Spatial Variability in Hydrologic Modeling Using Rainfall-Runoff Model and Digital Elevation Model

2002 ◽  
Vol 7 (6) ◽  
pp. 404-412 ◽  
Author(s):  
H. Sun ◽  
P. S. Cornish ◽  
T. M. Daniell
Keyword(s):  
Spatial Variability ◽  
Digital Elevation Model ◽  
Hydrologic Modeling ◽  
Rainfall Runoff ◽  
Digital Elevation ◽  
Rainfall Runoff Model ◽  
Elevation Model ◽  
Runoff Model

scholarly journals Estimation of synthetic flood design hydrographs using a distributed rainfall–runoff model coupled with a copula-based single storm rainfall generator

2014 ◽  
Vol 14 (7) ◽  
pp. 1819-1833 ◽  
Author(s):  
A. Candela ◽  
G. Brigandì ◽  
G. T. Aronica
Keyword(s):  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Digital Elevation ◽  
Design Hydrographs ◽  
Rainfall Runoff Model ◽  
Storm Rainfall ◽  
Elevation Model ◽  
Runoff Model

Abstract. In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall–runoff model, is presented. Rainfall–runoff modelling (R–R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service – Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R–R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.

scholarly journals Effects of digital elevation model resolution on topography-based runoff simulation under uncertainty

2014 ◽  
Vol 16 (6) ◽  
pp. 1343-1358 ◽  
Author(s):  
L. Cui ◽  
Y. P. Li ◽  
G. H. Huang ◽  
Y. Huang
Keyword(s):  
Water Resources ◽  
Digital Elevation Model ◽  
Water Resources Management ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Resources Management ◽  
Dem Resolution ◽  
Analysis Technique ◽  
Digital Elevation ◽  
Elevation Model

Topography plays a critical role in controlling water dispersion and soil movement in hydrologic modeling for water resources management with raster-based digital elevation model (DEM). This study aims to model effects of DEM resolution on runoff simulation through coupling fuzzy analysis technique with a topography based rainfall–runoff model (TOPMODEL). Different levels of DEM grid sizes between 30 m and 200 m are examined, and the results indicate that 30 m DEM resolution is the best for all catchments. Results demonstrate that the DEM resolution could have significant influence on the TOPMODEL rainfall–runoff simulation. Fuzzy analysis technique is used to further examine the uncertain DEM resolution based on considering Nash, sum of squared error, and sum of absolute error values of TOPMODEL. The developed model is calibrated and validated against observed flow during the period 2010–2012, and generally performed acceptably for model Nash–Sutcliffe value. The proposed method is useful for studying hydrological processes of watershed associated with topography uncertainty and providing support for identifying proper water resources management strategy.

scholarly journals Seamless Integration of Rainfall Spatial Variability and a Conceptual Hydrological Model

2021 ◽  
Vol 13 (6) ◽  
pp. 3588
Author(s):  
Yan Zhou ◽  
Zhongmin Liang ◽  
Binquan Li ◽  
Yixin Huang ◽  
Kai Wang ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Considerable Effect ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Seamless Integration ◽  
Integration Framework ◽  
Average Rainfall ◽  
Important Input ◽  
Rainfall Runoff Model ◽  
Runoff Model

Rainfall is an important input to conceptual hydrological models, and its accuracy would have a considerable effect on that of the model simulations. However, traditional conceptual rainfall-runoff models commonly use catchment-average rainfall as inputs without recognizing its spatial variability. To solve this, a seamless integration framework that couples rainfall spatial variability with a conceptual rainfall-runoff model, named the statistical rainfall-runoff (SRR) model, is built in this study. In the SRR model, the exponential difference distribution (EDD) is proposed to describe the spatial variability of rainfall for traditional rain gauging stations. The EDD is then incorporated into the vertically mixed runoff (VMR) model to estimate the statistical runoff component. Then, the stochastic differential equation is adopted to deal with the flow routing under stochastic inflow. To test the performance, the SRR model is then calibrated and validated in a Chinese catchment. The results indicate that the EDD performs well in describing rainfall spatial variability, and that the SRR model is superior to the Xinanjiang model because it provides more accurate mean simulations. The seamless integration framework considering rainfall spatial variability can help build a more reasonable statistical rainfall-runoff model.

