Asim Biswas

Effect of rice-husk biochar on selected soil properties in tropical Alfisols

Despite the large number of studies on biochar and soil properties, few studies have investigated the effects of biochar in contrasting soils. A study was conducted including four rice-husk biochar rates (0%, 0.1%, 0.5% and 1%) to understand the effects on selected soil properties of two Alfisols (sand and sandy loam) in Sri Lanka. Significant changes in soil properties including increases in pH, cation exchange capacity (CEC), organic carbon, water retention at field capacity and saturated hydraulic conductivity, and reduction in bulk density, were observed at higher rates of biochar (0.5% and 1%). Mean-weight-diameter increased only at 1% biochar application rate in sandy soil, whereas it significantly increased across all the rates in sandy loam soil over the control. Electrical conductivity showed no significant increase in either soil, indicating no threat of salinity. Biochar showed a potential for ameliorating acidity, especially in slightly acidic sandy soil. Soil aggregation and water flow improved markedly in sandy loam soil over sandy soil. Further, CEC and water retention of sandy soil had pronounced effects compared with sandy loam soil. Our study highlights the importance of soil type in determining the value of rice-husk biochar as a soil amendment to improve soil aggregation, water retention and flow and CEC.

Comprehensive Approaches in Rehabilitating Salt Affected Soils: A Review on Indian Perspective

Land, a non-renewable resource, is central to all primary production system. Increasing pressure of populationgrowth, economic development, climate change, land use changes, and environmental pollutionlead to different types of land degradation including salinization. Salt affected soils are normally uncultivated, uninhabited bare lands with poor quality and suffer from different stress conditions. These soils are generally not conducive for regeneration of vegetation. Salt affected soils are usually barren but potentially productive. Rehabilitation includes control of extension of salt affected soils, its reclamation, stabilization and eco-restoration. The rehabilitation of these lands is common through chemical means and engineering approaches. Extension of salt affected soils is controlled by utilizing the resource on sustainable basis. Good quality irrigation water and sufficient drainage facility accompanying with other physical measures help in reclamation of soil. Chemical reclamation requires different types of amendments for different soils. Biological reclamation of salt affected soil is more important from stabilization of soil quality and eco-restoration points of view. Selection of salt tolerant plants and crops are very important for cultivation in salt affected soils. Improved production systems including horticultural, pastoral, agri-horticultural, silvi-pastoral, silvi-cultural, agroforestry are the components of integrated farming system in bio-saline agriculture. The judicious use of the reclaimed lands for different production purposes and restoration of quality of soil through people’s participation in rehabilitative work is the way to get out of problem of salt affected soil.

Application of Multifractal and Joint Multifractal Analysis in Examining Soil Spatial Variation: A Review

© 2012 Biswas et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Application of Multifractal and Joint Multifractal Analysis in Examining Soil Spatial Variation: A Review

The Effects of Forest Fire on Soil Organic Matter and Nutrients in Boreal Forests of North America: A Review

Fire is the primary disturbance process affecting the structures and ecosystem functions of a forest by altering the carbon balance and nutrient dynamics of forest soils. A great deal of research indicates that frequency, severity, duration of forest fire will increase especially in boreal forest region with the increase in temperature and severe droughts resulting from climate change. However, with the large area and abundant biodiversity, boreal forest plays a vital role in mitigating climate change and acting as a carbon pool. Therefore, if the boreal forest is damaged by fires, it will incur a catastrophe on the ecosystem and the climate. With increasing risk of future fire activities, it is extremely important to understand the dynamic changes of soil resources as affected by fires which can give a crucial information on sustainable and adaptive management practices of forests and soils, as well as determine the resilience of forest soils to mitigate current climate change. In this paper, we review the main fire regimes and characteristics of boreal forests in North America and the dynamics of organic matter and nutrients in forest soils over short and long-term after fire. This work aims at providing useful knowledge on soil resource dynamics under fire disturbance which will further promote the adaptive management of forest soils.

