Soil Mapping Units Research Articles

Characterization and Evaluation of Land Resources of Valia Block, Bharuch District, Gujarat

Detailed soil survey (1:10000 scale) was carried out using base map prepared from satellite data (IRS-P6 LISS IV and Cartosat-1) and Digital Elevation Models (DEM) in conjunction with Survey of India (SOI) Toposheets of 1:50000 scale in Valia block, Bharuch district of Gujarat. On the basis of landform, slope, land use/land cover and ground truth, six landscape ecological Units (LEUs) were delineated and six soil series were identified in the block. Five soil series occur on alluvial plain (cover 66.16 %) and one soil series occupies pediplain 27.61 %. These series were mapped into ten soil mapping units as phases of soil series. The representative pedons of alluvial plain were moderately deep to very deep and their sand, silt and clay content ranged from 8.2 to 44.4, 9.8 to 40.2 and 43.8 to 55.6 per cent, respectively. These pedons were neutral to strongly alkaline (pH 6.8 - 9.7), non-saline with low to high organic carbon (0.18 – 1.2 %) content, low to high calcium carbonate (5.9 - 26.6 %) and high CEC [>35 cmol (p+) kg-1]. Exchangeable complex of these pedons were dominated by Ca2+ followed by Mg2+, Na+ and K+ cations with high base saturation (72.0 to 99. 4 %). Soils were classified as Vertic Haplustepts, Typic Haplusterts, Typic Calciustepts, Typic Haplustepts and Sodic Haplusterts. The representative pedon of pediplains was shallow, dark brown (7.5YR3/2), clayey, strongly alkaline (pH>8.5), non-saline (<2 dSm-1) and had moderate organic carbon (0.50-0.75 %) and calcium carbonate (5-15 %) with high CEC [>35 cmol (p+) kg-1] and classified as Lithic Haplustepts. The soils were evaluated for their suitability for commonly grown crops (cotton, pigeon pea, wheat and chick pea) and mapping unit 2 and 4 were highly suitable for cotton cultivation and other were moderately to marginal suitable for other crops.

Characterization and Suitability Evaluation of Soils of Chanavada Watershed in Aravalli Hills of Southern Rajasthan, for Optimum Land Use Planning

A detailed soil survey was carried out to characterize and classify the soils of Chanavada micro-watershed in Girwa tehsil of Udaipur district, Rajasthan using cadastral map overlaid on IRS P6 LISS IV images of October 2007 and March 2008 as a base. Based on the visual interpretation of satellite data, other collateral data and local micro features six landforms units viz. Steeply sloping hills, Moderately steeply sloping hills, Moderately sloping foot slope, Inter hill valley, Narrow valley and Broad valley were delineated. Tentatively eight soil series were identified in the watershed and mapped into 15 soil mapping units at the level of phases of soil series on 1: 4000 scales after establishing soil landform relationship. These soils were classified as Entisols (Lithic Ustorthents, Typic Ustorthents) and Inceptisols (Typic Haplustepts, Fluventic Haplustepts). The soils of the steeply sloping and moderately steeply sloping hills are very shallow to moderately shallow, excessively drained, dark yellowish brown, gravelly loam to gravelly sandy loam (surface horizon) soils with very severe soil erosion. The soils of moderately sloping foot slope are moderately deep to deep, well-drained, dark brown (10 YR 3/3) to very dark greyish brown (10 YR 3/2) sandy clay loam soils with severe erosion. The soils of the valley are deep, well-drained, very dark greyish brown (10 YR 3/2) to dark yellowish-brown (10 YR 3/4), sandy clay loam to loam on the surface and dark grey (7.5YR3/1) silt loam in sub-surface horizons with severe erosion. The soils of the hills were slightly acidic to neutral in reaction whereas the soils of the valley were neutral to moderately alkaline in reaction. All these soil were very high in organic carbon content on the contrary the content of available nitrogen is low. Most of the soils are medium to high in available phosphorous and available potassium whereas the content of available micronutrients was adequate to high. The soils of the hills are not suitable for arable field crops and the soils of foot slope and narrow valley were marginal to moderately suitable for growing crops. The soils of the broad valley were good cultivable lands with minor soil problems such as gentle slope, fairly satisfactory texture and slight stoniness. All climatically adapted crops can be grown under irrigation.

