Reconnaissance Soil Survey Research Articles

Characterization of Some Selected Soils Based on Fertility Capability Classification. In Madagali Local Government Area of Adamawa State, Nigeria

Characterization of soils using a scientific procedure is essential to assess the potential and constraints of a given land for agricultural purposes. The knowledge of soil limitations arising from land evaluation reports aims to provide practical approaches to ameliorating such limitations before or during the cropping period. This study was conducted to characterize selected soils in Madagali Local Government Area based on fertility capability classification. A reconnaissance soil survey was conducted in the study area. Ten auger point soil samples from each ward were randomly collected at depths of 0-20cm and 20-50cm using a digger, hoe, spade, and polyethylene bag. For each surface and sub-surface, ten samples were collected, making twenty samples representative of each ward. The twenty auger points collected from each ward were taken to the laboratory for analysis. Based on the laboratory results of selected soil properties, the fertility capability classification system classified the soils of Madagali Local Government into one FCC class (LLaedmk) for Hymbula, Gulak, Duhu, Kirchinga, and Palam. The fertility capability classification (FCC) revealed that all the soils in the study area were facing major constraints such as soil moisture stress (d), low organic matter (m), aluminium saturation (a), and low nutrient reserve (k). However, in the studied area, it is necessary to add potassium fertilizers or organic amendments with a significant K content, irrigate for dry-season farming, and add lime to overcome aluminium toxicity.

Studies on the Available Nutrient-Supplying Capacity of Soil in Degradation Vulnerable Soils of Central Dry Zone in Tumkur District, Karnataka, India

Land degradation resulting from various natural and anthropogenic activities including the loss of organic matter, decline in soil fertility, erosion, acidity, alkalinity and the effect of toxic chemical is a serious global environmental problem, which may be triggered by climatic factors and their aberrations. The detailed reconnaissance soil survey was carried out in Tumkur district of Karnataka to study plant available nutrients in degradation vulnerable soils of central dry zone in Tumkur district, Karnataka during 2021-2022 using remote sensing, GIS and field studies. Satellite imageries (Sentinal -2) of three seasons were used along with soil map to delineate the degradation soils through visual interpretation. Using this map resource characterization was carried out. Out of thirteen soil pedons studied from Tumkur district, nine pedons were studied from central dry zone of Tumkur covering six taluks. These pedons belongs to Alfisols, Inceptisols and Entisols soil order. Soils were very strongly acidic (4.54) to very strongly alkaline (9.33) with non- saline nature in all pedons. The organic carbon content was low high, with higher content in Hosahalli of Madhugiri and decreased with increased depth in pedons. Available nitrogen was low to high and available phosphorus and potassium were low to medium in range. Secondary and micronutrients is soil was low to high, except zinc and boron, showing deficiency in most of the pedon. Soil fertility status assessment of different major soils of central dry zone of Tumkur help in developing sustainable management plan for improving the productivity and also growing the suitable crop, by preventing the degradation.

Digital soil survey and mapping underpinning inherent and dynamic soil attribute condition assessments

We set out in this work to create a suite of 3D-like digital soil attribute maps for a research farming enterprise situated in the South Eastern Agricultural Zone of NSW, Australia. These digital maps come about because of a reconnaissance soil survey to map out the farm's soil baseline conditions and bring to bear the tools and processes of the digital convergence. This entails on-the-go proximal soil sensing for rapid and granular farm landscape characterisation, which helped inform field-based soil survey and sampling, and later the soil mapping too. Soil infrared spectroscopy associated inference (vis-NIR) was then used to facilitate very detailed soil characterisations of key soil attributes that included soil pH, carbon, soil texture, bulk density, and cation exchange capacity amongst others. This work then enabled the ability to build bespoke spatial models to generate 3D-like inherent and dynamic digital soil attribute maps. We highlight some of the digital soil infrastructure features which include flexibility, customisation, and work pipelines that will ease the updating and improvement of maps. We also highlight some immediate goals which include a formal inclusion of measurement uncertainties brought about by soil spectral inference into the spatial modelling process. To date, some of the digital soil mapping has been used for applications such as lime requirement estimations to address subsoil acidity issues and therefore changing/improving the soil's capability at BARS. Overall, the intention of this work is to provide a detailed account of what is entailed in creating a comprehensive digital soils infrastructure for a farm including the likely costs to implement and the associated opportunities it provides.

