Environ Geol (2009) 56:1237–1243 DOI 10.1007/s00254-008-1223-2
ORIGINAL ARTICLE
Changes in soil quality indicators under long-term sewage irrigation in a sub-tropical environment Reginald Ebhin Masto Æ Pramod K. Chhonkar Æ Dhyan Singh Æ Ashok K. Patra
Received: 5 December 2007 / Accepted: 28 January 2008 / Published online: 14 February 2008 Ó Springer-Verlag 2008
Abstract Though irrigation with sewage water has potential benefits of meeting the water requirements, the sewage irrigation may mess up to harm the soil health. To assess the potential impacts of long-term sewage irrigation on soil health and to identify sensitive soil indicators, soil samples were collected from crop fields that have been irrigated with sewage water for more than 20 years. An adjacent rain-fed Leucaena leucocephala plantation system was used as a reference to compare the impact of sewage irrigation on soil qualities. Soils were analyzed for different physical, chemical, biological and biochemical parameters. Results have shown that use of sewage for irrigation improved the clay content to 18–22.7%, organic carbon to 0.51–0.86% and fertility status of soils. Build up in total N was up to 2,713 kg ha-1, available N (397 kg ha-1), available P (128 kg ha-1), available K (524 kg ha-1) and available S (65.5 kg ha-1) in the surface (0.15 m) soil. Long-term sewage irrigation has also resulted a significant build-up of DTPA extractable Zn (314%), Cu (102%), Fe (715%), Mn (197.2), Cd (203%), Ni (1358%) and Pb (15.2%) when compared with the adjacent rain-fed reference soil. Soils irrigated with sewage exhibited a significant decrease in microbial biomass carbon (-78.2%), soil
R. E. Masto P. K. Chhonkar D. Singh A. K. Patra Division of Soil Science and Agricultural Chemistry, Indian Agricultural Research Institute, New Delhi 110 012, India Present Address: R. E. Masto (&) Environmental Management Division, Central Institute of Mining and Fuel Research, Digwadih Campus (Erstwhile Central Fuel Research Institute), Dhanbad 828 108, Jharkhand, India e-mail:
[email protected]
respiration (-82.3%), phosphatase activity (-59.12%) and dehydrogenase activity (-59.4%). An attempt was also made to identify the sensitive soil indicators under sewage irrigation, where microbial biomass carbon was singled out as the most sensitive indicator. Keywords Sewage water Irrigation Heavy metals Soil enzymes Microbial biomass carbon Soil quality indicators
Introduction In peri-urban agriculture around major metropolitan cities in India the use of domestic and industrial effluents for irrigation is inevitable due to over-exploitation of underground water. The farmers are enthusiastic to use sewage effluent for the purpose of irrigation because this is a rich source of organic matter and essential plant nutrients (Rattan et al. 2005). The use of sewage effluents for irrigating agricultural land is a worldwide practice (Feign et al. 1991). It is especially common in developing countries, where water treatment cost is high. As there is a gradual decline in availability of fresh water for irrigation in India, the use of sewage and other industrial effluents for irrigating agricultural lands is on the rise (Rattan et al. 2005). For the farmers, opportunities exist as sewage effluents from domestic origin are rich in organic matter and also contain appreciable amounts of major and micronutrients. Accordingly nutrient levels of soils are expected to increase with continuous irrigation with sewage water (Yadav et al. 2002). Although there is a strong possibility of agronomic and economic benefits of wastewater irrigation; however, in the long-term pollutants could be slowly introduced and accumulated in the soils and
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cause a potential risk to soil quality and productivity (Friedel et al. 2000). Studies conducted have shown that the application of sewage water to irrigate sandy soils has a marked effect on improving the soil texture and structure and increasing the water-holding capacity, the carbon content and soil aggregation, while decreasing the bulk density (BD) and improving the hydraulic conductivity. In the past, the effects of sewage water irrigation on soil physical and chemical parameters have been studied in more detail, but information on the effects of sewage effluent irrigation on soil biological and biochemical indicators are largely unknown. The present study was conducted to determine, (1) the effect (positive, negative or no effect) of long-term wastewater irrigation on soil quality indicators, (2) to evaluate the sensitivity of different microbial parameters and (3) to identify the most sensitive soil indicator under sewage irrigation. Materials and methods Experimental site The long-tern sewage irrigation plots at Indian Agricultural