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.
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