MAPPING OF SALT-AFFECTED SOILS Technical manual MAPPING OF SALT-AFFECTED SOILS Technical manual FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS ROME, 2020 i Recommended citation: Omuto CT, Vargas RR, El Mobarak, AM, Mohamed N, Viatkin K, Yigini Y. 2020. Mapping of salt-affected soils: Technical manual. Rome, FAO https://doi.org/10.4060/ca9215en The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. 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Front and back cover photos: ©FAO/Christian Omuto ii Contents FIGURES vi TABLES viii PREFACE ix ACKNOWLEDGEMENTS ix ABBREVIATIONS AND ACRONYMS x SYMBOLS AND NOTATIONS xii CONTRIBUTORS xii EXECUTIVE SUMMARY xiii 1 INTRODUCTION 2 1.1 Presentation 3 2 CHARACTERISTICS OF SALT-AFFECTED SOILS 5 2.1 Genesis of salt-affected soils 5 2.1.1 Soils-water-climate interaction model 5 2.1.2 Direct deposit model 6 2.2 Characteristics 6 2.3 Indicators for assessing salt-affected soils 7 2.4 Drivers of salt problems in the soil 8 2.4.1 Primary drivers 8 2.4.2 Secondary drivers 9 2.5 Classification of salt-affected soils 10 2.6 Global distribution of salt-affected soil 11 3 METHODS FOR MAPPING SALT-AFFECTED SOILS 13 3.1 Methods based on soil maps and expert opinion 14 3.2 Using remote sensing application 15 iii 3.3 Methods based on soil indicators of salts 18 3.4 Data requirements for mapping soil salinity 19 3.4.1 Soil data 19 3.4.2 Information on soil forming factors 20 3.4.3 Other ancillary data 21 3.4.4 Conversion models 21 SECTION TWO - DEVELOPMENT OF INFORMATION ON SALT-AFFECTED SOILS 23 4 PREPARATION FOR MULTISCALE MAPPING OF SALT-AFFECTED SOILS 24 4.1 Requirements 24 4.1.1 Input data 24 4.1.2 Computer and software 25 4.1.3 Example input data for demonstrating spatial mapping of salt-affected soils 26 4.2 Software requirements for multiscale mapping salt-affected soils 27 4.2.1 GIS application requirements 27 4.2.2 Data harmonization requirements 28 4.2.3 Spatial modelling requirements 29 4.3 Input data preparation for mapping salt-affected soils 29 4.3.1 Organizing spreadsheet data 30 4.3.2 Organizing GIS layers 33 4.3.3 Harmonizing input GIS layers 33 4.3.4 Input GIS database 38 5 COUNTRY-DRIVEN GLOBAL MAPPING APPROACH 41 5.1 Background 41 5.2 Step 1: Input data harmonization 42 5.2.1 Harmonizing GIS layers 43 5.2.2 Harmonization of input soil data 46 5.3 Step 2: Spatial modelling of indicators 51 5.3.1 Choosing suitable model 52 5.3.2 Model building and testing 54 5.3.3 Spatial prediction and uncertainty assessmentiv 56 5.4 Part 3: Spatial modelling of salt-affected soils 59 5.4.1 Spatial modelling of salt-affected soils 59 5.4.2 Accuracy assessment 60 5.4.3 Uncertainty assessment 61 5.5 Map update 66 5.5.1 Update needs assessment 66 5.5.2 Sampling for monitoring and gap filling 66 SECTION THREE | INFORMATION SHARING AND RESOURCES MOBILIZATION 68 6 PRODUCT DOCUMENTATION AND INFORMATION SHARING 68 6.1 Product documentation 68 6.1.1 Cartographics of map elements 69 6.1.2 Map metafile 70 6.2 Information sharing 71 6.3 Resource mobilization 74 6.3.1 Resource mobilization strategy 74 6.4 Technical capacity development program for spatial information development 77 6.4.1 Program overview 77 6.4.2 Duration and requirements 77 6.4.3 Objectives and outcomes 78 6.4.4 Schedule 78 6.4.5 Mode of delivery 80 6.4.6 Deliverables 80 References 