating the benefits of drawing upon geo-information data and models and EO sensors for water resources management.

You may choose our Joint Special Issue in Water.

Dr. Raffaele Albano
Prof. Dr. Jan Franklin Adamowski
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

geospatial information
remote sensing
citizen science
risk management
machine learning
environmental monitoring
floods prediction
Earth observation system
UAV
SAR
dynamic WebGIS
hydrological and hydraulic modeling
upscaling and downscaling
change detection
2D and 3D mapping
disaster relief and recovery

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Published Papers (9 papers)

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Research

21 pages, 3391 KiB

Open AccessArticle

Assessment of Surface Water Availability under Climate Change Using Coupled SWAT-WEAP in Hongshui River Basin, China

by Muhammad Touseef, Lihua Chen and Wenzhe Yang

ISPRS Int. J. Geo-Inf. 2021, 10(5), 298; https://doi.org/10.3390/ijgi10050298 - 5 May 2021

Cited by 17 | Viewed by 4770

Abstract

Climate change adversely affects the hydrological cycle at the basin level. This study integrated two models, the Soil and Water Assessment Tool (SWAT) for future climate prediction, and Water Evaluation and Planning (WEAP) for the simulation of water quantity in the Hongshui River Basin (HRB), to evaluate the impacts of climate change, which plays a significant role in the lives of inhabitants downstream of the basin. Downscaled monthly rainfalls and temperatures under four Representative Concentration Pathways (RCPs) emission scenarios from five global circulation models (GCMs) were used to generate streamflow using the SWAT model. Streamflow data (1991–2001) were used to calibrate and validate, with the period of 1991–1997 used for calibration and that of 1998–2001 used for validation. Six scenarios were established to evaluate the response of the basin under socio-economic scenarios. The simulated results show that precipitation and streamflow would likely undergo a slight increase. The available water resources would be sufficient to meet the existing needs until 2050. The results indicated that no water shortages exist under socio-economic, low, and medium climate change emission scenarios, however the basin will experience a water shortage under the high climate change emission scenario (RCP-8.5). The study proposed that, to ensure the sustainability of water resources, better long-term management policies are required to be implemented in the basin and to meet future downstream water needs. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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26 pages, 46431 KiB

Open AccessArticle

A Framework of Dam-Break Hazard Risk Mapping for a Data-Sparse Region in Indonesia

by Doddi Yudianto, Bobby Minola Ginting, Stephen Sanjaya, Steven Reinaldo Rusli and Albert Wicaksono

ISPRS Int. J. Geo-Inf. 2021, 10(3), 110; https://doi.org/10.3390/ijgi10030110 - 26 Feb 2021

Cited by 14 | Viewed by 3948

Abstract

This paper introduces a new simple approach for dam-break hazard mapping in a data-sparse region. A hypothetical breaching case of an earthen dam, i.e., the Ketro Dam in Central Java, (Indonesia) was considered. Open-access hydrological databases, i.e., TRMM and CHIRPS, were collected and compared with the rainfall ground station data to ensure data quality. Additionally, the 3-h rainfall distribution of the TRMM database was employed and validated with the measured data to establish the 24-h rainfall distribution of the probable maximum precipitation. The probable maximum flood discharge was computed with the SCS method, and the reservoir routing computation was conducted to determine the possible breaching mechanisms. The result shows that the Ketro Dam proves safe against overtopping, and thus only the piping mechanism has been taken into consideration. Using the breaching hydrograph, the open-access Digital Elevation Model MERIT Hydro, and the high-performance shallow water model NUFSAW2D, the flood propagation to the downstream part of the dam was simulated, enabling fast computations for different scenarios. The quantification of the susceptibility rate of urban areas was eased with overlay analysis utilizing InaSAFE, a plugin for the QGIS model. This study shows that even for a data-sparse region, the recent open-access databases in terms of hydrological and hydraulic aspects may be used to generate a dam-break hazard map. This will benefit the related stakeholders to take proper action to reduce the loss of life. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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17 pages, 4025 KiB

Open AccessArticle

Urban Coastal Flood-Prone Mapping under the Combined Impact of Tidal Wave and Heavy Rainfall: A Proposal to the Existing National Standard

by Dewayany Sutrisno, Ati Rahadiati, Aninda W. Rudiastuti, Ratna Sari Dewi and Munawaroh

ISPRS Int. J. Geo-Inf. 2020, 9(9), 525; https://doi.org/10.3390/ijgi9090525 - 1 Sep 2020

