Abstract
To improve management and conservation in ungauged catchments in northern Iran, we developed regional models to predict annual runoff and discharge using multi-year time series from 20 gauged catchments in Ardabil, Province. We employed correlation, Ward cluster analysis, and principal component analysis to reduce the total parameter set (69 parameters represent catchment geometry, geology, soil, rainfall, and climate) to robust sets for regression analysis. The reduction method based on PCA using non-log-transformed data produced the best results, based on several error metrics (modified Nash Sutcliffe efficiency, R2, root mean squared error, and bias). Important parameters included area and mean annual precipitation, as well as those indicative of catchment shape and geology. Despite excellent ability to simulate mean annual discharge and sediment yield in the 20 catchments, the models performed poorly when applied to estimating year-to-year discharge and sediment yield in individual catchments. Poor prediction likely resulted from (a) rainfall data of insufficient spatial resolution in the large area with greatly varying elevation including mountains; and (b) inability to include data reflecting yearly changes in land-cover/land-use. Nevertheless, the regional models are likely useful for estimating mean runoff and sediment yields in other catchments in the region with similar geology, geomorphology, and climate.
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Al-Alawi SM, Abdul-Wahab SA, Bakheit CS (2008) Combining principal component regression and artificial neural networks for more accurate predictions of ground-level ozone. Environ Model Softw 23:396–403
Andrews SS, Mitchell JP, Mancinelli R, Karlen DL, Hartz TK, Howarth WR, Pettygrove GS, Scow KM, Munk DS (2002) On-farm assessment of soil quality in California’s Central Valley. Agron J 94:12–23
Barbarossa V, Huijbregts MAJ, Hendriks AJ, Beusen AHW, Clavreul J, King H, Schipper AM (2017) Developing and testing a global-scale regression model to quantify mean annual streamflow. J Hydrol 544:479–487
Choubin B, Solaimani K, Habibnejad Roshan M, Malekian A (2017) Watershed classification by remote sensing indices: a fuzzy c-means clustering approach. J Mt Sci 14(10):2053–2063
Efron B (1982) The jackknife, the bootstrap, and other resampling plans (vol 38). Siam, Philadelphia
Esmali Ouri A, Ghorbani A (2011) Factors controlling suspended sediment yield from catchments in central Ardabil Province. Iran Afr J Agric Res 6(22):5112–5122
Farmer WH, Vogel RM (2013) Performance-weighted methods for estimating monthly streamflow at ungauged sites. J Hydrol 477:240–250
Feiznia S (1995) Rocks strength against erosion factors in different climates of Iran. J Nat Resour Iran 47:95–116
Fernandez W, Vogel RM, Sankarasubramanian A (2000) Regional calibration of a watershed model. Hydrol Sci J 45(5):689–707
Fournier F (1960) Climate and erosion. University of Paris, Paris
France SL, Vaghefi MS, Batchelder WH (2018) FlexCCT: a methodological framework and software for ratings analysis and wisdom of the crowd applications. IEEE Trans Comput Soc Syst 5(2):358–370
Galindo JAG, Valbuena JAG (2018) Caracterización hidrológica de 10 puntos de monitoreo del Río Cauca en su cuenca baja
Ghosh J, Porchelvan P (2018) Relationship between surface temperature and land cover types using thermal infrared band and NDVI for Vellore District, Tamilnadu, India. Nat Environ Pollut Technol 17(2):611–617
Gotzinger J, Bardossy A (2007) Comparison of four regionalisation methods for a distributed hydrological model. J Hydrol 333(2):374–384
Gyawali R, Griffis VW, Watkins DW, Fennessey NM (2015) Regional regression models for hydro-climate change impact assessment. Hydrol Process 29(8):1972–1985
Hair JE Jr, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Printice Hall, Upper Saddle River