Renewal of Archival Legacy Soil Data: A Case Study of the Busia Area, Kenya

Much older soils information, collectively known as legacy soils data lies idle in libraries or in the personal collections of retired soil scientists. The probability is very high for this legacy data to be lost or destroyed. We demonstrate the stepwise process of bringing legacy soils data “back to life” using the Reconnaissance Soil Survey of the Busia Area (quarter degree sheet No. 101) in western Kenya as an example. The first step, site identification, involves meeting and deliberating with key institutions to identify a setting for the study. The second step, data archeology, involves locating and cataloging legacy soil data from key institutions, which often requires numerous site visits and the assistance of individuals familiar with the target data. The third step, data rescue, involves converting paper copies of data into a digital format by scanning the maps, narrative descriptions, and tables, and storing the information in a database. The fourth step, data renewal, consists of bringing the data to modern standards by taking advantage of technological and conceptual advances in geoinformation technology. In our example, the resulting digital (scanned) soil map of the Busia Area is a significant upgrade from the fragile paper map. The fifth step, data interpretation, entails careful interpretation of the soil information available within the legacy soil survey to provide additional agronomic information. This allowed us to produce 10 land quality maps showing the ability of the land to perform specific agronomic functions, and 18 different crop suitability maps that were not previously available. The rescued maps and their associated tabular and narrative data also provide crucial inputs for generating more detailed soil maps using digital soil mapping techniques that were unavailable when the original mapping was conducted.

Soil-environmental relationships on the Brahmaputra and Ganges floodplains in Bangladesh

ABSTRACT The reconnaissance soil survey of Pakistan 1961–71 produced important new information on the environmental relationships of soils on the Brahmaputra and Ganges floodplains in East Pakistan (now Bangladesh) which provided a sound basis for agricultural land use planning in the country. The greater part of the territory was found to have been formed in sediments deposited by tributary and distributary rivers, not by the two major rivers themselves. Piedmont, river meander, estuarine and tidal floodplain landscapes of different ages were recognised, with intricate relief and soil patterns with associated local differences in land use and crop suitability. In all except current active floodplain and piedmont fan areas, seasonal flooding was found to be mainly by rainwater ponded on the floodplains by high seasonal flood levels in the major rivers flowing into the country. Therefore, the country’s floodplains are not occupied, as is popularly believed, by sediments receiving annual increments of fertile alluvium; they are mainly occupied by soils developed to different degrees according to differences in sediment origin and landscape age, with profiles reflecting local differences in relief and drainage, and further changed by degradation through ferrolysis and by puddling of topsoils for rice cultivation.

Spatial prediction of soil properties for the Busia area, Kenya using legacy soil data

Legacy soil data often contains considerable agronomic information that can help revitalize agriculture in countries with poor spatial data infrastructures. The objective of this study was to determine whether existing legacy soil data could be used to quantitatively predict soil properties at a higher resolution than the original legacy soil map using digital soil mapping techniques without conducting additional field work. A dataset of 76 soil profiles mined from the Reconnaissance Soil Survey of the Busia Area in Western Kenya together with a total of 23 environmental covariates were used to capture the soil forming factors and test the effectiveness of the individual predictive soil mapping (iPSM) technique to predict soil organic carbon, clay, silt, and sand over large areas in cases where data is limited. iPSM was compared to the stepwise multiple linear regression (SMLR) under two scenarios and ordinary kriging. In scenario one, SMLR prediction was achieved using the 23 original environmental soil covariates as predictors whereas in scenario two, SMLR prediction was achieved using principal components, generated from the 23 original covariates, as predictors. Ordinary kriging used only the soil property data for prediction. Ordinary kriging outperformed all the prediction models (RMSE = 0.02) for SOC, (RMSE = 0.30) for clay, (RSME = 0.10) for silt, and (RMSE = 0.32) for sand. This was attributed to the proximity between the calibration and the evaluation datasets and that these two datasets were not entirely independent. Ordinary kriging maps, however, provided very little spatial detail. Considering only those prediction models that used soil covariates, iPSM did not perform well in predicting soil properties compared to SMLR under the two scenarios. Regardless of the poor performance from iPSM relative to the other prediction models, SMLR (under the two scenarios) and ordinary kriging, iPSM best captured soil properties' spatial variability. A combination of the four models, using model averaging methods, resulted in a better prediction using the equal weights method for clay (%) (RMSE = 14.31), silt (%) (RMSE = 9.00), and sand (%) (RMSE = 16.67). On the contrary, SOC content (%) prediction from SMLR under the two scenarios performed best (RMSE = 0.43). Predicted soil property maps were at a resolution of 30 m, better than the current soil property maps for the study area with a 250 m resolution. The ability of predicted soil property maps to capture the variability of soils in our study area, except for ordinary kriging, supports the overall objective of this study. The sample size within legacy soil data, however, limits the use of complex DSM techniques. Therefore, efforts should continue to ensure that information mined from legacy soil data can be used to bolster the efforts made by various soil agencies to create harmonized soil profile databases to increase their usefulness for complex DSM methods.

