Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Figure 9.2 : Electromagnetic spectrum (Source: CRISP, 2003) COMPONENT Table 9.1 : Visible light spectrum (CRISP, 2003) Red Orange WAVELENGTH (nm) Yellow 610 – 700 Green 590 – 610 Blue 570 – 590 Indigo 500 – 570 Violet 450 – 500 430 – 450 400 – 430 Table 9.2 : Infrared spectrum (CRISP, 2003) BAND WAVELENGTH ( μm) Near infrared (NIR) 0.7 - 1.5 Short wavelength infrared (SWIR) 1.5 – 3 Mid wavelength infrared (MWIR) 3–8 Long wavelength infrared (LWIR) 8 - 15 Far infrared > 15 Microwaves are high wavelength EMR ranging from 1 mm to 1 m wavelengths and are widely used in advanced 'Microwave Remote Sensing'. Due to its larger wavelength, it is gifted with intense penetration power that can penetrate the clouds and layer of atmosphere to precisely depict the surface and subsurface features on the earth surface. The microwaves are divided into di erent frequency (wavelength) bands (Table 9.3). Other Electromagnetic waves include Ultraviolet: 3 to 400 nm; Radio Waves: 10 cm to 10 km 131
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables wavelength; X-Rays and Gamma Rays,which nds application ranging from communication to medical sciences for treatment of ailments such as Cancer (CRISP, 2003). Band Table 9.3 : Microwave remote sensing bands (CRISP, 2003) P L Frequency (Wavelength) S 0.3 – 1 GHz (30 – 100 cm) C 1 – 2 GHz (15 – 30 cm) X 2 – 4 GHz (7.5 – 15 cm) Ku 4 – 8 GHz (3.8 - 7.5 cm) K 8 - 12.5 GHz (2.4 - 3.8 cm) Ka 12.5 – 18 GHz (1.7 - 2.4 cm) 18 - 26.5 GHz (1.1 - 1.7 cm) 26.5 – 40 GHz (0.75 - 1.1 cm) Principal of Remote Sensing The remote sensing relies on EMR, where the source illuminates the target. Based on the physical characteristic of the target where a portion of the energy is absorbed and reected the atmosphere. Based on energy sources, remote sensing is classied into passive and active remote sensing. The passive remote sensing makes use of sensors that detect the reected or emitted electromagnetic radiation from natural sources. While active remote sensing makes use of sensors that detect reected responses from objects, which are irradiated from articially generated energy sources, such as radar. The principles of the remote sensing and its di erent components are described here (Figure9.3 and Figure9.4): 1. EMR Source or Illumination such as sun or active sensor of the satellite (A) 2. Interaction withAtmosphere (B) 3. Interaction with Target (C) 4. Reectance from Target (D) 5. Energy Reception by the Sensor (E) 6. Transmission and Processing (F) 7. Analysis and Interpretation (G) 8. Application for di erent purposes (H) 132
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Figure 9.3 : Components of remote sensing (Source: CCRS/CCT cited in NRCA N, 2015a) Figure 9.4 : Interaction of EMR with Earth's Surface and A tmosphere (A ckerman and W hittaker, 2011) India Space Research Organization (ISRO) launches the remote sensing satellites in the polar and geosynchronous orbits for several purposes in a variety of resolutions. India has the capability of remote sensing in the visible, infrared, thermal and microwave bands. Recently ISRO has also launched rst Indian Hyperspectral Imaging Satellite (HySIS) from Sriharikota on 29 November 2018. Some domestic remote sensing products are described in Table 9.4. Types of Resolution Spatial resolution: It isdescribed as the ability of a sensor to identify the smallest size detail of a pattern on an image. In other words, the distance between distinguishable patterns or objects in an image that can be separated from each other and is often expressed in meters (GIS lounge 2015). 133
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Spectral resolution: This denesthe sensitivity of a sensor to respond to a specic frequency range. The frequency ranges covered often include not only visible light but also non-visible light and electromagnetic radiation. Objects on the ground can be identied by the di erent wavelengths reected but the sensor used must be able to detect these wavelengths to see these features (GIS lounge 2015). Table 9.4 : Indigenous remote sensing products and their technical specications Sensor Resolution Swath Sensor Spectral Bands (μm) Platforms (m) Width Channels (km) Linear Imaging Self- 72 LISS-I - 1 0.45-0.52 (blue) IRS-1A Scanning System I LISS-I - 2 0.52-0.59 (green) IRS-1B 148 LISS-I - 3 0.62-0.68 (red) (LISS-I) LISS-I - 4 0.77-0.86 (near IR) Linear Imaging Self- 36 LISS-II-1 0.45-0.52 (blue) IRS-1A Scanning System II LISS-II-2 0.52-0.59 (green) IRS-1B 74 LISS-II-3 0.62-0.68 (red) (LISS-II) LISS-II-4 0.77-0.86 (near IR) Linear Imaging Self- 23 LISS-III-2 0.52-0.59 (green) IRS-1C Scanning System III 50 LISS-III-3 0.62-0.68 (red) IRS-1D 142 LISS-III-4 0.77-0.86 (near IR) RESOURCESAT -1 (LISS-III) 6 148 LISS-III-5 1.55-1.70 (mid-IR) IRS-1C 70 PAN 0.5 - 0.75 IRS-1D RESOURCESAT -1 High-Resolution LISS-IV-2 0.52-0.59 (green) RESOURCESAT -1 Linear Imaging Self- RESOURCESAT -2 Scanning System IV 5.8 24 - 70 LISS-IV-3 0.62-0.68 (red) (LISS-IV) LISS-IV-4 0.77-0.86 (near IR) Wide Field Sensor 188 WiFS-1 0.62-0.68 (red) IRS-1C (WiFS) 774 WiFS-2 0.77-0.86 (near IR) IRS-ID Advanced Wide Field 56-70 370- AWiFS -1 0.52-0.59 (green) RESOURCESAT -1 Sensor (AWiFS) 740 AWiFS -2 0.62-0.68 (red) AWiFS -3 0.77-0.86 (near IR) AWiFS -4 1.55-1.70 (mid-IR) Radiometric resolution: It describes the ability of the sensor to measure the signal strength (acoustic reectance) or brightness of objects (GIS lounge 2015). This resolution can give the idea of the contrast of the imagery. The acquisition of the imagery is done in the digital form and holds the information in a number of bits. The more is the number of bits, and higher is the range of Digital Numbers (DN) imagery can store. The number of bits denes the radiometric resolution of the imagery. For example, for imagery having an 8-bit 134
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables radiometric resolution, range of DN is given by (0 – (28– 1)), i.e. (0 – 255) (CRISP, 2003). Temporal resolution: It is an estimate of how often a satellite can acquire the imagery of the same location. Types of Corrections in Satellite Imagery Image processing is a process, which makes an image interpretable for a specic use. The most common methods of corrections are given below: Geometric Correction: To process the data with other data or maps in a GIS, all of the data must have the same reference system. A geometrical correction, also called geo- referencing, is a procedure where the content of a map can be assigned a spatial coordinate system (for example, geographical latitude and longitude) (SEOS, 2020). Radiometric Correction: System corrections are essential when technical defects and deciencies of the sensor and data transfer systems lead to mistakes in the image data construction. Causes can be detector failure and/or power failure from detectors operating simultaneously (SEOS, 2020). Atmospheric Correction: Removes the scattering and absorption e ects from the atmosphere. It obtains the surface characteristics. Dark object subtraction, radiative transfer models and atmospheric modelling are standard techniques used to correct for atmospheric disturbances (GIS Geography 2015). Resampling Resampling is the process of interpolating the pixel values while transforming your raster dataset. This is used when the input and output do not line up correctly (Desktop ArcGIS, 2019). Resampling methods Nearest- Performs the nearest neighbour assignment and is the fastest of the interpolation methods. It is used primarily for discrete data, such as a land-use classication since it will not change the values of the cells. The maximum spatial error will be one-half the cell size (DesktopArcGIS, 2019a). Bilinear- Performs a bilinear interpolation and determines the new value of a cell-based on a weighted distance average of the four nearest input cell centres. It is useful for continuous data and will cause some smoothing of the data (DesktopArcGIS, 2019a). Cubic- Performs a cubic convolution and determines the new value of a cell-based on tting a smooth curve through the 16 nearest input cell centres. It is appropriate for continuous data, although it may result in the output raster containing values outside the range of the input raster. It is geometrically less distorted than the raster achieved by 135
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables running the nearest neighbour resampling algorithm. The disadvantage of the Cubic option is that it requires more processing time. In some cases, it can result in output cell values outside the range of input cell values. If this is unacceptable, use Bilinear instead (Desktop ArcGIS, 2019a). Enhancement Techniques Image Enhancement is one of the most essential and challenging techniques. Image enhancement aims to improve the visual appearance of an image or to provide a “better transform representation for future automated image processing (Kaur et al., 2015). Many images like medical images, satellite images, aerial images and even real-life photographs su er from poor contrast and noise. It is necessary to enhance the contrast and remove the noise to increase image quality. Enhancement is the modication of an image to alter the impact on the viewer (Reshi, 2017). Generally, enhancement distorts the original digital values; therefore, enhancement is not done until the restoration processes are completed (Reshi, 2017). There is a strong inuence of contrast ratio on resolving power and detection capability of images. Techniques for improving image contrast are among the most widely used enhancement processes. To produce an image with the optimum contrast ratio, it is essential to use the entire brightness range of the display medium (Reshi, 2017). There are several methods used in contrast enhancement but Linear Contrast Stretch, Uniform distribution stretch and Gaussian stretch are more commonly used methods in image processing (Majumadar and Kumar, 2012; Obi reddy, 2018). Principal Component Analysis (PCA) is also used to transforms the information inherent in multispectral remotely sensed data into new principal component images that are more interpretable than the original data. It compresses the information content of several bands into a few primary component images. This enables the dimensionality reduction of hyperspectral data. More details can be found in GIS Geography 2015. Image Interpretation Interpretation is the process of detection, identication, description and assessment of signicant of an object and pattern imaged. There are two types of extraction of information from the images/photographs namely visual interpretation and Digital Image Classication. Both the interpretation techniques have merits and demerits (Geospatial world, 2010). Visual image interpretation The interpretation of satellite imagery and aerial photographs involves the study of various primary characters of an object concerning spectral bands. The basic elements of visual interpretation include tone, shape, size, pattern, texture, shadow and association. The following details for illustration of each elements of visual interpretation have been adapted from NRCAN, 2015b: 136
