Lecture 13

Soil information system for resource management – Tripura as a case study

The basic requirement to develop a soil information system (SIS) is to have large datasets. Such datasets are not generally available for all the states and Union Territories of the country. Tripura is one of the states for which relevant and pertinent datasets on natural resources are made available by the National Bureau of Soil Survey & Land Use Planning (NBSS&LUP; ICAR), Nagpur, during the past decade. While reviewing and interpreting the published data on the 1 : 50,000 scale, it was realized that a SIS can be developed which can serve as an example as to how such a system could be built for other States and Union Territories. Tripura was surveyed earlier by the All India Soil and Land Use Survey (AISLUS) and later by NBSS&LUP to develop soil datasets. Since the modern day information system of any natural resource requires its physical location in terms of space, exact referencing of natural resources has become necessary. The geographic information system (GIS) has been an important tool for geo-referencing the soil information system (GeoSIS). Soil information system elsewhere

Various countries have developed their own SIS1. The most widely used system is the Soil and Terrain Digital Database (SOTER; 1 : 1 m). It provides data for improved mapping, modelling and monitoring of changes of world soil and terrain resources. The SOTER methodology  allows mapping and characterization of areas of land with a distinctive, often repetitive pattern of landform, lithology, surface form, slope, parent material and soils 2. The approach resembles physiographic or land systems mapping. The collated materials are stored in a SOTER database linked to the GIS, permitting a wide range of environmental applications3,4. The SOTER is applied5 at scales ranging from 1 : 250,000 to 1 : 5 M. The SOTER method used for studies on carbon stocks and their changes in the Indo-Gangetic Plains (IGP), led to the following, viz. (i) linkage between soil profile data and spatial component of a SOTER map for environmental applications requires generalizations of measured soil (profile) data by soil unit and depth zone, (ii) the set of soil parameter estimates for the IGP should be seen as best estimates, based on the currently available selection of profile data held in IGP–SOTER and World Inventory of Soil Emission Potential (WISE), and (iii) the primary and secondary datasets for IGP will be useful6 for agroecological zoning, land evaluation and modelling of carbon stocks and changes at a scale of 1 : 1 M.

Soil information system in India

Recently, the National Agricultural Innovative Project (NAIP) has sponsored a NBSS&LUP-led project of georeferenced soil information system (NAIP–GeoSIS) on the soils of the IGP and those of the black soil regions (BSR)7. Various research projects in the field of natural resource management funded by the World Bank, Department of Science and Technology (DST), New Delhi and the Indian Council of Agricultural Research, New Delhi have produced datasets on soils which lay the foundation

Usefulness of soil series information

Soil series provide first-hand information on soil resources of the state in terms of morphological, physical, chemical and mineralogical properties. As discussed  earlier, such information helps understand the nature and  extent of a particular soil under different categories of acidity, physiographic position and land use. This soil  information can be systematically arranged according to the users’ demand. The soil information developed for Tripura has helped include 15 soil series in the National Register maintained by NBSS&LUP.

Application of soil information system

The SIS contains datasets on soil, landscape, land use, water and climate and as such provides a spatial framework for managing natural resources. The SIS of Tripura integrates outputs from various sources across the state and may be considered useful for monitoring natural resources, modeling soil physiographic relation, finding crop suitability, land-use options, estimating soil loss and conservation of natural resources. Modeling soil carbon and crop performances can also be a continuous exercise to comprehend the soil health and related changes in soils due to climate change. In isolation, each activity may not justify to provide appropriate information for natural resource management and planning, but in combination they provide a powerful tool to address the following issues for posterity. 

Soil information system – soil degradation

Two categories of soil degradation are recognized in Tripura. The first category deals with degradation by displacement of soil material, principally by water. The second one deals with the internal soil deterioration resulting from loss of nutrients (chemical deterioration) or through physical processes, including waterlogging and flooding (physical deterioration). SIS indicates that as much as 60% area of the state is under various types of degradation ⁸. If slight and moderate degrees of degradation are ignored, the extent of degradation is nearly 21% area of the state.

