Generalized Watershed Loading Function Research Articles

Climate change and its effects on the streamflow of an Andean river basin with volcanic activity

Abstract We use a Generalized Watershed Loading Function (GWLF) model to simulate streamflow in the Gualí River Basin. The model's performance is assessed using metrics such as percentage of bias (PBIAS), Nash–Sutcliffe efficiency (NSE), RMSE–observations standard deviation ratio (RSR), and Kling–Gupta efficiency (KGE) to indicate good performance. Furthermore, we analyze projections of precipitation and streamflow using several global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5). Despite the uncertainties and coarse resolution, our results show that increases in the mean streamflow and significantly decreasing trends in projected precipitation and streamflow are observed from 2015 to 2099 under the SSP5-8.5 scenario. Furthermore, our findings suggest an increase in long-term mid-flow and low-flow. Moreover, this work provides a methodological framework for hydrological modeling in small tropical river basins, by incorporating data from GCMs while raising concerns and caveats. This study offers valuable insights into the potential effects of climate change on streamflow in an Andean river basin characterized by volcanic activity and significant human impacts. The findings reported here provide useful information for future decisions related to water supply for the social, environmental, and productive sectors in the seven towns within the catchment.

The impacts of climate changes on watershed streamflow and total dissolved nitrogen in Danjiang Watershed, China

Abstract The impacts of future climate change on the watershed streamflow and total dissolved nitrogen (TDN) fluxes upstream of the Danjiang River were estimated. The newest shared socioeconomic pathways (SSP) in CMIP6 were used as a climate change scenario. The ensembles of downscaled GCM outputs from WorldClim were used as future climate change information. A combined modeling approach is proposed, including the Long Ashton Research Station Weather Generator (LARS-WG) model as a weather generator and the generalized watershed loading function (GWLF) model for watershed hydrochemical process model and scenario analysis. The results show that there is generally less annual streamflow but more annual TDN flux under future climate change scenarios. The monthly streamflow and TDN flux increased from May to July and decreased from August to October. Changes in streamflow and TDN fluxes were the greatest in the worst uncontrolled scenario of SSP 5-85, with a 12.1% decrease in annual streamflow in the 2070s and a 4.82% increase in annual TDN flux in the 2090s. This indicates that active climate policies can mitigate the impact of climate change on watersheds. Furthermore, the source apportionments of TDN from agricultural sources will increase to nearly 50% by the 2090s, and targeted management strategies should be implemented.

Assessing impacts of future climate change on hydrological processes in an urbanizing watershed with a multimodel approach

Abstract The sensitivity of hydrological processes to the changed environment is of great concern. The integrated impacts of climate change and urbanization in the future have been assessed in a watershed in Northwest China through a multimodel approach based on the combined application of Generalized Watershed Loading Functions, the Long Ashton Research Station Weather Generator, and the Land Change Modeler. The results showed that both climate change and urbanization would lead to more watershed streamflow, and their combination would have synergistic effects on additional increases. In addition, there would be different seasonal distributions of streamflow with a greater proportion of runoff. These study results are helpful in supporting projects and/or decision-making processes for managers by providing more insights into the regional hydrological changes affected by climate change and urbanization. The proposed methodology of the combined multimodel approach may be applicable in other areas with similar conditions.

Evaluating a parsimonious watershed model versus SWAT to estimate streamflow, soil loss and river contamination in two case studies in Tietê river basin, São Paulo, Brazil

Study regionThe Atibaia and Jacaré-Guaçu watersheds from the Tietê river basin, São Paulo, Brazil. Study focusThis study aims to compare estimates of flow, sediment yield and nutrients loads obtained from two distinct models with different structures and degree of complexity. The Generalized Watershed Loading Function (GWLF) and the Soil Water Assessment Tool (SWAT). We are particularly interested in understanding under which conditions the use of each model is to be recommended, namely when does the addition effort required to run the SWAT model leads to effective better results. As SWAT’s calibration procedure is cumbersome, the advantage of using a more detailed and distributed model fails to materialize when detailed data are not available or when monthly estimates are enough. GWLF model provides useful results with a reduced data gathering and calibration effort. New hydrological insights of the regionThe joint calibration of both models to two watersheds offered a robust set of parameter values for prevalent conditions of Tiête river basin given the existing data set, although not all modelled variables are reproduced accurately. The performance of both models is adequate when estimating streamflow at a monthly time, but decreases when estimating daily flow, sediment yield, and nutrients loads. The poor monitoring of sediments and nutrients concentration hinders the ability to fully calibrate the model’s water quality component.