Digital soil mapping for site-specific management of soils

Classification of fields into management zones based on variability of soil fertility parameters is under use in precision agriculture. The study was conducted in west Wollega zone of Ethiopia covering nearly 40 km2 of agricultural land, with the aim to explain variability of soils in the field, classify soils into mapping units and produce a map of these soils at a scale of 1:10000 using geostatistics. In this paper, soil mapping units (SMUs) were interchangeably used with management zones. Ten SMUs were identified in the study site. The SMU mean pH value varied between 5.3 in the SMU6 and 6.4 in the SMU7. Variation in soil texture, pH, exchangeable acidity, exchangeable potassium (K), calcium (Ca), magnesium (Mg), sodium (Na), cation exchange capacity (CEC), organic carbon (OC), total nitrogen (TN), and plant available phosphorus (AvP), were observed within and among SMUs. Variability of soil parameters ranged from 1.06% (Na) in the SMU5 to 172.94% (AvP) in the SMU8. The OC and AvP content of all SMUs were found in the very low and low critical ranges. Intensive grid sampling had helped to produce digital soil maps and exposed soil heterogeneity across the landscape. We suggest that classification of fields into management zones was a remedy to low crop production occurred from uniform applications of nutrients and chemical amendments to significantly varying soils.

Evaluation of land suitability on arabica coffee plantation by parametric method in Lintongnihuta District

This study aims to establish the land suitability class and improvement efforts that need to be done in each of the Soil Map Unit (SMU) on arabica coffee fields in Lintongnihuta district. Results of overlaying the map of soil type, the map of altitude and slope map with a scale of 1: 50,000 produced 13 SMU. Evaluation of several soil characteristics (texture, coarse fragment, CaCO3 and salinity) must consider the appropriate soil depth, where the normal root depth of the Arabica coffee plant is 150 cm, so that it uses 6 (six) parts of the depth of the soil with a depth of 25 cm for each section. Correction indexes used in succession are: 2.00 - 1.5 - 1.00 - 0.75 - 0.5 - 0.25.The results showed that all SMU in Arabica coffee land in Lintongnihuta District has the actual land suitability class S3 (f) (marginally suitable, limiting factor: soil fertility). Improvement efforts that can be done are: giving lime, organic material, fertilization and reclamation. All SMU has the potential land suitability classS2 (c,s)(moderately suitable, limiting factor: climate and natural soil).

Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework

Core Ideas Digital modeling framework for mapping ecological land units was developed. Digital maps eliminate spatial ambiguity of multicomponent soil map units. Spatial scale of modeling products can be optimized to meet management needs. National coverage of the training and covariate data provides ability to scale. Ecological site descriptions (ESDs) and associated state‐and‐transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing‐based spatial covariates (e.g., hyper‐temporal remote sensing, terrain attributes, climate data, land‐cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10‐fold cross‐validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly‐defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly‐defined ESG classes. Model accuracies were also evaluated using external‐validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national‐scale mapping effort of ecological sites.

Soil Fertility Status in Relation to Farmers’ Practices Under Maize Based Systems in Western Region of Kenya: Yield Gap Analysis

