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Nitrogen Flow Analysis from Different Land-Use of the Chi River Basin (Maha Sarakham Region, Thailand)

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Nitrogen Flow Analysis from Different Land-Use of the Chi River Basin (Maha Sarakham Region, Thailand) International Journal of GEOMATE, March., 2021, Vol.20, Issue 79, pp. 9-15 ISSN: 2186-2982 (P), 2186-2990 (O), Japan, DOI: https://doi.org/10.21660/2021.79.6165 Geotechnique, Construction Materials and Environment NITROGEN FLOW ANALYSIS FROM DIFFERENT LAND-USE OF THE CHI RIVER BASIN (MAHA SARAKHAM REGION, THAILAND) * Nida Chaimoon 1 1 Circular Resource and Environmental Protection Technology Research Unit (CREPT), Faculty of Engineering, Mahasarakham University, Thailand *Corresponding Author, Received: 03 Nov. 2020, Revised: 12 Jan. 2021, Accepted: 27 Jan. 2021 ABSTRACT: This paper aims at assessing the effect of land use on nitrogen flows from a significant land- use area in the Chi River basin (Maha Sarakham region) in Thailand. The Chi River is one of the main rivers, and many land use categories affect the quality of the river. Statistical data and referred data was collected as the secondary data from credible sources to identify the flows. The data show a strong effect of land use on nitrogen with the highest load dominated by paddy field (66,597.51 tonne/year), and the lowest value in the community (1,005.71 tonne/year). Nitrogen flow increased with the fertilizer application in paddy field and farm plants (34,834.07 tonne/year). Paddy field discharged nitrogen to the Chi River 47 tonne/year in form of surface runoff. Also, the community without wastewater collection system takes part in a non-point source (NPS) of nitrogen to the Chi River at 299 tonne/year. The management's suggestion is to control fertilizer application, burning of agricultural residue such as rice straw, and wastewater treatment before disposal. Keywords: Nitrogen; Chi River; Substance Flow Analysis (SFA); Land-Use 1. INTRODUCTION Nutrient problems can be magnified by the improper land-use that discharges nutrients to Pollution from natural phenomena or human water bodies [5, 6]. Concentrated agricultural activities and living things actions affects water activities and rapid urbanization created immense quality in any water resource. Water quality pressure on water quality. The percentage of disturbs the environment, natural resources, human agricultural land is significantly positive correlated activities, and human health [1, 2]. Pollution can with water pollution due to fertilizer application be categorized into point source (PS) and non- entering surface water through runoff [7]. point source (NPS) pollution. PS pollution mainly Urbanization is associated with changes in comprises of industrial and domestic wastewater land- uses through infrastructure development, loads, which can be identified through the population density, and community. The increase discharging point or pipe [3]. NPS pollution in impervious areas (i.e., roads, rooftops, usually comes from unidentified sources, such as impermeable pavement, and parking lots) results in agriculture land, street runoff, and the deposition NPS pollution increase in runoff and transportation of atmospheric pollutants [4]. The pattern of NPS of NPS pollutants to receiving waters [8]. The pollution leads to the effect of land use on water Forest area was considered as net sinks of nitrate quality. [9]. Land-use category is relevant to water quality Nutrient load is one of significant problems for within a watershed, and landscape alignments may water resource management, the interaction of be more sensitive predictors of water quality. nutrient, water and pathways has been traced and The Chi River is the longest river in Thailand. tracked by much research in the past. Nutrient load It is 765 km long. In wet seasons there are often in water is a result of several interacting processes flash floods in the floodplain of the Chi River in the basin, including an exchange between cycles basin. The river originates in the Phetchabun in the terrestrial, aquatic, geological, and mountains and then flows to the east part through atmospheric environment. These processes can be the central Isan provinces of Chaiyaphum, Khon characterized into: (1) nutrient release (e.g., Kaen, and Maha Sarakham, then turns south in Roi through mineralization, weathering, fertilization, Et and runs through Yasothon and joins the Mun atmospheric deposition, sewage effluents); (2) River in the Kanthararom district of Sisaket water transport (conducting, e.g., transit time and Province. The Chi River carries approximately 9.3 flow paths); and (3) transformation and km3 of water per annum [10] immobilization (e.g., denitrification, sedimentation, and adsorption). 