Multi-Objective Optimization for Selecting and Siting the Cost-Effective BMPs by Coupling Revised GWLF Model and NSGAII Algorithm

Best management practices (BMPs) are an effective way to control water pollution. However, identification of the optimal distribution and cost-effect of BMPs provides a great challenge for watershed policy makers. In this paper, a semi-distributed, low-data, and robust watershed model, the Revised Generalized Watershed Loading Function (RGWLF), is improved by adding the pollutant attenuation process in the river channel and a bank filter strips reduction function. Three types of pollution control measures—point source wastewater treatment, bank filter strips, and converting farmland to forest—are considered, and the cost of each measure is determined. Furthermore, the RGWLF watershed model is coupled with a widely recognized multi-objective optimization algorithm, the non-dominated sorting genetic algorithm II (NSGAII), the combination of which is applied in the Luanhe watershed to search for spatial BMPs for dissolved nitrogen (DisN). Fifty scenarios were finally selected from numerous possibilities and the results indicate that, at a minimum cost of 9.09 × 107 yuan, the DisN load is 3.1 × 107 kg and, at a maximum cost of 1.77 × 108 yuan, the total dissolved nitrogen load is 1.31 × 107 kg; with the no-measures scenario, the DisN load is 4.05 × 107 kg. This BMP optimization model system could assist decision-makers in determining a scientifically comprehensive plan to realize cost-effective goals for the watershed.

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models.

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

Estimating the Responses of Hydrological and Sedimental Processes to Future Climate Change in Watersheds with Different Landscapes in the Yellow River Basin, China.

This study concerned the sediment issue of the Yellow River basin. The responses of hydrological and sedimental processes to future climate change in two upland watersheds with different dominant landscapes were estimated. Four Representative Concentration Pathway (RCP) scenarios with different radiative forcing levels were considered. The outputs of eleven Global Climate Models (GCMs) were used to represent the future climate status of the 2050s and 2070s, and an ensemble means was achieved to avoid uncertainty. The Long Ashton Research Station Weather Generator (LARS-WG) was employed to downscale the outputs of GCMs for future site-scale daily weather data estimations. The Generalized Watershed Loading Functions (GWLF) model was employed to model the streamflow and sediment yields under various scenarios and periods. The results showed that there would be generally hotter and wetter weather conditions in the future. Increased erosion and sediment yields could be found in the study area, with lesser increments in sediment in woodland than in cultivated field. The peak of sediment would appear in the 2050s, and integrated measures for sediment control should be implemented to reduce erosion and block delivery. The multi-model approach proposed in this study had reliable performance and could be applied in other similar areas with modest data conditions.

The Improvement in GWLF Model Simulation Performance in Watershed Hydrology by Changing the Transport Framework

The correct and reasonable delineation of actual hydrologic processes is a footstone for the effective simulation of pollutants in watershed models. In this study, a simple but comprehensive semidistributed modeling approach based on the generalized watershed loading function (GWLF) was modified to enable the accurate simulation of hydrology in watersheds. The frame of the original GWLF model (ORM), with a lumped hydrological parameter, was modified by adding channel routing processes, which made it possible to introduce the concept of subbasins. Then, the revised GWLF model was applied to the Luanhe watershed (30,000 km2) on a monthly bias in comparison with the ORM and the previously revised version. The sensitivity analysis and generalized likelihood uncertainty estimation (GLUE) uncertainty analysis were individually conducted to evaluate these modifications. Eventually, we compared four extreme conditions for the daily streamflow simulations of the three model versions in the Tunxi watershed but without calibration. All of the results indicated that the stability and accuracy of the model and the validity of the parameters were all enhanced and improved by the new revised version of the model, which provided reliable simulation results and indicated that it is a prospective tool to support watershed management.

