However, Jiapu Township exceeds the water quality standards seriously because of the superfluous point source pollution. The water quality of other Townships ...
Land Use and Water Quality Response in the Northern Region of Changxing County Min Zhang, Qingsheng Liu, Gaohuan Liu State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences Beijing, China Abstract—In this paper, taking the northern region of Changxing County for example, with ammonia nitrogen as a pollution assessment index, we used an improved export coefficient method for estimate polluting load of non-point source pollution (NSP) and the social pollution survey data in the study area to estimate point source pollution. By comparing the total pollution output and the national surface water environmental quality standards find that the whole study area achieves the second water quality standard. However, Jiapu Township exceeds the water quality standards seriously because of the superfluous point source pollution. The water quality of other Townships is good. Further analysis showed that different types of land use and proportions in the northern region of Changxing County have a significant impact on the non-point source pollution, the general law is farmland contributes the largest share of the non-point source pollution output, followed by residential area and bare land, besides, with the increase in the proportion of forest and the decrease of farmland and residential area, the non-point source pollution reduces gradually. Keywords-Non-point source pollution; land use; land use structure; water quality response
I.
INTRODUCTION
The water quality response of different land use types has huge difference. Previous studies mostly focus on single type of land use, while little attention was paid to the water quality response of differ land usente combinations. However, in actual situation, land use types are always combined with each other, so the study about land use combination is more practical and significative. For example, adjusting the land use mix ratio appropriately can improve water quality and has little negative effect on the economy at the same time. The improved export coefficient method can avoid the complex process of non-point source pollution, utilizing the data of land use which is obtained easier, with fewer parameters needed and simpler operation. Moreover, it combines with GIS spatial analysis conveniently, and has accuracy and broad applicability for the estimation of non-point source pollution [1-4]. The specific model formula [3] is as follows:
n
L = λ{α ∑ Ei [Ai (I i )] + P} ; α = M i / M i =1
In the formula: L is the loss of nutrition; λ is the transport loss coefficient; α is the rainfall coefficient; Ei is the export coefficient of the kind I nutrient source;
Ai is the area of kind I
I i is the nutrient input volume of kind I source of nutrition; P is the amount of nutrients carried by rainfall; M is the average years of NSP loading; M i is the land use or the population;
NSP loading of drainage basin in year i. II.
OVERVIEW OF THE STUDY AREA
Changxing County is in Zhejiang Province, at latitude 30 ° 43'~30 ° 11 ', longitude 119 ° 33'~120 ° 06'. The regional area is 1434.447210 km2, has a subtropical marine monsoon climate. Most water quality is the Grade 2. In this paper, using GIS hydrological analysis module, we divide watershed based on 30-meter DEM data of Changxing County and select the most northern part which is a complete watershed as the study area, covering the whole area of Baixian Township, Meishan Township, Huaikan Township and Shuikou Township, also most part of Jiapu Township, Xiaopu Township and Zhicheng Township. III.
THE METHOD AND PROCESS OF ANALYSIS
A. Data collection and acquisition 1) The acquisition of land use data Through manual interpretation of 2.5 meters ALOS remote sensing satellite images, we get the land use map in study area. For the analysis combined with administrative division, we estimate the areas of different types of land use in each township and the administrative area of each township by the spatial analysis function of GIS. Besides, we divide land use structure for further analysis. The results of these analyses are expressed in TABLE I. 2) NSP output coefficient, transport loss coefficient, nutrient input coefficient of rainfall and the coefficient of rainfall effect
We get the output coefficient of farmland by the amount of fertilizer (1.1786 * 107kg), the area of farmland in Changxing (381.219951km2), and the ratio of the loss of nitrogen runoff to the amount of fertilizer of that year (6.36% [4]). Other coefficients refer to the ‘Technical specifications of Water Environment Comprehensive Control Planning in Taihu basin’ and related documents. The results of these analyses are
3) The data of population, amount of fowl and rainfall in townships and study area. We get the populations of townships by the relevant statistical yearbooks, using GIS spatial analysis to estimate the amount of fowl; besides, we calculate the rainfall by spatial interpolation. The results of these analyses are expressed in TABLE III.
expressed in TABLE II. (We estimate α = M i / M =0.597 by the ammonia nitrogen output in the northern region of Changxing in 2007 and 2008.) TABLE I.