Soil information system to develop soil loss and crop productivity model

Since soil erosion is the major reason for soil loss and imperative for the land-use managers and planners to adopt appropriate soil conservation measures. The soil loss and crop productivity model explains the development of regional-level methodology for estimation of actual soil loss in Tripura using the 5 km 5 km grid points11,22. Loss of crop yield due to loss of topsoil is compensated by the use of manure and fertilizer. At the same time, loss of topsoil by soil erosion is also compensated by the formation of fresh soil layers

through the process of pedogenesis. To calculate loss of topsoil it is necessary to take into account the amount of soil regenerated, keeping in view the difference in the rate of soil formation under different types of climatic conditions11. On the basis of available soil information8,11,14 and the rate of topsoil formation at each grid point, various soil loss limits were developed. The estimates of soil erosion sometimes appear exaggerated when factual information is scarce. To make the generated output more factual, SIS developed by NBSS&LUP was

utilized 8–11,14. The SIS can thus generate soil erosion datasets to enrich it and also make it more useful for soil conservation. Totally seven classes of soil erosion were identified. Taking the medium values of the soil erosion range, the total soil lost under different erosion classes was estimated. For humid, tropical climate like Tripura, an annual addition of 29 tonnes soilwas estimated23. In view of this the soil erosion class indicating ≤ 29 t ha–1 yr–1 was not considered while computing the effective soil loss. The estimated annual loss of soil was nearly 15 million tonnes (mt) every year.

Soil information system vis-a-vis conservation measures

While applying the soil loss and crop productivity model, potential erosion losses for each desired land use may be evaluated assuming that no specific soil conservation measures are applied, which indicates that the protection factor (P) is one. These results could be compared with what are considered as acceptable rates of soil loss under various levels of inputs23, that are followed for estimation of the required conservation needs and their associated costs. Soil conservation need is estimated as the protection factor (P) when lands are not under any conservation programmes. The average rate of erosion covers both the cultivated and the uncultivated parts of the crop and fallow-period cycle. Estimation of conservation need showed that the required soil loss reduction was 48.5 t ha–1 (146–97.5 t ha–1). In land under cultivation, the total soil loss over 6 years was 130 t ha–1 (12 + 18 + 100 t ha–1). Therefore, the conservation need (P factor) required to achieve this is 48.5/130 = 0.37. Soil conservation helps achieve three types of benefit, viz. (i) long-term reduction in checking the decline of agricultural production; (ii) gradual increase in agricultural production, and (iii) other non-agricultural benefits such as improved flow to the river during summer, reduction in periodicity and severity of flooding, reduction in siltation of reservoirs, reduction in damage of various costly infrastructure and low harmful impacts on farm lands. In Tripura many areas in the higher and middle elevations are under forest (58% TGA)8. The tilla lands and the lower foothills are used for plantation of rubber and/or for agricultural and horticultural crops. These lands are highly susceptible to soil erosion, and therefore require soil conservation measures such as benchterracing. Most of the areas showing nearly 15 mt soil erosion every year occupy the degraded uplands and forest areas used for jhumming. In rainfed areas like Tripura, terraces may be constructed on slopes ranging from 6% to 33%. The value of supporting conservation practice (P factor) using bench-terracing technique (0.5% longitudinal gradient, 2.5% inward gradient) is quite low (0.027) for very deep red soils in Ooty hills, with a slope of 25%. Judging by similar terrain conditions, such efforts could be recommended for Tripura. However, appropriate techniques could be evolved by the conservation experts. Tilla lands and part of the degraded lands with shrubs and bushes are now exposed to erosion due to lack of vegetation. These areas need proper afforestation programmes. Part of these areas may be recommended to be brought under rubber cultivation and other plantation and horticultural crops 8,9. Such practice will be doubly beneficial since it will save the loss of the most valuable natural resources like soil and would also generate income source among the local people.

Soil information system for suitability of different land uses

Eighteen model study areas and 390 grid-point observations were analysed in terms of 16 identified soil series vis-a-vis the suitability of land uses like horticulture and agriculture. Soil parameters vis-à-vis different selected crops indicated a general relationship of crop/land-use selection, elevation and KCl-extractable Al in the soils. Forest species predominate up to about 400 m elevation which includes oranges. The 400–250 m elevation could be ideal for plantations and horticultural crops, whereas 250–150 m may be ideal for upland paddy and other horticultural crops. Low lands (150 m) should be earmarked for lowland paddy and vegetables. It is interesting to note that the plantation and horticultural crops are suitable for those soils where KCl extractable Al is very high. Forest and upland paddy soils have a medium range of KCl–Al and the soils suitable for lowland paddy and vegetables contain very low amount of KCl-extractable Al.

