Geomorphometry for Geosciences

This volume is a contributionto the 4th International Conference on Geomorphometry

Geomorphometry 2015: Conference and WorkshopsGeomorphometry for natural hazards geomodelling

Poznań (Poland), June 22-26, 2015

Adam Mickiewicz University in Poznań - Institute of Geoecology and GeoinformationInternational Society for Geomorphometry

Association of Polish Geomorphologists

International Association of Geomorphologists’ Working Group on Landform Assessment for Geodiversity

Geomorphometry for GeosciencesEditors:

Jarosław Jasiewicz, Zbigniew Zwoliński, Helena Mitasova, Tomislav Hengl

Poznań 2015

© 2015 by Authors & Institute of Geoecology and Geoinformation, Adam Mickiewicz University in Poznań

Editors:Jarosław Jasiewicz, Institute of Geoecology and Geoinformation, Adam Mickiewicz University in Poznań, PolandZbigniew Zwoliński, Institute of Geoecology and Geoinformation, Adam Mickiewicz University in Poznań, PolandHelena Mitasova, Department of Marine Earth and Atmospheric Sciences, North Carolina State University, NC, USATomislav Hengl, International Soil Reference and Information Centre, Wageningen University and Research, the Netherlands

ISBN ISBN 978-83-7986-059-3

This publication is supported by: Ministry of Science and Higher Education of Poland, Adam Mickiewicz University in Poznań, Esri Polska

Book folding: Jarosław Jasiewicz, Jakub Nowosad

Cover image: 90m resolution geomorphometry map of the World (geomorphons mode) by Mitasova, H., Jasiewicz, J., Stepinski, T., Neteler., M., Gebbert, S., (2014) Analysis of Giga-size Earth Observation Data in Open Source GRASS GIS 7 - from Desktop to On-line Solutions, AGU Fall Meeting, SF, California, 2014

Citation: Jasiewicz J., Zwoliński Zb., Mitasova H., Hengl T. (eds), 2015. Geomorphometry for Geosciences. Adam Mickiewicz University in Poznań - Institute of Geoecology and Geoinformation, International Society for Geomorphometry, Poznań, pp. 278.

Publisher: Bogucki Wydawnictwo Naukowe, Poznań 2015

Printed in Poland from camera-ready materials provided by the Authors

Table of Contents

Manfred Zink, Alberto MoreiraTanDEM-X: A Challenging Radar Mission for Generating a New Earth's Topography 1

Christopher Wecklich, Carolina Gonzalez, Benjamin BräutigamHeight Accuracy for the First Part of the Global TanDEM-X DEM Data 5

Carlos Grohmann‘Radiography of the Amazon’ DSM/DTM data: comparative analysis with SRTM, ASTER GDEM 9

Piotr WoźniakHigh resolution elevation data in Poland 13

Shangmin Zhao, Li Wang and Wenjiao WuVertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data:taking Shanxi Plateau of

China as an example 15

Zbigniew Zwoliński and Joanna GudowiczGeomorphometric analysis of morphoclimatic zones on the Earth 19

Vincent Lecours, Vanessa Lucieer, Margaret Dolan and Aaron MicallefAn Ocean of Possibilities: Applications and Challenges of Marine Geomorphometry 23

Jozef Minar, Jozef Minar and Ian S. EvansTowards exactness in geomorphometry 27

Karin Ebert, Jerker Jarsjö and Karin EkstedtEffects of future sea level rise – the example of the island of Gotland, Sweden 31

Liyang Xiong and Guoan TangPre-Quaternary paleotopography reconstruction in the Ordos platform and its integration in the loess landform evolution modeling 35

Peter GuthGeomorphometry of Normal Faults: Abyssal Hills and Continental Rifts 39

Marco Bacenetti, Luca Ghiraldi, Marco Giardino and Luigi PerottiAnalysis of morphometric index to evaluate the tectonic activity: case study from Germanasca valley (NW

Italy) 43

Peter Bandura, Jozef Minár, Tatiana Harciníková and Lucian DrăguţTowards delineation of the morphostructural division of the Western Carpathians using object-based image analysis 47

