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Stream chemistry in the middle hills and high mountains of the Himalayas, Nepal
Journal &rology ELSEVIER
Journal
of Hydrology
166 (1995) 61-79
[31
Stream chemistry in the middle hills and high mountains of the Himalayas, Nepal Alan Jenkinsa,*, bDepartment
William T. Sloana, B. Jack Cosbyb
aInstitute of Hydrology, Wallingford, OX10 8BB. UK of Environmental Science, University of Virginia, Charlottesville. Received
29 April 1994; revision
accepted
16 August
VA 22903, USA
1994
Abstract The major ion chemistry of samples from 216 headwater streams in the Everest, Annapurna, Langtang and Nuwakot regions of the middle and high mountains of the Nepal Himalayas is described. Samples were collected at low flow during February-March 1992, the dry season
between the winter and summer monsoon periods. The resulting database provides a baseline against which to assess natural and anthropogenic influences on water chemistry in these environments. Differences in bedrock geology generally determine differences in chemical characteristics between the four regions. Ion concentrations tend to decrease with altitude, reflecting differences in land use, land management, natural vegetation and atmospheric deposition, all of which are correlated with altitude. The well buffered nature of the pristine, high altitude streams indicates that increased atmospheric deposition of S and N compounds is unlikely to cause acidification of streamwater, although these systems currently leak low concentrations of Nos. Terraced agriculture contributes significantly to differences in chemistry both between and within regions. Water draining agricultural catchments has higher concentrations of nutrients (NOs, PO,) and acid anions (Cl, SO& probably as a result of mineral fertiliser inputs and of trace metals (Fe, Al, Ba, St-, Mn) Si and F, potentially due to increased weathering.
1. Introduction
This study presents the first wide-scale survey of the chemistry of medium to high altitude first order streams in the Himalaya of Nepal. It was carried out in conjunction with a survey of stream macro-invertebrates (Rundle et al., 1993). The objective was to characterise the water chemistry of these geologically young environments and to determine the nature and degree of anthropogenic impacts on stream chemistry. * Corresponding
author.
0022-1694/95/$09.50 0 1995 - Elsevier Science B.V. All rights reserved SSDI 0022-l 694(94)02600-9
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The impact on water chemistry of anthropogenic pollution from industrial and agricultural sources has concerned environmentalists and scientists for the past two decades. In consequence, the chemistry of headwater streams, lakes and lowland rivers has been monitored widely in Europe and North America in an effort to define and quantify these anthropogenic impacts. An understanding of how anthropogenic pollutants affect water chemistry, and thereby the ability to predict the location and severity of potential impacts, can be achieved only through knowledge of hydrochemical processes in pristine waters of similar physico-chemical characteristics (Brims et al., 1991). If a sufficiently detailed knowledge of pristine, or baseline, water chemistry is available, the effects of local pollution, stemming from land use and land management, and of regional pollution, from atmospheric deposition of acidic oxides for example, can be quantified. Attention to the chemical quality of lakes and impoundments in the Himalayas has focused on the problem of eutrophication and salinity, in Nepal (Ferro, 1982; Lohmann et al., 1988; Jones et al., 1989) and in Kashmir (Kaul, 1977). The chemistry of running waters draining the high mountain areas of Asia, however, is largely unknown. Studies of water quality in these areas have been based on infrequent sampling of a few rivers draining large catchments (>lO km2). Major lowland rivers have been studied in, for example, the Kathmandu Valley, Nepal (Upadhyaya and Roy, 1982; Tiwari and Ali, 1987), the Kumaun Region, Uttar Pradesh, India (Paul and Verma, 1990; Bhatt and Pathak, 1992) and the Andhra Pradesh region, India (Naidu et al., 1989). The conclusions from these studies are that the degree of pollution of these rivers increases with distance from the high mountain first order streams and that pollution is increasing through time. This is intuitively expected since human populations within catchments increase with downstream distance as, indeed, do agricultural activity and effluent inputs. The fast growing population in many of the developing Asian countries is predicted further to intensify agricultural production requirements and so the use of mineral and organic fertilisers to increase crop yield and the conversion of upland grazing, alpine scrub and forest to terraced agricultural land is likely to increase in the near future. Furthermore, as tourism is established as a major industry in mountain and remote areas, human habitation and road transport will reach further into what were previously ‘natural’ environments. Recent awareness of this situation has led to calls for sustainable development of natural resources such that ecosystem stability is maintained (IUCN, 1988). Furthermore, many studies of snow chemistry from high altitude Himalayan glaciers have reported concentrations of NO3 and SO4 of magnitudes comparable to those experienced in areas of north-west Europe where surface waters are currently acidified (Mayewski et al., 1986; Nijampurkar et al., 1993). The deposition of acidic oxides is likely to increase in the future in line with expected increases in emissions in the developing areas of Asia (Galloway, 1989).
2. Survey area The streams sampled are located in four regions of the middle and high Himalayas of Nepal: the Shorong and Hinku Kholas, Everest area (Region A), the Modi Khola, Annapurna area (Region B), the Helambu and Langtang Kholas, Langtang area
A. Jenkins et al. / Journal
of Hydrology166
(1995) 61-79
63
(Region C) and the Likhu Khola, Nuwakot District (Region D) (Fig. 1). All of the streams are first or second order tributaries of five of the major rivers of Nepal which themselves drain into the Ganges. The detailed geology of the middle hills and high mountains is poorly documented (Fig. 1) and the dominant bedrock geology is reported to consist of Pre-Cambrian gneiss (United Nations, 1986). Large areas of low-grade metamorphic green schist were noted in the field in all sampling regions. The Central Himalayan Thrust fault is associated with a calcareous formation and dolomite was noted in the. field in the Annapurna area. Natural vegetation in all of the four regions is strongly zoned by altitude and so reflects a north (high mountains) to south (middle hills) gradient. In the subtropical climatic zone, from approximately 1000-1700 m, Chir pine forests predominate. The temperate zone, between 1700 and 3000 m approximately, is dominated by mixed forests of oak (Quercus), rhododendron and fir (Abies spectabilis and A. pindrow), although blue pine (Pirzus wallichiana), Himalayan hemlock (Tsuga dumosa), spruce (Picea smithiana) and bamboo (Bambusa sp. and Arundinaria sp.) are also present. In the subalpine zone, approximately 3000-3800 m, Himilayan silver fir (Abies spectabilis) and birch (Betula utilis) dominate but are replaced by juniper (Juniperus sp.) and bamboo at higher elevations. In the alpine zone, above the tree line and below the limit of permanent snow cover, juniper and rhododendron shrubs grow and grassland is common. Glaciers and permanent snow fields are widespread above the alpine zone and feed some of the high elevation streams directly. Agriculture in Nepal consists almost exclusively of terraced cultivation. Two types of terrace predominate; rice is grown on level terraces (khet land) and mainly maize, millet and mustard on sloping terraces (bari land). At lower elevations and near to stream channels, level terraces are irrigated by diverting streamflow whilst at high elevations and on catchment divides, rainwater is held back by terrace risers to ensure the necessary flooding of the rice padi. Sloping terraces are exclusively rain-fed. Extensive applications of pesticides, as well as of fertilisers, in the form of farmyard manure and inorganic nitrogen and phosphorous compounds, are common on khet land with less frequent or intensive application to bari land. The land-use of the catchments was classified from 1 : 50000 scale land-use maps (HMG Nepal, 1984) as a percentage of scrub, grazing, rock/ice, mixed forest and terraced land. Terraced land was not sub-divided according to management, terrace type or cropping intensity for the purpose of this study. The viability of terrace agriculture depends on water being available for irrigation, on summer air temperature and on stable and less steep slopes. These factors are all closely correlated with altitude and so there exists a strong altitudinal influence on land use. Since the range of altitudes (of the outflow point sampled) of catchments sampled in each region is different (Fig. 2) the proportion of catchments sampled under natural vegetation (forest scrub/grazing and rock/ice) and agricultural use (terrace) is different between the regions (Fig. 3). Catchments in Region D are at the lowest elevation and are exclusively under agricultural land use. The lack of agricultural catchments sampled in Region C, compared to region A, indicates that other geographical and cultural factors, as well as altitude, determine land use.
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A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
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A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
6 605 $- 50-
: : : : I : :
$
:
8070-
40-
I : I : :I:
3020lo-
O-,
Fig. 2. Cumulative sampling region.