Research Institute (IARI), New Delhi, India (28°40 N latitude, 77°120 E longitude; 228.2 m above sea level) was selected for this study. The plots have been irrigated with sewage water for more than 20 years. The experimental area is characterized as semi-arid sub-tropical with a mean annual precipitation of about 670 mm, mostly occurring during July–September and a mean annual maximum and minimum air temperature of 40.5 and 6.5°C, respectively. In the sewage-irrigated rice–wheat cropping system the high-yielding varieties of both the crops (rice, wheat) are grown with chemical fertilizers. A fertilizer dose of 120 kg N, 60 kg P2O5, and 60 kg K2O ha-1 is applied to each crop. Both crops are irrigated with sewage effluents from sewage treatment plants at the IARI Farm. Soil sampling The sewage irrigated rice–wheat plots were situated about 1 km away on the western fringe of the IARI research farm. The cropping histories of the sampling sites are SW1: paddy nursery followed by wheat, the field was kept fallow in between paddy transplantation and wheat sowing; SW2, SW3, SW4, SW5, SW6 are under continuous rice–wheat cultivation. Each sewage irrigated system had three replicated plots each more than 200 m2 area. Composite surface (0–15 cm depth) soil samples were collected from each plot after crop harvest in the year 2002. From each replicate, five soil cores were collected and pooled as composite sample. A soil sample was also collected from a nearby
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rain-fed agro-forestry system, which comprises mixed plantations of Eucalyptus tereticornis L. and Leucaena leucocephala L. The later was used as a reference to assess the impact of sewage irrigation on soil quality. Pseudoreplication approach of sampling has been adopted (Patra et al. 2005). The samples were characterized for various physical, chemical and biological parameters as follows. Methods of soil analysis Bulk density was determined from the soil cores using the procedure given by Veihmeyer and Hendrickson (1948), and porosity was derived from BD using the following formula: porosity (P) = [1 - (BD/PD)] 9 100, where PD is the particle density determined using a Keen Raczkowald (KR) box (Baruah and Barthakur 1999). Maximum water holding capacity (MWHC) was determined by equilibrating the soil with water through capillary action in a KR box (Baruah and Barthakur 1999). Percent clay, silt and sand were determined by the international pipette method (Piper 1966). Soil pH and EC were determined at 1:2.5 soil–water ratio using a glass electrode and conductivity bridge, respectively. Cation exchange capacity (CEC) was measured by the sodium saturation method (Jackson 1973). Soil organic carbon (SOC) was determined by dichromate oxidation (Walkley and Black 1934); total soil N by the Kjeldahl method (Bremner and Mulvaney 1982) and available N by the alkaline potassium permanganate distillation method (Subbiah and Asija 1956). Available phosphorus (P) in soil was determined by extracting samples with 0.5 M NaHCO3, and determining P colorimetrically using molybdate (Olsen et al. 1954). Available potassium was determined using 1 N ammonium acetate extraction followed by emission spectrometry (Jackson 1973). Available S was extracted with 0.15% CaCl2 solution and the S in the extract was determined turbidimetrically (Williams and Steinbergs 1959). Available Zn, Cu, Mn and Fe were determined using 0.005 M DTPA extraction followed by atomic absorption spectrometry (Lindsay and Norvell 1978). The P and K fixing capacities were determined by following the method prescribed by Waugh and Fitts (1966). Microbial biomass carbon was measured by the fumigation extraction method (Jenkinson and Ladd 1981). Soil dehydrogenase was determined using the method of Klein et al. (1971). Phosphatase enzyme activities were determined by the method of Tabatabai and Bremner (1969). Soil respiration was measured using a constant volume Warburg manometer (Umbrert et al. 1972). Statistical analysis Analysis of variance (ANOVA) was performed to determine the effects of sewage treatment on soil