81 Glossary 87 Appendices 90 Appendix A: Example image download from USGS 90 Appendix B: Frequently asked questions when implementing R 91 Appendix C: Checking for correct data organization in Excel 95 v Figures FIGURE 1.1: SURVEY RESULTS ON COUNTRY-LEVEL DATA AVAILABILITY FOR MAPPING SALT-AFFECTED SOILS 2 FIGURE 1.2: COUNTRY-DRIVEN FRAMEWORK FOR GLOBAL MAPPING OF SALT-AFFECTED SOILS 3 FIGURE 2.1: GENETIC PATHWAYS FOR DEVELOPMENT OF SALT-AFFECTED SOILS 5 FIGURE 2.2: GRAPHICAL ILLUSTRATION OF CHARACTERISTICS OF SALT-AFFECTED SOILS 6 FIGURE 2.3: PROPORTION OF SEVERITY OF SALT-AFFECTED AREAS OF THE WORLD 12 FIGURE 2.4: GLOBAL DISTRIBUTION OF SALT-AFFECTED COASTLINE AND RIVER VALLEYS (SOURCE: LI ET AL., 2014) 13 FIGURE 3.1: FRAMEWORK FOR DEVELOPING MAPPING METHODS FOR SALT-AFFECTED SOILS 13 FIGURE 3.2: EXAMPLE MAP OF SALT-AFFECTED SOILS (ADAPTED FROM SZABOLCS, 1979). 14 FIGURE 3.3: FRAMEWORK FOR REMOTE SENSING OF LAND SURFACE 15 FIGURE 3.4: GLOBAL MAP OF SOIL SALINITY USING REMOTE SENSING APPLICATIONS (SOURCE: IVUSHKIN ET AL., 2019) 17 FIGURE 3.5: APPROACHES FOR USING SOIL INDICATORS IN MAPPING SALT-AFFECTED SOILS 18 FIGURE 3.6: GLOBAL DISTRIBUTION OF SALT-AFFECTED SOILS (SOURCE: WICKE ET AL., 2011) 19 FIGURE 3.7: DATA REQUIREMENTS FOR MAPPING SALT-AFFECTED SOILS 21 FIGURE 4.1: REQUIREMENTS FOR MULTISCALE MAPPING OF SALT-AFFECTED SOILS 24 FIGURE 4.2: LOCATION OF SOIL PROFILE INFORMATION IN NORTHERN SUDAN 26 FIGURE 4.3: INPUT DATA HARMONIZATION FOR MULTISCALE MAPPING OF SALT-AFFECTED SOILS 28 FIGURE 4.4: STEPS FOR PROTECTING FOLDER WITH ORIGINAL DATA 30 FIGURE 4.5: INPUT SPREADSHEET DATA FORMAT 31 FIGURE 4.6: SAVING SPREADSHEET DATA IN MS EXCEL AS CSV TEXT FILE 32 FIGURE 4.7: REPROJECTING GIS LAYERS IN QGIS 34 FIGURE 4.8: STEPS FOR VECTOR-TO-RASTER CONVERSION IN QGIS 35 FIGURE 4.9: IMAGE PROCESSING USING SEMI-AUTOMATIC CLASSIFICATION PLUGIN 36 FIGURE 4.10: MOSAICKING REMOTE SENSING IMAGES 37 FIGURE 4.11: IMAGE CLIPPING USING QGIS 37 FIGURE 4.12: STEPS FOR DIGITAL TERRAIN ANALYSIS IN SAGA 38 FIGURE 4.13: DEVELOPMENT OF GIS DATABASE FOR MAPPING SALT-AFFECTED SOIL 39 FIGURE 4.14: CREATING SPATIALLY HARMONIZED GIS DATABASE IN ILWIS 39 FIGURE 5.1: MULTISCALE APPROACH FOR NATIONAL MAPPING SALT-AFFECTED SOILS BASED ON INDICATOR MAPS 41 FIGURE 5.2: EMPIRICAL STATISTICAL DISTRIBUTION OF IMAGE INDICES FROM SUDANESE CASE-STUDY DATASET 45 FIGURE 5.3: CORRELATION OF IMAGE INDICES AND SCREE PLOT OF THEIR PRINCIPAL COMPONENT 46 FIGURE 5.4: GRAPHICAL ILLUSTRATION OF RELATIONSHIP BETWEEN APPARENT AND MEASURED EC 49 FIGURE 5.5: EXAMPLE DEPTH HARMONIZATION FOR ECSE 50 FIGURE 5.6: BUBBLE PLOT FOR TOP 0-30CM HARMONIZED EC 50 FIGURE 5.7: FREQUENCY DISTRIBUTION BEFORE AND AFTER EC TRANSFORMATION 51 FIGURE 5.8: GRAPHICAL PLOT OF FREQUENCY DISTRIBUTION WITH PREDICTION LIMITS AT 95% CONFIDENCE INTERVAL 54 FIGURE 5.9: GRAPHICAL PLOT OF PREDICTED VERSUS MEASURED EC 55 FIGURE 5:10: REPRESENTATIVENESS OF VALIDATION (SAMPLE POINTS) EC RANGES IN PREDICTION MAP (FEATURE MAP) 56 FIGURE 5.11: SPATIAL PREDICTION WIDTH AT 95% CONFIDENCE INTERVAL AND OVERLAY OF VALIDATION POINTS 57 FIGURE 5.12: MAPS OF SALT-AFFECTED SOILS (0-30 CM) 58 FIGURE 5.13: GRAPHICAL ILLUSTRATION OF CLASSIFICATION ACCURACY FOR SALT-AFFECTED SOILS 60 FIGURE 5.14: MONTE CARLO UNCERTAINTY ESTIMATION PROCESS 61 FIGURE 5.15: CORRELATION FUNCTIONS