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Soil erosion modeling using geographical information system research study in binh gia district lang son province

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THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY JOSE ALBERTO UMALI DUNCA SOIL EROSION MODELING USING GEOGRAPHICAL INFORMATION SYSTEM: RESEARCH STUDY IN BINH GIA DISTRICT, LANG SON PROVINCE BACHELOR THESIS Study Mode: Full-time Major: Environmental Science and Management Batch: 2012-2016 Thai Nguyen, 2016 i Thai Nguyen University of Agriculture and Forestry Degree program Bachelor of Environmental Science and Management Full name Jose Alberto Umali Dunca Student ID DTN1353110554 Soil Erosion Modeling Using Geographical Information Thesis title System: Research Study In Binh Gia District, Lang Son Province Supervisor MSC NGUYEN VAN HIEU Supervisor Signature Abstract: Land area is one major component in the progress of the world’s biophysical resources Nowadays, soil erosion is an emerging topic regarding in the land’s degradation Erosion whether by the subjects’ water, wind, or tillage; involves three (3) diverse actions – soil detachment, movement and deposition Soil erosion is not just an ecological issue in Vietnam in general; additionally flash flooding is a significant danger to human life and property Binh Gia District is located75 kilometers far from the capital city of the province which is Lang Son City It is located in the tropical monsoon climate, influenced by the general climate of the north; the climate is humid tropical monsoon Average annual rainfall is 1,540 mm, and during the rainy season is 212 mm per month RUSLE is an erosion model designed average soil losses from sheet and rill erosion under specified condition and was developed by Wischmeier and ii Smith in 1978 However, there are significant limitations due the model only estimates rill and inter-rill erosion, this means that no wind erosion was taken in consideration for the simulation.By the used of GIS technology, this method was adapted by the researcher in conducting a case study in Binh Gia District to model soil erosion The result of the analysis showed that the amount of soil loss in the research area ranges from to 5893.09t/ha/year Furthermore the total soil loss in the area was about 80169 ton per year from 11.1 thousand hectare Soil Erosion, RUSLE Method, Geographical Keywords Information System (GIS) Number of pages 59 Date of submission iii Acknowledgements First of all I want to express my sincerest gratitude to my Research Adviser MSc Nguyen Van Hieu to this support to my Bachelor’s Thesis, as well as for his patience, motivation, and great knowledge His guidance has helped me from the beginning, from learning at first, and all throughout my research and for the writing of this thesis as well My special thanks also to his assistants for their support to the completion of my paper Deepest thanks to Laguna State Polytechnic University Siniloan Campus, Siniloan, Laguna to their recommendation to us to study abroad, and also to Thai Nguyen University of Agriculture and Forestry to their acceptance to study full-time in their University with a 100% scholarship Sincere thanks also to Nguyen Vu Tuan Anh, Jimlea Nadezhda Mendoza, Keraia Vince Geronimo, and Paul Ezekiel Losaria for always around to help, and share their knowledge for me to finish my study Last but not the least, I want to thank God for everything he gave to us; for my family, my aunt and uncle, grandma and grandpa for their love, supports and their challenges for me to study hard and be a better student than before And for my Dad, this is for you Thai Nguyen, 2016 Student Jose Alberto Umali Dunca iv Table of Contents Table of Contents v LIST OF FIGURES LIST OF TABLES LIST OF ABBREVIATION PART I INTRODUCTION 1.1 Background and rationale 1.2 Research objective 1.3 The requirement 1.4 The significance PART II.LITERATURE REVIEW 2.1 Theoretical basis 2.1.1 Soil Erosion 2.1.2 Geographical Information