So sánh các mô hình máy tính để ước lượng tài nguyên nước và chất lượng nước trong một lưu vực nông nghiệp

Springer Science and Business Media LLC - Tập 31 - Trang 3641-3665 - 2017
Yaoze Liu1, Sisi Li1,2, Carlington W. Wallace1,3, Indrajeet Chaubey1,4, Dennis C. Flanagan1,3, Lawrence O. Theller1, Bernard A. Engel1
1Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, USA
2Key Laboratory of Environment and Disaster Monitoring and Evaluation, Hubei, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, People’s Republic of China
3USDA-Agricultural Research Service, West Lafayette, USA
4Department of Earth, Atmospheric and Planetary Sciences, Purdue University, West Lafayette, USA

Tóm tắt

Nhiều mô hình máy tính, từ đơn giản đến phức tạp, đã được phát triển để mô phỏng thủy văn và chất lượng nước ở các quy mô từ đồng ruộng đến lưu vực. Tuy nhiên, nhiều người sử dụng vẫn chưa chắc chắn nên chọn mô hình nào khi ước lượng các điều kiện về số lượng và chất lượng nước trong một lưu vực. Nghiên cứu này đã so sánh các mô hình thủy văn/chất lượng nước bao gồm Công cụ bảng tính để ước lượng tải lượng ô nhiễm (STEPL)-Purdue, Công cụ Đánh giá Nước và Đất (SWAT), Tập trung cao độ (HIT), Đánh giá Tác động Thủy văn Dài hạn (L-THIA), Tải lượng ô nhiễm (PLOAD), Mô hình phân bố không gian và thời gian cho Quản lý Phospho (STEM-P), Khu vực 5, và mô hình tổng hợp (sử dụng STEPL-Purdue, SWAT, L-THIA, PLOAD, và STEM-P). Năng lực mô hình, đầu vào, và các phương pháp cơ bản để ước lượng lưu lượng dòng chảy, dòng chảy mặt, dòng chảy nền, dinh dưỡng, và trầm tích đã được xem xét. Các đầu ra không được hiệu chỉnh, đã được hiệu chỉnh, và đã được xác thực của các mô hình này và mô hình tổng hợp không hiệu chỉnh trong việc ước lượng số lượng và chất lượng nước cho một lưu vực nông nghiệp rộng 41,5 km2 ở miền Đông Bắc Indiana đã được khám phá, và các khuyến nghị đã được đưa ra về việc lựa chọn và sử dụng các mô hình. Các mô hình cần được chọn một cách cẩn thận dựa trên các mục tiêu mô phỏng, sự sẵn có của dữ liệu, đặc điểm của mô hình, ràng buộc về thời gian, và ngân sách dự án.