Drivers of spatio-temporal changes in paddy soil pH in Jiangxi Province, China from 1980 to 2010

The spatio-temporal distribution soil pH is critical for understanding the productivity and long-term sustainability of our agri-ecosystem. This study quantified the spatio-temporal distribution of paddy soil pH in Jiangxi province, China, and the potential driver of the change between 1980 and 2010. Data from the Soil Survey Information of Jiangxi province (1980s) and Jiangxi Soil Testing and Fertilizer Recommendation study (2010s) were collected and categorized into six pH ranges from strongly-acidic to strongly-alkaline with unit pH differences. Changes were calculated from the maps developed using the Pedological Knowledge base for 1980s data (without geolocation) and geostatistical methods for the 2010s data (geolocated). An overall 0.6-unit decrease and a major shift of soil pH from weakly-acidic (54% → 18%) to acidic (35% → 74%) was observed over the province in a scattered fashion with concentration in the central part and the Poyang Lake area. About half of the area under paddy cultivation went through acidification by at least one pH unit and 7% by at least 2 pH units, while 40% of the area remained unchanged. Excessive fertilizer application and acid-rain intensity contributed to the acidification. Thus, a more knowledge-based and comprehensive fertilizer management should be adopted to make paddy production sustainable in the province.

Characterizing soil particle sizes using wavelet analysis of microscope images

Abstract Soil texture (relative proportions of soil particles of varied sizes) is a fundamental soil physical property affecting almost all other soil physical properties and processes of agricultural, environmental and engineering importance. However, characterization of particle sizes in the laboratory presents a range of challenges in terms of the time, labor, difficulty and/or cost involved with the analysis. Continuous wavelet transform (CWT) has been used in characterizing scale-specific variations in spatial or temporal domain as well as in image analysis. The objective of this study was to develop a CWT-based computer vision algorithm to characterize soil particle sizes from digital images captured with a microscope. A cheap portable microscope with 5 MP camera and maximum magnification of 200× was used to develop an image acquisition system. Three images of air-dried, ground (2 mm) soil samples were captured in laboratory conditions for each soil sample (56 + 67 = 123) collected from two agricultural fields (Field26 and Field86) with highly variable soils. Triplicate in-situ images were also collected from 67 locations from Field86 after scrapping off surface residues. The color images were transferred to grey-scale images and the CWT was performed along the 20 equally-spaced rows and columns. The total area under the average global wavelet spectrum represented the total variation in any image. Two fractions of particle sizes; ‘coarse’ (diameter between 2.0 mm and 0.05 mm) and ‘fine’ (diameter

Temporally stable patterns but seasonal dependent controls of soil water content: evidence from wavelet analyses

Scale- and location-dependent relationships between soil water content (SWC) and individual environmental factors have been widely explored. SWC is controlled by multiple factors concurrently; however, the multivariate relationship is rarely explored at different scales and locations. Multivariate controls of SWC at different scales and locations in two seasons within a hummocky landscape of North America were identified using bivariate wavelet coherency and multiple wavelet coherence. Results showed that depth to CaCO3 layer which was correlated with elevation over all locations at scales of 36–144 m and cos(aspect) provided the best individual factor for explaining SWC variations in the spring (May 2) and summer (August 23), respectively. Although spatial patterns of SWC were temporally stable, different topographic indices affected spatial distribution of SWC in different seasons (elevation in spring and aspect in summer) due to different dominating hydrological processes. These varying hydrological processes also resulted in the distinct role of soil organic carbon (SOC) content in different seasons: a positive correlation in the spring and a negative correlation in the summer. Multiple wavelet coherence identified a combination of depth to CaCO3 layer and SOC in spring and a combination of cos(aspect) and SOC in summer that controlled SWC at different scales and locations, respectively. This indicated a combined effect of soil and topographic properties on SWC distribution and a clear need for these two factors in developing scale-dependent prediction of SWC in the hummocky landscape of North America.

