Jing River Research Articles

Assessment of extreme precipitation events and their teleconnections to El Niño Southern Oscillation, a case study in the Wei River Basin of China

Extreme precipitation index (EPI) is used to assess the extreme precipitation events, to further monitor and detect climate change impacts. The primary objective of the paper is to assess the extreme precipitation events and their spatiotemporal variability of 14 EPIs, and further investigate the linear and nonlinear relationships between typical EPIs and global climate anomalies El Niño Southern Oscillation (ENSO), using Niño 3.4 and SOI as climate indices, for the period of 1969–2016 in the Wei River Basin (WRB) of China. Observed daily precipitation data from 18 meteorological stations in the WRB were selected to calculate 14 EPIs derived or modified from core indices of the CCI/WCRP Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI). The trends of EPIs were estimated using Mann-Kendall non-parametric test. The teleconnections of ENSO to EPIs were revealed using principal component analysis (PCA), Pearson's correlation and wavelet analysis. Results indicate that: (1) The change patterns of extreme precipitation events varied for different EPIs and different meteorological stations for the period of 1969–2016 in the WRB. Four EPIs were negative trends dominated, and six EPIs were positive trends dominated, indicating that the extreme precipitation events had mainly increased for the past 48 years. (2) The spatial distributions of seven categories of trends were scattered and irregular for different EPIs and different areas of WRB. However, some of the EPIs had similar spatial distributions of trends. For example, the stations that had increasing trends mainly located at the northern part of WRB, especially in the Jing River Basin (JRB), for six precipitation intensity EPIs except R150, which was stationary trend dominated. (3) The nonlinear teleconnection relationships between typical EPIs and two climate anomalies revealed using wavelet analysis were consistent with linear relationships using correlation analysis. The Niño 3.4 and SOI had similar wavelet coherence but opposite phase difference with PC1 of typical EPIs. The phase differences between Niño 3.4 and PC1 of EPIs were anti-phase dominated, and in-phase dominated between SOI and PC1 of EPIs, indicating that the Niño 3.4 exerted negative climate impacts on the extreme precipitation events in the WRB and vice-versa for SOI. (4) The results should be beneficial to assess the extreme precipitation events, which provide references for the water resources planning and management in the WRB. It is possible to estimate and predict the future extreme precipitation events using climate models and global climate anomalies as potential predictors, which should be further studied in our future work.

A sustainable water-food-energy plan to confront climatic and socioeconomic changes using simulation-optimization approach

The provision of reliable water resources, safe grain production, and sustainable energy supply can be deemed as key guarantees for economic growth and human living improvement, but which have been challenged by imbalance relationship between increasing demand and limited supply capacity. In this study, a sustainable water-food-energy plan has been developed to conduct an optimal framework into a multiple water-reservoir system for confronting regional natural and artificial damages such as water deficit, food crisis and electric insufficient contemporarily. A simulation-optimization approach has been proposed to handle multiple uncertainties due to climatic and socioeconomic changes. The proposed approach has advantages of reflecting the climatic change in a lumped and conceptual way; meanwhile, it is effective to deal with socioeconomic uncertainties regarded as probability and possibility distributions, reducing the risk of decision-making with Green criterions. The developed water-food-energy plan with simulation-optimization approach can be applied to a real case study of Jing River, China. The obtained results of water-food-energy shortage, optimal water allocation-food production-energy generation, flood control, and system benefit under various policy-scenarios can be identify comprehensive water-food-energy alternatives in a multi-reservoir optimization system. Meanwhile, the results associated with credibility confidence, risk-averse attitude parameter and robustness coefficient can support the generation of a water-food-energy plan with a robust manner. It can support the improvement of water supply, irrigative production, energy generation, industrial pattern adjustment, flood risk control, supply capacity at a regional view, with aim to achieve sustainability of human activities and resource-energy conservation.

Estimation of the Fe and Cu Contents of the Surface Water in the Ebinur Lake Basin Based on LIBS and a Machine Learning Algorithm.