0
I
/’ ,’ I
frequency
----
I 1200
plot of catchment
* .. .... . B _
2400 Altitude (m)
1800
altitudes,
measured
3000
c ____ D
3600
at the catchment
outflow,
in each
The climate of Nepal is monsoonal with heavy rains at lower elevations (less than ca. 3000 m) and snow at higher elevations, from June to September. During the winter months (December to February) snowfall at elevations above ca. 2500 m is common but precipitation is minimal at lower elevations. The altitudinal variation in climate is marked with generally higher precipitation and warmer temperatures at lower elevations. For example, at Namche Bazaar (3450 m, Everest area) annual precipitation is about 1200 mm and temperatures range from a minimum of -8 to 8°C to a maximum of 6 to 15°C; at Pokhara (830 m, Annapurna area) annual precipitation totals about 3500 mm with maximum temperatures between 19 and 30°C and minimum temperatures between 6 and 21°C (HMG Nepal, 1988). 3. Sampling and analytical methodology Sampling was undertaken during February and March 1992. At this time flows were low at all elevations since the high level snow fields and glaciers had not yet started to melt and significant precipitation had not fallen at lower elevations since the previous summer monsoon. Sampling at low flows during a prolonged dry season was chosen primarily to reduce the variance in stream chemistry due to high flow events; this would produce regionally comparable data sets, but ease of access during this period was an important consideration. All of the sampling locations were remote with one to five days trek from the nearest road. A total of 216 stream samples were collected; 64 from region A, 79 from region B, 52 from region C and 21 from region D. At each stream, water was collected in a 100 ml syringe and filtered immediately through a 0.45 pm cellulose-ester membrane into two 60 ml high density polyethylene (HDPE) bottles. One of these bottles was acidified immediately to 1%
66
A. Jenkins et al. / Journal of Hydrology
a
m
166 (1995) 61-79
below detection
ND represents
112.5 8.4 0.12 0.151 0.07 1.1 0.02
15.1 4.4 0.01 0.005 0.015 0.06 _ _
limit
2.6 1.6 0.003 ND ND ND 0.02 _ _
68 3.1 0.03 0.012 0.015 0.022 0.012
1.6 154 20.2 5.1 1.5 1.6 0.39 0.19 9.3 _
8.5 240 26 12.3 3.7 5.9 0.7 0.69 11.0 ND
5.8 9 0.7 0.2 0.4 ND ND ND 0.2 ~
0.48 39.2 4.98 1.884 0.728 0.962 0.151 0.146 2.219 19.16 1.62 0.015 0.019 0.011 0.141 _
7.3 36 3.5 0.9 1.7 0.7 0.24 0.1 2.2
Mean
Min.
SD
Max.
Mean 8.7 640 13.6 37.9 7.5 4.9 8.6 0.8 36.5 ND 334.4 8.6 0.129 0.08 0.18 0.29 0.025 _
5.9 20 0.9 0.3 0.2 ND ND ND 0.1 ~ 6.5 0.5 0.004 ND ND ND 0.022 _
Min.
60 1.47 0.031 0.019 0.024 0.043 ~ _
0.64 105.4 14.96 7.757 1.103 1.117 1.031 0.178 7.612 _
SD 7.3 86 7.4 1.5 2.2 1.5 0.27 0.08 7.1 _ 22.4 4.2 0.02 0.004 0.015 0.061 _
Mean
Region
8.3 260 30 9.8 7.5 6.1 2.9 0.84 41.0 ND 93.2 10 0.09 0.032 0.1 0.34 0.006 _
Max.
C
0.45 50.7 6.22 2.125 1.215 1.168 0.485 0.133 6.044 _
6.3 17 1.1 0.3 0.4 ND ND ND 0.6 ~ 3.6 0.9 0.006 ND ND ND 0.003 _ 18.35 1.9 0.017 0.007 0.022 0.067 ~
SD
conductivity
Min.
Units are mg 1-l except pH (log) and electrical
Max.
B
in the four regions. Region
of water chemistry
Region A
statistics
HC03 Si Sr Ba Fe F MN Al
PO4
so4
PH Conductivity Ca Mg Na K Cl NO3
Table 1 Descriptive
7.5 102 5.7 1.4 6.9 2.0 1.07 0.04 2.6 0.06 35.1 9.3 0.03 0.013 0.104 0.122 0.014 0.24
Mean
Region
(@ cm-‘) D
1.9 150 13.2 3.2 11.1 4.6 2.8 0.27 9.4 0.6 54.9 16.9 0.07 0.031 0.79 0.23 0.119 0.44
Max.
7.0 60 2.8 0.6 0.9 ND ND ND 0.3 23.6 0.01 0.005 ND ND ND 0.003 0.14
Min.
0.29 24.6 2.4 0.762 1.987 0.925 0.616 0.066 2.531 0.134 8.95 3.08 0.016 0.007 0.177 0.056 -
SD
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
68
using high purity, concentrated HN03. Samples were transported to the UK and analysed 4-6 weeks after collection. Electrical conductivity, temperature and pH were measured using portable meters. In the laboratory, the acidified sample was analysed for Ca, Mg, Na, K, Si, Sr, Ba, Fe, Mn, SO4 and Al using inductively coupled plasma optical emission spectrometry (ICPOES). The unacidified sample was analysed for NOs, F, Cl and PO4 using calorimetric procedures. Bicarbonate was calculated as the total anion charge deficit. Excess pC02 (the ratio of the computed pC02 for the water and the air equilibrated value of 10-3.5) was estimated based on an equilibrium value corresponding to: [H+] - [HCO;]
= 5.13
where the concentrations
are expressed
(1) in peq 1-l (Avila and Roda,
1991).
4. Results - regional water chemistry characteristics The mean water chemistry of the headwater streams sampled in all four regions is characteristically well buffered with pH in the range 7.0-8.5, high concentrations of base cations and low concentrations of strong acid anions and, therefore, high calculated HC03 concentrations (Table 1). Calcium and HC03 are the dominant cation and anion, respectively, in all samples. This is consistent with studies in other similar environments (Bhatt and Pathak, 1992). Chloride and NO3 concentrations are uniformly low across all regions. Silica, on the other hand, is consistently high across all regions, generally oversaturated with respect to quartz (Krauskopf, 1956); this indicates the importance of weathering processes in the supply of ions to the streams (Casey and Neal, 1984). Mean estimated excess pCOZ is 3.67 but with a high standard deviation of 6.22 although 95% of the values range between 0 and 11. The highest values tend to occur at lower pH although data scatter is very high (Fig. 4). On a region by region basis, differences in stream chemistry are evident (Fig. 5). In regions A and C, both the mean and variability in base cation concentrations are similar (Table 1) with mean Ca > Na > Mg = K. In region D, mean concentrations are similar to regions A and C but there is much less variation in Ca; Na has the highest mean concentration followed by Ca > Mg = K. Region B waters differ in that the mean Ca concentration is an order of magnitude higher than in regions A, C and D, although with large variability. Magnesium concentrations in region B account for a much higher proportion of the total base cations than in A, C and D where Na and Ca dominate. Mean SO4 concentration in region B is almost double that in regions A and D but with high standard deviation. Chloride concentrations are highest in region D. Of the nutrients, NO3 and PO4 concentrations are seldom detected and, where present, are consistently low (< 1 mg 1-l). Highest mean NO3 concentration was found in region B and lowest in region D, whilst PO4 was detected only in region D. These represent minimum NO3 concentrations for these waters since no preservative was employed to prevent biological utilisation of the NO3 in the sample bottle.
