Soil And Water Assessment Tool Model Performance Research Articles

Hydrological Impacts of Climate Change in Tikur Wuha Watershed, Ethiopian Rift Valley Basin

According to Intergovernmental Panel on Climate Change (IPCC) rising of global surface temperature, sea level rises, arctic and land ice decrease, erratic precipitation and increase of CO2 concentration are the main indicators of climate change. The main objectives of the study was to investigate the possible hydrological impacts of climate change on stream flow and sedimentation in Tikur Wuha watershed, by downscaling canESM2 (Canadian Earth System Model of second generation) global climate model using Statistical Downscaling Model (SDSM). Based on IPCC recommendation baseline periods (1987–2016) were used for baseline scenario analysis. Future scenario analysis was performed for the 2020s, 2050s, and 2080s. canESM2 model consists of Representative Concentration Pathway (RCP) RCP2.6, RCP4.5 and RCP8.5 scenarios. Impact assessment on stream flow and sediment yield was done by Soil and Water Assessment Tool (SWAT) hydrological model. SWAT model performance in simulating monthly stream flow for the study area was satisfactory with R 2 (0.77 and 0.87), N SE (0.70 and 0.77) and D (-16 and -9) for calibration and validation periods respectively. The result of downscaled precipitation and temperature reveals a systematic increase in all future time periods for all three scenarios; RCP2.6, RCP4.5 and RCP8.5 scenarios. These increases in climate variables are expected to result in increase in mean annual stream flow of 8%, 13%, and 15 % for RCP2.6 scenario, 17%, 24%, and 31% for RCP4.5 scenario and 14%,24% and 35% for RCP8.5 scenario for the 2020s, 2050s, and 2080s, respectively. This leads to increment of sediment yield from different sub watershed. The estimated soil loss rate from different sub-watersheds had ranged from 0.42 tons/ha/yr to 28.31 tons/ha/year (1987-1999), whereas the annual weighted average soil loss rate from the watershed was estimated 16.80 tons/ha/year (2000-2100). Future work need to consider studying the effects of different climate change adaptation strategies. Keywords: Climate change Scenarios, Ethiopia, Hydrological impact, SWAT model DOI: 10.7176/JEES/10-2-04 Publication date: February 29 th 2020

Land Use/Cover Change and their Impacts on Streamflow in Kikuletwa Catchment of Pangani River Basin, Tanzania

Streamflow perturbation is highly prevalent in Kikuletwa catchment. However, little is known concerning land use/cover change (LULCC) with regard to streamflow perturbation in the catchment. This study aims to detect the historical and predict future LULCC and assess their impacts on streamflow amounts using the Soil and Water Assessment Tool (SWAT) model. Supervised classification of Landsat imagery data for 1985, 2000 and 2015 years was done in ERDAS 14 Imagine software. Future prediction of LULCC was done using Module for Land Use Change Evaluation (MOLUSCE) tool, a QGIS plug-in. An accuracy ranging from 79% to 82% was obtained for all steps. The results revealed that, from 1985 to 2000; 1985 to 2015; 1985 to 2030 and 1985 to 2050 the percentage of area change in cultivated land is +21.1%; +29.2%; +38.2% and +42.7%, respectively; forest is - 2.3%, -3.1%, -3.8% and -5.8%, respectively; and shrubland is -6.3%, -10%, -15.7% and - 16%, respectively. The performance of SWAT model during calibration were 0.74, 0.75, 0.51 and -0.5% for NSE, R2, RSR and PBIAS, respectively. The impacts of LULCC indicated that, between 1985 to 2000; 1985 to 2015; 1985 to 2030 and 1985 to 2050, the percentage increase in average simulated annual flow is 4.7%, 6.8%, 12.6% and 19.3%, respectively. Surface runoff increased from 25.2 mm (baseline) to 34.5 mm (36.9%); 36.2 mm (42.4%); 41.4 mm (64.3%) and 47.6 mm (88.9%), respectively. Base flow decreased marginally from 82.2 mm (baseline) to 79 mm (-3.8%); 77.8 mm (5.4%); 75.4 mm (-8.3%) and 73.9 mm (- 10.1%), respectively. Thus, apart from climate effects, streamflow perturbation in the catchment is also related to disturbances of catchment influences such as LULCC as revealed in this study. The study is useful for land planners and water resources managers and policy makers in managing resources sustainably.

