Abstract
Although previous studies have analyzed ecohydrological changes, external pressure sources on the ecohydrological regime have rarely been clarified, and knowledge about the individual impacts of large reservoir regulation is still insufficient. In this study, we reconstructed the natural flow in the middle reaches of the Yangtze River (MRYR) not regulated by the Three Gorges Reservoir (TGR) based on a long–short-term memory model. We then evaluated the dynamics of ecohydrological regimes using environmental flow components and ecohydrological risk indicators and quantified the impacts of the TGR. The results showed that the hydrological stability has increased after TGR construction, with significant decreases in the frequency and duration of extremely low-flows, large floods, and small floods. In addition, there is a high ecohydrological risk in the MRYR, with a higher ecodeficit and showing a continuous upward trend. The impact of the TGR on environmental flow components decreases along the river, averaging 42.1%, with the strongest impact on small floods, accounting for 56.2%. Overall, reservoir regulation has counteracted the increased eco-risk caused by climate change. Considering only the TGR, the ecosurplus in the spring and winter seasons increased, while the ecodeficit increased in the autumn season, with corresponding contribution rates of 81.4, 82.7, and 53.1%, respectively.
HIGHLIGHTS
Reconstructed the natural flow of the river without the influence of reservoirs.
Investigated the relationship between environmental flow patterns in response to reservoir construction.
Assessed the independent influence of reservoirs on daily flow processes throughout the year.
Separated the impacts of reservoir construction and natural factor changes on river ecohydrological components at long–short time scales.
Graphical Abstract
INTRODUCTION
Ecohydrological processes are an important driving force in the evolution of river ecosystems (Li et al. 2019; Bestgen et al. 2020; Wu et al. 2020). Climate change and human activities are two dominant factors causing changes in ecohydrology regimes (Zolfagharpour et al. 2020; Yang et al. 2022). Climate change mainly affects hydrological processes through factors such as temperature, precipitation, and evaporation, while human activities change the underlying surface of the watershed through land use, vegetation cover changes, and water conservancy projects, thereby indirectly changing the runoff mechanism (Sun et al. 2019; Xin et al. 2019; Sadeghi et al. 2020). Under the coupled action of climate change and human activities, the natural ecohydrological conditions of rivers consequently change, the species composition, habitat distribution, and corresponding ecological functions of the ecosystem are altered (Rolls et al. 2018; Thompson et al. 2021). When the change in habitat conditions exceeds the biological self-regulation and recovery capacity, species will face the threat of decline, endangerment, and extinction, resulting in the destruction of river ecosystems (Wang et al. 2015).
Given the critical role of natural hydrological regimes in protecting native species and maintaining ecological integrity, the ecological effects of river flows have received increasing attention (Suen 2011; Taylor et al. 2014; McGregor et al. 2018; van Oorschot et al. 2018; Bestgen et al. 2020). Richter et al. (2006) proposed the ‘environmental flow vocabulary’ that can fully assess flow changes and their ecological significance. Wang et al. (2016) qualitatively analyzed the changes in hydrological conditions of the Yangtze River before and after the construction of the Gezhouba and Three Gorges Reservoirs and the impact of these changes on aquatic biodiversity and fish community structure, particularly on migratory fish. Ma et al. (2019) proposed a river hydrological health assessment method covering different health states of river ecosystems based on different flow thresholds within the year. Therefore, from the perspective of hydrological fluctuations, a comprehensive evaluation of river ecohydrological events and ecohydrological risks is of great significance for adapting to the healthy management of rivers in a changing environment.
Climate change alters the regional water cycle processes. According to the Intergovernmental Panel on Climate Change (IPCC) report, global warming is 1.5 °C above pre-industrial levels and there have been substantial changes in indices related to extreme cold and hot events, as well as the duration of warm periods, as the climate continues to warm (IPCC 2022). Meanwhile, there exists a strong coupling effect between precipitation and temperature, and climate warming not only intensifies heatwaves but also induces drought conditions, aggravating the risk of ecological degradation (Liu et al. 2021; Zhang et al. 2021). In addition, for river ecosystems, the regulation of reservoirs has been proven to be one of the main sources of pressure for many rivers (van Oorschot et al. 2018; Best 2019; Zhang et al. 2022). However, previous research mainly focused on the broad impacts of climate change and human activities, mainly at the macroscopic scale (Xu et al. 2014; Fan et al. 2017; Yang et al. 2022). More reservoir construction and the continued coupling of climate warming will push organisms and ecosystems to the limit of resilience. In this context, the dynamic response mechanisms of key ecological hydrological variables to climate change and reservoir regulation should be further understood in detail.
