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Spatial variability studies of soil hydro-physical properties using GIS for sustainable crop planning of a watershed of eastern India and its testing in a rainfed rice area.

Introduction

Most of eastern India (Assam, West Bengal, Orissa, Jharkhand, eastern Uttar Pradesh, and Chhartisgarh) has good quality natural resources basic to agriculture (soils, hydrology, topography, etc.) and plenty of rainfall (1000-2000 mm), but poor management of these resources has led to a situation where people of this resource-rich region are resource poor. The land use and cropping systems in most of these regions are inappropriate, exploitive, and unscientifically planned, resulting in very low productivity and cropping intensity. Site-specific, sustainable land use and cropping system plans based on potential and prospects of existing natural resources, especially soil hydro-physical properties and topography, may improve productivity and profitability (Kar et al. 2004). With the advent of tools such as the geographic information system (GIS), appraisal, integration, and depiction of spatial distribution of natural resources have become much easier (Sharma et al. 2001).

Water retention and available water capacity are the main determining factors for growing second crops after rainy season rice in the region. These parameters may be determined directly using laboratory methods (by measuring soil water content over a range of matric pressure heads) or indirectly by relating water retention functions (pedo-transfer functions) to some easily measured soil physico-chemical parameters such as soil texture, oven-dry bulk density, organic carbon, cation exchange capacity, etc. Development of pedo-transfer functions is a growing field (Pachepsky et al. 1996; Elsenbeer 2001; Tomasella et al. 2003). Estimation of soil hydraulic properties by pedo-transfer functions can be an alternative to difficult and expensive measurements (Romano and Santini 1997; Cornelis et al. 2001; Romano and Palladino 2002; Nemes et al. 2003). Kern (1995) and Minasny et al. (1999) evaluated soil water retention models based on soil physical properties. In this study we attempted to predict water retention characteristics (water content at field capacity, permanent wilting point) and available water capacity from some easily measured soil physical and chemical properties by developing linear regression equations. Under Indian conditions, some earlier workers have predicted profile water storage through soil physical and chemical properties (Yadav et al. 1995; Das and Dutta 1997) with acceptable precision and cost compared with traditional methods of investigation.

We used GIS for integrating different soil hydro-physical properties (texture, available water capacity, organic matter) at 0-0.30 m depth with topography and existing land use to generate a composite land development unit (CLDU) map of a watershed. Keeping the existing land use/cover as a base and using the potential and prospects of other spatially distributed natural resources in the CLDU, an action plan map on alternative land use/cropping system was developed and tested in a representative rainfed rice area of the watershed.

Materials and methods

Study area

The study was conducted in a representative watershed of eastern India, the Kadalipal watershed (latitude 20.80-20.86[degrees]N, longitude 85.54-86.50[degrees]E) of Dhenkanal district, Orissa, which belongs to the sub-humid climatic region of eastern India (Fig. 1). The average annual rainfall of the area is 1400 mm with 80% of rainfall received during the south-west monsoon. The cultivated area of the district is 205 607 ha, of which 33% has light-textured soil with low water retention and fertility status. The district is predominantly agricultural where the rainy season is the main cropping season and rice is the principal crop. The mean monthly major weather parameters of the study area are given in Table 1.

[FIGURE 1 OMITTED]

Data collection and analysis

The detailed methodology starting from data collection, analysis, action plan development, and implementation are given in 3 sequential steps.

Step I. Appraisal of spatial variability of soil hydro-physical properties, topography, and existing land use using GIS

For determining soil hydro-physical properties, grid profile sampling (250 by 250 m) was carried out in the watershed. Water retention at field capacity and wilting point was estimated by using pressure plate apparatus. Water retention between field capacity and wilting point was considered as available water capacity of the soils. The processed soil samples (<2 mm size) were analysed for their mechanical composition (soil texture analysis) following the international pipette method. The spatial coverage of soil texture was prepared from visual interpretation of IRS-1D (LISS-III) satellite imagery using on the basic elements of image characteristics such as tone, texture, shape, size, pattern, association, etc., along with extensive ground-truth observations and textural analysis (International Pipette method). The organic carbon content of the soils was determined by following standard procedures. The soil texture, organic carbon, and available water capacity at 0-0.30 m depth along with topography and existing land cover were utilised for alternative land-use planning throughout the watershed. The organic carbon, soil water constants and soil texture, oven-dry bulk density, cation exchange capacity (CEC), and calcium carbonate of 0.15, 0.15-0.30, 0.30-0.60, 0.60-0.90, and 0.90-1.2 m soil depths in a rainfed rice area of the watershed (representing 80% of total area of watershed) was used to develop the pedo-transfer function.