Traditional technology for detecting heavy metals in water is time consuming and difficult and thus is not suitable for quantitative detection of large samples. Laser-induced breakdown spectroscopy (LIBS) can identify multi-state (such as solid, liquid, and gas) substances simultaneously, rapidly and remotely. In this study, water samples were collected from the Ebinur Lake Basin. The water samples were subjected to LIBS to extract the characteristic peaks of iron (Fe) and copper (Cu). Most of the quantitative analysis of LIBS rarely models and estimates the heavy metal contents in natural environments and cannot quickly determine the heavy metals in field water samples. This study creatively uses the Fe and Cu contents in water samples and the characteristics of their spectral curves in LIBS for regression modelling analysis and estimates their contents in an unknown water body by using LIBS technology and a machine learning algorithm, thus improving the detection rate. The results are as follows: (1) The Cu content of the Ebinur Lake Basin is generally higher than the Fe content, the highest Fe and Cu contents found within the basin are in the Ebinur Lake watershed, and the lowest are in the Jing River. (2) A number of peaks from each sample were found of the LIBS curve. The characteristic analysis lines of Fe and Cu were finally determined according to the intensities of the Fe and Cu characteristic lines, transition probabilities and high signal-to-background ratio (S/B). Their wavelengths were 396.3 and 324.7 nm, respectively. (3) The relative percent deviation (RPD) of the Fe content back-propagation (BP) network estimation model is 0.23, and the prediction ability is poor, so it is impossible to accurately predict the Fe content of samples. In the estimation model of BP network of Cu, the coefficient of determination (R2) is 0.8, the root mean squared error (RMSE) is 0.1, and the RPD is 1.79. This result indicates that the BP estimation model of Cu content has good accuracy and strong predictive ability and can accurately predict the Cu content in a sample. In summary, estimation based on LIBS improved the accuracy and efficiency of Fe and Cu content detection in water and provided new ideas and methods for the accurate estimation of Fe and Cu contents in water.

Complexity Analysis of Precipitation and Runoff Series Based on Approximate Entropy and Extreme-Point Symmetric Mode Decomposition

Many regional hydrological regime changes are complex under the influences of climate change and human activities, which make it difficult to understand the regional or basin al hydrological status. To investigate the complexity of precipitation and the runoff time series from 1960 to 2012 in the Jing River Basin on different time scales, approximate entropy, a Bayesian approach and extreme-point symmetric mode decomposition were employed. The results show that the complexity of annual precipitation and runoff has decreased since the 1990sand that the change occurred in 1995. The Intrinsic Mode Function (IMF)-6 component decomposed by extreme-point symmetric mode decomposition of monthly precipitation and runoff was consistent with precipitation and runoff. The IMF-6 component of monthly precipitation closely followed the 10-year cycle of change, and it has an obvious correlation with sunspots. The correlation coefficient is 0.6, representing a positive correlation before 1995 and a negative correlation after 1995. However, the IMF-6 component of monthly runoff does not have a significant correlation with sunspots, and the correlation coefficient is only 0.41, which indicates that climate change is not the dominant factor of runoff change. Approximate entropy is an effective analytical method for complexity, and furthermore, it can be decomposed by extreme-point symmetric mode decomposition to obtain the physical process of the sequences at different time scales, which helps us to understand the background of climate change and human activity in the process of precipitation and runoff.

Study on the Movement Characteristics of Loess Landslide on the South Bank of Jing River

Through field work and data, the typical profile and internal structure of loess landslide in the south bank of Jing river are analyzed. Through the physical model experiment, the deformation and failure process of terrace formation can be drawn, and a similar terrace model is analyzed under different conditions. This reflects the internal structure of the movement process when the loess landslide movement push terraces, and analysis the influence of the main factors affecting this process.

Evaluation of potential evapotranspiration in the Weihe River Basin based on statistical downscaling

The Hargreaves method of using the average temperature (Tav) was used to calibrate the estimation of potential evapotranspiration (PE) for daily meteorological data of 35 weather stations from 1951 to 2015 in the Weihe River Basin and a statistical downscaling model was applied to downscale the Hadley Centre Sea-Atmosphere Coupled Model (HadCM3) output data to each station. The future temporal and spatial variations of temperature and evapotranspiration under different climate change scenarios were evaluated for the periods of 2016–2039, 2040–2069, and 2070–2099. The results show that the downscaling method is well suited for estimating the PE and that the PE in the Weihe River Basin is larger in May–July and smaller in autumn and winter. The mean annual temperature and annual PE exhibit an increasing trend for the high greenhouse gas emission scenario (RCP8.5) and low greenhouse gas emissions scenario (RCP4.5) and the magnitude of increase is greater for the RCP8.5 scenario. Greater increases in the PE were mainly distributed in the south of the Weihe River, the upper reaches of the Beiluo River, and the middle reaches of the Jinghe River, whereas most of the northern reaches of the Weihe River exhibited smaller changes that were located in the lower reaches of the Jing River. The regional distribution of the PE is consistent with the temperature changes. This study provides the basis for regional water resource management planning.

