scholarly journals Quantifying the streamflow response to groundwater abstractions for irrigation or drinking water at catchment scale using SWAT and SWAT–MODFLOW

2020 ◽  
Vol 32 (1) ◽  
Author(s):  
Wei Liu ◽  
Seonggyu Park ◽  
Ryan T. Bailey ◽  
Eugenio Molina-Navarro ◽  
Hans Estrup Andersen ◽  
...  
Keyword(s):  
Drinking Water ◽  
Hydrological Model ◽  
Swat Model ◽  
Distributed Hydrological Model ◽  
Groundwater Abstraction ◽  
Catchment Scale ◽  
Model Complex ◽  
Streamflow Response ◽  
Further Development ◽  
Streamflow Depletion

Abstract Background Groundwater abstraction can cause a decline in the water table, and thereby affects surface streamflow connected to the aquifer, which may impair the sustainability of both the water resource itself and the ecosystem that it supports. To quantify the streamflow response to groundwater abstractions for either irrigation or drinking water at catchment scale and compared the performance of the widely used semi-distributed hydrological model SWAT and an recently integrated surface–subsurface model SWAT–MODFLOW, we applied both SWAT and SWAT–MODFLOW to a groundwater-dominated catchment in Denmark and tested a range of groundwater abstraction scenarios. Results To accommodate the study area characteristics, the SWAT–MODFLOW model complex was further developed to enable the Drain package and an auto-irrigation routine to be used. A PEST (parameter estimation by sequential testing)-based approach which enables simultaneous calibration of SWAT and MODFLOW parameters was developed to calibrate SWAT–MODFLOW. Both models demonstrated generally good statistical performance for the temporal pattern of streamflow, with better R2 and NSE (Nash–Sutcliffe efficiency) for SWAT–MODFLOW but slightly better PBIAS (percent bias) for SWAT. Both models indicated that drinking water abstractions caused some degree of streamflow depletion, while abstractions for returned irrigation led to a slight total flow increase, but may influence the hydrology outside the catchment. However, the streamflow decrease caused by drinking water abstractions simulated by SWAT was unrealistically low, and the streamflow increase caused by irrigation abstractions was exaggerated compared with SWAT–MODFLOW. Conclusion We conclude that the SWAT–MODFLOW model produces much more realistic signals relative to the SWAT model when quantifying the streamflow response to groundwater abstractions for irrigation or drinking water; hence, it has great potential to be a useful tool in the management of water resources in groundwater-dominated catchments. With further development of SWAT–MODFLOW and the PEST-based approach developed for its calibration, this study would broaden the SWAT–MODFLOW application and benefit catchment managers.

scholarly journals Comparing SWAT with SWAT-MODFLOW hydrological simulations when assessing the impacts of groundwater abstractions for irrigation and drinking water

2019 ◽  
Author(s):  
Wei Liu ◽  
Seonggyu Park ◽  
Ryan T. Bailey ◽  
Eugenio Molina-Navarro ◽  
Hans Estrup Andersen ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Resources ◽  
Groundwater Resources ◽  
Swat Model ◽  
Temporal Patterns ◽  
Simulation Performance ◽  
Model Complex ◽  
The Impact ◽  
Streamflow Depletion ◽  
Catchment Model

Abstract. Being able to account for temporal patterns of streamflow, the distribution of groundwater resources, as well as the interactions between surface water and groundwater is imperative for informed water resources management. We hypothesize that, when assessing the impacts of water abstractions on streamflow patterns, the benefits of applying a coupled catchment model relative to a lumped semi-distributed catchment model outweigh the costs of additional data requirement and computational resources. We applied the widely used semi-distributed SWAT model and the recently developed SWAT-MODFLOW model, which allows full distribution of the groundwater domain, to a Danish, lowland, groundwater-dominated catchment, the Uggerby River Catchment. We compared the performance of the two models based on the observed streamflow and assessed the simulated streamflow signals of each model when running four groundwater abstraction scenarios with real wells and abstraction rates. The SWAT-MODFLOW model complex was further developed to enable the application of the Drain Package of MODFLOW and to allow auto-irrigation on agricultural fields and pastures. Both models were calibrated and validated, and an approach based on PEST was developed and utilized to enable simultaneous calibration of SWAT and MODFLOW parameters. Both models demonstrated generally good performance for the temporal pattern of streamflow, albeit SWAT-MODFLOW performed somewhat better. In addition, SWAT-MODFLOW generates spatially explicit groundwater-related outputs, such as spatial-temporal patterns of water table elevation. In the abstraction scenarios analysis, both models indicated that abstraction for drinking water caused some degree of streamflow depletion, while abstraction for auto-irrigation led to a slight total flow increase (but a decrease of soil or aquifer water storages, which may influence the hydrology outside the catchment). In general, the simulated signals of SWAT-MODFLOW appeared more plausible than those of SWAT, and the SWAT-MODFLOW decrease in streamflow was much closer to the actual volume abstracted. The impact of drinking water abstraction on streamflow depletion simulated by SWAT was unrealistically low, and the streamflow increase caused by irrigation abstraction was exaggerated compared with SWAT-MODFLOW. We conclude that the further developed SWAT-MODFLOW model calibrated by PEST had a better hydrological simulation performance, wider possibilities for groundwater analysis, and much more realistic signals relative to the semi-distributed SWAT model when assessing the impacts of groundwater abstractions for either irrigation or drinking water on streamflow; hence, it has the potential to be a useful tool in the management of water resources in groundwater-affected catchments. However, this comes at the expense of higher computational demand and more time consumption.

