Background

The Bohai Sea located in the northwest corner of the Yellow Sea is one of the world’s most ecologically important and stressed bodies of water. The Bohai Sea suffers ecologically from over-fishing, pollution, and reduced inflow of freshwater from upstream basins. The Hai Basin is one of the seven basins that drain into the Bohai Sea.

Records of dried up channels in the basins show increasing evidence of the severity of overuse of surface water. The fast social and economic development has led to a strong competition between water users for the scarcely available resources. Since a large part of the surface water is being used by cities and industries the availability of water resources for agriculture has declined. Driven by a growing population, the acreage of irrigated farmlands has increased over the last decades. Agricultural water supply therefore mainly depends on groundwater. This has resulted in severe groundwater exhaustion. In parts of the plain the shallow groundwater table has dropped over 30 meters resulting in a sharp rise of irrigation costs and unsustainability of the food producing systems.

The Global Environment Fund (GEF) project on Integrated Water and Environment Planning and Management in the Hai Basin presents a new Remote Sensing based methodology to assess water shortages. Project results have shown that the most effective way to enhance stream flow out of the basin is to reduce evapotranspiration. A key element in the project is the establishment of real water savings program through an evapotranspiration reduction strategy, which will enhance the freshwater discharges into the Bohai Sea. Remote Sensing has proven to be an extremely useful tool to gain insight in spatial patterns of evapotranspiration; however there is a strong need be able to evaluate several intervention strategies (e.g. groundwater overdraft, irrigation, land use changes) on the downstream fresh water availability. A suitable tool to evaluate these strategies and to develop predictive capacity is the Soil and Water Assessment Tool (SWAT).

For this project FutureWater has set-up a SWAT model for the Hai Basin. At basin scale valuable conclusions are drawn about the partitioning of water in the different compartments of the water balance and the effects of anthropogenic interventions. This first model is set-up using global datasets and further fine tuning of the model can be done in the future through incorporating regional available datasets. The main objective of this study is to show the strength of hydrological modelling in water system analysis in the Hai Basin to explore options for reducing evapotranspiration.

Methodology

For the Hai Basin in China a SWAT model was built. To gain insight in the sensitivity of the model to important input parameters a sensitivity analysis for a number of parameters was conducted. The model was run for the baseline situation and one land use change / management scenario to illustrate the power of such tools in analyzing the complex interaction between land use and water resources. The model was calibrated using SEBAl Remotely Sensed evaporation data.

Figure 1. SWAT model.

SWAT represents all the components of the hydrological cycle including: rainfall, snow, snow-cover and snow-melt, interception storage, surface runoff, up to 10 soil storages, infiltration, evaporation, evapotranspiration, lateral flow, percolation, pond and reservoir water balances, shallow and deep aquifers, channel routing. It also includes irrigation from rivers, shallow and deep groundwater stores, ponds/reservoirs and rivers, transmission losses and irrigation onto the soil surface. It includes sediment production based on a modified version of the Universal Loss Equation and routing of sediments in river channels. SWAT tracks the movement and transformation of several forms of nitrogen and phosphorus in the watershed. It also tracks the movement and decay of pesticides. All include channel routing components and carrying of pollutants by sediments.

One of the major advances of the SWAT model is the enormous amount of detail and processes that can be dealt with. At the same time, relatively swift analysis of major processes can be assessed. This makes the model suitable to commence stakeholder interest and awareness by making quick and general runs, followed by detailed and more time-consuming water resources assessment and planning incorporating additional data.

Results and conclusions

The main results of the study can be viewed using the FutureWater webmapping tool.

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Dealing with the complexity of water resource management in the Hai Basin requires a systems approach which quantifies the partitioning of water in the different compartments of the hydrological system. Besides this quantification it also requires instruments which can evaluate the impact of management measures in the future. The SWAT model has demonstrated to be a valuable instrument in addressing these issues. Using mainly public domain datasets a hydrological model has been built with relative ease and the results are promising and realistic. Figure 3 shows an example of the monthly water balance for the irrigated winter wheat / maize rotation.

Figure 2. Monthly water balance irrigated winter wheat – corn.

The strength of an integrated modelling approach was shown explicitly in the scenario analysis. It was shown that there is almost a linear relationship between irrigation, actual evapotranspiration and groundwater table decline. The effects of irrigation on the water balance have been demonstrated. It does show that there is a lot of scope for reducing evapotranspiration. The model provides the tool to assess water conserving measures (e.g. deficit irrigation) without reducing crop yields. Now the initial base model is in place the next step is to refine the model with local available datasets. Figure 2 shows an example of the scenario analysis results.

Figure 3. Evapotranspiration per county (left is original scenario, right is 50% irrigation reduction)..

Please feel free to contact the Project Leader of this project for more information.