Yuichi S. Hayakawa, Hidetsugu Yoshida, Lucian Dragut and Takashi OguchiComparative analysis of manual and automatic extractions of hummock landforms in Mt. Gassan,

northwestern Japan 51

Domenico Guida, Antonello Cestari, Alba Cuomo, Francesco Dramis, Vincenzo Palmieri and Vincenzo SiervoThe Salerno University Geomorphological Informative Mapping System: the Licosa polygenetic case study

(Cilento European geopark, southern Italy) 53

Piotr WężykMaking the invisible visible – the DTM modelling in complex environments 57

Waldemar KociubaGeometrical parameters of TLS-based DEM acquisition for a small Arctic catchment (Svalbard SW) 61

Marjan Temovski and Ivica MilevskiDEM based geomorphometric analyses of karst surface in the Republic of Macedonia 65

Michal Gallay, Ján Kaňuk, Jaroslav Hofierka, Zdenko Hochmuth and John MeneelyMapping and geomorphometric analysis of 3-D cave surfaces: a case study of the Domica Cave, Slovakia 69

Marek Kasprzak, Artur Sobczyk, Szymon Kostka and Anna HaczekSurface geophysical surveys and LiDAR DTM analysis combined with underground cave mapping – an efficient tool for karst system exploration: Jaskinia Niedźwiedzia case study (Sudetes, SW Poland) 75

Ian Evans and Nicholas J. CoxSize and shape of glacial cirques 79

Andrea Mandarino, Francesca Ferraris and Marco FirpoUnderstanding landscape evolution by using DEM analysis, low order channels gradient and Asymmetry

Factor: the case study of the upper Scrivia river basin (Northern Apennines, Italy) 83

Fayuan Li and Mingwei ZhaoSlope landscape change in a simulated watershed 87

Ivica Milevski and Anita MilevskaImprovement of slope angle models derived from medium to fine-scale DEM's Key study: Skopje area 91

Markus MetzSearching for water: hydrological modelling concepts in GRASS GIS 95

Tomasz Niedzielski, Bartlomiej Mizinski, Dapeng YuHydrological forecasting in real time: an experimental integrated approach 97

Jarosław Jasiewicz, Jolanta CzerniawskaConditional hydrological simulations as a tool for analysis of denudational transformation of post-glacial plains 103

Laura Coco, Viviana Cestrone and Marcello BuccoliniGeomorphometry for studying the evolution of small basins: an example in the Italian Adriatic foredeep 107

Libor Burian, Andrey Mitusov and Jean PoesenRelationships of attributes of gullies with morphometric variables 111

Adam Łajczak, Barbara Czajka and Ryszard KaczkaReinterpretation of morphometry of headwater areas using LiDAR data in homoclinal flysch mountain ridge

modelled by landslides. Case study of the Babia Góra Mt., the Western Carpathians 115

Ovidiu Csillik, Ian S. Evans and Lucian DrăguțAutomated transformation of slope and surface curvatures to avoid long tails in frequency distributions 119

Xiaoli Huang, Kai Liu and Liyang XiongThe Influence of DEM Resolution on the Extraction of Terrain Texture 123

Bartłomiej SzypułaRelief Index (RI) as a simple tool for geomorphometry 127

Shuanglin Liu, Fayuan Li, Ruqiao Jiang, Ruixue Chang and Wei LiuA Method of Automatic Topographic Recognition Based on Slope Spectrum 129

Vincent Lecours, Alvin Simms, Rodolphe Devillers, Vanessa Lucieer and Evan EdingerFinding the Best Combinations of Terrain Attributes and GIS software for Meaningful Terrain Analysis 133

Scott PeckhamLongitudinal Elevation Profiles of Rivers: Curve Fitting with Functions Predicted by Theory 137

Tomasz F. Stepinski, Jaroslaw Jasiewicz, Pawel Netzel and Jacek NiesterowiczDoing Geomorphometry with Pattern Analysis 141

Przemysław Stpiczyński, Dominik Szałkowski, Leszek Gawrysiak and Łukasz ChabudzińskiHybrid implementation of evaluation of primary topographic parameters using GPU-accelerated clusters 145

Sergio Camiz and Maurizio PoscolieriGeomorpho: a program for the classification of terrain units 149

Jarosław Jasiewicz, Alfred Stach, Jakub NowosadTerrain misclassification problem – analysis using pattern simulation approach 153

Anita BernatekVisualizing morphometric changes in a piping system using DEM and GIS analysis: the Bieszczady Mts., Poland 157

