The Improved Reservoir Module of SWAT Model with a Dispatch Function and Its Application on Assessing the Impact of Climate Change and Human Activities on Runoff Change
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data
3. Methods
3.1. The Improved SWAT Model with the Dispatch Function
3.1.1. SWAT Model
3.1.2. The Dispatch Function
3.1.3. Evaluation Indicators
3.2. Attribution Analysis of the Impact of Reservoir Regulation and Climate Change on Runoff
3.2.1. Mann–Kendall Trend Test
3.2.2. Scenario Setting and Simulation Method
3.2.3. Quantitative Assessment of the Impact on Runoff
3.3. Runoff Change Prediction under Climate Change in the Next 30 Years
3.3.1. Selection of Typical GCMs
3.3.2. Runoff Prediction under Climate Change
4. Results
4.1. The Improved SWAT Model with a Dispatch Function
4.1.1. Hydrological Parameter Calibration before the Reservoir Impact Period
4.1.2. The Dispatch Function of Reservoirs
4.1.3. Evaluation of the Improved SWAT Based on Reservoir Inflow and Outflow Simulation
4.1.4. Evaluation of the Improved SWAT Based on Runoff Simulation at Hydrological Stations
4.2. Attribution Analysis on Runoff Changes
4.2.1. Trend Analysis of Runoff
4.2.2. Quantitative Assessment of the Impacts of Climate Change and Human Activities on Extreme Runoff
4.2.3. Quantitative Assessment of the Impacts of Climate Change and Human Activities on Mean Runoff
4.3. Prediction of Runoff Changes in Future under Climate Change Scenarios
4.3.1. Changes of Meteorological and Hydrological Elements in Future
4.3.2. Change Percentages of Simulated Runoff under Different Decades
5. Discussion
6. Conclusions
- (1)
- The dispatch function method exhibits superior performance in simulating reservoir outflow and runoff at hydrological stations compared to the original reservoir module in the SWAT model. The advantages of the dispatch function method are more pronounced when applied to reservoirs with greater regulation capacity.
- (2)
- The attribution analyses demonstrate that the operation of reservoirs leads to a certain reduction in the basin’s runoff volume. However, the positive impact of climate change on runoff is more pronounced and has a dominant effect on river runoff.
- (3)
- Over the next 30 years, both precipitation and temperature will increase compared to the base period (1970–2005), with a larger increase in precipitation. However, the changes in runoff do not follow a consistent pattern and exhibit a higher level of uncertainty. An increase in precipitation does not necessarily result in a proportional change in runoff.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Nomenclature
Abbreviations | Full Name |
BNU | Beijing Normal University Earth System Model |
CCSM4 | Community Climate System Model version 4 |
CMCC | Cambiamenti Climatici Climate Model |
CMIP5 | Coupled Model Intercomparison Project Phase 5 |
CSIRO | Commonwealth Scientific and Industrial Research Organisation |
DEM | Digital Elevation Model |
DHSVM | Distributed Hydrology Soil Vegetation Model |
GCM | Global Climate Model |
GFDL | Geophysical Fluid Dynamics Laboratory |
HEC-HMS | Hydrologic Engineering Center-Hydrologic Modeling System |
HIMS | Hydroinformatic Modeling System |
IPCC | Intergovernmental Panel on Climate Change |
IPSL | Institute Pierre Simon Laplace |
LARSIM | Large Area Runoff Simulation Model |
LULC | Land Use/Land Cover |
MIROC | Model for Interdisciplinary Research on Climate |
Pref | Reference period |
Ptest | Test period |
RCP | Representative Concentration Pathway |
SUFI-2 | Uncertainty in Sequential Uncertainty Fitting |
SWAT | Soil and Water Assessment Tool |
SWIM | Soil and Water Integrated Model |
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River System | Reservoir | Initial Water Storage Time | Normal Storage Water Level (m) | Regulation Performance | Total Reservoir Capacity (108 m3) |
---|---|---|---|---|---|
Middle reaches of the Jinsha River | Liyuan | 2014.11 | 1618 | weekly | 8.05 |
Jin’anqiao | 2010.11 | 1418 | weekly | 9.13 | |
Guanyinyan | 2014.10 | 1134 | weekly | 20.72 | |
Lower reaches of the Jinsha River | Xiluodu | 2013.5 | 600 | incomplete annual | 126.7 |
Xiangjiaba | 2012.10 | 380 | seasonal | 51.63 | |
Lower reaches of the Yalong River | Jinping I | 2012.11 | 1880 | annual | 77.6 |
Ertan | 1998.5 | 1200 | seasonal | 58 |
Datatype | Data Description | Source |
---|---|---|
DEM | The resolution of 200 m | Geospatial Data Cloud (http://www.gscloud.cn, accessed on 1 May 2020) |
Soil data | Harmonized World Soil Database (v1.1), with a resolution of 1000 m | Cold and Arid Regions Sciences Data Center at Lanzhou (http://westdc.westgis.ac.cn, accessed on 1 June 2020) |