Evaluation of Soil and Water Assessment Tool and Artificial Neural Network models for hydrologic simulation in different climatic regions of Asia

In this study, a physically-based hydrological model, Soil and Water Assessment Tool (SWAT) and three types of Artificial Neural Network (ANN) models were used to simulate daily streamflow, and results were compared with observed data for performance analysis. The study was carried out in three different river basins with three different climatic characteristics, namely the West-Seti River Basin in a sub-tropical (partially wet) climatic region, Sre Pok River Basin in a tropical (wet) climatic region and Hari Rod River Basin in a semi-arid (dry) climatic region. The SWAT and ANN models were evaluated using statistical indicators such as the correlation coefficient (R2), Nash-Sutcliffe efficiency (NSE), and percentage bias (PBIAS). The performance of ANN models was found to be very good with both R2 and NSE values greater than 0.95 for the training and validation periods in the West-Seti River Basin and Sre Pok River Basin. Whereas, in the Hari Rod River Basin, the performance of the SWAT model was good with both R2 and NSE values greater than 0.60 for the calibration and validation periods. Moreover, the performance of SWAT and ANN models was evaluated based on hydrological indicators (i.e. annual discharge, base flow, Qdry, and Qwet), during different flow periods (very high to very low flow) using flow duration curves (FDCs). The SWAT model was found to be better for low flow simulation and the ANN model performed better for high flow simulation in the three river basins.

Estimation of Streamflow with Incomplete Soil Dataset in Krasioa Basin Using Soil-Landscape Evaluation Approach and SWAT Model

Data on soil properties are indispensable for process-based hydrological modeling. Soil information of Thailand is primarily provided by the Land Development Department (LDD), nevertheless soil property data are available only in arable land whose slope is less than 35%. The steep-slope land was generally labeled as Slope Complex (SC), there is no information available. This paper demonstrated the application of soil-landscape evaluation approach for predicting the missing properties of soil which resulted on enhancement of model performance in streamflow estimation in Krasioa Basin by the Soil and Water Assessment Tool (SWAT) model. The physical properties of soil-soil thickness, fraction of soil particles (clay, sand, organic matter) were predicted using the Soil-Landscape Estimation and Evaluation Program (SLEEP). The additional properties of soil including bulk density, hydraulic conductivity, and available water content were estimated using the pedo-transfer functions (ROSETTA). It was found that SLEEP model could provide consistent information on physical properties of soil. The SWAT model performance in streamflow simulation at the Krasioa Reservoir was improved using the proposed approach. Appropriate model inputs can generate reasonable output. Model performance can further be improved by calibration.

Understanding the effects of soil data quality on SWAT model performance and hydrological processes in Tamedroust watershed (Morocco)

Hydrological modeling remains an indispensable tool for water resources research in order to understand the watershed functioning and to effectively manage water supplies. The study of the hydrologic functioning of a semi-arid watershed is a real challenge in the lack of reliable and regular data. In this work, we propose (1) to evaluate the performance of Soil and Water Assessment Tool (SWAT) on the TAMEDROUST watershed (Morocco) under extremely contrasted climatic conditions during the period 1998–2002 and (2) to test the effects of the soil data resolution on the watershed response. For this second purpose, two soil databases are compared: (i) HWSD-2L, a low-resolution soil database with three soil types obtained from the Harmonized World Soil Database produced by FAO and (ii) TAMED-SOL, a refined database with eleven soil types, performed from field measurements and laboratory analyses.Results before calibration showed a considerable variability and a significant effect of the soil characteristics on the different components of the hydrological cycle such as SW (soil water content) and GWQ groundwater discharge into reach). Flows obtained by HWSD-2L soil database were consistently lower than those simulated by TAMED-SOIL but both databases overpredicted streamflow if compared to observed data. To harmonize the data of the two databases, we proceeded to a harmonization of the soil depth by considering in HWSD-2L only the surface layer, thus creating a third database HWSD-1L which was also considered in the evaluation of the model response. After the calibration period, both soils databases (TAMED-SOIL and HWSD-2L) improved the model performance in terms of streamflow, with values of R2 and NSE between 0.64 and 0.65. Model validation was acceptable and similar for both databases with R2 and NSE values of 0.76 and 0.57.We can conclude that the quality and resolution of soil data affects all hydrological cycle components, mainly SW and water yield (WYLD), but do not lead to significant discrepancies in streamflow simulation, especially after the model calibration.