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Tone refers to the relative brightness or colour of objects in an image. Generally, the tone is the fundamental element for distinguishing between di erent targets or features. Variations in tone also allow the elements of shape, texture, and pattern of objects to be identied (NRCAN, 2015b). Shape refers to the general form, structure, or outline of individual objects. The shape can be a very distinctive clue for interpretation. Straight edge shapes typically represent urban or agricultural (eld) targets, while natural features, such as forest edges, are generally more irregular in shape, except where man has created a road or clear cuts. Farm or cropland irrigated by rotating sprinkler systems would appear as circular shapes (NRCAN, 2015b). Size of objects in an image is a function of scale. It is vital to assess the size of a target relative to other objects in a scene, as well as the absolute size, to aid in the interpretation of that target. A quick approximation of target size can direct interpretation to an appropriate result more quickly. For example, if an interpreter had to distinguish zones of land use, and had identied an area with several buildings in it, large structures such as factories or warehouses would suggest a commercial property, whereas small buildings would indicate residential use (NRCAN, 2015b). Pattern refers to the spatial arrangement of visibly discernible objects. Typically, an orderly repetition of similar tones and textures will produce a distinctive and ultimately recognizable pattern. Orchards with evenly spaced trees and urban streets with regularly spaced houses are good examples of the pattern (NRCAN, 2015b). Texture refers to the arrangement and frequency of tonal variation in particular areas of an image. Rough textures would consist of a mottled tone where the grey levels change abruptly in a small space, whereas smooth textures would have minimal tonal variation. Smooth textures are most often the result of uniform, even surfaces, such as elds, asphalt, or grasslands. A target with a rough surface and irregular structure, such as a forest canopy, results in a rough textured appearance. Texture is one of the most important elements for distinguishing features in radar imagery (NRCAN, 2015b). Shadow is also helpful in interpretation as it may provide an idea of the prole and relative height of a target or targets, which may make identication easier. However, shadows can also reduce or eliminate interpretation in their area of inuence, since targets within shadows are much less (or not at all) discernible from their surroundings. Shadow is also useful for enhancing or identifying topography and landforms, particularly in radar imagery (NRCAN, 2015b). Association takes into account the relationship between other recognizable objects or features in proximity to the target of interest. The identication of features that one would expect to associate with other features may provide information to facilitate identication. In the example given above, commercial properties may be associated with proximity to 137
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables major transportation routes, whereas residential areas would be associated with schools, playgrounds, and sports elds. For example, a lake is associated with boats, a marina, and adjacent recreational land (NRCAN, 2015b). Digital Image Classification Image classication is the process of assigning land cover classes to pixels (GIS Geography 2014). The unsupervised and supervised techniques are generally used in digital image classication (Figure 9.5). In unsupervised classication, it rst groups pixels into “clusters” based on their properties and then each cluster can be classied with a land cover class (GIS Geography 2014). Clustering is the process by which a set of objects are grouped together in such a way that the objects in the same group are more similar to each other than to objects in the di erent group (Wikipedia 2020a).In order to create “clusters”, analysts use image-clustering algorithms such as K-means and Iterative Self Organizing Data Analysis Technique (ISODATA). After picking a clustering algorithm, you identify the number of groups you want to generate. For example, you can create 8, 20 or 42 clusters. To be clear, these are unclassied clusters because, in the next step, you manually identify each cluster with land cover classes. For example, if you want to classify vegetation and non-vegetation, you'll have to merge clusters into only 2 clusters (GIS Geography 2014). In supervised classication, you select representative samples for each land cover class. The software then uses these “training sites” and applies them to the entire image. It uses the spectral signature dened in the training set. For example, it determines each class on what it resembles most in the training set. The common supervised classication algorithms are maximum likelihood and minimum-distance classication. In this, the main steps include selection of training areas, generate signature le and classify. The techniques of supervised classication algorithm involve Euclidean algorithm, Box classier or parallelepiped classication and Maximum likelihood classier (GIS Geography 2014). Accuracy assessment The classied image can be compared to another data source that is considered to be accurate or ground truth data. The most common method of accuracy assessment is to create a set of random points from the ground truth data and compare that to the classied data in a confusion matrix (Desktop ArcGIS 2019b). The accuracy of classied imageries can be assessed by using di erent performance indicators such as overall accuracy, Producer's accuracy, User's Accuracy and Kappa coe cient. More details about accuracy assessment using ERDAS Imagine software can be referred to this web http://knightlab.org/rscc/labs/Lab11_Accuracy_Assessment-2016.pdf. 138
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables FCC IRS 1D LISS-III (1977) FCC IRS P VI LISS-III (2005) Land use map (1977) d) Land use map (2005) Figure 9.5 : Satellite imageries and its classication (Jat et al., 2008) Applications of Remote Sensing The remote sensing techniques is being used in several areas for monitoring, impact assessment and preparing adaptions strategies. These includes coastal regions, ocean, hazard assessment, natural resources management, environmental monitoring and impact assessment etc.The collected data can be used for coastal mapping and erosion prevention, ocean resources management. Also, impacts of a natural disaster and create preparedness strategies to be used before and after a hazardous event. Minimize the damage that urban growth has on the environment and decide how to protect natural resources best. 139
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Geographical Information System (gis) GIS is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data (Wikipedia 2020b).The rst known use of the term \"GIS\" was by Roger Tomlinson in the year 1968 and he known as the \"father of GIS\". GIS data can be used to identify number of features such as a) The location of features and relationships to other features, b) Where the most and/or least of some functionality exists, c) The density of elements in a given space, d) What is happening inside an area of interest (AOI), e) What is happening nearby some feature or phenomenon, and f) How a specic area has changed over time? The di erent GIS programs/software is available for database creation and spatial analysis. Commonly used software includes ArcGIS, QGIS, ILWIS, etc. Similarly, GIS can be used for hydrological modelling (surface, sub-surface and groundwater) where GIS output can be used for di erent studies using di erent hydro-climatic models such as SWAT, WEAP, SWMM, MODFLOW etc. In GIS, spatial and non-spatial data are represented as raster and vector data sets, respectively (Figure.9.6). Raster data is represented by pixels with values creating a grid. It allows certain types of operations, which are not possible with vector data. The index maps can be created using map algebra with multiple data layers. While vector data can be stored as points, lines and polygons, which use less memory than raster format data and does not lose positional accuracy. Figure.9.6 :Raster V s. Vector (Source: GICHD IMSMA , 2016) 140
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Geo-referencing and watershed delineation Before creating any GIS database, geo-referencing and dening projection system are very important. It is representation of earths curved surface on the at surface either on a map or on a computer screen. For projection, rst datum is selected to model the surface of the earth. There are di erent projection methods best suiting to the area of map extent and preserving the map projection properties. Because the curved surface of the earth cannot be represented accurately on a at surface (Figure.9.7). Some of the standard map projections are Lambert Conformal Conic projection (LCC), Polyconic Projection and Universal Traverse Mercator projection (UTM). The error should be minimal and always need to check the Root Mean Square (RMS) error values (Figure.9.8). Also, we need to provide an appropriate projection system and follow a uniform project projection system for all raster and vector layers (e.g. Table 9.5). If the study area covers in more than one toposheet, then we need to join the multiple toposheets together to cover the whole study area (e.g. Figure.9.9). Generally, watersheds can be delineated by using existing toposheets with help of contours following the ridgeline (Fig. 10). Watersheds can be delineated using the DEM or contours map in ArcGIS. Soil and Water Assessment Tool (SWAT) can also delineate the watersheds and sub-watersheds automatically by using DEM. Figure.9.7 : Map projections (Source: MTPE, 2001) 141
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Figure 9.8 : Geo-referencing of the Toposheet (Uppaluri, 2011) Table 9.5 : Projection parameters Figure.9.9 : Joining (Mosaicking) multiple toposheet (Uppaluri, 2011) 142
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Once the successful geo-referencing, projection system and watershed delineation, creation of a GIS database can be undertaken. The database creation includes on-screen digitisation of line, polygon and point feature datasets (Figure.9.11). Similarly, some of these data sets can be generated automatically using DEM such as drainage network and contours with the help of ArcGIS andSWAT. The following data can be utilized to understand the watershed responses in terms of water quality and quantity at di erent spatial (spring shed, watershed, sub-watershed, river basin) and temporal scales (daily, sub- daily, weekly, monthly and annual): Figure.9.10 : Watershed delineation over SOI Toposheet i) Meteorological data (e.g. rainfall, temperature, evapotranspiration, relative humidity, wind speed etc.) ii) Hydrological data such as spring ow and river ow iii) Topographic characteristics such as DEM iv) Land use/land cover v) Soil characteristics vi) Geological characteristics vii) Groundwater data viii) Environmental parameters such as air and quality related data, pollution data etc. 143
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Figure.9.11 : Spatial analysis techniques & creation of a GIS database (Uppaluri, 2011) Conclusion Remote sensing and GIS techniques have proved to be an e cient tool for impact assessment studies. GIS and remote sensing play an important tool for decision-makers in river basin/watershed level and regional level planning. The di erent issues and challenges related to water availability, droughts, soil erosion, environment and rainfall-runo could be easily understand using GIS. The assessment, monitoring and evaluation can be easily undertaken using these geospatial technologies for better water resources planning and management. LULC impacts, groundwater, watershed management and interventions activities can also be studied in detail to identify catchment treatment measures, adaptation and mitigation strategies in future. References Jat MK, Choudhary M, Saxena A (2017). Application of geo-spatial techniques andcellular automata for modelling urban growth of a heterogeneous urban fringe, TheEgyptian journal of remote sensing and space science, 20 (2), 223-241. Jat MK, Garg PK, Khare D (2008). Monitoring and modelling of urban sprawl usingremote sensing and GIS techniques, International journal of applied earth observation andgeoinformation, 10, 26-43. 144