Effect of climate change on morphological characteristics of the soils of Vaigai River Basin, Alluvial Tract, Madurai District, Tamil Nadu

The pedological characterization of alluvial tract soils of Vaigai river basin, Madurai District, Tamil Nadu was taken during 2019-20. Initially a Reconnaissance Soil Survey was carried out with Toposheet as a base map. Totally nine representative pedons in Northern and Southern bank of the Vaigai river alluvial basin were selected and studied for their morphological characteristics. Along the course of Vaigai river basin, deposition of alluvial soil was evidenced by the poorly developed AC profiles in both side. The depth of the soil varied from d4 to d5 in both banks. The color of the pedons varies with hue ranging from 10YR to 7.5YR, value 2 to 6and chroma 2- 8 and in Northern bank ; from 10YR to 7.5YR,values varies by 2.5 to 6 and chroma by 1 to 6 in the Southern bank. The texture of soil varied from weak to structure less. Some yellowish brown mottles with jarosite were foundin the Northern bank and micaceous coatings found in the Southern banks. The calcium carbonate nodules were found in most of the pedons and the permeability of the soil was very rapid. Coconut, Banana and paddy are the major crops grown in this alluvial tract. Climate change, urbanization, is short of monsoon rain and industrialization had created the major impact on the shrinkage of land under cultivation and smash up the soil health. The present study on characteristics of alluvial tract of Vaigai River basin both in Northern and southern banks understood about the change due to anthropogenic activities and climate change scenario.

Soil - site suitability evaluation for major crops in Jammalamadugu - Proddutur tract of Pennar river basin in YSR Kadapa district, Andhra Pradesh

A reconnaissance soil survey was undertaken in Jammalamadugu - Proddutur tract of Pennar river basin in YSR Kadapa district, Andhra Pradesh to evaluate the suitability of soils for growing rice, cotton, bengalgram and sunflower crops. The soil belongs to Inceptisols, Entisols and Vertisols. All the pedons (P1 to P11) were marginally suitable for growing crops suchas rice, cotton, sunflower and bengalgram except P1 which is moderately suitable for growing cotton. Soil texture, pH and organic carbon, CaCO3 and drainage are the major limitations for crop growth in all the pedons. In general, the limitation levels of the land characteristics varied from crop to crop. The suitability classes for major crops can be improved if soil fertility characteristics are altered through soil amelioration measures. The actual and potential suitability classes of the soils also varied depending upon kind of limitations. If the limitation is due to properties like slope, erosion etc., it can be rectified or improved by adopting suitable soil and water conservation measures and introducing lifesaving irrigations but if the limitations are of permanent type like soil depth it is impossible to convert those lands into better suitability classes than the prevailing one.

Free, open, quantitative and adaptable digital soil map data and database for Nigeria.

Nigeria's digital soil map (DSM) and database is the most comprehensive and detailed source of quantitative information on the country's soil distribution. Digital cartography and geographic information system (GIS) operations were methods used in producing the DSM and database. We obtained analogue soil data in 8 hard copy maps (each at a displayable scale of 1: 650,000) from the Federal Department of Agricultural Land Resources (FDALR), which archived the result of Nigeria's reconnaissance soil survey. The survey started in 1985 and by 1990; it has completed the compilation of hard copy maps that outline Nigeria's major soil distribution. Our experimental design begins with electronic scanning of these paper maps. We set the scanning system to 500 dpi, creating high-resolution raster images, which were imported into ESRI ArcGIS software, for orthorectification by geo-referencing to WGS 1984 geographic coordinate system. We applied a spatial processing tool on the orthorectified images and created a geometrically-seamless mosaicked raster image for the soil data of the whole Nigeria. Using GIS on-screen digitization – with optimal snapping tolerance – we created vector polygons (spatial data) of soil components (mapping units). Finally, we coded the metadata (attributes) of Nigeria's soil distribution into Microsoft EXCEL spreadsheet, which we linked to the soil spatial data. The combined spatial and attribute soil data forms the soil database for Nigeria and provides, on-demand, vital soil information, such as thematic maps of soil characteristics. The department of Geoinformatics and surveying University of Nigeria, Enugu Campus (UNEC) is the major repository of Nigeria's DSM and database.