Cited by 12 | Viewed by 3902

Abstract

The drivers for coastal flooding may vary from extremely high intensity and persistent rainfall, morphological factors of the coastal area, to extreme waves from the ocean. This means that the flood vulnerability of a coastal area does not solely depend on a single driver but can be a combination with others. A national standard for coastal flooding based on rainfall drivers has been developed. As an evaluation, this study aimed to develop a method for coastal flood-prone mapping by combining rainfall with tidal waves. The steps included the assessment of the coastal flood-prone areas driven by rainfall (CFR) and the coastal flood-prone areas by combined drivers (CFC), which was developed by employing the analytic hierarchy process (AHP), spatial-overlaid, weighted-scored, and logical tests. The coastal area of Mataram City on the Island of Lombok in Indonesia was selected as the study area, since it is frequently affected by flooding. The findings determined the essentiality of the CFC method for identifying flood vulnerability areas. Thus, the minimum standard for CFC parameters can be defined with climatic and land characteristic factors. Further, the findings also identified the need for expert judgment in the development of the CFC weighted score-based method. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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19 pages, 4024 KiB

Open AccessArticle

Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology

by Iguniwari Thomas Ekeu-wei and George Alan Blackburn

ISPRS Int. J. Geo-Inf. 2020, 9(9), 512; https://doi.org/10.3390/ijgi9090512 - 25 Aug 2020

Cited by 11 | Viewed by 4645

Abstract

Consistent data are seldom available for whole-catchment flood modelling in many developing regions, hence this study aimed to explore an integrated approach for flood modelling and mapping by combining available segmented hydrographic, topographic, floodplain roughness, calibration, and validation datasets using a two-dimensional Caesar-Lisflood hydrodynamic model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria. Available segments of remotely-sensed and in situ datasets (including hydrological, altimetry, digital elevation model, bathymetry, aerial photo, optical imagery, and radar imagery data) available to different degrees in the Niger-South hydrological area were systematically integrated to draw maximum benefits from all available data. Retrospective modelling, calibration, and validation were undertaken for the whole Niger- South hydrological catchment area of Nigeria, and then these data were segmented into sub-domains for re-validation to understand how data variability and uncertainties impact the accuracy of model outcomes. Furthermore, aerial photos were applied for the first time in the study area for flood model validation and for understanding how different physio-environmental properties influenced the synthetic aperture radar flood delineation capacity in the Niger Delta region of Nigeria. This study demonstrates how the complementary strengths of open, readily available geospatial datasets and tools can be leveraged to model and map flooding within acceptable levels of uncertainty for flood risk management. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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12 pages, 4252 KiB

Open AccessArticle

Assessing the Spatial Pattern of Irrigation Demand under Climate Change in Arid Area

by Liping Wang, Shufang Wang, Liudong Zhang, Mohamed Khaled Salahou, Xiyun Jiao and Honghui Sang

ISPRS Int. J. Geo-Inf. 2020, 9(9), 506; https://doi.org/10.3390/ijgi9090506 - 23 Aug 2020

Cited by 5 | Viewed by 2357

Abstract

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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23 pages, 4272 KiB

Open AccessArticle

Spatiotemporal Assessment of Irrigation Performance of the Kou Valley Irrigation Scheme in Burkina Faso Using Satellite Remote Sensing-Derived Indicators

by Alidou Sawadogo, Louis Kouadio, Farid Traoré, Sander J. Zwart, Tim Hessels and Kemal Sulhi Gündoğdu

ISPRS Int. J. Geo-Inf. 2020, 9(8), 484; https://doi.org/10.3390/ijgi9080484 - 11 Aug 2020

Cited by 15 | Viewed by 5253

Abstract

Traditional methods based on field campaigns are generally used to assess the performance of irrigation schemes in Burkina Faso, resulting in labor-intensive, time-consuming, and costly processes. Despite their extensive application for such performance assessment, remote sensing (RS)-based approaches remain very much underutilized in Burkina Faso. Using multi-temporal Landsat images within the Python module for the Surface Energy Balance Algorithm for Land model, we investigated the spatiotemporal performance patterns of the Kou Valley irrigation scheme (KVIS) during two consecutive cropping seasons. Four performance indicators (depleted fraction, relative evapotranspiration, uniformity of water consumption, and crop water productivity) for rice, maize, and sweet potato were calculated and compared against standard values. Overall, the performance of the KVIS varied depending on year, crop, and the crop’s geographical position in the irrigation scheme. A gradient of spatially varied relative evapotranspiration was observed across the scheme, with the uniformity of water consumption being fair to good. Although rice was the most cultivated, a shift to more sweet potato farming could be adopted to benefit more from irrigation, given the relatively good performance achieved by this crop. Our findings ascertain the potential of such RS-based cost-effective methodologies to serve as basis for improved irrigation water management in decision support tools. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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18 pages, 8152 KiB

Open AccessArticle

Spatio-Temporal Visualization Method for Urban Waterlogging Warning Based on Dynamic Grading

by Jingyi Zhou, Jie Shen, Kaiyue Zang, Xiao Shi, Yixian Du and Petr Šilhák

ISPRS Int. J. Geo-Inf. 2020, 9(8), 471; https://doi.org/10.3390/ijgi9080471 - 27 Jul 2020