Application of numerical model in evaluating the effects of a planned reservoir on reach-scale bankfull discharge of the lower Wei River

Predicting the responses of an alluvial channel to changes in flow and sediment supply is essential for engineering design. Many methods have been developed in the last few decades to describe sectional bankfull characteristics (elevation and discharge); however, studies on long-term reach-scale bankfull discharge are still limited. In this study, a hydraulic model is built to calculate the reach-scale bankfull discharge, and the effects of reservoir building on downstream bankfull discharges are discussed. The studied river reach is located at the lower Wei River (WR), where the planned Dongzhuang Reservoir would be built on its largest tributary, the Jing River. A quasi-two-dimensional numerical model coupled with a bankfull discharge estimating method is put forward to calculate the reach-scale bankfull discharge. The soundness of the model is verified. Results show that the temporal variation of reach-scale bankfull discharge of the lower reach of the WR would be highly influenced by the planned reservoir, especially during the first 20 years of operation. The effect of the planned reservoir on bankfull discharge may reach its maximum when the total trapped sediment load reaches approximately 75% of the reservoir capacity. Our results show that after the first 17 years of operation, the effect of the planned reservoir on bankfull discharge of the river reach may decrease gradually. The soundness and predictive capability of the coupled model have also been calibrated by comparing with existing reservoirs. All analyses indicate that the numerical model can be used to predict the changed reach-scale bankfull discharge of the lower WR.

Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information

In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.

Spatial-temporal changes of rainfall erosivity in the loess plateau, China: Changing patterns, causes and implications

Rainfall erosivity is one of the key factors influencing soil erosion by water. Improved knowledge of rainfall erosivity is critical for prediction of soil erosion and the implementation of soil and water conservation plan as well as sediment management projects under climate change. In this study, the Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau in China was selected as a case study. Spatial-temporal changing patterns of rainfall erosivity in the JRB were first examined, followed by detailed investigations of the underlying causes through exploring the relations among annual rainfall, large-scale atmospheric circulation patterns and rainfall erosivity using the cross wavelet technique. Furthermore, implications of changing rainfall erosivity for sediment load and vegetation cover were analyzed. Results indicated that: (1) the year 1985 was a turning point in the time series of annual rainfall erosivity, demonstrating the non-stationary feature. Seasonal rainfall erosivity showed a spatial gradient with decrease from the upper to the lower stream. Rainfall erosivity was the largest in summer, and has increased significantly in the eastern basin; (2) annual rainfall erosivity showed a strong positive correlation with annual rainfall amount, implying that decrease of rainfall may have led to the reduction of rainfall erosivity in recent decades; (3) El Niño-Southern Oscillation and Pacific Decadal Oscillation were correlated with rainfall erosivity during 1982–1991, suggesting that large-scale atmospheric circulation patterns have strong influences on the changing patterns of rainfall erosivity; (4) changing rainfall erosivity had negligible impacts on the variation of vegetation cover (as indexed by the Normalized Differential Vegetation Index), but has detectable influence on sediment discharge which was further modulated by local soil and water conservation practice since the 1970s. These findings are helpful for prediction of soil erosion and adaptation strategies through local soil erosion control measures and sediment control projects.

River habitat assessment for ecological restoration of Wei River Basin, China.

As an important composition component of river ecosystems, river habitats must undergo quality assessment to potentially provide scientific basis for river ecological restoration. Substrate composition, habitat complexity, bank erosion degree, river meandering degree, human activity intensity, vegetation buffer width, water quality, and water condition were determined as indicators for river habitat assessment. The comprehensive habitat quality index (CHQI) was established for the Wei River Basin. In addition, the indicator values were determined on the basis of a field investigation at 12 national hydrological stations distributed across the Wei, Jing, and Beiluo Rivers. The analytic hierarchy process was used to determine the indicator weights and thus distinguish the relative importance of the assessment indicator system. Results indicated that the average CHQIs for the Wei, Jing, and Beiluo Rivers were 0.417, 0.508, and 0.304, respectively. The river habitat quality for the three rivers was well. As for the whole river basin, the river habitat quality for 25% of the cross section was very well, the other 25% was well, and the 50% remaining was in critical state. The river habitat quality of the Jing River was better than that of the Wei and Beiluo Rivers.