Soil information system for crop suitability

Each plant requires definite soil and climatic conditions for optimum growth. Since the availability of both water and plant nutrients is largely controlled by the physical and chemical properties and micro-environments of soils, the success and failure of any species in a particular area is governed by soil characteristics, which indicates the significance of SIS. SIS was extensively used for evaluating lands for suitability of different types of crops and plantation species. Suitability criteria for rubber plantations in Tripura showed most of the areas as moderately suitable in the undulating plains and uplands without forests. It should be mentioned that most of the horticultural crops have similar soil-site requirements, which naturally compete with the rubber growing areas. It was, therefore, recommended that the rubber might be restricted to the marginal areas with further higher slopes. Using SIS the probable expansible area for rubber plantation was estimated 8,10 as 5.11%.

Soil information system – clay minerals vis-à-vis crop suitability

The soil series association map (1 : 50,000 scale) was used as a base map to establish the relation between clay mineralogy and crop suitability. Clay samples (<2 μm) of the selected soil series were analysed using X-ray diffraction techniques to estimate clay mineral content. Soil parameters such as CEC, clay and organic matter content were used to correlate the mineral make-up in the clay fractions. Data on clay minerals for 48 soil series from Tripura were utilized to generate a clay mineral map for the state. The data indicated dominance of hydroxyl interlayered Kaolin interstratified with HIV. (Kl) in fine and total clay fractions. Presence of hydroxyl interlayered smectites (HIS) was also noticed. Interestingly, mica and kaolinite minerals are also present as interstratified minerals with HIV as M/HIV and Kl/HIV12, 24–26. On the basis of mineral make-up of different soil series, clay mineralogy maps of various combinations were generated. Tilla lands used mostly for rubber and horticultural crops, are dominated by soils with less than 10% HIS, high hills (forests) are dominated by soils with less than 10–20% HIS and inter-hill valleys (agricultural crops) are dominated by soils with more than 20% HIS. Tilla lands are also dominated by soils with less than 17% HIV, high hills with less than 17–20% HIV and inter-hill valleys with more than 20% HIV. Tilla lands, used mostly

 for rubber and horticultural crops, are dominated by soils with less than 35% Kl/HIV; high hills covered under forests are dominated by soils with less than 35–50% Kl/HIV and inter-hill valleys growing paddy and other agricultural crops are dominated by soils with more than 50% Kl/HIV. In the humid tropical weathering environment of Tripura, the presence of vermiculite/low charge smectites is common. Minerals in clay fractions have not yet weathered to reach the stage of kaolinite. Thus the mineralogy class of these soils as mixed appears to be more appropriate. During humid tropical weathering, huge quantity of Al3+ ions are liberated to cause higher acidity (H+), which was estimated as 149 kg ha–1. It is interesting to note that vermiculites adsorb Al3+ ions as hydroxy-cations to form HIV/HIS. The vermiculite minerals thus act as a natural sink to sequester Al3+ ions. A representative acid soil of Tripura can sequester Al in the first 30 cm depth25,26 to the tune of 65 kg ha–1. This is the reason why Tripura soils show relatively higher proportion of hydroxy interlayered vermiculites effecting lower concentration of Al3+ ions in the soil solution. This fact may possibly help in removing a myth about Al-toxicity in acid soils in general and in acid soils of Tripura in particular.

Soil information system – soil health vis-à-vis organic carbon in soils

The SIS of Tripura helps to find out the soil health in terms of soil organic carbon (SOC). In Tripura, SOC content varies from 0.34% to 1.88%. Relatively high SOC isfound in deep to very deep, well to excessively drained loamy hill soils. The North Eastern Region (NER) in India has been declared as a green belt. Earlier SOC level of 1.0% was shown as a threshold limit for soils with good health21,27,28. SIS of Tripura helps estimate SOC stock. The data show that nearly 58% area in Tripura hasmore than 45 kg ha–1 SOC stock in the first 30 cm depth of soils. The SOC stock of Tripura in various soil depths is shown in. Total estimated SOC stock in India and Tripura is 9.55 Pg and 0.05 Pg, respectively23. It shows that SOC stock in Tripura is maintained at 0.046 Pg ha–1 compared to the all-India average of0.029 Pg ha–1. Earlier, using the 14 agro-climatic zones (ACZs) of the Planning Commission, ACZ 2, representing the entire NER was found to store organic carbon @0.064 Pg/m ha of soils29. Such threshold values of SOC stock ranging from 0.05 to 0.06 Pg/m ha should, therefore, be maintained in areas declared as the green belt to protect natural ecosystems.