Impacts of land-use changes on watershed discharge and water quality in a large intensive agricultural area in Thailand

Figures & data

Figure 1. Lower Yom River Basin showing the 14 water sampling points.

Table 1. Location of surface water stations.

Station	Location
YO.01	Phothale district, Phijit province
YO.02	Phopratubchang district, Phijit province
YO.03	Samngam district, Phijit province
YO.04	Bangrakam district, Phitsanulok province
YO.05	Mueang district, Sukhothai province
YO.06	Tumbon Pakquare Meuang district, Sukhothai province
YO.07	Sawankalok district, Sukhothai province
YO.08	Srisatchanalai district, Sukhothai province
YO.09	Wangching district, Phrae province
W01	Discharging waste water point of Bangrakam district, Phitsanulok province
W02	Discharging waste water point of Samngam district, Phijit province
W03	Discharging waste water point of Meuang district, Sukhothai province
W04	Discharging waste water point of Sawankalok district, Sukhothai province
W05	Discharging waste water point of Srisatchanalai district, Sukhothai province

Table 2. Data sources for the SWAT (Soil and Water Assessment Tool) model.

Main theme	Year	Sub-theme	Data sources
DEM		DEM	Derived from elevation data with GIS
Soil group	2001	Soil texture	Derived from 1:50 000 scale digital map of the Land Development Department (LDD)
Land use	2003, 2009	Land use	Derived from the LDD
Hydrology	2004	Sub-basin	Derived from digital map of the Water Resources Department
		Stream
		Hydro station	Royal Irrigation Department (RID)
Meteorology	2000–2013	Precipitation	Thai Meteorological Department (TMD)
		Temperature
		Relative humidity
		Solar radiation
		Wind speed
		Meteorology station
Water quality	2008–2013	NO3^–N	Region 2 Environment Office (EO), Lampang province and Region 3 EO, Phitsanulok province, Ministry of Natural Resources and Environment
		PO4^3−
Sediment	2006–2013	Sediment yields	RID
Reservoirs and diversion data	2013		Region 3 RID Office, Phitsanulok province
Management operations	2013	Rotation timings in planting and fertilizer application	Agricultural Land Reform Office, Ministry of Agriculture and Cooperatives

Figure 2. Spatial input maps for the SWAT model in the Lower Yom River showing (a) the digital elevation model (DEM), (b) soil groups, (c) land use in 2003, and (d) land use in 2009.

Figure 3. Observation stations in the Lower Yom River Basin used for the SWAT model calibration and validation.

Figure 4. Calibration and validation periods of (a) streamflow, (b) sediment and (c) nitrate and phosphate.

Table 3. Location of the hydrological observation stations used for the calibration and validation of flow, sediment yields and NO₃⁻ and PO₄³⁻ levels.

Station	Location	Calibration	Validation
Y.6	Srisatchanalai, Sukhothai	Flow (2006–2009)	Flow (2000–2004, 2010–2013)
Y.4	Mueang, Sukhothai	Sediments (2006–2009)	Sediments (2010–2013)
Y.16	Bangrakam, Phitsanulok	NO3^–N (2008–2010)	NO3^–N (2011–2013)
Y.17	Samnagm, Phichit	PO4^3− (2008–2010)	PO4^3− (2011–2013)
Y.5	Phothale, Phichit

Figure 5. Analysis of water quality of the Lower Yom River Basin showing the average temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), NO₃-N and PO₄³⁻ levels.

Figure 6. Comparison of the observed and simulated results for the monthly water flow (m³ s⁻¹; CMS) at, from top to bottom, hydrological stations Y.6 (R² = 0.85), Y.4 (R² = 0.77), Y.16 (R² = 0.74), Y.17 (R² = 0.71), and Y.5 (R² = 0.71).

Figure 7. Comparison of the observed and simulated results for monthly sediment yield at, from top to bottom, hydrological stations Y.6 (R² = 0.69), Y.4 (R² = 0.64), Y.16 (R² = 0.71), Y.17 (R² = 0.63), and Y.5 (R² = 0.68).

Figure 8. Comparison of the observed and simulated results for the river water NO₃-N concentrations at, from top to bottom, hydrological stations Y.6 (R² = 0.66), Y.4 (R² = 0.73), Y.16 (R² = 0.86), Y.17 (R² = 0.64), and Y.5 (R² = 0.70).

Figure 9. Comparison of the observed and simulated results for the river water PO₄³⁻ concentrations at, from top to bottom, hydrological stations Y.6 (R² = 0.70), Y.4 (R² = 0.61), Y.16 (R² = 0.87), Y.17 (R² = 0.91), and Y.5 (R² = 0.65).

Table 4. Description and optimal values used in the SWAT model calibration/validation.

