Evaluating the impact of lower resolutions of digital elevation model on rainfall-runoff modeling for ungauged catchments

Ghumman, Abdul Razzaq; Al-Salamah, Ibrahim Saleh; AlSaleem, Saleem S.; Haider, Husnain

doi:10.1007/s10661-017-5766-0

Cited by 20 publications

(16 citation statements)

References 27 publications

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“…from satellite imagery, such as ASTER and SRTM). In large areas (greater than 100 km 2 ), Ghumman et al (2017) found similar model efficiencies in the accuracy of rainfall-runoff models using both higher (5 or 10 m) and lower (30 and 90 m) DEM resolutions. However, in small areas (less than 1 km 2 ), the extra detail inherent in very high resolution (10 cm) terrestrial data is valuable when running surface models and analysing flood risk values (Sampson et al, 2012).…”

Section: Introductionmentioning

confidence: 55%

“…In agricultural catchments, DEM resolutions must be optimised in order to identify critical source areas of diffuse pollution and to capture any microtopographic features acting as topographic barriers or channels which divert runoff away from the hillslope scale flow direction (Thomas et al, 2017). In large areas (greater than 100 km 2 ), Ghumman et al (2017) found similar model efficiencies in the accuracy of rainfall-runoff models using both higher (5 or 10 m) and lower (30 and 90 m) DEM resolutions. LiDAR at 1 m) to a lower resolution reduces model accuracy much less than the use of low-resolution DEM (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Influence of DEM resolution on modelling hydrological connectivity in a complex agricultural catchment with woody crops

López‐Vicente

Álvarez

2018

Earth Surf Processes Landf

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Digital elevation model (DEM) resolution influences hydrological simulation. However, its influence when modelling hydrological connectivity (HC) in woody crops remains to be seen. We assessed surface topography, microtopography and HC in an agricultural sub‐catchment (27.4 ha) using six photogrammetry‐derived DEMs with 0.03, 0.05, 0.1, 0.2, 0.5 and 1 m cell sizes. Land uses included vineyards, olive groves, cereal fields, and forestry patches. We ran an updated version of Borselli's HC index (IC) using the D‐Infinity approach. We assessed HC in woody crops at high spatial resolution for the first time. After analysing the differences in the contributing area, the flow width, the soil roughness, the convergence index and the IC (normalised and non‐normalised) at different scales (hillslope, land uses and compartments, ephemeral gullies, depositional areas and the sub‐catchment outlet) and accounting for the field vertical components, we propose an optimum DEM resolution (0.2 m) to improve modelling of structural HC in woody crops. The modelled hydrological features at this threshold resolution matched well with the geomorphic features associated with the short‐ and medium‐term patterns of soil redistribution. Higher DEM resolutions, especially at 0.03 and 0.05 m, introduced bias in the input data and the IC computations. Finally, we observed good agreement between the outputs at the lowest resolution, 1 × 1 m, and the long‐term soil redistribution patterns (functional connectivity). Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Influence of DEM resolution on modelling hydrological connectivity in a complex agricultural catchment with woody crops

López‐Vicente

Álvarez

2018

Earth Surf Processes Landf

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“…Accurate streamflow simulation is imperative to the sustainability of water resources. It is exceptionally challenging to implicate the procedure in these simulations due to its nonlinear and multidimensional dynamics [1]. Varied modeling techniques have been utilized to predict the streamflow, such as physically based distributed models [1][2][3], stochastic models [4], lumped conceptual models [5], and black-box models [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Impact Assessment of Rainfall-Runoff Simulations on the Flow Duration Curve of the Upper Indus River—A Comparison of Data-Driven and Hydrologic Models

