Integration of SRTM and TRMM date into the GIS-based hydrological model for the purpose of flood modelling

Abstract

Due to land use and climate changes, more severe and frequent floods occur worldwide. Flood simulation as the first step in flood risk management can be robustly conducted with integration of GIS, RS and flood modeling tools. The primary goal of this research is to examine the practical use of public domain satellite data and GIS-based hydrologic model. Firstly, database development process is described. GIS tools and techniques were used in the light of relevant literature to achieve the appropriate database. Watershed delineation and parameterizations were carried out using cartographic DEM derived from digital topography at a scale of 1:25 000 with 30 m cell size and SRTM elevation data at 30 m cell size. The SRTM elevation dataset is evaluated and compared with cartographic DEM. With the assistance of statistical measures such as Correlation coefficient (<i>r</i>), Nash-Sutcliffe efficiency (NSE), Percent Bias (PBias) or Percent of Error (PE). According to NSE index, SRTM-DEM can be used for watershed delineation and parameterization with 87% similarity with Topo-DEM in a complex and underdeveloped terrains. Primary TRMM (V6) data was used as satellite based hytograph for rainfall-runoff simulation. The SCS-CN approach was used for losses and kinematic routing method employed for hydrograph transformation through the reaches. It is concluded that TRMM estimates do not give adequate information about the storms as it can be drawn from the rain gauges. Event-based flood modeling using HEC-HMS proved that SRTM elevation dataset has the ability to obviate the lack of terrain data for hydrologic modeling where appropriate data for terrain modeling and simulation of hydrological processes is unavailable. However, TRMM precipitation estimates failed to explain the behavior of rainfall events and its resultant peak discharge and time of peak

Distributed-Framework Basin Modeling System: I. Overview and Model Coupling

“…In the 1960s and 1970s, the technologies employed for the geographic information system GIS and professional models of water were developed independently [20]. In the late 1980s, researchers started to work on the integration of GIS and hydrological models to meet the requirement of GIS function analysis [21]. On the other hand, more and more projects and studies began to need precise geographic information [22].…”

“…The development of distributed hydrological models is becoming increasingly dependent on GIS. There are four different ways to integrate hydrological models and GIS [21]: (a) embedding GIS in the hydrological model, such as RiverCAD, HEC-RAS (version 5.0.4 and later), RiverTools, and MODFLOW; (b) embedding the hydrological model in GIS, such as ArcGIRD and Arc Hydro from ESRI, Redlands, CA, USA; (c) a loosely coupled model that is integrated using independent software; and (d) a tightly coupled model with GIS and a hydrological model with a customized unified interface achieved by combining functions of different software. However, all these integrations are only technology-driven, that is to say, the integrations result from coupling based on the data form, not the internal structure.…”

Remapping annual precipitation in mountainous areas based on vegetation patterns: a case study in the Nu River basin

“…Recently, remote-sensing-based precipitation (RSBP) products, such as the Global Precipitation Climatology Project (GPCP) (Schamm et al, 2014), the Tropical Rainfall Measuring Mission (TRMM) (Council, 2005), and the Climate Prediction Center Morphing Method (CMORPH) (Joyce et al, 2004), have been extensively used in ungauged or sparsely gauged areas to bridge the gap between the need for precipitation estimates and the scarcity in gauge observations (Akbari et al, 2012;Kneis et al, 2014;Li et al, 2015;Worqlul et al, 2015;Mourre et al, 2016;Wong et al, 2016). Also, data fusion across satellite and gauge observations is being conducted to further the application of RSBPs (Rozante et al, 2010;Woldemeskel et al, 2013;AriasHidalgo et al, 2013;Zhou et al, 2016).…”

Remapping precipitation in mountainous area based on vegetation pattern

“…Recently, remote-sensing-based precipitation (RSBP) products, such as the Global Precipitation Climatology Project (GPCP) (Schamm et al, 2014), the Tropical Rainfall Measuring Mission (TRMM) (Council, 2005), and the Climate Prediction Center Morphing Method (CMORPH) (Joyce et al, 2004), have been extensively used in ungauged or sparsely gauged areas to bridge the gap between the need for precipitation estimates and the scarcity in gauge observations (Akbari et al, 2012;Kneis et al, 2014;Li et al, 2015;Worqlul et al, 2015;Mourre et al, 2016;Wong et al, 2016). Also, data fusion across satellite and gauge observations is being conducted to further the application of RS-BPs (Rozante et al, 2010;Woldemeskel et al, 2013;Arias-Hidalgo et al, 2013;Zhou et al, 2016). However, due to the relatively coarse spatial resolution (e.g., 0.25-5 • ) and uncertainties of RSBPs, their applications in mountainous basins, where the precipitation shows large spatial variability, are still very limited (Krakauer et al, 2013;.…”