IWMM 모형을 이용한 작물과 토양의 물리적 특성에 따른 관개용수량 변동 특성 분석
Analysis of Irrigation Water Amount Variability based on Crops and Soil Physical Properties Using the IWMM Model
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초록
In this study, we analyzed the variability of irrigation water amounts based on the combination of various crops and soil textures using the Irrigation Water Management Model (IWMM). IWMM evaluates the degree of agricultural drought using the Soil Moisture Deficit Index (SMDI). When crops are damaged by the water scarcity under the drought condition indicating that the SMDI values are in negative (SMDI<0), IWMM irrigates appropriate water amounts that can shift the negative SMDI values to “0” to crop fields. To test the IWMM model, we selected the Bandong-ri (BDR) and Jucheon (JC) sites in Gangwon-do and Jeollabuk-do provinces. We derived the soil hydraulic properties using the near-surface data assimilation scheme form the Time Domain Reflectrometry (TDR)-based soil moisture measurements. The daily root zone soil moisture dynamics (R: 0.792/0.588 and RMSE: 0.013/0.018 for BDR/JC) estimated by the derived soil parameters were matched well with the TDR-based measurements for validation. During the long-term (2001~2015) period, IWMM irrigated the minimum water amounts to crop fields, while there were no irrigation events during the rainy days. Also, Sandy Loam (SL) and Silt (Si) soils require more irrigation water amounts than others, while the irrigation water were higher in the order of radish, wheat, soybean, and potato, respectively. Thus, the IWMM model can provide efficient irrigation water amounts to crop fields and be useful for regions at where limited water resources are available.
Abstract
In this study, we analyzed the variability of irrigation water amounts based on the combination of various crops and soil textures using the Irrigation Water Management Model (IWMM). IWMM evaluates the degree of agricultural drought using the Soil Moisture Deficit Index (SMDI). When crops are damaged by the water scarcity under the drought condition indicating that the SMDI values are in negative (SMDI<0), IWMM irrigates appropriate water amounts that can shift the negative SMDI values to “0” to crop fields. To test the IWMM model, we selected the Bandong-ri (BDR) and Jucheon (JC) sites in Gangwon-do and Jeollabuk-do provinces. We derived the soil hydraulic properties using the near-surface data assimilation scheme form the Time Domain Reflectrometry (TDR)-based soil moisture measurements. The daily root zone soil moisture dynamics (R: 0.792/0.588 and RMSE: 0.013/0.018 for BDR/JC) estimated by the derived soil parameters were matched well with the TDR-based measurements for validation. During the long-term (2001~2015) period, IWMM irrigated the minimum water amounts to crop fields, while there were no irrigation events during the rainy days. Also, Sandy Loam (SL) and Silt (Si) soils require more irrigation water amounts than others, while the irrigation water were higher in the order of radish, wheat, soybean, and potato, respectively. Thus, the IWMM model can provide efficient irrigation water amounts to crop fields and be useful for regions at where limited water resources are available.
참고문헌 (25)
- Belmans, C., "Simulation of the water balance of a cropped soil", SWATRE. J. Hydrol, 63, pp.271~286 (1983)
- Eom, K. C., "Soil Water", Korean J. Soil Sci. Fert, 42, pp.102~125 (1999)
- 엄기철, "봄배추의 물 절약형 관개기준 설정", 한국토양비료학회지(Korean Journal of Soil Science and Fertilizer), 43(6), pp.812~822 (2010), 한국토양비료학회
- Feddes, R. A., "Simulation Monographs" (1978), Pudoc. Wageningen
- Goldberg, D. E., "Genetic algorithms in search and optimization and machine learning" (1989), Addison-Wesley Publishing Co Inc
- Holland, J. H., "On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms: a numerical study for mixed pixel environment", Adv Water Resour, 28, pp.856~870 (1975)
- Ines, A. V. M., "On quantifying agricultural and water management practices from low spatial resolution RS data using genetic algorithms: A numerical study for mixedpixel environment", Adv. Water Resour, 28, pp.856~870 (2005)
- Amor V. M. Ines, "Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithm: 1. Conceptual modeling", Water Resources Research, 44(6) (2008), Wiley-Blackwell[DOI]
- Amor V. M. Ines, "Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithms: 2. Using airborne remote sensing during SGP97 and SMEX02", Water Resources Research, 45(1) (2009), Wiley-Blackwell[DOI]
- Amor V. M. Ines, "Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithms: 2. Using airborne remote sensing during SGP97 and SMEX02", Water Resources Research, 45(1) (2009), Wiley-Blackwell[DOI]
- Jeon, S., "Optimum conditions of automatic irrigation control system and irrigation for cucumber cultivation under greenhouse", Ph.D, Major in Agricultural Chemistry, pp.2010
- 정필균, "가을배추의 물 절약형 관개기준 설정", 한국토양비료학회지(Korean Journal of Soil Science and Fertilizer), 44(5), pp.679~687 (2011), 한국토양비료학회
- Kim, H. S., "Analysis of irrigation water use for upland crops in Jeju", KCID, 12(1), pp.50~59 (2005)
- User’s guide of SWAP version 2.0; Simulation of water, solute transport, and plant growth in the Soil-Atmosphere-Plant environment, "Kroes, J. G.", Wageningen Agricultural University, DLO Winand Staring Centre, 53~128, pp.Report 81 (1999)
- Leij, F. J., "Characterization and Measurement of the Hydraulic Properties of Unsaturated Porous Media", pp.1269~1281 (1999), Univ. of Calif.
- Ministry of Agriculture Food and Rural Affairs, "Food, agriculture, forestry and fisheries statistical yearbook" (2012)
- Mualem, Y., "A new model for predicting the hydraulic conductivity of unsaturated porous media", Water Resour. Res, 12, pp.513~522 (1976)
- Narasimhan, B., "Development and evaluationof soil moisture deficit index (SMDI) and Evapotranspiration deficit index (ETDI) for agricultural drought monitoring", Agric. Forest Meteorol, 133, pp.69~88 (2005)
- Yongchul Shin, "Soil hydraulic properties in one-dimensional layered soil profile using layer-specific soil moisture assimilation scheme", Water Resources Research, 48(6) (2012), Wiley-Blackwell[DOI]
- Yongchul Shin, "Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications", Water Resources Research, 49(10), pp.6208~6228 (2013), Wiley-Blackwell[DOI]
- Shin, Y., "Development of irrigation water management model for reducing drought severity using remotely sensed soil moisture footprints", J. Irrig. Drain. Eng, 140(7), pp.1~11 (2014)
- 신용철, "원격탐사자료를 이용한 시⋅공간적으로 분포되어 있는 토양수분산정 및 가뭄평가: (I) 토양수분", 한국물환경학회지, 32(1), pp.60~69 (2016), 한국물환경학회
- van Genuchten, M. T., "A closed-form equation foe predicting the hydraulic conductivity of unsaturated soils", J. Soil Sci Soc Am, 44, pp.892~898 (1980)
- Theory of SWAP version 2.0: Simulation of water flow and plant growth in the soil water-atmosphere-plant environment, "van Dam, J. C.", Wageningen Agric.Univ., and DLO Winand Staring Cent., ~, pp.Tech. Doc. 45 (1997)
- van Dam, J. C., "Field-scale water flow and solute transport. SWAP model concepts, parameter estimation and case studies", Ph.D, pp.2000