A Bayesian modeling approach for phosphorus load apportionment in a reservoir with high water transfer disturbance.

Phosphorus loading from external and internal sources poses a potential risk to eutrophication of lakes or reservoirs. However, the relative contribution of external and internal sources to eutrophication is still unclear especially for reservoirs with water transfer disturbance. The objective of this paper is to estimate the phosphorus loading from external (water transfer and diffusing emission) and internal sources (sediment release) in Yuqiao Reservoir (YQR) and compare their relative contribution of external and internal sources. In this study, we estimated the phosphorus loading considering both external (water transfer and diffusing source emission) and internal (release from sediment) sources of YQR. The phosphorus loading from water transfer was estimated by total phosphorus (TP) concentration × monthly flow of inflow. The phosphorus loading from nonpoint source emission was estimated using a generalized watershed loading function (GWLF). The phosphorus loading from internal sources was estimated with a Bayesian phosphorus budget model. Our result showed that water transfer TP load is the biggest (45.2%) source of TP load in YQR and internal TP load (20.5%) accounts for a comparable proportion of TP load as nonpoint source (34.3%) in YQR and dominates the total loading in some months. Analysis of seasonal total phosphorus load apportionment indicated that water transfer TP load takes the largest proportion in winter (60.8%), spring (60.2%), and autumn (47.8%). Nonpoint source TP load takes the largest proportion in summer (60.1%), and internal TP load is the second source of YQR in summer (22.4%). Our study indicates that water transfer may be the major driver of eutrophication for some reservoir systems, and sediment release may prevent recovery of many eutrophic lakes and reservoirs. Our analysis suggests that TP pollution control strategies in YQR should be preferentially focused on the improvement of water quality in the upstream reservoir, and nonpoint source TP load reductions should be focused on summer. Compared with conventional nutrient apportionment model applications, this paper provides a new approach to estimate external and internal TP loads simultaneously. Graphical abstract ᅟ.

Estimation of hydrological response to future climate change in a cold watershed

Abstract The vulnerability of the natural water system in cold areas to future climate change is of great concern. A coupled model approach was applied in the headwater watershed area of Yalu River in the northeastern part of China to estimate the response of hydrological processes to future climate change with moderate data. The stochastic Long Ashton Research Station Weather Generator was used to downscale the results of general circulation models to generate synthetic daily weather series in the 2050s and 2080s under various projected scenarios, which were applied as input data of the Generalized Watershed Loading Functions hydrological model for future hydrological process estimations. The results showed that future wetter and hotter weather conditions would have positive impacts on the watershed runoff yields but negative impacts on the watershed groundwater flow yields. The freezing period in winter would be shortened with earlier snowmelt peaks in spring. These would result in less snow cover in winter and shift the monthly allocations of streamflow with more yields in March but less in April and May, which should be of great concern for future local management. The proposed approach of the coupled model application is effective and can be used in other similar areas.

Estimation of the Source Apportionment of Phosphorus and Its Responses to Future Climate Changes Using Multi-Model Applications

The eutrophication issue in the Yangtze Basin was considered, and the phosphorus loads from its tributary, the Modaoxi River, were estimated. The phosphorus flux and source apportionment of the Modaoxi River watershed were modeled and quantified, and their changes with respect to future projected climate scenarios were simulated with multiple model applications. The Regional Nutrient Management (ReNuMa) model based on Generalized Watershed Loading Functions (GWLF) was employed as a tool to model the hydrochemical processes of the watershed and thereby estimate the monthly streamflow and the phosphorus flux as well as its source apportionment. The Long Ashton Research Station Weather Generator (LARS-WG) was used to predict future daily weather data through the statistical downscaling of the general circulation model (GCM) outputs based on projected climate scenarios. The synthetic time series of daily precipitation and temperatures generated by LARS-WG were further used as input data for ReNuMa to estimate the responses of the watershed hydrochemical processes to future changed climate conditions. The results showed that both models could be successfully applied and that the future wetter and warmer climate trends would have generally positive impacts on the watershed phosphorus yields, with greater contributions coming from runoff. These results could provide valuable support for local water environmental management.

