Wavelet-based regularization of the extracted topographic index from high-resolution topography for hydro-geomorphic applications

Nourani, Vahid; Zanardo, S.

doi:10.1002/hyp.9665

Cited by 14 publications

(9 citation statements)

References 71 publications

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“…Digital Elevation Model for the watersheds was interpolated to 25 m grid based on LiDAR data. The grid size was this is a compromise between using a lower resolution that causes a loss of information about hillslope flow pathways, and a high resolution that is influenced by noise (Nourani and Zanardo 2014). Based on the flow accumulation maps generated using GIS tools, the TWI value was assigned to each raster cell in the digital elevation models of the watersheds.…”

Section: Terrain Characteristicsmentioning

confidence: 99%

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

Jeziorska

Niedzielski

2018

Acta Geophys.

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River basins located in the Central Sudetes (SW Poland) demonstrate a high vulnerability to flooding. Four mountainous basins and the corresponding outlets have been chosen for modeling the streamflow dynamics using TOPMODEL, a physically based semi-distributed topohydrological model. The model has been calibrated using the Monte Carlo approach-with discharge, rainfall, and evapotranspiration data used to estimate the parameters. The overall performance of the model was judged by interpreting the efficiency measures. TOPMODEL was able to reproduce the main pattern of the hydrograph with acceptable accuracy for two of the investigated catchments. However, it failed to simulate the hydrological response in the remaining two catchments. The best performing data set obtained Nash-Sutcliffe efficiency of 0.78. This data set was chosen to conduct a detailed analysis aiming to estimate the optimal timespan of input data for which TOPMODEL performs best. The best fit was attained for the half-year time span. The model was validated and found to reveal good skills.

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Section: Terrain Characteristicsmentioning

confidence: 99%

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

Jeziorska

Niedzielski

2018

Acta Geophys.

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“…Therefore for both daily and monthly data of two case studies (the Delaney Creek and Payn selected sub-series via four feature extraction criteria (i.e., H, MI, E and CC). In order to survey the performance of H, CC, E and MI feature extraction criteria, for instance in daily data, the sub-series of the first, second and third ranks (according to the Table 4) were primarily considered as the inputs of FFNN; thereinafter, the sufficient number of inputs was consequently determined using the maximum reduction rate method proposed by Nourani and Zanardo (2014). Table 5 presents the results of developed FFNN models using the selected sub-series decomposed by Haar, db2 and db4 mother wavelets for daily data.…”

Section: Results Of Ewann Modelmentioning

confidence: 99%

“…As a research plan and due to social and economic importance of the study areas, it is suggested to couple the proposed ANN-based model to a geomorphology-based rainfall-runoff model (e.g., TOPMODEL, Nourani and Zanardo, 2014) to have a comprehensive semi-distributed rainfall-runoff modeling for the site.…”

Section: Discussionmentioning

confidence: 99%

Application of Entropy Concept for Input Selection of Wavelet-ANN based Rainfall-Runoff Modeling

Nourani¹,

Khanghah²,

Baghanam³

2015

J ENV INFORM

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This paper presents a Wavelet-based Artificial Neural Network (WANN) approach to model rainfall-runoff process of the Delaney Creek and Payne Creek watersheds with distinct hydro-geomorphological characteristics, located in Florida. Wavelet is utilized to handle the multi-frequency characteristics of the process in daily and monthly time scales. Thus, rainfall and runoff time series were decomposed into several sub-series by various mother wavelets. Due to multiple components obtained through wavelet decomposition, input sets to the Feed Forward Neural Network (FFNN) were enhanced. The application of two information content based criteria (i.e., entropy, H, and mutual information, MI) to select more reliable input sets (among all potential input sets) and to have better insight into the physics of process is considered as the basic innovation of the study which led to a more accurate and compact model. The increase in the number of input of the FFNN might lead to a complex structure and low performance. The results demonstrated that MI as a supervised feature extraction criterion could lead to more reliable outcomes due to its non-linear nature. Furthermore, results indicated the superiority of proposed entropy-based WANN model (EWANN) in comparison to simple FFNN. Moreover, multi-step-ahead FFNN, conventional WANN and classic Auto Regressive Integrated Moving Average with eXogenous inputs (ARIMAX) models could not reveal appropriate forecasting results with regard to EWANN model. The superiority of the EW-ANN over the WANN and FFNN models is not only in terms of efficiency criteria, but also due to its appropriate ability to provide information about the physics of the process. The consequences of EWANN for rainfall-runoff modeling of two watersheds revealed that the proposed EWANN could simulate the process of a small and flat sub-basin slightly reliable than a sloppy and wild watershed. The poor outcome of monthly modeling in regard to daily modeling might be due to involvement of more uncertainty in the monthly data.

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“…Topographical factors have an important influence on the spatial distribution of cultivated land elements. A single elevation or slope does not accurately reflect the degree of impact [48]. Therefore, this paper introduces the topographical position index (comprehensive calculation of elevation and slope) to characterize the spatial distribution characteristics of cultivated land.…”

Section: Topographic Position Indexmentioning

confidence: 99%

The Spatial-Temporal Characteristics of Cultivated Land and Its Influential Factors in The Low Hilly Region: A Case Study of Lishan Town, Hubei Province, China

Zhang

Wang

et al. 2019

Sustainability

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Cultivated land is a basic resource that is related to the sustainable development of the global economy and society. Studying the spatial and temporal distribution of cultivated land and its influential factors at the township scale is an important way to improve its sustainable use. Based on the land use data in 2009 and 2015, this paper comprehensively uses kernel density estimation, spatial autocorrelation analysis, and the spatial autoregressive model to analyze the spatial distribution characteristics and influential factors of cultivated land. The results show that in 2009 and 2015, the maximum kernel density of cultivated land in Lishan Town was 31/km2 and 38/km2, respectively, and there is an increasing tendency for it in the future. The global spatial autocorrelation Moran’s I of the proportion of cultivated land area in the administrative villages of Lishan Town in 2009 and 2015 was 0.5251 and 0.3970, respectively. Cultivated land has significant spatial self-positive correlation agglomeration characteristics in spatial distribution. Based on spatial error model (SEM) analysis, the regression coefficients of the village were 0.236 and 0.196 in 2009 and 2015, respectively. The regression coefficients of the road were 0.632 and 0.630, respectively. The regression coefficients of the water system were 0.481 and 0.290, respectively. The regression coefficients of the topographic position index were −0.817 and −0.672, respectively. By comparing 2015 with 2009, the regression coefficients of each influential factor have been reduced to varying degrees.

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Wavelet-based regularization of the extracted topographic index from high-resolution topography for hydro-geomorphic applications

Cited by 14 publications

References 71 publications

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

Application of Entropy Concept for Input Selection of Wavelet-ANN based Rainfall-Runoff Modeling

The Spatial-Temporal Characteristics of Cultivated Land and Its Influential Factors in The Low Hilly Region: A Case Study of Lishan Town, Hubei Province, China

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