System (GIS) 13 2.2 Practical Basis 14 PART III.METHODS 26 3.1 Materials 26 3.2 The content 26 3.3 Methods 26 3.3.1 Collecting and selecting data 26 3.3.2 Inherited method 26 v 3.4 The Revised Universal Soil Loss Equation (RUSLE) 27 3.4.1 R factor (rainfall erosivity) 29 3.4.2 K Factor (soil erodibility) 29 3.4.3 LS Factor (Slope Steepness and Slope Length) 32 3.4.4 Factor C (Crop Management) 34 3.4.5 P Factor (Management Practice) 35 PART IV.RESULTS 37 4.1 The natural conditions and socioeconomic in research area (Binh Gia District) 37 4.1.1 Area’s Climate and weather 38 4.1.2 Digital Elevation Model Map of Binh Gia District 38 4.1.3 Water Resources 39 3.1.4 Forest resources 39 4.1.5 Mineral Resources 40 4.1.6 Human 41 4.2 Result of soil erosion map 42 4.2.1 Rainfall Erosivity Factor (R) 42 4.2.2 Soil Erodibility Factor (K) 43 4.2.3 Slope length and Slope steepness factor (LS) 44 4.2.4 Crop Management (C) 48 4.2.5 Erosion Management Practice Factor (P) 50 4.2.6 Map editor (In ArcGIS 10.2 Software) 54 PART V DISCUSSION AND CONCLUSION 57 PART VI.REFERENCES 59 vi LIST OF FIGURES Figure 3.1 Diagrams of RUSLE Method Figure 3.2 Diagrams of Calculating LS Factor Figure 4.1 Binh Gia District Map Figure 4.2 DEM of Binh Gia District Figure 4.3 Rainfall Erosivity Map (Factor R) Figure 4.4 Soil Erodibility Map (Factor K) Figure 4.5 Slope Map of Binh Gia District Figure 4.6 Slope Steepness (Factor S) Figure 4.7 Flow Directions and Accumulation Figure 4.8 Factor M and F Figure 4.9 Slope Lengths (Factor L) Figure 4.10 Topographic Map (Factor LS) Figure 4.11 Normalized Difference Vegetation Index Map Figure 4.12 Crop Management Map (Factor C) Figure 4.13 Soil Loss Map of Binh Gia Figure 4.14 Soil erosion chart Figure 4.15 Date Frame Tool Figure 4.16 Map Locator Figure 4.17 Other map elements Figure 4.18 Edited Soil Erosion Map of Binh Gia District LIST OF TABLES Table 3.1 K Factor Value in Northern Part of Vietnam Table 3.2 Coefficient of Vegetation in Vietnam Table 4.1 Soil Erosion Value in every commune LIST OF ABBREVIATION ADB: Asian Development Bank DBMS: Database Management System DEM: Digital Elevation Model ESRI: Environmental Systems Research Institute ETM: Enhanced Thematic Mapper FAO: Food And Agriculture Organization GIS: Geographical Information System IDW: Inverse Distance Weighted MNF: Minimum Noise Fraction MSEC: Management Of Soil Erosion Consortium NDVI: Normalized Difference Vegetation Index PLER: Predict And Localize Erosion And Runoff RUSLE: Revised Universal Soil Loss Equation SLR: Soil Loss Ratio SMA: Spectral Mixture Analysis SWAT: Soil And Water Assessment Tools TIN: Triangulated Irregular Network USLE: Universal Soil Loss Equation USPED: Unit Stream Power Erosion/Deposition WCP: World Climate Programme PART I INTRODUCTION 1.1 Background and rationale Land area is to be deliberated as the one important geographic sector in the progress advancement of the world's biophysical assets (Bakimchandra, 2011) Impacts of soil erosion picking up the danger of lessening area accessibility and crisp water accessible per capita, in this way, nourishment security and manageable advancement are vital issues in the low accessible area per capita nations (Dercon et al., 2012), for example, in Vietnam The essential reason of soil erosion are ecological debasement, for example, deforestation, heightened land use, and the expanding scene populace (Ahmed et al., 2010), atmosphere and morphological conditions, for occurrence high concentrated precipitation, steep hill slopes Sometime ago in tropical locales, the top soil layer was regularly ensured by thick vegetation spread, root frameworks (Kefi et al., 2011) Soil erosion is not just an ecological issue in Vietnam in general; additionally flash flooding is a significant danger to human life and property Flash floods are characterized as remarkable floods delivered by extreme precipitation, over rapidly reacting of catchments and happen inside six hours of the causal precipitation occurrences Binh Gia District is located in