Cited by 5 | Viewed by 3199

Abstract

With the acceleration of the urbanization process, the problems caused by extreme weather such as heavy rainstorm events have become more and more serious. During such events, the road and its auxiliary facilities may be damaged in the process of the rainstorm and waterlogging, resulting in the decline of its traffic capacity. Rainfall is a continuous process in a space–time dimension, and as rainfall data are obtained through discrete monitoring stations, the acquired rainfall data have discrete characteristics of time interval and space. In order to facilitate users in understanding the impact of urban waterlogging on traffic, the visualization of waterlogging information needs to be displayed under different spatial and temporal granularity. Therefore, the appropriateness of the visualization granularity directly affects the user’s cognition of the road waterlogging map. To solve this problem, this paper established a spatial granularity and temporal granularity computing quantitative model for spatio-temporal visualization of road waterlogging and the evaluation method of the model was based on the cognition experiment. The minimum visualization unit of the road section is 50 m and we proposed a 5-level depth grading method and two color schemes for road waterlogging visualization based on the user’s cognition. To verify the feasibility of the method, we developed a prototype system and implemented a dynamic spatio-temporal visualization of the waterlogging process in the main urban area of Nanjing, China. The user cognition experiment showed that most participants thought that the segmentation of road was helpful to the local visual expression of waterlogging, and the color schemes of waterlogging depth were also helpful to display the road waterlogging information more effectively. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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15 pages, 3539 KiB

Open AccessEditor’s ChoiceArticle

Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds

by Krzysztof Bakuła, Magdalena Pilarska, Adam Salach and Zdzisław Kurczyński

ISPRS Int. J. Geo-Inf. 2020, 9(4), 248; https://doi.org/10.3390/ijgi9040248 - 17 Apr 2020

Cited by 13 | Viewed by 3189

Abstract

This paper presents a methodology for levee damage detection based on Unmanned Aerial System (UAS) data. In this experiment, the data were acquired from the UAS platform, which was equipped with a laser scanner and a digital RGB (Red, Green, Blue) camera. Airborne laser scanning (ALS) point clouds were used for the generation of the Digital Terrain Model (DTM), and images were used to produce the RGB orthophoto. The main aim of the paper was to present a methodology based on ALS and vegetation index from RGB orthophoto which helps in finding potential places of levee failure. Both types of multi-temporal data collected from the UAS platform are applied separately: elevation and optical data. Two DTM models from different time periods were compared: the first one was generated from the ALS point cloud and the second DTM was delivered from the UAS Laser Scanning (ULS) data. Archival and new orthophotos were converted to Green-Red Vegetation Index (GRVI) raster datasets. From the GRVI raster, change detection for unvegetation ground areas was analysed using a dynamically indicated threshold. The result of this approach is the localisation of places, for which the change in height correlates with the appearance of unvegetation ground. This simple, automatic method provides a tool for specialist monitoring of levees, the critical objects protecting against floods. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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29 pages, 18680 KiB

Open AccessArticle

The Measurement of Mobility-Based Accessibility—The Impact of Floods on Trips of Various Length and Motivation

by Marta Borowska-Stefańska, Michał Kowalski and Szymon Wiśniewski

ISPRS Int. J. Geo-Inf. 2019, 8(12), 534; https://doi.org/10.3390/ijgi8120534 - 27 Nov 2019

Cited by 12 | Viewed by 3522

Abstract

The main purpose of this article was to develop a method of researching accessibility in the event of a flood through the application of measurement based on mobility. In the course of the research, it has been proven that changes in mobility (and the related travel speed) are too significant to be ignored when studying accessibility in unusual circumstances. The vast majority of existing accessibility studies rely primarily on speed models, which – in the event of a flood – do not indicate the external effects of the natural disaster. On the basis of the conducted research it has been stated that the occurrence of a flood has a significant impact on changes in the spatial distribution of traffic and its related speeds. Such changes vary depending on the particular means of transport. With the most commonly applied methods of measuring accessibility, which are customarily based on speed models, the changes we observed would not be recorded. The application of mobility-based research in the analyses of accessibility – especially in the event of a flood – indicates the disaster’s influence on the capacity of the road network, and thus, it allows for more effective flood-risk management. Furthermore, this article also demonstrates the possibility of applying source materials available in most member states of the EU, i.e., flood-risk maps and digital terrain models (NMPT), for the purposes of analysing and identifying road section closures within the transport network after the occurrence of a flood. Full article

(This article belongs to the Special Issue Observation-Driven Understanding, Prediction, and Management in Hydrological/Hydraulic Hazard and Risk Studies)

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