| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 3,019 |
| تعداد مقالات | 33,734 |
| تعداد مشاهده مقاله | 44,973,079 |
| تعداد دریافت فایل اصل مقاله | 46,413,444 |
ارزیابی روش‌های برآورد نسبت تحویل رسوب در حوزه آبخیز معرف-زوجی خامسان | ||
| مهندسی و مدیریت آبخیز | ||
| مقاله 5، دوره 16، شماره 3، مهر 1403، صفحه 394-414 اصل مقاله (1.32 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijwmse.2024.358084.1965 | ||
| نویسندگان | ||
| نسرین اعظمی1؛ عبدالواحد خالدی درویشان* 2؛ لیلا غلامی3 | ||
| 1دانش‌‌آموخته کارشناسی ارشد، گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور، ایران | ||
| 2دانشیار، گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور، ایران | ||
| 3دانشیار، گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران | ||
| چکیده | ||
| مقدمه فرسایش خاک، به‌طور خاص و تخریب خاک، به‌طور عام در نتیجه فعالیت انسان، امروزه به‌عنوان یک معضل اجتماعی مطرح بوده و نقش عامل انسانی در پیدایش و تسریع روند تخریب خاک در بسیاری از مناطق روشن شده است. دستیابی به آمار و اطلاعات دقیق در مورد میزان فرسایش خاک و رسوب در حوزه‌های آبخیز به‌منظور اجرای برنامه‌های حفاظت خاک و تعیین روش‌های مبارزه با فرسایش خاک و کاهش تولید رسوب ضروری است. به‌دلیل کمبود آمار در زمینه فرسایش خاک و تولید رسوب در بسیاری از حوزه‌های آبخیز کشور، به‌کارگیری روش‌های تجربی مناسب برای برآورد فرسایش، رسوب‌دهی و به‌ویژه نسبت تحویل رسوب اجتناب‌ناپذیر است. مواد و روش بدین منظور در پژوهش حاضر از مدل‌های برآورد نسبت تحویل رسوب شامل مدل‌های تجربی مبتنی بر متغیرهای زودیافت و سه مدل SATEEC، InVEST و WaTEM/SEDEM در حوزه آبخیز معرف-زوجی خامسان در غرب ایران استفاده شد. مدل WaTEM/SEDEM در بخش WaTEM برای برآورد فرسایش خاک مبتنی بر مدل RUSLE و در بخش SEDEM مبتنی بر عملکرد عوامل فیزیکی مؤثر در رابطه انتقال رسوب است. در بسیاری از منابع از روش سزیم-137 به‌عنوان تنها روش موجود و قابل‌اعتماد برای اندازه‌گیری اجزای بودجه رسوب شامل فرسایش کل، رسوب‌گذاری کل، فرسایش خالص (رسوب‌دهی) و نسبت تحویل رسوب به‌ویژه در مقیاس دامنه و زیرحوزه آبخیز یاد شده است. برای ارزیابی مدل‌های مورداستفاده، از نتایج محاسبه نسبت تحویل رسوب در روش سزیم-137 حاصل پژوهش‌های قبلی استفاده شد که برای کل حوزه آبخیز و متوسط 15 زیرحوزه آبخیز به‌ترتیب برابر 25.61 و 58.94 درصد است و صحت آن با استفاده از داده‌های رسوب مشاهداتی در خروجی حوزه آبخیز مورد تأیید قرار گرفته است. نتایج و بحث از بین مدل‌های بررسی شده برای برآورد نسبت تحویل رسوب، مدل‌های Renfro and Waldo (1983)، Williams and Brendt (1962)، Roehl (1962)، با بارش مازاد یک ساعت، Walling (1983)، Ferro (1995)، Vanoni (1975) و USDA (1972)، در مقیاس کل حوزه آبخیز و مدل‌های Renfro (1975)، USDA (1972)، USDA-SCS (1979)، SATEEC and Roehl (1962)، با بارش مازاد یک ساعت در مقیاس زیرحوزه آبخیز نزدیک‌ترین برآوردها را به روش سزیم-137 با در نظر گرفتن خطای 10± درصد داشتند و به‌عنوان مدل‌های مناسب برای برآورد نسبت تحویل رسوب در حوزه آبخیز معرف-زوجی خامسان انتخاب شدند. همچنین، این مدل‌ها می‌توانند برای برآورد نسبت تحویل رسوب در حوزه‌های آبخیز مشابه با حوزه آبخیز معرف-زوجی خامسان نیز مورداستفاده قرار داده شوند. نتیجه‌‌گیری در مقیاس زیرحوزه آبخیزها برآوردهای معادلات مبتنی بر متغیرهای زودیافت جز روش Roehl (1962)-بارش مازاد 0.1 ساعت به‌طور معنی‌داری کمتر از مدل SATEEC بوده، از طرفی برآوردهای تمام روش‌های مذکور به‌جز روش Roehl (1962) بارش مازاد 0.1 ساعت به‌طور معنی‌داری بیشتر از مدل WaTEM/SEDEM و InVEST بود. این موضوع بر اهمیت در نظر گرفتن شرایط بارش مازاد برای برآورد نسبت تحویل رسوب در معادلات ارائه شده توسط Roehl تأکید دارد. همچنین، در مقیاس کل آبخیز نیز برآوردهای معادلات مبتنی بر متغیرهای زودیافت به‌جز روش Mutchler and Bowie (1975)، کمتر از نتایج مدل SATEEC بود. اختلاف زیاد عملکرد روش‌های مورد بررسی در دو مقیاس زیرحوزه آبخیز و کل حوزه آبخیز ناشی از اثر انکارناپذیر دشت میانی حوزه آبخیز خامسان در کاهش شدید انتقال رسوب زیرحوزه آبخیزها تا خروجی کل حوزه آبخیز بوده است. | ||
