Application of remote sensing and geographical information systems in flood management : a review

Floods are one of the most widely distributed hazards around the world and their management is an important issue of concern among all the stakeholders. The aim of this review is to synthesize the state of art literature in the application of Geographical Information Systems (GIS) and Remote Sensing (RS) techniques in all the flood management stages (pre-flood, during flood and post-flood stages). Flood types and common concepts in flood management are precisely explained. Case studies of flood management using GIS and RS are summarized. Current challenges in using GIS and RS techniques for flood management are also given. One lesson we learn from this review is that flood management is very diverse and it requires multidisciplinary involvement. It can also be deduced that RS techniques offer cheaper and faster options of accessing spatial data about the flood event even in the physically inaccessible areas. GIS techniques on the other hand facilitate hydrological models in data collection, analysis, querying and presentation of information in a more simplified format. The present review is expected to contribute to an improved understanding of the potential applications of RS and GIS techniques in flood management, especially among scientists in the developing countries where the use of these techniques particularly in flood management has generally been limited

Applied Hydrological Modeling with the Use of Geoinformatics: Theory and Practice

Water resource management and catchment analysis are crucial aspects of the twenty-first century in hydrological and environmental sciences. Linked directly with studies and research about climate change effects in global resources (e.g., diminution of rainfall dynamic), as well as continuously growing extreme natural phenomena with catastrophic results (e.g., floods and erosion), hydrological modeling has become a key priority in modern academic research goals. On a national or lower administrative level, the need for coping with natural disasters—affecting mainly human life, property, local economy, infrastructure, etc.—and the need to design management plans and projects for sustainable exploitation of natural resources set hydrological modeling in high demand by government organizations and local authorities. Thus, hazard assessment and risk evaluation modeling have become a strategic aim and an extremely useful tool for stakeholders, decision-makers, and scientific community

Modelling in ungauged catchments using PyTOPKAPI : a case study of Mhlanga catchment.

Masters Degree. University of KwaZulu-Natal, Durban.Hydrological modeling of rainfall-runoff processes is a powerful tool used in various water resources applications, including the simulation of water yield from ungauged catchments. Many rivers in developing countries are poorly gauged or fully ungauged. This gives rise to a challenge in the calibration and validation of hydrological models. This study investigated the applicability of PyTOPKAPI, a physically based distributed hydrological model, in simulating runoff in ungauged catchments, using the Mhlanga River as a case study. This study is the first application of the PyTOPKAPI model to simulate daily runoff on an ungauged catchment in South Africa. The PyTOPKAPI model was parameterised using globally available digital elevation data (DEM), satellite-derived land cover, soil type data and processed hydro-meteorological data collected from various sources. Historical 30-year (1980-2009) quaternary monthly streamflow (from a well-tested and calibrated model) and daily meteorological variables (rainfall, temperature, humidity and so on) were obtained. The rainfall data were subjected to double mass curve test to check for consistency. The monthly streamflow was transposed to the catchment and disaggregated to daily streamflow time step. The PyTOPKAPI model was calibrated using an average runoff ratio as an alternative to matching streamflow data that is usually used for model calibrations. The simulated results were thereafter compared with the disaggregated monthly quaternary data. The model results show good overall performance when compared with the average runoff ratio, monthly disaggregated streamflow and the expected mean annual runoff in the catchment. In general, PyTOPKAPI can be used to predict runoff response in ungauged catchments, and thus may be adopted for water resources management applications

Benefits of GIS Application in Hydrological Modeling: A Brief Summary

During recent years, Geographic Information Systems (GIS) as a powerful tool have had a tremendous impact on research techniques in the realm of geography and spatial analysis. The integrative ability of GIS to capture, store, manipulate, analyze, manage, and finally present all types of geographical spatial data, has drawn many attentions to it. Water Resources Engineering as a interdisciplinary field requires modeling and analyzing data with different spatial resolutions. Therefore, GIS could definitely be utilized as a suitable tool for solving water resources problems from local to global scale. This paper tries to present the larger scheme of the benefits for the applications of GIS in water resources and hydrological modeling in particular. Certainly, within the few pages ahead only the surface is scratched and a more thorough and comprehensive review requires more time and effort. The fundamental reason for the need of integrating GIS and hydrological modeling is briefly discussed and different tools are introduced. Also, various examples of GIS application are presented to create a better understanding. Case studies such as the Wadi Madoneh Basin in Jordan, Kuronagi River in Japan and San Antonio River Basin in Central Texas, USA, are presented. The good agreement between the results from a fairly simple GIS model and observations in cases such as Kuronagi River and Wadi Madoneh is indicating a promising future for GIS application in hydrological modeling. Finally, the benefits of GIS utilization in the field are discussed and summarized