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
5.5
6
6.5
7
7.5 PH
8
8.5
9
69
9.5
PH Fig. 4. The relationship regions.
between
pH and calculated
HCO,
(top) and excess $02
(bottom)
across
all
Trace metal concentrations in each region are summarised in Table 1. The mean Fe concentration in region D is a factor of ten times higher than in any other area. Aluminium was detected in only five samples in total, all located in region D. Concentrations ranged from 0.14 to 0.44 mg 1-l. Manganese was detected in trace quantities in two samples from both regions A and B and in all samples from region D. In general, the concentration of ionic species decreases with altitude (Table 2) although correlation coefficients are low, indicating a high degree of scatter. Notable exceptions to this general trend are N03, SO4 and Ca which increase with altitude in
A. Jenkins et al. 1 Journal of Hydrology 166 (1995) 61-79
70
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A. Jenkins et al. 1 Journal
of Hydrology 166
(1995) 61-79
Table 2 Pearson Product Moment correlation coefficients and significance level (NS = below 90%) of ionic species against altitude for three of the four regions. Region D is not included as all of the catchments were at similar low elevations Region
Ba Ca Cl F Fe K Mg Na NO3
Si so4
Sr HC03
A
Region
B
Region
C
,
Correlation coefficient
Significance level (%)
Correlation coefficient
Significance level (%)
Correlation coefficient
Significance level (%)
-0.21 -0.27 -0.37 -0.06 -0.18 -0.39 -0.22 -0.38 -0.02 -0.35 -0.11 -0.18 -0.32
99 95 99 NS NS 99 90 99 NS 99 NS NS 95
-0.22 0.32 0.02 -0.36 0.03 -0.03 -0.24 -0.30 0.34 -0.53 0.33 0.14 0.01
95 99 NS 99 NS NS 95 99 99 99 99 NS NS
-0.54 -0.11 -0.26 -0.01 -0.02 -0.63 -0.45 -0.41 0.18 -0.55 -0.33 -0.15 -0.25
99 NS 95 NS NS 99 99 99 NS 99 99 NS 90
region B. Clearly, altitude itself has no bearing on ionic concentrations but is highly correlated with other physical characteristics such as land use, the majority of forests occurring at high altitude and terrace agriculture at low altitude, and temperature which will influence solubility coefficients of some ion species. Bedrock geology may also be related to altitude. The interaction of these factors is responsible for the scatter in the altitude-ion concentration relationships.
5. Discussion 5.1. Geological
controls on stream chemistry
Given that the mean chemistry of each region differs, principal components analysis (PCA) was carried out on a region by region basis to identify the major ion relationships. Since PCA relies upon correlation of variables, missing values or those values below the detection limit decrease the statistical significance of the results and make interpretation more difficult. For this reason, Mn, Al, and P04, which were seldom detected, were omitted from the analysis in all regions and F from the analysis in regions A, B and C. pH was omitted as the range of values is small. The first four vectors account for ca. 70&90% of the total variance in all regions (Table 3). The PCA highlights strong relationships between the dominant ions in the stream waters of each region, which are apparently consistent across all four regions. This might be expected since the study was carried out during a dry period with low atmospheric inputs and flow so that the major source of cations and Si to surface waters was from chemical weathering. In the absence of acidic deposition, chemical
1 2 3 4
Component
Fe
NO3
Ba Ca K Mg SO4 Na NO3 Si Fe Sr
44.7 17.5 17.6 7.3
29.1 17.6 11.0 10.0
Ba Ca K Mg SO4 Cl Na Si
37.8 20.5 12.8 9.5
% Total variance explained
% Total variance explained
Significant ions
% Total variance explained
Significant ions
C
B
A
Ba Ca Cl K Mg SO4 NO3 Si Na Fe
Significant ions
Significant ions
Ba Ca K Mg SO, Sr Na Si Cl NO3 Fe
% Total variance explained 45.9 23.5 10.1 8.6
D
Table 3 The results of principle components analysis on the chemistry of each region. Only the first four components are shown as these explain most of the overall variance. The most significant ions contributing to each component determined as those with coefficients greater than 0.4
Fig. 6. Base cation relationships
across all regions;
all units are mg 1-l. Samples
from each region are plotted
Na using the characteristic
letter identifier
(A-D).
2
74
A. Jenkins et al. / Journal of Hydrology I66 (1995) 61-79
weathering reactions depend primarily on the dissolution of CO2 and the formation of carbonic acid. On average, pC02 is 3.7 times atmospheric although large deviations from this level at low pH are probably due to organic anion contributions (Fig. 4). There is, however, a high variability in base cation concentrations within and between regions (Fig. 6); this is presumably derived from differences in local geology and the variable weathering of different minerals. High Ca concentrations in all four regions are generally associated with high Mg. A sub-sample of streams in region B, corresponding to an altitude range of 20003000 m, demonstrates high Ca and relatively low Mg and so deviates from the overall trend. These high Ca concentrations confirm the location of the calcareous formation associated with the Central Himalayan Thrust. Similarly, samples from streams draining the west facing slope of the Modi Khola in region B, between altitudes of 1200 and 1700 m, exhibit high concentrations of Mg relative to K and Na. Again, this can presumably be attributed to local geological features. In general, the streams in region B with high Ca concentrations also exhibit relatively low K concentrations compared to the other three regions. Sulphate concentration is apparently independent of base cations despite its inclusion in the first principal component with the base cations (Fig. 6). Undoubtedly, the high SO4 concentrations in region B indicate the widespread existence of SO4 minerals throughout the region. Gneiss contains a small percentage of S but this is unlikely to account for the high concentrations observed. In regions A and B, the impact of fertiliser application (particularly ammonium sulphate) cannot be discounted although in region D, where the catchments drain almost exclusively terraced land, SO4 concentrations are not appreciably higher than the other regions. The relationship between Si and Na is generally consistent across all regions with a strong positive correlation (Fig. 7). Region D is characterised by the highest Na and Si and the ratio of Si: Na is somewhat lower. There is no apparent relationship between Cl and any other ion either within or between regions. 5.2. The influence of agriculture Because of the impact of different local geology on the water chemistry characteristics of the four regions, it is inappropriate to compare catchments draining different land uses across the four regions. On a region by region basis, however, chemical differences due to catchment land use can be inferred. In region D, where all streams drain catchments exclusively under terrace agriculture, mean chemical characteristics differ from the other regions (Table 1). Mean Cl concentration is highest in region D. This might be attributed to the greater water use for irrigation and, therefore, potentially increased evapotranspiration losses. This would increase the concentration of solutes, such as Cl, which are regarded as conservative. It could also reflect input of Cl associated with mineral fertilisers. Mean Si and Na concentrations are also highest in region D. This might reflect a higher weathering rate, given that the agricultural land management techniques utilised in these terraced systems include extensive ploughing of flooded terraces, seasonal saturation and seasonally high temperatures. Iron concentrations are also high in region D, implying higher weathering rates although ‘red’
A. Jenkins et al. 1 Journal of Hydrology
166 (1995) 61-79
15
iron-rich soils are evident in this region. Nitrate and SO4 concentrations are low despite high doses of mineral fertilisers. In terms of NOs, this might be caused by plant uptake since crops are under cultivation and stream water is diverted across terraces for irrigation during the dry season. Phosphate, also heavily applied as mineral fertiliser, was detected only in region D, although in very low concentrations. Aluminium was detected only in region D. Mean concentrations of Sr, Ba, F and Mn are high and presumably of geological origin.
D D
1
IDA
0
4
D
8 Ca
Si
1
i Na Fig. 7. The ionic relationships between SO4 and Ca (top) and Si and Na (bottom) across all regions; all units are mg 1-l. Samples from each region are plotted using the characteristic letter identifier (A-D).