Ateeq-ur-Rauf

Ghumman

2018

Water

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As a major component of the hydrologic cycle, rainfall runoff plays a key role in water resources management and sustainable development. Conceptual models of the rainfall-runoff process are governed by parameters that can rarely be directly determined for use in distributed models, but should be either inferred through good judgment or calibrated against the historical record. Artificial neural network (ANN) models require comparatively fewer such parameters, but their accuracy needs to be checked. This paper compares a Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) conceptual model and an ANN model based on the conjugate gradient method for streamflow prediction. Daily precipitation, temperature, and streamflow data of the Upper Indus River for a period of 20 years (1985-2004) are used as input for calibrating in the case of the HEC-HMS, and for training in case of the ANN. Ten years of data (2005-2014) are used to validate the HEC-HMS model and test the ANN. The performance of the models is assessed using different statistical indicators such as the Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), mean bias error (MBE), and the coefficient of determination (R 2). The results show good predictions for streamflow in the case of both HEC-HMS and ANN models. A parametric study is conducted using Monte Carlo analysis and finds that the most important parameters for HEC-HMS models are the storage coefficient and the time of concentration; while for ANN models, input combinations are the most important. This study investigates the sensitivity of these parameters, which can be used to determine preliminary estimation ranges of their values for future modeling. Finally, evaluating the impact of the simulated streamflow's accuracy on the flow duration curve shows that the curve is significantly affected by any streamflow simulation inaccuracy.

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“…This type of data is not available in most of the arid environmental regions. However, advancements in satellite imaging and geographical information system (GIS) tools have introduced geomorphological parameters that can be used to estimate the runoff from catchments with scarce data [21][22][23].…”

Section: Hec-hms and Gismentioning

confidence: 99%

Sustainability Evaluation Framework of Urban Stormwater Drainage Options for Arid Environments Using Hydraulic Modeling and Multicriteria Decision-Making

Alhumaid¹,

Ghumman

Haider

et al. 2018

Water

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Stormwater drainage systems in urban areas located in arid environmental regions generally consist of storm-sewer networks and man-made ponds for the collection and disposal of runoff, respectively. Due to expansion in cities' boundaries as a result of population growth, the capacity of existing drainage systems has been exhausted. Therefore, such systems overflow even during the smaller (than the design) return period floods. At the same time, changing rainfall patterns and flash floods due to climate change are other phenomena that need appropriate attention. Consequently, the municipalities in arid environmental regions are facing challenges for effective decision-making concerning (i) improvement needs for drainage networks for safe collection of stormwater, (ii) selection of most feasible locations for additional ponds, and (iii) evaluation of other suitable options, such as micro-tunneling. In this research, a framework has been developed to evaluate different stormwater drainage options for urban areas of arid regions. Rainfall-runoff modeling was performed with the help of Hydrological-Engineering-Centre, Hydrological-Modelling-System (HEC-HMS). To evaluate the efficacy of each option for handling a given design flood, hydraulicmodeling was performed using SewerGEMS. Meteorological and topographical data was gathered from the Municipality of Buraydah and processed to generate different inputs required for hydraulic modeling. Finally, multicriteria decision-making (MCDM) was performed to evaluate all the options on the basis of four sustainability criteria, i.e., flood risk, economic viability, environmental impacts, and technical constraints. Criteria weights were established through group decision-making using the Analytic Hierarchy Process (AHP). Preference-Ranking-Organization-Method for Enrichment-Evaluation (PROMETHEE II) was used for final ranking of stormwater drainage options. The proposed framework has been implemented on a case of Buraydah City, Qassim, Saudi Arabia, to evaluate its pragmatism. Micro-tunnelling was found to be the most sustainable option.

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Evaluating the impact of lower resolutions of digital elevation model on rainfall-runoff modeling for ungauged catchments

Cited by 20 publications

References 27 publications

Influence of DEM resolution on modelling hydrological connectivity in a complex agricultural catchment with woody crops

Influence of DEM resolution on modelling hydrological connectivity in a complex agricultural catchment with woody crops

Impact Assessment of Rainfall-Runoff Simulations on the Flow Duration Curve of the Upper Indus River—A Comparison of Data-Driven and Hydrologic Models

Sustainability Evaluation Framework of Urban Stormwater Drainage Options for Arid Environments Using Hydraulic Modeling and Multicriteria Decision-Making

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