علوم و مهندسی آبیاری

علوم و مهندسی آبیاری

بررسی تأثیر استراتژی‌های مختلف کوددهی بر روی میزان نیترات خروجی شبکه آبیاری با استفاده از مدل SWAT (مطالعه موردی: شبکه آبیاری و زهکشی دز)

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکتری آبیاری و زهکشی، گروه آبیاری و زهکشی، دانشکده مهندسی آب و محیط زیست، دانشگاه شهید چمران اهواز، اهواز، ،ایران.
2 استاد، گروه آبیاری وزهکشی، دانشکده مهندسی آب و محیط زیست، دانشگاه شهید چمران اهواز، اهواز، ایران.
3 دانشیار ، گروه آبیاری و زهکشی، دانشکده مهندسی آب و محیط زیست، دانشگاه شهید چمران اهواز، اهواز، ایران.
4 استاد، گروه آبیاری و زهکشی، دانشکده مهندسی آب و محیط زیست ، دانشگاه شهید چمران اهواز، اهواز، ایران.
5 استاد گروه مهندسی آب، دانشگاه علوم کشاورزی و منابع طبیعی ساری ساری ایران.
چکیده
افزایش جمعیت و تقاضا مستلزم بالا بردن میزان تولید در واحد سطح است. رقابت برای افزایش عملکرد موجب استفاده‌ی بیش‌ازحد از کودهای شیمیایی شده است. مصرف بی‌رویه کودهای شیمیایی و تخلیه زهاب اراضی کشاورزی حاوی این ترکیبات منجر به آلودگی منابع آب می‌شود. لذا در پژوهش حاضر تأثیر استراتژی‌های مختلف کوددهی بر میزان نیترات خروجی در شبکه آبیاری و زهکشی رودخانه دز با استفاده از مدل SWAT مورد بررسی قرار گرفت. واسنجی و اعتبارسنجی مدل برای شبیه‌سازی میزان نیترات با استفاده از داده‌های آماری سال‌های 1995 تا 2017 در خروجی شبکه (ایستگاه بامدژ) صورت گرفت. برای
دست­یابی به اهداف مطالعه حاضر اطلاعات مربوط به مدیریت کشاورزی منطقه شامل الگوی کشت و تاریخ کاشت و برداشت، میزان و زمان آبیاری و میزان کود دهی براساس اطلاعات دریافتی برای سطح حوضه مورد مطالعه وارد مدل شد. به‌منظور ارزیابی تأثیر میزان کود دهی بر کیفیت آب‌های سطحی سناریوهای کاهش میزان کود دهی به مدل معرفی شد. نتایج حاصل از ارزیابی مدل با استفاده از ضرایب
R2 و NSE نشان دهنده عملکرد مناسب مدل در شبیه‌سازی پارامترهای مذکور می‎باشد. نتایج حاصل از اعمال سناریوهای کاهش کوددهی نشان داد با اعمال 10، 20، 30، 40، 50، 60 و 70 درصد کاهش کوددهی، نیترات به­ترتیب به میزان 74/2، 31/9، 25/11، 83/14، 95/17، 23/21 و 62/26  کاهش یافت. مطابق یافته های این تحقیق می توان گفت با توجه به تأثیر بالای کود دهی، با کنترل میزان کود مصرفی می‌توان تا حدود زیادی آلودگی منابع آب سطحی را کنترل نمود.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Studying the effect of different fertilization strategies on the output nitrate of irrigation network using SWAT model (Case study: Dez irrigation and drainage network)

نویسندگان English

Abbas Bakhtiarifar 1
Mohmmad Albaji 2
Mona Golabi 3
Saeid Boroomandnasab 4
Ali Shahnazari 5
1 PhD. Student of irrigation and drainage, Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz , Ahvaz, Iran
2 Professor, Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, ,Ahvaz, Iran,
3 Associate Professor, Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
4 Professor, Department of Irrigation and Drainage, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
5 Professor of Water Engineering Department, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran.
چکیده English

Increasing population and demand require increasing production per unit area. Competition for increased yield has led to excessive use of chemical fertilizers. Excessive use of chemical fertilizers and discharge of agricultural land drainage containing these compounds leads to pollution of water resources. Therefore, in the present study, the effect of different fertilization strategies on the amount of nitrate output in the irrigation and drainage network of the Dez River was investigated using the SWAT model. The calibration and validation of the model to simulate the amount of nitrate was carried out using statistical data from 1995 to 2017 at the network outlet (Bamdej station). To achieve the objectives of the present study, information related to the agricultural management of the region, including cropping pattern and planting and harvesting dates, irrigation rate and time, and fertilization rate, were entered into the model based on the information received for the study basin level. In order to evaluate the effect of fertilization rate on surface water quality, scenarios for reducing fertilization rate were introduced into the model. The results of model evaluation using R2 and NSE coefficients indicate the appropriate performance of the model in simulating the mentioned parameters. The results of applying fertilizer reduction scenarios showed that by applying 10, 20, 30, 40, 50, 60 and 70 percent reduction in fertilizer, nitrate was reduced by 2.74, 9.31, 11.25, 14.83, 17.95, 21.23 and 26.62, respectively. According to the findings of this study, it can be said that due to the high impact of fertilization, by controlling the amount of fertilizer used, pollution of surface water resources can be controlled to a large extent