the hilly and mountainous part of Lang Son Province Binh Gia’s population is 53 214 and covering land area of 1,091 km2 Binh Gia district is fragmented by rocky hills that have a slope of 25-300 or more The valley is narrow that annual crops are not much, leading to low revenue It is located in the tropical monsoon climate, influenced by the general climate of the north; the Figure 4.9.Slope Length (Factor L) Figure 4.10.Topographic Map of Binh Gia District 47 Topographic factor LS was represented by a more complex layer The slope steepness was very much affected by how the chosen the grid cell dimensions in the DEM Wu (2005) stated that the estimation of soil loss by empirical models decreases significantly when the grid cell size is increased This was mainly due to the reduction in general slope steepness The next step in the calibration was therefore mainly focused on determining the right conditions for the LS-factor layer in terms of the grid cell resolution In order to calibrate the model it was executed using a 10, 15, 20, 25, 30, 40 and 50 meter grid cell size 4.2.4 Crop Management (C) Figure 4.11.Normal Difference Vegetation Index Map of Binh Gia To calculate the Normal Difference Vegetation Index (NDVI) the researcher followed the formula using the landsat images: “(band5-band4)/(band5+band4)” 48 Figure 4.12.Crop Management Map (Factor C) of Binh Gia After Calculating the NDVI of the research area next step is calculating the C factor which resulted in the picture above The C-factor is based on the concept of a standard deviation, in this case an area under clean-tilled continuous-fallow conditions The Soil Loss Ratio (SLR) is then an estimate of the ratio of soil loss under actual conditions to losses experienced under the reference conditions "C" represents the effects of plants, soil cover, soil biomass, and soil disturbing activities on erosion RUSLE uses a sub factor method to compute soil loss ratios, which are the ratios at any given time in a cover management sequence to soil loss from the unit plot Soil loss ratios vary with time as canopy, ground cover, roughness, soil biomass and consolidation change A "C" factor value is an average soil loss ratio weighted according to the distribution of R during the year The sub factors used to compute a soil loss ratio values are canopy, surface cover, surface 49 roughness, prior land use and antecedent soil moisture If a C factor of 0.15 represents the specified cropping management system, it signifies that the erosion will be reduced to 15 percent of the amount that would have occurred under continuous fallow conditions 4.2.5 Erosion Management Practice Factor (P) The erosion management practice, P value, is also one factor that governs the soil erosion rate The P-value ranges from 0-1 depending on the soil management activities employed in the specific plot of land In this case the researcher used p = Modeling the soil erosion map Using the following formula: A = R K LS C P Using Raster Calculator tool 50 Figure 4.13.Soil Loss Map of Binh Gia 51 Table 4.1.Soil Erosion Value in every commune Communes Soil Erosion (ha) No Erosion (ha) Binh Gia (Townlet) Binh La Hoa Binh Hoa Tham Hoang Van Thu Hong Phong Hong Thai Hung Dao Minh Khai Mong An Quang Trung Quy Hoa Tan Hoa Tan Van Thien Hoa Thien Long Thien Thuat To Hieu Vinh Yen Yen Lo 15.6 44.6 102 162.2 153 Total Area (ha) 315.2 8.5 26 57.8 120.2 76.3 23.1 13 142.6 36.2 21.3 26.2 66 81.3 127.2 45.3 34.3 57.2 34.5 38.1 526 1035 1928.8 807.7 1036.8 395.7 647.2 1512.7 692.5 1324.8 1176.7 1150.8 643.4 1579.7 1056.2 1458.9 429.3 858.2 1500 1925.7 2722.4 6171.4 1911.1 3676.1 2123.1 2290.5 3546.7 1798 3501.7 4612.5 2899.1 1732.5 4243.1 2702.9 4810.9 1544.2 2483.1 4516.3 2460.2 3783.4 8158 2839 4789.2 2541.9 2950.7 5202 2526.7 4847.8 5815.4 4115.9 2457.2 5950 3804.4 6304.1 2030.7 3375.8 6054.4 899.5 1489.5 3140.6 1185.4 2409.3 1288.2 1001.2 1312.5 900.9 991.1 2438.1 1815.9 1439.6 2411.8 1687.2 2196.1 965 1562.1 1726.3 3359.7 5272.9 11298.6 4024.4 7198.5 3830.1 3951.9 