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quality parameters. For statistical analysis of data (PCA, correlations) Microsoft Excel and SPSS window version 10.0 (SPSS Inc., Chicago, USA) packages were used. Soil quality indicators were tested for their level of significance at P = 0.05. Results and discussions Soil physical properties The clay content (Table 1) in sewage irrigated soils was higher (18–22.7%) than that of reference soil (18%), consequently the textural class of the sewage irrigated soils was sandy clay loam, whereas it was sandy loam in the reference soil. Abd Elnaim et al. (1987) reported textural changes in the profiles due to prolonged irrigation with sewage water. The increase in clay content of soil by sewage irrigation is mainly due to the clay addition from sewage water. Mathan (1994) reported 32% clay in dry matter (35%) of sewage water used for irrigation. Physical properties like BD, porosity and water holding capacity was not much increased in sewage irrigated soils. The values of BD in sewage irrigated soils ranged from 1.47 to 1.51 Mg m-3 whereas the BD of reference soil was 1.28 Mg m-3. Contrary to the findings of the present study, Mathan (1994) reported that the physical properties of the sandy loam soils were improved by using sewage irrigation water. Continuous use of sewage water progressively improved the hydraulic conductivity, BD and porosity. Other workers claimed that the increase in the organic matter content of soils by sewage improves the physical properties of the soils (Diez 1981; Furrer and Stauffer 1981). Thus the major factor in improving the physical condition is the organic matter, in the present study as the reference soil is an undisturbed plantation site, the organic matter was very high in reference soil (1.14%) than sewage irrigated soils (0.51–0.86%). Higher organic carbon content in the reference soil (1.14%) might have decreased the BD by diluting the soil matrix with less denser material (organic matter) as well as by improving soil aggregation (Sur et al. 1993). The variation in MWHC of soils, here in, might be due to the organic matter or clay content of soils or their combinations. The very high organic matter content in reference soil has masked the effect of sewage irrigation on soil physical properties. However, the observed values under sewage plots are well within the acceptable levels for cultivated agricultural soils (Masto et al. 2007, 2008).
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In general the pH was not affected due to sewage irrigation, probably due to the improvement in soil buffering capacity owing to increase in soil clay content. EC was very high under SW-5 (0.978) and for rest of the sewage-irrigated soils it varied from 0.550 to 0.700 dS m-1, the EC at reference soil was 0.374 dS m-1. The increase in soluble salts in sewage treated soils could be ascribed to the extensive additions of anions and cations in the sewage. Similar result was reported by Subbiah and Ramulu (1979). The sewage system showed a significant difference in CEC with the highest value under SW-2 (14.89) followed by SW-1 (14.73) and SW-3 (14.00), and sewage nursery recorded the lowest CEC of 12.51 cmol (p+) kg-1. The variation in CEC of soils, here in, might be due to the variation in SOC or clay content or their combinations. The SOC ranged from 0.510% for SW-4 to 0.860% for SW-2. Saber (1986) reported increased SOC contents in fields irrigated with wastewater, and ascribed this to increased organic matter input via irrigation water. There was significantly higher SOC in the sewage-treated soil as compared with the limits provided by Masto et al. (2007, 2008) due to the addition of carbonaceous materials and maintenance of anaerobic conditions (Subbiah and Ramulu 1980; Gupta et al. 1993). Total N varied from 1,869 kg ha-1 for SW-4 to 2,713 for SW-2 and available N from 213 kg ha-1 for SW-5 to 397 for SW-2. The increase in available N content due to addition of sewage might have been a result of increased microbial activity leading to greater mineralization. SW-1 and SW-2 had very high amount of available P viz. 112.7 and 128 kg ha-1, respectively, for rest of the sewage treatments it ranged between 60.3 and 87.7. Sewage treatment increased the soil available P content to greater extent, which might be due to lesser P fixation. Baddesha et al. (1997) also observed increase in available P following irrigation with sewage water over a period of 30 years. Maximum K content was observed under SW-5 (524 kg ha-1) and the least under sewage nursery (334). The range of available S in sewage systems was from 17.5 mg kg-1 for SW-4 to 65.5 for SW-5. The increase in SO42- concentration with prolonged sewage application may be due to the biological oxidation of the protein sulphur in the sewage. Thus, among the chemical parameters the EC was affected in some sewage treated plots in comparison with reference, besides there was a significant built up of plant nutrients particularly P and S due to sewage irrigation.
Soil chemical parameters
Trace metals
The pH (1:2.5) of the soils under different sewage irrigated plots and reference soil ranged from 7.43 to 7.7 (Table 1).
The accumulation of heavy metals in soils and their uptake by plants represent the greatest potential problem of
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Table 1 Effect of long-term sewage irrigation on soil physical, chemical and biological properties Parameters
SW-1
SW-2
SW-3
SW-4
SW-5
SW-6
Ref.