Basics of Geospatial Techniques for Interpretation of Hydro-Environmental Variables Kaur N, Baghla S, Kumar S (2015). A review: Image enhancement and its varioustechniques, International journal of advances in science engineering and technology,3 (3), 141-144. Majumdar PP, Kumar DN (2012). Floods in a changing climate: hydrologic modelling,Cambridge University Press, 95. Obi Reddy GB(2018). Geospatial technologies in land resources mapping, monitoringand management, Springer,638. Olson CE Jr (1960). Elements of photographic interpretation common to several sensors.Photogrammetric Engineering, 26(4): 651-656. Reddy GPO (2018). Satellite remote sensing sensors: Principles and applications,geospatial technologies in land resources mapping, monitoring and management,Publisher: Springer, 21-43. Reshi IA (2017). New techniques used for image enhancement, IOSR Journal of VLSIand Signal Processing (IOSR-JVSP), 7(6) I: 18-22. Root RR, Miller LD(1971). Identication of urban watershed units using remotemultispectral sensing. Completion Report OWRR Project No.A-012-COLO. Uppaluri S. (2011). Assessment of Water logging in a canal command area using RemoteSensing & GIS. An unpublished PhD thesis, Dept. of Civil Engineering, IIT Roorkee. 145
10 METEOROLOGY : GUIDE TO INSTRUMENTATION AND METHODS OF OBSERVATIONS Sandipan Mukherjee Abstract This chapter is aimed to provide basic theoretical understanding of atmospheric structure, energetics, constituents, and their inter-relationships with the changing climate. Subsequently, methods of scientic measurements of basic meteorological parameters with traditional equipment are elaborated. Therefore, this chapter is expected to be benecial for meteorology and environmental science graduate student and research enthusiast. Keywords:Atmospheric structure, Methods of measurement, and Instrumentation Introduction 'Meteorology' is the branch of science concerned with the processes and phenomena of the atmosphere, especially as a means of forecasting the weather (OUP, 2011).Similarly, air pollution is dened as the presence of substance in the atmosphere that can cause adverse e ects to man and the environment' (Tiwary et al., 2019). Therefore, assessment of air pollution through biogenic emission of gasses and particulate matters requires substantial understanding of meteorology at a vivid spatio-temporal scale. However, pre-requisite of any meteorological knowledge dissemination is to know basics of atmospheric structure, energetics, and constituents. Therefore, the following section describes briey the structure, energy budget, and constituents of the lower atmosphere. Structure of atmosphere The temperature - based classication of atmospheric boundary layer includes four layers (i) troposphere, (ii) stratosphere, (iii) mesosphere, and (iii) thermosphere (Figure 10.1). However, interaction between atmosphere and earth's surface is maximum within the Sandipan Mukherjee, Ph.D. Centre for Land and Water Resource Management G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, India. [email protected] Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 146
Meteorology : Guide to Instrumentation and Methods of Observations troposphere, approximately around 10-12 km above mean sea level. Therefore, most of the atmospheric processes, including cyclones, storms, spell of severe air pollution, etc. occur with in the troposphere. The troposphere vertically extends upto around 8km inpolar region and around10-12 km in the equator, and generically, the air temperature decreases with increasing elevation with in the troposphere. Figure 10.1: Temperature based vertical structure of atmosphere The vertical structure is linear up to 40 km and logarithmic above 40 km (Lawes and Weather, 1993) 147
Meteorology : Guide to Instrumentation and Methods of Observations Figure 10.2 : The vertical structure of troposphere indicating di erent layers (Oak, 1987) However, depending on the transport and buoyancy characteristics, the troposphere could further be divided into several categories (Figure 10.2). Approximately, a temporal scale of one day interaction between earth's surface and atmosphere is constrained with in a shallower region of the Planetary boundary layer (PBL) or atmospheric boundary layer (ABL). This layer has a character of well mixed turbulence. Due to the daytime heating of the atmosphere, the height of PBL could reach up to 1-2 Km. Subsequently, during night time cooling of atmosphere results lowering of PBL height to around 100m. The turbulent surface layer (SL) is associated to generation of small-scale turbulent structure produced by heterogeneous roughness and convection of Earth's surface. The day time period height of the SL could be up to 50-100m but can vary signicantly based on the Earth's surface property and convection. This layer is associated to approximately constant shearing stress in the vertical direction, and inuence of the earth's rotation is minimal in this layer. Beneath the SL, there are two layers, (i) roughness layer and (ii) laminar boundary layer. The roughness layer is a thin layer above a surface element and can be up to 1-2 times the height of a surface element where turbulence is highly irregular. The laminar boundary layer is in direct contact with the surface and non-turbulent in nature (Stull, 1988). Solar radiation and energy budget The mixing and turbulent processes that occur within the ABL are mostly driven by the energy received from sun, very much like formation of water bubbles and transport 148
Meteorology : Guide to Instrumentation and Methods of Observations processes within a water pan when heated from the bottom. Therefore, it is imperative that we understand how solar energy regulates energy budget of atmosphere. Below are few basic characteristics of the radiation energetics (Bryant,1997): We can estimate the energy output of Sun by solving the Stefan-Boltzmann Law of radiation: E =κT4 where, E is energy of the surface of Sun, κ is Stefan-Boltzmann constant (5.67x10-8W m-2 K-4) and T is the surface temperature of Sun. The solution of above equation provides us a value of 6.3x106 W m-2 energy emission from the Sun. Now, Sun is 149.6x106 km away from Earth. Therefore, the earth receives 0.46x10-7 % of Sun's energy output. Over the total area of Earth facing the Sun, 1353 (1368) Wm−2 energy is received. The Earth's disk receives around 350 Wm−2 of energy. However, 29% of the 350 Wm−2 of energy is directly reected back to the universe and the rest (approx. 250 Wm−2) is absorbed by the atmosphere and Earth's surface. Subsequently, approx. 250 Wm−2 energy is distributed to various components following Figure 10.3 : Schematics of energy partition (Silverman, 2008) One of the important aspects of this energy partition within Earth's atmosphere and surface is, changes in the wavelength of reected radiation, i.e. most of the short-wave radiations are reected back as long-wave radiation. Therefore, these reected radiations mostly lie within the infra-red region of energy spectrum. The energetics within atmosphere plays an important role in controlling surface temperature of Earth and subsequently a ects the warming and cooling of atmosphere, as described below. 149
Meteorology : Guide to Instrumentation and Methods of Observations Radiative forcing and greenhousegases One of the most important aspects of the radiation energetics of earth's atmosphere is ab- sorption of certain radiation by chemical constituents of earth's atmosphere other than Nitrogen (~78% of all the gases) and Oxygen (~20.9% of all the gases). Although, the incoming solar radiation is the principal source of energy for the atmosphere, the long- lived greenhouse gases such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) absorb the long-wave radiation and increases the temperature of the Earth. This is known as positive Radiative Forcing resulting global warming. However, there are quite a few other chemical species, particularly aerosols, which are having opposite e ect to green house gases. Global average radiative forcing (RF) in 2005 with respect to year 1750 for GHG sand the assessed Level Of Scientic Understanding (LOSU) is presented in Figure 10.4 For a greater emphasis on how these GHGs are impacting Earth's atmosphere and biophysical properties, a brief discussion on CO2and N2O is provide below. CO2 (Ballav, 2014): The most important greenhouse gas CO2 has increased from about 280 ppm in preindustrial time (Etheridge et al.,1996) to 380 ppm of recent time as per IPCC report. The present concentration is the highest (Siegenthaler et al., 2005) for the period of last 650,000 years and perhaps throughout the last 20 million years (Pearson , 2000). Human activities such as the fossil fuel emission and deforestation are thought to be the main drivers of increasing CO2 concentration (Canadell et al., 2007). Such a continuously increasing atmospheric CO2 concentration has raised concern for contribution to climate change through global warming and ozone depletion. Furthermore, the changing climate can a ect the terrestrial ecosystems, marine organism, ocean chemistry and the emergence of statistical distribution of weather pattern, large-scale hazards to human health, loss of biodiversity and growth of infectious diseases. N2O (Mukherjee, 2013): Emission of non-CO2 greenhouse gases is believed to contribute substantially to global warming and nitrous oxide (N2O) is one of the more potent non-CO2 green- house gases in the context of agricultural anthropogenic emissions. The100-year average global warming potential of N2O is 310 time higher than anequal mass of CO2 (Crutzen et al.,2008). An estimated 6% of total green house warming is contributed by N2O and it is the fourth largest single contributor to positive radiative forcing of the atmosphere (Denman et al., 2007). Tropospheric N2O is primarily inert, and therefore, the atmospheric residence time of N2O is more than 100 years (Cicerone, 1989). However, it is a principal source of nitric oxide (NO) in the stratosphere and indirectly responsible for ozone depletion. The Ozone Depleting Potential (ODP) of N2O is similar to some of the chlorouoro carbons and it has been estimated by Ravishankara et al.(2009) that the N2O emission of the present time is the single most important ozone-depleting contributor and will remain so for the 21 stcentury. A global scale relationship between the amount of nitrogen xed by the bio geochemical and atmospheric processes in the terrestrial ODP of a chemical compound is dened as the ratio between the amount of stratospheric ozone destroyedby the release of aunit mass of that chemical at Earth's surface to the amount destroyed by there lease of aunit mass of chlorouorocarbon 11, (CFCl3) (Ravishankara et al., 2009) 150
Meteorology : Guide to Instrumentation and Methods of Observations biosphere, and the total nitrogen released in the atmosphere through emission of N2O has been investigated by Crutzen et al. (2008). Estimates show that for both pre-industrial period and recent times the concentration growth of newly xed N to N2O has anoverall conversion factor of 3-5%, and the atmospheric mixing ratio of N2O has changed from 270 nmol/mol of the pre- industrial period to 315 nmol/mol of recent times. The atmospheric concentration of N2O is increasing at an annual rate of 0.2-0.3% (Prather et al.,1995) and 80% of all anthropogenic sources of N2O is contributed by the agricultural sector (Saggaretal., 2010). Figure 10.4 : Schematics of radiative forcing of individual GHGs (A dapted from IPCC Synthesis report 2009) Standards and definition The term 'standard' and other similar terms denote the various instruments, methods and scales used to establish the uncertainty of measurements. The denition of can vary based on international agreement, country, highest metrological quality available at given location or an organization (primary standards), already dened primary standards (secondary standards), etc. Inorder to control e ectively the standardization of meteorological instruments on a national and international scale, a system of national and regional standards has been adopted by the World Meteorological Organization (WMO). 151