Digital Elevation Hydrological Modelling in a Small Catchment in South Australia

2003 ◽  
Vol 34 (3) ◽  
pp. 161-178
Author(s):  
H. Sun ◽  
P. S. Cornish ◽  
T. M. Daniell
Keyword(s):  
Soil Moisture ◽  
Spatial Data ◽  
South Australia ◽  
Moisture Distribution ◽  
Rainfall Runoff ◽  
Estimation Errors ◽  
Small Catchment ◽  
Digital Elevation ◽  
Rainfall Runoff Model ◽  
Runoff Model

A rainfall runoff model based on a digital elevation model (DEM) was applied to a small catchment in Happy Valley, South Australia to predict catchment storm runoff. The DEM was used to partition the catchment into several thousand irregular shaped elements. These elements, with an average size of 825 m2 each, form an interconnected one-dimensional flow network for runoff routing. The rainfall runoff model is a kinematic flow model which combines the solving of flow continuity equation and the Manning's equation to generate surface and subsurface runoff. This study improves on the existing rainfall runoff model in several areas. It adds spatial rainfall averaging methods to derive spatial rainfalls for catchment modelling; and it improves the catchment soil moisture representation by developing a boundary wetness index, and relates this index to antecedent catchment flow to derive spatial catchment moisture distribution. Improved runoff predictions were obtained as a result of the improvement in spatial data input and spatial soil moisture representation. The study identifies these improvements as the key areas for better runoff prediction. It demonstrates that where prediction results showed larger than expected variance, it is frequently caused by the inability to derive good spatially distributed input data rather than parameter estimation errors.

STUDY OF THE LANDSLIDE MORPHOLOGY BASED ON GNSS DATA AND AIRBORNE SOUNDING (ON THE EXAMPLE OF A SECTION OF THE PROTVA RIVER VALLEY)

2018 ◽  
Vol 12 (5-6) ◽  
pp. 50-57 ◽  
Author(s):  
I. S. Voskresensky ◽  
A. A. Suchilin ◽  
L. A. Ushakova ◽  
V. M. Shaforostov ◽  
A. L. Entin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Geodetic Network ◽  
Aerial Survey ◽  
River Valley ◽  
Ease Of Use ◽  
Digital Elevation ◽  
Loose Deposits ◽  
Positioning Method ◽  
Landslide Body ◽  
Elevation Model

To use unmanned aerial vehicles (UAVs) for obtaining digital elevation models (DEM) and digital terrain models (DTM) is currently actively practiced in scientific and practical purposes. This technology has many advantages: efficiency, ease of use, and the possibility of application on relatively small area. This allows us to perform qualitative and quantitative studies of the progress of dangerous relief-forming processes and to assess their consequences quickly. In this paper, we describe the process of obtaining a digital elevation model (DEM) of the relief of the slope located on the bank of the Protva River (Satino training site of the Faculty of Geography, Lomonosov Moscow State University). To obtain the digital elevation model, we created a temporary geodetic network. The coordinates of the points were measured by the satellite positioning method using a highprecision mobile complex. The aerial survey was carried out using an unmanned aerial vehicle from a low altitude (about 40–45 m). The processing of survey materials was performed via automatic photogrammetry (Structure-from-Motion method), and the digital elevation model of the landslide surface on the Protva River valley section was created. Remote sensing was supplemented by studying archival materials of aerial photography, as well as field survey conducted immediately after the landslide. The total amount of research results made it possible to establish the causes and character of the landslide process on the study site. According to the geomorphological conditions of formation, the landslide refers to a variety of landslideslides, which are formed when water is saturated with loose deposits. The landslide body was formed with the "collapse" of the blocks of turf and deluvial loams and their "destruction" as they shifted and accumulated at the foot of the slope.

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