Từ khóa

#mô hình máy tính #thủy văn #chất lượng nước #lưu vực nông nghiệp #mô phỏng

Tài liệu tham khảo

Abbaspour K, Vejdani M, Haghighat S, Oxley L, Kulasiri D (2007) SWAT-CUP calibration and uncertainty programs for SWAT. Modsim 2007: International Congress on Modelling and Simulation 1603-1609 Ahiablame L, Engel BA, Chaubey I (2012) Representation and evaluation of low impact development practices with L-THIA-LID: an example for site planning. Environ Pollut 1(2) Arnold JG, Allen PM (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records1. J Am Water Resour As 35(2):411–424 Azamathulla HM (2012) Linear programming for irrigation scheduling-a case study (book chapter). Linear programming: new frontiers in theory and applications 174–192 Azmi M, Sarmadi F (2015) Dynamic modelling of water resources sustainable development using a mathematical approach. KSCE J Civ Eng 19(6):1675 Bhaduri B, Minner M, Tatalovich S, Harbor J (2001) Long-term hydrologic impact of urbanization: a tale of two models. J Water Res Pl-ASCE 127(1):13–19 Chen J, Theller L, Gitau MW, Engel BA, Harbor JM (2017) Urbanization impacts on surface runoff of the contiguous United States. J Environ Manag 187:470–481 Coffey ME, Workman SR, Taraba JL, Fogle AW (2004) Statistical procedures for evaluating daily and monthly hydrologic model predictions. T ASAE 47(1):59 Diodato N, Guerriero L, Fiorillo F, Esposito L, Revellino P, Grelle G, Guadagno FM (2014) Predicting monthly spring discharges using a simple statistical model. Water Resour Manag 28(4):969–978 Duan Q, Gupta HV, Sorooshian S, Rousseau AN, Turcotte R (2003) Calibration of watershed models. Am Geophys Union 6:1–345 Duan Q, Ajami NK, Gao X, Sorooshian S (2007) Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv Water Resour 30(5):1371–1386 Engel BA, Choi JY, Harbor J, Pandey S (2003) Web-based DSS for hydrologic impact evaluation of small watershed land use changes. Comput Electron Agr 39:241–249 Foster GR, McCool DK, Renard KG, Moldenhauer WC (1981) Conversion of the universal soil loss equation to SI metric units. J Soil Water Conserv 36(6):355–359 Fraser R (1999) SEDMOD: a GIS-based delivery model for diffuse source pollutants (doctoral dissertation). Yale University Ghavidelfar S, Alvankar SR, Razmkhah A (2011) Comparison of the lumped and quasi-distributed Clark runoff models in simulating flood hydrographs on a semi-arid watershed. Water Resour Manag 25(6):1775–1790 Gitau MW, Chen J, Ma Z (2016) Water quality indices as tools for decision making and management. Water Resour Manag 30(8):2591–2610 Harbor J (1994) A practical method for estimating the impact of land use change on surface runoff, groundwater recharge and wetland hydrology. J Am Plan Assoc 60:91–104 Jones PG, Thornton PK (2013) Generating downscaled weather data from a suite of climate models for agricultural modelling applications. Agric Syst 114:1–5 Laouacheria F, Mansouri R (2015) Comparison of WBNM and HEC-HMS for runoff hydrograph prediction in a small urban catchment. Water Resour Manag 29(8):2485–2501 Li S, Zhang L, Gitau M, Engel BA, Liu HB, Flanagan D (2017) Development of a spatially and temporally distributed hydrological and phosphorus model to facilitate non-point source pollution control. Department of Agricultural and Biological Engineering Report. Purdue University, West Lafayette, IN Liu Y, Ahiablame LM, Bralts VF, Engel BA (2015a) Enhancing a rainfall-runoff model to assess the impacts of BMPs and LID practices on storm runoff. J Environ Manag 147:12–23 Liu Y, Bralts VF, Engel BA (2015b) Evaluating the effectiveness of management practices on hydrology and water quality at watershed scale with a rainfall-runoff model. Sci Total Environ 511:298–308 Liu Y, Chaubey I, Bowling LC, Bralts VF, Engel BA (2016a) Sensitivity and uncertainty analysis of the L-THIA-LID 2.1 model. Water Resour Manag 30(13):4927–4949 Liu Y, Cibin R, Bralts VF, Chaubey I, Bowling LC, Engel BA (2016b) Optimal selection and placement of BMPs and LID practices with a rainfall-runoff model. Environ Modell Softw 80:281–296 Liu Y, Theller LO, Pijanowski BC, Engel BA (2016c) Optimal selection and placement of green infrastructure to reduce impacts of land use change and climate change on hydrology and water quality: An application to the