Charles JacksonCaution: dust storms may do exist (and so do mountains): Modeling dust source suitability within an object-

oriented geoecology 161

Viktor Kaufmann and Andreas Kellerer-PirklbauerRegional quantification of rock glacier movement in Central Austria using authoritative data sources 165

Rafal Wawer and Artur LopatkaThermal satellite scenes in single event modelling of wind erosion 169

Vaclav Petras, Helena Mitasova and Anna PetrasovaMapping gradient fields of landform migration 173

Marco Giardino, Luigi Perotti, Walter Alberto, Sara RattoMultidimensional approach to natural instabilities in mountain areas: how geomorphometry can improve both hazard modelling and risk perception 177

Janusz Wasowski, Fabio Bovenga, Raffaele Nutricato, Davide Oscar Nitti and Maria Teresa ChiaradiaHigh resolution satellite SAR multi temporal interferometry for regional scale detection of landslide and

subsidence hazards 181

François Clapuyt, Veerle Vanacker, Kristof Van Oost and Fritz SchluneggerVery-high resolution monitoring of movement of surface material within a landslide 185

Xavier Bodin, Dario Trombotto and Alvaro SorucoEvaluation of a terrestrial photogrammetry method for the study of high mountain dynamics. Quebrada del Medio rock glacier, Mendoza, Argentina 189

Mario Kummert and Reynald DelaloyeQuantifying sediment transfer between the front of an active alpine rock glacier and a torrential gully 193

Rafał Kroczak and Tomasz BryndalAn attempt to assess the influence of road network on flash flood wave parameters. The case study of the

Carpathian Foothills 197

Mihai NiculitaAutomatic extraction of landslide flow direction using geometric processing and DEMs 201

Daniele Strigaro, Massimiliano Moretti, Matteo Mattavelli, Mattia De Amicis, Valter Maggi and Antonello ProvenzaleDevelopment of GIS methods to assess glaciers response to climatic fluctuations: a Minimal Model approach 205

Cheng-Zhi Qin, Xue-Wei Wu, Yanjun Lu, Jing-Chao Jiang and A-Xing ZhuCase-based formalization of knowledge on digital terrain analysis 209

Magdy Torab and Nora DalalNatural hazards mapping of mega waves on the NW coast of Egypt 213

Piotr Kłapyta and Natalia KoleckaCombining laser scanning with field mapping and Schmidt-hammer relative age dating - examples from the

Babia Góra range (Westen Carpathians, Poland) 217

Aleksander Adamczyk, Marcin Sobiech, Agata Urbańska and Wojciech WysotaGeomorphometric analysis of glacial curvilineations (GCL) in Dobrzyń Lakeland, Central Poland 221

Lucas Ruiz and Xavier BodinAnalysis and improvement of surface representativeness of high resolution Pléiades DEMs: Examples from glaciers and rock glaciers in two areas of the Andes 223

Ruqiao Jiang and Guoan TangA Method of Depression Filling with Consideration of Local Micro-relief Features 227

Marcin Brach and Jarosław ChormańskiComparison of digital elevation models of riparian wetland generated from airborne laser scanning of

different accuracy 231

Extracting possible terrace surfaces from digital elevation models – methodological issues and case study

from Hungary

Ângelo Moura Araújo, Paulo Pereira, Renato Henriques and Diamantino PereiraWater resources assessment using GIS procedures: application in Ceará State (Brazil) 237

Adriana Sărășan and Lucian DrăguțAssessing contextual information from SRTM data as abasis for classifying landform types. Case study: dune fields 241

Maciej HajdukiewiczThe potential accuracy of the survey of landform changes using archival orthophotos: case study of the Białka

River valley 243

Milena Różycka, Aleksandra Michniewicz, Piotr Migoń and Marek KasprzakIdentification and morphometric properties of landslides in the Bystrzyckie Mountains (Sudetes, SW Poland) based on data derived from airborne LiDAR 247

Małgorzata MazurekGeomorphometric attributes of channel heads initiated by seepage erosion in a postglacial zone (NW Poland) 251

Virginia Ruiz-Villanueva, Markus Stoffel and Hanna HajdukiewiczUnderstanding large wood deposition during floods: a modelling approach 255