Soil oven-dry bulk density was estimated on undisturbed samples collected with metal cores of 4.2 cm diameter and 5.8 cm height. The calcium carbonate and CEC were estimated following standard procedures.

The slope map was prepared from contours of Survey of India Toposheet (1:50000 scale). The slope percentage was calculated as:

(Vertical drop/horizontal distance in between the contours) x 100

The vertical drop was measured from the contour intervals and horizontal distance in between the contours was measured by multiplying map distance by the scale factor. Accordingly, 5 categories of slope (0-1, 1-2, 3-5, 5-10, >35%) were available throughout the watershed. The existing land use/land cover map was prepared from visual interpretation of IRS-1D, LISS-III imagery together with extensive ground truth observation. After preparing individual thematic maps of available water capacity, soil texture, organic carbon, land use, and slope from different sources, these were scanned and on-screen digitised using Raster to Vector (R2 V) software to form ARC INFO GIS coverage. The digitised map, i.e. vector layer of different thematic coverage, was then cleaned and checked for errors such as dangles and pseudonodes, etc. After removing errors, the layer was built for topology using commands in the PC ARC/INFO 4.0 GIS package. Each coverage was projected using Polyconic Projection and Spheroid Everest geoid system for area estimation of different classes for a particular map. Arc View (Version 3.8.1) GIS software was used for spatial analysis through query building tools after integrating all individual thematic coverage into a CLDU map. Based on profile sampling (250 by 250 m grid), organic carbon and available water capacity maps were prepared using GIS. The GIS methodologies followed in preparing the digital database and spatial mapping of soil hydro-physical properties, along with topography and existing land use, are given in Fig. 2. Using Arc View GIS software, based on available water capacity, soils were grouped in to 6 classes (0.08-0.12, 0.12-0.16, 0.16-0.20, 0.20-0.24, 0.24-0.28, 0.28-0.32 [m.sup.3]/[m.sup.3]) for alternative crop planning. The organic carbon content was found to be low, and was grouped into 6 classes (0.2-0.3, 0.3-0.4, 0.4-0.5, 0.5-0.6, 0.6-0.7, 0.7-0.8%) in different parts of watershed. Different textural classes (clay, clayey loam, loamy sand, loam, sandy loam, sandy clay loam) were identified and geo-spatially mapped.

[FIGURE 2 OMITTED]

Step II. Development of action plan on sustainable land use and cropping system in the watershed

In this step, based on potential and prospects of existing soil hydro-physical properties, land use/cover, and slope, an action plan on a sustainable land use and cropping system was developed using GIS tools (Table 2). The watershed area was dominated by rainfed rice (843 ha out of 1320 ha total area of watershed), found in various parts of the topography; and in some areas fields in fallow, residual hills, or degraded forests were found. In the action plan rice was discouraged in light-textured soils in the rice area owing to its low and unstable productivity, and low water requiring crops such as maize, groundnut, blackgram, cowpea, and pigeonpea were suggested through sole- or inter-cropping.

Double cropping on such soils was suggested through maize-horsegram/sesamum rotation. The idea of crop diversification in light-textured, upland, rainfed rice soils is to emphasise that these crops can provide an assured income in soils with low water retention, and even with low rainfall, because the water requirement of these crops is less than that of rice. Since medium- to heavy-textured rice soils comprise a vast area (12.1 Mha) in eastern India, and rice is the staple food of the country, emphasis was given to improving productivity of rainfed rice during the rainy season, and second crops (post rice season) were suggested to utilise residual soil moisture. In the rainfed rice ecosystem with moderate available water capacity and medium textured soil, rice cropping for 120 days was suggested during the rainy season. Low-water-requiring crops such as blackgram, linseed, and safflower were suggested for the dry season (winter), utilising residual soil moisture after rice harvesting. In the lowland valley fill area with heavy-textured soil and higher available water capacity, a rice-based cropping system was suggested using rice (150 days)--pea/blackgram/ greengram rotation.

Agro-forestry, horti-pasture, and horticultural plantation such as cashew orchard, or pomegranate were also suggested to grow in upland degraded forest areas where arable crop cultivation was not possible.

