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Evaluation of the predictive reliability of a new watershed health assessment method using the SWAT model

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Abstract

The purpose of watershed assessments is to give information about conditions of water quality, stream morphology, and biological integrity to identify the sources of stressors and their impacts. In recent decades, different watershed assessment methods have been developed to evaluate the cumulative impacts of human activities on watershed health and the condition of aquatic systems. In the current research, we propose a new approach for assessing watershed vulnerability to contamination based on spatial analysis by using geographic information systems (GIS) and the analytic hierarchy process (AHP) technique. This new procedure, designed to identify vulnerable zones, depends on six basic factors that represent watershed characteristics: land use/land cover, soil type, average annual precipitation, slope, depth to groundwater, and bedrock type. The general assumptions for assessing watershed vulnerability are based on the response of watersheds to different contamination impacts and how the six selected factors interact to affect watershed health. The new watershed vulnerability assessment technique was used to create maps showing the relative vulnerabilities of specific sub-watersheds in the Eagle Creek Watershed in central Indiana. The results showed a remarkable difference in watershed susceptibility between the sub-watersheds in their vulnerability to pollution. To test the reliability of the proposed vulnerability assessment technique, the SWAT (Soil and Water Assessment Tool) model was applied to predict the water quality in each sub-watershed. Using the SWAT model, some parameters (e.g., total suspended solids [TSS] and nitrate) were tested based on the availability of the data needed for comparison. Both the SWAT and the newly proposed method produced good results in predicting water quality loads, which validated the proposed method. Hence, the results of the evaluation of the predictive reliability of the watershed vulnerability assessment method revealed that the proposed approach is suitable as a decision-making tool to predict watershed health.

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References

  • Abbaspour, K.C., 2015. SWAT-CUP: SWAT calibration and uncertainty programs – a user manual. https://swat.tamu.edu/media/114860/usermanual_swatcup.pdf (accessed 11 Mar 2019).

  • Abbaspour, K., Vaghefi, S., & Srinivasan, R. (2017). A guideline for successful calibration and uncertainty analysis for soil and water assessment: a review of papers from the 2016 international SWAT Conference. Water, 10(1), 6. https://doi.org/10.3390/w10010006.

    Article  Google Scholar 

  • Adams, S., Titus, R., Pietersen, K., Tredoux, G., & Harris, C. (2001). Hydrochemical characteristics of aquifers near Sutherland in the Western Karoo, South Africa. Journal of Hydrology, 241(1–2), 91–103. https://doi.org/10.1016/s0022-1694(00)00370-x.

    Article  CAS  Google Scholar 

  • Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., & Jha, M. K. (2012). SWAT: model use, calibration, and validation. Transactions of the ASABE, 55(4), 1491–1508.

    Google Scholar 

  • Arnold, J. G., Youssef, M. A., Yen, H., White, M. J., Sheshukov, A. Y., et al. (2015). Hydrological processes and model representation: impact of soft data on calibration. Transactions of the ASABE, 58(6), 1637–1660.

    CAS  Google Scholar 

  • Bai, J., Shen, Z., Yan, T., Qiu, J., & Li, Y. (2017). Predicting fecal coliform using the interval-to-interval approach and SWAT in the Miyun watershed, China. Environmental Science and Pollution Research, 24(18), 15462–15470.

    Google Scholar 

  • Bakker, M. M., Govers, G., Van Doorn, A., Quetier, F., Chouvardas, D., & Rounsevell, M. (2008). The response of soil erosion and sediment export to land-use change in four areas of Europe: the importance of landscape pattern. Geomorphology., 98(3–4), 213–226.

    Google Scholar 

  • Bannwarth, M., Sangchan, W., Hugenschmidt, C., Lamers, M., Ingwersen, J., Ziegler, A., & Streck, T. (2014). Pesticide transport simulation in a tropical catchment by SWAT. Environmental Pollution, 191, 70–79. https://doi.org/10.1016/j.envpol.2014.04.011.