76
A. Jenkins et al. / Journal of Hydrology
166 (1995) 61-79
The main impact of terrace agriculture is apparently to increase chemical weathering rates. It is possible, on the other hand, that these observed chemical differences simply reflect a geology different from that of the other regions rather than a land use impact. If land use is a dominant influence on stream chemistry, these impacts should be detectable in the comparison of lower elevation agricultural and higher elevation forest and scrub (pristine) catchments in regions A and B (Note: no agricultural cat&n-tents were found in region C.) Pearson Product Moment correlations of ion concentrations with the percentage of catchment under terrace agriculture for regions A and B, however, are confusing with respect to the interpretation of the mean chemistry in region D. The highest correlation coefficients in region A are for Ba (0.35, sig. level = 99%), F (0.33, sig. level = 95%), K (0.33, sig. level = 99%) and Mg (0.32, sig. level = 95%). Of these four ions, mean F concentration is an order of magnitude higher in region D than in the other regions and mean K and Ba concentrations are marginally higher in region D. It is not clear, however, how agricultural or anthropogenic activity could affect the concentrations of these ions. The correlation between Mg and terrace cover is most likely related to regional geology. In region B, the highest correlation coefficients are for Ca (-0.47, sig. level = 99.9%), Si (0.44, sig. level = 99.9%) SO4 (-0.27, sig. level = 95%) and pH (-0.45, sig. level = 99.9%). Of these, only Si supports the hypothesis from region D that agricultural activity promotes higher weathering rates. It is likely that the impact of bedrock geology overwhelms the land use response in region B and the correlations merely support local differences in geology which are related to altitude (Table 2). Comparison of chemistry data from dominantly (greater than 66% cover) agricultural and forested catchments within regions A and B provides further evidence of agricultural impacts (Table 4). In region A, the mean concentrations of Ca, Cl, Ba, F, Fe, K, Mg, NO3 and SO4 are higher in streams with catchments dominated by agriculture although of these, only Cl, F and Ba are statistically significantly differences (Table 4). This pattern is entirely consistent with the expected impacts of agricultural land use, that is, increased concentrations of K, NO3 and SO4 from addition of mineral fertilisers, increased concentrations of Ca, Mg, Fe, G and Ba due to enhanced chemical weathering and increased Cl concentrations from fertiliser input or enhanced water use. The observations are also broadly consistent with the mean chemical characteristics of region D. In region B, agricultural catchments have higher mean concentrations of Cl, F, Fe, Na, and NO3 than forested catchments but none of these were statistically significant. It is clear from this analysis that agriculture causes a change in the chemistry of streams in these mountain environments. The quantification and process mechanism causing the change is difficult to ascertain since the classification of land use as a continuous variable (percentage of catchment) or simply as a qualitative variable (dominant cover or use) is apparently inappropriate. It is likely that the distribution of land uses within the catchment will be as important as the total cover since, for example, terraced land is most likely to be situated in riparian areas, due to irrigation requirements. In this case, even in the catchments with low total area of terrace, the stream chemistry might be greatly influenced by the agricultural practices carried out on the terraced land.
77
A. Jenkins et al. / Journal of Hydrology I66 (1995) 61-79
Table 4 Mean chemistry for agricultural and forested catchments in regions A and B. Statistical significance of the difference between the means is tested by ANOVA. Calculated F-statistic and significance level (NS, below 90%; ***, greater than 99%; **, greater than 95%; *, greater than 90%) are given Element
Region
A
Terrace Ca Na Mg K Cl NO3 so4
F Ba Si Sr Fe HC03 PH
Cond Alt
5.39 1.54 2.26 1.44 0.29 0.11 3.04 0.11 0.02 3.94 0.01 0.004 24.4 7.5
59 2027
Region Forest 3.59 1.67 0.81 0.72 0.19 0.08 2.43 0.04 0.003 4.23 0.01 0.001 14.03 7.3
32 2492
F
Significance
0.53 0.18 2.68 2.42 3.18 0.45 0.31 12.19 3.42 0.2 0.05 0.38 1.39 0.91
NS NS NS NS * NS NS ** * NS NS NS NS NS
2.08 9.21
NS ***
B
Terrace 6.27 1.78 2.09 1.15 1.63 0.23 4.23 0.04 0.005 3.93 0.01 0.067 25.38 7.0
70 1709
Forest 26.16 1.25 6.66 1.63 0.29 0.18 9.15 0.01 0.02 2.93 0.16 0.004 88.76 7.8
187 1898
F
Significance
26.93 7.12 3.4 1.9 1.58 0.63 1.23 9.14 5.07 8.58 1.05 1.45 13.49 15.74
*** ** * NS NS NS ** *** ** *** NS NS *** ***
15.09 2.19
*** *
6. Conclusions Stream chemistry in mid-high altitude Himalayan mountain streams is well buffered with pH in the range 7.0-8.5. Bicarbonate is the dominant anion and Ca and Mg are the dominant cations. Bedrock geology is the main influence on water chemistry both between and within regions. There is generally a decrease in concentration of all ions with altitude. This reflects changing land use (forest at high altitude and terrace at low altitude), temperature influences on solubility, existence of human habitation, and soil thickness. Land use impacts are masked by geological differences and land use information may be at an inappropriate scale for detailed statistical analysis. Nevertheless, concentrations of F, Fe, Cl, S04, Si, NOs, P04, K and Na are apparently increased by agricultural activity. This is a result of increased weathering and breakdown of the soil structure, addition of mineral fertilisers and extensive irrigation. Trace metal concentrations (Al, Sr, Ba, Mn) are also high in agricultural catchments. More detailed studies directed specifically at pristine and agricultural catchments of similar geology are required to confirm these preliminary observations and interpretations. The high altitude forest and alpine scrub covered catchments in these areas are unlikely to be sensitive to atmospheric deposition of acidic pollutants. In general the waters from these catchments have high concentrations of SO4 derived from weathering sources. High pH indicates that a large buffering capacity exists within the system and that further additions of anthropogenic SO, would be readily buffered. These systems already, however, leak a small amount of NO3 and this
78
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
might increase in response to increased NO, deposition. Whilst this is unlikely to cause increased acidification of these upland streams and the biological implications of increased NO3 concentrations are not known, downstream eutrophication problems may occur. Close links have been reported between stream invertebrate community structure and stream chemistry (Rundle et al., 1993) in these environments and land use change could have biological consequences through changes in water chemistry. Future surveys of water chemistry and biology are needed in similar Himalayan environments to provide the necessary baseline data against which to assess damage caused by anthropogenic influences; in particular, the impact of land use and land cover on stream chemistry should be quantified so that the sensitivity of these systems to anthropogenic pollution can be assessed. This is particularly important given the desire to maintain ecosystem stability and bio-diversity in the face of continued development of these areas in response to increasing population pressure in the middle hills and increasing tourist pressure in the high hills.
Acknowledgements The success of this survey is due to the hard work and effort of the sampling teams who covered large distances on foot over difficult terrain and in a short time. Thanks are due to Jo and Mollie Porter, Roger Wyatt, Dick Johnson and John Law. Logistical help and support was provided by R. Maskey (Central Division of Soil Science, HMG Nepal) and P. B. Shah (ICIMOD). A skilled and dedicated team carried out the chemical analyses and thanks are due to Margaret Neal, Hazel Jeffries and Martin Harrow. The research described here was funded in part by the Environmental Monitoring and Assessment Program (EMAP) of the United States Environmental Protection Agency (USEPA). It has not been subjected to peer and/or policy review by the USEPA and, therefore, does not necessarily reflect the views of the USEPA. No official endorsement by the USEPA should be inferred.
References Avila, A. and Roda, F., 1991. Red rains as major contributors of nutrients and alkalinity to terrestrial ecosystems at Montseny (NE Spain). Orsis, 6: 21 S-229. Bruns, D.A., Wiersma, G.B. and Rykiel, E.J., 1991. Ecosystem monitoring at global baseline sites. Environ, Monit. Assess., 17: 3-31. Bhatt, S.D. and Pathak, J.K., 1992. Himalayan Environment: Water Quality of the Drainage Basins. Shree Almora Book Depot, Almora, India. Casey, H. and Neal, C., 1984. Abiological controls on silica in chalk streams and groundwaters. In: P.G. Sly (Editor), Sediments and Water Interactions. Proc. 3rd Int. Symp. Interaction between Sediments and Water, Geneva, pp. 329-340. Ferro, W., 1982. Limnology of the Pokhara Valley lakes and its implications for fishery and fish culture. J. Nepal Res. Centre, 5/6: 27-52. Galloway, J.N., 1989. Atmospheric acidification: Projections for the future. Ambio, 18: 161-166.