| کلیدواژه‌ها | ||
| سزیم-137؛ فرسایش خاک؛ مدل RUSLE؛ مدل InVEST؛ مدل SATEEC | ||
| عنوان مقاله [English] | ||
| Evaluation of sediment delivery ratio estimation methods in Khamsan Representative-Paired Watershed | ||
| نویسندگان [English] | ||
| Nasrin Azami1؛ Abdulvahed Khaledi Darvishan2؛ Leila Gholami3 | ||
| 1Former Master Student, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran | ||
| 2Associate professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran | ||
| 3Associate professor, Department of Watershed Management Engineering, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran | ||
| چکیده [English] | ||
| Introduction Today, soil erosion in particular and soil degradation in general as a result of human activities have been raised as a social problem, and the role of the human factor in the emergence and acceleration of the soil degradation process has been clarified in many fields. Obtaining accurate statistics and information about soil erosion and sediment yield in the watersheds is necessary for the implementation of soil conservation programs and methods for determining the resistance to soil erosion and reducing sediment yield. Due to the lack of data about soil erosion and sediment yield in many watersheds of Iran, the use of appropriate empirical methods is inevitable to erosion estimation, sediment yield and especially sediment delivery ratio. Martial and methods For this purpose, in the present study, empirical models for estimation of the sediment delivery ratio based on easy-to-measure variables and three models of SATEEC, InVEST and WaTEM/SEDEM were used in the Khamsan representative-paired watershed, western Iran. The WaTEM module of the WaTEM/SEDEM model is based on the RUSLE model for estimating soil erosion, and in the SEDEM module is based on the performance of effective physical factors in the sediment transport equation. In many sources, the 137Cs method is mentioned as the only available and reliable method for measuring the components of the sediment budget, including total erosion, total sedimentation, net erosion (sediment yield) and sediment delivery ratio, especially at the hillslope and sub-watershed scales. To evaluation of the used models, the results of calculating the sediment delivery ratio using the 137Cs method obtained from previous researches were used, which are 25.61% and 58.94% for the entire watershed and the average of 15 sub-watersheds, respectively, and its accuracy is based on the observed sediment data at the outlet of the watershed has been confirmed. Results and discussion Among the studied sediment delivery ratio models, Renfro and Waldo (1983), Williams and Brendt (1972), Roehl (1962) considering one hour excess precipitation, Walling (1983), Ferro (1995), Vanoni (1975) and USDA (1972) provided the closest estimates (±10%) to the 137Cs method for the whole watershed scale and the Renfro (1975), USDA (1972), USDA-SCS (1979), SATEEC and Roehl (1962) considering one hour excess precipitation for the sub-watershed scale provided the closest estimates (±10%) to the 137Cs method for the sub-watershed scale and were selected as suitable sediment delivery ratio models for Khamsan representative-paired watershed. Also, these models can be used to estimate the sediment delivery ratio in watersheds similar to Khamsan representative-paired watershed. Conclusion In the sub-watersheds