LSD (P = 0.05)
Clay (%)
22.7
21
22.3
23.2
18
19.7
18
NS
Silt (%)
23
24.7
22.3
22.3
21.7
21
27.7
NS
Sand (%)
54.3
54.3
55.3
54.5
60.3
59.3
54.3
Texture
Sandy clay loam
Sandy clay loam
Sandy clay loam
Sandy clay loam
Sandy loam
Sandy loam
Bulk density (Mg m-3)
1.5
1.47
1.47
1.44
1.51
1.49
Porosity (%)
36
37.4
37.4
38.6
35.9
36.5
45.7
NS
Water holding capacity (%)
36.4
39.6
39.7
37
36.3
37.9
58.1
NS NS
Sandy loam 1.28
pH
7.7
7.53
7.43
7.73
7.47
7.63
7.6
EC (dS m-1)
0.545
0.66
0.634
0.698
0.978
0.453
0.374
-1
CEC (cmol (P+) kg )
12.51
14.73
14.89
14
13.76
13.04
Organic carbon (OC) (%)
0.618
0.604
0.86
0.609
0.51
0.51
Total N (kg ha-1)
2,209
2,153
2,713
2,061
1,891
1,869
Available N (kg ha-1)
309
385
397
275
213
271
Available P (kg ha-1)
60.3
112.7
128
87.7
76
87
16.25 1.149 4,714 390 17.7
4.03 – NS
0.048 0.94 0.03 211 27.7 11.1
P fixing capacity (%)
6.3
13.5
16.1
17.2
7.4
6.9
19
1.31
Available K (kg ha-1)
334
359
456
374
524
466
480
9.00
K fixing capacity (%)
33.6
35.2
36.6
31.5
38.4
36.8
38.7
3.00
Available S (kg ha-1) DTPA-Zn (mg kg-1)
58.3 3.22
60.5 1.86
63.3 10.02
63.7 4.12
65.5 2.39
17.5 2.43
10.84 2.42
4.4 0.42
DTPA-Cu (mg kg-1)
1.83
2.87
4.6
1.91
2.18
1.14
1.42
0.51
DTPA-Mn (mg kg-1)
7.62
9.51
12.2
13.5
14.9
22
7.4
2.8
DTPA-Fe (mg kg-1)
37.7
24.8
54
21.6
36.6
12.3
6.62
2.7
DTPA-Cd (mg kg-1)
0.035
0.071
0.09
0.073
0.03
0.091
0.03
0.034
DTPA-Pb (mg kg-1)
2.94
3.42
4.18
3.57
3.16
3.53
3.63
0.35
DTPA-Ni (mg kg-1)
0.429
0.309
0.364
0.744
0.173
0.327
0.051
0.099
Respiration (ll O2 g
-1
-1
5.98
5.63
4.85
4.9
2.97
1.89
Microbial biomass carbon (MBC) (mg kg-1)
h )
395
488
557
340
147
146
10.65
MBC/OC
6.39
8.09
6.48
5.57
2.89
2.87
Dehydrogenase (lg TPF g-1 soil for 24 h)
112
65.3
80.4
66.7
52.9
70.8
160.9
7.5
Acid phosphatase (lg PNP g-1 h-1)
113.6
66.3
115.2
91.4
35.6
53.5
96.3
24.1
Alkaline phosphatase (lg PNP g-1 h-1)
282
226
259
186
209
186
670 5.87
455
0.34 54.3 0.91
20.4
SW sewage water irrigated field
sewage disposal to agricultural land. Generally, the accumulation of trace metals resulting long-term irrigation with sewage water was in the following order: Fe [ Mn [ Zn [ Pb [ Cu [ Ni [ Cd. Long-term sewage irrigation resulted into significant build-up of DTPA extractable Zn (314%), Cu (102%), Fe (715%), Mn (197.2), Cd (203%), Ni (1358%) and Pb (15.2%) when compared with adjacent rain-fed reference soil. There was significant accumulation of trace metals particularly Ni and Fe.
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Soil biological parameters Changes in soil biological characteristics may be sensible indicators of soil health, since they are more dynamic and often more sensitive than physical or chemical soil properties. The dehydrogenase activity ranged from 52.9 lg TPF -1 g /24 h for SW-4 to 112 for SW-1. Dehydrogenase activity is sensitive to heavy metal pollution (Reddy et al.