    Article  CAS  Google Scholar 

  • Bateni, F., Fakheran, S., & Soffianian, A. (2013). Assessment of land cover changes & water quality changes in the Zayandehroud River Basin between 1997–2008. Environmental Monitoring and Assessment, 185(12), 10511–10519.

    CAS  Google Scholar 

  • Behera, S., & Panda, R. (2006). Evaluation of management alternatives for an agricultural watershed in a sub-humid subtropical region using a physical process based model. Agriculture, Ecosystems and Environment, 113(1–4), 62–72. https://doi.org/10.1016/j.agee.2005.08.032.

    Article  Google Scholar 

  • Blanchard, P. E., & Lerch, R. N. (2000). Watershed vulnerability to losses of agricultural chemicals: interactions of chemistry, hydrology, and land-use. Environmental Science & Technology, 34(16), 3315–3322.

    CAS  Google Scholar 

  • Boithias, L., Sauvage, S., Srinivasan, R., Leccia, O., & Sánchez-Pérez, J. (2014). Application date as a controlling factor of pesticide transfers to surface water during runoff events. CATENA, 119, 97–103.

    CAS  Google Scholar 

  • Bracken, L. J., & Croke, J. (2007). The concept of hydrological connectivity and its contribution to understanding runoff-dominated geomorphic systems. Hydrological Processes, 21(13), 1749–1763.

    Google Scholar 

  • Brainwood, M., Burgin, S., & Maheshwari, B. (2004). Temporal variations in water quality of farm dams: impacts of land use and water sources. Agricultural Water Management, 70(2), 151–175.

    Google Scholar 

  • Brunner, P., Cook, P. G., & Simmons, C. T. (2009). Hydrogeologic controls on disconnection between surface water and groundwater. Water Resources Research, 45(1). https://doi.org/10.1029/2008wr006953.

  • Calijuri, M. L., Castro, J. D., Costa, L. S., Assemany, P. P., & Alves, J. E. (2015). Impact of land use/land cover changes on water quality and hydrological behavior of an agricultural subwatershed. Environment and Earth Science, 74(6), 5373–5382.

    Google Scholar 

  • Carey, R. O., Migliaccio, K. W., Li, Y., Schaffer, B., Kiker, G. A., & Brown, M. T. (2011). Land use disturbance indicators and water quality variability in the Biscayne Bay Watershed, Florida. Ecological Indicators, 11(5), 1093–1104.

    CAS  Google Scholar 

  • Chang, X., Meyer, M. T., Liu, X., Zhao, Q., Chen, H., Chen, J., & Shu, W. (2010). Determination of antibiotics in sewage from hospitals, nursery and slaughter house, wastewater treatment plant and source water in Chongqing region of Three Gorge Reservoir in China. Environmental Pollution, 158(5), 1444–1450.

    CAS  Google Scholar 

  • Chhabra, R. (1996). Soil salinity and water quality. London: Routledge.

    Google Scholar 

  • Cho, K. H., Pachepsky, Y. A., Kim, J. H., Kim, J., & Park, M. (2012). The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA. Water Research, 46(15), 4750–4760.

    CAS  Google Scholar 

  • Daly, C., 1996. Overview of the PRISM model, PRISM climate map** program. http://www.ocs.orst.edu/prism/ prism_new.html (accessed 18 March 1999).

  • Deshmukh, A., & Singh, R. (2016). Physio-climatic controls on vulnerability of watersheds to climate and land use change across the U.S. Water Resources Research, 52(11), 8775–8793.

    Google Scholar 

  • Driscoll, C., Whitall, D., Aber, J., Boyer, E., Castro, M., & Cronan, C. (2003). Nitrogen pollution in the northeastern United States: Sources, effects, and management options. BioScience, 53(4), 357. https://doi.org/10.1641/0006-3568(2003)053[0357:npitnu]2.0.co;2.

