Abstract
In this contribution, the authors present their preliminary investigations into modeling the rainfall–runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system.
Highlights
Introduction and MotivationThe Jiulong River (JLR) runs 258 km through a subtropical catchment situated at 24.2–25.8◦N, 117–118◦ E in Fujian Province, on the southeast coast of China (Figure 1), covering an area of14,700 km2
The JLR consists of two major branches: North Stream (Bei’Xi) and West Stream (Xi’Xi)
The RR method (1) seems to be more susceptible to systematic of streamflow) than Hydrological Simulation Program-Fortran (HSPF); (2) fails to produce realistic hourly runoff, whilst HSPF does not have this biases (~10% underestimation of streamflow) than HSPF; (2) fails to produce realistic hourly runoff, problem, as it is physically based; (3) has regression coefficients and systematic bias characteristics whilst HSPF does not have this problem, as it is physically based; (3) has regression coefficients and that may not be stationary over time, so it is not suitable for scenario studies
Summary
Introduction and MotivationThe Jiulong River (JLR) runs 258 km through a subtropical catchment situated at 24.2–25.8◦N, 117–118◦ E in Fujian Province, on the southeast coast of China (Figure 1), covering an area of14,700 km. The Jiulong River (JLR) runs 258 km through a subtropical catchment situated at 24.2–25.8◦. N, 117–118◦ E in Fujian Province, on the southeast coast of China (Figure 1), covering an area of. The JLR consists of two major branches: North Stream (Bei’Xi) and West Stream (Xi’Xi). The annual average runoff of the catchment is 1.2 × 1010 m3 , with over two-thirds of the total runoff contributed by the North Stream. The catchment shows significant intra-annual unevenness in precipitation, as approximately 70% of the total runoff occurs during April–September due to Atmosphere 2019, 10, 62; doi:10.3390/atmos10020062 www.mdpi.com/journal/atmosphere. Atmosphere 2019, 10, 62 typhoon and tropical storm events. The catchment is largely rural, where over 60% of the total area is Atmosphere 2018, 9, [1].
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