A. Jenkins et al. 1 Journal of Hydrology 166 (1995) 61-79
19
His Majesty’s Government (HMG) of Nepal, 1984. Land Use Classification Map. Topographical Survey Branch, Kathmandu. His Majesty’s Government (HMG) of Nepal, 1988. Climatological Records of Nepal 1985-1986. Ministry of Water Resources, Kathmandu, Nepal. International Union for the Conservation of Nature (IUCN), 1988. The National Conservation Strategy for Nepal, Malla Press, Kathmandu, Nepal. Jones, J.R., Knowlton, M.F. and Swar, D.B. 1989. Limnological reconnaissance of waterbodies in central and southern Nepal. Hydrobiol., 184: 171-189. Kaul, V., 1977. Limnological survey of Kashmire lakes with reference to trophic status and conservation. Int. J. Ecol. Environ. Sci., 3: 19-44. Krauskopf, K.B., 1956. Dissolution and precipitation of silica at low temperatures. Geochim. Cosmochim. Acta, 10: l-26. Lohmann, K., Jones, J.R., Knowlton, M.F., Swar, D.B., Pamperi, M.A. and Brazos, B.J., 1988. Pre- and post-monsoon limnological characteristics of lakes in the Pokhara and Kathmandu Valleys, Nepal. Verh. Int. Ver. Limnol., 23: 558-565. Mayewski, P.A., Lyons, W.B., Spencer, M.J. and Spencer, J.L., 1986. Snow chemistry from Xixabangama Peak, Tibet. J. Glacial., 30: 112-142. Naidu, P.T., Narasimha Rao, K.L. and Prasad, K.S.S., 1989. Hydrochemistry of Polar river basin, Chittor district, Andhra Pradesh, Asian Environ., 11: 3-l 1. Nijampurkar, V.N., Sarin, M.M. and Rao, D.K., 1993. Chemical composition of snow and ice from Chhota Shigri glacier, Central Himalaya. J. Hydrol., 151: 19-34. Paul, D.K. and Verma, P.K., 1990. Hydrological status of a hill stream of Santhal Pargana (Bihar). J. Freshwater Biol., 2: 37-43. Rundle, SD., Jenkins, A. and Ormerod, S.J., 1993. Macroinvertebrate communities in streams in the Himalaya, Nepal. Freshwater Biol., 30: 169-180. Tiwari, T.N. and Ali, M., 1987. River pollution in Kathmandu Valley - variations of water quality index. Int. J. Environ. Pollut., 7: 3477351. United Nations, 1986. Groundwater in Continental Asia. Natural Resources/Water Series No. 15. United Nations, New York. Upadhyaya, N.P. and Roy, N.N., 1982. Studies in river pollution in Kathmandu Valley, Indian. J. Environ. Health, 24: 124-135.
Journal
of Hydrology
166 (1995) 61-79
[31
Stream chemistry in the middle hills and high mountains of the Himalayas, Nepal Alan Jenkinsa,*, bDepartment
William T. Sloana, B. Jack Cosbyb
aInstitute of Hydrology, Wallingford, OX10 8BB. UK of Environmental Science, University of Virginia, Charlottesville. Received
29 April 1994; revision
accepted
16 August
VA 22903, USA
1994
Abstract The major ion chemistry of samples from 216 headwater streams in the Everest, Annapurna, Langtang and Nuwakot regions of the middle and high mountains of the Nepal Himalayas is described. Samples were collected at low flow during February-March 1992, the dry season
between the winter and summer monsoon periods. The resulting database provides a baseline against which to assess natural and anthropogenic influences on water chemistry in these environments. Differences in bedrock geology generally determine differences in chemical characteristics between the four regions. Ion concentrations tend to decrease with altitude, reflecting differences in land use, land management, natural vegetation and atmospheric deposition, all of which are correlated with altitude. The well buffered nature of the pristine, high altitude streams indicates that increased atmospheric deposition of S and N compounds is unlikely to cause acidification of streamwater, although these systems currently leak low concentrations of Nos. Terraced agriculture contributes significantly to differences in chemistry both between and within regions. Water draining agricultural catchments has higher concentrations of nutrients (NOs, PO,) and acid anions (Cl, SO& probably as a result of mineral fertiliser inputs and of trace metals (Fe, Al, Ba, St-, Mn) Si and F, potentially due to increased weathering.
1. Introduction
This study presents the first wide-scale survey of the chemistry of medium to high altitude first order streams in the Himalaya of Nepal. It was carried out in conjunction with a survey of stream macro-invertebrates (Rundle et al., 1993). The objective was to characterise the water chemistry of these geologically young environments and to determine the nature and degree of anthropogenic impacts on stream chemistry. * Corresponding
author.
0022-1694/95/$09.50 0 1995 - Elsevier Science B.V. All rights reserved SSDI 0022-l 694(94)02600-9
62
A. Jenkins et al. / Journal of Hydrology
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The impact on water chemistry of anthropogenic pollution from industrial and agricultural sources has concerned environmentalists and scientists for the past two decades. In consequence, the chemistry of headwater streams, lakes and lowland rivers has been monitored widely in Europe and North America in an effort to define and quantify these anthropogenic impacts. An understanding of how anthropogenic pollutants affect water chemistry, and thereby the ability to predict the location and severity of potential impacts, can be achieved only through knowledge of hydrochemical processes in pristine waters of similar physico-chemical characteristics (Brims et al., 1991). If a sufficiently detailed knowledge of pristine, or baseline, water chemistry is available, the effects of local pollution, stemming from land use and land management, and of regional pollution, from atmospheric deposition of acidic oxides for example, can be quantified. Attention to the chemical quality of lakes and impoundments in the Himalayas has focused on the problem of eutrophication and salinity, in Nepal (Ferro, 1982; Lohmann et al., 1988; Jones et al., 1989) and in Kashmir (Kaul, 1977). The chemistry of running waters draining the high mountain areas of Asia, however, is largely unknown. Studies of water quality in these areas have been based on infrequent sampling of a few rivers draining large catchments (>lO km2). Major lowland rivers have been studied in, for example, the Kathmandu Valley, Nepal (Upadhyaya and Roy, 1982; Tiwari and Ali, 1987), the Kumaun Region, Uttar Pradesh, India (Paul and Verma, 1990; Bhatt and Pathak, 1992) and the Andhra Pradesh region, India (Naidu et al., 1989). The conclusions from these studies are that the degree of pollution of these rivers increases with distance from the high mountain first order streams and that pollution is increasing through time. This is intuitively expected since human populations within catchments increase with downstream distance as, indeed, do agricultural activity and effluent inputs. The fast growing population in many of the developing Asian countries is predicted further to intensify agricultural production requirements and so the use of mineral and organic fertilisers to increase crop yield and the conversion of upland grazing, alpine scrub and forest to terraced agricultural land is likely to increase in the near future. Furthermore, as tourism is established as a major industry in mountain and remote areas, human habitation and road transport will reach further into what were previously ‘natural’ environments. Recent awareness of this situation has led to calls for sustainable development of natural resources such that ecosystem stability is maintained (IUCN, 1988). Furthermore, many studies of snow chemistry from high altitude Himalayan glaciers have reported concentrations of NO3 and SO4 of magnitudes comparable to those experienced in areas of north-west Europe where surface waters are currently acidified (Mayewski et al., 1986; Nijampurkar et al., 1993). The deposition of acidic oxides is likely to increase in the future in line with expected increases in emissions in the developing areas of Asia (Galloway, 1989).