Halim R, Clemente RS, Routray JK, Shrestha RP (2007) Integration of biophysical and socio-economic factors to assess soil erosion hazard in the Upper Kaligarang Watershed, Indonesia. Land Degrad Dev 18(4):453–469
Heng S, Suetsugi T (2013) An approach to the model use for measuring suspended sediment yield in ungauged catchments. Am J Environ Sci 9(4):367–376
Heuvelmans G, Muys B, Feyen J (2006) Regionalisation of the parameters of a hydrological model: comparison of linear regression models with artificial neural nets. J Hydrol 319(1):245–265
Isik S (2013) Regional rating curve models of suspended sediment transport for Turkey. Earth Sci Inform 6:87–98
Jafarian Z, Kargar M, Ghorbani J (2013) Comparison of soil physical and chemical properties in grassland and shrub land communities, Iran. Commun Soil Sci Plant Anal 44(1–4):331–338
Jahanshahi A, Golshan M, Afzali A (2017) Simulation of the catchments hydrological processes in arid, semi-arid and semi-humid areas. Desert 22(1):1–10
Jamab Consulting Engineering Company, JCEC (2003) The comprehensive studies project of water resources in Ardabil province
James LD (1972) Hydrologic modeling, parameter estimation and watershed characteristics. J Hydrol 17:283–307
Javan K, Lialestani MRFH, Nejadhossein M (2015) A comparison of ANN and HSPF models for runoff simulation in Gharehsoo River watershed, Iran. Model Earth Syst Environ 1(4):41
Jemberu W, Baartman J, Fleskens L, Selassie Y, Ritsema C (2018) Magnitudes and dynamics of runoff and sediment yield: an extensive analysis of hydrological responses of three sub-watersheds in the Ethiopian highlands. EGU Gen Assem Conf Abstr 20:2957
Jorenoosh MH, Sepaskhah AR (2018) Prediction of frost occurrence by estimating daily minimum temperature in semi-arid areas in Iran. Iran Agricultural Research, Karaj
Kachigan SK (1991) Multivariate statistical analysis: a conceptual introduction, 2nd edn. Radius Press, New York
Kavian A, Mohammadi M, Gholami L, Rodrigo–comino J (2018) Assessment of the spatiotemporal effects of land use changes on runoff and nitrate loads in the Talar River. Water 10(445):1–19. https://doi.org/10.3390/w10040445
Kebede Gurmessa T, Bárdossy A (2009) A principal component regression approach to simulate the bed-evolution of reservoirs. J Hydrol 368:30–41
Kheirfam H, Vafakhah M (2015) Assessment of some homogeneous methods for the regional analysis of suspended sediment yield in the south and southeast of the Caspian Sea. J Earth Syst Sci 124:1247–1263
Khoshravan H, Nasehi F (2015) Pollutants hazard potential and environmental vulnerability of Qarah Su River. J Appl Hydrol 2(1):31–37
Kokkonen TS, Jakeman AJ, Young PC, Koivusalo HJ (2003) Predicting daily flows in ungauged catchments: Model regionalization from catchment descriptors at the Coweeta Hydrologic Laboratory, North Carolina. Hydrol Process 17:2219–2238
Magette WL, Shanholtz VO, Carr JC (1976) Estimating selected parameters for the Kentucky Watershed Model from watershed characteristics. Water Resour Res 12:472–476
Melesse AM, Ahmad S, McClain ME, Wang X, Lim YH (2011) Suspended sediment load prediction of river systems: an artificial neural network approach. Agric Water Manag 98:855–866
Merz R, Blöschl G (2004) Regionalisation of catchment model parameters. J Hydrol 287:95–123
Moeini A, Zarandi NK, Pazira E, Badiollahi Y (2015) The relationship between drainage density and soil erosion rate: a study of five watersheds in Ardebil Province, Iran. WIT Trans Ecol Environ 197:129–138
Murtagh F, Legendre P (2014) Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? J Classif 31(3):274–295
Mwakalila S (2003) Estimation of stream flows of ungauged catchments for river basin management. Phys Chem Earth 28:935–942