Meteorology : Guide to Instrumentation and Methods of Observations Meteorological instruments in operational use at a service should be periodically compared directly or indirectly with the National Standards. Comparisons should be carried out between operational instruments of di erent designs (or principles of operation) to ensure homogeneity of measurements over space and time. Site selection Meteorological observing stations are designed so that representative measurements (or observations) can be taken according to the type of station involved. Thus, a station in the synoptic network should make observations to meet synoptic- scale requirements, where as a naviation meteorological observing station should make observations that describe the conditions specic to the local (aerodrome) site. Where stations are used for several purposes, for example, aviation, synoptic and climatological purposes, the most stringent requirement will dictate the precise location of an observing site and its associated sensors. Representativeness The representativeness of an observation is the degree to which it accurately describes the value of the variable needed for a specic purpose. Hence, for proper representation of a process, both spatial and temporal scale of that process is to be identied. Examples of various hydro-meteorological processes having various spatial scales are given below: Microscale (less than 100 m) for agricultural meteorology, for example, evaporation and transpiration. Toposcale or local scale (100-3km), for example, air pollution, tornadoes. Mesoscale (3-100 km), for example, thunderstorms, sea and mountain breezes. Large scale (100-3000 km), for example, fronts, various cyclones, cloud clusters. Planetary scale (larger than 3000 km), for example, long upper tropospheric waves. Measurement of basic meteorologicalparameters This section describes the instrumentation used for measurement of meteorological parameters, particularly, air temperature, wind speed and direction and rainfall. Instrumentation for airtemperature Thermometers are traditionally used for air temperature measurement. Normally air temperature measurement thermometers can be divided into two categories (i) Ordinary thermometers and (ii) Electronic thermometers, however, the following thermometers may also be available in a full climatic station: Dry bulb thermometer: this type of thermometer is used to measure true thermodynamic air temperature and should be shielded from moisture and radiation. Wet bulb thermometer: The wet bulb thermometer should be always covered with a moist cloth at 100% relative humidity and be shielded from radiation. The wet bulb temperature is used to assess moisture content in the air. 152
Meteorology : Guide to Instrumentation and Methods of Observations Characteristics of ordinary thermometers are given below: Ÿ This is a highly accurate instrument for air temperature measurement. Usually it is a mercury-in-glass-type thermometer. Ÿ Its scale markings have an increment of 0.2 K or 0.5 K, and the scale is longer than that of the other meteorological thermometers. Ÿ A support keeps it in a vertical position with the bulb at the lower end. The form of the bulb is that of a cylinder or an onion. Figure 10.5 : Left panel shows ordinary dry and wet bulb thermometers Right panel shows a Stevenson Screen that protects these thermometers from radiation Ÿ A Stevenson Screen is normally used as a radiation screen for such thermometers. Characteristics of electronic thermometers are given below: Ÿ Radiation shielded electronic thermometer needs a data logger and constant supply of direct current electricity. Ÿ The radiation shield is a solar radiation and precipitation shield supporting temperature and humidity probe installations in outdoor applications. Ÿ These instruments are maintenance free, naturally ventilated and easy to install on a vertical pole, horizontal beam or at surface. 153
Meteorology : Guide to Instrumentation and Methods of Observations Figure 10.6 : Left panel shows electronic sensor for air temperature measurement Right panel shows a radiation screen within which the thermometer sensor is inserted Particular sources of error in common to all liquid-in-glass thermometers are the following: Ÿ Elastic errors: errors caused by the emergent stem. Ÿ Parallax and gross reading errors. Ÿ Changes in the volume of the bulb produced by exterior or interior pressure. Ÿ Capillarity; errors in scale division and calibration. Ÿ Inequalities in the expansion of the liquid and glass over the range considered. For the shielded electronic sensors (such as HMP45A of Vaisala, Finland), direct and reected energy are the principal sources of error. Ideally, the shield should completely reect any incoming energy, which does not happen in practice as all reection coatings absorb energy. Therefore, inclusion of the systematic error of any measurement instrument is necessary when reporting the results. Some other sources of error may include: input voltage uctuation, data storage error etc. Instrumentation for wind speed and direction A wind speed measurement sensor is termed as anemometer. Cup anemometers with wind vane are traditionally used for wind speed and direction measurement. However, various designs of combined cup anemometer and wind vane are available in the market. Moreover, these combined anemometers are electronic in nature, can measure up to 100 m/s of wind 154
Meteorology : Guide to Instrumentation and Methods of Observations speed within an accuracy of ±0.5 ms−1, hence, require a data logger (Figure 10.7). Wind direction measurements are reported within a scale of 0-360o having measurement accuracy up to ±5o. Characteristics of traditional cup anemometers and wind vanes are given below: Figure 10.7 : Left panel shows a combined cup anemometer with a wind vane Right panel shows a combined wind speed and direction sensor (Make is R.M. Young Company, USA ) Ÿ Cup and propeller anemometer sare used to determine wind speed and consist of two sub-assemblies: the rotor and the signal generator. Ÿ In well-designed systems, the angular velocity of the cup or propeller rotor is directly proportion alto the wind speed, or, precisely, in the case of the propeller rotor, to the component of the wind speed parallel to the axis of rotation. However, the traditional cup anemometers are noted to have following measurement issues: Ÿ For almost all cup and propeller-type wind sensors, the response is faster for acceleration than for deceleration, so that the average speed of these rotors overestimates the actual average wind speed. Ÿ Moreover, vertical velocity uctuations can cause over-speeding of cupanemometers as a result of reduced cup interference in oblique ow. Recently, electronic wind speed measurement sensors are used for measurement of 3- wind components i.e. horizontal, lateral and vertical wind vectors (Figure 10.8). This equipment are termed as sonic anemometers which works on pulsed acoustic mode and also measures speed of sound. Generally, output of the sonic anemometers could be of a maximum rate of 155
Meteorology : Guide to Instrumentation and Methods of Observations 60Hz. Maximum range of measurement for three velocity components of wind could be ±60, 60 and 10 ms−1 for horizontal, lateral, and vertical wind vectors. The generic characteristics of sonic anemometers could be as follows: Figure 10.8 : Left panel shows a 3-D sonic anemometer design from Campbell Sci, USA Right panel shows a 3-D anemometer design from Gill Instruments, UK Sonic anemometers measure the time between emission and reception of an ultrasonic pulse travelling over a xed distance. Because sonic anemometers have no moving parts owing to their principle, they have high durability and little accuracy deterioration. Some types of recent sonic anemometers can measure wind even in rainy conditions. The measuring frequency of the sonic anemometers can vary between 5-60Hz. A data logger is required to store the sonic measurements of wind components which can be used to estimate wind speed and direction. The costs of the sonic anemometers are considerably higher than the traditional cup anemometers. Primary sources of errors in the anemometers, both cup-vane and sonic, are provided below: Ÿ For the cup anemometers, care should be taken to ensure that the bearings and signal generator have low starting and running frictional torques, and that the moment of inertia of the signal generator does not reduce the response too much. 156
Meteorology : Guide to Instrumentation and Methods of Observations Ÿ In cases of long-distance transmission, voltage signals decrease due to cable resistance losses and are inferior to pulse frequency signals, which are not so a ected during transmission. For the wind vane, signicant error can accumulate if the sensor is not set- up with the geographical north of the eld. Ÿ For the sonic anemometer, observations during rainfall can be unrealistic. Ÿ If the sonic anemometer is mounted on at all tower, the e ect of tower width on ow properties should also be evaluated as it can cause systematic errors for ows coming from a direction. Ÿ The current voltage input to the anemometer should be uninterrupted. The sonic anemometers should be placed over a relatively homogeneous terrain so that the observed ow is not modulated. Instrumentation forrainfall Rainfall gauges (or rain gauges) are the most common instruments used to measure rain fall. Generally, an open receptacle with vertical sides is used, usually in the form of a right cylinder, with a funnel if its main purpose is to measure rain (Fig. 10.9).Since various sizes and shapes of orice and gauge heights are used in di erent countries, the measurements are not strictly comparable (WMO, 2008). However, to measure rainfall, i.e. liquid precipitation, area of the collector orice should be around 200 cm2 having maximum value up to 500 cm2. The current automatic rain gauges are 'Tipping Bucket' in nature (as indicated in the right panel of Figure 10.9). Such rain gauges can have resolution up to 0.01 mm per tip. Figure 10.9 : Left panel shows a tradition al rain gauge where as the right panel shows the electronic structure of the same 157
Meteorology : Guide to Instrumentation and Methods of Observations Signicant sources of errors in a rain gauge could be exposure, wind speed and direction and topography. Systematic error accumulation in a rain gauge can be upto 30% depending on magnitude of wetting error, rain fall splashing out of the orice and insu ciently narrow entrance of the container. Conclusion This brief chapter on 'Meteorology: Guide to instrumentation and methods of observations' is a small e ort to introduce atmospheric structure and instrumentation to enthusiasts of meteorology and atmospheric science. Subsequently, this e ort has enormous scope for developing a detail document on various meteorological instruments for monitoring multitude of atmospheric processes and chemical constituents. However, it is anticipated that this document would be useful for establishment of a small weather observation facility by any stake holder. Disclaimer This chapter is a compilation of resources from already published books, manuals, research papers and theses, and e orts are made to refer all such documents. The book chapter is intended for academic use only, hence, conict of any copy-write issue is not addressed. References Ballav S (2014). Simulation of CO2 transport by a regional model and comparison with observed data. Ph. D. thesis, Jadavpur University, West Bengal, India. Bryant E (1997). Climate process and change. Cambridge University Press, Cambridge. Canadell J G, Marland G, Le Quere C, Raupach M R, and Field C B (2007). Contribution of accelerating atmospheric co2 growth from economic activity, carbon intensity and e ciency of natural sinks. Proceeding of National Academy of Sciences,104 (47), 18866–18870. Cicerone R J (1989). Analysis of the sources and sinks of atmospheric nitrous oxide (N2O). Journal of Geophysical Research, 94, 18265–18271. Crutzen P, Mosier A, Smith K, and Winiwarter W (2008). N2O release from agro-biofuel production negates global warming reduction by replacing fossil fuels. Atmospheric Chemistry and Physics, 8, 389–395. Denman K, Brasseur G, Chidthaisong G, Ciais P, Cox R, Dickinson D, Hauglustaine C, Heinze E, Holland E, Jacob D, Lohmann U, Ramachandran S, da Silva D, Wofsy F, and Zhang X (2007). Couplings between changes in the climate system and biogeochemistry. In Climate change 2007: The physical science basis. Contribution of the working group 1 to the fourth assessment report of the Intergovernmental Panel on Climate Change, 499–587. Cambridge University Press, Cambridge, UK. 158