As the largest hydro project in the world, the operation of the Three Gorges Reservoir (TGR) has changed the natural hydrological regimes of the middle reaches of the Yangtze River (MRYR) (Chen et al. 2016). Many scholars have used a variety of research methods to evaluate the impact of the TGR on river hydrology from different perspectives (Wu et al. 2012; Li et al. 2016; Tao et al. 2020; Xiong et al. 2020; Zhao et al. 2021). These studies mainly attribute the changes in hydrological and ecological indicators before and after reservoir impoundment or between upstream and downstream to the construction of the reservoir (Wang et al. 2016, 2020; Tian et al. 2019; Yu et al. 2019; Li et al. 2021). However, the approach does not take into account changes in natural factors such as climate and upstream inflows. As the main influencing factor of the hydrological cycle, the influence of natural factors on ecological flow is obvious and important (Cao et al. 2021; Wang et al. 2022). Therefore, it is necessary to restore the natural flow process that is not affected by TGR operation in the MRYR by modeling, which is necessary to quantify the driving force of the evolution of ecological hydrology, clarify the mechanism of TGR changing river ecosystems, and evaluate the multiple effects of the TGR on ecological hydrology in a comprehensive timescale.
In summary, the objective of this study is to investigate the impacts of large reservoir regulation on ecohydrological conditions. To achieve this, we (1) reconstructed the natural flow of the MRYR without TGR regulation using a long–short-term memory model, (2) evaluated the ecohydrological conditions of the MRYR using environmental flow components and ecohydrological risk indicators, and (3) quantified the impacts of the TGR and climate change on the ecohydrological conditions. The findings of this study improve our understanding of the evolving features and driving mechanisms of ecohydrological conditions under changing environments, and provide scientific evidence for guiding water resources management and ecosystem protection.
MATERIALS AND METHODS
Study area and data
The Yangtze River is 6,379 km long, with a basin area of 1.8 × 106 km2, accounting for one-fifth of China's total land area and a total water resource of 9.6 × 1012 m3, making it the largest river basin in China and the third longest river in the world. The main stream of the Yangtze River is the midstream section from Yichang to Hukou, with a length of 955 km and a basin area of 6.8 × 105 km2 (Figure 1). The climate of the basin is subtropical monsoon climate, and the main flood season usually occurs from June to August every year (Liu et al. 2018).
The TGR is the largest hydropower hub project in the world. The dam height is 181 m and the total reservoir capacity reaches 3.9 × 1010m3. Its operation has had a profound impact on runoff, sediment, and water temperature conditions downstream of the reservoir. Yichang Station is located 37 km downstream of the TGR, which is the water control station in the upper reaches of the Yangtze River and the water inflow control station in the middle reaches of the Yangtze River (MRYR). Luoshan Station is located in Baiji Dolphin National Nature Reserve in Xinluo Section of Yangtze River, which controls the ecological and hydrological situation in the reserve (Ban et al. 2014). Hankou Station is located at the confluence of the Han River and the Yangtze River, which is the main hydrological control station in the MRYR. Chenglingji and Xiantao are outlet control stations of Dongting Lake and Han River, respectively.
Flow data: The daily flow data of seven hydrological stations from 1965 to 2019, including Cuntan, Wulong, Yichang, Chenglingji, Luoshan, Xiantao, and Hankou, provided by the Yangtze River Water Conservancy Committee were selected.
Meteorological data: Daily meteorological data of Yichang, Luoshan and Hankou Stations from 1965 to 2019, including daily average temperature, daily rainfall, relative humidity, sunshine duration, and evaporation, the data come from the National Meteorological Science Data Center (https://data.cma.cn/).
The reconstruction method of the natural flow series without TGR regulation
Long–short-term memory model
Model architecture, evaluation parameters, and reliability verification
In order to quantitatively separate the independent effects of the TGR on the ecohydrological regime in the MRYR, different influencing factors need to be considered in the reconstruction of the flow at Yichang, Luoshan, and Hankou Stations. Therefore, the independent variable data used to drive the operation of the model are shown in Table 1.