A study was carried out in Kenya Cereal Enhancement Project site in Western region of Kenya to examine the soil fertility status in relation to the current blanket fertilizer recommendations and farmers’ practices across the four wards, namely: Motosiet, Keiyo, Cherangani and Kwanza. The baseline fertility status in different soil mapping units was assessed in terms of soil productivity index with a view of analyzing the levels of nutrients and yield gaps. Using the standard soil survey procedures, six soil mapping units were identified as UUr1, UUr2, UUr3, RUd, RUrb, and BU1.. The results showed that the highest productivity index was in unit BU1, followed by UUr1, UUr2, UUr3, and RUrb with values of 40.5, 29.4, 25.0, 16.0 and 8.9% respectively. Keiyo Ward had the highest level of nitrogen, being 125.82, followed by Motosiet, Cherangani and Kwanza with values of 99.92, 97.12, and 81.12 kg/ha respectively. Phosphorous level was highest in Kwanza (136.41 kg/ha), followed by Cherangani (106.82 kg/ha) and Keiyo Ward (76.08 kg/ha). The lowest level was recorded in Motosiet with the value of 72.56 kg/ha. Potassium was found to be adequate in all the four Wards with values ranging between 347.67 and 410.34 kg/ha. The maximum maize production recorded in the project sites was 9,000 kg/ha, with a yield gap of 1,000 kg/ha. This was achieved through application of 100 and 50 kg/ha of DAP and CAN respectively. This was followed by 6,750 kg/ha obtained through application of 50 kg/ha of DAP and CAN. The yields from the rest of the sites ranged between 1,800 and 4,500 kg/ha with yield gaps varying from 3,250 to 8,650 kg/ha. The lowest yields were obtained in Keiyo, followed by Kwanza Ward despite the relatively high macro- nutrient levels in the soils of the two Wards. This was attributed to soil-related constraints caused by the increased soil structural degradation and loss of soil tilth. Therefore, it is recommended that the envisaged climate smart technologies be geared towards enhancement of nutrient and water use efficiency through improved soil structure and tilth.

Land Capability Classification of Wadi Jerafi Basin, North Sinai Egypt

The Egyptian Government pays a great attention nowadays to encourage the agricultural investment in Sinai Peninsula. The current study focused on wadi Jerafi which is one of the most promising areas in North Sinai Governorate. The goal of this study is to evaluate the land capability classification of Wadi Jerafi basin using two universal software’s systems, namely as: MicroLEIS DSS (Cervatana Model) as semi-quantitative approach and Revised Storie Index as parametric approach. Accordingly, a grid soil survey was done through a total of 137 soil profiles. These soil profiles were investigated and sampled, then were chemically and physically analyzed. Based on soil variation in depth, gravel content and soil texture, seven soil mapping units (SMU) were delineated and evaluated to assess their agricultural capability. Cervatana Model classified the studied area into two capability classes; good capability (S2l) covering the largest area (63.25 %) and marginal capability (S3l) covering the lowest area (36.75 %). The most limiting factors are soil depth, gravel content, soil texture and/or salinity. On the other hand, Revised Storie Index (using Storie method equation) divided the land capability of the studied area into two classes unsuitable (N) which covers of about 60.87 % of the total area and marginal suitable (S3) covering of about 39.13 % of the total area. Another method of capability index calculation called Square Root Method was applied and therefore it distinguished three capability classes; moderately suitable (S2) covering 8.87 % of the total area, marginal suitable (S3) covering 75.39 % of the total area and unsuitable (N) covering 15.74 % of the total area. Accordingly, this paper recommend to implement Revised Storie Index as a parametric approach to evaluate the rate of each soil parameter and to use Square Root method to calculate the capability index of each mapping unit.

Land suitability evaluation of Kubanni floodplain for rice production in Zaria, Kaduna State, Nigeria

Land suitability evaluation analysis is necessary to achieve optimum management and utilization of the available land resources for sustainable agricultural crops production. The objective of this study was to determine the suitable of Kubanni floodplain for rice production in Zaria Kaduna State Nigeria. Qualitative and quantitative land suitability evaluation of two mapping units in Kubanni floodplain which covers an area of 11.6 ha was carried using the detailed soil survey method of classification. Generally, the surface texture was sandy loam to loam. The soil reactions were slightly acidic to neutral, organic carbon, available phosphorus and total nitrogen were rated low. The CEC (NH4OAc) were medium and Base saturation was rated high while EC and ESP were low. Qualitatively, soil mapping units KBI and KBII were currently not suitable (N1) for rice production due to limitation imposed by soil chemical properties. Quantitatively the two units were also currently not suitable (N1) but KBII was marginally suitable (S3) potentially. With proper soil fertility management, the potentials of these soils can be raise to moderately suitable (S2) for rice through increase in organic matter to improve soil structural development, drainage and aeration thereby improving the fertility of the soils.