2. Survey area The streams sampled are located in four regions of the middle and high Himalayas of Nepal: the Shorong and Hinku Kholas, Everest area (Region A), the Modi Khola, Annapurna area (Region B), the Helambu and Langtang Kholas, Langtang area
A. Jenkins et al. / Journal
of Hydrology166
(1995) 61-79
63
(Region C) and the Likhu Khola, Nuwakot District (Region D) (Fig. 1). All of the streams are first or second order tributaries of five of the major rivers of Nepal which themselves drain into the Ganges. The detailed geology of the middle hills and high mountains is poorly documented (Fig. 1) and the dominant bedrock geology is reported to consist of Pre-Cambrian gneiss (United Nations, 1986). Large areas of low-grade metamorphic green schist were noted in the field in all sampling regions. The Central Himalayan Thrust fault is associated with a calcareous formation and dolomite was noted in the. field in the Annapurna area. Natural vegetation in all of the four regions is strongly zoned by altitude and so reflects a north (high mountains) to south (middle hills) gradient. In the subtropical climatic zone, from approximately 1000-1700 m, Chir pine forests predominate. The temperate zone, between 1700 and 3000 m approximately, is dominated by mixed forests of oak (Quercus), rhododendron and fir (Abies spectabilis and A. pindrow), although blue pine (Pirzus wallichiana), Himalayan hemlock (Tsuga dumosa), spruce (Picea smithiana) and bamboo (Bambusa sp. and Arundinaria sp.) are also present. In the subalpine zone, approximately 3000-3800 m, Himilayan silver fir (Abies spectabilis) and birch (Betula utilis) dominate but are replaced by juniper (Juniperus sp.) and bamboo at higher elevations. In the alpine zone, above the tree line and below the limit of permanent snow cover, juniper and rhododendron shrubs grow and grassland is common. Glaciers and permanent snow fields are widespread above the alpine zone and feed some of the high elevation streams directly. Agriculture in Nepal consists almost exclusively of terraced cultivation. Two types of terrace predominate; rice is grown on level terraces (khet land) and mainly maize, millet and mustard on sloping terraces (bari land). At lower elevations and near to stream channels, level terraces are irrigated by diverting streamflow whilst at high elevations and on catchment divides, rainwater is held back by terrace risers to ensure the necessary flooding of the rice padi. Sloping terraces are exclusively rain-fed. Extensive applications of pesticides, as well as of fertilisers, in the form of farmyard manure and inorganic nitrogen and phosphorous compounds, are common on khet land with less frequent or intensive application to bari land. The land-use of the catchments was classified from 1 : 50000 scale land-use maps (HMG Nepal, 1984) as a percentage of scrub, grazing, rock/ice, mixed forest and terraced land. Terraced land was not sub-divided according to management, terrace type or cropping intensity for the purpose of this study. The viability of terrace agriculture depends on water being available for irrigation, on summer air temperature and on stable and less steep slopes. These factors are all closely correlated with altitude and so there exists a strong altitudinal influence on land use. Since the range of altitudes (of the outflow point sampled) of catchments sampled in each region is different (Fig. 2) the proportion of catchments sampled under natural vegetation (forest scrub/grazing and rock/ice) and agricultural use (terrace) is different between the regions (Fig. 3). Catchments in Region D are at the lowest elevation and are exclusively under agricultural land use. The lack of agricultural catchments sampled in Region C, compared to region A, indicates that other geographical and cultural factors, as well as altitude, determine land use.
64
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
65
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
6 605 $- 50-
: : : : I : :
$
:
8070-
40-
I : I : :I:
3020lo-
O-,
Fig. 2. Cumulative sampling region.
0
I
/’ ,’ I
frequency
----
I 1200
plot of catchment
* .. .... . B _
2400 Altitude (m)
1800
altitudes,
measured
3000
c ____ D
3600
at the catchment
outflow,
in each
The climate of Nepal is monsoonal with heavy rains at lower elevations (less than ca. 3000 m) and snow at higher elevations, from June to September. During the winter months (December to February) snowfall at elevations above ca. 2500 m is common but precipitation is minimal at lower elevations. The altitudinal variation in climate is marked with generally higher precipitation and warmer temperatures at lower elevations. For example, at Namche Bazaar (3450 m, Everest area) annual precipitation is about 1200 mm and temperatures range from a minimum of -8 to 8°C to a maximum of 6 to 15°C; at Pokhara (830 m, Annapurna area) annual precipitation totals about 3500 mm with maximum temperatures between 19 and 30°C and minimum temperatures between 6 and 21°C (HMG Nepal, 1988). 3. Sampling and analytical methodology Sampling was undertaken during February and March 1992. At this time flows were low at all elevations since the high level snow fields and glaciers had not yet started to melt and significant precipitation had not fallen at lower elevations since the previous summer monsoon. Sampling at low flows during a prolonged dry season was chosen primarily to reduce the variance in stream chemistry due to high flow events; this would produce regionally comparable data sets, but ease of access during this period was an important consideration. All of the sampling locations were remote with one to five days trek from the nearest road. A total of 216 stream samples were collected; 64 from region A, 79 from region B, 52 from region C and 21 from region D. At each stream, water was collected in a 100 ml syringe and filtered immediately through a 0.45 pm cellulose-ester membrane into two 60 ml high density polyethylene (HDPE) bottles. One of these bottles was acidified immediately to 1%
66
A. Jenkins et al. / Journal of Hydrology
a
m
166 (1995) 61-79
below detection
ND represents
112.5 8.4 0.12 0.151 0.07 1.1 0.02
15.1 4.4 0.01 0.005 0.015 0.06 _ _
limit
2.6 1.6 0.003 ND ND ND 0.02 _ _
68 3.1 0.03 0.012 0.015 0.022 0.012
1.6 154 20.2 5.1 1.5 1.6 0.39 0.19 9.3 _
8.5 240 26 12.3 3.7 5.9 0.7 0.69 11.0 ND
5.8 9 0.7 0.2 0.4 ND ND ND 0.2 ~
0.48 39.2 4.98 1.884 0.728 0.962 0.151 0.146 2.219 19.16 1.62 0.015 0.019 0.011 0.141 _
7.3 36 3.5 0.9 1.7 0.7 0.24 0.1 2.2
Mean
Min.
SD
Max.
Mean 8.7 640 13.6 37.9 7.5 4.9 8.6 0.8 36.5 ND 334.4 8.6 0.129 0.08 0.18 0.29 0.025 _
5.9 20 0.9 0.3 0.2 ND ND ND 0.1 ~ 6.5 0.5 0.004 ND ND ND 0.022 _
Min.
60 1.47 0.031 0.019 0.024 0.043 ~ _
0.64 105.4 14.96 7.757 1.103 1.117 1.031 0.178 7.612 _
SD 7.3 86 7.4 1.5 2.2 1.5 0.27 0.08 7.1 _ 22.4 4.2 0.02 0.004 0.015 0.061 _
Mean
Region
8.3 260 30 9.8 7.5 6.1 2.9 0.84 41.0 ND 93.2 10 0.09 0.032 0.1 0.34 0.006 _
Max.
C
0.45 50.7 6.22 2.125 1.215 1.168 0.485 0.133 6.044 _
6.3 17 1.1 0.3 0.4 ND ND ND 0.6 ~ 3.6 0.9 0.006 ND ND ND 0.003 _ 18.35 1.9 0.017 0.007 0.022 0.067 ~
SD
conductivity
Min.
Units are mg 1-l except pH (log) and electrical
Max.
B
in the four regions. Region
of water chemistry
Region A
statistics
HC03 Si Sr Ba Fe F MN Al
PO4
so4
PH Conductivity Ca Mg Na K Cl NO3
Table 1 Descriptive
7.5 102 5.7 1.4 6.9 2.0 1.07 0.04 2.6 0.06 35.1 9.3 0.03 0.013 0.104 0.122 0.014 0.24
Mean
Region
(@ cm-‘) D
1.9 150 13.2 3.2 11.1 4.6 2.8 0.27 9.4 0.6 54.9 16.9 0.07 0.031 0.79 0.23 0.119 0.44
Max.
7.0 60 2.8 0.6 0.9 ND ND ND 0.3 23.6 0.01 0.005 ND ND ND 0.003 0.14
Min.
0.29 24.6 2.4 0.762 1.987 0.925 0.616 0.066 2.531 0.134 8.95 3.08 0.016 0.007 0.177 0.056 -
SD
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
68
using high purity, concentrated HN03. Samples were transported to the UK and analysed 4-6 weeks after collection. Electrical conductivity, temperature and pH were measured using portable meters. In the laboratory, the acidified sample was analysed for Ca, Mg, Na, K, Si, Sr, Ba, Fe, Mn, SO4 and Al using inductively coupled plasma optical emission spectrometry (ICPOES). The unacidified sample was analysed for NOs, F, Cl and PO4 using calorimetric procedures. Bicarbonate was calculated as the total anion charge deficit. Excess pC02 (the ratio of the computed pC02 for the water and the air equilibrated value of 10-3.5) was estimated based on an equilibrium value corresponding to: [H+] - [HCO;]
= 5.13
where the concentrations
are expressed
(1) in peq 1-l (Avila and Roda,
1991).