TWINLATIN: Twinning European and Latin-American river basins for research enabling sustainable water resources management. Combined Report D3.1 Hydrological modelling report and D3.2 Evaluation report

Water use has almost tripled over the past 50 years and in some regions the water demand already exceeds supply (Vorosmarty et al., 2000). The world is facing a “global water crisis”; in many countries, current levels of water use are unsustainable, with systems vulnerable to collapse from even small changes in water availability. The need for a scientifically-based assessment of the potential impacts on water resources of future changes, as a basis for society to adapt to such changes, is strong for most parts of the world. Although the focus of such assessments has tended to be climate change, socio-economic changes can have as significant an impact on water availability across the four main use sectors i.e. domestic, agricultural, industrial (including energy) and environmental. Withdrawal and consumption of water is expected to continue to grow substantially over the next 20-50 years (Cosgrove & Rijsberman, 2002), and consequent changes in availability may drastically affect society and economies. One of the most needed improvements in Latin American river basin management is a higher level of detail in hydrological modelling and erosion risk assessment, as a basis for identification and analysis of mitigation actions, as well as for analysis of global change scenarios. Flow measurements are too costly to be realised at more than a few locations, which means that modelled data are required for the rest of the basin. Hence, TWINLATIN Work Package 3 “Hydrological modelling and extremes” was formulated to provide methods and tools to be used by other WPs, in particular WP6 on “Pollution pressure and impact analysis” and WP8 on “Change effects and vulnerability assessment”. With an emphasis on high and low flows and their impacts, WP3 was originally called “Hydrological modelling, flooding, erosion, water scarcity and water abstraction”. However, at the TWINLATIN kick-off meeting it was agreed that some of these issues resided more appropriately in WP6 and WP8, and so WP3 was renamed to focus on hydrological modelling and hydrological extremes. The specific objectives of WP3 as set out in the Description of Work are

Potential of Spaceborne X & L-Band SAR-Data for Soil Moisture Mapping Using GIS and its Application to Hydrological Modelling: the Example of Gottleuba Catchment, Saxony / Germany

Hydrological modelling is a powerful tool for hydrologists and engineers involved in the planning and development of integrated approach for the management of water resources. With the recent advent of computational power and the growing availability of spatial data, RS and GIS technologies can augment to a great extent the conventional methods used in rainfall runoff studies; it is possible to accurately describe watershed characteristics in particularly when determining runoff response to rainfall input. The main objective of this study is to apply the potential of spaceborne SAR data for soil moisture retrieval in order to improve the spatial input parameters required for hydrological modelling. For the spatial database creation, high resolution 2 m aerial laser scanning Digital Terrain Model (DTM), soil map, and landuse map were used. Rainfall records were transformed into a runoff through hydrological parameterisation of the watershed and the river network using HEC-HMS software for rainfall runoff simulation. The Soil Conservation Services Curve Number (SCS-CN) and Soil Moisture Accounting (SMA) loss methods were selected to calculate the infiltration losses. In microwave remote sensing, the study of how the microwave interacts with the earth terrain has always been interesting in interpreting the satellite SAR images. In this research soil moisture was derived from two different types of Spaceborne SAR data; TerraSAR-X and ALOS PALSAR (L band). The developed integrated hydrological model was applied to the test site of the Gottleuba Catchment area which covers approximately 400 sqkm, located south of Pirna (Saxony, Germany). To validate the model historical precipitation data of the past ten years were performed. The validated model was further optimized using the extracted soil moisture from SAR data. The simulation results showed a reasonable match between the simulated and the observed hydrographs. Quantitatively the study concluded that based on SAR data, the model could be used as an expeditious tool of soil moisture mapping which required for hydrological modelling

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

Multimodel combination techniques for analysis of hydrological simulations: Application to distributed model intercomparison project results