Step III. Implementation of developed action plan in different rainfed rice ecosystems of the watershed

Since the watershed was dominated by a rainfed rice area where productivity and cropping intensity were low, the action plan was implemented at some locations in the rainfed rice area of the watershed as per the crop treatments below.

Light-textured rainfed rice soils. To explore the possibility of crop diversification in rainfed light-textured rice soils, groundnut (Arachis hypogea L.), pigeonpea (Cajanas cajan L.), blackgram (Vigna mungo L.), groundnut + pigeonpea (4: 1), and groundnut + blackgram (4: 1) were tested in 4 ha of land comprising 10 farmers of the watershed considering one farmer as one replication. Rice of 90 days duration (cv. Vandana) was grown as a control.

Medium-textured rainfed rice soils with moderate available water capacity. In the action plan map of medium-textured soils, instead of local varieties, improved rice variety Lalat of 120 clays duration was suggested as a test crop for the rainy season. During the winter dry season (November-March), low-water-requiring crops of safflower (Carthamous tinctorious L. cv. Bhima), linseed (Linum usitattisimum cv. Sekhar), and blackgram (Vigna mungo L. cv. T9) were advocated and tested in farmers' field of 4 ha of land utilising residual soil moisture after rainy season rice.

Heavy-textured rice soils with high water retention capacity. Under the rainfed rice area with higher available water capacity and heavy-textured soil, improved rice variety Gayatri of 150 days duration was suggested and implemented in 5 ha of such land during the rainy season, involving 15 farms in the watershed. On the same land, blackgram (Vigna mungo L. cv. T9), pea (Pisum sativum L.), and gram (Cicer arietinum L.) were grown during the dry season utilising residual soil moisture after rainy season rice.

Results and discussion

Spatial variability of soil texture

In this study, to visualise the effects of mechanical composition of soils on water retention or available water capacity, the soil texture of 0-0.30 m was geo-spatially mapped and is presented in Fig. 3. The data indicate that sandy loam was the main soil texture at 0-0.30 m depth, covering an area of 463 ha, followed by loam (328 ha), and clayey loam texture (229 ha). Coarse-textured soils were mainly found in unbunded upland topography, whereas, the heavy-textured soils occurred in lowland valley fill areas of the watershed, where residual soil moisture can be expected after harvest of rainy season rice.

[FIGURE 3 OMITTED]

Spatial distribution of available water capacity of soils

Profile available water capacity is an important determinant of crop growth and is controlled by soil texture, soil depth, finer clay minerals, etc. For the study area, available water capacity ([m.sup.3]/[m.sup.3]) was determined and geo-spatial distributions are presented in Fig. 4. The available water capacity in different parts of watershed was grouped into 6 classes: 0.08-0.12, 0.12-0.16, 0.16-0.20, 0.20-0.24, 0.24-0.28, and 0.28-0.32 [m.sup.3]/[m.sup.3]. Most of the research area had a water storage capacity of 0.08-0.12 [m.sup.3]/[m.sup.3], followed by the categories of 0.12-0.16 [m.sup.3]/[m.sup.3] and 0.20-0.24 [m.sup.3]/[m.sup.3].

[FIGURE 4 OMITTED]

Spatial distribution of soil organic carbon

Organic carbon content was low in parts of watershed and was mainly responsible for low soil fertility. The geo-spatial distribution of the organic carbon (%) for the upper soil profile (0-0.30 m) is shown in Fig. 5. It ranged from 0.20 to 0.80% in different parts of the watershed, indicating low organic carbon content. Organic carbon in the soil profile was very low in the light-textured soil (0.3-0.4%), and hence, rice-based monoculture, especially in light-textured soil with slopping topography, should be avoided. Integrated nutrient management, such as including legumes in the cropping system during the rainy season and addition of organic matter, are advocated to sustain soil fertility and assure higher net economic return. In medium- to heavy-textured soils with lowland topography, the majority of the area had an organic carbon content of 0.60-0.70%.