Nemati A, Sedghi M, Sharifi RS, Seiedi MN (2009) Investigation of correlation between traits and path analysis of corn (Zea mays L.) grain yield at the climate of Ardabil region (Northwest Iran). Notulae Botanicae Horti Agrobotanici Cluj-Napoca 37(1):194
O'Neill MA, Denos M, Reed D (2018) Using SDS–PAGE gel fingerprinting to identify soft-bodied wood-boring insect larvae to species. Pest Manag Sci 74(3):705–714
Pazhouhesh M, Gorji M, Taheri SM, Keshavarzi A (2011) Determination of soil erodibility factor using fuzzy rule base system. Int J Environ Sci 1:1874–1883
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 267:1117–1123
Restrepo JD, Kjerfve B, Hermelin M, Restrepo JC (2006) Factors controlling sediment yield in a major South American drainage basin: the Magdalena River, Colombia. J Hydrol 316:213–232
Sadat-Noori SM, Ebrahimi K, Liaghat AM (2014) Groundwater quality assessment using the Water Quality Index and GIS in Saveh-Nobaran aquifer, Iran. Environ Earth Sci 71:3827–3843
Sadeghi SHR, Singh JK (2005) Development of a synthetic sediment graph using hydrological data. J Agric Sci Technol (JAST) 7:69–77
Sassolas-Serrayet T, Cattin R, Ferry M (2018) The shape of watersheds. Nat Commun 9(1):3791
Sellami H, La Jeunesse I, Benabdallah S, Baghdadi N, Vanclooster M (2014) Uncertainty analysis in model parameters regionalization: a case study involving the SWAT model in Mediterranean catchments (Southern France). Hydrol Earth Syst Sci 18:2393
Shahriar G (2015) Assessing ecological power in natural habitat of Cerasus avium in northern forest of Iran. Bul Teknol Tanaman Bil 12:138–149
Solaimani K (2009) Flood forecasting based on geographical information system. Afr J Agric Res 4(10):950–956
Syvitski JPM, Milliman JD (2007) Geography and humans battle for dominance over the delivery of fluvial sediment to the coastal ocean. J Geol 115:1–19
Tayfur G, Karimi Y, Singh VP (2013) Principle component analysis in conjuction with data driven methods for sediment load prediction. Water Resour Manag 27:2541–2554
Velasque MCS, Biudes MS, Machado NG, de Morais Danelichen VH, Vourlitis GL, de Souza Nogueira J (2018) Modeling gross primary production of tropical forest by remote sensing. Revista Brasileira de Climatologia 22:38–54
Vogel R (2005) Regional calibration of watershed models. In: Singh V, Frevert D (eds) Watershed models. CRC Press, Baco Raton, pp 47–71
Vousoughi FD, Dinpashoh Y, Aalami MT, Jhajharia D (2013) Trend analysis of groundwater using non-parametric methods (case study: Ardabil plain). Stoch Environ Res Risk Assess 27(2):547–559
Walling DE, Fang D (2003) Recent trends in the suspended sediment loads of the world’s rivers. Glob Planet Change 39:111–126
Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58:236–244
Warrick JA, Melack JM, Goodridge BM (2015) Sediment yields from small, steep coastal watersheds of California. J Hydrol Reg Stud 4:516–534
Wuttichaikitcharoen P, Babel MS (2014) Principal component and multiple regression analyses for the estimation of suspended sediment yield in ungauged basins of northern Thailand. Water 6(8):2412–2435
Xu CY (2003) Testing the transferability of regression equations derived from small sub-catchments to a large area in central Sweden. Hydrol Earth Syst Sci 7:317–324
Zeyaeyan S, Fattahi E, Ranjbar A, Vazifedoust M (2017) Classification of rainfall warnings based on the TOPSIS method. Climate 5(2):33
Ziegler AD, Sidle RC, Phang VX, Wood SH, Tantasirin C (2014) Bedload transport in SE Asian streams—uncertainties and implications for reservoir management. Geomorphology 227:31–48
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Golshan, M., Kavian, A., Esmali, A. et al. Runoff and sediment yield modeling in data-sparse catchments in the Garehsoo River basin, northern Iran. Environ Earth Sci 79, 351 (2020). https://doi.org/10.1007/s12665-020-09084-2
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DOI: https://doi.org/10.1007/s12665-020-09084-2