6514.5 3427.6 5838.9 8253.5 5931.8 3896.8 8361.8 5491.6 8500.2 2995.7 4937.9 7780.7 Total Area (ha) 1050.7 19805 59313.3 80169 31013.3 111182.3 Strong Moderate Weak Total Value of (T/ha/year) (Ministry of Natural Resources and Environment, 2012.Circular 14/2012 / TT - BTNMT on Administrative Rules Committee investigation techniques land degradation) No erosion: Weak Erosion: < 10 Moderate Erosion: ≥ 10 - 50 Strong Erosion: ≥ 50 52 Soil Erosion 1% 18% 28% 53% Strong Moderate Weak No Erosion Figure 4.14.Soil Erosion Chart Based on the result after processing the data using ArcGIS 10.2, it shows that the amount of soil loss in Binh Gia District was about 80169 ton per year from 11.1 thousand hectare The size of the research area is 111182.3 Binh Gia district’s 31013.3 of land area have no erosion Hoa Tam and Quy Hoa are the communes that are not having a great number of soil erosion Minh Khai commune is the largest area having strong erosion, measuring of 142.6 followed by Thien Hoa commune then Hoang Van Thu The total area having strong erosion in the research area is 1050.7 ha, only 1% of the total land area 18% of the total area of Binh Gia District is affected by moderate erosion Binh Gia townlet, Hong Tai and To Hieu communes have the least number of moderate losses of soil Around a half of the land area of Binh Gia district have weak soil erosion with the total of 59313.3 Most of the communes have much number of it compare to the area having strong, moderate and no erosion 53 The spatial areas of the high spot range for soil disintegration in the study uncovered that the potential soil misfortune is regularly more prominent along the more extreme incline banks of tributaries Other high soil disintegration ranges scattered all through the bowl and is ordinarily connected with high disintegration potential area employments The plain range of the bowl demonstrates the slightest defenseless against soil disintegration 4.2.6 Map editor (In ArcGIS 10.2 Software) Creating a new page layout The first step in ArcMap was changing the map view to layout Figure 4.15.Data frame tool Adding a data frame to the page layout The data frame displays a collection of layers drawn in a particular order for a given map extent and map projection Adding a data frame to the page layout using the Insert menu From this menu, insert additional data frames These additional data frames for locator or detail maps If using multiple data frames, may want to consider using extent indicators to show the extent of one data frame within another data frame A good locator map will also contain an indicator, such as an outline, showing where the extent of the 54 detail map fits within a larger extent For example, the locator map might show the location of a state within a country Figure 4.16.Map Locator Adding other map elements to the page layout Using the Insert menu to select other map elements to add to layout Using this menu to add a title to the page The added text will be the same as the text entered for the title in the Map Document Properties dialog box Along with a title, it’s can be add (static) Text and Dynamic Text Figure 4.17.Other map elements Printing and exporting layout 55 After completed this work on the layout, printing the map or create other types of output formats—PDF files, PostScript files, or Illustrator files Under the file menu, using options to open the Page and Print Setup dialog box, Print Preview, Print the page, or to Export Map Figure 4.18.Edited Soil Erosion Model Map of Binh Gia District 56 PART V DISCUSSION AND CONCLUSION The goal of the study was to assess the capital distribution of soil loss in Binh Gia District, Lang Son Province By the used of ARCGIS 10.2 software the researcher modeled soil loss map of the research area After applying RUSLE method in modeling soil erosion map of Binh Gia District, the researcher found that the research area was not greatly affected by soil erosion, only in Southwest part where the vegetation was on moderate level RUSLE method