    Article  Google Scholar 

  • Eimers, J. L., Weaver, J. C., Terziotti, S., Midgette, R. W. 2000. Methods of rating unsaturated zone and watershed characteristics of public water supplies in North Carolina. Raleigh, NC: U.S. Dept. of the Interior, U.S. Geological Survey.

  • El Kateb, H., Zhang, H., Zhang, P., & Mosandl, R. (2013). Soil erosion and surface runoff on different vegetation covers and slope gradients: a field experiment in Southern Shaanxi Province, China. CATENA, 105, 1–10. https://doi.org/10.1016/j.catena.2012.12.012.

    Article  Google Scholar 

  • Fan, M., & Shibata, H. (2015). Simulation of watershed hydrology and stream water quality under land use and climate change scenarios in Teshio River watershed, northern Japan. Ecological Indicators, 50, 79–89. https://doi.org/10.1016/j.ecolind.2014.11.003.

    Article  CAS  Google Scholar 

  • Fox, D., Bryan, R., & Price, A. (1997). The influence of slope angle on final infiltration rate for interrill conditions. Geoderma, 80(1–2), 181–194.

    Google Scholar 

  • Furniss, M.J., Roby, KB., Cenderelli, D., Chatel, J., Clifton, C.F., Clingenpeel, A., Weinhold, M., 2013. Assessing the vulnerability of watersheds to climate change: results of national forest watershed vulnerability pilot assessments. doi:https://doi.org/10.2737/pnw-gtr-884.

  • Gassman, P. W., Reyes, M. R., Green, C. H., & Arnold, J. G. (2007). The Soil and Water Assessment Tool: historical development, applications, and future research directions. Transactions of the ASABE, 50(4), 1211–1250.

    CAS  Google Scholar 

  • Göbel, P., Dierkes, C., & Coldewey, W. (2007). Storm water runoff concentration matrix for urban areas. Journal of Contaminant Hydrology, 91(1–2), 26–42. https://doi.org/10.1016/j.jconhyd.2006.08.008.

    Article  CAS  Google Scholar 

  • Govender, M., & Everson, C. S. (2005). Modelling streamflow from two small South African experimental catchments using the SWAT model. Hydrological Processes, 19(3), 683–692.

    Google Scholar 

  • Gray, H. H., Ault, C. H., & Keller, S. J. (1987). Bedrock geologic map of Indiana. Indiana Geological Survey, Miscellaneous Map, 48 scale 1:500,000.

  • Hall, R. D. (1999). Geology of Indiana (2nd ed.) IUPUI Department of Geology and Center for Earth and Environmental Science and Department of Geology.

    Google Scholar 

  • Hanson, L., Habicht, S., Daggupati, P., Srinivasan, R., & Faeth, P. (2017). Modeling changes to streamflow, sediment, and nutrient loading from land use changes due to potential natural gas development. JAWRA., 53(6), 1293–1312.

    CAS  Google Scholar 

  • Hazbavi, Z., & Sadeghi, S. H. (2017). Watershed health characterization using reliability-resilience-vulnerability conceptual framework based on hydrological responses. Land Degradation and Development, 28(5), 1528–1537.

    Google Scholar 

  • Heathman, G., Flanagan, D., Larose, M., & Zuercher, B. (2008). Application of the Soil and Water Assessment Tool and annualized agricultural non-point source models in the St. Joseph River Watershed. Journal of Soil and Water Conservation, 63(6), 552–568.

    Google Scholar 

  • Heathwaite, A. L., & Johnes, P. J. (1996). Contribution of nitrogen species and phosphorus fractions to stream water quality in agricultural catchments. Hydrological Processes, 10(7), 971–983.

    Google Scholar 

  • Herman, M. R., & Nejadhashemi, A. P. (2015). A review of macroinvertebrate- and fish-based stream health indices. Ecohydrology and Hydrobiology, 15(2), 53–67.