Evaluation of SWAT Model performance on glaciated and non-glaciated subbasins of Nam Co Lake, Southern Tibetan Plateau, China

This paper presents an assessment of the Soil and Water Assessment Tool (SWAT) on a glaciated (Qugaqie) and a non-glaciated (Niyaqu) subbasin of the Nam Co Lake. The Nam Co Lake is located in the southern Tibetan Plateau, two subbasins having catchment areas of 59 km2 and 388 km2, respectively. The scores of examined evaluation indices (i.e., R2, NSE, and PBIAS) established that the performance of the SWAT model was better on the monthly scale compared to the daily scale. The respective monthly values of R2, NSE, and PBIAS were 0.94, 0.97, and 0.50 for the calibration period while 0.92, 0.88, and −8.80 for the validation period. Glacier melt contribution in the study domain was simulated by using the SWAT model in conjunction with the Degree Day Melt (DDM) approach. The conjunction of DDM with the SWAT Model ensued improved results during both calibration (R2=0.96, NSE=0.95, and PBIAS=−13.49) and validation (R2=0.97, NSE=0.96, and PBIAS=−2.87) periods on the monthly time scale. Average contribution (in percentage) of water balance components to the total streamflow of Niyaqu and Qugaqie subbasins was evaluated. We found that the major portion (99.45%) of the streamflow in the Niyaqu subbasin was generated by snowmelt or rainfall surface runoff (SURF_Q), followed by groundwater (GW_Q, 0.47%), and lateral (LAT_Q, 0.06%) flows. Conversely, in the Qugaqie subbasin, major contributor to the streamflow (79.63%) was glacier melt (GLC_Q), followed by SURF_Q (20.14%), GW_Q (0.13%), and LAT_Q (0.089%). The contribution of GLC_Q was the highest (86.79%) in July and lowest (69.95%) in September. This study concludes that the performance of the SWAT model in glaciated catchment is weak without considering glacier component in modeling; however, it performs reasonably well in non-glaciated catchment. Furthermore, the temperature index approach with elevation bands is viable in those catchments where streamflows are driven by snowmelt. Therefore, it is recommended to use the SWAT Model in conjunction with DDM or energy base model to simulate the glacier melt contribution to the total streamflow. This study might be helpful in quantification and better management of water resources in data scarce glaciated regions.

Calibration of a hydrological model and sensitivity analysis of its parameters: a case study of Seonath river basin

The objective of this paper is surface runoff estimation of the Seonath river basin using a semi-distributed hydrological model, i.e., soil and water assessment tool (SWAT). In this paper, the study on calibration and sensitivity is carried out using SWAT-CUP (calibration and uncertainty program) along with sequential uncertainty fitting (SUFI-2) algorithm. The performance of SWAT model is evaluated by various statistical measures; such as Nash-Sutcliffe (NS) coefficient, coefficient of determination (R2), percent bias (Pbias), p factor, r factor and ratio of the root-mean-square error (RMSE) to the standard deviation of the observation (RSR). In the current work, 31 years (1980-2010) of weather data was used. The time slice for model calibration was 15 years, i.e., 1987-2001 with seven years of warming period 1980-1986 and validation period was comprised of nine years (2002-2010). In the study, the calibration of the model was done for the two stations which is a major step for carrying out further study related to climate and land use change impact assessment. The study yielded satisfactory results in terms of model performance.