[FIGURE 5 OMITTED]

Existing land use/land cover map

Existing land use/land cover map of the watershed shows that of the 1320 ha total area, 1051 ha was under arable field crops (Fig. 6). The agricultural land area was dominated by rainfed, monocropped rainy season rice (843 ha) where productivity was low and unstable. Based on the topography, the rainfed rice area of the watershed was divided into rainfed upland and rainfed lowland. The 139.6 ha of arable land was mainly light-textured, having low water-holding and nutrient status. This type of land physiography either remained fallow or rainfed rice was grown during the rainy season. Second rainfed crops were not possible on such land because the residual soil moisture alter harvest of rainy season rice was insufficient. The 222 ha and 481 ha of land occupied by medium- and heavy-textured arable land, respectively, grew rice during the rainy season. Normally in the dry season these areas remained fallow due to lack of appropriate crop and water management strategies despite adequate residual soil moisture after the harvest of rainy season rice. In some areas, lathyrus was grown as second crop during the dry season; that was exclusively under a relay cropping system with less productivity of 0.15-0.20 t/ha. The watershed area also comprised unused areas with degraded forest and residual hill in 44 ha and 199 ha, respectively.

[FIGURE 6 OMITTED]

Slope coverage

The slope map was prepared from the Survey of India Toposheet (1:50000) as described in the methodology and is presented in Fig. 7. The majority of land (612 ha) had a very gentle slope (1-3%) with medium- to heavy-textured soil. The gentle slope (3-5%) covered an area of 420 ha where the soil was light- to medium-textured with unbunded to bunded fields. Higher slope (>35%) was found in residual hills or degraded forest area. The contours, along with drainage lines, are depicted in Fig. 8, and study reveals that the predominant drainage pattern of the watershed is dendritic, indicating existence of rocks with uniform resistance to erosion in the watershed.

[FIGURES 7-8 OMITTED]

Results of implementation of action plan

Based on potential of existing hydro-physical properties, land use, and topography, an action plan on alternative sustainable land use was developed and its spatial coverage is presented in Fig. 9. The plan was tested in few locations during 20004)1 and 2001 02 as per the alternative crops mentioned in the methodology. Study revealed that the developed cropping system plan was improving production, productivity, and profitability in the rainfed rice area.

[FIGURE 9 OMITTED]

Enhancement of productivity and profitability through crop diversification in a light-textured, rainfed rice area

Through crop diversification in light-textured rice soils, productivity and profitability were enhanced by 3-4 times compared with a rice-only crop. Productivity of different crops/crop combinations grown on light-textured soils was converted into rice-equivalent yield for better comparison. Study (average of 2 years pooled data; Fig. 10a) revealed that the highest rice-equivalent yield (6839 kg/ha) was obtained from groundnut + pigeonpea, followed by sole groundnut (5940 kg/ha) and sole pigeonpea (5315 kg/ha), whereas sole rice produced only 1930 kg/ha. Higher net economic return per annum was also obtained from groundnut + pigeonpea, followed by sole groundnut and sole pigeonpea (Fig. 10b).

[FIGURE 10 OMITTED]

Increasing productivity, profitability, and cropping intensity in medium-textured soil

In the medium-textured soils, emphasis was given to improving the productivity of rice during the rainy season and to growing second crops after harvest. Rice was grown with both farmers' and improved management practices during the rainy season, and linseed, safflower, and greengram were grown during the post-rice (dry) season, utilising residual soil moisture. The productivity of double crops (rice-linseed/safflower/greengram) was converted into rice-equivalent yield and compared with that of sole rice to evaluate the enhancement of yield after introduction of the new cropping system. Sole rice of 120 days duration was grown as a control under both improved and farmers' management practices. Rice-equivalent yields of 5028, 5861, and 5307 kg/ha were obtained from rice-linseed, rice safflower, and rice-greengram, respectively (from 2000-01 and 2001-02 pooled data), whereas sole rice produced only 3540 and 2870 kg/ha yield under improved and farmers' management, respectively (Fig. 11a). Productivity, cropping intensity, and profitability of medium-textured, rainfed rice areas can be improved through crop management utilising residual soil moisture after a rice crop (Fig. 11b).

[FIGURE 11 OMITTED]

Enhancement of productivity and profitability in a heavy-textured, rainfed rice area

In the heavy-textured rice soils, rice of 150 days duration (cv. Gayatri) was grown during the rainy season with both farmers' and improved management practices. During the post-rice (dry) season, pea, blackgram, and gram were grown utilising residual soil moisture.