The effect of land use change on soil fertility parameters in densely populated areas of Kenya

The current study seeks to assess sustainability of agricultural land use by identifying the effect of land use change on soil quality using cross-sectional data collected through a household survey among 525 farm households in densely populated areas of Kenya. Soil samples were collected, analyzed and compared across three land use types: undisturbed, semi-disturbed and cultivated. To achieve these objectives, descriptive, Nutrient Index approach and Classification and Regression Tree (CART) analysis methods were used. Results indicate that within a period of five decades, agricultural land use has led to a decline in Total Organic Carbon (−72%), Magnesium (−65%) and Boron (−61%), Iron (−22%) and Total Nitrogen (−15%). The drivers of deterioration identified were cutting across inherent properties such as soil chemical (pH), physical (soil mapping unit) and biological (organic carbon) attributes, farmer practices (agricultural commercialization) and exogenous factors (population density and Agro-ecological zones). The study concludes that indeed conversion of land from natural vegetation is associated with deterioration in soil quality and therefore policy needs to create incentives for the build-up of soil organic matter, replenishment of soil macro and micro nutrients. Blending of commercial fertilizers with targeted micro-nutrients, maintenance of soil conservation techniques and long term fallowing are encouraged.

Yield Monitor Data Cleaning is Essential for Accurate Corn Grain and Silage Yield Determination

Core Ideas Corn silage and grain yield monitors collect yield data of relevance to farmers. Evaluation of quality of yield monitor data is essential, especially for silage. A data cleaning protocol, consistent across fields, farms, and years, is needed. Semi‐automation is needed for quick and consistent processing of whole‐farm data. Yield monitor data are being used for a variety of purposes including conducting on‐farm studies, assessing nutrient balances, determining yield potential, and creating management zones. However, standardization of raw data processing is needed to obtain comparable data across fields, farms, and years. Our objective was to evaluate the impact of data cleaning protocols on corn (Zea mays L.) grain and silage yield data at the whole field (with and without headlands) and within field (soil map unit) scales. Corn silage data from 145 fields (three farms) and grain data from 88 fields (three farms) were processed. Comparisons were made to evaluate yields among three levels of cleaning: (i) none; (ii) automated cleaning (“Auto”) with filter settings derived for 10 fields per farm; and (iii) automated cleaning with manual inspection for unrepresentative patterns, after the automated cleaning step was completed (“Auto+”). The Auto+ cleaning process was conducted separately by three individuals to evaluate person‐to‐person differences. Spatial Management System software was used to read raw data and transfer to Ag Leader format. Yield Editor software was used to clean data (Auto and Auto+). Results showed the necessity of data cleaning, especially for corn silage. However, considering less than 5% deviation between methods at three spatial scales, the Auto and Auto+ cleaning resulted in similar output, as long as (i) each field or subfield included at least 100 harvester measurement points, and (ii) a moisture filter was applied for corn silage data.

Soil health assessments: how and why?

The information presented in this article comes from an on‐farm soil health assessment study in central Iowa. Researchers utilized available farm management records to design a sampling strategy that represented the predominant soil map units and provided soil that was analyzed for biological, chemical, and physical indicators of soil health. Earn 1 CEU in Soil & Water Management by reading this article and taking the quiz at www.certifiedcropadviser.org/education/classroom/classes/627.