Meteorology : Guide to Instrumentation and Methods of Observations Etheridge D, Steele L, Langenfeld R, Francey R, Barnola J, and Morgan V (1996). Natural and anthropogenic changes in atmospgeric co2 over the last 1000 years from air in Antarctic ice and rn. Journal of Geophysical Research, 101(D2), 4115–4128. Lawes H (1993). Back to basics: an introduction to meteorology for students and young people. Weather, 48,339–344. Mukherjee S (2013). On the estimation of nitrous oxide ux from agricultural elds of Canterbury, New Zealand, using micro-meteorological methods. Ph.D. thesis, University of Canterbury, Christchurch, New Zealand. Oak T (1987). Boundary-Layer Climates. Methuen, London and New York. OUP (2011). Oxford Dictionary and Thesaurus. Oxford university Press. Pearson P and Palmer M (2000). Atmospheric carbon dioxide concentrations over the past 60 million years. Nature, 406(6797), 695-699. Prather M, Derwent R, Ehhalt D, Fraser P, Sanhueza E, and Zhou X (1995). Climate Change 1994. Radiative Forcing of Climate Change and an Evaluation of the IPCC IS92. Emission Scenarios. Houghton J T, Meira Filho L G, Bruce J, Hoesung Lee, Callander BA, Haites E, Harris N and Maskell K (Eds). Cambridge University Press,Cambridge. Ravishankara A, Daniel J, and Portmann R (2009). Nitrous oxide (N2O): The dominant ozone-depleting substance emitted in the 21st century. Science, 326, 123–125. Saggar S, Harvey M, Singh J, Giltrap D, Pattey E, Bromley T, Martin R, Dow D, Moss R, and McMillan A (2010). Chambers, micrometeorological measurements, and the New Zealand denitrication-decomposition model for nitrous oxide emission estimates from an irrigated dairy-grazed pasture. Journal of Integrative Environmental Sciences,7(supp1), 61–70. Siegenthaler U, StockerT, MonninE, Luthi D, and Schwander J et al. (2005). Stable carbon cycle: climate relationship during the late Pleistocene. Science, 310(5752), 1313–1317. Silverman D (2008). Lecture talk UC, Irvine. Department of Physics andAstronomy. Stull R (1988). An Introduction to Boundary-Layer Meteorology. Kluwer Academic Publishers, The Netherlands. Tiwary A, Williams I, and Colls J (2019). Air Pollution: Measurement, modeling and mitigation. CRC Press - Taylor and Francis Group. WMO (2008). Guide to meteorological instruments and methods of observation. Number 978-92-63-10008-5. World Meteorological Organization. 159
11 FUNDAMENTAL CONCEPTS OF SOIL Sumit Rai Abstract The 3 dimensional natural body as a thin layer covering the earth surface is mainly known as soil made from the transformation or decomposition of rocks and their transportation and mixing with organic matter to become a mixture of heterogeneous nature to support plant nutrition and habitat of innumerable living organisms. The soil supports life of every terrestrial living organism on the earth directly or indirectly by providing the all essential living factors. Soil not only provide physical support to the plants and other organisms but also act as a nutrient supplier as well as it stores the moisture that is utilized by the plants. This chapter draws a conceptual framework in the mind of new practitioners with the soil and helps them to deal with more scientically to assess the capacity of soil as a physical supporter, plant nutrient media and moisture capacitor. Keywords: soil composition, physico- chemical properties, soil- water relationship, Introduction All the ancient civilizations had close bond with the soil. Even if we see the population density of any region that could be easily correlated with the fertility & health status of soil of that region. Soil is one of the most nonlinear and highly variable complex systems having innite number and variety of chemical and biological phenomena. They ensure that the system is never static, never at equilibrium. If anyone wants to understand soils, it must be studied from its atomic to global scales. The studies of soil in and of themselves as are between the Sky and the depths of the oceans. Soil and land both are considered coterminous in several aspects, however; they both are di erent in terms of dimensions. They both are related to each other as the land is 2- dimensional, where as soil is 3-dimensional. The soil and its relationship with the Sumit Rai, Ph.D. Centre for Environment Assessment and Climate Change G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora [email protected] Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 160
Fundamental Concepts of Soil environment, di erent life forms and societies are so intricate and intimate in such a way that our culture, civilization, or existence can't be imagined without this thin unconsolidated layer of crust. Soil scientist uses di erent laws of physics, chemistry and biology in an integrated manner to meet the pervasive importance of the soil resource in contemporary human a airs. The evolution and understanding of the soil science have a very long history which is mainly concentrated in the direction of the e ects of the larger earth surface environment on the development of soil and the role of soil as a unique environment that supports many forms of life. Soil scientists integrate principles developed in cognate disciplines (biology, chemistry, mineralogy, and physics) for the cataloguing, modeling, and quantifying of soil diversity. It not only includes discovering patterns of soil properties and their inter-relationships, but also the surveying and mapping of di erent types of spatial and temporal variability with the determining fundamental mechanisms for variability. This kind of puzzle-solving research is broad in scope, needs state-of-the-art technology, and applies an array of sophisticated, mutually supportive, fundamental concepts and instrumentation at progressively increasing levels of resolution. Basic soil science is both a eld and a laboratory science because soil in nature is a three-dimensional continuum, temporally dynamic and spatially anisotropic, both vertically and laterally (Sposito and Reginato 1992). A motivating challenge is then to transfer results from laboratory studies or model simulations to this three-dimensional, natural system. Basic soil science is also challenging because it leads to interaction among many disciplines in developing a more holistic concept of earth environment and behavior. This kind of research must take its place alongside the well-recognized basic research e orts in other bio- and geosciences (e.g., plant science or ocean science) to provide the reservoir of fundamental understanding needed to develop lasting, e ective solutions to the problems of modern agriculture, commerce, and environmental control as they relate to the soil resource. Concept of Pedology and Edaphology Soil science is the study of soil as a natural resource on the surface of the earth including soil formation, classication and mapping; physical, chemical, biological, and fertility properties of soils; and these properties in relation to the use and management of soils. Sometimes terms which refer to branches of soil science, such as pedology (formation, chemistry, morphology and classication of soil) and edaphology (inuence of soil on organisms, especially plants), are used as if synonymous with soil science. The diversity of names associated with this discipline is related to the various associations concerned. Indeed, engineers, agronomists, chemists, geologists, physical geographers, ecologists, biologists, microbiologists, silviculture, archaeologists, and specialists in regional planning, all contribute to further knowledge of soils and the advancement of the soil sciences. Soil scientists have raised concerns about how to preserve soil and arable land in a world with a growing population, possible future water crisis, increasing per capita food consumption, and land degradation. Soil occupies the pedosphere, one of Earth's spheres that the geosciences use to organize the Earth conceptually. This is the conceptual perspective of pedology and edaphology, the two main branches of soil science. Pedology 161
Fundamental Concepts of Soil is the study of soil in its natural setting. Edaphology is the study of soil in relation to soil- dependent uses. Both branches apply a combination of soil physics, soil chemistry, and soil biology. Due to the numerous interactions between the biosphere, atmosphere and hydrosphere that are hosted within the pedosphere, more integrated, less soil-centric concepts are also valuable. Many concepts essential to understanding soil come from individuals not identiable strictly as soil scientists. This highlights the interdisciplinary nature of soil concepts. One treats soil as a natural body, weathered and synthesized product in nature (Pedology) while other treats soil as a medium for plant growth (Edaphology). Pedological Approach: The origin of the soil, its classication and its description are examined in Pedology. (From Greek word pedon, means soil or earth). Pedology is the study of soil as a natural body and does not focus on the soil's immediate practical use. A pedologist studies, examines, and classies soil as they occur in their natural environment. Edaphological Approach: Edophology (from Greek word edaphos, means soil or ground) is the study of soil from the standpoint of higher plants. Edaphologists consider the various properties of soil in relation to plant production. They are practical and have the production of food and bre as their goal. They must determine the reasons for variation in the productivity of soils and nd means for improvement. Soil Composition By Volume A desirable surface soil in good condition for plant growth contains approximately 50% solid material and 50% pore space (Figure 11.1). The solid material is composed of mineral material and organic matter. Mineral material comprises 45% to 48% of the total volume of a typical soil. About 2 to 5% of the volume is made up of organic matter, which may contain both plant and animal residues in varying stages of decay or decomposition. Under ideal moisture conditions for growing plants, the remaining 50% soil pore space would contain approximately equal amounts of air (25%) and water (25%). Figure 11.1 : Volume composition of a desirable surface soil 162
Fundamental Concepts of Soil Soil formation The mineral material of a soil is the product of the weathering of underlying rock in place, or the weathering of transported sediments or rock fragments. The material from which a soil has formed is called its parent material. The weathering of residual parent materials to form soils is a slow process that has been occurring for millions of years. However, certain soil features (such asAhorizons, discussed below) can form in several months to years. The rate and extent of weathering depends on: Ÿ the chemical composition of the minerals that comprise the rock or sediment Ÿ the type, strength, and durability of the material that holds the mineral grains together Ÿ the extent of rock aws or fractures Ÿ the rate of leaching through the material Ÿ the extent and type of vegetation at the surface Physical weathering is a mechanical process that occurs during the early stages of soil formation as freeze-thaw processes and di erential heating and cooling breaks up rock parent material. After rocks or coarse gravels and sediments are reduced to a size that can retain adequate water and support plant life, the rate of soil formation increases rapidly. As organic materials decompose, the evolved carbon dioxide dissolves in water to form carbonic acid, a weak acid solution. The carbonic acid reacts with and alters many of the primary minerals in the soil matrix to make ner soil particles of sand, silt, and secondary clay minerals. As soil-forming processes continue, some of the ne clay soil particles (<0.002 mm) are carried, or leached, by water from the upper or surface soil into the lower or subsoil layers. As a result of this leaching action, the surface soil texture becomes coarser and the subsoil texture becomes ner as the soil weathers. Soil horizons Soils are layered because of the combined e ects of organic matter additions to the surface soil and long-term leaching. These layers are called horizons. The vertical sequence of soil horizons found at a given location is collectively called the soil prole (Figure 11.2). The principal master soil horizons found in managed agricultural elds are: Ÿ A horizon or mineral surface soil (if the soil has been plowed, this is called the Ap horizon) Ÿ B horizon or subsoil Ÿ C horizon or partially weathered parent material 163
