A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China
Introduction
Global climatic change caused by growing atmospheric concentration of carbon dioxide and other trace gases has become evident (IPCC, 1995, Houghton et al., 2001, Kamga, 2001). Climate change or its increased variability is expected to alter the timing and magnitude of runoff. As a result it has important implications for existing water resources systems as well as for future water resources planning and management. For instance, under the climate change in recent years, the imbalance between water supply and water demands has been increasing, which has given rise to great attention from both the relevant authorities and the general public to water resources planning programs. Hence, urgent action is required for understanding and solving potential water resources problems for human's existence and well-being, especially, quantitative estimates of hydrological effects of climate change are essential.
In assessing climate change impacts, an important topic is the long-term forecasting of the water cycle changes and their spatial distribution, which includes two steps. The first step is to employ the general circulation models (GCMs) and regional climate models (RCMs) to produce the values of temperature and precipitation for each grid. The second step is the application of the macro-scale distributed hydrological models, normally the monthly water balance model, to each grid, for converting the projected rainfall into runoff. Generally, the monthly water balance model is mainly applied in three fields, i.e. reconstruction of the hydrology of basins, assessment of climatic change impacts, and evaluation of the seasonal and geographical patterns of water supply and irrigation demand (Xu and Singh, 1998).
Currently there are many different monthly water balance models and many researches in this field have been intensively conducted. In the 1940s and 1950s, Thornthwaite and Mather (1955) developed a set of deterministic monthly water balance models, in which only two parameters were used. In developing an index of meteorological drought, Palmer (1965) suggested a model that divides the soil moisture storage into two layers. In 1981, Thomas proposed a four-parameter abcd water balance model. Alley (1984) reviewed and examined the Thornthwaite–Mather models, the Palmer (1965) model, and the Thomas, 1981, Thomas et al., 1983 abcd models in considerable detail. He concluded that predication errors were relatively similar among these models. Gleick (1987) developed a monthly water balance model specifically for climate impact assessment and addressed the advantages of using water balance type models in practice. In the 1990s, more monthly water balance models were developed for studying the impact of climate change on the hydrological balance and for general water resources planning and management (Mimikou et al., 1991, Vandewiele et al., 1992, Guo, 1995, Guo and Yin, 1997, Panagoulia and Dimou, 1997, Xu and Singh, 1998, Xiong and Guo, 1997, Xiong and Guo, 1999).
For the purpose of water resources assessment and study of climate change impacts, a semi-distributed monthly water balance model was proposed and developed in this paper to simulate and predict the hydrological process and water resources in the macro-scale basins of China. GIS techniques were used as a tool to analyze topography, river networks, land-use, human activities, vegetation and soil characteristics. The model parameters were linked to these basin characteristics by regression and optimization methods. A parameterization scheme was developed and the model parameters were estimated for each grid element. Based on the different GCM and RCM outputs, the sensitivities of hydrology and water resources for China to global warming were studied.
Section snippets
A semi-distributed monthly water balance model
Xiong and Guo, 1997, Xiong and Guo, 1999 proposed and developed a two-parameter monthly water balance model. The model has been tested in 100 small and medium size basins in China and compared with other water balance models, including Belgium model (Vandewiele et al., 1992) and the Xinanjiang monthly model (Zhao, 1992). The two-parameter monthly water balance model proved to be quite efficient in simulating the monthly runoff with the simple structure. It was also shown that the two-parameter
Impact of climate change on water resources in China
Climate change or its variability is expected to alter the timing and magnitude of runoff. As a result, it has important implications for the existing water resources systems and for future water resources planning and management. Quantitative estimates of hydrological effects of climate change are essential for understanding and solving potential water resources problems (IPCC, 1995, McCarthy et al., 2001).
Three main types of climate scenarios have been employed in impact assessments:
Summary and discussion
A semi-distributed water balance model has been developed and applied to macro-scale basins in China. Based on GCM and RCM outputs, the sensitivity of hydrological and water resources system variables to global warming in China was investigated and analyzed. The main conclusions are summarized as follows:
- (1)
Climate change or its variability has important implications for the existing hydrological cycle and water resources system in China.