scale, the equations estimations based on easy-to-measure variables except the Roehl (1962) method - excess rainfall of 1.0 h was significantly lower than the SATEEC model, on the other hand, the estimations of all the methods except the Roehl (1962) method - excess rainfall of 0.1 h was significantly higher than WaTEM/SEDEM and InVEST models. This issue emphasizes the importance of considering excess precipitation conditions to estimation of the sediment delivery ratio in the presented equations by Roehl. Also, at the scale of the whole watershed, the estimations of the equations based on easy-to-measure variables, except for the Mutchler and Bowie (1975) method, were lower than the results of the SATEEC model. The great difference of the investigated methods performance in the two scales of the sub-watershed and the whole watershed is due to the undeniable effect of the middle plain of the Khamsan watershed in the drastic reduction of the sediment transportation from the sub-watersheds to the outlet of the watershed. | ||
| کلیدواژه‌ها [English] | ||
| 137Cs, InVEST Model, RUSLE Model, SATEEC Model, Soil Erosion | ||
| مراجع | ||
|
Aneseyee, A.B., Elias, E., Soromessa, T., Feyisa, G.L., 2020. Land use/land cover change effect on soil erosion and sediment delivery in the Winike watershed, Omo Gibe Basin, Ethiopia. Sci. Total Environ. 728, 138776. Arnold, J.G., Williams, J.R., Srinivaasan, R., King, K.W., 1996. The soil and water assessment tool (SWAT) user? Manual. Temple, TX, PP. 560-572. Asadi Nalivan, O., Mohseni Saravi, M., Sour, A., Dastranj, A., Taei, S., 2013. Determine the most appropriate experimental method to estimate the SDR using EPM and physical properties basin, case study Watershed Ghurchay, Golestan Province. Irriga. Water Engineer. 3(2), 19-28 (in Persian). Asghari Srasknrod, S., FizolahPour, M., Mohammadnezhad Arvegh, V., 2013. Study of sediment delivery ratio (SDR) in Jajroad River Watershed. Quantita. Geomorpho. Res. 4(1), 67-78 (in Persian). Batista, P.V., Laceby, J.P., Davies, J., Carvalho, T.S., Tassinari, D., Silva, M.L., Curi, N., Quinton, J.N., 2021. A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data. Environ. Modell. Soft. 137, 104961. Bayat, R., Moradi, Sh., 2014. A review of research on sediment delivery ratio. Watershed Manage. Soci. Iran 2(5), 27-36 (in Persian). Behzadfar, A., Khaledi Darvishan, A., Gharagozlu, A., 2017. Increasing the accuracy of predicting sediment yield in watem/sedem model using image fusion algorithm, case study: Darkesh Watershed. J. Water Soil Resour. Conserv. 7(1), 99-112 (in Persian). Boyce, R.C., 1975. Sediment routing with sediment delivery ratios. In: Present and Prospective Technology for Predicting Sediment Yields and Sources. US Dept. Agric. Publ. ARS-S-40, 61-65. Cislaghi, A., Bischetti, G.B., 2019. Source areas, connectivity, and delivery rate of sediments in mountainous-forested hillslopes: A probabilistic approach. Sci. Total Environ. 652, 1168-1186. Damian, G., Năsui, D., Damian, F., Ciurte, D.L., 2014. Erosion assessment modeling using the SATEEC GIS model on the Prislop catchment. Present Environ. Sustain. Develop. 1, 217-224. Dercon, G., Mabit, L., Hancock, G., Nguyen, M.L., Dornhofer, P., Bacchi, O.O.S., Benmansour, M., Bernard, C., Froehlich, W., Golosov, V.N., Haciyakupoglu, S., Hai, P.S., Klik, A., Li, Y., Lobb, D.A., Onda, Y., Popa, N., Rafiq, M., Ritchie, J.C., Schuller, P., Shakhashiro, A., Wallbrink, P., Walling, D.E., Zapata, F., Zhang, X., 2012. Fallout radionuclide-based techniques for assessing the impact of soil conservation measures on erosion control and soil quality: an overview of the main lessons learnt under an FAO/IAEA Coordinated Research Project. Environ. Radioacti. 