The productivity of double crops (rice--pea/blackgram/ gram) was converted into rice-equivalent yield for comparison. Rice-equivalent yields (2 years' pooled data) of 6458, 6378, and 5089 kg/ha were obtained from rice-pea, rice--blackgram, and rice-gram, respectively, whereas sole rice produced 3240 and 4050 kg/ha yield with farmers' and improved management, respectively (Fig. 12a). The net returns increased in the order: sole rice (farmers' management), sole rice (improved management), rice-gram, rice blackgram, and rice-pea (Fig. 12b).

[FIGURE 12 OMITTED]

Pedo-transfer functions for prediction of soil water constants and available water capacity

Since direct measurement of water retention characteristics over a large area is expensive, time-consuming, and difficult, in this investigation some of the easily measured soil physical and chemical properties were determined in rainfed rice area and pedo-transfer functions were derived through regression equations to predict water content at field capacity, permanent wilting point, and available water capacity. The correlation matrix for different hydro-physical properties, namely sand, silt, clay, bulk density, organic carbon, calcium carbonate, and cation exchange capacity on water content at field capacity, wilting point, and available water was computed for rainfed rice area of the watershed and results are presented in Table 3. Study revealed that moisture retention at field capacity, wilting point, and available water in these soils were influenced by 2 sets of factors with opposing effects. Silt, clay, organic carbon, calcium carbonate, and cation exchange capacity had a positive influence, while sand and bulk density had a negative influence. The available water content was also influenced by the same set of factors and in a similar manner.

Water content at field capacity and wilting point had a close relationship with clay (r = 0.87* and 0.92*, respectively) and cation exchange capacity (r = 0.80** and 0.74**, respectively). These were significantly but negatively associated with sand and bulk density, indicating that with an increase in value of either sand or bulk density or with a decrease in magnitude of clay or silt or cation exchange capacity, water content, [theta] ([m.sup.3]/[m.sup.3]) of these soils at field capacity and wilting point decreases. Coarse fraction (sand) had a close relationship with bulk density (r = 0.67**), whereas a negative association existed between coarse fraction and finer fraction, i.e. silt (r = 0.85**) and clay (r = 0.86**). Available water showed positive correlation coefficient values with silt, clay, calcium carbonate, and cation exchange capacity, and negative values with sand and bulk density. These results are in good agreement with those of earlier Indian studies (Yadav et al. 1995; Das and Dutta 1997). Stepwise regression equations were developed to predict field capacity, wilting point, and available water capacity from measured soil physico-chemical properties and are presented in Table 4.

Conclusion

The study has demonstrated the potential of GIS in the development of action plans for alternative land-use in watersheds, based on existing soil hydro-physical properties, land cover, and topography. The implemented action plan was found profitable and sustainable with stable productivity in different rainfed rice ecosystems over 2 years. This study has created a great impact in eastern India, where development of site-specific, sustainable cropping systems is vital to improve productivity and cropping intensity of rainfed areas. Pedo-transfer functions will be useful in developing simulation models for predicting soil water constants for large rainfed rice ecosystems of eastern India.
Table 1.
Mean monthly major weather parameters of study area, Dhenkanal
(20[degrees]50'N, 85[degrees]36'E, height 139 m above m.s.l.)

Month Max. Min. Morning Afternoon
 temp. temp. humidity humidity
 ([degrees]C) ([degrees]C) (%) (%)

January 30.9 9.7 75 47
February 36.5 10.0 70 38
March 38.7 12.7 66 33
April 44.6 20.6 64 34
May 46.2 21.5 65 39
June 42.0 23.6 73 60
July 35.7 24.6 82 77
August 38.0 23.4 83 79
September 33.6 23.4 83 77
October 33.8 18.6 80 67
November 32.2 11.5 74 53
December 29.4 9.0 73 48

Month Rain Wind Av. vapour Av. atm.
 (mm) speed pressure pressure
 (km/h) (mb) (mb)

January 15.5 4.8 14.05 999.35
February 17.2 5.8 14.30 996.90
March 25.4 6.6 15.30 994.00
April 37.5 8.1 19.70 990.75
May 64.8 9.6 24.30 986.40
June 263.6 9.3 27.85 983.40
July 369.1 8.2 30.05 983.70
August 281.6 7.2 30.35 985.00
September 220.6 6.3 29.90 988.25
October 93.6 5.5 25.70 993.90
November 25.2 4.5 18.20 997.60
December 4.5 5.0 14.40 999.50

