Multi-Variable Sensitivity Analysis, Calibration, and Validation of a Field-Scale SWAT Model: Building Stakeholder Trust in Hydrologic and Water Quality Modeling

2020 ◽  
Vol 63 (2) ◽  
pp. 523-539 ◽  
Author(s):  
Ritesh Karki ◽  
Puneet Srivastava ◽  
David D. Bosch ◽  
Latif Kalin ◽  
Jasmeet Lamba ◽  
...  
Keyword(s):  
Water Quality ◽  
Soil Moisture ◽  
Crop Yield ◽  
Swat Model ◽  
Nutrient Transport ◽  
Agricultural Productivity ◽  
Water Quality Modeling ◽  
Field Scale ◽  
Management Scenarios ◽  
Model Robustness

HighlightsSWAT can adequately simulate runoff, soil moisture, cotton and peanut yields, and nitrate at field scale.Muskingum routing and adjusting DIS_STREAM are important to simulate fields as watersheds rather than HRUs.Crop yield calibration is critical for improving SWAT model robustness in nutrient transport simulations and for building stakeholder trust.SWAT can quantify the impacts of different management scenarios at the field scale.Abstract. Multi-variable calibration of a field-scale Soil and Water Assessment (SWAT) model is critical for understanding the true impacts of irrigation and nutrient best management practices (BMPs) on hydrology, water quality, and agricultural productivity and for building stakeholder trust for eventual BMP implementation at the watershed scale. This study evaluated the ability of SWAT to simulate runoff, soil moisture, cotton and peanut yields, and nitrate in conventionally tilled and strip-tilled plots while also evaluating the differences in hydrological and nutrient simulation parameters for the two tillage practices. Modeling results showed that SWAT adequately simulated runoff, soil moisture, cotton and peanut yields, and nitrate at the field scale and that calibrated values for the curve number of operation (CNOP) were different for the conventionally tilled and strip-tilled plots and critical to runoff calibration. It was also important to change the routing method from variable storage to Muskingum and to adjust DIS_STREAM for runoff simulation if the field was to be simulated as a watershed rather than as an HRU. Sequential calibration of surface runoff, soil moisture, crop yield, and nitrate showed that crop yield can be an important consideration for improving SWAT model robustness in nutrient transport simulations. Soil moisture calibration did not have a significant effect on runoff simulations. Evaluation of the impacts of different management scenarios showed that soil moisture sensor-based irrigation, cover crop, and strip tillage had the highest potential for reducing nutrient loss and conserving water while maintaining agricultural productivity in southern Georgia. This study also demonstrated to stakeholders that the SWAT model can successfully quantify the impacts of different management scenarios on their farm fields. Keywords: Agricultural BMPs, Field-scale SWAT, Multi-variable calibration, SWAT, SWAT-CUP.

Discharge Assessment by Using Integrated Hydrologic Model for Environmental Technology Development

2014 ◽  
Vol 911 ◽  
pp. 378-382 ◽  
Author(s):  
Mohd Fozi Ali ◽  
Nor Faiza A. Rahman ◽  
Khairi Khalid
Keyword(s):  
Water Quality ◽  
River Water ◽  
River Discharge ◽  
Technology Development ◽  
Swat Model ◽  
Hydrologic Model ◽  
Water Quality Modeling ◽  
River Water Quality ◽  
Environmental Technology ◽  
Current State

River water quality degradation is one of the most significant environmental challenges. Over the years, many models have been used to investigate the current state of Malaysian rivers and its effects to the environment. River discharge is an important factor in water quality investigation. An integrative computational model, GIS coupled with SWAT model was being used to predict river discharge of this research. The simulation results in the period 1999 to 2010 represented fluctuation of discharge relatively well with both R2and NSI values were above 0.6. The results proved that the development of integrative GIS technology coupled with SWAT model is a good tool for environmental technology development in terms of investigating the current state of Langat river water quality as well as the capability of simulating the river discharge in the river basin. This shows that GIS-SWAT interface can be a reliable tool for water quality modeling in Malaysia in the future and further development on the software technology is a benefit for the water resources and environmental studies.

scholarly journals Assessing the Impact of Site-Specific BMPs Using a Spatially Explicit, Field-Scale SWAT Model with Edge-of-Field and Tile Hydrology and Water-Quality Data in the Eagle Creek Watershed, Ohio

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1299 ◽  
Author(s):  
Katherine Merriman ◽  
Prasad Daggupati ◽  
Raghavan Srinivasan ◽  
Chad Toussant ◽  
Amy Russell ◽  
...  
Keyword(s):  
Water Quality ◽  
Cover Crops ◽  
Best Management Practices ◽  
Swat Model ◽  
Monitoring Data ◽  
Quality Data ◽  
Field Scale ◽  
Water Quality Data ◽  
Creek Watershed ◽  
The Impact

The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads.

