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AYO PERBANYAK KUNJUNGI BLOG INI TRIMAKASIH

5 Mar 2012

Organic Pollutan

monitorring of organic pollutants in  streams and a reservoir
(case study in selorejo dam, malang ,jawa timur, indonesia)

BAMBANG PARI PURWANTO
Brawijaya University, Malang, East of Java, Indonesia
Jl. Mayjen Haryono No.167, Telp. 0341-553286, 587710, 587711, Fax. 0341-551430 Malang 65145

The Efect of fertilizer in land agriculture has become decreasing water quality that couse Eutrophication. Analysis Method that used is analysis model with AVSWAT 2000, at characteristic of study area are : 237.312 km2 catchment area of Selorejo Dam
, simulation devide in 62 subwatershed area cacthment, including : Forest 0.395 %, mix-dry field 0.128 %, Rice Field 0.214 %, dry land 0.154 %, Urban 0.088 %, lake  0.021 %. The result show that the power river concerning to load polutant is calss III,that value is minimaly for categoried on good water quality . The result of simulation model 2003-2005 has become decreasing lake water quality, 18.5 % dan 23.5 %, total N (Mesotrophic)and Total P (Eutrophic). Meanwhile, the alteration of landuse in 2010 latters couses increasing load pollutant in lake of Selorejo DAM. The deviation of Model AVSWAT 2000, concerning to discarge model and measurement, R2 value is 0.9303, significance level ≤10, concerning to load polutant, R2 value is 0.907, significance level ≤10. The result of models are nonhomogeneous form time by time but homogeneous form space model and measurement.
Keywords : power river, Mesotrophic, Eutrophic.


RESULTS AND DISCUSSION
Runoff  generated by the AVSWAT2000 is based on the Soil Conservation Services (SCS) runoff equation. The SCS curve number is a functional of a soil’s permeability, land use and antecedent soil water condition for dry soil. Outcomes from model simulation from 2003 to 2005 were accurate when compared with the measured data ( R2 = 0.9303).      

Calibration of SWAT was performed for 2003 while 2005, as shown in Fig 8. First step, SWAT simulation was executed for 2003-2005 with land use data 2003 condition. Second; SWAT simulation was executed for 2005-2010 with land use data 2010 condition. (See Fig.9)

Result of SWAT simulation was divided into tree phases, first in land area, second in stream and finally at reservoir.


RISK LEVEL OF EUTROPHICATION IN RIVER
   RISK LEVEL OF EUTROPHICATION IN LAKE
The result of simulation model 2003-2005 has become decreasing lake water quality, 18.5 % dan 23.5 %, total N (Mesotrophic)and Total P (Eutrophic)

Conclusion

The SWAT model was the first time applied to the Selorejo reservoir Catchment area which is located in Brantas River basin East Java. The model was calibrated for the flow and initial results are presented for the nitrogen and phosphorous loadings in the watershed.

In general, the change of land cover in the land would be effected to increase runoff especially for nutrient loading on reservoir


Reference

J.R. Williams. 1998. Large Area Hydrologic Modelling and Assessment. Part I. Model development. J. Am. Water Resource. Assc. 34:73-89.
Dyad Rahway, Pengkajian Awal Kasus Pencemaran Waduk Karangkates, Malang Jawa Timur, Pusat Penelitian dan Pengembangan Sumber Daya Air, 2002.
Leone, A., F. Preti, M.N.Ripa, and G. Benigni, (2001), Evaluating of Agricultural Nutrient Diffuse Sources and Related Land Management. Rivista Di Ingegneria Agraria, XXXII (1):20-25
Lone A. & M.N. Ripa, (2002), Land use, Pollutant Nonpoint Sources and Related Modelling for Lakes Management. Lake Vico Experinece, Bolsena Int. Conference, 1-3 October 2002.
Neitsch, S.L., J.G. Arnold, J.R. Williams (1999) SWAT-Soil and Water assessment Tool-User’s Mannual Version 99.2
Spahr, N.E., end K.H. Wynn. 1997. Nitrogen and phosphorous in surface water of the Colorado River Basin. Journal of the American Water resources Association,.33:547-560.
Young, R.A., C.A. Onstad, D.D Bosh, and W.P Anderson. 1989. AGNPS. A Nonpoint-source pollution model for evaluating agricultural watershed. J. Soil Water Cons, 3.168, 173.
Wang Xixi , and Peilian Cui, Support soil conservation practices by identifying critical erosion areas within an American watershed using the GIS-AGNPS model.
 

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