Suitability evaluation for pigeon pea in southern transition zone of Karnataka Plateau, India

Soil - crop suitability studies provide information on choice of crops to be grown on best suited soil unit for maximizing crop production per unit of land, labour and inputs. Soil-site suitability evaluation for identifying potential areas of pigeon pea (Cajanus cajan) was conducted at 1:8000 scale in Basavanagiri of Mysore district, Karnataka. Detailed soil survey of study area was carried out using cadastral map and four soil series mapped with 23 soil-mapping units. The results showed that 22 per cent of total area covering four mapping units of Bg 3 soil series is highly suitable for growing pigeon pea. Whereas, sixteen units covering 122 ha is moderately suitable and two mapping units of Bg1soil series are found not suitable for pigeon pea cultivation. Soil depth, topography, effective rooting depth and gravelliness found to be major limitations for pigeon pea production in the study area.

Updating conventional soil maps by mining soil–environment relationships from individual soil polygons

Conventional soil maps contain valuable knowledge on soil–environment relationships. Such knowledge can be extracted for use when updating conventional soil maps with improved environmental data. Existing methods take all polygons of the same map unit on a map as a whole to extract the soil–environment relationship. Such approach ignores the difference in the environmental conditions represented by individual soil polygons of the same map unit. This paper proposes a method of mining soil–environment relationships from individual soil polygons to update conventional soil maps. The proposed method consists of three major steps. Firstly, the soil–environment relationships represented by each individual polygon on a conventional soil map are extracted in the form of frequency distribution curves for the involved environmental covariates. Secondly, for each environmental covariate, these frequency distribution curves from individual polygons of the same soil map unit are synthesized to form the overall soil–environment relationship for that soil map unit across the mapped area. And lastly, the extracted soil–environment relationships are applied to updating the conventional soil map with new, improved environmental data by adopting a soil land inference model (SoLIM) framework. This study applied the proposed method to updating a conventional soil map of the Raffelson watershed in La Crosse County, Wisconsin, United States. The result from the proposed method was compared with that from the previous method of taking all polygons within the same soil map unit on a map as a whole. Evaluation results with independent soil samples showed that the proposed method exhibited better performance and produced higher accuracy.

Measuring Rotation and Manure Effects in an Iowa Farm Soil Health Assessment

Core Ideas Farms with known management histories contribute to soil health research. Rotation‐based systems may increase soil organic carbon when combined with appropriate tillage. Inherent soil properties must be considered in soil health assessments. Rotation effects were more noticeable than manure effects on soil health groupings. Data from on‐farm sites with known management histories are needed to quantify soil biological, chemical, and physical properties influencing carbon stocks and soil health. Surface (0–15 cm) and deep core (0–122 cm) soil samples were collected from fields under two rotations in Boone County, IA. The first was a 5‐yr corn [Zea mays (L.)], soybean [Glycine max (L.) Merr.], corn, oat [Avena sativa (L.)], and alfalfa [Medicago sativa (L.)] rotation to which 0, 18, or 36 Mg ha−1 of a manure/biosolids mixture was applied prior to planting corn. The second was an 8‐yr rotation with 6 yr of mixed grass and legume pasture followed by corn and an oat crop within which the pasture mixture was reestablished. Soil samples were collected evenly across the predominant soil map units (SMUs). Bulk density (BD), soil organic C (SOC), water‐stable aggregates (WSA), microbial biomass carbon (MBC), pH, Mehlich‐3 and diethylenetriaminepentaacetic acid (DTPA) extractable nutrients, electrical conductivity (EC), and nitrogen (total‐, NH4–, and NO3–N) were measured. Surface SOC data were consistent with Soil Survey values for the various SMUs. Crop rotation effects were more noticeable than manure/biosolid application rate effects. Data from this study were combined with previously published SOC data in Iowa. Results suggest extended rotation systems or those with cover crops may increase SOC 8 ± 4 g kg−1 compared to corn–soybean rotations (33 vs. 25 g kg−1). This study provides on‐farm reference values for soil health assessment tools and draws attention to the importance of inherent soil properties for these assessments.