The architecture of the flow model
Target . | Driven data . |
---|---|
Yichang | Flow data for Cuntan and Wulong Stations, meteorological data for Yichang |
Luoshan | Flow data for Cuntan, Wulong and Chenglingji Stations, meteorological data for Luoshan |
Hankou | Flow data for Cuntan, Wulong, Chenglingji and Xiantao Stations, meteorological data for Hankou |
Target . | Driven data . |
---|---|
Yichang | Flow data for Cuntan and Wulong Stations, meteorological data for Yichang |
Luoshan | Flow data for Cuntan, Wulong and Chenglingji Stations, meteorological data for Luoshan |
Hankou | Flow data for Cuntan, Wulong, Chenglingji and Xiantao Stations, meteorological data for Hankou |
In this study, the performance of the LSTM model is comprehensively evaluated based on the three indicators of root mean square error (RMSE), mean absolute percentage error (MAPE) and determination coefficient (R2). The specific significance and calculation formula of each indicator are shown in the literature (Graf et al. 2019; Pan et al. 2020; Van et al. 2020). Meanwhile, the 9-year flow data (1965–1974) are selected to verify the reliability of the flow process without the TGR in the reconstructed MRYR under different data drivers.
Validation results at Yichang, Luoshan, and Hankou stations
Station . | Train . | Test . | ||||
---|---|---|---|---|---|---|
MAPE (%) . | RMSE . | R2 . | MAPE (%) . | RMSE . | R2 . | |
Yichang | 8.70 | 1,206.7 | 0.9870 | 10.20 | 1590.9 | 0.9788 |
Luoshan | 5.65 | 1,308.8 | 0.9890 | 6.98 | 1,739.3 | 0.9812 |
Hankou | 5.09 | 1,288.3 | 0.9907 | 5.82 | 1,561.8 | 0.9852 |
Station . | Train . | Test . | ||||
---|---|---|---|---|---|---|
MAPE (%) . | RMSE . | R2 . | MAPE (%) . | RMSE . | R2 . | |
Yichang | 8.70 | 1,206.7 | 0.9870 | 10.20 | 1590.9 | 0.9788 |
Luoshan | 5.65 | 1,308.8 | 0.9890 | 6.98 | 1,739.3 | 0.9812 |
Hankou | 5.09 | 1,288.3 | 0.9907 | 5.82 | 1,561.8 | 0.9852 |
Assessing the ecohydrological regime alteration
Environmental flow components
Environmental flow components (EFC) are the flow and its processes required to maintain the ecological environment of rivers, including low-flow, extreme low-flow, high-flow pulses, small floods, and large floods, a total of 34 ecologically significant indicators in five groups (Table 3). The inter-annual fluctuation of river flow patterns can be described in detail by EFC, and the threshold division of flow events related to EFC can be found in Richter & Thomas (2007).
Indicators used in EFC and ecological function
Groups . | Indicators . | Ecological function . |
---|---|---|
Low-flow (1–12) | Monthly low-flow | Maintain groundwater levels in floodplains, provide drinking water for terrestrial animals, etc. |
Extreme low-flow (13–16) | Peak, duration, timing, frequency | Expand the species of floodplain plants and prevent the invasion of alien species, etc. |
High-flow pulse (17–22) | Peak, duration, timing, frequency, rise rate, fall rate | Shape physical characteristics of river course and maintain normal water quality conditions, etc. |
Small flood (23–28) | Peak, duration, timing, frequency, rise rate, fall rate | Provide clues to fish migration and spawning, recharge water levels in flooding areas, control the population structure and distribution of floodplain plants, etc. |
Large flood (29–34) | Peak, duration, timing, frequency, rise rate, fall rate | Maintain the balance of species in aquatic and riparian communities, and promote material exchange in channels and floodplains, etc. |
Groups . | Indicators . | Ecological function . |
---|---|---|
Low-flow (1–12) | Monthly low-flow | Maintain groundwater levels in floodplains, provide drinking water for terrestrial animals, etc. |
Extreme low-flow (13–16) | Peak, duration, timing, frequency | Expand the species of floodplain plants and prevent the invasion of alien species, etc. |
High-flow pulse (17–22) | Peak, duration, timing, frequency, rise rate, fall rate | Shape physical characteristics of river course and maintain normal water quality conditions, etc. |
Small flood (23–28) | Peak, duration, timing, frequency, rise rate, fall rate | Provide clues to fish migration and spawning, recharge water levels in flooding areas, control the population structure and distribution of floodplain plants, etc. |
Large flood (29–34) | Peak, duration, timing, frequency, rise rate, fall rate | Maintain the balance of species in aquatic and riparian communities, and promote material exchange in channels and floodplains, etc. |
Note: Numbers 1–34 represent various indicators.