107, 78-85. Dreibrodt, S., Lubos, C., Terhorst, B., Damm, B., Bork, H.R., 2010. Historical soil erosion by water in Germany: Scales and archives, chronology, research perspectives. Quarter. Interna. 222(1-2), 80-95. Faraji, J., 2018. Etimating spatial variations of sedeiment delivery ratio in Khamsan Representative Watershed using WaTEM/SEDEM. MSc Thesis, 68 pages. Fernandez, C., Wu, J.Q., McCool D.K., Stockle, C.O., 2003. Estimating water erosion and sediment yield with GIS, RUSLE and SEDD. J. Soil Water Conserv. 58, 128-136. Ferro, V., Minacapillia, M., 1995. Sediment delivery processes at basin scale. Hydrol. Sci. J. 40(6), 703-718. Ferro, V., Porto, P., 2000, Sediment Delivery Distributed (SEDD) model. J. Hydrol. Engineer. 5(4), 633-647. Fu, G., Chen, S., McCool, D.K., 2006. Modeling the impacts of no-till practice on soil erosion and sediment yield with RUSLE, SEDD, and ArcView GIS. Soil Till. Res. 85(1-2), 38-49. Gaspar, L., Navas, A., Walling, D.E., Machín, J., Arozamena, J.G., 2013. Using 137Cs and 210Pbex to assess soil redistribution on slopes at different temporal scales. Catena 102, 46-54. Giguet-Covex, C., Arnaud, F., Poulenard, J., Disnar, J.R., Delhon, C., Francus, P., David, F., Enters, D., Rey, P.J., Delannoy, J.J., 2011. Changes in erosion patterns during the Holocene in a currently treeless subalpine catchment inferred from lake sediment geochemistry (Lake Anterne, 2063 m a.s.l., NW French Alps): The role of climate and human activities. The Holocene 21(4), 651-665. Glymph, L.M., 1954. Study of sediment yields from watersheds. In: Assemblée Générale de Rome 1954 Tome I, IAHS. Publ. No. 36, 173-191. Gubin, F., Shulin, C., Donald, K.M., 2005. Modeling the impacts of no-till practice on soil erosion and sediment yield with RUSLE, SEDD, and ArcView GIS. Soil Till. Res. 85(1-2), 36-49. Haan, C.T., Barfield, B.J., Hayes, J.C., 1994. Design hydrology and sedimentology for small catchments. Academic Press, INC., 588 pages. Hadley, R.F., Mizuyama, T., 1993. Sediment problems: Strategies for monitoring, prediction and control. Wallingford, Oxfordshire, UK, IAHS Publ. 217, 231-240. Hagos, D.B., 2004. A distributed sediment delivery ratio concept for sediment yield modelling. PhD Thesis, 133 pages. Hamel, P., Falinski, K., Sharp, R., Auerbach, D.A., Sánchez-Canale, M., Dennedy-Frank, P.J., 2017. Sediment delivery modeling in practice: Comparing the effects of watershed characteristics and data resolution across hydroclimatic regions. Sci, Total Environ. 580, 1381-1388. Hamel, P., Chaplin-Kramer, R., Sim, S., Mueller, C., 2015. A new approach to modeling the sediment retention service (InVEST 3.0): case study of the Cape Fear Catchment, North Carolina, USA. Sci. Total Environ. 524, 166-177. Javadi, M., Rahmati, S., Rangavar, A., 2017. Assessment of efficiency and accuracy of USLE and its versions for estimating event base sediment in the semi-arid rangelands, case study: Sanganeh Soil Conservation Research Institute of Mashhad. Watershed Manage. Rese. J. 30(1), 45-53. Kaffas, K., Pisinaras, V., Al Sayah, M.J., Santopietro, S., Righetti, M., 2021. A USLE-based model with modified LS-factor combined with sediment delivery module for Alpine basins. Catena 207, 105655. Karthikeya, M., Kumar, S.S., Reddy, S.B., 2018. Geospatial assessment of soil conservation impacts in musi project. Int. J. Res.Technol. 