Land Evaluation for Site-Specific Crop Planning-A Case Study of Chincholi Khurd-1 Microwatershed, Aland Taluk, Gulbarga District, Karnataka, India

Land evaluation is the assessment of the suitability of land for specified land uses. Land evaluation and quantitative land use systems analysis support the planning of sustainable use of land. Six soil series and their phases identified and mapped during land resource inventory were evaluated for their soil-site suitability for different crops in Chincholi Khurd-1 microwatershed, Aland Taluk, Gulbarga District, Karnataka. The soil mapping units were classified and grouped into land capability classes II, III and IV with limitations of erosion and soil characteristics. Soil-site suitability evaluation for sorghum, maize, red gram, sunflower, cotton and soybean showed that Rajnala (RNL) soil series are calcareous clay and Mahagaon (MAN) soil series are cracking clay soils and are highly suitable (S1) for sorghum, sunflower, cotton, soybean except mapping unit RNLmC2g1. They are marginally suitable (S3) for maize and moderately suitable (S2) for red gram, respectively. Novinihala (NHA) and Bhimanahalli (BHI) soil series are moderately suitable (S2) for all crops except sunflower, and Margutti (MGT) soil series with nine mapping units are not suitable (N) for all the assessed crops. Soil factors (depth, soil texture, gravelliness and slope) and soil erosion are the major limitations for cultivation of the crops in the microwatershed.

Geospatial Technology Potentials in Reawakening the Consciousness of Soil Distribution in Nigeria’s North-Central Region and Mediating the Herdsmen-Farmers Conflicts

The pervasive herdsmen-farmers conflicts in the north-central region of Nigeria have changed the narrative of Nigeria’s enduring ethnic crises to ideologies, which are in-controvertibly sinister. The consequences of this tension, which has defied possible military responses, political, religious and cultural strategies are potentially devastating, not just for Nigeria, but the whole of West African region. Since the particular nature of these conflicts increasingly highlights the significance and inevitability of land resources for crops farming and cattle rearing, it is imperative to create awareness of the elemental nature of soils, especially their diversities in these conflict-prone areas. This study’s objective was to produce a Geographic Information System (GIS) based digital soil map (DSM) of the north-central region of Nigeria, and to delineate soil distribution and unique properties. Based on this study, the DSM offers a quick access to quantitative soil data covering the study area. It indicates that soil mapping units 15d, 18d and 24b are dominant, and constitute about 40% of the local arable lands. The broad pattern of distribution of these soils reflects both the climatic conditions and the geological structure of the region. The soils are highly weathered with limited capacities to supply essential nutrients needed by crop plants. These issues raise a number of questions, most of which focuses on the best possible way to maximize these soils to accommodate both crop farming and cattle rearing. It is our hope that taking the advantage of GIS to stimulate the knowledge and consciousness of soil distribution in the region will place the weight where it is appropriate in terms of food security through crops production and cattle rearing, and hence forge a more realistic pathway to reconciliation and conflict resolution.

Potential Water Conservation Using Site-Specific Variable Rate Irrigation

Abstract. Site-specific variable-rate irrigation (VRI) systems can be used to spatially manage irrigation within sub-field-sized zones and optimize spatial water use efficiency. The goal of the research is to provide farmers and consultants a tool to evaluate the potential benefits of implementing VRI. The specific objective of this research is to evaluate the potential water savings using VRI management compared with uniform irrigation management to maintain soil water holding capacity above 50% depletion using two irrigation scenarios: 1) a standard 12.5 mm irrigation per application; and 2) an application to refill the soil profile to field capacity. A 21-year simulation study was carried out on a selected field with varying degrees of soil and topographic variability. The simulated field had 12 soil mapping units with water holding capacities in the top 0.30-m ranging from 42 to 70 mm. The 21-year simulation covering all weather conditions for each soil produced only two significantly different irrigation management zones for scenario 1, and for scenario 2 only one management zone. However, when the 21-year period was divided into periods with different ratios of rainfall to reference evapotranspiration, the simulations identified 1 to 5 management zones with significantly different irrigation requirements. These results indicate that variable rate irrigation system design and management should not be solely based on long term average weather conditions. Years with differing weather conditions should be used for potentially identifying management zones for VRI systems. Irrigation application depths between management zones ranged from 17 to 38 mm. However, when the actual soil areas of the study field were utilized to calculate the total volume of irrigation water applied, it resulted in an increase in water usage in the 2 and 4 management zones ranging from -1.2% to 5.8%. Water usage with VRI over uniform irrigation was greater by -1.6% to 6.8% in the 12.5 mm irrigations and by -1.2% to 2.2% for the field capacity irrigations Keywords: Management zones, Precision farming, Variable-rate irrigation, Water conservation.