Improved spatial modelling of crop productivity using geophysics-based soil mapping: Two case studies beyond the field scale

2020 ◽  
Author(s):  
Cosimo Brogi ◽  
Johan Alexander Huisman ◽  
Michael Herbst ◽  
Anne Klosterhalfen ◽  
Heye Bogena ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Case Studies ◽  
Crop Yield ◽  
Growing Season ◽  
Crop Growth ◽  
Soil Sampling ◽  
Added Value ◽  
Soil Maps ◽  
Field Scale

<p>Water shortage in soil can result in a considerable reduction in crop yield, thus representing a severe threat to agricultural sustainability and profitability. It is therefore crucial to improve our understanding and prediction of the spatial variability of water stress and crop yield. Within this context, detailed soil maps obtained from the combination of hydrogeophysical methods, such as electromagnetic induction (EMI), and direct soil sampling can prove vital. However, it is still challenging to derive and exploit such data beyond the field-scale and their added value has not been fully investigated yet. In this study, we present results from two case studies where the added value of hydrogeophysical measurements in agriculture have been evaluated. In the first caone, high-resolution multi-configuration EMI data was measured on 51 adjacent agricultural fields (102 ha) near Selhausen (Germany). Each field was separately measured and six apparent electrical conductivity (ECa) maps with increasing depth of investigation were obtained. A supervised image classification method was applied to the ECa maps to obtain a 1 m resolution map of the study area that identifies 18 soil units with similar ECa signature. Afterwards, 100 ground truth locations were randomly selected and information on horizon type, depth and texture were collected until a maximum depth of 2 m. Statistical tests proved that each soil unit had unique soil characteristics in comparison to other units, thus confirming the effectiveness of the methodology in producing a highly detailed soil map in a complex environment that extends well beyond the field scale. To test its added value in agricultural applications, this geophysics-based soil map was used as input in agro-ecosystem simulations of crop growth and productivity for the 2016 growing season. For this, the one-dimensional AgroC model was used, which couples SoilCO<sub>2</sub>, RothC, and SUCROS subroutines to simulate crop growth. The necessary hydraulic parameters were estimated using pedotransfer functions. The leaf area index (LAI) of six crops simulated with AgroC showed clear correlation with LAI observed in six RapidEye satellite images. At the same time, further AgroC simulations based on commonly available soil maps performed significantly worse in terms of RMSE, model efficiency, and R<sup>2</sup>. Following these encouraging results, further simulations were performed to quantify the costs and benefits of irrigation within the study area in 2016 in terms of economical profit and CO<sub>2</sub> sequestration. Despite the apparent added value of geophysics-based soil information, it was found that additional data recorded during the growing season would allow improving modelling and predictions, for example, through data assimilation. For this reason, the second case study considers a set-up with additional soil moisture sensors installed in two orchards near Agia (Greece). In each field, EMI and soil sampling were combined to inform the placement of SoilNet soil moisture sensor surrounding a cosmic-ray neutron probe. The purpose of this second case study is to integrate soil data, hydrological modelling, and weather forecasts to provide farmers with an efficient decision support system that would enhance financial gains and sustainability of their irrigation practices in the long term.</p>

scholarly journals Water Quality Modeling of Mahabad Dam Watershed–Reservoir System under Climate Change Conditions, Using SWAT and System Dynamics

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 394 ◽  
Author(s):  
Mohammad Nazari-Sharabian ◽  
Masoud Taheriyoun ◽  
Sajjad Ahmad ◽  
Moses Karakouzian ◽  
Azadeh Ahmadi
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
System Dynamics ◽  
Water Conservation ◽  
Assessment Tool ◽  
Swat Model ◽  
Water Quality Modeling ◽  
Quality Data ◽  
Livestock Farming ◽  
Water Quality Data

The total phosphorus (TP) concentration, as the primary limiting eutrophication factor in the Mahabad Dam reservoir in Iran, was studied, considering the combined impacts of climate change, as well as the scenarios on changes in upstream TP loadings and downstream dam water allocations. Downscaled daily projected climate data were obtained from the Beijing Normal University Earth System Model (BNU-ESM) under moderate (RCP4.5) and extreme (RCP8.5) scenarios. These data were used as inputs of a calibrated Soil and Water Assessment Tool (SWAT) model of the watershed in order to determine the effects of climate change on runoff yields in the watershed from 2020 to 2050. The SWAT model was calibrated/validated using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). Moreover, to model TP concentration in the reservoir and to investigate the effects of upstream/downstream scenarios, along with forecasted climate-induced changes in streamflow and evaporation rates, the System Dynamics (SD) model was implemented. The scenarios covered a combination of changes in population, agricultural and livestock farming activities, industrialization, water conservation, and pollution control. Relative to the year 2011 in which the water quality data were available, the SD results showed the highest TP concentrations in the reservoir under scenarios in which the inflow to the reservoir had decreased, while the upstream TP loadings and downstream dam water allocations had increased (+29.9%). On the other hand, the lowest TP concentration was observed under scenarios in which upstream TP loadings and dam water allocations had decreased (−18.5%).

Multi-variable sensitivity and identifiability analysis for a complex environmental model in view of integrated water quantity and water quality modeling

2012 ◽  
Vol 65 (3) ◽  
pp. 539-549 ◽  
Author(s):  
Jiri Nossent ◽  
Willy Bauwens
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Process Model ◽  
Swat Model ◽  
Screening Method ◽  
Water Quality Modeling ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Latin Hypercube ◽  
Environmental Models

Environmental models are often over-parameterized. A sensitivity analysis can identify influential model parameters for, e.g. the parameter estimation process, model development, research prioritization and so on. This paper presents the results of an extensive study of the Latin-Hypercube–One-factor-At-a-Time (LH-OAT) procedure applied to the Soil and Water Assessment Tool (SWAT). The LH-OAT is a sensitivity analysis method that can be categorized as a screening method. The results of the sensitivity analyses for all output variables indicate that the SWAT model of the river Kleine Nete is mainly sensitive to flow related parameters. Rarely, water quality parameters get a high priority ranking. It is observed that the number of intervals used for the Latin-Hypercube sampling should be sufficiently high to achieve converged parameter rankings. Additionally, it is noted that the LH-OAT method can enhance the understanding of the model, e.g. on the use of water quality input data.

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