Assessment of Sediment Impact on the Risk of River Diversion during Dam Construction: A Simulation-Based Project Study on the Jing River, China

Dams are vital for water resource utilization, and river diversion is key for dam construction safety. As sandy river basins are important exploitation areas that have special diversion features, the impact of sediment on the risk of river diversion during dam construction should be assessed. Diversion uncertainty is the origin of diversion risk, and sediment uncertainty changes the storage and discharge patterns of the diversion system. Two Gumbel–Hougaard (GH) copula functions are adopted to couple the random variables of flood and sediment, so that the sediment impacts on diversion storage and discharge can be obtained by the sampling of flood peaks. Based on variable coupling and sediment amendment, a method of Monte Carlo simulation (MCS) with a water balance calculation can quantitatively assess the risk of sandy river diversion, by evaluating the probability of upstream cofferdam overtopping. By introducing one diversion project on the Jing River in China with a clear water contrast, the risk values of dam construction diversion with or without sediment impacts can be obtained. Results show that the MCS method is feasible for diversion risk assessment; sediment has a negative impact on the risk of river diversion during dam construction, and this degradation effect is more evident for high-assurance diversion schemes.

Interaction between landsliding materials and the underlying erodible bed in a loess flowslide

Loess landslides exhibit strong interactions with the terrace sediments of the Jing River on the South Jingyang Platform, Jingyang, Xi'an, China. Analysis of past landslide events revealed that the sand layer of this terrace was thrust up to the surface, accompanied by other terrace sediments of carrying. This led to the formation of a thrust nappe structure over a long distance. We performed ring shear tests to examine the shear behavior of this sand layer, with the finding that saturated sand was highly susceptible to liquefaction-induced failure. The groundwater level of the study area is high, resulting in near-saturation of the sand layer. Therefore, topographic interferences contributed additional variables and increased interaction complexities. Simulations indicated that the liquefied sand layer was compressed and forced. Due to the absence of constraints, the sand layer near the bottom of the slope was sheared out over a relatively short distance. On the other hand, particle interia and constraints of the stable layer resulted in the sand layer near the distal part of the deposits being sheared upward to the ground. Finally, an initiation-movement model of loess flowslides is proposed. It describes static liquefaction of the loess layer of the slope resulted in occurrence of flowslides. Collisions between the deposits from the platform edge slope and terrace sediments resulted in the shear liquefaction of sands. The landslide experienced four stages as they moved: scraping collisions, floating scrapes, folded thrusts, and nappe accumulation.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis.

Water quality is highly dependent on landscape characteristics. This study explored the relationships between landscape patterns and water quality in the Ebinur Lake oasis in China. The water quality index (WQI) has been used to identify threats to water quality and contribute to better water resource management. This study established the WQI and analyzed the influence of landscapes on the WQI based on a stepwise linear regression (SLR) model and geographically weighted regression (GWR) models. The results showed that the WQI was between 56.61 and 2886.51. The map of the WQI showed poor water quality. Both positive and negative relationships between certain land use and land cover (LULC) types and the WQI were observed for different buffers. This relationship is most significant for the 400-m buffer. There is a significant relationship between the water quality index and landscape index (i.e., PLAND, DIVISION, aggregation index (AI), COHESION, landscape shape index (LSI), and largest patch index (LPI)), demonstrated by using stepwise multiple linear regressions under the 400-m scale, which resulted in an adjusted R 2 between 0.63 and 0.88. The local R 2 between the LPI and LSI for forest grasslands and the WQI are high in the Akeqisu River and the Kuitun rivers and low in the Bortala River, with an R 2 ranging from 0.57 to 1.86. The local R 2 between the LSI for croplands and the WQI is 0.44. The local R 2 values between the LPI for saline lands and the WQI are high in the Jing River and low in the Bo River, Akeqisu River, and Kuitun rivers, ranging from 0.57 to 1.86.

A new method to evaluate floodwater for control/use in high-sediment rivers of Northwest China

Evaluating the quantity of flood season floodwater that is difficult to control or use in rivers with high sediment concentration is an important part of water resource evaluation and floodwater resource utilisation. This study proposes a method coupling water quantity and quality to evaluate such floodwater. The method divides floodwater into floodwater that is difficult to control (‘difficult-controllable’) and floodwater that is controllable but difficult to use (‘controllable but difficult-use’). A case study of the Bajiazui Reservoir in the Jing River in China’s Loess Plateau is presented. The average annual quantity of difficult-controllable floodwater is 10.4 million m3. The annual mean quantity of the difficult-controllable/-use floodwater is 38.1 million m3. The majority of that amount (78.21%) comprised controllable but difficult-use floodwater. An analysis of 64 combinations of factors influencing the quantity of the difficult-controllable/-use floodwater shows that the sediment concentration of run-off is the primary factor influencing the difficult-controllable/-use floodwater. The reservoir’s maximum flood release capacity and floodwater rejection coefficient are the primary factors affecting the difficult-controllable and controllable but difficult-use floodwater, respectively. The new evaluation method is superior to traditional methods and is suitable for evaluating difficult-controllable/-use floodwater in high-sediment rivers.

Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

Abstract. Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011–2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011–2040 to 1961–2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011–2040 to 1961–2005 increased by 1.25 ± 0.55. Streamflow variability was predicted to become greater over most months on the seasonal scale because of the increased monthly maximum streamflow and decreased monthly minimum streamflow. The increase in streamflow variability was attributed mainly to larger positive contributions from increased precipitation variances rather than negative contributions from increased mean temperatures.

Spatiotemporal variation in the attribution of streamflow changes in a catchment on China's Loess Plateau

Identifying the controlling factors of streamflow changes across space and time is important for water resources management. This study investigated the streamflow changes and related them to climate and land use in the Jing River catchment on China's Loess Plateau. The spatiotemporal attribution was examined with the Budyko framework through splitting the whole catchment/study period into subbasins/subperiods. The annual mean streamflow significantly decreased by 0.6–1.0mmyr−1 (p<0.05). Land surface change and climate variability decreased streamflow for most regions and periods. Over different regions, the land surface change accounted for 38–58% to the streamflow reduction; temporally, the contributions of land surface change are gradually increasing over time. The contributions of precipitation to streamflow change are much larger than those of potential evapotranspiration. The catchment characteristics parameter (w) in the Budyko framework is well correlated with the accumulative area fraction of forest and grassland, which provides a potential method to develop an empirical form for w.

Development of integrated approaches for hydrological data assimilation through combination of ensemble Kalman filter and particle filter methods

This study improved hydrologic data assimilation through integrating the capabilities of particle filter (PF) and ensemble Kalman filter (EnKF) methods, leading to two integrated data assimilation schemes: the coupled EnKF and PF (CEnPF) and parallelized EnKF and PF (PEnPF) approaches. The applicability and usefulness of CEnPF and PEnPF were demonstrated using a conceptual rainfall-runoff model. The performance of two new developed data assimilation methods and traditional EnKF and PF approaches was tested through a synthetic experiment and two real-world cases with one located in the Jing River basin and one located in the Yangtze River basin. The results show that both PEnPF and CEnPF approaches have more opportunities to provide better results for both deterministic and probabilistic predictions than traditional EnKF and PF approaches. Moreover, the computational time of the two integrated methods is manageable. But the proposed PEnPF may need much more time for some large-scale or time-consuming hydrologic models since it generally needs three times of model runs used by EnKF, PF and CEnPF.

A multi-reservoir based water-hydroenergy management model for identifying the risk horizon of regional resources-energy policy under uncertainties

In this study, a multi-reservoir based water-hydroenergy management (MWH) model is developed for planning water allocation and hydroenergy generation (WAHG) under uncertainties. A mixed fuzzy-stochastic risk analysis method (MFSR) is introduced to handle objective and subjective uncertainties in MWH model, which can couple fuzzy credibility programming and risk management within a general two-stage context, with aim to reflect the infeasibility risks between expected targets and random second-stage recourse costs. The developed MWH model (embedded by MFSR method) can be applied to a practical study of WAHG issue in Jing River Basin (China), which encounters conflicts between human activity and resource/energy crisis. The construction of water-energy nexus (WEN) is built to reflect integrity of economic development and resource/energy conservation, as well as confronting natural and artificial damages such as water deficit, electricity insufficient, floodwater, high sedimentation deposition contemporarily. Meanwhile, the obtained results with various credibility levels and target-violated risk levels can support generating a robust plan associated with risk control for identification of the optimized water-allocation and hydroenergy-generation alternatives, as well as flood controls. Moreover, results can be beneficial for policymakers to discern the optimal water/sediment release routes, reservoirs’ storage variations (impacted by sediment deposition), electricity supply schedules and system benefit plans with an effective/sustainable manner.

基于CMDAS驱动SWAT模式的精博河流域水文相关分量模拟、验证及分析

基于CMDAS驱动SWAT模式的精博河流域水文相关分量模拟、验证及分析