9 International Journal of GEOMATE, March., 2021, Vol.20, Issue 79, pp. 9-15 Fig.1 Chi River Basin [12] Substance Flow Analysis (SFA) is an 2.2 System Boundary environmental accounting tool used to trace and track environmental problems. SFA is an The Chi river basin covers the middle part of appropriate method to answer the questions of the northeastern region (Fig.1). The area of the substance flows from input transformation basin in Maha Sarakham province was selected to processes until discharging in system boundary be the specific system boundary (Fig 2) Maha [11]. Therefore, this study aimed to analyze Sarakham is the fast-growing city located along nitrogen flows by SFA quantitatively, and propose the Chi River. It has undergone rapid urbanization. implemented solutions in the system boundary. Chi River is used as a water resource of tap water supply, agriculture and fishery. 2. METHODOLOGY 2.1 Substance Flow Analysis (SFA) Substance Flow Analysis (SFA) is an environmental accounting tool based on the concept of mass balance in a specific area and time. SFA for nitrogen provides a systematic assessment of flows and stocks within a defined system in space and time. It was undertaken to quantify nitrogen flows from different land-use area (as a process) in the Chi river basin (Maha Sarakham region). Fig. 2 Maha Sarakham province Location [13] 10 International Journal of GEOMATE, March., 2021, Vol.20, Issue 79, pp. 9-15 PI4 PI5 PO1 PO2 FI5 FI6 FI7 FI8 FO1 FO2 PI1 Paddy Field PO4 PI2 PO5 PI3 PS1 FI1 Farm Plants FO FI2 4 FI3 FO5 FS1 FI4 CI1 Community CI2 CI3 CI4 CI5 CI6 CI7 CS1 CI8 PO3 FO3 CO1 Chi River (Maha Sarakham Region) Fig.3 Nitrogen flows The Chi River basin area is 53.18% of Maha 2.3 Data Collection Sarakham province which was 2,998 km2. The land-use area in the system boundary was Nitrogen flows in the system boundary were categorized into community along the Chi River traced to define quantity and pathway through 6.83% (205 km2), agriculture 82.88% (2,484 km2), relevant processes until discharge to the forestry 3.94% (118 km2) and miscellaneous environment. The nitrogen flow diagram of the 2.63% (79 km2). The activities that have an impact system boundary is shown in Fig 3. on the Chi River were only community and In order to know the nitrogen flows through the agriculture along the Chi River. The major various land use categories, secondary data was agriculture included paddy field 62.17% (1,864 obtained from official reports by related km2), corn 0.01% (0.3 km2) and cassava 11.28% organizations and relevant literature review [14- (338 km2). The period of data collection was in the 29]. Details of data acquisition were described as year of 2018 (one year period). follows: 11 International Journal of GEOMATE, March., 2021, Vol.20, Issue 79, pp. 9-15 2.1.1 Statistical Data Table 2 Data acquisition and calculation for farm Official reports from governmental plants organizations such as Department of Land Development, National Statistical Office, Flows Material Calculation Department of Irrigation, and Office of Regional Input Fertiliser corn % N in fertilizer × Environment. (FI1) area × fertilizer consumption × loops 2.1.1 Reference Data Fertiliser % N in fertilizer × Due to unavailable data in the system boundary, cassava (FI2) area × fertilizer secondary data (nitrogen concentrations) was consumption × loops obtained from a nearby area, which has similar Irrigation corn N in irrigated water × management based on literature review was (FI3) area × water applied to the nitrogen flows. consumption × loops Irrigation N in irrigated water × 2.3 Calculation cassava (FI4) area × water consumption × loops The calculations basically multiplied the flows Rain water N in rainwater × area (which is recognized as activity) of input, output, corn (FI5) and stock of each land-use area in the system Rain water N in rainwater × area boundary with their nitrogen concentration ([N], corn (FI6) mg N/L). Finally, the results of nitrogen flows Atmospheric N in atm × area × were shown in the unit of tonne N/year. Nitrogen fixation corn loops flows were calculated based on mass balance over (FI7) the processes. Determination methods for nitrogen Atmospheric N in atm × area × flows were summarized in Tables 1-3. fixation loops cassava (FI ) Table 1 Data acquisition and calculation for paddy 8 Output Burning (FO ) N in input × % field 1 burning Evaporation N in input × % Flows Material Calculation (FO2) evaporation Surface runoff N in input × factor of N in fertilizer × area Fertiliser (PI ) (FO3) runoff 1 × loops Corn N in corn x area × N in irrigated water × production loops Irrigation (PI2) area × water (FO4) consumption × days Cassava N in cassava × area × production loops Input Rain water N in rainwater × area (FO5) (PI3) × loops Stock Infiltration N in input × % N in seed × area × Seed (PI ) (FS1) infiltration 4 loops Atmospheric N in atm × area × Table 3 Data acquisition and calculation for community fixation (PI5) loops N in input × % Burning (PO1) Flows Material Calculation burning Input Water supply N in water supply × Evaporation N in input × % (CI1) water consumption × (PO2) evaporation population Surface runoff N in input × % Rice N in rice × Output (PO3) burning consumption consumption × Rice (CI2) population production N in rice × area Beef N in beef × (PO4) consumption consumption × Rice straw N in rice straw × area (CI3) population (PO5) × rice straw Pork N in pork × Infiltration N in input × % consumption consumption × Stock (CI ) population (PS1) infiltration 4 10 International Journal of GEOMATE, March., 2021, Vol.20, Issue 79, pp.
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