Table 2.
Action plan development based on existing natural resources

Present land use system Texture Organic matter
 range (%)

Current fallow Sandy 0.29
Rainfcd rice Sandy loam 0.29-0.63
Current fallow Sandy loam 0.35-0.65
Degraded forest Sandy loam, loam 0.40-0.68
Degraded forest Loam 0.62
Rubber plantation Sandy loam 0.45
Residual hills Sandy, sand loam 0.29-0.45
Residual hills Sandy loam 0.38-0.52
Residual hills Sandy loam 0.38-0.42
Rice (100 days)-fallow Sandy loam 0.38-0.45
Rice (100 days)-fallow Clayey loam 0.65-0.68
Rice (125 days)-fallow Loamy sand 0.52-0.68
Rice (125 days)-fallow Clayey loam 0.45-0.68
Rice (125 days)-fallow Clay 0.70-0.75
Rice (145 days)-fallow Clayey loam 0.52-0.68
Rice (145 days)-fallow Sandy loam 0.50-0.52
Rural settlement -- --

Present land use system Available water Slope range
 capacity range (%)
 ([m.sup.3]/
 [m.sup.3])

Current fallow 0.009-0.122 3-5, 5-10
Rainfcd rice 0.12-0.139 1-3, 3- 5
Current fallow 0.128-0.140 1-3
Degraded forest 0.118-0.135 1-3, 3-5
Degraded forest 0.111-0.123 3-5, 5-10
Rubber plantation 0.129-0.139 3-5
Residual hills 0.106-0.145 3-5
Residual hills 0.119-0.199 >35
Residual hills 0.119-0.123 3-5
Rice (100 days)-fallow 0.109-0.123 1-3, 3-5
Rice (100 days)-fallow 0.220-0.257 3-5
Rice (125 days)-fallow 0.194-0.239 1-3, 0-1
Rice (125 days)-fallow 0.257-0.285 1-3, 0-1
Rice (125 days)-fallow 0.257-0.306 0-1, 0-3
Rice (145 days)-fallow 0.227-0.257 1-3
Rice (145 days)-fallow 0.173-0.195 3-5, 1-3
Rural settlement -- --

Present land use system Proposed land use system

Current fallow Horticulture (cashew, lemon)
Rainfcd rice Crop diversification (groundnut,
 pigeonpea,groundnut+pigeonpea)
Current fallow Crop diversification (groundnut,
 pigeonpea,groundnut+pigeonpea)
Degraded forest Agroforestry
Degraded forest Horti-pasture
Rubber plantation Plantation
Residual hills Forestry
Residual hills Forestry
Residual hills Agroforestry
Rice (100 days)-fallow Maize (90 days-horsegram
Rice (100 days)-fallow Maize (90 days)-horsegram
Rice (125 days)-fallow Rice (120 days)-linseed/safflower
Rice (125 days)-fallow Rice (120 days)-linseed/safflower
Rice (125 days)-fallow Rice (120 days)-linseed/safflower
Rice (145 days)-fallow Rice (150 days)-pea/black/greengram
Rice (145 days)-fallow Rice (150 days)-pea/black/greengram
Rural settlement Rural settlement

Table 3.
Correlation matrix of different soil hydro-physical parameters
CEC, Cation exchange capacity; PWP, permanent wilting point;
FC, field capacity; AWC, available water capacity

 Sand Silt Clay Bulk
 (%) (%) (%) density
 (Mg/
 [m.sup.3])
Sand 1
Silt -0.85 * 1
Clay -0.86 * 0.50 * 1
Bulk density 0.67 * -0.65 * -0.59 * 1
Organic C -0.09 0.15 -0.02 -0.48 *
CaC03 -0.56 * 0.46 * 0.51 * 0.56 *
CEC -0.76 * 0.48 * 0.73 * -0.59 *
[theta] (FC) -0.86 * 0.68 * 0.87 * -0.64 *
[theta] (PWP) -0.82 * 0.56 * 0.92 * -0.54 *
[theta] (AWC) -0.76 * 0.74 * 0.66 * -0.62 *

 Organic CaC[O.sub.3] CEC
 carbon (%) (cmol/kg)
 (%)

Sand
Silt
Clay
Bulk density
Organic C 1
CaC03 0.14 1
CEC 0.12 0.44 * 1
[theta] (FC) 0.03 0.54 * 0.80 *
[theta] (PWP) 0.04 0.54 * 0.74 *
[theta] (AWC) 0.16 0.48 * 0.67 *

 [theta] (FC) [theta] (PWP) [theta] (AWC)
 ([m.sup.3]/ ([m.sup.3]/ ([m.sup.3]/
 [m.sup.3]) [m.sup.3]) [m.sup.3])

Sand
Silt
Clay
Bulk density
Organic C
CaC03
CEC
[theta] (FC) 1
[theta] (PWP) 0.91 * 1
[theta] (AWC) 0.95 * 0.68 * 1

* P < 0.05.