    Google Scholar 

  • Hoang, L., Van Griensven, A., Van der Keur, P., Refsgaard, J. C., Troldborg, L., Nilsson, B., & Mynett, A. (2014). Comparison and evaluation of model structures for the simulation of pollution fluxes in a tile-drained river basin. Journal of Environmental Quality, 43(1), 86–99. https://doi.org/10.2134/jeq2011.0398.

    Article  CAS  Google Scholar 

  • Homer, C. G., Dewitz, J. A., Yang, L., **, S., Danielson, P., **an, G., Coulston, J., et al. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States-representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354.

    Google Scholar 

  • Im, S., Brannan, K. M., Mostaghimi, S., & Kim, S. M. (2007). Comparison of HSPF and SWAT models performance for runoff and sediment yield prediction. Journal of Environmental Science and Health, Part A, 42(11), 1561–1570.

    CAS  Google Scholar 

  • Jabbar, F. K., & Grote, K. (2018). Statistical assessment of nonpoint source pollution in agricultural watersheds in the Lower Grand River watershed, MO, USA. Environmental Science and Pollution Research, 26(2), 1487–1506. https://doi.org/10.1007/s11356-018-3682-7.

    Article  CAS  Google Scholar 

  • Jang, W. S., Engel, B., & Ryu, J. (2018). Efficient flow calibration method for accurate estimation of baseflow using a watershed scale hydrological model (SWAT). Ecological Engineering, 125, 50–67. https://doi.org/10.1016/j.ecoleng.2018.10.007.

    Article  Google Scholar 

  • Johnson, T. E., Butcher, J. B., Parker, A., & Weaver, C. P. (2012). Investigating the sensitivity of U.S. streamflow and water quality to climate change: U.S. EPA Global Change Research Program’s 20 Watersheds Project. Journal of Water Resources Planning and Management, 138(5), 453–464.

    Google Scholar 

  • Jones, K. B., Neale, A. C., Nash, M. S., van Remortel, R. D., Wickham, J. D., Riitters, K. H., & O’Neill, R. V. (2001). Predicting nutrient and sediment loadings to streams from landscape metrics: a multiple watershed study from the United States Mid-Atlantic region. Landscape Ecology, 16(4), 301–312.

    Google Scholar 

  • Jun, K. S., Chung, E., Sung, J., & Lee, K. S. (2011). Development of spatial water resources vulnerability index considering climate change impacts. Science of The Total Environment, 409(24), 5228–5242.

    CAS  Google Scholar 

  • Kim, J., & An, K. (2015). Integrated ecological river health assessments, based on water chemistry, physical habitat quality and biological integrity. Water, 7(11), 6378–6403.

    CAS  Google Scholar 

  • Kim, G., Yur, J., & Kim, J. (2007). Diffuse pollution loading from urban stormwater runoff in Daejeon City, Korea. Journal of Environmental Management, 85(1), 9–16.

    CAS  Google Scholar 

  • Kundu, D., Van Ogtrop, F. F., & Vervoort, R. W. (2016). Identifying model consistency through stepwise calibration to capture streamflow variability. Environmental Modelling and Software, 84, 1–17.

    Google Scholar 

  • Laurent, F., & Ruelland, D. (2011). Assessing impacts of alternative land use and agricultural practices on nitrate pollution at the catchment scale. Journal of Hydrology, 409(1–2), 440–450.

    CAS  Google Scholar 

  • Lehr, C., Pöschke, F., Lewandowski, J., & Lischeid, G. (2015). A novel method to evaluate the effect of a stream restoration on the spatial pattern of hydraulic connection of stream and groundwater. Journal of Hydrology, 527, 394–401.

    CAS  Google Scholar 

  • Lenhart, C. F., Verry, E. S., Brooks, K. N., & Magner, J. A. (2011). Adjustment of prairie pothole streams to land-use, drainage and climate changes and consequences for turbidity impairment. River Research and Applications, 28(10), 1609–1619.