Comparison of SWAT and GWLF Model Simulation Performance in Humid South and Semi-Arid North of China

Watershed models have gradually been adapted to support both decision and policy making for global environmental pollution control. In this study, two watershed models with different complexity, the Soil and Water Assessment Tool (SWAT) and the Generalized Watershed Loading Function (GWLF), were applied in two catchments in data scarce China, namely the Tunxi and the Hanjiaying basins with contrasting climatic conditions (humid and semi-arid, respectively). The performances of both models were assessed via comparison between simulated and measured monthly streamflow, sediment yield, and total nitrogen. Time series plots as well as four statistical measures (the coefficient of determination (R2), the Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE (root mean square error)—observations standard deviation ratio (RSR)) were used to estimate the performance of both models. The results show that both models were generally able to simulate monthly streamflow, sediment, and total nitrogen loadings during the simulation period. However, SWAT performed better for detailed representations, while GWLF could produce much better average values of the observed data. Thus, GWLF offers a user-friendly prospective alternative watershed model that requires little input data and that is applicable for areas where the input data required for SWAT are not always available. SWAT is more suitable for projects that require high accuracy and offers an advantage when measured data are scarce.

Using multiple watershed models to assess the water quality impacts of alternate land development scenarios for a small community

Chesapeake Bay, the largest estuary in North America, is impaired by excess nutrient discharges, especially from urban and agricultural land. Watershed simulation models have provided key insights to understanding land-to-water connections, but rarely are these models applied to guide local land management to explore and communicate uncertainty in the model predictions. In this study, three watershed simulation models; the Soil and Water Assessment Tool (SWAT), the Generalized Watershed Loading Function (GWLF) model, and the Chesapeake Bay Program's Chesapeake Watershed Model (CBP-CWM) were implemented to predict water, total nitrogen, and total phosphorus discharges from small tributaries in the town of Queenstown, Maryland, USA. Based on our evaluation metrics, none of the models consistently provided better results. In general, there was a good agreement on annual average water flow between the SWAT and CBP-CWM models, and the GWLF and CBP-CWM models predicted similar TN and TP loads. Each model has strengths and weaknesses in flow and nutrient predictions, and predictions differed among models even when models were initialized with the same data. Using multiple models may enhance the quality of model predictions and the decision making process. However, it could also be the case that the complexity of implemented watershed models and resolution of our understanding currently are not yet suited to provide scientifically credible solutions.

Modeling and Evaluating of Non‐Point Source Pollution in a Semi‐Arid Watershed: Implications for Watershed Management

Watershed models are cost‐effective and powerful tools for evaluating and controlling non‐point source (NPS) pollution. Generalized Watershed Loading Functions (GWLF) model, a relative parsimonious model, was applied to simulate watershed streamflow and nutrient loads in Liu River watershed, northern China. The model results were used to evaluate watershed NPS load, and the implications for NPS pollution mitigation measures were investigated. The temporal‐spatial distribution, the critical source areas (CSAs) at sub‐watershed level, and the best management practices (BMPs) efficiencies at CSAs were investigated by GWLF model. Due to the contrasting hydrological conditions, the NPS loads of wet year and flood season were much more than those of dry year and non‐flood season. Four sub‐watersheds were identified as CSAs, and the results showed that CSAs had high level of load intensities due to the high percentage of agricultural land and residential land. Through evaluating the efficiency and cost of seven BMPs, conservation tillage and vegetative buffers were selected as the measures to implement in the CSAs, and they can reduce 14.2% and 12.5% of total nitrogen and total phosphorus NPS loads in Liu river watershed. These findings can provide valuable information for implementing more effective and reasonable management measures to control NPS pollution in Liu River watershed and indicate the utility of GWLF with modest data requirements for such application.