Individualization of soil classes by disaggregation of physiographic map polygons

Abstract: The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify the existing combinations between the soil classes of each physiographic unit. Based on these combinations, rules were established to select typical areas of occurrence of each soil type in order to train a decision tree model to predict the occurrence of soil classes. The model was trained using the Weka software and was validated with a set of georeferenced soil profiles. Disaggregation enables the individualization and spatialization of soil classes and is useful in producing detailed soil maps.

Assessment of land degradation using comprehensive geostatistical approach and remote sensing data in GIS-model builder

This study was conducted to assess Land Degradation (LD) status under different land use. Geostatistical technique used to interpolate spatially distribution of soil physical, chemical and biological properties. Salinity indices were applied on Hyperspectral and Multispectral Data to predict the salt affected areas. Arc GIS model-builder implemented to integrate the available LD methodologies and produce the overall degradation map of the study area in Chamrajanagar district (CDK), Karnataka, India. Remote sensing data was found to be useful tools to map land resources, especially in the areas where accessibility is limited like mountains. This study determined spatial distribution by calculating different soil properties for soils profiles. For LD calculations, eighteen soil profiles were dug and 79 samples were analyzed. This along with the parameters taken into consideration i.e., soil, slope, rainfall, DEM, land use, and land characteristics maps. It was found by adopting the logical criteria that LD of CDK categorized as very high, high, moderate, low and very low. The result of this research work could be potentially used as a useful tool to guide policy decision makers for sustainable land resource management in CKD. Based on the imagery interpretation and soil map unit description, hotspots were identified for representing different types of degraded soils. From the physical and chemical characteristics of pedons studied, it has been found that soils of CDK are exposed to degradation in the surface and sub surface horizons.

LAND EVALUATION OF SOME AREAS OF EL-FAYOUM DEPRESSION, EGYPT USING REMOTE SENSING AND GIS TECHNIQUES

The purpose of this study is to evaluate some soils in ElFayoum depression using Remote Sensing (RS) and Geographic Information System (GIS). For this purpose, twenty-five soil profiles and seventy-two minipits were described in the field and their representative samples were laboratory analyzed. Using, geological map, Digital Elevation Model (DEM) and visual interpretation of satellite data a physiographic soil map was produced to present soil mapping units of the studied area. The area under investigation was classified into four landscape units, i.e. Alluvial Plain, Lacustrine Plain, Aeolian Plain and finally lake and lagoon (13.14 % of the total studied area). Soil taxonomic unit were identified. These soils can classified into Aridisols, Vertisols, and Entisols orders. Land capability was used to evaluate the soils of studied area. According to modified Storie Index model. The area is classified into five capability grades reflect the limitation factors. Grade 1 about 41.85 % without any limiting factors, Grade 2 about 15.94 % where the soil main limiting factor is soil profile depth, Grade 3 about 17.30 %, where soil depth of soil profile. Texture and salinity are the main limiting factors, Grade 4 about 6.91 %. Where the limiting factors are soil depth and salinity. Grade 5 about 4.86 % represented the most area of shallow soils. Four crops were selected to assess soil suitability for cultivation in the studied area, i.e. wheat, barley, cotton and olive. The results indicated that olive was the best crop for growing in such soils.