Evaluating the impact of spatial variability of precipitation on streamflow simulation using a SWAT model

Abstract The spatial variability of precipitation is often considered to be a major source of uncertainty for hydrological models. The widely used Soil and Water Assessment Tool (SWAT) is insufficient to calculate a sub-basin's mean areal precipitation (MAP) since it only uses data from the rainfall station nearest to the centroid of each sub-basin. Therefore, Inverse Distance Weighting (IDW), Thiessen Polygons (TP) and Ordinary Kriging (OK) were applied as alternative interpolation methods in this study to calculate sub-basin MAP. The MAP results from the four methods used for the Xixian Basin were quite different in terms of amount and spatial distribution. The SWAT model performance was then assessed at monthly and daily timescales, based on Nash–Sutcliffe efficiency (NSE), the Coefficient of Determination (R2) as well as Percentage Bias (PBIAS) at the basin outlet. The results under different network densities and spatial distributions of gauge stations indicated that the modified MAP models did not have an advantage over the default Nearest Neighbour (NN) method in simulating monthly streamflow. However, the modified areal precipitation obtained through IDW and TP showed relatively high accuracy in simulating daily flows as the applied rainfall stations changed. The difference in terms of estimated rainfall and streamflow in this study confirmed that evaluation of interpolation methods is necessary before building a SWAT model.

Assessment of SWAT Model Performance in Simulating Daily Streamflow under Rainfall Data Scarcity in Pacific Island Watersheds

Evaluating the performance of watershed models is essential for a reliable assessment of water resources, particularly in Pacific island watersheds, where modeling efforts are challenging due to their unique features. Such watersheds are characterized by low water residence time, highly permeable volcanic rock outcrops, high topographic and rainfall spatial variability, and lack of hydrological data. The Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the Nuuanu area watershed (NAW) and Heeia watershed on the Island of Oahu (Hawaii). The NAW, which had well-distributed rainfall gauging stations within the watershed, was used for comparison with the Heeia watershed that lacked recoded rainfall data within the watershed. For the latter watershed, daily rain gauge data from the neighboring watersheds and spatially interpolated 250 m resolution rainfall data were used. The objectives were to critically evaluate the performance of SWAT under rain gauge data scarce conditions for small-scale watersheds that experience high rainfall spatial variability over short distances and to determine if spatially interpolated gridded rainfall data can be used as a remedy in such conditions. The model performance was evaluated by using the Nash–Sutcliffe efficiency (NSE), the percent bias (PBIAS), and the coefficient of determination (R2), including model prediction uncertainty at 95% confidence interval (95PCI). Overall, the daily observed streamflow hydrographs were well-represented by SWAT when well-distributed rain gauge data were used for NAW, yielding NSE and R2 values of > 0.5 and bracketing > 70% of observed streamflows at 95PCI. However, the model showed an overall low performance (NSE and R2 ≤ 0.5) for the Heeia watershed compared to the NAW’s results. Although the model showed low performance for Heeia, the gridded rainfall data generally outperformed the rain gauge data that were used from outside of the watershed. Thus, it was concluded that finer resolution gridded rainfall data can be used as a surrogate for watersheds that lack recorded rainfall data in small-scale Pacific island watersheds.

Effects of dynamic land use inputs on improvement of SWAT model performance and uncertainty analysis of outputs

The objective of this study was to evaluate the impacts of static and dynamic land use input conditions on the performance of non-point source (NPS) model and find out whether dynamic land use input can improve the model accuracy. Soil and Water Assessment Tool (SWAT) model was selected as the evaluation model and seven different land use input conditions were set by setting the land use update file in SWAT. The results showed that the land use pattern in the study area changed from 2000 to 2015 due to climate change and human activities, leading to inconsistencies between different land use patterns. The calibrated results indicated that dynamic land use input conditions could apparently improve the simulation accuracy of total nitrogen (TN) and total phosphorus (TP). CE5Y condition had the best calibrated result with R2 and NSE larger than 0.7 and 0.6, respectively. However, for flow simulation, the land use input conditions had no apparent effect on the model calibration and validation results. The deviation analysis of the model outputs indicated that monthly outputs were more affected by the land use input conditions than annual outputs and that deviations in wet seasons were larger than those in normal and dry seasons. The highest MAD occurred in June and August with a value of 82.87 t and 1.56 t for TN and TP, respectively. This study revealed the importance to consider the land use change when simulating the NPS pollution, and could provide support for land use input settings of NPS pollution models.