- (2)
The proposed semi-distributed and macro-scale water balance
Acknowledgements
This study was financially supported both by the National Key Basic Research Program of China (G19990436) and National Natural Science Foundation of China (50179026). We are grateful to editors and three anonymous reviewers whose comments and suggestions helped to clarify and improve the paper.
References (26)
- et al.
A simple model for estimating the sensitivity of runoff to long-term changes in precipitation without a change in vegetation
Adv. Water Resour.
(1999) - et al.
Regional hydrological effects of climate changes
J. Hydrol.
(1991) - et al.
River flow forecasting through conceptual models
J. Hydrol.
(1970) - et al.
Linking space-time scale in hydrological modeling with respect to global climate change: model properties and experimental design
J. Hydrol.
(1997) - et al.
Methodology and comparative study of monthly water balance models in Belgium, China and Burma
J. Hydrol.
(1992) On the treatment of evapotranspiration, soil moisture accounting and aquifer recharge in monthly water balance models
Water Resour. Res.
(1984)Evaporation into the Atmosphere: Theory, History and Applications
(1992)- et al.
Estimation of hydrological parameters at ungauged catchments
J. Hydrol.
(1993) The development and testing of a water balance model for climate impact assessment: modeling the Sacramento basin
Water Resour. Res.
(1987)Impact of climate change on hydrological balance and water resource systems in the Dongjiang Basin, China
IAHS Publication No. 231
(1995)
Uncertainty analysis of impact of climatic change on hydrology and water resource
Sustainability of Water Resource Under Increasing Uncertainty (Proceedings of Morocco Symposium, July 1997)
Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)
IPCC Second Report of Assessment of Climate Change
Cited by (163)
Insurance and climate change
2024, Current Opinion in Environmental SustainabilityImpacts of climate change and anthropogenic stressors on runoff variations in major river basins in China since 1950
2023, Science of the Total EnvironmentQuantification of the effects of conservation practices on surface runoff and soil erosion in croplands and their trade-off: A meta-analysis
2023, Science of the Total EnvironmentComprehensive evaluation of parameter importance and optimization based on the integrated sensitivity analysis system: A case study of the BTOP model in the upper Min River Basin, China
2022, Journal of HydrologyCitation Excerpt :Numerical model calibration has been a mandatory step in all aspects of hydrological and environmental sciences prior to water cycle scenario assessment (Azari et al., 2015; Meyer Oliveira et al., 2021), soil erosion simulation (Guo et al., 2002; Santos et al., 2012; Shirazi et al., 2020), drought and flood monitoring (Chen et al., 2016; Reddy and Singh, 2014), as well as water pollution assessment and prevention (Cho and Ha, 2010; Liang et al., 2015; Xia et al., 2019), which is always accomplished through parameter optimization.
Reconciling the water balance of large lake systems
2020, Advances in Water ResourcesCitation Excerpt :Global, continental, and basin-scale water balance modeling research typically focuses on improving representation of terrestrial and atmospheric physical processes collectively governing precipitation, evapotranspiration, and streamflow (Crow et al., 2008; Kim and Stricker, 1996; Milly and Dunne, 2017; Senay et al., 2011; Vörösmarty et al., 1998). This body of research, while providing foundational hydrologic data for much of the planet’s land surface, rarely explicitly resolves mass and energy fluxes over large freshwater surfaces (Makhlouf and Michel, 1994; Xu and Singh, 1998; Arnell, 1999; Guo et al., 2002). Put differently, we find that the primary physical processes driving the water balance of large lakes, including over-lake evaporation (i.e. turbulent heat fluxes), over-lake precipitation, and predominant channel lake inflows and outflows, are represented poorly (if at all) in large-scale terrestrial land surface models and corresponding data sets.