Cezary Kaźmierowski, Jakub Ceglarek, Jerzy Cierniewski, Jarosław Jasiewicz, Sławomir Królewicz and Michał Wyczałek Soil surface roughness quantification using DEM obtained from UAV photogrammetry 259

Claudia Scopesi, Ivano Rellini, Marco Firpo, Michael Maerker, Elmar Schmaltz and Silvia OlivariAssessment of an extreme flood event using rainfall-runoff simulation based on terrain analysis in a small Mediterranean catchment(Vernazza, Cinque Terre National Park) 263

Zbigniew Zwoliński and Ewa SznigirSpatial distribution of hypsometric curves within the Parsęta River drainage basin (Poland) as a geoindicator

of geomorphological hazards 267

Zbigniew Zwoliński and Estera StefańskaRelevance of moving window size in landform classification by TPI 273

Edina Józsa

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Water resources assessment using GIS procedures: application in Ceará State (Brazil)

Ângelo Moura Araújo, Paulo Pereira, Renato Henriques, Diamantino Pereira

Institute of Earth SciencesPole of the University of Minho

Braga, Portugalarangeo@gmail.com

Abstract—A methodological approach and preliminary results on water resources assessment in large areas are described with the case study of Ceará State (Brazil). The methodology includes analysis and interpolation of climatic and hydrological data, Digital Elevation Model (DEM) production and interpretation, and GIS procedures. The present results include the distribution of historical rainfall and fluvial discharges and the definition of a 7-levels river and watershed hierarchy in the Ceará State. The highest rainfall and discharge average values are located in the northeastern sector of the state confirming the important role of climatic features in hydrological diversity. Water resources management must then consider technical tools for water resources assessment, in the line of other methods for quantitative assessment of natural features either biotic or abiotic..

I. INTRODUCTION

Water must be understood as an environmental and social asset, an economical resource and a matter of extreme importance for all societies. Therefore water management must be handled as a technical subject but also as a political topic once water needs can lead to conflicts and ambitions by different factions evolving priority decisions [1]. Water resources quantitative assessment [2] [3] [4] has a special importance in the scope of the hydrological diversity approach [5]. In spite of being a rather new notion, geodiversity is defined [6] as the natural range (diversity) of geological (rocks, minerals, fossils), geomorphological (landforms, topography, physical processes), soil and hydrological features. It includes their assemblages, structures, systems and contributions to landscape. Water features are then elements of geodiversity being a very important agent in geological and biological processes and evolution. To be accepted as a useful tool, that diversity must be assessed according to objective methodologies in order to be used for nature conservation and land-use planning, as biodiversity currently is [7]. Common geological, geomorphological, soil or hydrographical maps are important in qualitative, but not in quantitative diversity assessment. In addition, as technical documents, they are difficult to read for non-specialists, thus limiting their use in routine planning. In that scope, the first

results on the assessment of water resources diversity in the Ceará State (Brazil) are presented. This work followed a methodology based on hydro and climatological data, spatial information and GIS procedures analysis.

II. METHODS

Relevant outcomes [8] [9] [10] [11] on water resources quantification using GIS based procedures were considered in the development of the method for the assessment of the hydrological diversity in the Ceará State. Ceará is one of the 27 states of Brazil, located in the northeastern part of the country, on the Atlantic coast, covering an area of 148,016 km2. With about 8.5 million inhabitants it is the eighth-largest Brazilian State by population. Ceará lies partly upon the northeast slope of the Brazilian Highlands, and partly upon the sandy coastal plain. The rivers of the state are small and, with one or two exceptions, become completely dry in the dry season. The largest is the Jaguaribe River, which flows entirely across the state in a northeast direction. Several data was acquired and a database was created for eventual analysis and processing. The database includes: DEM (Digital Elevation Model) of Ceará State based on the SRTM (Shuttle Radar Topography Mission) 90 metres per pixel resolution and enhanced to 30 metres resolution [12]; rainfall and discharge data (34 years series) in selected locations [13]; spatial information in vector format [14]. Methodological procedures included: statistical analysis of a 30 years sequence rainfall and discharge data and its distribution all over the territory; DEM treatment for automatic fluvial channels, networks and watersheds generation; hierarchy order of fluvial channels according to Strahler model [15]. Microsoft Excel© software was used to perform statistical operations. ESRI ArcGIS© 10.1 version, ESRI Arc Hydro© extension and Quantum GIS© 2.6.1 version software were used in DEM production, water resources analysis and GIS procedures.