The deviation factor FD represents the deviation of each index value before and after man-made interference relative to the reference period, and the FD of each index is calculated as in the following equation:
Risk of ecohydrological condition
Referring to Gao et al. (2012), the flow series in the MRYR from 1965 to 2002 was used as the base period flow that was not affected by the impoundment of the TGR. The threshold FDC was constructed according to the rearranged 25% quantile and 75% quantile of daily flow in the base period, as the flow target for river ecological protection. The ecosurplus in the target year is defined as the portion above 75% FDC, and the ecodeficit is defined as the portion below 25% FDC. In order to eliminate the large magnitude difference of observed flow at different research stations, the ecosurplus and ecodeficit are divided by the areas below 75 and 25% FDC, respectively, for normalization (Wang et al. 2017).
Ecohydrological regimes transition caused by TGR regulation
Hydrological scenarios setting
According to the flow reconstruction method, the natural flow change process of the MRYR without the influence of the TGR is obtained. Then, combined with 34 environmental flow parameters and ecological flow indicators, a variety of flow reconstruction scenarios (Table 4) were set up, and the comparison of each group of scenarios was used to quantitatively evaluate the impacts of the TGR operation and changes in other natural factors on the ecological and hydrological situation.
Different scenarios of flow in the MRYR
Groups . | Scenarios . | Flow process in the MRYR . |
---|---|---|
Group 1 | Q1 | Measured flow process from 1965 to 2002 (Obspre-TGR) |
Q2 | Measured flow process from 2003 to 2019 (Obspost-TGR) | |
Q3 | Reconstruction flow process 1965–2002 (Simpre-TGR) | |
Q4 | Reconstruction flow process 2003–2019 (Simpost-TGR) | |
Group 2 | S1 | Measured EFC changes |
S2 | Variation of EFC only under the influence of changes in natural factors | |
S3 | EFC changes under TGR influence | |
Group 3 | E1 | Measured changes in ecosurplus and ecodeficit |
E2 | Variation of ecosurplus and ecodeficit only under the influence of changes in natural factors | |
E3 | Ecosurplus and ecodeficit changes under TGR influence |
Groups . | Scenarios . | Flow process in the MRYR . |
---|---|---|
Group 1 | Q1 | Measured flow process from 1965 to 2002 (Obspre-TGR) |
Q2 | Measured flow process from 2003 to 2019 (Obspost-TGR) | |
Q3 | Reconstruction flow process 1965–2002 (Simpre-TGR) | |
Q4 | Reconstruction flow process 2003–2019 (Simpost-TGR) | |
Group 2 | S1 | Measured EFC changes |
S2 | Variation of EFC only under the influence of changes in natural factors | |
S3 | EFC changes under TGR influence | |
Group 3 | E1 | Measured changes in ecosurplus and ecodeficit |
E2 | Variation of ecosurplus and ecodeficit only under the influence of changes in natural factors | |
E3 | Ecosurplus and ecodeficit changes under TGR influence |
Group 1: Comparing Q1 and Q3, the reliability of the LSTM model to reconstruct the natural flow process in the MRYR that is not affected by the TGR is evaluated. Comparing Q2 and Q4, the flow changes caused by the operation of the TGR are evaluated.
Group 2: Define the thresholds of each EFC indicator according to the base period Q1. The deviation factors S1 and S2 of the 34 EFC indicators under the Q2 and Q4 scenarios were obtained, respectively. The effect of the TGR was then quantitatively differentiated by comparing S1 and S2.