    Google Scholar 

  • Liu, Y., Yang, W., Yu, Z., Lung, I., & Gharabaghi, B. (2015). Estimating sediment yield from upland and channel erosion at a watershed scale using SWAT. Water Resources Management, 29(5), 1399–1412.

    Google Scholar 

  • Lopez, R. D., Nash, M. S., Heggem, D. T., & Ebert, D. W. (2008). Watershed vulnerability predictions for the Ozarks using landscape models. Journal of Environmental Quality, 37(5), 1769.

    CAS  Google Scholar 

  • Luo, Y., & Zhang, M. (2009). Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT. Environmental Pollution, 157(12), 3370–3378.

    CAS  Google Scholar 

  • Luo, Y., Ficklin, D. L., Liu, X., & Zhang, M. (2013). Assessment of climate change impacts on hydrology and water quality with a watershed modeling approach. Science of The Total Environment, 450–451, 72–82.

    Google Scholar 

  • Ma, X., Li, Y., Zhang, M., Zheng, F., & Du, S. (2011). Assessment and analysis of non-point source nitrogen and phosphorus loads in the Three Gorges Reservoir Area of Hubei Province, China. Science of The Total Environment, 412–413, 154–161.

    Google Scholar 

  • Malagó, A., Bouraoui, F., Vigiak, O., Grizzetti, B., & Pastori, M. (2017). Modelling water and nutrient fluxes in the Danube River Basin with SWAT. Science of The Total Environment, 603–604, 196–218.

    Google Scholar 

  • Mano, V., Nemery, J., Belleudy, P., & Poirel, A. (2009). Assessment of suspended sediment transport in four alpine watersheds (France): influence of the climatic regime. Hydrological Processes, 23(5), 777–792.

    Google Scholar 

  • Marcarelli, A. M., Kirk, R. W., & Baxter, C. V. (2010). Predicting effects of hydrologic alteration and climate change on ecosystem metabolism in a western U.S. river. Ecological Applications, 20(8), 2081–2088.

    Google Scholar 

  • Meierdiercks, K. L., Kolozsvary, M. B., Rhoads, K. P., Golden, M., & McCloskey, N. F. (2017). The role of land surface versus drainage network characteristics in controlling water quality and quantity in a small urban watershed. Hydrological Processes, 31(24), 4384–4397.

    Google Scholar 

  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Binger, R. L., Harmel, R. D., & Veith, T. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885–900. https://doi.org/10.13031/2013.23153.

    Article  Google Scholar 

  • Neitsch, S.L., Arnold, J.G., Kiniry, J.R.,Williams, J.R., 2011. Soil and Water Assessment Tool theoretical documentation: Version 2009. USDA–ARS, Grassland, Soil and Water Research Laboratory, Temple, TX; and Blackland Research and Extension Center, Texas AgriLife Research, Temple, TX. Texas Water Resources Institute Technical Rep. 406, Texas A&M University System, College Station, TX.

  • Neupane, R. P., & Kumar, S. (2015). Estimating the effects of potential climate and land use changes on hydrologic processes of a large agriculture dominated watershed. Journal of Hydrology, 529, 418–429. https://doi.org/10.1016/j.jhydrol.2015.07.050.

    Article  Google Scholar 

  • Olsen, R. L., Chappell, R. W., & Loftis, J. C. (2012). Water quality sample collection, data treatment and results presentation for principal components analysis – literature review and Illinois River Watershed case study. Water Research, 46(9), 3110–3122. https://doi.org/10.1016/j.watres.2012.03.028.

    Article  CAS  Google Scholar 

  • Peraza-Castro, M., Ruiz-Romera, E., Meaurio, M., Sauvage, S., & Sánchez-Pérez, J. (2018). Modelling the impact of climate and land cover change on hydrology and water quality in a forest watershed in the Basque Country (Northern Spain). Ecological Engineering, 122, 315–326. https://doi.org/10.1016/j.ecoleng.2018.07.016.