A. Fluvial network, channel orders and watershed delimitation

The DEM is a computational representation of the altitude distribution in Ceará State, using a pixel grid with 30 metres of

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resolution. From it a set of information can be analysed and different maps can be produced: hypsometry (Fig. 1); slopes; aspect; morphological surfaces; hydrography; runoff flow directions. Besides, it is an important tool in erosional patterns, roughness textures and geomorphological analysis, allowing tridimensional visualization of different features [16].

In order to establish the fluvial network definition, the channel order classification and the watersheds delimitation the following tasks were performed using the ESRI Arc Hydro© tool:

1. Assemblage of the mosaic from the original DEM files;

2. Conversions in datum projection (from WGS 84 to SIRGAS 2000 - 24S Zone);

3. Cropping of the DEM mosaic, accordingly to the limits of the Ceará State area.

4. Specific in-software procedures to fluvial network and basins delimitation → Fill Sinks → Flow Direction → Flow Accumulation → Stream Definition → Stream Segmentation → Catchment Grid Delineation → Catchment Polygon Processing → Drainage Line Processing → Adjoin Catchment Processing → Drainage Point Processing → Batch Point Generation → Watershed Delineation → Export shapefile

Figure 1. Digital Elevation Model (DEM) with 30 m resolution of the northeastern sector of Ceará State (Brazil).

B. Rainfall and discharge analysis

The climatological and hydrological features regarding the proposed method were handled by the following procedures:

1. Research and acquisition of official rainfall data from 1974 to 2014;

2. Average values for more than 700 precipitation stations, from automatic calculation using Microsoft Excel© software.

3. Exclusion of stations with absent or irregular values and inclusion of stations that have at least 85% of complete rainfall information for the 1974-2014 period;

4. Calculation of discharge historical average values for 69 stations, from the rainfall average values (34 years period and year 2014) and the discharge values of the year 2014;

5. Data exportation to ESRI ArcGIS© and Quantum GIS© software;

6. Interpolation of rainfall (Kriging method) and discharge (Inverse Distance Weighting) values.

III. RESULTS

The processing of values according to the described methodology provided maps with the distribution of historical rainfall (Fig. 2) and fluvial discharges (Fig. 3) in Ceará State.

Seven hierarchy orders (levels) were credited to rivers in result of the DEM analysis. Then, watersheds were classified according to the river hierarchy, and a polygon was produced for each river segment considered in the analysis [17]. Level 1 and level 2 watersheds were excluded to avoid a large number of polygons thus level 3 rivers express the 327 watersheds defined in Ceará State. These are included in 57 level 4, 13 level 5, 3 level 6 and 1 level 7 watersheds.

IV. DISCUSSION

The annual rainfall average values (Fig. 2) in Ceará State range from 284 e 1400 mm, constituting a large disparity (1116 mm) between some regions. The northeastern sector of the state has the highest rainfall values mostly due to the Atlantic influence and the variety of air fronts in different times of the year. The lowest values in the central-western sector (less than 300 mm per year) are related with the local inland atmospheric circulation [18]. These climatic features have an important role in a water resources overview. The river discharge values (Fig. 3) are even more wide-ranging, between 7 m3/s and 12069 m3/s because different types of river were included in the analysis and also regarding the station location, if more upwards or downwards the watershed.

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Figure 2. Average values (34 years series) of annual rainfall (in mm) in the northeastern sector of Ceará State (Brazil).

However, considering rivers and watersheds of the same level, the highest discharge values are present in the northeastern sector of the state, combining the influence of the highest rainfall and the specific fluvial dynamics in that region.

These are some preliminary results aiming to quantify the water resources and their distribution in a large region with important within climatic differences. They constitute a basis for the knowledge of regional issues concerning water needs, flood and droughts events and even engineering solutions for water resources management. Although at this point we look forward to discuss and define the best way to represent water resources diversity. The improvement of these preliminary results in a second stage of quantification is expected, using data interpolation techniques and eventually producing a hydrological diversity index and the map of the water resources diversity of the Ceará State.

Figure 3. Average values (34 years series) of river discharge (in m3/s) in the northeastern sector of Ceará State (Brazil).