5(2), 83-87. Khaledi Darvishan, A., Faraji, J., Gholami, L., Khorsand, M., 2021. Spatio-temporal variation of soil erosion in Khamsan representative watershed using RUSLE. Watershed Engin, Manage. 13(3), 534-547 (in Persian). Kheirkhah, A., Nazarnezhad, H., 2013. Determination of Sediment Delivery Ratio (SDR) based on area-based models (case study: Gojar Watershed). Agricul. Edu. Promo. Res. Organiz. Period 1 (in Persian). Kinnell, P.I.A., 2006. Alternative approaches for determining the USLE-M slope length factor for grid cells. Soil Sci. Soci. Ameri. J. 69(3), 674-680. Kinsey-Henderson, A., Prosser, I., Post, D., 2003. SubNet–predicting sources of sediment at sub-catchment scale using SedNet. In: MODSIM Conference, Townsville, 590-595. Lai, R., Bium, W.H., Valentie, C., Stewart, B.A., 1998. Methods for assessment of soil degradation. Advance. Soil Sci. 558 pages. Lim, K.J., Sagong, M., Engel, B.A., Tang, Z., Choi, J., Kim, K.S., 2005. GIS-based sediment assessment tool. Catena 64, 61-80. Lu, H., Moran, C.J., Prosser, I.P., 2006. Modeling sediment delivery ratio over the murray darling basin. Environ. Modell. Soft. 21, 1297-1308. Lu, H., Moran, C.J., Prosser, I.P., Sivapalan, M., 2004. Modeling sediment delivery ratio based on physical principles. In Pahl-Wostl, C., Schmidt, S., Rizzoli, A.E., Jakeman, A.J., (eds) Complexity and Integrated Resources Management, vol 3. Trans. Second Bienn. Meeti. Internat. Environ. Model. Soft. Soci. Manno, 1117-1122. Lu, H., Raupach, M.R., McVicar, T.R., Barrett, D.J., 2003. Decomposition of vegetation cover into woody and herbaceous components using AVHRR NDVI time series. Remote Sens. Environ. 86(1), 1-18. Maner, S.B., 1958. Factors affecting sediment delivery rates in the Red Hills physiographic area. Eos, Trans. Ameri. Geophysi. Union 39(4), 669-675. Moore, I.D., Burch, G.J., 1986. Modeling erosion and deposition. Topographic Effects. Trans. Americ. Soci. Agricul. Enginee. 29, 1624-1630. Mutchler, A., Bowie, J., 1975. National engineering hand book, Section 3, Sedimentation. Mutua, B., Klik, A., 2004. Development of a physically based model for estimation of spatial sediment delivery ratio for large remote catchments. J. Spatial Hydrol. 5(1), 1-15. Nasri, M., Najafi, A., 2015. Determining mathematical relationship between sediment delivery ratio and Watershed Factors'. Nat. Ecosys. Iran 6(2), 1-12 (in Persian). Park, Y.S., Kim, J., Kim, N.W., Kim, S.J., Jeon, J.H., Engel, B.A.E., Jang, W., Lim, K.J., 2010. Development of new R, C and SDR modules for the SATEEC GIS system. Comput. Geoscie. 36(6), 726-734. Pimentel, D., Harvey, C., Resosudarmo, P., Sinclair, K., Kurz, D., McNair, M., Crist, S., Shpritz, L., Fitton, L., Saffouri, R., Blair, R., 1995. Environmental and economic costs of soil erosion and conservation benefits. Science, 267(5201), 1117-1123. Porto, P., Walling, D.E., 2012. Validating the use of 137Cs and 210Pbex measurements to estimate rates of soil loss from cultivated land in southern Italy. Environ. Radioacti. 106, 47-57. Rahman, M.R., Shi, Z.H., Chongfa, C., 2009. Soil erosion hazard evaluation-an integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecologi, Modell, 220(13), 1724-1734. Ramos-Scharron, C.E., MacDonald, L.H., 2007. Development and application of a GIS-based sediment budget model. J. Environ. Manage. 84, 157-172. Razali, N.M., Wah, Y.B., 2011. Power comparisons of Shapiro-Wilk, Kolmogorov Smirnov, Lilliefors and Anderson-Darling tests. J. Statisti. Model. Analyt. 