Characterization and Evaluation of Soils Occurring on Toposequence In Eastern Plains, Bhilwara District, Rajasthan for Land Use Planning

A reconnaissance soil survey was undertaken at 1:50, 000 scale to characterize and evaluate the land resources of Bhilwara district in Rajasthan for land use planning. Based on landforms seven typifying pedons along the toposequence were studied for their soil-site and physico-chemical characteristics in eastern plain. The study indicates that the soils of steeply sloping hilly terrain were very shallow, excessively drained, dark brown, sandy loam in texture with fine, weak sub-angular blocky structure. The soils of very gently sloping plain and nearly level plain are deep to very deep, imperfectly drained to well drained, olive brown to dark brown soils associated with higher water content at -33 and -1500 kPa and the organic carbon content was higher in the surface soils compared to subsurface and it decreased with depth. The calcium carbonate content ranged from 1.0 to 36.5 percent and the calcium carbonate content increased with depth. The soils of the hilly terrain (P1) and undulating pediment (P2) have been classified as Lithic Ustorthents and Lithic Haplustepts, respectively. Soils of the intervening valley (P3), undulating plain (P4) and gently sloping plain (P5) categorized as Typic Haplustepts, whereas the soils occurring on the very gently sloping plains (P6) were classified as Vertic Haplustepts. The soils formed on nearly level plain have been classified as Sodic Haplusterts (P7). The soils are grouped under IIes, IIIs, IVes and Ves land capability sub-classes and 2s, 3s, 3st, 3sd, 4st and 5st land irrigability sub-classes. The land suitability for major crops growing in the region indicated that the soils of the hilly terrain (P1) and undulating pediment (P2) are not suitable for most of the crops due to their very severe limitations of slope, erosion and soil depth. The soils of the intervening valley (P3) were moderately suitable for maize and sorghum and marginally suitable for wheat, cotton and mustard. Soils of undulating plain (P4) were highly suitable for maize, sorghum, wheat and moderately suitable for groundnut, cotton and gram. Soils of the gently sloping plains (P5) were highly suitable for sorghum; moderately suitable for maize, wheat, cotton and mustard; and marginally suitable for groundnut and gram. Soils of the very gently sloping plain (P6) were moderately suitable for sorghum and marginally suitable for maize, wheat, cotton and unsuitable for groundnut and gram. Soils of the nearly level plains were moderate to marginally suitable for other crops and unsuitable for groundnut and gram (P7).

GIS-based agroecological assessment of land suitability for food crop development at a regional scale: A study case of Buton Island.

Agriculture has long become a prime sector for regional development in Buton Island, although local government emphasis on perennial crops. Food crop have been developed in very limited land areas, mainly on transmigration areas, as parts of central government programs. Today, the central government has launched a national strategic program on food self-sufficiency and has imposed the local government to optimize available land for cultivating food crop. The primary aim of study is to develop rapid assessment on a spatial basis using GIS for agricultural land suitability evaluation of agriculture commodities, i.e., rice (irrigated paddy field, rainfed rice) and corn (Zea maize L.). The study was undertaken using the following procedures: (i) conducting reconnaissance soil survey based on land units; (ii) constructing soil database in a GIS; and (iii) classifying land suitability using the FAO method. Spatial data were generated from digital topographic map, soil survey, soil characteristics, as well as climate data. Preliminary results indicate that quite large area available for food crop cultivation both in the context of land suitability (mostly in S2 and S3 classes) and land availability. All data bases were managed in GIS, then it is amenable to various operations in GIS to accommodate possible additional assessment including socio-economic and policy assessment.