			Optimal value at sub-basins:
Parameter	Model process	Description	1–15	16–22	23–25	26–29
CN	Flow	SCS runoff curve number for moisture condition II	*0.65	*0.3	*0.4	*0.4
SOL_AWC	Flow	Available water capacity of the soil layer (mm H2O/mm soil)	*0.9	*0.9	*0.9	*0.98
GWQMN	Flow	Threshold depth of water in shallow aquifer for percolation to occur (mm)	23	15	15	15
GW_DELAY	Flow	Groundwater delay time (d)	50	100	100	70
ESCO	Flow	Soil evaporation compensation coefficient	0.05	0.05	0.05	0.05
RCHRG_DP	Flow	Deep aquifer percolation fraction	0.5	0.5	0.5	0.5
ALPHA_BF	Flow	Baseflow alpha factor	0.08	0.08	0.08	0.08
GW_REVAP	Flow	Groundwater “revap” coefficient	0.02	0.02	0.02	0.02
REVAPMN	Flow	Threshold water level in shallow aquifer for “revap”	0.0	0.0	0.0	0.0
USLE_P	Sediments	USLE equation support practice (P) factor	0.0005	0.0005	0.0005	0.0005
SPEXP	Sediments	Exponential parameter for calculating sediment re-entrained in channel sediment routing	1.5	1.5	1.5	1.5
SPCON	Sediments	Linear parameter for calculating the maximum amount of sediment	0.3	0.1	0.1	0.1
RSDCO	Nitrate-N	Residue decomposition coefficient	0.09	0.09	0.09	0.09
NPERCO	Nitrate-N	Nitrogen percolation coefficient	0.05	0.05	0.05	0.05
SHALLST_N	Nitrate-N	Initial concentration of nitrate in shallow aquifer	0.10	0.10	0.12	0.12
RSDCO	Phosphate	Residue decomposition coefficient	0.05	0.05	0.05	0.05
PPERCO	Phosphate	Phosphorus percolation coefficient	10	10	10	10
GWSOLP	Phosphate	Concentration of soluble P in groundwater	0.09	0.10	0.10	0.10

Note: * means the default values of the parameters are multiplied by the number following the *

Table 5. Change detection for the Lower Yom River, 2003–2009.

Change	Area (km^2)	Percentage area (%)
Forest to Fieldcrop	355.69	2.53
Forest to Paddy	147.98	1.05
Forest to Perennial	99.68	0.71
Forest to Water	48.07	0.34
Forest to Urban	23.46	0.17
Fieldcrop to Urban	140.66	1.00
Paddy to Urban	84.34	0.60
Perennial to Urban	3.23	0.02

Figure 10. Land-use changes in the Lower Yom River from 2003 to 2009.

Figure 11. Effects of land-use change between 2003 and 2009 on the runoff (m³ s⁻¹; CMS).

Figure 12. Effect of land-use change between 2003 and 2009 on (a) annual runoff, (b) sediment yield, (c) NO₃⁻, and (d) PO₄³⁻ levels in the Lower River Yom Basin.

Figure 13. Effects of land-use change (2003–2009) on sediment yield.

Figure 14. Effects of land-use change (2003–2009) on NO₃-N load in the Lower Yom River Basin.

Table 6. Nitrate load observed in this study compared to previous studies around the world (modified from Huang et al. 2012, Oeurng et al. 2016).

Region	Anthropogenic area* (%)	Nitrate yield (kg N km^−2 year^−1)	Reference
Illinois, USA	91	~4000	David et al. (1997)
Northeastern USA	9.81	132.9	Mayer et al. (2002)
Northeastern USA	32.85	582.8	Mayer et al. (2002)
California, USA	3.2	58.0	Sobota et al. (2009)
California, USA	24.4	170.9	Sobota et al. (2009)
Central Germany	66.2	1850–4120	Rode et al. (2009)
Central Germany	61.6	2391	Müller et al. (2018)
Germany	< 1.0	336–493	Langusch and Matzner (2002)
Spain	< 0.1	561	Merchan et al. (2013)
Spain	48	2702	Merchan et al. (2013)
Northern Taiwan Northern Taiwan	< 0.1 5	660 2550	Kao et al. (2004) Kao et al. (2004)
Central Taiwan	< 0.1	585	Huang et al. (2012)
Central Taiwan	0.6–8.9	2327	Huang et al. (2012)
Central Taiwan	24.7	40 827	Huang et al. (2012)
3S Basin, Cambodia, Lao PDR and Vietnam	~12–44	135–1619	Oeurng et al. (2016)
Lower Yom River, Thailand	70.45	2770	This study

* Refers to areas subject to anthropogenic activities, such as increased population and urbanization, encroachment of forests by agriculture and urban areas, and degradation of forest resources.

Figure 15. Effects of land-use change (2003–2009) on PO₄³⁻ load in the Lower River Yom Basin.

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