4. Results - regional water chemistry characteristics The mean water chemistry of the headwater streams sampled in all four regions is characteristically well buffered with pH in the range 7.0-8.5, high concentrations of base cations and low concentrations of strong acid anions and, therefore, high calculated HC03 concentrations (Table 1). Calcium and HC03 are the dominant cation and anion, respectively, in all samples. This is consistent with studies in other similar environments (Bhatt and Pathak, 1992). Chloride and NO3 concentrations are uniformly low across all regions. Silica, on the other hand, is consistently high across all regions, generally oversaturated with respect to quartz (Krauskopf, 1956); this indicates the importance of weathering processes in the supply of ions to the streams (Casey and Neal, 1984). Mean estimated excess pCOZ is 3.67 but with a high standard deviation of 6.22 although 95% of the values range between 0 and 11. The highest values tend to occur at lower pH although data scatter is very high (Fig. 4). On a region by region basis, differences in stream chemistry are evident (Fig. 5). In regions A and C, both the mean and variability in base cation concentrations are similar (Table 1) with mean Ca > Na > Mg = K. In region D, mean concentrations are similar to regions A and C but there is much less variation in Ca; Na has the highest mean concentration followed by Ca > Mg = K. Region B waters differ in that the mean Ca concentration is an order of magnitude higher than in regions A, C and D, although with large variability. Magnesium concentrations in region B account for a much higher proportion of the total base cations than in A, C and D where Na and Ca dominate. Mean SO4 concentration in region B is almost double that in regions A and D but with high standard deviation. Chloride concentrations are highest in region D. Of the nutrients, NO3 and PO4 concentrations are seldom detected and, where present, are consistently low (< 1 mg 1-l). Highest mean NO3 concentration was found in region B and lowest in region D, whilst PO4 was detected only in region D. These represent minimum NO3 concentrations for these waters since no preservative was employed to prevent biological utilisation of the NO3 in the sample bottle.
A. Jenkins et al. / Journal of Hydrology 166 (1995) 61-79
5.5
6
6.5
7
7.5 PH
8
8.5
9
69
9.5
PH Fig. 4. The relationship regions.
between
pH and calculated
HCO,
(top) and excess $02
(bottom)
across
all
Trace metal concentrations in each region are summarised in Table 1. The mean Fe concentration in region D is a factor of ten times higher than in any other area. Aluminium was detected in only five samples in total, all located in region D. Concentrations ranged from 0.14 to 0.44 mg 1-l. Manganese was detected in trace quantities in two samples from both regions A and B and in all samples from region D. In general, the concentration of ionic species decreases with altitude (Table 2) although correlation coefficients are low, indicating a high degree of scatter. Notable exceptions to this general trend are N03, SO4 and Ca which increase with altitude in
A. Jenkins et al. 1 Journal of Hydrology 166 (1995) 61-79
70
.....................................
.....................................
..............................
..............................
.. . . . . . . . . . . . . .
.. . . . . . ..___.........__................
.. . . . . . . . . . . . . . . . . .._._......____.......
8 t
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.
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.
.
.
.
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g
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0 ‘___________________.....----.........---~~
u)’ ii
E E 2 8 8 .___........________........... .______._____.......--------.........-..~
A. Jenkins et al. 1 Journal
of Hydrology 166
(1995) 61-79
Table 2 Pearson Product Moment correlation coefficients and significance level (NS = below 90%) of ionic species against altitude for three of the four regions. Region D is not included as all of the catchments were at similar low elevations Region
Ba Ca Cl F Fe K Mg Na NO3
Si so4
Sr HC03
A
Region
B
Region
C
,
Correlation coefficient
Significance level (%)
Correlation coefficient
Significance level (%)
Correlation coefficient
Significance level (%)
-0.21 -0.27 -0.37 -0.06 -0.18 -0.39 -0.22 -0.38 -0.02 -0.35 -0.11 -0.18 -0.32
99 95 99 NS NS 99 90 99 NS 99 NS NS 95
-0.22 0.32 0.02 -0.36 0.03 -0.03 -0.24 -0.30 0.34 -0.53 0.33 0.14 0.01
95 99 NS 99 NS NS 95 99 99 99 99 NS NS
-0.54 -0.11 -0.26 -0.01 -0.02 -0.63 -0.45 -0.41 0.18 -0.55 -0.33 -0.15 -0.25
99 NS 95 NS NS 99 99 99 NS 99 99 NS 90
region B. Clearly, altitude itself has no bearing on ionic concentrations but is highly correlated with other physical characteristics such as land use, the majority of forests occurring at high altitude and terrace agriculture at low altitude, and temperature which will influence solubility coefficients of some ion species. Bedrock geology may also be related to altitude. The interaction of these factors is responsible for the scatter in the altitude-ion concentration relationships.
5. Discussion 5.1. Geological
controls on stream chemistry
Given that the mean chemistry of each region differs, principal components analysis (PCA) was carried out on a region by region basis to identify the major ion relationships. Since PCA relies upon correlation of variables, missing values or those values below the detection limit decrease the statistical significance of the results and make interpretation more difficult. For this reason, Mn, Al, and P04, which were seldom detected, were omitted from the analysis in all regions and F from the analysis in regions A, B and C. pH was omitted as the range of values is small. The first four vectors account for ca. 70&90% of the total variance in all regions (Table 3). The PCA highlights strong relationships between the dominant ions in the stream waters of each region, which are apparently consistent across all four regions. This might be expected since the study was carried out during a dry period with low atmospheric inputs and flow so that the major source of cations and Si to surface waters was from chemical weathering. In the absence of acidic deposition, chemical
1 2 3 4
Component
Fe
NO3
Ba Ca K Mg SO4 Na NO3 Si Fe Sr
44.7 17.5 17.6 7.3
29.1 17.6 11.0 10.0
Ba Ca K Mg SO4 Cl Na Si
37.8 20.5 12.8 9.5
% Total variance explained
% Total variance explained
Significant ions
% Total variance explained
Significant ions
C
B
A
Ba Ca Cl K Mg SO4 NO3 Si Na Fe
Significant ions
Significant ions
Ba Ca K Mg SO, Sr Na Si Cl NO3 Fe
% Total variance explained 45.9 23.5 10.1 8.6
D
Table 3 The results of principle components analysis on the chemistry of each region. Only the first four components are shown as these explain most of the overall variance. The most significant ions contributing to each component determined as those with coefficients greater than 0.4
Fig. 6. Base cation relationships
across all regions;
all units are mg 1-l. Samples
from each region are plotted
Na using the characteristic
letter identifier
(A-D).
2
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weathering reactions depend primarily on the dissolution of CO2 and the formation of carbonic acid. On average, pC02 is 3.7 times atmospheric although large deviations from this level at low pH are probably due to organic anion contributions (Fig. 4). There is, however, a high variability in base cation concentrations within and between regions (Fig. 6); this is presumably derived from differences in local geology and the variable weathering of different minerals. High Ca concentrations in all four regions are generally associated with high Mg. A sub-sample of streams in region B, corresponding to an altitude range of 20003000 m, demonstrates high Ca and relatively low Mg and so deviates from the overall trend. These high Ca concentrations confirm the location of the calcareous formation associated with the Central Himalayan Thrust. Similarly, samples from streams draining the west facing slope of the Modi Khola in region B, between altitudes of 1200 and 1700 m, exhibit high concentrations of Mg relative to K and Na. Again, this can presumably be attributed to local geological features. In general, the streams in region B with high Ca concentrations also exhibit relatively low K concentrations compared to the other three regions. Sulphate concentration is apparently independent of base cations despite its inclusion in the first principal component with the base cations (Fig. 6). Undoubtedly, the high SO4 concentrations in region B indicate the widespread existence of SO4 minerals throughout the region. Gneiss contains a small percentage of S but this is unlikely to account for the high concentrations observed. In regions A and B, the impact of fertiliser application (particularly ammonium sulphate) cannot be discounted although in region D, where the catchments drain almost exclusively terraced land, SO4 concentrations are not appreciably higher than the other regions. The relationship between Si and Na is generally consistent across all regions with a strong positive correlation (Fig. 7). Region D is characterised by the highest Na and Si and the ratio of Si: Na is somewhat lower. There is no apparent relationship between Cl and any other ion either within or between regions. 5.2. The influence of agriculture Because of the impact of different local geology on the water chemistry characteristics of the four regions, it is inappropriate to compare catchments draining different land uses across the four regions. On a region by region basis, however, chemical differences due to catchment land use can be inferred. In region D, where all streams drain catchments exclusively under terrace agriculture, mean chemical characteristics differ from the other regions (Table 1). Mean Cl concentration is highest in region D. This might be attributed to the greater water use for irrigation and, therefore, potentially increased evapotranspiration losses. This would increase the concentration of solutes, such as Cl, which are regarded as conservative. It could also reflect input of Cl associated with mineral fertilisers. Mean Si and Na concentrations are also highest in region D. This might reflect a higher weathering rate, given that the agricultural land management techniques utilised in these terraced systems include extensive ploughing of flooded terraces, seasonal saturation and seasonally high temperatures. Iron concentrations are also high in region D, implying higher weathering rates although ‘red’
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15
iron-rich soils are evident in this region. Nitrate and SO4 concentrations are low despite high doses of mineral fertilisers. In terms of NOs, this might be caused by plant uptake since crops are under cultivation and stream water is diverted across terraces for irrigation during the dry season. Phosphate, also heavily applied as mineral fertiliser, was detected only in region D, although in very low concentrations. Aluminium was detected only in region D. Mean concentrations of Sr, Ba, F and Mn are high and presumably of geological origin.