Evaluation of agricultural land resources for irrigation in the cotton growing Yavatmal district, Maharashtra, India

The main objective of this study is to evaluate suitability of shrink-swell soils for surface irrigation system based upon a parametric evaluation system in low irrigation potential (7%) of cotton growing Yavatmal district, Maharashtra, India. The thirty three shrink-swell soil series on basaltic landforms were identified from reconnaissance soil survey on 1:50,000 scale and evaluated for surface irrigation methods using Geographic Information System (GIS). The standard weekwise rainfall data showed that the rainfall is less than 20% of total precipitation during September and December, the top A horizon reaches to wilting point and needs supplementary protective irrigation to cotton based cropping systems . It was estimated that ten soil mapping units (1.8 Mha and 13.89%) of shrink-swell soils on moderate slopes (5 to 8%) were evaluated as suitable for surface methods and calculated the irrigation intervals that vary from 8.61±1.35 days for cotton to 8.9±1.4 days for wheat and 10±1.64 days for sugar cane. The study emphasized the utility of soil resource maps helps to delineate the soils with large PAWC(>200mm) with slight yield advantage and will serve as benchmark sites to monitor the interrelationships of soil water dynamics with respect to climate and cotton yields.

A reconnaissance soil survey of County Fermanagh

Abstract not available...

Combination of Fuzzy Logic and Analytical Hierarchy Process Techniques to Assess Potassium Saturation Percentage of Some Calcareous Soils (Case Study: Fars Province, Southern Iran)

This research was carried out to evaluate the capability of a combined fuzzy logic-based approach and analytical hierarchy process (AHP) for potassium saturation percentage (KSP) estimation in some calcareous soils of southern Iran. Based on a reconnaissance soil survey, 52 soil series were selected and different physical and chemical properties were determined. Five soil parameters including clay, cation exchange capacity, calcium carbonate equivalent, electrical conductivity, and organic carbon were chosen for analysis. Mapping was developed with the kriging method for each parameter. Different fuzzy membership functions were employed and weights for all parameters were calculated according to AHP. Finally, KSP classes were provided for each land unit. Results indicated that about 60% of the studied area is classified as having moderate to high KSP content (>3%) and 40% of had low or very low KSP content (<3%). Then 15 sample points were used for determination of the accuracy of the fuzzy method. Results showed that the fuzzy and AHP methods have a high accuracy for KSP estimation in the studied soils. Further development of the fuzzy and AHP methods would be worthwhile for improving the accuracy of KSP analysis.

Soil informatics for agricultural land suitability assessment in Seoni district, Madhya Pradesh, India

The soil informatics for agromanagement at district level is a valuable tool for making environmentally suitable land use systems and assessing fertility constraints for crop production in tribal dominated Seoni district, Madhya Pradesh, India. The methodology combining soil survey with geographic information system and standard land evaluation procedures were adopted to evaluate suitability of soil units for locally suitable crops. The physiography - soil map with thirty soil mapping units (series association) was generated over fourteen distinct basaltic and granitic landforms through reconnaissance soil survey. The arability and suitability analysis showed that fifty six per cent of arable land is suitable for eleven land use zones. In arable lands, twenty four per cent of basaltic clay soils in northern plateaus were evaluated as suitable for citrus, sorghum and soybean cropping systems with fertility constraints of low available nitrogen , phosphorus and zinc while 15.3 per cent of granitic soils in southern zone for sorghum and cotton systems having limitations of stoniness, low water holding capacity, low status of available nitrogen, phosphorus, potassium and zinc.

Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements

Patterns in crop development and yield are often directly related to lateral and vertical changes in soil texture causing changes in available water and resource supply for plant growth, especially under dry conditions. Relict geomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions of uniformity in precision agriculture, subsurface hydrology, and crop modeling. Hence a better detection of these subsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area index (LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for the first time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensor measuring soil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0–0.25 to 0–1.9m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomography (ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties at ten arable fields. The moderate to excellent spatial consistency (R2 0.19–0.82) of ECa patterns and LAI crop marks that indicate a higher water storage capacity as well as the increased correlations between large-offset ECa data and the subsoil clay content and soil profile depth, implies that along this buried paleo-river structure the subsoil is mainly responsible for better crop development in drought periods. Furthermore, observed stagnant water in the subsoil indicates that this paleo-river structure still plays an important role in subsurface hydrology. These insights should be considered and implemented in local hydrological as well as crop models.