Fundamental Concepts of Soil Ÿ R-Rock layer or unconsolidated parent materials similar to that from which the soil developed Unmanaged forest soils also commonly contain an organic O horizon on the surface and a light-colored leached zone (E horizon) just below theAhorizon. The surface soil horizon(s) or topsoil (the Ap or A+ E horizons) is often coarser than the subsoil layer and contains more organic matter than the other soil layers. The organic matter imparts a grayish, dark-brownish, or black color to the topsoil. Soils that are high in organic matter usually have dark surface colors. The A or Ap horizon tends to be more fertile and have a greater concentration of plant roots of any other soil horizon. In unplowed soils, the eluviated (E) horizon below the A horizon is often light-colored, coarser-textured, and more acidic than either theAhorizon or the horizons below it because of leaching over time. The subsoil (B horizon) is typically ner in texture, denser, and rmer than the surface soil. Organic matter content of the subsoil tends to be much lower than that of the surface layer, and subsoil colors are often stronger and brighter, with shades of red, brown, and yellow predominating due to the accumulation of iron coated clays. Subsoil layers with high clay accumulation relative to theAhorizon are described as Bt horizons. The C horizon is partially decomposed and weathered parent material that retains some characteristics of the parent material. It is more like the parent material from which it has weathered than the subsoil above it. Soil Physical Properties The physical properties of a soil are the result of soil parent materials being acted upon by climatic factors (such as rainfall and temperature), and being a ected by relief (slope and direction or aspect), and by vegetation, with time. A change in any one of these soil-forming factors usually results in a di erence in the physical properties of the resulting soil. The important physical properties of a soil are: Ÿ texture Ÿ aggregation Ÿ structure Ÿ porosity 164
Fundamental Concepts of Soil Figure 11.2 : Soil prole horizons. Texture The relative amounts of the di erent soil size (<2 mm) particles, or the neness or coarseness of the mineral particles in the soil, is referred to as soil texture. Mineral grains which are >2 mm in diameter are called rock fragments and are measured separately. Soil texture is determined by the relative amounts of sand, silt, and clay in the ne earth (< 2 mm) fraction. 165
Fundamental Concepts of Soil Ÿ Sand particles vary in size from very ne (0.05 mm) to very coarse (2.0 mm) in average diameter. Most sand particles can be seen without a magnifying glass. Sands feel coarse and gritty when rubbed between the thumb and ngers, except for mica akes which tend to smear when rubbed. Ÿ Silt particles range in size from 0.05 mm to 0.002 mm. When moistened, silt feels smooth but is not slick or sticky. When dry, it is smooth and oury and if pressed between the thumb and nger will retain the imprint. Silt particles are so ne that they cannot usually be seen by the unaided eye and are best seen with the aid of a strong hand lens or microscope. Ÿ Clay is the nest soil particle size class. Individual particles are ner than 0.002 mm. Clay particles can be seen only with the aid of an electron microscope. They feel extremely smooth or powdery when dry and become plastic and sticky when wet. Clay will hold the form into which it is molded when moist and will form a long ribbon when extruded between the ngers. Determining textural class with the textural triangle The textural classes are dened by their relative proportions of sand, silt, and clay as shown in the USDA textural triangle (Figure 11.3). Each textural class name indicates the size of the mineral particles that are dominant in the soil. Texture can be estimated in the eld by manipulating and feeling the soil between the thumb and ngers but should be quantied by laboratory particle size analysis. To use the textural triangle: 1. First, you will need to know the percentages of sand, silt, and clay in your soil, as determined by laboratory particle size analysis. 2. Locate the percentage of clay on the left side of the triangle and move inward horizontally, parallel to the base of the triangle. 3. Follow the same procedure for sand, moving along the base of the triangle to locate your sand percentage 4. Then, move up and to the left until you intersect the line corresponding to your clay percentage value. 5. At this point, read the textural class written within the bold boundary on the triangle. For example: a soil with 40% sand, 30% silt, and 30% clay will be a clay loam. With a moderate amount of practice, soil textural class can also be reliably determined in the eld. If a soil contains 15% or more rock fragments, a rock fragment content modier is added to the soil's texture class. For example, the texture class designated as gravelly silt loam would contain 15 to 35% gravels (> 2 mm) within a silt loam (< 2 mm) ne soil matrix. 166
Fundamental Concepts of Soil E ects of texture on soil properties Water inltrates more quickly and moves more freely in coarse-textured or sandy soils, which increases the potential for leaching of mobile nutrients. Sandy soils also hold less total water and fewer nutrients for plants than ne-textured soils. In addition, the relatively low water holding capacity and the larger amount of air present in sandy soils allows them to warm faster than ne-textured soils. Sandy and loamy soils are also more easily tilled than clayey soils, which tend to be denser. In general, ne-textured soils hold more water and plant nutrients and thus require less frequent applications of water, lime, and fertilizer. Soils with high clay content (more than 40% clay), however, actually hold less plant-available water than loamy soils. Fine- textured soils have a narrower range of moisture conditions under which they can be worked satisfactorily than sandy soils. Soils high in silt and clay may puddle or form surface crusts after rains, impeding seedling emergence. High clay soils often break up into large clods when worked while either too dry or too wet. Aggregation and soil structure Soil aggregation is the cementing of several soil particles into a secondary unit or aggregate. Soil particles are arranged or grouped together during the aggregation process to form structural units (known to soil scientists as peds). These units vary in size, shape, and distinctness (also known as strength or grade). The types of soil structure found in most Mid-Atlantic soils are described in Table 11.1 and illustrated in Figure 11.4. Figure 11.3 : The USDA textural triangle (Soil Survey Division Sta , 1993) 167
Fundamental Concepts of Soil Table 11.1 : Types of soil structure. Structure type Description Granular Blocky Soil particles are arranged in small, rounded units. Granular structure is very common in surface soils (A horizons) and is usually most distinct in soils with Platy relatively high organic matter content. Prismatic Soil particles are arranged to form block-like units, which are about as wide as Structureless they are high or long. Some blocky peds are rounded on the edges and corners; others are angular. Blocky structure is commonly found in the subsoil, although some eroded ne-textured soils have blocky structure in the surface horizons. Soil particles are arranged in plate-like sheets. These plate-like pieces are approximately horizontal in the soil and may occur in either the surface or subsoil, although they are most common in the subsoil. Platy structure strongly limits downward movement of water, air, and roots. Platy structure may occur just beneath the plow layer, resulting from compaction by heavy equipment, or on the soil surface when it is too wet to work satisfactorily. Soil particles are arranged into large peds with a long vertical axis. Tops of prisms may be somewhat indistinct and normally angular. Prismatic structure occurs mainly in subsoils, and the prisms are typically much larger than other typical subsoil structure types such as blocks. Either: Ÿ Massive, with no denite structure or shape, as in some C horizons or compacted material. Or: Ÿ Single grain, which is typically individual sand grains in A or C horizons not held together by organic matter or clay. Figure 11.4 : Types of soil structure. 168
Fundamental Concepts of Soil E ects of structure on soil properties The structure of the soil a ects pore space size and distribution and therefore, rates of air and water movement. Well-developed structure allows favourable movement of air and water, while poor structure retards movement of air and water. Since plant roots move through the same channels in the soil as air and water, well-developed structure also encourages extensive root development. Water can enter a surface soil that has granular structure (particularly ne-textured soils) more rapidly than one that has relatively little structure. Surface soil structure is usually granular, but such granules may be indistinct or completely absent if the soil is continuously tilled, or if organic matter content is low. The size, shape, and strength of subsoil structural peds are important to soil productivity. Sandy soils generally have poorly developed structure relative to ner textured soils, because of their lower clay content. When the subsoil has well developed blocky structure, there will generally be good air and water movement in the soil. If platy structure has formed in the subsoil, downward water and air movement and root development in the soil will be slowed. Distinct prismatic structure is often associated with subsoils that swell when wet and shrink when dry, resulting in reduced air and water movement. Very large and distinct subsoil prisms are also commonly associated with fragipans, which are massive and dense subsoil layers. Porosity Soil porosity, or pore space, is the volume percentage of the total soil that is not occupied by solid particles. Pore space is commonly expressed as a percentage: % pore space = 100 - [bulk density ÷ particle density x 100] Bulk density is the dry mass of soil solids per unit volume of soils, and particle density is the density of soil solids, which is assumed to be constant at 2.65 g/cm3. Bulk densities of mineral soils are usually in the range of 1.1 to 1.7 g/cm3. A soil with a bulk density of about 1.32 g/cm3 will generally possess the ideal soil condition of 50% solids and 50% pore space. Bulk density varies depending on factors such as texture, aggregation, organic matter, compaction/consolidation, soil management practices, and soil horizon. Under eld conditions, pore space is lled with a variable mix of water and air. If soil particles are packed closely together, as in graded surface soils or compact subsoils, total porosity is low and bulk density is high. If soil particles are arranged in porous aggregates, as is often the case in medium-textured soils high in organic matter, the pore space per unit volume will be high and the bulk density will be correspondingly low. 169