An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

Accurate mean areal precipitation (MAP) estimates are essential input forcings for hydrologic models. However, the selection of the most accurate method to estimate MAP can be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct weighted average, surface-fitting, and remotely sensed methods). Multiple methods (n = 19) were used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely sensed data sets. Each method was validated against the hydrologic model simulated stream flow using the Soil and Water Assessment Tool (SWAT). SWAT was validated using a split-site method and the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed of the central USA. Cross-validation results showed the error associated with surface-fitting and remotely sensed methods ranging from −4.5 to −5.1%, and −9.8 to −14.7%, respectively. Split-site validation results showed the percent bias (PBIAS) values that ranged from −4.5 to −160%. Second order polynomial functions especially overestimated precipitation and subsequent stream flow simulations (PBIAS = −160) in the headwaters. The results indicated that using an inverse-distance weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may improve SWAT model simulations. Collectively, the results highlight the importance of spatially distributed observed hydroclimate data for precipitation and subsequent steam flow estimations. The MAP methods demonstrated in the current work can be used to reduce hydrologic model uncertainty caused by watershed physiographic differences.

English

The hydrology of Holetta River and its seasonal variability is not fully studied. In addition to this, due to scarcity of the available surface water and increase in water demand for irrigation, the major users of the river are facing a problem of allocating the available water. Therefore, the aim of this research was to investigate the water availability of Holetta River using Geographical Information Systems (GIS) tool and hydrological model. The rainfall runoff process of the catchment was modeled by using Soil and Water Assessment Tool (SWAT). According to SWAT classification, the watershed was divided in to 6 subbasins and 33 hydrological response units (HRUs). The only gauged subbasin in the catchment is subbasin one that is found in the upper part of the area. Therefore, sensitivity analysis, calibration and validation of the model were performed at subbasin one and then the calibrated model was used to estimate runoff at the ungauged part of the catchment. The performance of SWAT model was evaluated by using statistical (coefficient of determination [R2], Nash-Sutcliffe Efficiency Coefficient [NSE] and Index of Volumetric Fit [IVF]) and graphical methods. The result showed that R2, NSE and IVF were 0.85, 0.84 and 102.8, respectively for monthly calibration and 0.73, 0.67 and 108.9, respectively for monthly validation. These indicated that SWAT model performed well for simulation of the hydrology of the watershed. Key words: Holetta River, SWAT, runoff, rainfall, variability.

Hydrological modelling of ungauged urban watershed using SWAT model

The effects of urbanization on hydrological processes and water resources have been quantified and predicted by detailed characterization and modeling of the affected urban area. The model of the soil and water assessment tool (SWAT) has been selected to test its applicability in ungauged urban watershed of Vadodara city, Gujarat India. The main objective of this work is to study the SWAT model and its applicability i.e. test and assess the capabilities, and performance of SWAT model for Vadodara city, which is ungauged urban area by simulating the water balance components in order to understand the status of hydrological process and water resources in that area. The Vadodara city watershed is ungauged. Therefore, a regionalization approach has used to predict the river discharge at the outlet of the watershed. SUFI-2 algorism using SWAT-CUP2012 used for calibration and validation of runoff process has been done on monthly basis. The model was calibrated and validated based on the comparison of simulated and observed flow rates at the basin outlet for the periods 1979–2001 and 2002–2013 respectively. Therefore, for the monthly time step, the application of the NSE values was 0.53 and 0.61, the determining coefficient (R2) was 0.69 and 0.51, while the value of PBIAS was 5.3 and 10.4%, and RSR values were registered as 0.71 and 0.63 for the periods of the calibration and validation process respectively. The result suggests that there has been a good match between simulated and observed flow. Therefore, the model performance is applicable and strong predictive ability for the ungauged watershed of Vadodara city.