has limitation and it is clearly stated on the definition that the model only estimates rill and inter-rill erosion This means that no wind erosion is taken in consideration for the simulation Application of RUSLE method using ARCGIS 10.2 software serves as a useful tool for soil erosion modeling in a large scale However, there are significant boundaries of remotely sensed data due to coarse resolution and geometric distortions that constrains the accuracy of erosion modeling In spite of the fact that, dirt disintegration hazard displaying suits a few shortcomings, disintegration hazard maps will help ecological and normal assets administration offices screen the status of disintegration and influenced components to soil Soil Erosion, for example, land spread, land use, and topographic elements, overlaying disintegration hazard maps and slant limit maps empower land supervisors and strategy producers to at first recognize areas and territories of assurance backwoods which can diminish soil disintegration and enhance environment quality Moreover, it is conceivable to incorporate remotely detected information and the RUSLE inside GIS stages as a screening apparatus when settling on choices on 57 selecting fitting area use situations Be that as it may, reenacted disintegration dangers ought to be reviewed and accepted with genuine information Land supervisors and strategy producers ought to lead soil disintegration hazard appraisal for upland zones in the area use arranging Fusing additionally supporting information, for example, nearby learning, financial states of neighborhood family units, approach, and others, to assemble a multi-criteria or multi-operators model - based woodland land arranging 58 PART VI.REFERENCES Ahmed M Y, Biswajeet P, & Abdallah M H (2010) Flash flood risk estimation along the St Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery Environ Earth Sci (2011) 62:611–623.Andersson, L (2010) Soil Loss Estimation Based on the USLE / GIS Approach Through Small Catchments - A Minor Field Study in Tunisia Bakimchandra, O (2011) Integrated Fuzzy-GIS approach for assessing regional soil erosion risks Universitsty of Stuttgart, Germany PhD thesis Barrios, A and Quinonez, E (2000) Soil Erosion Assessment Using the RUSLE Model, supported by GIS Application in Watershed of Venezuelan Andes, 44(1), 65–71 Bizuwerk, A., Taddese, G., & Getahun, Y (2003) Application of GIS for Modeling Soil loss rate in Awash River Basin, Ethiopia Iternational Livestock Research Institue(ILRI),Addis Ababa,Ethiopia, 1–11 Blanco, A C., & Nadaoka, K (2006) A Comparative Assessment and Estimation of Potential Soil Erosion Rates and Patterns in Laguna Lake Watershed Using Three Models : Towards Development of an Erosion Index System for Integrated WatershedLake Management Aquaculture, (December), 1–12 College of Agricultural Technology; I.J Shelton - Ontario Institute of Pedology de Carvalho, D F., Durigon, V L., Antunes, M A H., de Almeida, W S., & de Oliveira, P T S (2014) Predicting soil erosion using Rusle and NDVI time series from TM Landsat Pesquisa Agropecuaria Brasileira, 49(3), 215–224 http://doi.org/10.1590/S0100-204X2014000300008 Dercon, G., Mabit, L., Hancock, G., Nguyen, M L., Dornhofer, P., Bacchi, O O S., Zhang, X (2012) Fallout radionuclide-based techniques for assessing the impact of soil conservation measures on erosion control and soil quality: an overview of the 18 main lessons learnt under an FAO/IAEA Coordinated Research Project Journal of environmental radioactivity, 107(0), 78-85 doi: 10.1016/j.jenvrad.2012.01.008 Ganasri, B P., & Ramesh, H (2015) Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin Geoscience Frontiers, 1–9 http://doi.org/10.1016/j.gsf.2015.10.007 10 Gecolea, M L (1994) Lincoln University Digital Thesis WEIGHING DECISION FACTORS IN A GIS-ASSISTED 59 11 González, A M R., Arellano, U R., & Vizcarrondo, C (n.d.) Soil Erosion Calculation using Remote Sensing and GIS in Río Grande de Arecibo Watershed , Puerto Rico University of Puerto