This paper examines several multimodel combination techniques that are used for streamflow forecasting: the simple model average (SMA), the multimodel superensemble (MMSE), modified multimodel superensemble (M3SE), and the weighted average method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multimodel combination results were obtained using uncalibrated DMIP model simulations and were compared against the best-uncalibrated as well as the best-calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the accuracy levels of the multimodel simulations. This study revealed that the multimodel simulations obtained from uncalibrated single-model simulations are generally better than any single-member model simulations, even the best-calibrated single-model simulations. Furthermore, more sophisticated multimodel combination techniques that incorporated bias correction step work better than simple multimodel average simulations or multimodel simulations without bias correction. © 2006 American Meteorological Society

Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System

A physical based, distributed hydrological model was developed to route overland flows during isolated HISD storms. The model has operated on a grid or cell basis and routed the excess rainfall over the grids, conforming to the DEM-derived drainage paths, to the basin outlet. The rainfall-runoff hydrological modelling was implemented in MATLAB 7.0. The system has integrated GIS, RS, DEM, data management capability and a dynamic basin model within a common Windows environment. The simulation algorithms of the rainfall-runoff model have operated on grid bases compatible with the MATLAB programming language, which has been used to write instructions to many grid-based operations. Due to the MATLAB architecture, the system has been proven successful for large-scale basin modeling, which requires high level resolution, record keeping and technical transfer. The model has estimated the runoff using the Soil Conservation Service-Curve Numbers (SCS-CN), determined by the land use/ land cover and the hydrological soil group found in each grid. The overland flow mechanics were described by the diffusion wave approximation of St Venant equations, which were numerically solved for depth of flow and runoff by the finite volume method (FVM). The grid cell physical properties such as topography, land use, soil, and Manning’s roughness’ coefficient were extracted from published maps for discretized cells of the Klang River basin(KRB) using a GIS. The land use/cover classes were derived from interpreted information of Landsat TM imagery using the combined object-oriented segmentation - fuzzy logic algorithm. The DEM of 90m resolution, used to calculate slopes that generated runoffs, was derived from radar data sets (C-band) of the Shuttle Radar Topography Mission (SRTM) using the interferometric approach. Four criteria were used for the assessment of the model performance - Model bias, Nash– Sutcliffe and model efficiencies for both low and high flows during both calibration and validation periods. The results showed the advantages of integrating RS, DEM and GIS with hydrologic simulation in generating runoff processes in the spatial domain, attaining as well fairly high precision simulation with the general hydrologic trends well captured by the model. This study has also involved the application of flood modeling, which has integrated the results of the grid-based overland flow routing model into MIKE11 onedimensional hydrodynamic model. The discharge hydrographs were extracted from the grid-based overland flow routing model in ASCII format and imported into MIKE11 hydrodynamic modeling system. The MIKE11 model was developed based on surveyed, stream cross-section data to perform hydrodynamic simulation of the flooding process. The MIKE11 modeling was applied to the Klang River system comprising 9 main tributaries. The analysis has considered the river system with and without Stormwater Management and Road Tunnel (SMART) project, which involve structural flood mitigations measures including retention ponds, bypass tunnel and flow diversions, where the river physical condition was modified accordingly. Hourly data for flow were created into compatible MIKE11 time series in a separate file as input to the parameter editors. Initial and boundary conditions were based on the inputs for MIKE11 operational analysis. It has been found that the modeled predictions of depth and discharge matched observed data. A good agreement between the simulated and observed data was achieved for rating curves with RMSE = 0.96, 0.94, 0.95, and 0.97 at respective calibration points. From the results revealed by the MIKE11 modeling simulation, there were evidences that SMART was useful for flood mitigation of Klang River Basin. For instance at Tun Perak Bridge, the normal level for the Klang River was 25m, the alert level was 28m and the danger level was 29.5m. The value from the simulation showed that the maximum water level without SMART was 32m. However this level with SMART was only 27.8m which did not exceed the alert and danger level at Tun Perak Bridge. This area is the most critical part of KL. Once the water level from the Klang River exceeds the flood wall, the whole KL will be badly flooded. Finally, the results of the runoff modeling were integrated in MIKE-GIS model for flood inundation mapping. A digital planimetric view and topographic mapping of the floodplain was developed using the three-dimensional floodplain visualization approach through the integration of a digital terrain model. This model was synthesized from MIKE11 stream cross-sectional coordinate into a digital surface model, generated from aerial stereo pair photos using Ortho Engine PCI image processing software. The resulting formulated surface model provided a good representation of the general landscape and contained additional details within the stream channel. Integration of 3D-GIS and spatial analytical techniques together with hydrologic and hydraulic modeling processes has enhanced the visualization and display techniques for visual presentation and generation of flood inundation maps for early warning and contingency planning