Group 3: The 25 and 75% FDCs were determined according to the base period Q1 and the ecosurplus and ecodeficit at the annual and seasonal scales were calculated from the FDC quantile curves of the base period in Q2 and Q4. By comparing Q1 and Q2, the changes in the measured ecosurplus and ecodeficit in the MRYR can be analyzed (E1). Comparing Q1 and Q4, quantify the ecohydrological regime under the influence of changes in natural factors (E2). By comparing E1 and E2, the effect of the TGR operation can be quantitatively distinguished.
Attribution analysis
RESULTS
Effects of the TGR on the intra-annual flow process
Reconstruction results of flow process
Station . | Pre-TGR . | Post-TGR . | ||||
---|---|---|---|---|---|---|
MAPE (%) . | RMSE . | R2 . | MAPE (%) . | RMSE . | R2 . | |
Yichang | 13.33 | 1,522.1 | 0.9796 | 18.18 | 3,083.4 | 0.8698 |
Luoshan | 8.96 | 2,106.3 | 0.9721 | 11.44 | 2,423.1 | 0.9451 |
Hankou | 9.53 | 1,986.6 | 0.9781 | 13.37 | 2,660.0 | 0.9406 |
Station . | Pre-TGR . | Post-TGR . | ||||
---|---|---|---|---|---|---|
MAPE (%) . | RMSE . | R2 . | MAPE (%) . | RMSE . | R2 . | |
Yichang | 13.33 | 1,522.1 | 0.9796 | 18.18 | 3,083.4 | 0.8698 |
Luoshan | 8.96 | 2,106.3 | 0.9721 | 11.44 | 2,423.1 | 0.9451 |
Hankou | 9.53 | 1,986.6 | 0.9781 | 13.37 | 2,660.0 | 0.9406 |
Comparison of measured and reconstructed flows in Yichang, Luoshan and Hankou before and after the construction of the TGR.
Comparison of measured and reconstructed flows in Yichang, Luoshan and Hankou before and after the construction of the TGR.
For the Luoshan Station, the influence of the TGR is mainly significant from January to June and September to October due to the regulation of lake. For the downstream Hankou station, the TGR's impact is mainly significant in September and October, and the impact is alleviated by climate changes and the convergence of tributaries during other months. Table 4 shows that the changes in the MAPE and RMSE for the measured and reconstructed values at the Luoshan and Hankou Stations were smaller than those at the Yichang Station, with the MAPE increasing from 8.96% and 9.53% during the pre-TGR period to between 11.44 and 13.37% during the post-TGR period, and the RMSE increasing from 2,106 and 1,987 m3/s to 2,423 and 2,660 m3/s, respectively. R2 also decreased from 0.9721 and 0.9781 to 0.9451 and 0.9406, respectively. These changes indicate that the impact of the TGR on downstream flow decreases with distance.
The potential impacts of the TGR on the EFCs
Multi-scenario alteration of EFCs
Comparison of measured and simulated environmental flows in the MRYR (a: Yichang; b: Luoshan and c: Hankou).
Comparison of measured and simulated environmental flows in the MRYR (a: Yichang; b: Luoshan and c: Hankou).
Comparing the environmental flow structure of the measured S1 and the non-TGR-affected S2, the impact of the TGR operation on the environmental flow was quantitatively distinguished. The results show that the reservoir has a strong simplification impact on the annual flow events in the downstream. Compared with S1, S2 has more abundant flow events, more small flood events, and frequent extreme low-flow events, especially the difference in Yichang Station. The above phenomena reflect the great flood control function and ecological water supplement function of the TGR, and the weakening influence on the ecological hydrological situation along the MRYR.
The deviation factor of environmental flow in the MRYR after the operation of the TGR (1–34 correspond to 34 environmental flow parameters).
The deviation factor of environmental flow in the MRYR after the operation of the TGR (1–34 correspond to 34 environmental flow parameters).