Land-use data | Land-use dates of 1980, 1990, 2000, 2015, with the resolution of 1000 m | Resources and Environment Data Cloud Platform (http://www.resdc.cn, accessed on 1 June 2020) |
Meteorological data | Daily precipitation, min/max/average temperature, relative humidity, solar radiation, and wind speed from 30 weather stations in 1970–2018 | China Meteorological Science Data Center (http://data.cma.cn, accessed on 1 July 2020) |
Runoff data | Daily runoff data in 6 hydrological stations in 1970–2018 | Bureau of Hydrology, Changjiang Water Resources Commission |
Reservoir operation data | The storage capacity, daily inflow, outflow, and water level of 7 reservoirs | |
GCMs in CMIP5 | Daily precipitation, min/max/ The average temperature in 1970–2050 | Lawrence Livermore National Laboratory (https://esgf-node.llnl.gov, accessed on 1 July 2020) |
Scenarios | Reservoir Regulation | Climate Data | Mean Annual Simulated Runoff Depth (mm) |
---|---|---|---|
S1 | Pref | Pref | R1 (benchmark) |
S2 | Ptest | Pref | R2 (only influenced by reservoirs) |
S3 | Pref | Ptest | R3 (only influenced by climate) |
S4 | Ptest | Ptest | R4 (jointly influence) |
Stations | Water System | Calibration Period (1985–1997) | Validation Period (1970–1984) | ||||
---|---|---|---|---|---|---|---|
R2 | NSE | PBIAS (%) | R2 | NSE | PBIAS (%) | ||
Yajiang | Yalong River | 0.82 | 0.80 | –3.4 | 0.80 | 0.79 | 3.7 |
Xiaodeshi | Yalong River | 0.88 | 0.86 | 13.1 | 0.86 | 0.83 | 14.8 |
Shigu | Upper Jinsha River | 0.82 | 0.77 | 10.2 | 0.83 | 0.78 | 12.3 |
Panzhihua | Middle reaches of Jinsha River | 0.89 | 0.84 | –3.5 | 0.90 | 0.86 | 0.7 |
Huatan | Lower reaches of Jinsha River | 0.93 | 0.92 | 6.4 | 0.93 | 0.92 | 2.1 |
Pingshan | Lower reaches of Jinsha River | 0.94 | 0.92 | 11.0 | 0.93 | 0.91 | 13.3 |
Absolute average | 0.88 | 0.85 | 5.63 | 0.88 | 0.85 | 7.82 |
Reservoirs | Flood Season | Non-Flood Season | ||
---|---|---|---|---|
Dispatch Function | CC | Dispatch Function | CC | |
Ertan | 0.94 | 0.88 | ||
Jinping I | 0.93 | 0.97 | ||
Liyuan | 0.99 | 0.91 | ||
Jin’anqiao | 0.98 | 0.87 | ||
Guanyinyan | 0.96 | 0.91 | ||
Xiluodu | 0.94 | 0.90 | ||
Xiangjiaba | 0.97 | 0.95 |
Station | Yajiang | Shigu | Xiaodeshi | Panzhihua | Huatan | Pingshan | |
---|---|---|---|---|---|---|---|
Evaluation Period | 1998–2008 | 2011–2018 | 1999–2018 | 2011–2018 | 2011–2018 | 2011–2018 | |
Target storage capacity method | NSE | 0.84 | 0.77 | −0.78 | 0.69 | 0.57 | 0.37 |
R2 | 0.84 | 0.86 | 0.24 | 0.84 | 0.73 | 0.66 | |
PBIAS (%) | 2.6 | −10 | −3.2 | −17.9 | −4.2 | 0.9 | |
Without considering the reservoir influence | NSE | 0.84 | 0.77 | 0.52 | 0.71 | 0.75 | 0.73 |
R2 | 0.84 | 0.86 | 0.58 | 0.86 | 0.83 | 0.82 | |
PBIAS (%) | 2.6 | −10 | −5.4 | −18.4 | −5.3 | −1.2 | |
Dispatch function method | NSE | 0.84 | 0.77 | 0.67 | 0.72 | 0.84 | 0.78 |
R2 | 0.84 | 0.86 | 0.68 | 0.85 | 0.87 | 0.80 | |
PBIAS (%) | 2.6 | −10 | −3.1 | −17.8 | −4.0 | 1.4 |
Influence Rate (%) | Hydraulic Engineering | Climate Change | Joint Effect | |
---|---|---|---|---|
Panzhihua | 1d-max | −0.1 | 6.3 | 6.1 |
5d-max | −0.1 | 7.0 | 6.9 | |
15d-max | 0.2 | 9.4 | 9.4 | |
95% quant | 0.0 | 15.1 | 15.1 | |
Xiaodeshi | 1d-max | −10.7 | 8.2 | −1.2 |
5d-max | −8.9 | 8.8 | 0.5 | |
15d-max | −6.2 | 8.7 | 3.1 | |
95% quant | −7.6 | 9.6 | −0.2 | |
Pingshan | 1d-max | −5.4 | 5.4 | −0.2 |
5d-max | −5.1 | 5.5 | 0.2 | |
15d-max | −4.7 | 6.3 | 1.9 | |
95% quant | −4.2 | 11.0 | 6.2 |
Attribution Proportions (%) | Panzhihua | Xiaodeshi | Pingshan |
---|---|---|---|
Reservoir regulation | −2.0 | −11.3 | −10.6 |
Climate change | +102.0 | +111.3 | +110.6 |
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Sheng, S.; Chen, Q.; Li, J.; Chen, H. The Improved Reservoir Module of SWAT Model with a Dispatch Function and Its Application on Assessing the Impact of Climate Change and Human Activities on Runoff Change. Water 2023, 15, 2620. https://doi.org/10.3390/w15142620
Sheng S, Chen Q, Li J, Chen H. The Improved Reservoir Module of SWAT Model with a Dispatch Function and Its Application on Assessing the Impact of Climate Change and Human Activities on Runoff Change. Water. 2023; 15(14):2620. https://doi.org/10.3390/w15142620
Chicago/Turabian StyleSheng, Sheng, Qihui Chen, Jingjing Li, and Hua Chen. 2023. "The Improved Reservoir Module of SWAT Model with a Dispatch Function and Its Application on Assessing the Impact of Climate Change and Human Activities on Runoff Change" Water 15, no. 14: 2620. https://doi.org/10.3390/w15142620