    Article  Google Scholar 

  • Pyron, M., & Neumann, K. (2008). Hydrologic alterations in the Wabash River Watershed, USA. River Research and Applications, 24(8), 1175–1184. https://doi.org/10.1002/rra.1155.

    Article  Google Scholar 

  • Rai, P. K., Dhanya, C. T., & Chahar, B. R. (2018). Coupling of 1D models (SWAT and SWMM) with 2D model (iRIC) for map** inundation in Brahmani and Baitarani river delta. Natural Hazards, 92(3), 1821–1840. https://doi.org/10.1007/s11069-018-3281-4.

    Article  Google Scholar 

  • Rodgers, K. S., Kido, M. H., Jokiel, P. L., Edmonds, T., & Brown, E. K. (2012). Use of integrated landscape indicators to evaluate the health of linked watersheds and coral reef environments in the Hawaiian islands. Environmental Management, 50(1), 21–30. https://doi.org/10.1007/s00267-012-9867-9.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy processes. New York: McGraw-Hill.

    Google Scholar 

  • Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Science and Technology, 1(1), 83–98.

    Google Scholar 

  • Schilling, K. E., & Spooner, J. (2006). Effects of watershed-scale land use change on stream nitrate concentrations. Journal of Environmental Quality, 35(6), 2132–2145. https://doi.org/10.2134/jeq2006.0157.

    Article  CAS  Google Scholar 

  • Schuol, J., Abbaspour, K. C., Srinivasan, R., & Yang, H. (2008). Estimation of freshwater availability in the West African sub-continent using the SWAT hydrologic model. Journal of Hydrology, 352(1–2), 30–49. https://doi.org/10.1016/j.jhydrol.2007.12.025.

    Article  Google Scholar 

  • Setegn, S. G., Srinivasan, R., & Dargahi, B. (2008). Hydrological modelling in the Lake Tana Basin, Ethiopia using SWAT model. The Open Hydrology Journal, 2(1), 49–62. https://doi.org/10.2174/1874378100802010049.

    Article  Google Scholar 

  • Shaver, R. H., Ault, C. H., Burger, A. M., Carr, D. D., Droste, J. B., Eggert, D. L., Gray, H. H., et al. (1986). Compendium of rock-unit stratigraphy in Indiana; a revision. IGS, 59.

  • Singh, A. K., Mondal, G. C., Singh, P. K., Singh, S., Singh, T. B., & Tewary, B. K. (2005). Hydrochemistry of reservoirs of Damodar River Basin, India: Weathering processes and water quality assessment. Environmental Geology, 48(8), 1014–1028. https://doi.org/10.1007/s00254-005-1302-6.

    Article  CAS  Google Scholar 

  • Tedesco, L. P., Pascual, D. L., Shrake, L. K., Hall, R. E., Casey, L. R., Vidon, P. G. F., Hernly, F. V., et al. (2005). Eagle Creek Watershed Management Plan: an integrated approach to improved water quality. In Eagle Creek watershed Alliance, CEES publication 2005–07. Indianapolis: IUPUI http://www.cees.iupui.edu.

    Google Scholar 

  • Teshager, A. D., Gassman, P. W., Secchi, S., Schoof, J. T., & Misgna, G. (2015). Modeling agricultural watersheds with the Soil and Water Assessment Tool (SWAT): calibration and validation with a novel procedure for spatially explicit HRUs. Environmental Management, 57(4), 894–911. https://doi.org/10.1007/s00267-015-0636-4.

    Article  Google Scholar 

  • Tiner, R. W. (2004). Remotely-sensed indicators for monitoring the general condition of “natural habitat” in watersheds: an application for Delaware’s Nanticoke River watershed. Ecological Indicators, 4(4), 227–243. https://doi.org/10.1016/j.ecolind.2004.04.002.