2, 21-33. Renfro, G.W., 1975. User of erosion equation and sediment delivery ratio for predicting sediment yield. In present and prospective technology for predicting sediment yield and sources. Agricul. Resour. Servic. ARS, 33-45. Renfro, R., Waldo, P., 1983. Validations of sediment delivery ratio prediction techniques. Fort Worth TX: US Soil Conservation Service, Southern Reg. Tech. Ctr., 95 pages. Roehl, J.W., 1962. Sediment source areas, delivery ratios and influencing morphological factors. Inter, Associa. Sci. Hydrol. Commis. Land Erosion. Sadeghi, H.R., Gholami, L., Khaledi Darvishan, A., 2008. Comparison of sediment delivery ratio estimation methods in Chehelgazi Watershed of Gheshlagh Dam. Water Soil. 22(1), 141-150 (in Persian). Sánchez, Y., Martínez-Graña, A., Santos-Francés, F., Yenes, M., 2018. Influence of the sediment delivery ratio index on the analysis of silting and break risk in the Plasencia reservoir, central system, Spain. Nat. Hazard. 91(3), 1407-1421. Sedighi, F., Khaledi Darvishan, A., Zare, M., 2020. Assessment of the slop gradient on the estimated erosion and sediment delivery ratio by using 137Cs in the Khamsan Representative Watershed. Watershed Manage. Res. J. 33(3), 2-19 (in Persian). Sedighi, F., Khaledi Darvishan, A., Golosov, V., Zare, M.R., Spalevic, V., 2022. Influence of land use on changes of sediment budget components: western Iran case study. Turkish J. Agricul. Forest. 46(6), 838-851. Sedighi, F., Khaledi Darvishan, A., Zare, M.R., 2021. Effect of watershed geomorphological characteristics on sediment redistribution. Geomorphol. 375, 107559. Shahoei, S., Abdoulmalki, P., Najmedin, N., Shahoei, S., Tomarian, N., 1992. The relationship between erosion rate and factors during event. 3th Soil Sci. Conference Tehran, 41-56 (in Persian). Semgalawe, Z.M., Folmer, H., 2000. Household adoption behaviour of improved soil conservation: the case of the North Pare and West Usambara Mountains of Tanzania. Land Use Policy 17, 321-336. Tenge, A.J., Okoba, B.O., Sterk, G., 2007. Participatory soil and water conservation planning using a financial analysis tool in the West Usambara highlands of Tanzania. Land Degrad. Develop. 18(3), 321-337. USDA-SCS., 1979. Sediment sources, yields, and delivery ratios. National Engineering Handbook, Section 3, Sedimentation. USDA-SCS., 1981. Soil conservation service engineering handbook, Section 3, Sedimentation. Vanoni, V.A., 1975. Sedimentation engineering. Manuals and Reports on Engineering Practice No. 54. American Society of Civil Engineers, New York. Vigiak, O., Borselli, L., Newham, L.T.H., McInnes, J., Roberts, A.M., 2012. Comparison of conceptual landscape metrics of define hillslope-scale sediment delivery ratio. Geomorphol. 138(1), 74-88. Walling, D.E., 1983. The sediment delivery problem. J. Hydrol. 65(1-3), 209-237. Wilkinson, B.H., McElroy, B.J., 2007. The impact of humans on continental erosion and sedimentation. Geo. Soci. America Bull. 119(1-2), 140-156. Williams, J.R., Brendt, A.D., 1972. Sediment yield computed with the universal equation. American Soci. Civil Engineer. 98(HY12), 2087-2098. Williams, J.R., Berndt, H.D., 1977. Sediment yield prediction based on watershed hydrology. Trans. ASAE, 20(6), 1100-1104. Wu, L., Yao, W., Ma, X., 2018. Using the comprehensive governance degree to calibrate a piecewise sediment delivery ratio algorithm for dynamic sediment predictions: a case study in an ecological restoration watershed of northwest China. J. Hydrol. 564, 888-899. | ||
|
آمار تعداد مشاهده مقاله: 345 تعداد دریافت فایل اصل مقاله: 133 |
||