Rico at Mayaguez geologic ages in almost all parts of the earth with man ’ s increasing interventions with the Civil Engineering 12 Ha, N M (2011) Application Usle and Gis Tool to Predict Soil Erosion Potential and Proposal Land Cover Solutions to Reduce Soil Loss in Tay Nguyen Bridging the Gap Between Cultures, (May 2011), 18–22 http://doi.org/10.1017/CBO9781107415324.004 13 Jebari S (2009) Water erosion modeling using fractal rainfall disaggregation – A study in semiarid Tunisia Water resources engineering, Lund University, Sweden 14 Kefi, M., Yoshino, K., Setiawan, Y., Zayani, K., & Boufaroua, M (2011) Assessment of the effects of vegetation on soil erosion risk by water: a case of study of the Batta watershed in Tunisia Environmental Earth Sciences, 64(3), 707-719 doi: DOI 10.1007/s12665-010-0891-x 15 Kim, H S (2006) Soil erosion modeling using RUSLE and GIS on the Imha watershed, South Korea, 120 16 Ministry of Natural Resources and Environment (2012 ) Circular 14/2012 / TT BTNMT on Administrative Rules Committee investigation techniques land degradation 17 Nguyen Hong Quang, (2016) Modelling Soil Erosion , Flash Flood Prediction and Evapotranspiration in Northern Vietnam of the Georg-August-Universität Göttingen within the doctoral program of Geoscience / Geography of the Georg-August University School of Science ( GAUSS ) 18 Nguyen Ngoc Lung, Vo Dai Hai (1997), Initial results regarding protective effect of certain water vegetation and building forest water source protection, Agricultural Publication, Hanoi 19 Nguyen Trong Ha (1996) Definition the affected factors to the soil erosion and prediction soil loss in the sloped area Ph.D thesis, Hanoi University of the Irrigation 20 NRCS: USDA State Office of Michigan, Technical Guide to RUSLE use in Michigan, 2002 21 OMAFRA Staff; G Wall - Ontario Institute of Pedology; C.S Baldwin - Ridgetown 22 Phai, D D., Orange, D., Migraine, J., Toan, T D., & Vinh, N C (n.d.) Applying GISAssisted Modelling to Predict Soil Erosion for a Small Agricultural Watershed within Sloping Lands in Northern Vietnam Methods, 212–228 23 Tran Thi Phuong, Chau Vo Trung Thong, Nguyen Bich Ngoc, & Huynh Van Chuong (2014) Modeling Soil Erosion within Small Moutainous Watershed in Central Vietnam 60 Using GIS and SWAT Resources and Environment, 4(3), 139–147 http://doi.org/10.5923/j.re.20140403.02 24 Ty, P H (2008) Soil Erosion Risk Modeling Within Upland Landscapes Using Remotely Sensed Data and the Rusle Model, (1999), 1–6 Retrieved from http://wgrass.media.osakacu.ac.jp/gisideas08/viewpaper.php?id=250\npapers3://publication/uuid/18E478BE-F51E4262-A769-1620812AAA22 25 Wall, G., Baldwin, C.S., and Shelton, I.J.(2003) Soil Erosion – Causes and Effects Ontario Ministry of Agricultural and Food, Ontario, Canada 26 Weesies G Predicting soil erosion by water: a guide to conversation planning with the Revised Universal Soil Loss Equation (RUSLE) Agricultural Handbook No.703 1998 27 Weesies, G.A (1998) “Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE).” Agriculture Handbook No 703 Washington, District of Columbia, USA 28 Wischmeier W.H., D.D.Smith.1978 Predicting Rainfall erosion Loss USDA Agricultural research Service Handbook 537 29 Wu, S.; Li, J., Huang, G.: An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models, Department of Agriculture, Regina, Saskatchewan, Canada, 2005 61 ... Umali Dunca Student ID DTN1353110554 Soil Erosion Modeling Using Geographical Information Thesis title System: Research Study In Binh Gia District, Lang Son Province Supervisor MSC NGUYEN VAN HIEU... the province which was Lang Son City In the north of Binh Gia was Trang Dinh district, in the south was Bac Son district, in the east Van Quan and Van Lang districts all from Lang Son Province; ... precipitation occurrences Binh Gia District is located in the hilly and mountainous part of Lang Son Province Binh Gia? ??s population is 53 214 and covering land area of 1,091 km2 Binh Gia district is fragmented

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