D D
1
IDA
0
4
D
8 Ca
Si
1
i Na Fig. 7. The ionic relationships between SO4 and Ca (top) and Si and Na (bottom) across all regions; all units are mg 1-l. Samples from each region are plotted using the characteristic letter identifier (A-D).
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The main impact of terrace agriculture is apparently to increase chemical weathering rates. It is possible, on the other hand, that these observed chemical differences simply reflect a geology different from that of the other regions rather than a land use impact. If land use is a dominant influence on stream chemistry, these impacts should be detectable in the comparison of lower elevation agricultural and higher elevation forest and scrub (pristine) catchments in regions A and B (Note: no agricultural cat&n-tents were found in region C.) Pearson Product Moment correlations of ion concentrations with the percentage of catchment under terrace agriculture for regions A and B, however, are confusing with respect to the interpretation of the mean chemistry in region D. The highest correlation coefficients in region A are for Ba (0.35, sig. level = 99%), F (0.33, sig. level = 95%), K (0.33, sig. level = 99%) and Mg (0.32, sig. level = 95%). Of these four ions, mean F concentration is an order of magnitude higher in region D than in the other regions and mean K and Ba concentrations are marginally higher in region D. It is not clear, however, how agricultural or anthropogenic activity could affect the concentrations of these ions. The correlation between Mg and terrace cover is most likely related to regional geology. In region B, the highest correlation coefficients are for Ca (-0.47, sig. level = 99.9%), Si (0.44, sig. level = 99.9%) SO4 (-0.27, sig. level = 95%) and pH (-0.45, sig. level = 99.9%). Of these, only Si supports the hypothesis from region D that agricultural activity promotes higher weathering rates. It is likely that the impact of bedrock geology overwhelms the land use response in region B and the correlations merely support local differences in geology which are related to altitude (Table 2). Comparison of chemistry data from dominantly (greater than 66% cover) agricultural and forested catchments within regions A and B provides further evidence of agricultural impacts (Table 4). In region A, the mean concentrations of Ca, Cl, Ba, F, Fe, K, Mg, NO3 and SO4 are higher in streams with catchments dominated by agriculture although of these, only Cl, F and Ba are statistically significantly differences (Table 4). This pattern is entirely consistent with the expected impacts of agricultural land use, that is, increased concentrations of K, NO3 and SO4 from addition of mineral fertilisers, increased concentrations of Ca, Mg, Fe, G and Ba due to enhanced chemical weathering and increased Cl concentrations from fertiliser input or enhanced water use. The observations are also broadly consistent with the mean chemical characteristics of region D. In region B, agricultural catchments have higher mean concentrations of Cl, F, Fe, Na, and NO3 than forested catchments but none of these were statistically significant. It is clear from this analysis that agriculture causes a change in the chemistry of streams in these mountain environments. The quantification and process mechanism causing the change is difficult to ascertain since the classification of land use as a continuous variable (percentage of catchment) or simply as a qualitative variable (dominant cover or use) is apparently inappropriate. It is likely that the distribution of land uses within the catchment will be as important as the total cover since, for example, terraced land is most likely to be situated in riparian areas, due to irrigation requirements. In this case, even in the catchments with low total area of terrace, the stream chemistry might be greatly influenced by the agricultural practices carried out on the terraced land.
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Table 4 Mean chemistry for agricultural and forested catchments in regions A and B. Statistical significance of the difference between the means is tested by ANOVA. Calculated F-statistic and significance level (NS, below 90%; ***, greater than 99%; **, greater than 95%; *, greater than 90%) are given Element
Region
A
Terrace Ca Na Mg K Cl NO3 so4
F Ba Si Sr Fe HC03 PH
Cond Alt
5.39 1.54 2.26 1.44 0.29 0.11 3.04 0.11 0.02 3.94 0.01 0.004 24.4 7.5
59 2027
Region Forest 3.59 1.67 0.81 0.72 0.19 0.08 2.43 0.04 0.003 4.23 0.01 0.001 14.03 7.3
32 2492
F
Significance
0.53 0.18 2.68 2.42 3.18 0.45 0.31 12.19 3.42 0.2 0.05 0.38 1.39 0.91
NS NS NS NS * NS NS ** * NS NS NS NS NS
2.08 9.21
NS ***
B
Terrace 6.27 1.78 2.09 1.15 1.63 0.23 4.23 0.04 0.005 3.93 0.01 0.067 25.38 7.0
70 1709
Forest 26.16 1.25 6.66 1.63 0.29 0.18 9.15 0.01 0.02 2.93 0.16 0.004 88.76 7.8
187 1898
F
Significance
26.93 7.12 3.4 1.9 1.58 0.63 1.23 9.14 5.07 8.58 1.05 1.45 13.49 15.74
*** ** * NS NS NS ** *** ** *** NS NS *** ***
15.09 2.19
*** *
6. Conclusions Stream chemistry in mid-high altitude Himalayan mountain streams is well buffered with pH in the range 7.0-8.5. Bicarbonate is the dominant anion and Ca and Mg are the dominant cations. Bedrock geology is the main influence on water chemistry both between and within regions. There is generally a decrease in concentration of all ions with altitude. This reflects changing land use (forest at high altitude and terrace at low altitude), temperature influences on solubility, existence of human habitation, and soil thickness. Land use impacts are masked by geological differences and land use information may be at an inappropriate scale for detailed statistical analysis. Nevertheless, concentrations of F, Fe, Cl, S04, Si, NOs, P04, K and Na are apparently increased by agricultural activity. This is a result of increased weathering and breakdown of the soil structure, addition of mineral fertilisers and extensive irrigation. Trace metal concentrations (Al, Sr, Ba, Mn) are also high in agricultural catchments. More detailed studies directed specifically at pristine and agricultural catchments of similar geology are required to confirm these preliminary observations and interpretations. The high altitude forest and alpine scrub covered catchments in these areas are unlikely to be sensitive to atmospheric deposition of acidic pollutants. In general the waters from these catchments have high concentrations of SO4 derived from weathering sources. High pH indicates that a large buffering capacity exists within the system and that further additions of anthropogenic SO, would be readily buffered. These systems already, however, leak a small amount of NO3 and this
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might increase in response to increased NO, deposition. Whilst this is unlikely to cause increased acidification of these upland streams and the biological implications of increased NO3 concentrations are not known, downstream eutrophication problems may occur. Close links have been reported between stream invertebrate community structure and stream chemistry (Rundle et al., 1993) in these environments and land use change could have biological consequences through changes in water chemistry. Future surveys of water chemistry and biology are needed in similar Himalayan environments to provide the necessary baseline data against which to assess damage caused by anthropogenic influences; in particular, the impact of land use and land cover on stream chemistry should be quantified so that the sensitivity of these systems to anthropogenic pollution can be assessed. This is particularly important given the desire to maintain ecosystem stability and bio-diversity in the face of continued development of these areas in response to increasing population pressure in the middle hills and increasing tourist pressure in the high hills.
Acknowledgements The success of this survey is due to the hard work and effort of the sampling teams who covered large distances on foot over difficult terrain and in a short time. Thanks are due to Jo and Mollie Porter, Roger Wyatt, Dick Johnson and John Law. Logistical help and support was provided by R. Maskey (Central Division of Soil Science, HMG Nepal) and P. B. Shah (ICIMOD). A skilled and dedicated team carried out the chemical analyses and thanks are due to Margaret Neal, Hazel Jeffries and Martin Harrow. The research described here was funded in part by the Environmental Monitoring and Assessment Program (EMAP) of the United States Environmental Protection Agency (USEPA). It has not been subjected to peer and/or policy review by the USEPA and, therefore, does not necessarily reflect the views of the USEPA. No official endorsement by the USEPA should be inferred.
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