Characterization and fertility assessment of soils of markapur mandal, Prakasam district, Andhra Pradesh for sustainable land use planning

A rapid reconnaissance soil survey of Markapur mandal of Prakasam district, Andhra Pradesh was carried out in 2009–10 using geo-referred false colour composite image (IRS-P6, LISS-III) and Survey of India (SOI) topo-maps (1: 50, 000 scale) set. The soils of hill side slope and undulating pediments developed over quartzite, sandstone and shale complex was shallow to moderately deep, brown (7.5 YR 4/4) to dark brown (7.5 YR 3/4) in colour, well drained with poor fertility. These soils are under forest, open scrub and rainfed farming in patches. The soils of pediplains and stream bank from shale was yellowish red (5 YR 4/6) to dark reddish brown (5 YR 3/3), deep to very deep low fertility and cultivated (rainfed) in pediplains but waste land in stream bank. The soils of undulating pediments and hill side slope were grouped under land capability class IV and VII whereas soils of pediplains and stream bank were placed under land capability class II and III respectively.

Soil Resource Mapping and Assessment of Soils at Different Physiographic Divisions in Selected Mandals of Prakasam District, Andhra Pradesh: A Remote Sensing and GIS Approach

A rapid reconnaissance soil survey of Markapur, Kambham, Giddalur and Komarulu mandals of Prakasam district, Andhra Pradesh was carried out in 2009–10 for soil resource mapping using a hard copy of geo-referred false colour composite image of IRS-P6, LISS-III, and Survey of India (SOI) topo-maps no. 57 I/16, 57 M/1, 57 M/2, 57 M/3, 57 M/4, 57 M/5 and 57 M/6 of 1:50,000 scale as auxiliary data set. The study area lies between 15°30’ to 16°00’ N latitudes and 78°45’ to 79°30’ E longitudes with total geographical area of 3, 52,185 ha. Alluvium, quartzite, sandstone and shale were main geologic formation. Physiographically, soils of hill side slope and undulating pediments developed over mixed geology of quartzite, sandstone and shale 1 apped into 9 mapping units. Likewise, Soils of pediplains and stream bank developed over shale are light to dark coloured, deep to very deep and have fine loamy to fine texture and low fertile. These soils are mostly under rainfed cultivation in pediplains and waste land in stream bank extended over 51.2% of the total area and mapped into 7 mapping units. Based on soil limitations, soils of undulating pediments and hill side slope are grouped under land capability class VI and VII whereas soils pediplains and stream bank was under land capability class II and III respectively.

Evaluation of Best First Decision Tree on Categorical Soil Survey Data for Land Capability Classification

Land capability classification (LCC) of a soil map unit is sought for sustainable use, management and conservation practices. High speed, high precision and simple generating of rules by machine learning algorithms can be utilized to construct pre-defined rules for LCC of soil map units in developing decision support systems for land use planning of an area. Decision tree (DT) is one of the most popular classification algorithms currently in machine learning and data mining. Generation of Best First Tree (BF Tree) from qualitative soil survey data for LCC reported in reconnaissance soil survey data of Wardha district, Maharashtra has been demonstrated in the present study with soil depth, slope, and erosion as attributes for LCC. A 10-fold cross validation provided accuracy of 100%. The results indicated that BF Tree algorithms had good potential in automation of LCC of soil survey data, which in turn, will help to develop decision support system to suggest suitable land use system and soil and water conservation practices. General Terms Data mining algorithms, Decision Tree

Capability and quality assessment of rice growing hydric soils in majuli river island, assam, India

The wetland soils in majuli island is a unique in maintaining rice ecology and geoenvironment in Brahmaputra valley of Assam due to increasing rate of bankline erosion in southern bank and expansion of channel bars on northern banks. These hydric soils in the subgroups of aquents and aquepts are saturated throughout year as assessed from depleted matrix with hue 10YR, 2.5Y and 5Y, chroma less than 2, stratified textures, neutral to slightly alkaline reaction, low cation exchange capacity and poor exchangeable base status. The assessment of land capability and soil quality for rice production in hydric soils was conducted on twenty four soil mapping units derived from reconnaissance soil survey done on 1:50000 scale. As per land capability assessment, these soils are good(classII) to fairly good(IV) for arable use with limitations of low fertility status, moderate to severe wetness and moderate to rapid permeability. The soil quality rating with multiple variable indicator transform(MVIT) technique of twenty hydric soil units in active and old floodplains was medium (35 to 65per cent) with six indicators(pH, organic carbon, base saturation, effective rooting depth , structure and texture) meeting the thresh hold value above 65 per cent. Thirty five per cent of total area is suitable for rice cultivation as against the current cropped area of 7.2 per cent with potassium and zinc deficiency. The determination of soil quality in relation to land capability was found useful to design best management practices for wetlands in the region that ensure sustainable land use.