ACKNOWLEDGMENT

The authors express their gratitude to the Brazilian research fostering institution ‘Cordenação de Aperfeiçoamento de Pessoal de Nível Superior’ (CAPES) for awarding the Ciência Sem Fronteiras (CSC) PhD scholarship that enabled this work and for the financial support given by the Fundação para a Ciência e a Tecnologia (FCT) to the Institute of Earth Sciences (Pole of the University of Minho), which partially supported this research.

REFERENCES

[1] Abers, R., 2010. “Água e política: atores, instituições e poder nos Organismos Colegiados de Bacia Hidrográfica no Brasil”, Annablume, São Paulo, 248 p. (in Portuguese).

[2] Singh, V., and Fevert, D., (2000). “Mathematical models of large watershed hydrology”, Water Resources Publications, 914 p.

[3] Mariño, M., and Simonovic, S., 2001. “Integrated Water Resources Management”, International Association of Hydrological Sciences Publication nº 22, 74 p.

[4] Yan, D., Wang, H., Li, H., Wang, G., Qin, T., Wang, D., and Wang, L., 2012. “Quantitative analysis on the environmental impact of large-scale

Geomorphometry.org/2015 Araújo et al.

240

water transfer project on water resource area in a changing environment”., Hydrology and Earth System Sciences, 16: 2685-2702.

[5] Simić, S., 2011. “Hydrological heritage within protection of geodiversity in Serbia - legislation history”. Journal of the Geographical Institute Jovan Cvicic, 61(3): 17-32.

[6] Gray M., 2013. “Geodiversity: Valuing and Conserving Abiotic Nature”, 2nd Ed., Wiley, 508 p.

[7] Pereira D.I., Pereira P., Brilha J., and Santos L., 2013. “Geodiversity Assessment of Paraná State (Brazil): An Innovative Approach”. Environmental Management, 52(3): 541-552.

[8] Chiang, S., Tsay, T., Ni X., and Stephan J., 2002. “Hydrologic regionalization of watersheds. II: applications”. Journal of Water Resources Planning and Management, 128(1): 12-20.

[9] Alcamo J., Döll, P., Henrichs, T., Kaspar, F, Lehner, B., Rösch, T, and Siebert, S., 2003. “Development and testing of the WaterGAP 2 global model of water use and availability”. Hydrological Sciences Journal, 48(3): 317-337.

[10] Lorandi, R., and Cançado, C., 2002. “Parâmetros físicos para gerenciamento de Bacias Hidrográficas”, In Schiavetti A., and Camargo A. (Eds.) “Conceitos de Bacias Hidrográficas: teorias e aplicações, Editus, p. 37-65 (in Portuguese).

[11] Werth, S., and Güntner A., 2010. “Calibration analysis for water storage variability of the global hydrological model WGHM”. Hydrology and Earth System Sciences, 14: 59-78.

[12] Miranda, E. (Coord.), 2005. “Brasil em Relevo: monitoramento por Saté l i te” , avai lable in the EMBRAPA websi te , a t h t tp : / /www.relevobr.cnpm.embrapa.br (in Portuguese).

[13] COGERH, 2015. Precipitation and fluvial discharge data for the Ceará State, available in the Companhia de Gestão dos Recursos Hídricos website, at http://www.hidro.ce.gov.br (in Portuguese).

[14] IBGE, 2015. Digital cartography of the Ceará State, available in the Instituto Brasileiro de Geografia e Estatística website, at http://www.ibge.gov.br (in Portuguese).

[15] Strahler, A., 1957. “Quantitative analysis of watershed geomorphology”. Transactions of the American Geophysical Union, 8(6): 913-920.

[16] Araujo, A., and Silva, A., 2011. “Modelagem de áreas de escoamento superficial a partir do Modelo Digital de Terreno”. GEOUSP - Espaço e Tempo, 30: 194-204. (in Portuguese).

[17] Oliveira, S., 2008. “Metodologia para delimitação e análise multivariada de atributos morfométricos de bacia de drenagem usando modelo digital de elevação hidrologicamente corrigido”. Master Thesis in Geography, University of Brasilia, 74 p. (in Portuguese).

[18] Ferreira, A., and Mello, N., 2005. “Principais sistemas atmosféricos atuantes sobre a região nordeste do Brasil e a influência dos oceanos Pacífico e Atlântico no clima da região”. Revista Brasileira de Climatologia, 1(1): 15-28. (in Portuguese).

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