LAND USE TYPES AND STRUCTURES OF TOWNSHIPS
2517797 (3.23%)
Xiaopu (Partly) 6144232 (9.69%)
8914193 (10.74%)
Zhicheng (Partly) 28718498 (32.71%)
Jiapu (Partly) 18356917 (51.19%)
563069 (0.62%)
904111 (1.16%)
1064899 (1.68%)
1577257 (1.90%)
215916 (0.25%)
105146 (0.29%)
6064817 (1.26%)
36325809 (83.9%)
73990502 (81.64%)
61026762 (78.30%)
45817202 (72.24%)
66855210 (80.53%)
34452669 (39.24%)
6656819 (18.56%)
298257126 (61.85%)
Meadow
8620 (0.02%)
244141 (0.27%)
1050282 (1.35%)
454184 (0.72%)
3212 (0.0039%)
22059 (0.025%)
0 (0.00%)
1782498 (0.37%)
Water
137781 (0.32%)
810160 (0.89%)
530737 (0.68%)
988655 (1.56%)
1663847 (2.00%)
3971461 (4.52%)
4097155 (11.43%)
21315787 (4.42%)
Settlement Place
3466174 (8.01%)
6864439 (7.57%)
7530801 (9.66%)
6470301 (10.20%)
3768506 (4.54%)
18353916 (20.91%)
5762505 (16.07%)
70202697 (14.56%)
Bare Area
813746 (1.88%)
3591713 (3.96%)
4380861 (5.62%)
2487001 (3.92%)
237391 (0.29%)
2056457 (2.34%)
880465 (2.46%)
14447632 (3%)
Total Area
43296049
90627301
77941351
63426474
83019616
87790976
482198166
Structure
Priority to forests (I)
Priority to forests (I)
Priority to forests (I)
ForestFarmlandResidential area (II)
ForestFarmland (III)
ForestFarmlandResidential area (II)
35859007 FarmlandForestWaterResidential area (IV)
Baixian
Huaikan
Meishan
Farmland
909501 (2.10%)
4563277 (5.04%)
Garden
1634418 (3.77%)
Forest
Shuikou
Study Area 70127609 (14.54%)
ForestFarmlandResidential area (II) Unit: Square meter
TABLE II.
POLLUTION EXPORT COEFFICIENT, TRANSPORT LOSS COEFFICIENT AND RAINFALL COEFFICIENT
Type
NSP output coefficients
Ratio into the river
Farmland
1966 kg ⋅ km −2 ⋅ a −1
1[5]
−2
−1
Degradation coefficients
Transport loss coefficient 0.09[5, 6]
Garden plot
15.84 kg ⋅ km ⋅ a [7]
0.962[5]
0.08658[5, 6]
Forest
1.74 kg ⋅ km −2 ⋅ a −1 [7]
0.945[5]
0.08505[5, 6]
Meadow
1.92 kg ⋅ km −2 ⋅ a −1 [7]
0.978[5]
0.08802[5, 6]
Water
0 kg ⋅ km −2 ⋅ a −1
/
/ 0.08235[5, 6]
−2
−1
Residential area
1.12 t ⋅ km ⋅ a [3]
0.915[5]
Bare Area
1.49 t ⋅ km −2 ⋅ a −1 [2]
1
Urban Population
1.8 kg ⋅ ca −1 ⋅ a −1
0.8
Rural Population
1.46 kg ⋅ ca −1 ⋅ a −1
0.7
0.063
0.6
0.054
0.6
0.054
Pig Cattle
−1
−1
0.74 kg ⋅ ca ⋅ a [3] −1
−1
10.21 kg ⋅ ca ⋅ a [3] −1
−1
0.09 0.09[6]
0.072
Sheep
0.4 kg ⋅ ca ⋅ a [3]
0.6
0.054
Fowl
0.04 kg ⋅ ca −1 ⋅ a −1 [3]
0.6
0.054
−1
Rainfall
1.27 mg ⋅ L [8]
/
/
Point Source
/
1
0.09
effectively. The pollution output of forest which takes 61.85 percent of total area is very low; however, the ratio of ammonia nitrogen output of farmland, residential area and bare area which take 14.54 percent, 14.56 percent and 3 percent of total area achieve 64 percent, 25 percent and 10 percent. Therefore, we must control the pollution output of farmland, residential
B. The estimation of point source pollution, NSP and the assessment of water quality in study area and townships Using improved export coefficient method to estimate the NSP, while getting point source pollution by the data of pollution survey in Huzhou, and then we assess the water quality referring to the ‘Surface water quality standards’. TABLE III. Township