Trail Creek Watershed, Indiana. Sci Total Environ 553:149–163 MDEQ (Michigan Department of Environmental Quality) (1999) Pollutants controlled calculation and documentation for section 319 watersheds training manual. Lansing Mishra SK, Singh VP (2004) Long-term hydrological simulation based on the soil conservation Service curve number. Hydrol Process 18(7):1291–1313 Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. T ASABE 50(3):885–900 Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute, College Station NRC (National Research Council) (2001) Assessing the TMDL approach to water quality management. National Research Council, Washington, D.C. Osei-Twumasi A, Falconer RA, Bockelmann-Evans BN (2015) Experimental studies on water and solute transport processes in a hydraulic model of the Severn estuary, UK. Water Resour Manag 29(6):1731–1748 Ouyang D, Bartholic J, Selegean J (2005) Assessing sediment loading from agricultural croplands in the Great Lakes Basin. J Am Sci 1(2):14–21 Ouyang Y, Xu D, Leininger TD, Zhang N (2016) A system dynamic model to estimate hydrological processes and water use in a eucalypt plantation. Ecol Eng 86:290–299 Park YS (2014) Development and enhancement of web-based tools to develop Total maximum daily load (Doctoral dissertation, PURDUE UNIVERSITY) PLOAD (2001) PLOAD version 3.0: an ArcView GIS tool to calculate nonpoint sources of pollution in watershed and stormwater projects, User’s manual. U.S. Environmental Protection Agency, Washington, D.C. Renard K, Foster G, Weesies G, McCool D, Yoder D (1996) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). USDA, agriculture handbook number 703 Runkel RR, Crawford CG, Cohn TA (2004) Load Estimator (LOADEST): a Fortran program for estimating constituent loads in streams and rivers. Techniques and methods book 4, chapter A5. US Geological Survey, Reston Schueler T (1987) Controlling urban runoff: a practical manual for planning and designing urban BMPs. Metropolitan Washington Council of Governments, Washington, D.C. Shi P, Chen C, Srinivasan R, Zhang X, Cai T, Fang X, Qu S, Chen X, Li Q (2011) Evaluating the SWAT model for hydrological modeling in the Xixian watershed and a comparison with the XAJ model. Water Resour Manag 25(10):2595–2612 Spruill C, Workman S, Taraba J (2000) Simulation of daily and monthly stream discharge from small watersheds using the SWAT model. T ASAE 43(6):1431–1439 Tetra Tech, Inc (2011) User’s guide spreadsheet tool for the estimation of pollutant load (STEPL) version 4.1. Tetra Tech, Inc, Fairfax Thiessen AH (1911) Precipitation averages for large areas. Mon Weather Rev 39(7):1082–1089 Turner BL, Menendez HM, Gates R, Tedeschi LO, Atzori AS (2016) System dynamics modeling for agricultural and natural resource management issues: review of some past cases and forecasting future roles. Resour 5(4):40 USEPA (United States Environmental Protection Agency) (2001) PLOAD version 3.0, an ArcView GIS tool to calculate nonpoint sources of pollution in watershed and Stormwater projects, User’s Manual Viney NR, Bormann H, Breuer L, Bronstert A, Croke BFW, Frede H, Gräff T, Hubrechts L, Huisman JA, Jakeman AJ, Kite GW (2009) Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: ensemble combinations and predictions. Adv Water Resour 32(2):147–158 Wang R, Bowling LC, Cherkauer KA, Cibin R, Her Y, Chaubey I (2017) Biophysical and hydrological effects of future climate change including trends in CO2, in the St. Joseph River watershed, Eastern Corn Belt. Agr Water Manage 180:280–296 Wang R, Kalin L, Kuang W, Tian H (2014) Individual and combined effects of land use/cover and climate change on Wolf Bay watershed streamflow in southern Alabama. Hydrol Process 28(22):5530–5546 White KL, Chaubey I (2005) Sensitivity analysis, calibration, and validations for a multisite and multivariable swat model. J Am Water Resour Assoc 41:1077–1089 Wright TJ, Liu Y, Carroll NJ, Ahiablame LM, Engel BA (2016) Retrofitting LID practices into existing neighborhoods: is it worth it? Environ Manag 57(4):856–867 Zahiri A, Azamathulla HM, Ghorbani K (2014) Prediction of local scour depth downstream of bed sills using soft computing models. In computational intelligence techniques in earth and environmental Sciences. Springer, Netherlands, pp 197–208