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1987; Kandeler et al. 1996). The acid phosphatase ranged from 35.6 to 115.2 and alkali phosphatase from 186 to 282 lg PNP g-1 h-1. Soil respiration was much affected by sewage treatments; the least respiration was recorded under SW-4 (1.89 ll O2 g-1 h-1) or SW-5 (2.97), whereas the respiration recorded at reference soil was 10.65. The MBC was significantly affected by sewage treatments, SW5 and SW-4 had lowest MBC of 147 and 146 mg kg-1 respectively and MBC was found to be higher in SW-2 (557) and SW-1 (485). Higher MBC recorded in some sewage-treated soils was due to the supply of easily biodegradable organic matter. However, in SW-4 and SW-5 the MBC was suppressed because of the high soluble salt content (EC 1:2.5 = 0.978 dS m-1) found in these soils. Application of wastewater containing organic matter and nutrients has been found to increase total soil microbial
biomass (Goyal et al. 1995) and bacteria, fungi and actinomycetes (Saber 1986) in field experiments. Among the sewage system the MBC/OC ranged from 2.89 for SW-4 to 8.09 for SW-1. As such, soil respiration, microbial biomass and other enzyme activities were lower in sewage-irrigated soils than the rain-fed soil.
Identification of soil indicators Principal component analysis (PCA) has been widely used as a tool to identify soil indicators (Wander and Bollero 1999; Andrews et al. 2002; Sharma et al. 2005; Masto et al. 2008). Principal components (PCs) for a data set are defined as linear combinations of the variables that account for maximum variance within the set by describing vectors
Table 2 Results of principal component analysis of soil parameters under long-term sewage irrigation plots Principal components
PC-1
PC-2
PC-3
PC-4
PC-5
PC-6
Eigenvalue
10.0
5.04
3.75
2.90
2.02
1.01
Variation (%) Cumulative variation (%)
37.08 37.08
18.69 55.77
13.90 69.67
10.73 80.41
7.48 87.95
3.77 91.68
Eigenvectors Clay
0.572
-0.366
-0.400
-0.138
0.399
Silt
0.463
-0.257
-0.008
-0.261
-0.686
0.003
Sand
-0.692
0.423
0.365
0.241
0.001
0.157
Bulk density
-0.371
-0.148
0.655
0.494
-0.234
0.164 0.168
Water holding capacity
-0.213
0.457
0.437
-0.115
0.299
-0.562
pH
-0.152
-0.502
-0.391
0.240
-0.137
0.536
EC
-0.188
0.221
0.505
-0.769
0.002
0.235
CEC
0.537
0.620
-0.104
-0.402
-0.234
0.005
Organic carbon
0.916
0.227
0.009
0.127
0.244
0.003
Total nitrogen
0.880
0.144
0.230
0.258
0.005
0.120
Available nitrogen
0.853
0.108
-0.006
0.235
-0.297
-0.218
Available potassium
-0.449
0.735
0.381
0.0005
0.226
0.003
Available phosphorus
0.612
0.688
-0.141
0.0009
-0.163
-0.008
Available sulphur DTPA zinc
0.517 0.734
-0.158 0.395
0.420 0.129
-0.649 0.208
0.003 0.449
0.297 0.136
DTPA manganese
0.799
0.448
0.347
-0.002
-0.001
0.005
DTPA iron
0.637
0.105
0.672
-0.002
0.284
0.002
DTPA zinc
-0.001
-0.644
0.558
-0.315
0.288
0.235
DTPA cadmium
0.264
0.516
-0.540
0.396
-0.216
0.120
DTPA lead
0.508
0.722
-0.260
0.171
0.128
0.127 0.472
DTPA nickel
0.266
-0.310
-0.611
-0.008
0.304
Soil respiration
0.760
-0.553
0.004
-0.215
-0.188
0.007
Dehydrogenase activity
0.394
-0.677
0.009
0.502
0.135
-0.006
Acid phosphatase
0.741
-0.363
-0.005
0.332
0.318
0.167
Alkali phosphatase
0.605
-0.398
0.567
0.275
-0.009
-0.179
Microbial biomass carbon
0.966
-0.007
-0.001
-0.004
-0.123
-0.119
Boldface factor loadings are considered highly weighed
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Table 3 Correlations among the highly loaded variables
Silt
Silt
BD
pH
1.00
-0.18
0.18
0.02
0.186
0.314
0.183
0.352
0.085
-0.05
0.039
0.169
0.528
0.072
0.014
-0.320
-0.049
0.251
-0.378
-0.156
0.056
-0.364
-0.444
0.165
-0.374
1.000
-0.335
-0.235
-0.155
-0.393
-0.359
-0.185
-0.410
-0.283
0.393
0.325
-0.161
1.000
-0.157
-0.177
0.459
-0.080
0.647
0.301
-0.169
-0.260
-0.584
-0.206
1.000
0.911
-0.128
0.660
0.399
0.753
0.639
0.171
0.337
0.829
1.000
-0.169
0.598
0.382
0.738
0.557
0.084
0.370
0.800
1.000
0.118
-0.196
0.143
0.222
-0.552
-0.584
-0.539
1.000
0.116
0.279
0.799
-0.074
-0.299
0.598
1.000
0.622
-0.019
0.144
-0.013
0.492
1.000