    Article  Google Scholar 

  • Tran, L. T., Knight, C. G., O'Neill, R. V., & Smith, E. R. (2004). Integrated environmental assessment of the Mid-Atlantic region with analytical network process. Environmental Monitoring and Assessment, 94(1–3), 263–277. https://doi.org/10.1023/b:emas.0000016893.77348.67.

    Article  Google Scholar 

  • USDA – SCS 1972. National Engineering Handbook, Section 4: Hydrology, Chapters 4–10, United States Department of Agriculture – Soil Conservation Service, Washington, DC.

  • USGS 2016. USGS Watershed Boundary Dataset (WBD) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) Watershed Boundary Dataset (WBD): U.S. Geological Survey - National Geospatial Technical Operations Center (NGTOC).

  • Varanka, S., Hjort, J., & Luoto, M. (2014). Geomorphological factors predict water quality in boreal rivers. Earth Surface Processes and Landforms, 40(15), 1989–1999. https://doi.org/10.1002/esp.3601.

    Article  Google Scholar 

  • Vilaysane, B., Takara, K., Luo, P., Akkharath, I., & Duan, W. (2015). Hydrological stream flow modelling for calibration and uncertainty analysis using SWAT model in the Xedone river basin, Lao PDR. Procedia Environmental Science, 28, 380–390.

    Google Scholar 

  • Walter, J., Chesnaux, R., Cloutier, V., & Gaboury, D. (2017). The influence of water/rock − water/clay interactions and mixing in the salinization processes of groundwater. Journal of Hydrology: Regional Studies, 13, 168–188.

    Google Scholar 

  • Wilson, C., & Weng, Q. (2010). Assessing surface water quality and its relation with urban land cover changes in the Lake Calumet area, Greater Chicago. Environmental Management, 45(5), 1096–1111. https://doi.org/10.1007/s00267-010-9482-6.

    Article  Google Scholar 

  • Xu, Z. X., Pang, J. P., Liu, C. M., & Li, J. Y. (2009). Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model. Hydrological Processes, 23(25), 3619–3630. https://doi.org/10.1002/hyp.7475.

    Article  Google Scholar 

  • Yen, H., Bailey, R. T., Arabi, M., Ahmadi, M., White, M. J., & Arnold, J. G. (2014). The role of interior watershed processes in improving parameter estimation and performance of watershed models. Journal of Environmental Quality, 43(5), 1601. https://doi.org/10.2134/jeq2013.03.0110.

    Article  CAS  Google Scholar 

  • Zhang, X., Srinivasan, R., & Bosch, D. (2009). Calibration and uncertainty analysis of the SWAT model using genetic algorithms and Bayesian model averaging. Journal of Hydrology, 374(3–4), 307–317.

    Google Scholar 

  • Zhu, C., & Li, Y. (2014). Long-term hydrological impacts of land use/land cover change from 1984 to 2010 in the Little River watershed, Tennessee. International Soil and Water Conservation Research, 2(2), 11–21. https://doi.org/10.1016/s2095-6339(15)30002-2.

    Article  Google Scholar 

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Acknowledgments

The authors would like to express our appreciation to the Ministry of Higher Education and Scientific Research and the Ministry of Water Resources in Iraq for their support.

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  1. Department of Geosciences and Geological and Petroleum Engineering, Missouri University of Science and Technology, McNutt Hall, 1400 N. Bishop Ave, Rolla, MO, 65401, USA

    Fadhil K. Jabbar & Katherine Grote

  2. College of Science, University of Misan, Amarah, Iraq

    Fadhil K. Jabbar

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  1. Fadhil K. Jabbar
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Jabbar, F.K., Grote, K. Evaluation of the predictive reliability of a new watershed health assessment method using the SWAT model. Environ Monit Assess 192, 224 (2020). https://doi.org/10.1007/s10661-020-8182-9

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