Fundamental Concepts of Soil The size of the individual pore spaces, rather than their combined volume, will have the most e ect on air and water movement in soil. Pores smaller than about 0.05 mm (or ner than sand) in diameter are typically called micropores and those larger than 0.05 mm are called macropores. Macropores allow the ready movement of air, roots, and percolating water. In contrast, micropores in moist soils are typically lled with water, and this does not permit much air movement into or out of the soil. Internal water movement is also very slow in micropores. Thus, the movement of air and water through a coarse-textured sandy soil can be surprisingly rapid despite its low total porosity because of the dominance of macropores. Fine-textured clay soils, especially those without a stable granular structure, may have reduced movement of air and water even though they have a large volume of total pore space. In these ne-textured soils, micropores are dominant. Since these small pores often stay full of water, aeration, especially in the subsoil, can be inadequate for root development and microbial activity. The loosening and granulation of ne- textured soils promotes aeration by increasing the number of macropores. Soil Organic Matter Soil organic materials consist of plant and animal residues in various stages of decay. Primary sources of organic material inputs are dead roots, root exudates, litter and leaf drop, and the bodies of soil animals such as insects and worms. Earthworms, insects, bacteria, fungi, and other soil organisms use organic materials as their primary energy and nutrient source. Nutrients released from the residues through decomposition are then available for use by growing plants. Soil humus is fully decomposed and stable organic matter. Humus is the most reactive and important component of soil organic matter and is the form of soil organic material that is typically reported as “organic matter” on soil testing reports. Factors that a ect soil organic matter content The organic matter content of a soil will depend on: Type of vegetation: Soils that have been in grass for long periods usually have a relatively high percentage of organic matter in their surface. Soils that develop under trees usually have a low organic matter percentage in the surface mineral soil but do contain a surface litter layer (O horizon). Organic matter levels are typically higher in topsoil supporting hay, pasture, or forest than in a topsoil used for cultivated crops. Tillage: Soils that are tilled frequently are typically low in organic matter. Ploughing and otherwise tilling the soil increases the amount of air in the soil, which increases the rate of organic matter decomposition. This detrimental e ect of tillage on organic matter is particularly pronounced in very sandy well-aerated soils because of the tendency of frequent tillage to promote organic matter oxidation to CO2. 170
Fundamental Concepts of Soil Drainage: Soil organic matter is generally higher in poorly drained soils because of limited oxidation, which slows down the overall biological decomposition process. Soil texture: Soil organic matter is generally higher in ne-textured soils because soil humus forms stable complexes with clay particles. E ect of organic matter on soil properties Adequate soil organic matter levels benet soil in several ways. The addition of organic matter improves soil physical conditions, particularly aggregation and pore space. This improvement leads to increased water inltration, improved soil tilth, and decreased soil erosion. Organic matter additions also improve soil fertility, since plant nutrients are released to plant-available mineral forms as organic residues are decomposed (or mineralized). A mixture of organic materials in various states of decomposition helps maintain a good balance of air and water components in the soil. In coarse-textured soils, organic material bridges some of the space between sand grains, which increases water-holding capacity. In ne-textured soil, organic material helps maintain porosity by preventing ne soil particles from compacting. Soil-Water Relationships Water-holding capacity Soil water-holding capacity is determined largely by the interaction of soil texture, bulk density/pore space, and aggregation. Sands hold little water because their large pore spaces allow water to drain freely from the soils. Clays adsorb a relatively large amount of water, and their small pore spaces retain it against gravitational forces. However, clayey soils hold water much more tightly than sandy soils, so that not all the moisture retained in clayey soils is available to growing plants. As a result, moisture stress can become a problem in ne-textured soils despite their high water-holding capacity. Field capacity and permanent wilting percentage The term eld capacity denes the amount of water remaining in a soil after downward gravitational drainage has stopped. This value represents the maximum amount of water that a soil can hold against gravity following saturation by rain or irrigation. Field capacity is usually expressed as percentage by weight (for example, a soil holding 25% water at eld capacity contains 25% of its dry weight as retained water). The amount of water a soil contains after plants are wilted beyond recovery is called the permanent wilting percentage. Considerable water may still be present at this point, particularly in clays, but is held so tightly that plants are unable to extract it. The amount of water held by the soil between eld capacity and the permanent wilting point is the plant- available water. 171
Fundamental Concepts of Soil Tillage and moisture content Soils with a high clay content are sticky when wet and form hard clods when dry. Tilling clayey soils at the proper moisture content is thus extremely important. Although sandy soils are inherently droughty, they are easier to till at varying moisture contents because they do not form dense clods or other high-strength aggregates. Sandy soils are far less compacted as compared to clays, if cultivated wet. However, soils containing high proportions of ne sand may be compacted by tillage when moist. Soil Drainage Soil drainage is the rate and extent of vertical or horizontal water removal during the growing season. Important factors a ecting soil drainage are: Ÿ slope (or lack of slope) Ÿ depth to the seasonal water table Ÿ texture of surface and subsoil layers, and of underlying materials Ÿ soil structure Ÿ problems caused by improper tillage, such as compacted subsoils or lack of surface soil structure Another denition of drainage refers to the removal of excess water from the soil to facilitate agriculture, forestry, or other higher land uses. This is usually accomplished through a series of surface ditches or the installation of subsoil drains. Soil drainage and soil color The nature of soil drainage is usually indicated by soil color patterns (such as mottles) and color variations with depth. Clear, bright red and/or yellow subsoil colors indicate well- drained conditions where iron and other compounds are present in their oxidized forms. A soil is said to be well-drained when the solum (A+E+B horizon) exhibits strong red/yellow colors without any gray mottles. When soils become saturated for signicant periods of time during the growing season, these oxidized (red/yellow) forms of iron are biochemically reduced to soluble forms and can be moved with drainage waters. This creates a matrix of drab, dominantly graycolors. Subsoil zones with mixtures of bright red/yellow and gray mottling are indicative of seasonally uctuating water tables, where the subsoil is wet during the winter/early spring and unsaturated in the summer/early fall. Poorly drained soils also tend to accumulate large amounts of organic matter in their surface horizons because of limited oxidation and may have very thick and darkAhorizons. 172
Fundamental Concepts of Soil Soils that are wet in their upper 12 inches for considerable amounts of time during the growing season and that support hydrophytic vegetation typical of wetlands are designated as hydric soils. Drainage mottles in these soils are referred to as redoximorphic features. Drainage classes The drainage class of a soil denes the frequency of soil wetness as it limits agricultural practices and is usually determined by the depth in soil to gray mottles or other redoximorphic features. The soil drainage classes in Table 11.2 are dened by the USDA- NRCS. They refer to the natural drainage condition of the soil without articial drainage. Table 11.2 : Soil drainage classes Drainage Class Soil Characteristics E ect on Cropping Excessively drained Water is removed rapidly from soil. Well drained Will probably require supplemental Moderately well drained irrigation. Somewhat poorly drained Water is removed readily, but not rapidly. No drainage required. Poorly drained Very poorly drained Water is removed somewhat slowly at May require supplemental drainage if some periods of the year. crops that require good drainage are grown. Water is removed so slowly that soil is wet at Will probably require supplemental shallow depths periodically during the drainage for satisfactory use in growing season. production of most crops. Free water is present at or near the surface during the growing season Soil Chemical Properties The plant root obtains essential nutrients almost entirely by uptake from the soil solution. The chemistry and nutrient content of the soil solution is, in turn, controlled by the solid material portion of the soil. Soil chemical properties, therefore, reect the inuence of the soil minerals and organic materials on the soil solution. Soil pH Soil pH denes the relative acidity or alkalinity of the soil solution. The pH scale in natural systems ranges from 0 to 14. A pH value of 7.0 is neutral. Values below 7.0 are acid and those above 7.0 are alkaline, or basic. Soil pH is a measurement of hydrogen ion (H+) activity, or e ective concentration, in a soil and water solution. Soil pH is expressed in logarithmic terms, which means that each unit change in soil pH amounts to a tenfold change in acidity or alkalinity. For example, a soil with a pH of 6.0 has 10 times as much active H+ as one with a pH of 7.0. 173
Fundamental Concepts of Soil Soils become acidic when basic cations (such as calcium, or Ca2+) held by soil colloids are leached from the soil, and are replaced by aluminum ions (Al3+), which then hydrolyze to form aluminum hydroxide (Al(OH)3) solids and H+ ions in solution. This long-term acidication process is accelerated by the decomposition of organic matter which also releases acids to soil solution. Cation exchange capacity (CEC) The net ability of a soil to hold, retain, and exchange cations (positively charged ions) such as calcium (Ca2+), magnesium (Mg2+), potassium (K+), sodium (Na+), ammonium (NH4+), aluminum (Al3+), and hydrogen (H+) is called cation exchange capacity, or CEC. All soils contain clay minerals and organic matter that typically possess negative electrical surface charges. These negative charges are present more than any positive charges that may exist, which gives soil a net negative charge. Negative surface charges attract positively charged cations and prevent their leaching. These ions are held against leaching by electrostatic positive charges, but are not permanently bound to the surface of soil particles. Positively charged ions are held in a “di use cloud” within the water lms that are also strongly attracted to the charged soil surfaces. Cations that are retained by soils can thus be replaced, or exchanged, by other cations in the soil solution. For example, Ca2+ can be exchanged for Al3+ and/or K+, and vice versa. The higher a soil's CEC, the more cations it can retain. There is a direct and positive relationship between the relative abundance of a given cation in solution and the amount of this cation that is retained by the soil CEC. For example, if the predominant cation in the soil solution of a soil is Al3+, Al3+ will also be the predominant exchangeable cation. Similarly, when large amounts of Ca2+ are added to soil solution by limes dissolving over time, Ca2+ will displace Al3+ from the exchange complex and allow it to be neutralized in solution by the alkalinity added with the lime. The CEC of a soil is expressed in terms of moles of charge per mass of soil. The units used are cmol+/kg (centimoles of positive charge per kilogram) or meq/100g (milliequivalents per 100 grams; 1.0 cmol+/kg = 1.0 meq/100g). Soil CEC is calculated by adding the charge equivalents of K+, NH4+, Ca2+, Mg2+, Al3+, Na+, and H+ that are extracted from a soil's exchangeable fraction. Sources of negative charge in soils The mineralogy of the clay fraction greatly inuences the quantity of negative charges present. One source of negative charge is isomorphous substitution, which is the replacement of a Si4+ orAl3+ cation in the mineral structure with a cation with a lower surface charge. For example, Si4+ might be replaced with Al3+, or Al3+ with either Mg2+ or Fe2+. Clay minerals with a repeating layer structure of two silica sheets sandwiched around an aluminum sheet (2:1 clays, such as vermiculite or smectite), typically have a higher total negative charge than clay minerals with one silica sheet and one aluminum sheet (1:1 clays, such as kaolinite). 174
