Comparative Water Environment Simulation Study of Two Typical Models with BMPs in a Karst Basin

Carbonate rocks are widely distributed in southwest China, forming a unique karst landscape. The Lijiang River Basin provides a typical example of an area with concentrated karst. Research on the laws of hydrology and water quality migration in the Lijiang River Basin is important for the management of the water resources of Guilin City and similar areas. In this study, we combined three meteorological data with the soil and water assessment tool (SWAT) model and the hydrological simulation program-Fortran (HSPF) model to simulate the hydrological and water quality processes in the Lijiang River Basin separately. We chose the Nash–Sutcliffe efficiency (NSE) coefficient, coefficient of determination (R2), root mean square error-observations standard deviation ratio (RSR), and mean absolute error (MAE) as the metrics used to evaluate the models. The results, combined with the time-series process lines, indicated that the SWAT model provides a more accurate performance than the HSPF model in streamflow, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) simulations. In addition, we divided the karst and non-karst areas, and we analyzed the differences between them in water balance, sediment transport, and pollution load. We further identified the key source areas of pollution load in the Lijiang River Basin, evaluated the pollution reduction effect of best management practices (BMPs) on surface source pollution, and proposed some pollution control countermeasures. Each scenario, especially returning farmland to forest and creating vegetation buffer zones, reduces the NH3-N and DO pollution load.

Hydrological Modeling of the Paligad Watershed (India) Using HSFP Model

For hydrological studies, it is well known that each hydrological system behaves differently and in order to effectively manage those systems, it is necessary to understand their behavior. The hydrological component of Hydrological Simulation Program – FORTRAN (HSPF) model was set up and calibrated for Paligad watershed which is a sub-basin of Aglar watershed in the Uttarakhand state of India. The calibration of the model was done manually and an expert advice system called as HSPEXP+ was used to aid calibration. The values of evaluation indicators such as coefficient of determination (

Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China

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.

Parameter Estimation and Uncertainty Analysis: A Comparison between Continuous and Event-Based Modeling of Streamflow Based on the Hydrological Simulation Program–Fortran (HSPF) Model

Hydrologic modeling is usually applied to two scenarios: continuous and event-based modeling, between which hydrologists often neglect the significant differences in model application. In this study, a comparison-based procedure concerning parameter estimation and uncertainty analysis is presented based on the Hydrological Simulation Program–Fortran (HSPF) model. Calibrated parameters related to base flow and moisture distribution showed marked differences between the continuous and event-based modeling. Results of the regionalized sensitivity analysis identified event-dependent parameters and showed that gravity drainage and storage outflow were the primary runoff generation processes for both scenarios. The overall performance of the event-based simulation was better than that of the daily simulation for streamflow based on the generalized likelihood uncertainty estimation (GLUE). The GLUE analysis also indicated that the performance of the continuous model was limited by several extreme events and low flows. In the event-based scenario, the HSPF model performances decreased as the precipitation became intense in the event-based modeling. The structure error of the HSFP model was recognized at the initial phase of the rainfall-event period. This study presents a valuable opportunity to understand dominant controls in different hydrologic scenario and guide the application of the HSPF model.