scholarly journals Development of load duration curve system in data-scarce watersheds based on a distributed hydrological model

2019 ◽  
Vol 50 (3) ◽  
pp. 886-900
Author(s):  
Jia Wang ◽  
Xin-hua Zhang ◽  
Chong-Yu Xu ◽  
Hao Wang ◽  
Xiao-hui Lei ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
River Basins ◽  
Point Sources ◽  
Guizhou Province ◽  
Polluted Water ◽  
Distributed Hydrological Model ◽  
Load Duration ◽  
Load Duration Curve

AbstractMany developing countries and regions are currently facing serious water environmental problems, especially the lack of monitoring systems for medium- to small-sized watersheds. The load duration curve (LDC) is an effective method to identify polluted waterbodies and clarify the point sources or non-point sources of pollutants. However, it is a large challenge to establish the LDC in small river basins due to the lack of available observed runoff data. In addition, the LDC cannot yet spatially trace the specific sources of the pollutants. To overcome the limitations of LDC, this study develops a LDC based on a distributed hydrological model of the Soil and Water Assessment Tool (SWAT). First, the SWAT model is used to generate the runoff data. Then, for the control and management of over-loaded polluted water, the spatial distribution and transportation of original sources of point and non-point pollutants are ascertained with the aid of the SWAT model. The development procedures of LDC proposed in this study are applied to the Jian-jiang River basin, a tributary of the Yangtze River, in Duyun city of Guizhou province. The results indicate the effectiveness of the method, which is applicable for water environmental management in data-scarce river basins.

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals Assessment of Hydrological Parameters of the Watershed using ArcSWAT

2020 ◽  
Vol 9 (1) ◽  
pp. 599-602
Keyword(s):  
Climate Change ◽  
Surface Runoff ◽  
Hydrological Model ◽  
Swat Model ◽  
Ice Age ◽  
Western India ◽  
Distributed Hydrological Model ◽  
Hydrological Parameters ◽  
The Earth ◽  
Temperature Rate

Climate change is an inevitable phenomenon that has lead the earth to evolve from an ice age to present era. Due to rise in temperature, rate of Evapotranspiration is increasing that leads to higher rate of maximum event. This raises the need to analyse the watersheds which shows considerable vulnerability towards climate change. SWAT model is chosen to simulate the analysis which is a semi-distributed hydrological model. The model run has been carried out for 35 years where model outputs are compared with the observed values of Evapotranspiration. Model is successfully validated for five years giving NSE as 0.89. Calibrated & Validated model shows that average values of Evapotranspiration & Surface Runoff in mm against 882mm of rainfall are 303mm & 285mm respectively. A Hathmati watershed of western India is taken to demonstrate the work

scholarly journals Exploring the application of flood scaling property in hydrological model calibration

2021 ◽  
Author(s):  
Yanchen Zheng ◽  
Jianzhu Li ◽  
Ting Zhang ◽  
Youtong Rong ◽  
Ping Feng
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Flood Frequency ◽  
Efficiency Coefficient ◽  
Distributed Hydrological Model ◽  
Flood Peak ◽  
Scaling Property ◽  
Streamflow Data