کلیدواژه‌ها English

Simulation
SWAT
Fertilization Scenario
Agriculture
Water Resources Pollution
  • Ababei, B. and T. Sohrabi., 2009. Assessing the performance of SWAT model in Zayandeh Rud Watershed. Journal of Water and Soil Conservation, 16(3): 41-58. DOI: 1001.1.23222069.1388.16.3.3.7 (In Persian).

 

2- Abbaspour K.C., Yang ,J., Maximov, I., Siber, R.,  Bogner, K., Mieleitner, J., Zobrist, J. and Srinivasan, R., 2007. Modelling hydrology and water quality in theprealpine/alpineThur watershed using SWAT, Journal of Hydrology 333: 413– 430. DOI:10.1016/j.jhydrol.2006.09.014.

3- Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H. and Klove, B., 2015. A continentalscale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. Journal of Hydrology. 524: 733–752. DOI:10.1016/j.jhydrol.2015.03.027

 

4- Ahmadzadeh, H., Murid, S. and Delaver, M., 2013. Evaluation of changes in the performance of agricultural products and input to Lake Urmia in the Zarinerood basin under the influence of changing irrigation systems from surface to pressurized using the SWAT model. Journal of Irrigation and Drainage of Iran, 8(1): 1-15. DOI: 20.1001.1.20081758.1400.17.2.3.1

 

5- Akhavan, S., Abedi, j., Mosavi, S, F., Abbaspour, K., Afyoni, M. and Eslamian, S., 2010. Estimation of "blue water" and "green water" using SWAT model in Hamadan-Bahar watershed. Water and soil Sciences (agricultural sciences and techniques and natural resources), 14(53): 9-23. DOI: 10.22067/geo.v8i3.81998 (In Persian).  

 

6- Akhavan, S. and Jodi Hameze Abad, A., 2015. Simulation of Inflow to Urmia Lake Using SWAT Model. Journal of Water and Soil Science, 19(72): 23-34. DOI: 10.18869/acadpub.jstnar.19.72.3 (In Persian).

 

7- Albaji, M., 2010. Land suitability evaluation for sprinkler irrigation systems. Khuzestan Water and Power Authority (KWPA), Ahwaz, Iran (in Persian), 14(3), pp.16-25.

 

8- Annual report of Khuzestan Water and Electricity Organization, 2016.  Exploitation of irrigation networks in North Khuzestan region, KWPA Technical Rep, p13

 

9- Arnold, J. G., Srinivasan, R., Muttiah, R. S. and Williams, J. R., 1998. Large area hydrologic modeling and assessment part 1: model development. American Water Resources Association.volume 34, 73–89. DOI:10.1111/j.1752-1688.1998.tb05961.x.

 

10- Basaltpour, A. and Hosseinzadeh, N., 2016. Theory & training step by step construction and implementation of SWAT model. Valiasr University of Rafsanja. (In Persian).

 

11- Bindra, S.P., Lawafi, A., Abulifa, S. and Gouma, M., 2014. Change and Development in Biological Civil & Environmental Engineering Education in Libya. International Conference on Biological, Civil and Environmental Engineering (BCEE-2014) March 17-18, 2014 Dubai (UAE). DOI:10.15242//LLCBE.C0314079

 

12- Gassman, P.W., Reyes, M. R., Green, C. H. and Arnold, J. G. 2007. The soil and water assessment tool historical development, applications, and future research directions. American Society of Agricultural and Biological Engineers 50(4), 1211–1250. DOI: 10.13031/2013.23637

 

13- Giri, S., Qiu, Z., Prato, T. and Luo, B., 2016. An integrated approach for targeting critical source areas to control nonpoint source pollution in watersheds. Water Resour Management. Volume 30, 5087–5100. DOI: 10.1007/s11269-016-1470-z

 

14- Jingyuan, J., Shiyu, L., Jiatang, H. and Huang, J., 2014 .A modeling approach to evaluating the impacts of policy-induced land management practices on non-point source pollution: A case study of the Liuxi River watershed, China. Agricultural Water Management Volume 131:1-16. DOI: 10.1016/j.agwat.2013.09.005

 

15- Li S., Li J., Xia J. and Hao G., 2021. Optimal control of nonpoint source pollution in the Bahe River Basin, Northwest China, based on the SWAT model. Environmental Science and Pollution Research, DOI: 10.1007/s11356-021-14869-4

 