Fundamental Concepts of Soil Soil pH also has a direct relationship to the quantity of negative charges contributed by organic matter and, to a lesser extent, from mineral surfaces such as iron oxides. As soil pH increases, the quantity of negative charges increases and vice versa. This pH dependent charge is particularly important in highly weathered topsoils where organic matter dominates overall soil charge. Cation mobility in soils The negatively charged surfaces of clay particles and organic matter strongly attract cations. However, the retention and release of these cations, which a ects their mobility in soil, is dependent on several factors. Two of these factors are the relative retention strength of each cation and the relative amount or mass of each cation present. For a given cation the relative retention strength by soil is determined by the charge of the ion and the size, or diameter of the ion. In general, the greater the positive charge and the smaller the ionic diameter of a cation, the more tightly the ion is held (i.e., higher retention strength) and the more di cult it is to force the cation to move through the soil prole. For example, Al3+ has a positive charge of three and a very small ionic diameter and moves through the soil prole very slowly, while K+ has a charge of one and a much larger ionic radius, so it leaches much more readily. If cations are present in equal amounts, the general strength of adsorption that holds cations in the soil is in the following order: Al3+>> Ca2+> Mg2+> K+ = NH4+> Na+ E ect of CEC on soil properties A soil with a low CEC value (1-10 meq/100 g) may have some, or all, of the following characteristics: · high sand and low clay content · low organic matter content · low water-holding capacity · low soil pH · will not easily resist changes in pH or other chemical changes · enhanced leaching potential of plant nutrients such as Ca2+, NH4+, K+ · low productivity A soil with a higher CEC value (11-50 meq/100g) may have some or all of the following characteristics: 175
Fundamental Concepts of Soil · low sand and higher silt + clay content · moderate to high organic matter content · high water-holding capacity · ability to resist changes in pH or other chemical properties · less nutrient losses to leaching than low CEC soils Base saturation Of the common soil-bound cations, Ca2+, Mg2+, K+, and Na+ are considered to be basic cations. The base saturation of the soil is dened as the percentage of the soil's CEC (on a charge equivalent basis) that is occupied by these cations. A high base saturation (>50%) enhances Ca, Mg, and K availability and prevents soil pH decline. Low base saturation (<25%) is indicative of a strongly acid soil that may maintain Al3+ activity high enough to cause phytotoxicity. Bu ering capacity The resistance of soils to changes in pH of the soil solution is termed bu ering. In practical terms, bu ering capacity for pH increases with the amount of clay and organic matter. Thus, soils with high clay and organic matter content (high bu er capacity) will require more lime to increase pH than sandy soils with low amounts of organic matter (low, or weak, bu er capacity). Conclusion Soil is a basic and fundamental component of agriculture which performs multifaceted functions like providing food, fuel, feed and bre needs of the burgeoning populations, regulating the quality of the atmosphere and water, decomposing organic waste, recycling nutrients and ltering pollutants. This natural resource base need to be explored with respect to the physical, chemical and live components and this implications and manifestation is necessary to open the hidden treasure present in the soil. These will not only help to improve the living standard of humans but also help to develop best management practices for farmers to improve production and sustaining their productivity. References Brady NC, and Weil RR (2001). The nature and properties of soils (13th ed.) PrenticeHall, Upper Saddle River, NJ. Das DK (2003). Introductory Soil Science, Kalyani Publishers. Sposito G and Reginato R (1992). Opportunities in Basic Soil Science Research. Wisconsin, Madison, SSSA, 109. 176
12 SOIL NUTRIENT DEFICIENCIES AS REFLECTED IN CROPS/PLANTS Paromita Ghosh Abstract There are 17 essential plant nutrients and if any one of the nutrients is decient then plant growth will slow down even if other essential nutrients are adequately available. Therefore, for obtaining maximum yield potential there is need to have a proper balance of nutrients. Majority of small farmers do not have enough resources to get their soil and plants tested in accredited laboratories. Therefore, for obtaining maximum yield potential there is need to have a proper balance of nutrients. Majority of small farmers do not have enough resources to get their soil and plants tested in accredited laboratories. Therefore, it is essential to train them to identify visual deciency symptoms in plants that reect the deciency in soil. Many times, farmers apply overdose of fertilizers that again lead to soil nutrient toxicity and soil quality deterioration. So plant nutrition management for food security and protection of environment calls for low cost yet e cient awareness and skill building programme for small farmers and rural youth associated with agriculture where visual identication of deciency and toxicity symptoms need to be taught in class and then on eld hands on training be provided. The lecture note describes the importance of plant nutrients, their function and how to identify the deciency and toxicity through visual symptoms in crops and plants and potential limitations of visual diagnosis. Keywords: Plant/soil nutrients, micronutrients, deciency, toxicity, visual symptoms, Introduction The plant nutrient functions and deciency and toxicity symptoms module is extension material designed for agro-consultants and producers with relevant information on nutrient management issues. This lecture note was created under the green skill building program with the following objectives: Paromita Ghosh, Ph.D. Centre for Socio-Economic Development G. B. Pant National Institute of Himalayan Environment, Kosi - Katarmal, Almora paroghosh@redi mail.com Monitoring and A ssessment of Environmental Parameters Eds. V. A gnihotri, S. Rai, A . Tiwari, S. Mukherjee, K. Kumar, R. Joshi, GBPNIHE, A lmora, Uttarakhand, India ©GBPNIHE 2020 177
Soil Nutrient Deciencies as Reected in Crops/Plants 1. To help farmers and practioners recognize plant nutrient deciency and toxicity symptoms in the eld by diagonizing external symptoms. 2. Know potential limitations of visual diagnosis. 3. Understand how to use the key for identifying symptoms and 4. Distinguish between mobile and immobile nutrient deciencies. Plant nutrition is the study of the chemical elements and compounds necessary for plant growth, plant metabolism and their external supply. In 1972, Emanuel Epstein dened two criteria for an element to be essential for plant growth: 1. In its absence the plant is unable to complete a normal life cycle. or 2. The element is part of some essential plant constituent or metabolite. Essential plant nutrients include carbon, oxygen and hydrogen which are absorbed from the air where as other nutrients including nitrogen are typically obtained from the soil (exceptions include some parasitic or carnivorous plants)\". The seventeen most important nutrients are listed as per category below. Macronutrients, used in relatively large amounts (> 0.1% of dry plant tissue): Nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), sulfur (S), magnesium (Mg), (Brady and Weil, 2002) Micronutrients (or trace minerals) used in relatively small amounts (0.1% of dry plant tissue): Iron (Fe), boron (B), chlorine (Cl), manganese (Mn), Zinc (Zn), copper (Cu), molybdenum (Mo), nickel (Ni), sodium (Na), silicon (Si) and Cobalt (Co) (Brady and Weil, 2002). These elements stay beneath soil as salts, so plants consume these elements as ions. Plants absorb the elements in the form of ions. Those elements that are consumed in large quantities are called macronutrients. They constitute 95% of plant biomass on dry matter basis (Table 12.1). 178
Soil Nutrient Deciencies as Reected in Crops/Plants Table 12.1 : Typical ranges of macronutrients concentrations in mature leaf tissues Nutrient Decient Su cient (normal) Excessive (Toxic) (%) Nitrogen <2.50 2.50 - 4.50 >6.0 Phosphorus <0.15 0.20 - 0.75 >1.0 Potassium <1.0 1.50 - 5.50 >6.0 Sulfur <0.20 0.25 - 1.00 >3.0 Calcium <0.50 1.00 - 4.00 >5.0 Magnesium <0.20 0.25 - 1.00 >1.5 (Source: IPNI (International Plant Nutrition Institute)) Carbon, hydrogen, and oxygen are supplied by either air or water. Micronutrients are present in plant tissue in quantities measured in parts per million, ranging from 0.1 to 200 ppm or less than 0.02% dry weight (Table 12.2). Table 12.2: Typical ranges of micronutrients concentrations in mature leaf tissues Nutrient Decient Su cient (normal) Excessive (Toxic) (ppm) Boron 5-30 10-200 50-200 Chloride <100 100-500 500-1000 Copper 2-5 5-30 20-100 Iron <50 100-500 >500 Manganese 15-25 20-300 300-500 Molybdenum 0.30-0.15 0.1-2.0 >100 Zinc 10-20 27-100 100-400 (Source: IPNI (International Plant Nutrition Institute)) 179
Soil Nutrient Deciencies as Reected in Crops/Plants Plants can adapt to climate and soil conditions and complete their life cycle in natural conditions in most soil types found across the world even when fertilizer is not applied. However, if the soil is cropped it is necessary to articially modify soil fertility through the addition of fertilizers to promote growth and sustain yield. A balanced and optimum use of fertilizers can help farmers to achieve crop production targets for food security and improve the livelihood of small farmers. Majority of small farmers do not have enough resources to get their soil and plants tested for nutrient deciencies in accredited laboratories, therefore it is essential to train them to identify visual deciency symptoms in plants that reect the deciency in soil. Sometimes farmers also apply overdose of fertilizers that again leads to soil nutrient imbalance and nutrient antagonism and consequently soil quality deteriorates. Most of the nutrient deciency's symptoms are normally visible in leaves. Some of the common deciency symptoms are presented in Table 12.3. The present study aims to describe the visible symptoms used in diagnosing nutrient deciency symptoms in plants/crops. Table 12.3 : Nutrient deciency symptoms Nutrient Position on Chlorosis Leaf margin Colour and N plant necrosis leaf shape Yes All leaves No Yellowing of No leaves and leaf Yes veins Yes P Older leaves Yes No Purplish patches K Older leaves Yes Mg Older leaves Yes Yes Yellow patches Ca Young leaves S Young leaves - No Yellow patches Mn, Fe Young leaves No Yellow leaves No Yellow leaves No Interveinal chlorosis B, Zn, Cu, Mo Young leaves - Deformed leaves 180
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