Application of SWAT model for predicting soil erosion and sediment yield

Hirakud, the longest earthen dam in Asia on the river Mahanadi, has been affected by sedimentation problems which affect reservoir storage capacities and different reservoir operations. This article presents the hydrological modeling of the Mahanadi catchment up to Hirakud, located in the states of Chhattisgarh and Odisha in India, using the modified version of Soil and Water Assessment Tool (SWAT) with an interface of ArcView Geographic Information System software to predict soil erosion and sediment transport to the reservoir for improving its useful life. The data sources used in the study were: terrain data 90 m resolution of Shuttle Radar Topography Mission, Land Use and Land Cover derived from Landsat Enhanced Thematic Mapper Plus, soil map published by National Bureau of Soil Survey and Land Use Planning, India and meteorological data collected from India Meteorological Department, India. The study involves the analysis of sensitive parameters of the simulated data (discharge 15, sediment load 6); 5-year calibration and 3-year validation on daily basis to predict the discharge and sediment load. The sensitivity analysis was carried out using the Latin Hypercube and One-factor-At-a-Time. The results also show that the prediction of sediment yield is highly sensitive to the sizes of different sub-basins due to the sensitivity of topographic factors used in the Modified Universal Soil Loss Equation. The graphical as well as statistical results achieved in this study indicate that the model is capable to identify critical erosion-prone areas within the watershed on the scale of sub-watershed which helps the hydrologists to introduce effective management practices at the lowest cost. The study shows that about 34% area of total catchment falls under high or above soil erosion zones with combination of coarse loamy type of soil and agricultural type of land use and land cover condition. The results of this study also identify regions of high sediment yield and sediment delivery ratio. To enhance the SWAT model performance, it is recommended to use sub-daily data and to prioritize soil erosion at the Hydrological Response Units level for improvement of watershed management.

Evaluation of the SWAT model performance for simulating river discharge in the Himalayan and tropical basins of Asia

Abstract This study evaluated the Soil and Water Assessment Tool (SWAT) model performance for 11 basins located in two contrasting climatic regions of Asia: the Himalayan and the Southeast Asian tropics. A large variation existed among the case study basins in relation to basin size (330–78,529 km2), topography (377–4,310 metres above sea level) and annual rainfall (1,273–2,500 mm). Performance of the model was evaluated using R2 and wR2 for a low discharge event; Nash–Sutcliffe efficiency (NSE), R2 and RMSE-observation standard deviation ratio (RSR) for high discharge events; and NSE, R2, PBIAS, RSR, NSErel and wR2 for the overall hydrographs. SWAT was found to be suitable for both climatic regions but yielded better performance in the Himalayan basins (NSE 0.72–0.81 at calibration) compared to the tropical basins (NSE 0.36–0.72 at calibration). Although most of the models underperformed in either low or high discharge events, a few of those remaining showed a balance between the extremes, proving that it is possible to achieve a balanced hydrograph with the SWAT model. The consistency of model performance across numerous Himalayan and tropical basins in the area confirmed the versatility and reliability of SWAT as a hydrological model and suitable tool for water resources planning and management.

PENGGUNAAN MODEL HIDROLOGI DI SUB DAS CILIWUNG HULU

A watershed has complex hydrological components and may be difficult to understand comprehensively. Modelling can be used to simplify and predict the processes which will happen. SWAT (Soil and Water Assessment Tool) is a model which can predict hydrology and simulate various processes in watershed.The objective of this research was: to analyse performance of SWAT model which predict discharge flow in upper Ciliwung watershed through calibration. Methods applied included analysis of the input data and calibration. The research was conducted in the period of June 2011 until June 2012. Based on the data of daily discharge flow in February and March 2008 and 2009, the calibration results showed values of R 0,80 and NSE 0,55. These results described that SWAT model can be used to predict hydrological processes in upper Ciliwung watershed.Prediction of hydrology could be used as the base to manage land agriculture towards sustainable agriculture.

Evaluation of precipitation input for SWAT modeling in Alpine catchment: A case study in the Adige river basin (Italy)

Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13years (1998–2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting data), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and TRMM (Tropical Rainfall Measuring Mission) has been considered. Both model performances (comparing simulated and measured streamflow data at the catchment outlet) as well as parameter and prediction uncertainties have been quantified. For all three subbasins, the use of elevation bands is fundamental to match the water budget. Streamflow predictions obtained using IDW inputs are better than those obtained using the other datasets in terms of both model performance and prediction uncertainty. Models using the CHIRPS product as input provide satisfactory streamflow estimation, suggesting that this satellite product can be applied to this data-scarce Alpine region. Comparing the performance of SWAT models using different precipitation datasets is therefore important in data-scarce regions. This study has shown that, precipitation is the main source of uncertainty, and different precipitation datasets in SWAT models lead to different best estimate ranges for the calibrated parameters. This has important implications for the interpretation of the simulated hydrological processes.