POPULATION AND THE AMOUNT OF FOWL AND RAINFALL
Rural Population
Baixian 1.077
Huaikan 1.472
Meishan 1.781
Xiaopu (Partly) 1.785
Shuikou 1.756
Zhicheng (Partly) 1.765
Jiapu (Partly) 1.421
Study Area 44.608
Urban Population
0.028
0.043
0.641
0.196
0.057
5.933
0.029
19.380
Pig
1.391
2.912
2.504
2.038
2.667
2.821
1.152
46.090
Cattle
0.012
0.025
0.022
0.018
0.023
0.024
0.010
0.400
Sheep
0.580
1.214
1.044
0.850
1.112
1.176
0.480
19.220
Fowl
23.092
48.337
41.571
33.829
44.280
46.824
19.126
765.080
Rainfall (mm)
1158.900
1235.000
1570.000
1248.100
1570.000
1280.200
1266.300
9328.500 Unit: Ten thousand
TABLE IV.
ESTIMATION OF POLLUTION EXPORT AND ASSESSMENT OF WATER QUALITY
The amount of Ammonia nitrogen export（*109mg） Point Source Non-point Source
Amount of Runoff (*109L)
Water Quality
Baixian
0.29
0.036
0.33
0.36
0.59
0.74
1.47
1.69
The Total Pollution Output 2.02
22
I
Huaikan
0.00
0.056
0.056
1.16
0.81
1.56
1.57
3.52
3.58
45
I
Meishan
1.33
0.83
2.16
1.04
0.98
1.34
1.99
3.36
5.52
39
I
Xiaopu(Partly)
0.49
0.25
0.74
1.21
0.98
1.09
1.59
3.28
4.02
32
I
Shuikou
0.70
0.074
0.78
1.18
0.96
1.43
1.99
3.57
4.35
41
I
Zhicheng(Partly)
4.92
7.69
12.60
4.24
0.97
1.51
1.63
6.72
19.30
44
II
Jiapu(Partly)
38.20
0.037
38.30
2.35
0.78
0.62
1.61
3.74
42.00
18
>V
Total
45.70
8.94
54.90
11.52
6.07
8.28
11.85
25.88
80.80
241
II
Township
Indust ry
Urban Population
Total
Land Use
Rural Population
TABLE IV shows that the water quality of study area is Grade II, and the contribution of NSP has reached 32.03 percent, of which the land use pollution output is dominant, the ratio of industry contamination is 84 percent in point source pollution; the northern part of Zhicheng township also attains Grade III water quality, but the point source pollution is serious, especially the urban population domestic pollution, land use pollution output still dominant in NSP; the water quality of Jiapu exceeds standard badly, the main reason is industry pollution, we can estimate by the data in TABLE IV that the reduction rate of ammonia nitrogen will be 57.14 percent if Jiapu achieves Grade III water quality. The water quality of other townships is Grade I, most output of ammonia nitrogen is from NSP, the contribution of land use and fowl pollution output are larger. C. The relationship between water quality and land use 1) The water quality response of different land use types The pollution load ratios of study area based on the data above are depicted in Figure 1. Most ammonia nitrogen output of NSP is from land use, following by fowl and population. So the reasonable usage of land use will reduces the NSP
Fowl
Rainfall (mg)
Total
area and bare area efficiently to reduce the ammonia nitrogen output of land use.
Figure 1. The pollution load ratio chart
2) The water quality response of different land use structures Different townships have different land use structures; in order to know the impact of diverse structures to non-point source pollution we draw Figure 2 and Figure 3 for comparative study.