Soil Water Measurement Using Actively Heated Fiber Optics at Field Scale

Several studies have demonstrated the potential of actively heated fiber optics (AHFO) to measure soil water content (SWC) at high spatial and temporal resolutions. This study tested the feasibility of the AHFO technique to measure soil water in the surface soil of a crop grown field over a growing season using an in-situ calibration approach. Heat pulses of five minutes duration were applied at a rate of 7.28 W m−1 along eighteen fiber optic cable transects installed at three depths (0.05, 0.10 and 0.20 m) at six-hour intervals. Cumulative temperature increase (Tcum) during heat pulses was calculated at locations along the cable. While predicting commercial sensor measurements, the AHFO showed root mean square errors (RMSE) of 2.8, 3.7 and 3.7% for 0.05, 0.10 and 0.20 m depths, respectively. Further, the coefficients of determination (R2) for depth specific relationships were 0.87 (0.05 m depth), 0.46 (0.10 m depth), 0.86 (0.20 m depth) and 0.66 (all depths combined). This study showed a great potential of the AHFO technique to measure soil water at high spatial resolutions (<1 m) and to monitor soil water dynamics of surface soil in a crop grown field over a cropping season with a reasonable compromise between accuracy and practicality.

Identifying localized and scale-specific multivariate controls of soil organic matter variations using multiple wavelet coherence

Environmental factors have shown localized and scale-dependent controls over soil organic matter (SOM) distribution in the landscape. Previous studies have explored the relationships between SOM and individual controlling factors; however, few studies have indicated the combined control from multiple environmental factors. In this study, we compared the localized and scale-dependent univariate and multivariate controls of SOM along two long transects (northeast, NE transect and north, N transect) from China. Bivariate wavelet coherence (BWC) between SOM and individual factors and multiple wavelet coherence (MWC) between SOM and factor combinations were calculated. Average wavelet coherence (AWC) and percent area of significant coherence (PASC) were used to assess the relative dominance of individual and a combination of factors to explain SOM variations at different scales and locations. The results showed that (in BWC analysis) mean annual temperature (MAT) with the largest AWC (0.39) and PASC (16.23%) was the dominant factor in explaining SOM variations along the NE transect. The topographic wetness index (TWI) was the dominant factor (AWC = 0.39 and PASC = 20.80%) along the N transect. MWC identified the combination of Slope, net primary production (NPP) and mean annual precipitation (MAP) as the most important combination in explaining SOM variations along the NE transect with a significant increase in AWC and PASC at different scales and locations (e.g. AWC = 0.91 and PASC = 58.03% at all scales). The combination of TWI, NPP and normalized difference vegetation index (NDVI) was the most influential along the N transect (AWC = 0.83 and PASC = 32.68% at all scales). The results indicated that the combined controls of environmental factors on SOM variations at different scales and locations in a large area can be identified by MWC. This is promising for a better understanding of the multivariate controls in SOM variations at larger spatial scales and may improve the capability of digital soil mapping.

Sampling Designs for Validating Digital Soil Maps: A Review

Abstract Sampling design (SD) plays a crucial role in providing reliable input for digital soil mapping (DSM) and increasing its efficiency. Sampling design, with a predetermined sample size and consideration of budget and spatial variability, is a selection procedure for identifying a set of sample locations spread over a geographical space or with a good feature space coverage. A good feature space coverage ensures accurate estimation of regression parameters, while spatial coverage contributes to effective spatial interpolation. First, we review several statistical and geometric SDs that mainly optimize the sampling pattern in a geographical space and illustrate the strengths and weaknesses of these SDs by considering spatial coverage, simplicity, accuracy, and efficiency. Furthermore, Latin hypercube sampling, which obtains a full representation of multivariate distribution in geographical space, is described in detail for its development, improvement, and application. In addition, we discuss the fuzzy k-means sampling, response surface sampling, and Kennard-Stone sampling, which optimize sampling patterns in a feature space. We then discuss some practical applications that are mainly addressed by the conditioned Latin hypercube sampling with the flexibility and feasibility of adding multiple optimization criteria. We also discuss different methods of validation, an important stage of DSM, and conclude that an independent dataset selected from the probability sampling is superior for its free model assumptions. For future work, we recommend: 1) exploring SDs with both good spatial coverage and feature space coverage; 2) uncovering the real impacts of an SD on the integral DSM procedure; and 3) testing the feasibility and contribution of SDs in three-dimensional (3D) DSM with variability for multiple layers.