Quantifying the impacts of the TGR along the river reach
The relative contribution of the TGR to EFCs
EFC . | Yichang . | Luoshan . | Hankou . | Mean . |
---|---|---|---|---|
Low-flow (%) | 62.7 | 48.6 | 42.7 | 51.3 |
Extreme low-flow (%) | 44.2 | 45.3 | 37.6 | 42.4 |
High-flow pulse (%) | 56.8 | 41.7 | 56.2 | 51.6 |
Small flood (%) | 86.3 | 34.9 | 47.3 | 56.2 |
Large flood (%) | 0.00 | 0.00 | 0.00 | 0.00 |
ALL (%) | 52.6 | 36.0 | 37.7 | 42.1 |
EFC . | Yichang . | Luoshan . | Hankou . | Mean . |
---|---|---|---|---|
Low-flow (%) | 62.7 | 48.6 | 42.7 | 51.3 |
Extreme low-flow (%) | 44.2 | 45.3 | 37.6 | 42.4 |
High-flow pulse (%) | 56.8 | 41.7 | 56.2 | 51.6 |
Small flood (%) | 86.3 | 34.9 | 47.3 | 56.2 |
Large flood (%) | 0.00 | 0.00 | 0.00 | 0.00 |
ALL (%) | 52.6 | 36.0 | 37.7 | 42.1 |
Contributions of TGR and changes in natural factors to the variation of 34 environmental flow indicators in the MRYR.
Contributions of TGR and changes in natural factors to the variation of 34 environmental flow indicators in the MRYR.
On the numerical side, the FD of low-flow from September to November decreased under TGR regulation, especially in October (−10.29%), with the highest increase of 19.88% in January. Under the impact of the TGR, the frequency of extreme low-flow was significantly reduced (−244.34%), which far exceeded the 159.60% influence of natural factors change. The TGR also showed a positive effect on high-flow pulses, in which the FD of the rise rate changed by 49.01% under the influence of the reservoir, while the impact of natural factors change was basically 0. In addition, since the occurrence of large flood events has not been observed in the statistical years (2003–2019) in the post period of the TGR construction, the contribution of the TGR to its changes is still counted as 0.
The potential impacts of the TGR on the ecohydrological risk
Changes in the ecosurplus and ecodeficit
Distribution characteristics of FDC in the MRYR at different time scales (a: Yichang; b: Luoshan and c: Hankou).
Distribution characteristics of FDC in the MRYR at different time scales (a: Yichang; b: Luoshan and c: Hankou).
Evolution characteristics of ecosurplus and ecodeficit at different time scales in the MRYR.
Evolution characteristics of ecosurplus and ecodeficit at different time scales in the MRYR.
Quantifying the impacts of the TGR
Comparing E1 and E2, the contribution of the TGR and natural factors to the changes of ecosurplus and ecodeficit indicators in the MRYR in the temporal and spatial patterns were quantified. According to the fitting results of Figure 9(E2), in the scenario without the TGR operation, upstream inflow and climate change mainly caused the increase of ecodeficit in Yichang, reflecting the decrease of low-flow hydrological magnitude. For the other two river sections affected by tributary confluence, the ecosurplus in spring and winter had similar periodic changes. Before 2000, the fluctuation of ecosurplus decreased and then increased. In summer and autumn, the ecodeficit generally showed an increasing trend, especially in the autumn with the largest change.
Effects of natural factor changes and TGR on ecohydrological risk indicators in Yichang, Luoshan and Hankou Stations.
Effects of natural factor changes and TGR on ecohydrological risk indicators in Yichang, Luoshan and Hankou Stations.
Affected by the reservoir, the changes of ecological indicators in Yichang were significantly higher than those in the downstream stations, and the impact of the TGR on the MRYR generally showed a decrease in space along the route (Figure 10). At the same time, the changes of ecological surplus and ecological deficit of the three monitoring sections in the MRYR are synchronized in the time domain, and the peak-to-valley changes of ecological surplus and ecological deficit also have a significant negative correlation. The operation of the TGR to a certain extent leads to an average increase of 0.015 in annual ecosurplus and an average decrease of 0.002 in ecodeficit, which are generally beneficial to the ecological hydrological regime in the MRYR (Table 7). Because the application of the TGR was mainly carried out in spring and winter, the ecological surplus of downstream reservoir increased significantly, which increased by 0.057 and 0.11, respectively. In the summer flood season, the TGR flood control task requires its peak flow. When the inflow is lower than the flood control target, the water level of the reservoir area is reduced to 145 m by increasing the discharge, and then the water is equal to the discharge. Therefore, the TGR has little influence on the downstream ecological indicators in this period, and it mainly contributes to the reduction of the ecological deficit by 0.01. In autumn, in order to meet the requirements of power generation, the reservoir began to store water, and the discharge was much lower than the inflow, resulting in a decrease in the downstream ecological surplus and a substantial increase in the ecological deficit, and the growth rate reached the annual maximum (0.051).