The water quality of study area is Grade II; it’s also good in every township but Jiapu. •
We have studied the water quality response of different land use types, structures and ratios in the northern part of Changxing. The general law is the contribution of farmland to the NSP output is largest, following by residential area and bare area. Along with the increase of forest and the decrease of farmland and residential area, the pollution will reduce. So the water quality of structure I is best, while if the proportion of farmland is highest, the water quality will be worst. The pollution outputs of other structures are at the middle level. In order to meet the standard of water quality and keep sustainable economic development at the same time, different places could adjust the structures and ratios of land use according to local nature conditions.
•
Transport loss coefficient should obtain through field test and the water quality response of land use types and structures also should take space variation into account. There is still room for improvement in these areas.
Figure 2. Ammonia nitrogen export Figure 3. Ammonia nitrogen export of different land use structure of different land use ratio in structure I
We know from Figure 2 that the ammonia nitrogen output of structure I is lowest, while structure IV is most, structure II and III are at the middle level, furthermore, structure II is a little higher than structure III. The townships in Fig.3 are all belong to structure I, but the ammonia nitrogen outputs are not the same because of the different ratio of forest cover in those townships. We find that the output of pollution is lower if the forest cover increase. Along with one percent decrease of forest, ammonia nitrogen output of per unit area will increase one milligram. The townships in TABLE V are all belong to structure II, but the ratio of land use types are different, so the output of pollution differs from each other. If the ratios of farmland and residential area are decreased, while forest TABLE V.
AMMONIA NITROGEN EXPORT OF LAND USE STRUCTURE II
Township
Residential area (%)
Forest (%)
Farmland (%)
Xiaopu(Partly)
0.102
0.7224
0.0969
19.06735175
Zhicheng(Partly)
0.2091
0.3924
0.3271
47.97869996
Study Area
0.1456
0.6185
0.1454
23.79344997
increase, the pollution will reduce. Along with three percent decrease of forest and one percent increase of residential area, and two percent increase of farmland, ammonia nitrogen output of per unit area will increase three milligram. We know from TABLE V, in a certain extent, the NSP could be controlled by the reasonable land use structures and ratios. This kind of processing method is more practical and effective than changing single kind of land use type. Furthermore, it is very good for maintaining the diversity of the ecosystem and keeping the sustainable development of economy and environment in long term point of view. IV.
CONCLUSIONS AND OUTLOOK
From the study above, we can draw some conclusions and propose some prospects below. •
•
We get a series of coefficient which are appropriate for Changxing by the collection of social survey data and lots of literatures, and also the spatial analysis of GIS, furthermore, we estimate the point source pollution and NSP in study area irrationally. According to the standard of surface water quality, we assess the water quality of study area and townships:
Normalized Ammonia nitrogen export(mg)
REFERENCE [1]
[2]
[3]
[4]
[5]
[6]
[7] [8]
L. Xue and L. Yang, “Research advances of export coefficient model for non-point source pollution,” Chinese Journal of Ecology, vol. (4), pp. 755-761, 2009. X. Ding, R. Liu and Z. Shen, “Method for obtaining parameters of export coefficient model using hydgology and water quility data and its application,” Journal of Beijing Normal University (Natural Science), vol. 42(5), pp. 534-538, 2006. M. Cai, H. Li and Y. Zhuang, “Application of modified export coefficient method in polluting load estimation of non-point source pollution,” Journal of Hydraulic Engineering, vol. (7), pp. 40-45, 2004. L. Yang, D. Wang and L. Xia, “The Features and Control Approachs of Taihu Agricultural Pollution,” China Water Resources, vol. (20), pp. 2930, 2004. H. Cheng, F. Hao and X. Ren, “The study of the rate loss of nitrogenous non --point source pollution loads in diferent precipitation levels,” Aeta Scientiae Circumstantiae, vol. (3), pp. 392-397, 2006. Y. Chen, B. Xi, L. He and J.Wang, “Application of QUAL2 K model for prediction of water quality in West Shaoxi,” Chinese Journa1 of Environmenta1 Engineering, vol. (7), pp. 1000-1003, 2008. Y. Gao. “Research on the nutrient under different landuse in the west of Taihu Lake Basin,” Hohai University, Nanjing, 2007. H. Li, X. Liu and G. Yang, “Nutrient Pollutant Load Analysis of Xitiaoxi Watershed in Taihu Region,” Journal of Lake Sciences, vol. A16, pp. 89-98, 2004.