Effect of Land-use Change Scenarios on Nutrients and TSS Loads

The projected growth in population in Israel by 50 % by 2030 will greatly enhance urban density and motivate increased urbanization of rural regions in the country. The Lake Kinneret watershed is a rural region of which only about 3 % of the total area is used for residence, and currently, it is the least populated region in Israel. A significant land-use change and growth of urbanized regions is therefore expected in the near future, leading to changes in water quality management in the watershed. In this study, we attempted to quantify the effects of these possible changes in land-use on the flow and pollutant loads discharged from the watershed into Lake Kinneret. To that end, we calibrated and verified the AVGWLF (ArcView (GIS) Generalized Watershed Loading Function) model to simulate stream flows, sediment and nutrient loads under the conditions of a Mediterranean climate watershed. In addition to AVGWLF model, we used two external tools, namely: the HYdrological Model for Karst Environment (HYMKE) to predict daily flows of streams which were not simulated by the AVGWLF model, and a Mediterranean Multiplication Factor (MMF) which was used to improve sediment transport and nutrient load simulations. The combined suite of tools successfully simulated the observed data (r2 > 0.70 and Nash-Sutcliffe efficiency >0.69 for flowrate, sediment and nutrient), including extreme values. The successful combination of the models provides watershed and lake managers the ability to examine the potential land-use changes and their impact on the watershed and the lake downstream.

A Multi-Criteria Model Selection Protocol for Practical Applications to Nutrient Transport at the Catchment Scale

Process-based models are widely used to investigate nutrient dynamics for water management purposes. Simulating nutrient transport and transformation processes from agricultural land into water bodies at the catchment scale are particularly relevant and challenging tasks for water authorities. However, few practical methods guide inexperienced modelers in the selection process of an appropriate model. In particular, data availability is a key aspect in a model selection protocol, since a large number of models contain the functionalities to predict nutrient fate and transport, yet a smaller number is applicable to specific datasets. In our work, we aim at providing a model selection protocol fit for practical application with particular emphasis on data availability, cost-benefit analysis and user’s objectives. We select for illustrative purposes five process-based models with different complexity as “candidates” models: SWAT (Soil and Water Assessment Tool), SWIM (Soil and Water Integrated Model), GWLF (Generalized Watershed Loading Function), AnnAGNPS (Annualized Agricultural Non-Point Source Pollution model) and HSPF (Hydrological simulation program-FORTRAN). The models are described in terms of hydrological and chemical output and input requirements. The model selection protocol considers data availability, model characteristics and user’s objectives and it is applied to hypothetical scenarios. This selection method is particularly formulated to choose process-based models for nutrient modeling, but it can be generalized for other applications which are characterized by a similar degree of complexity.

Nutrient loadings from urban catchments under climate change scenarios: Case studies in Stockholm, Sweden

Anthropogenic nutrient emissions and associated eutrophication of urban lakes are a global problem. Future changes in temperature and precipitation may influence nutrient loadings in lake catchments. A coupling method, where the Generalized Watershed Loading Functions method was tested in combination with source quantification in a Substance Flow Analysis structure, was suggested to investigate diffuse nutrient sources and pathways and climate change effects on the loadings to streamflow in urban catchments. This method may, with an acceptable level of uncertainty, be applied to urban catchments for first-hand estimations of nutrient loadings in the projected future and to highlight the need for further study and monitoring. Five lake catchments in Stockholm, Sweden (Råcksta Träsk, Judarn, Trekanten, Långsjön and Laduviken) were employed as case studies and potential climate change effects were explored by comparing loading scenarios in two periods (2000–2009 and 2021–2030). For the selected cases, the dominant diffuse sources of nutrients to urban streamflow were found to be background atmospheric concentration and vehicular traffic. The major pathways of the nitrogen loading were suggested to be from both developed areas and natural areas in the control period, while phosphorus was indicated to be largely transported through surface runoff from natural areas. Furthermore, for nitrogen, a modest redistribution of loadings from surface runoff and stormwater between seasons and an increase in the annual loading were suggested for the projected future climate scenarios as compared to the control period. The model was, due to poor monitoring data availability, only able to set an upper limit to nutrient transport by groundwater both in the control period and the future scenarios. However, for nitrogen, groundwater appeared to be the pathway most sensitive to climate change, with a considerable increase and seasonal redistribution of loadings. For phosphorus, loadings by different pathways were apparently less sensitive to climate change.