Abstract Model calibration has always been one major challenge in hydrological community. Flood scaling property (FS) is often used to estimate the flood quantiles for data-scarce catchments based on the statistical relationship between flood peak and contributing areas. This paper investigates the potential of applying FS and multivariate flood scaling property (MLR) as constraints in model calibration. Based on the assumption that the scaling property of flood exists in four study catchments in Northern China, eight calibration scenarios are designed with adopting different combination of traditional indicators and FS or MLR as objective functions. The performance of the proposed method is verified by employing a distributed hydrological model, namely Soil and Water Assessment Tool (SWAT) model. The results indicate that reasonable performance could be obtained in FS with less requirements of observed streamflow data, exhibiting better simulation on flood peak than Nash-Sutcliffe efficiency coefficient calibration scenario. The observed streamflow data or regional flood information are required in MLR calibration scenario to identify the dominant catchment descriptors, and MLR achieve better performance on catchment interior points, especially for the events with uneven distribution of rainfall. On account of the improved performance on hydrographs and flood frequency curve at watershed outlet, adopting the statistical indicators and flood scaling property simultaneously as model constraints is suggested. The proposed methodology enhances the physical connection of flood peak among sub-basins and considers watershed actual conditions and climatic characteristics for each flood event, facilitating a new calibration approach for both gauged catchments and data-scarce catchments.

scholarly journals Assessment of surface water resources availability using catchment modelling and the results of tracer studies in the mesoscale Migina Catchment, Rwanda

2014 ◽  
Vol 18 (12) ◽  
pp. 5289-5301 ◽  
Author(s):  
O. Munyaneza ◽  
A. Mukubwa ◽  
S. Maskey ◽  
S. Uhlenbrook ◽  
J. Wenninger
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Hydrological Model ◽  
Model Parameters ◽  
Water Resources Planning ◽  
Distributed Hydrological Model ◽  
Hydrograph Separation ◽  
Catchment Scale ◽  
Streamflow Data ◽  
Resources Planning

Abstract. In the present study, we developed a catchment hydrological model which can be used to inform water resources planning and decision making for better management of the Migina Catchment (257.4 km2). The semi-distributed hydrological model HEC-HMS (Hydrologic Engineering Center – the Hydrologic Modelling System) (version 3.5) was used with its soil moisture accounting, unit hydrograph, liner reservoir (for baseflow) and Muskingum–Cunge (river routing) methods. We used rainfall data from 12 stations and streamflow data from 5 stations, which were collected as part of this study over a period of 2 years (May 2009 and June 2011). The catchment was divided into five sub-catchments. The model parameters were calibrated separately for each sub-catchment using the observed streamflow data. Calibration results obtained were found acceptable at four stations with a Nash–Sutcliffe model efficiency index (NS) of 0.65 on daily runoff at the catchment outlet. Due to the lack of sufficient and reliable data for longer periods, a model validation was not undertaken. However, we used results from tracer-based hydrograph separation from a previous study to compare our model results in terms of the runoff components. The model performed reasonably well in simulating the total flow volume, peak flow and timing as well as the portion of direct runoff and baseflow. We observed considerable disparities in the parameters (e.g. groundwater storage) and runoff components across the five sub-catchments, which provided insights into the different hydrological processes on a sub-catchment scale. We conclude that such disparities justify the need to consider catchment subdivisions if such parameters and components of the water cycle are to form the base for decision making in water resources planning in the catchment.

scholarly journals Uncertainty analysis of a spatially-distributed hydrological model with rainfall multipliers

2016 ◽  
Vol 43 (12) ◽  
pp. 1062-1074 ◽  
Author(s):  
Arpana Rani Datta ◽  
Tirupati Bolisetti
Keyword(s):  
Uncertainty Analysis ◽  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Error Model ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Input Uncertainty ◽  
Spatially Distributed ◽  
Input Error

This paper has developed an input error model to account for input uncertainty, and applied the rainfall multiplier approaches to the calibration and uncertainty analysis of Soil and Water Assessment Tool (SWAT), a spatially-distributed hydrological model. The developed input error model has introduced the season-dependent rainfall multipliers to the Bayesian framework and reduced the dimension of the posterior probability density function. The method is applied to a watershed located in Southwestern Ontario, Canada. The results of the developed method are compared with two other methods. The SWAT model parameters and the input error model parameters are jointly inferred by a Markov chain Monte Carlo sampler. The results show the measured precipitation data overestimates the true precipitation values for the study area. The uncertainty in model prediction is underestimated for high flows and overestimated for low flows. There is no significant change in the estimation of parameter uncertainty and streamflow prediction uncertainty in the developed method from those in the other methods. The study emphasizes that the rainfall multiplier approaches are applicable to spatially-distributed hydrological modelling for accounting of input uncertainty.

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