Quantification of changes in ecohydrological risk indicators in the middle reach of the Yangtze River
Time scale . | Actual change . | Contribution of TGR . | Contribution of natural factors . | |||
---|---|---|---|---|---|---|
Ecosurplus . | Ecodeficit . | Ecosurplus . | Ecodeficit . | Ecosurplus . | Ecodeficit . | |
Annual | 0.000 | 0.032 | 0.015 (50%) | − 0.002 (5.6%) | − 0.015 (50.0%) | 0.034 (94.4%) |
Spring | 0.044 | − 0.013 | 0.057 (81.4%) | − 0.013 (92.9%) | − 0.013 (18.6%) | − 0.001 (7.1%) |
Summer | − 0.018 | 0.028 | 0.004 (16.0%) | − 0.010 (20.8%) | − 0.021 (84.0%) | 0.038 (79.2%) |
Autumn | − 0.025 | 0.096 | − 0.001 (4.0%) | 0.051 (53.1%) | − 0.024 (96.0%) | 0.045 (46.9%) |
Winter | 0.132 | − 0.014 | 0.110 (82.7%) | − 0.011 (78.6%) | 0.023 (17.3%) | − 0.003 (21.4%) |
Time scale . | Actual change . | Contribution of TGR . | Contribution of natural factors . | |||
---|---|---|---|---|---|---|
Ecosurplus . | Ecodeficit . | Ecosurplus . | Ecodeficit . | Ecosurplus . | Ecodeficit . | |
Annual | 0.000 | 0.032 | 0.015 (50%) | − 0.002 (5.6%) | − 0.015 (50.0%) | 0.034 (94.4%) |
Spring | 0.044 | − 0.013 | 0.057 (81.4%) | − 0.013 (92.9%) | − 0.013 (18.6%) | − 0.001 (7.1%) |
Summer | − 0.018 | 0.028 | 0.004 (16.0%) | − 0.010 (20.8%) | − 0.021 (84.0%) | 0.038 (79.2%) |
Autumn | − 0.025 | 0.096 | − 0.001 (4.0%) | 0.051 (53.1%) | − 0.024 (96.0%) | 0.045 (46.9%) |
Winter | 0.132 | − 0.014 | 0.110 (82.7%) | − 0.011 (78.6%) | 0.023 (17.3%) | − 0.003 (21.4%) |
DISCUSSIONS
The natural fluctuation of flow determines the material cycle, energy transfer, and the interaction between habitats and organisms of the river ecosystems (Hart & Finelli 1999; Zhang et al. 2015; Wang et al. 2022). This study found that the TGR led to different degrees of frankness in the annual flow process of each river section in the MRYR, and its influence effect decreased along the course, which was in line with the existing research results (Chen et al. 2016; Liu et al. 2018). According to our assessment of the ecological response of the MRYR, after the TGR impoundment, the hydrological stability of the MRYR is enhanced, and no extreme low-flow and large flood events occur, and the duration and frequency of small floods are significantly reduced (Figure 5). Meanwhile, the ecodeficit in the MRYR shows an increasing trend on an annual scale. In spring and winter, the magnitude of low-flow increases, which reduces the ecodeficit and increases the ecosurplus. In autumn, the magnitude of the low-flow decreases, resulting in a significant increase in the ecodeficit (Figure 9(E2)).
The disappearance of the extreme low-flow event means that the survival pressure of organisms such as macrophytes, algae and fish is relieved (Zeng et al. 2018). However, the disappearance of large floods and the obvious indigenous changes of small floods will lead to the decline of the self-purification capacity of rivers, reduce the lateral connectivity between rivers and flood areas, cause the fragmentation of large-scale habitats, and affect the natural reproduction of fish with drifting eggs (Yi et al. 2010; Zhao et al. 2021). The ecosurplus reflects the change of water regime of high-level flow, and its increase means the increase of the flow rate and the rise of the water level, which is conducive to the growth of submerged vegetation and the reproduction of viscous spawning fish (Baumgartner et al. 2018; Lei et al. 2022). But high-water levels can also crowd out living space for terrestrial creatures. The increase of ecological deficit reflects the change of water regime with low-flow rate. In dry season, this may be manifested as the continuous occurrence of ultra-low water level in the MRYR for many years. Although it is beneficial for some birds feeding on the rhizomes of submerged plants to obtain food, it will threaten the survival of benthic organisms (Gao et al. 2012). For vegetation, the original hygrophyte community will gradually evolve into the xerophyte community type (Han et al. 2017).