Table 4.
Linear regressions (y = bx + a) for predicting soil water constants
and available water y; Output (FC/PWP/AWC); x, inputs (soil physical
and physico-chemical properties); a, constant; b, slope

 a b

 Sand Silt Clay Bulk
 (%) (%) (%) density
 (Mg/
 [m.sup.3])

For field capacity ([theta], [m.sup.3]/[m.sup.3])

 1.56 -0.015 -0.014 -0.013 0.042
 -5.524 0.058 0.062 0.065 -0.105
 -9.955 0.106 0.105 0.112 -0.201
 -9.945 0.096 0.102 0.105 -0.187
 -4.321 0.045 0.048 0.051 --
 -0.711 0.008 0.004 -- --
 0.574 -0.006 -- -- --
 0.524 -0.006 0.002 -- --

For wilting point ([theta], [m.sup.3]/[m.sup.3])

 9.78 -0.007 -0.097 -0.096 0.043
 6.70 -0.068 -0.068 -0.064 -0.018
 5
 3.69 -0.037 -0.033 -0.032 -0.085
 5.34 0.054 -0.050 0.049 -0.039
 6.34 -0.063 -0.065 -0.058 --
 0.49 -0.006 0.005 -- --
 0.30 0.004 -- -- --
 0.40 -0.005 0.005 -- --

For available water ([theta], [m.sup.3]/[m.sup.3])

 -8.29 0.082 0.087 0.085 0.003
-12.49 0.124 0.128 0.126 -0.085
-13.63 0.138 0.143 0.142 -0.116
-14.72 0.151 0.157 -0.154 -0.147
-10.64 0.109 0.113 0.108 --
 0.27 -0.003 0.002 -- --
 0.25 -0.004 -- -- --
 0.14 -0.002 0.003 -- --

 b [R.sup.2]

 Bulk Organic CaC[0.sub.3] CEC
 density carbon (%) (%) (cmol/kg)
 (Mg/
[m.sup.3])

For field capacity ([theta], [m.sup.3]/[m.sup.3])

 0.042 0.004 0.014 0.004 0.84
 -0.105 0.002 0.016 -- 0.80
 -0.201 -0.059 -- -- 0.82
 -0.187 -- -- -- 0.82
 -- -- -- -- 0.80
 -- -- -- -- 0.79
 -- -- -- -- 0.83
 -- -- -- 0.003 0.84

For wilting point ([theta], [m.sup.3]/[m.sup.3])

 0.043 -0.017 0.012 0.001 0.86
 -0.018 -0.015 0.012 -- 0.84

 -0.085 -0.019 -- -- 0.85
 -0.039 -- -- -- 0.85
 -- -- -- -- 0.83
 -- -- -- -- 0.85
 -- -- -- -- 0.79
 -- -- -- 0.001 0.86

For available water ([theta], [m.sup.3]/[m.sup.3])

 0.003 0.013 0.004 0.003 0.66
 -0.085 -0.015 0.005 -- 0.64
 -0.116 -0.013 -- -- 0.65
 -0.147 -- -- -- 0.62
 -- -- -- -- 0.63
 -- -- -- -- 0.61
 -- -- -- -- 0.60
 -- -- -- 0.002 0.66


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Manuscript received 2 September 2003, accepted 2 March 2004

Gouranga Kar (A,B), Ravender Singh (A), and Harsh Nath Verma (A)

(A) Water Technology Center for Eastern Region (I.C.A.R.), PO, S.E. Railway Project Complex, Chandrasekharpur, Bhubaneswar--751023, Orissa, India.

(B) Corresponding author; email: kar_wtcer@yahoo.com
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Author:Kar, Gouranga; Singh, Ravender; Verma, Harsh Nath
Publication:Australian Journal of Soil Research
Date:Jul 1, 2004
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