0.251
-0.217
0.305
0.546
1.000
0.167 1.000
-0.202 0.211
0.370 0.211
BD pH EC SOC
1.000
EC
SOC
TN
TN Av. K
Av. K -0.52
Av. P Av. S
Av. P
Av. S
Fe Pb Ni DEH
Fe
Pb
Ni
DEH
1.000
MBC
MBC
0.377 1.000
BD bulk density, SOC soil organic carbon, TN total nitrogen, Av. available, DEH dehydrogenase activity, MBC microbial biomass carbon Boldface r values were considered as highly correlated
of closets fit to the n observations in p-dimensional space, subject to being orthogonal to one another (Dunteman 1989). Standardized PCA of all (untransformed) data were performed using SPSS package. PCs with eigenvalue C 1 (Kaiser 1960) and explained at least 5% of the variation of the data are examined (Wander and Bollero 1999, Sharma et al. 2005). Under a particular PC, only the variables with high factor loading were retained for inclusion as indicators. High factor loading were defined as having absolute value within 10% of the highest factor loading (Wander and Bollero 1999; Andrews et al. 2002; Sharma et al. 2005, Masto et al. 2008). When more than one variable was retained under a single PC, multivariate correlation were employed to determine if the variables could be considered redundant and, therefore, eliminated from the indicator set (Andrews et al. 2001). If the highly loaded factors were not correlated then each was considered important, and thus, retained in the indicator set. Among well-correlated variables, the variable with the highest factor loading (absolute value) was chosen as indicator. The entire data set was subjected to PCA to identify the critical soil parameters under the sewage irrigation that can be considered as soil indicators. The first six PCs had eigenvalues [ 1.0 (Table 2). The highly weighted variables under PC-1 were microbial biomass carbon, organic carbon, and total nitrogen, PC-2: available P, K, Pb and dehydrogenase activity, PC-3: BD, available Fe and Ni, PC-4: EC, available S, PC-5: silt, PC-6: pH. Correlation analysis among the above highly weighted variables were done to remove the redundant variables (Table 3), accordingly organic carbon, total nitrogen and microbial biomass are highly correlated, and finally only microbial biomass
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carbon was included in the indicator set owing to its higher factor loading (Table 2) than organic carbon or total N. Thus the retained indicators in descending order of importance are as follows: microbial biomass carbon [ available K [ DTPA-Pb [ available P [ dehydrogenase activity [ DTPA-Fe [ bulk density [ DTPA-Ni [ electrical conductivity [ available S [ silt content [ soil pH. Thus these indicators may be used for evaluation of the sewageirrigated soil in future. Similar type of PCA-based soil indicators were developed by Andrews et al. (2001, 2002), they suggested that once the MDS is established there may be no need for testing a broad array of other indicators to assess soil health over time.
Conclusions Use of sewage for irrigation improved the organic carbon to 0.51–0.86% and fertility status of soils. Build up in total N was up to 2,713 kg ha-1, available N (397 kg ha-1), available P (128 kg ha-1), available K (524 kg ha-1) and available S (65.5 kg ha-1) in the surface (0–15 cm depth) soil. In line with plant nutrients the undesirable bioavailable heavy metals have increased. Long-term sewage irrigation resulted into significant build-up of DTPA extractable Zn (314%), Cu (102%), Fe (715%), Mn (197.2%), Cd (203%), Ni (1358%) and Pb (15.2%) when compared with adjacent rain-fed reference soil. Soils receiving sewage irrigation exhibited significant decrease in microbial biomass carbon (-78.2%), soil respiration (-82.3%), phosphatase activity (-59.12%) and dehydrogenase activity (-59.4%). An attempt was also made to
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identify the sensitive soil indicators under sewage irrigation, where microbial biomass carbon was found to be the most sensitive indicator.
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