Estimation of watershed hydrologic processes in arid conditions with a modified watershed model

Watershed models play an important role in modern water resource management, increasingly demanding a robust hydrologic data framework to estimate watershed hydrochemical processes. The Generalized Watershed Loading Function (GWLF), a typical watershed model with modest data requirements, has been applied to watershed-scale hydrochemical estimation worldwide. However, while it generally successfully estimates flows in humid regions, the model suffers from a weakness in hydrologic estimation during low-flow periods, which are projected to continue increasing with global climate change in many places. To address this issue, three algorithms describing functional responses of flows to saturated water storage, the segment function approach, linear function approach, and exponential function approach, have been proposed in this paper, integrated with a previous leakage mechanism for unsaturated water storage used in two earlier GWLF versions, and applied to a case study of Shuai Shui River watershed in China. Comparisons of this version, including new algorithms or algorithm linkages, with the earlier GWLF versions, show that all the new algorithms improve model accuracy in low-flow months; the linear function approach linking the leakage process has the best effect. This work refines the framework of GWLF model to address both humid and arid conditions that can be used as alternatives for future applications. These new functional dynamic responses should also have potential application in other similar watershed models.

Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China

Excessive nitrogen loads and subsequent eutrophication risk have led to a series of critical water quality problems in Chinese watersheds. To address this issue, a modeling approach is useful for quantifying nitrogen sources, assessing source apportionment, and guiding management responses. In this study, we modeled the main hydrochemical processes of the Lian River watershed located in the south of China using the Regional Nutrient Management (ReNuMa) model, a model derived from the Generalized Watershed Loading Function (GWLF) model and incorporating Net Anthropogenic Nitrogen Inputs (NANI) to estimate runoff nitrogen concentrations. An informal Bayesian method, the Generalized Likelihood Uncertainty Estimation (GLUE) procedure, was applied for model calibration and uncertainty analysis. The resulting modeled monthly total nitrogen fluxes have high Nash-Sutcliff coefficients (>0.85) for the calibration (2005–2009) and verification (2003, 2004 and 2010) periods, representing an acceptable goodness-of-fit. The model outputs were further processed using multivariate statistical analysis to determine latent rules of nitrogen source apportionment under different circumstances, including different water regimes, seasonal patterns, and loading levels. The main nitrogen contributions in different natural and management-driven conditions have been identified, and appear to be significant for supporting decision-making priorities. We find that the ReNuMa model, with its Bayesian procedure and the linkage of subsequent multivariate statistical analysis, represents a useful approach with applicability within China and a great potential to be extended elsewhere.

Modification of generalized watershed loading functions (GWLF) for daily flow simulation

This study modified the generalized watershed loading functions (GWLF) model, and applied the modified model to simulate the water flow of the catchment area of the Lan-Yang River, by entering the current status of land use, hydrological data, and meteorological data into the model. This modified model took soil resistance into consideration when calculating evapotranspiration and added the parameters of moisture content in the unsaturated zone and hydraulic conductivity to calculate percolation. This model also considered the percolation that directly penetrated into the saturated zone. The modifications enabled the GWLF model to simulate the nature of daily stream flows. The results indicated that the modified GWLF model could improve the calculation of percolation and evapotranspiration in the unsaturated zone for the dry season. Because percolation enhanced groundwater flow, we adjusted the underestimations for low-rainfall periods to simulate the daily stream flow. The results showed that the modified GWLF model was appropriate for simulating not only monthly, but also daily stream flows.