Under the strong interference of upstream inflow, regional climate, tributary catchment, and TGR, the ecological response process in the MRYR fluctuates greatly, the stability of river ecological structure, and the integrity of function are destroyed. The change of 34 inter-annual indicators and two intra-annual indicators also confirmed this conclusion. It is found that in terms of inter-annual indexes, the influence of the TGR is basically the same as that of natural factors (Table 6), and the relative contribution of the TGR to low-flow, high-flow pulse, and small flood events has exceeded the influence of natural factors. This feature is most obvious in Yichang, which clarifies the specific mechanism of reservoir regulation of river ecological response processes (Figure 7). In terms of intra-annual indexes, changes in natural factors in most cases lead to the decrease of ecosurplus and the increase of ecodeficit. The operation of the TGR increased the ecosurplus and decreased the ecodeficit at the annual scale in the MRYR, and its influence weakened along the way. On the seasonal scale, TGR mainly increases the ecosurplus in spring and winter in the MRYR by water supplement, and reduces the discharge in autumn to meet the power generation, resulting in a substantial increase in the ecological deficit.
However, there are still defects in this study. Both the EFC index and the ecosurplus and ecodeficit index cannot reflect the change process of the appropriate ecological flow in the year, so they cannot give specific protection objectives from the perspective of management. In the future, it is necessary to improve the accuracy of research methods according to the specific requirements of river ecological protection, and further deepen the research framework to give the flow process of river ecological protection.
CONCLUSIONS
This study comprehensively evaluated the temporal characteristics of the ecohydrological regime in the MRYR using the environmental flow components and ecohydrological risk indicators. Then, the natural flow regime of the MRYR without TGR was reconstructed based on the LSTM model. Combining the contribution evaluation method, the multiple effects of large-scale reservoir regulation on the transformation of ecohydrological regimes were examined. The results showed that after the TGR was constructed, the ecohydrological events in the MRYR were mainly composed of high-flow pulses and low-flow events. The frequency of small flood events has significantly decreased, especially at the Yichang Station. On an annual basis, the ecodeficit and ecosurplus of the three hydrological stations showed an increasing trend, with the former showing a stronger growth trend and higher average level, indicating an increase in potential ecohydrological risks.
TGR not only enhanced the singularity of ecohydrological events but also significantly reduced the frequency and duration of extremely low-flows and small flood events, showing a decreasing trend along the river. TGR had the greatest impact on small flood events, accounting for 12.4% higher than climate change, leading to the increase of the peak, rise and fall rate, and the significant decrease of duration and frequency, especially at the Yichang Station. Overall, 42.1% of the changes in the EFC coefficient were attributed to the reservoir. On an annual scale, TGR increased ecosurplus and slightly decreased ecodeficit, with contributions of 50.0 and 5.6%, respectively. On a seasonal scale, only considering the regulation of TGR, the ecosurplus in spring and winter in the MRYR increased, while the ecodeficit in autumn increased, with contributions of 81.4, 82.7, and 53.1%, respectively. Reservoir regulation resisted the increase of ecological risks caused by climate change, but climate change is still the dominant factor.
The study results demonstrate that the modeling method is an effective and reliable means to evaluate the impact of reservoir regulation on the hydrological regimes and quantify the specific effects of large-scale reservoirs, which were not fully considered in previous studies. In future work, more comprehensive ecohydrological indicators will be incorporated to analyze the ecohydrological effects of the basin under future climate scenarios. Combining with key ecological protection objectives, the ecohydrological response model of the basin will be established to ultimately determine multi-objective eco-flow management thresholds, providing solutions to maintain the health of river ecosystems and ease basin water use conflicts.
DATA AVAILABILITY STATEMENT
Data cannot be made publicly available; readers should contact the corresponding author for details.
CONFLICT OF INTEREST
The authors declare there is no conflict.