Improving SWAT for simulating water and carbon fluxes of forest ecosystems

As a widely used watershed model for assessing impacts of anthropogenic and natural disturbances on water quantity and quality, the Soil and Water Assessment Tool (SWAT) has not been extensively tested in simulating water and carbon fluxes of forest ecosystems. Here, we examine SWAT simulations of evapotranspiration (ET), net primary productivity (NPP), net ecosystem exchange (NEE), and plant biomass at ten AmeriFlux forest sites across the U.S. We identify unrealistic radiation use efficiency (Bio_E), large leaf to biomass fraction (Bio_LEAF), and missing phosphorus supply from parent material weathering as the primary causes for the inadequate performance of the default SWAT model in simulating forest dynamics. By further revising the relevant parameters and processes, SWAT's performance is substantially improved. Based on the comparison between the improved SWAT simulations and flux tower observations, we discuss future research directions for further enhancing model parameterization and representation of water and carbon cycling for forests.

Influence of spatial resolution of radar images on the parameterization and performance of SWAT model

Recent advances in environmental monitoring improve data quality and availability in space and time, but questions about their beneficial use in water resources analysis and modeling still remain. This study assesses the dependency of the parameterization and performance of a watershed-scale simulation model, the Soil and Water Assessment Tool (SWAT), on high-quality (rainfall) data at different spatial resolutions. The SWAT model was applied to the upstream of the Yeongsan River in Korea which remained relatively unexploited, and was calibrated and validated with the observed daily flow and monthly sediment data for the periods of 2012–2013 and 2014, respectively. Results showed that the radar rainfall estimates, derived using bias adjustment factors A1 and A2 which allowed the number and magnitude of storm events to be corrected, respectively, fitted excellently with the standard gauging data (R2 = 0.97–0.98). Interestingly, the recommended parameter sets for steam flow were significantly different among the rainfall data-sets at different resolutions, but not for sediment concentration. The prediction accuracy of the model was, on average, higher not only during the calibration period than for the short-term validation period, but also using all the radar data-sets than using the standard gauging data. These results demonstrate that although we cannot recommend the best input among the new rainfall products in this preliminary study, the optimal parameter sets developed from many local and regional studies using the SWAT model need to be revisited fundamentally.

Assessment of SWAT Model Applicability and Performance for Predicting Surface Runoff in an Ungauged Watershed in the Philippines

The Soil and Water Assessment Tool (SWAT) model, owing to its robustness and wide applicability, was tested in Mabacan watershed in Laguna, Philippines, with the objective of developing a model for predicting surface runoff or streamflow in ungauged watersheds under conditions of limited hydrologic data. Model parameterization was performed based on the physical characteristics of the watershed and guided by sensitivity analysis. SWAT-predicted monthly surface runoff values for a 7-year period were then compared with manually computed values obtained using water balance and SCS-Curve Number methods. Agreement between runoff values was evaluated using the coefficient of determination (R2) and Nash-Sutcliffe model efficiency (NSE). Correlation analysis between SWAT-simulated monthly runoff and observed monthly rainfall was also performed to further assess the plausibility of simulation results. Sensitivity analysis showed that that the curve number (CN2), soil evaporation compensation factor (ESCO), and soil depth (SOL_Z) are the most sensitive parameters with sensitivity index (I) of 2.92, 0.08, and 0.04, respectively. Comparison between SWAT-predicted surface runoff with those obtained using water balance and SCS-CN methods yielded R2 values of 0.95 and 0.94, and NSE values of 0.70 and 0.63, respectively. The SWAT-simulated runoff series also proved to be well-correlated with observed rainfall series (R2=0.82). Results of this study suggest that the SWAT model is highly applicable for predicting surface runoff or streamflow in ungauged watersheds in the Philippines even with limited hydrologic data and that familiarity with the physical characteristics of the watershed area is essential in enhancing model parameterization and performance.