16- Misaghi, F. and Nouri, M., 2017. Simulating the amount of nitrate entering the river from agricultural land using the SWAT model (case study: Zanjan River). Iran Water Resources Research, 14(2): 155-168. DOI: 10.22104/AET.2020.4298.1214 (In Persian (

 

17- Mohammadi, M., Kavian, a. and Gholmi, L., 2017. Simulation of discharge and water nitrate in Talar watershed using SWAT model. Watershed Management Research Journal, 8(15):45-60.  DOI: 10.29252/jwmr.8.15.45

 

18- Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D. and Veith, T. L., 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. 50(3): 885-900. DOI: 10.13031/2013.23153

 

19- Naseri, A.A., Albaji, M., Boroomand Nasab, S., Landi, A., Papan, P., Bavi, A.2009. Land suitability evaluation for principal crops in the Abbas Plain, Southwest Iran. Journal of Food, Agriculture & Environment.7 (1): 208-213. DOI: https://doi.org/10.1234/4.2009.1502

 

20- Nash, J. and Sutcliffe, J., 1970. River flow forecasting through conceptual models: Part 1. A discussion of principles. Journal of Hydrology, 10, 282‐290. DOI: 10.1016/0022-1694(70)90255-6

 

21- Nazari-Sharabian, M., Taheriyoun, M., Ahmad, S., Karakouzian, M. and A. Ahmadi., 2019. Water quality modeling of Mahabad Dam watershed–reservoir system under climate change conditions, using SWAT and system dynamics. Water 2019, 11, 394. DOI: 10.3390/w11020394.

 

22- Neitsch, S.L., Arnold, J.G., Kiniry, J.R. and Williams, J.R., 2011. Soil and Water Assessment Tool Theoretical Decumention version 2009 (user, manual). Texas Water Resources Institute, 647 pp. DOI: 10.4236/jwarp.2010.25047

 

23-Nouri, Z., Selajqa, A., Malekian, A. and Moghadamniac, A., 2016. Investigating the effect of the best management measures in reducing point and non-point sources of water pollution using the SWAT model (case study: Simre watershed, Simre river). - Iran Water and Soil Research, Volume 48, Number 5, Bahman and Esfand 99-106. DOI: 10.22059/ijswr.2018.225610.667617 (In Persian (.

 

24- Qiang, W and YuSchilling, H., 2021. Identifying critical source areas of nonpoint source pollution in a watershed with SWAT–ECM and AHP methods. Hydrology Research,.52)6(, 1184 DOI: 10.2166/nh.2021.010.

 

25- Schilling, K. E. and Wolter, C.F., 2009. Modeling nitrate-nitrogen load reduction strategies for the Des Moines River, Iowa Using SWAT. Environmental Management, 44 (4), 671–682. DOI: 10.1007/s00267-009-9364-y

 

26- Sheikhi Grakoui, K., Navabian, M., Vazifeh Dost, M., 2017. Investigating the accuracy of salinity simulation using heavy metals and nitrogen cycle in SWAT model (case study: Navroud watershed). Iran Water and Soil Research, 94)1(: 25-37. DOI: 10.22059/ijswr.2017.207586.667467. (In Persian).

 

27- Sheikh Zainuddin, A., Esmaili, A. K. and M. Sebet., 2015. Policy incentives to reduce nitrate leaching in agricultural fields: the study area of Drudzen irrigation and drainage network. Agricultural Economics and Development, 30(2): 127-135. DOI: 10.22067/jead2.v30i2.40451

 

28-. The United Nations World Water Development Report 2021, Published in 2021 by the United Nations Educational, Scientific and Cultural Organization, 7, place de Fontenoy, 75352 Paris 07 SP, France

 

29- Wu, Q and Yu, H., 2021. Identifying critical source areas of nonpoint source pollution in a watershed with SWAT–ECM and AHP methods. Hydrology Research, 52(6), 1184 DOI: 10.2166/nh.2021.010

 

30- Zarei Gorkhodi, A., Shahnazari, A. and F. Mohammadi., 2022. Evaluating the effect of dams on two parameters of runoff and sediment using SWAT model (case study: Tejn River watershed, Mazandaran). Iran Irrigation and Drainage Journal, 16(2): 294-307. DOI: 20.1001.1.20087942.1401.16.2.3.2 (In Persian).

31- Zhang, X. and Zhang, M., 2011. Modeling effectiveness of agricultural BMPs to reduce sediment load and organophosphate pesticides in surface runoff. Journal of Science of the Total Environment, 409(10):1949-1958. DOI: 10.1016/j.scitotenv.2011.02.012.

دوره 49، شماره 2
تابستان 1405
صفحه 73-88

  • تاریخ دریافت 21 تیر 1403
  • تاریخ بازنگری 10 مهر 1403
  • تاریخ پذیرش 06 آبان 1403
  • تاریخ انتشار 14 مرداد 1405