Integrated hydrological modeling to support basin-scale water resources management

Transcription

1 Integrated hydrological modeling to support basin-scale water resources management Yi Zheng School of Environmental Science and Engineering Southern University of Science and Technology, China October 27, 2016

2 Presentation Outline 1. Background and study area 2. Methods 3. Main results 4. Concluding remarks

3 Irrigation in arid and semi-arid areas Large water consumption Groundwater: a critical water source for both agricultural systems and natural ecosystems Irrigation Ecosystems sustained by groundwater GW pumping Wetland Desert vegetation Agricultural irrigation represents a significant human-nature water conflict in such areas!

4 Heihe River Basin (HRB) 2 nd largest inland river basin in China: ~130,000 km 2 Middle-lower dividing Pt.: Zhengyixia Upper-middle dividing Pt.: Yingluoxia

5 Upper Heihe (Qilianshan Mts.) Middle Heihe (farmlands with substantial irrigation) Lower Heihe (Gobi Desert) Terminal Lake (East Juyan Lake) Before 2000, the intensive flow diversion in the middle had caused serious ecological issues in the lower, e.g., vegetation degradation, dried terminal lakes, etc.

6 Water allocation curve (WAC) Since 2000, a water allocation plan has been enforced to protect the environmental flow towards the downstream Controversial! For the middle irrigation districts, even harder to meet the regulation in wet years! Flow to the lower Gobi area Actual cond. in Inflow from the upper mountain area

7 The middle HRB vs. the lower HRB Middle HRB Unregulated pumping Lower HRB Tradeoff between the groundwater levels in the middle and lower basins Increased pumping caused the GW decline in the middle HRB (Tian Y, Zheng Y*, et al., Water Resources Research, 2015)

8 The scientific question How integrated hydrological modeling could efficiently and effectively support basin-scale water resources management to address humannature water conflicts.

9 Presentation Outline 1. Background and study area 2. Methods 3. Main results 4. Concluding remarks

10 Improved GSFLOW GSFLOW: a physically-based fully integrated hydrological model developed by USGS Embedded an advanced hydraulic module to explicitly account for water diversion, pumping and irrigation Improved ET calculation (Tian Y, Zheng Y*, et al., Environmental Modelling & Software, 2015)

11 The GSFLOW model for the Zhangye Basin ~9,106 km 2 Surface: 104 subbasins, 588 Hydrological Response Units (HRUs) Subsurface: 5 layers, 9106 grids (1km 1km) each layer Average GW level Stream flow from Zhengyixia NSE=0.81 (Wu B, Zheng Y*, et al., Water Resources Research, 2014)

12 Surrogate modeling Computationally expensive model Surrogate model: Difficult to apply! Surrogate modeling (meta-modeling) approaches Analyses which require many model evaluations, such as optimization analysis, uncertainty analysis, etc. 1) To fully or partially replace the original complex model during the analysis 2) Computationally much cheaper than the original model 3) Usually in form of a response surface, such as support vector machine (SVM), radial basis function (RBF), etc. 12

13 A surrogate-based optimization approach Surrogate-based Optimization for Integrated surface water-groundwater Modeling (SOIM), which innovatively couples SVM and SCE-UA Only a couple of hundred of original model evaluations needed As effective as, but potentially more efficient than, DYCORS Benchmarking with DYCORS Framework of SOIM (Wu B, Zheng Y*, et al., Water Resources Research, 2015)

14 Optimization problems e.g., spatial optimization R: annual streamflow at Zhengyixia (i.e., the environmental flow for the lower HRB) S: annual GW storage change (+ increase, -decrease) X: proportions of GW in total irrigation water (pumping ratios) Scheme A: maximize R, provided a constraint on S Scheme B: maximize S, given a constraint on R 18 irrigation districts in the Zhangye Basin A B

15 Various scenarios considered e.g., spatial optimization For both schemes, we investigated multiple scenarios (i.e., different R or S constraints) Considered different hydrological conditions (i.e., inflow at Yingluoxia) taking into account the climate uncertainty

16 Presentation Outline 1. Background and study area 2. Methods 3. Main results 4. Concluding remarks

17 Spatially optimized pumping ratios Total ET reduction Basin-scale water saving More pumping in GW discharge areas and less in recharge areas (Wu B, Zheng Y*, et al., Water Resources Research, 2015) Changes of pumping ratio after the optimization

18 Water allocation curve (WAC) revisited S=-0.15 S=0 Given the existing WAC regulation, even with optimization, the middle HRB would still have to sacrifice its ecological health for that of the lower HRB. Otherwise, it must reduce its irrigation demand! (Wu B, Zheng Y*, et al., Water Resources Research, 2015)

19 Temporal optimization Changes of surface water ratio Use more groundwater in the dry season Groundwater reservoir! Use more surface water during the flood season (Wu X, Zheng Y*, et al., Agricultural Water Management, 2016)

20 Hydrological mechanisms of the optimization Increased pumping and enhanced groundwater recharge, which can lead to an ET reduction (Wu X, Zheng Y*, et al., Agricultural Water Management, 2016)

21 Quantifying the water conflict Inflow-outflow relationships after the temporal optimization To meet the WAC regulation, even with the optimization, the middle HRB needs to either encounter a 0.1 to 0.2 billion m 3 /year decrease of GW storage, or cut around 20% of its current irrigation water use to maintain its GW storage (Wu X, Zheng Y*, et al., Agricultural Water Management, 2016)

22 Presentation Outline 1. Background and study area 2. Methods 3. Main results 4. Concluding remarks

23 A simulation-optimization (SO) analysis can help identify potential solutions for real-world water conflicts The surrogate modeling approach makes it feasible to involve a physically based fully integrated hydrological model in decision-making Involving an integrated hydrological model helps reveal the underlying physical mechanisms to improve water resources management

24 Acknowledgments Funding sources: National Natural Science Foundation of China (grant no , , ) Data sources: Cold and Arid Regions Science Data Center of CAREERI/CAS (

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