Calibration of LEACHN model using LH-OAT sensitivity analysis

The partial runoff is complicated in semi-arid and some semi-humid zones in terms of what the runoff generates in partial vertical positions. The partial runoff is highlighted by horizontal soil heterogeneity as well. How to identify the partial runoff and develop a variable threshold for runoff generation is a great difficulty and challenge. In this work, the partial runoff is identified by using a variable active runoff layer structure, and a variable soil water storage capacity is proposed to act as a threshold for runoff generation. A variable layer-based runoff model (VLRM) for simulating the complex partial runoff was therefore developed, using dual distribution curves for variable soil water storage capacity over basin. The VLRM is distinct in that the threshold for runoff generation is denoted by variable soil water storage capacity instead of infiltration capacity or constant soil water storage capacity. A series of flood events in two typical basins of North China are simulated by the model, and also by the Xinanjiang model. Results demonstrate that the new threshold performs well and the new model outperforms the Xinanjiang model. The approach improves current hydrological modelling for complex runoff in regions with large deficiencies in soil water storage.

Section: Sensitivity and Uncertainty Analysesmentioning

confidence: 99%

Rainfall–Runoff Processes and Modelling in Regions Characterized by Deficiency in Soil Water Storage

Shi

Yang

et al. 2019

“…In the LH method, proposed by McKay for use instead of the Monte Carlo method, the parameter space is divided into N intervals with the same probability, and only one variable is randomly extracted from each interval and analyzed by multivariate linear regression. Though this method is advantageous compared to other global sensitivity analyses in that its computational calculation is efficient [34,37], it has limitations in that a linear regression analysis is assumed and the sensitivity to one specific individual variable cannot be identified [34]. To analyze the sensitivity in the OAT method, on the other hand, only one variable in the parameter space is sequentially selected for a small change of the selected parameter, while other parameters are fixed as constant [36,38].…”

Section: Sensitivity Analysis Using Latin-hypercube-one-factor-at-a-tmentioning

confidence: 99%

Dynamical Modeling of Water Flux in Forward Osmosis with Multistage Operation and Sensitivity Analysis of Model Parameters

Ryu

Mushtaq

Park

et al. 2019

To mathematically predict the behavior of a forward osmosis (FO) process for water recovery, a model was constructed using an asymmetric membrane and glucose as a draw solution, allowing an examination of both phenomenological and process aspects. It was found that the proposed model adequately described the significant physicochemical phenomena that occur in the FO system, including forward water flux, internal concentration polarization (ICP), external concentration polarization (ECP), and reverse solute diffusion (RSD). Model parameters, namely the physiochemical properties of the FO membrane and glucose solutions, were estimated on the basis of experimental and existing data. Through batch FO operations with the estimated parameters, the model was verified. In addition, the influences of ECP and ICP on the water flux of the FO system were investigated at different solute concentrations. Water flux simulation results, which exhibited good agreement with the experimental data, confirmed that ICP, ECP, and RSD had a real impact on water flux and thus must be taken into account in the FO process. With the Latin-hypercube-one-factor-at-a-time (LH-OAT) method, the sensitivity index of diffusivity was at its highest, with a value of more than 40%, which means that diffusivity is the most influential parameter for water flux of the FO system, in particular when dealing with a high-salinity solution. Based on the developed model and sensitivity analysis, the simulation results provide insight into how mass transport affects the performance of an FO system. Several types of membrane-based desalination technology, including electrodialysis, membrane distillation, reverse osmosis (RO), and forward osmosis (FO), have been developed [3,4]. Among these, FO-based water desalination, of which the driving force is an intrinsic osmotic pressure gradient, has a unique position because (1) it is highly resistant to membrane fouling [5], (2) it requires much lower energy [6] and exerts higher driving force than conventional physical separation methods if proper draw solutes are used, and (3) it does not deteriorate the physical properties of feed solution (e.g., color, taste, aroma, and nutrition) [7,8]. For these reasons, FO is viewed as workable especially for difficult feed water with high salinity or foulants. FO can be applied to treat hypersaline streams that are too concentrated for RO [9]. Special cases in which there is no requirement to regenerate draw solution also have high potential, as draw solute: It is possible to use diluted fertilizer for direct fertigation [10][11][12] including wastewater treatment [13] and food concentration [7,8]. One such case is the use of fertilizer.However, there are still many difficult barriers to field implementation of the FO process. Typical problems involve intrinsic, performance-reducing properties, including concentration polarization (CP) and reverse solute diffusion (RSD) [14]. Since both sides of the membrane are in contact with two kinds of solutions, feed solution, and draw s...

“…The determination of the most sensitive parameters is the key, and first step, for model calibration and validation at the watershed scale [50]. The sensitivity analysis can classify the sensitive parameters, from most sensitive to least sensitive for the input parameters.…”

Section: Model Calibration and Validationmentioning

confidence: 99%

Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China

Jin

Zhu

Zhao

et al. 2016

Abstract:The assessment of water resource responses to climate change is required in water resource planning and management, protecting environmental quality, and managing watersheds. This study modeled surface runoff and baseflow responses to variations in precipitation (0%, ±10%, and ±20%) and temperature (0 • C, ±1 • C, and ±2 • C) in 25 types of scenarios in the Lanhe Watershed (1140 km 2 ), which possesses the typical hydrological and meteorological characteristics of the Loess Plateau in China. The study is based on the Soil and Water Assessment Tool (SWAT), which was calibrated and validated using the coefficient of determination (R 2 ), Nash-Suttcliffe (Ens), and Percent bias (PBIAS), using the observed streamflow of Shangjingyou Station, a unique gauging station in the study area. The model was calibrated with daily streamflow, from 1967 to 1996, and then validated from 1997 to 2011. R 2 , Ens, and PBIAS were 0.95 and 0.84, 0.78 and 0.72, and 0.6% and −9.1% in annual and monthly calibration periods, 0.90 and 0.78, 0.74 and 0.67, and 22.1% and 18.8% in annual and monthly validation periods, and the overall performance ratings was "satisfactory". The assessment indicates that surface runoff is likely to be more affected than baseflow when altering temperatures and precipitation, and the noticeable changes of surface and baseflow are from June to September and October to November, respectively. Results also indicate that surface runoff and baseflow are very sensitive to the projected reduction in temperature, rather than to an increase of temperature, while precipitation is a constant. In turn, when the temperature is a constant, the surface runoff is sensitive to the projected increase in precipitation and the baseflow is sensitive to the decrease in precipitation.