ArticlePublisher preview available

Hydrological responses of three gorges reservoir region (China) to climate and land use and land cover changes

Springer Nature
Natural Hazards
Authors:
  • INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH,CAS
To read the full-text of this research, you can request a copy directly from the authors.

Abstract and Figures

Three Gorges Dam is the largest hydraulic infrastructure in the world, playing a pivotal role in flood mitigation. The hydrological responses of the Three Gorges Reservoir Region (TGRR) to climate change and human activities are unclear, yet critical for the Three Gorges Dam’s flood control and security. We simulated streamflow and water depth by coupling the Variable Infiltration Capacity model and the CaMa-Flood model. Daily discharge at the outlet of TGRR was well modeled with a relative error within 2% and a Nash-Sutcliffe efficiency coefficient of approximately 0.81. However, the flood peak was overestimated by 2.5–40.0% with a peak timing bias ranging from 5 days earlier to 2 days later. Runoff and water depth in the TGRR increased from 2015 to 2018 but decreased during flood seasons. Land use and land cover changes in 2015 (LUCC2015) and 2020 (LUCC2020) were analyzed to quantify their hydrological impacts. During the 2015–2018 period, land use conversion increased in built-up areas (+ 0.6%) and water bodies (+ 0.1%), but decreased in woodland grassland (-0.7%) and cropland (-0.1%). This led to a slight increase in runoff and inflow of less than 4‰ across the TGRR, a 7.70% decrease in average water depth, and a 15.4‰ increase in maximum water depth. Water depths in the TGRR decreased during flood seasons, and increased during non-flood seasons. Increasing water depth was identified in northern TGRR. This study clarifies the historical TGRR’s hydrological features under LUCC and climate changes, aiding regional flood mitigation in the TGRR.
This content is subject to copyright. Terms and conditions apply.
ORIGINAL PAPER
Received: 23 May 2024 / Accepted: 6 August 2024 / Published online: 14 August 2024
© The Author(s), under exclusive licence to Springer Nature B.V. 2024
Qiang Zhang
zhangq68@bnu.edu.cn
1 Faculty of Geographical Science, Beijing Normal University, Beijing, China
2 Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University,
Zhuhai, China
3 China Institute of Water Resources and Hydropower Research, Beijing, China
4 Department of Biological and Agricultural Engineering and Zachry Department of Civil &
Environmental Engineering, Texas A&M University, College Station, TX, USA
5 National Water and Energy Center, UAE University, Al Ain, UAE
Hydrological responses of three gorges reservoir region
(China) to climate and land use and land cover changes
YixinSun1· QiangZhang2· WenlongSong3· SenlinTang2· Vijay P.Singh4,5
Natural Hazards (2025) 121:1505–1530
https://doi.org/10.1007/s11069-024-06870-0
Abstract
Three Gorges Dam is the largest hydraulic infrastructure in the world, playing a piv-
otal role in ood mitigation. The hydrological responses of the Three Gorges Reservoir
Region (TGRR) to climate change and human activities are unclear, yet critical for the
Three Gorges Dam’s ood control and security. We simulated streamow and water depth
by coupling the Variable Inltration Capacity model and the CaMa-Flood model. Daily
discharge at the outlet of TGRR was well modeled with a relative error within 2% and a
Nash-Sutclie eciency coecient of approximately 0.81. However, the ood peak was
overestimated by 2.5–40.0% with a peak timing bias ranging from 5 days earlier to 2 days
later. Runo and water depth in the TGRR increased from 2015 to 2018 but decreased
during ood seasons. Land use and land cover changes in 2015 (LUCC2015) and 2020
(LUCC2020) were analyzed to quantify their hydrological impacts. During the 2015–2018
period, land use conversion increased in built-up areas (+ 0.6%) and water bodies (+ 0.1%),
but decreased in woodland grassland (-0.7%) and cropland (-0.1%). This led to a slight
increase in runo and inow of less than 4‰ across the TGRR, a 7.70% decrease in
average water depth, and a 15.4‰ increase in maximum water depth. Water depths in the
TGRR decreased during ood seasons, and increased during non-ood seasons. Increasing
water depth was identied in northern TGRR. This study claries the historical TGRR’s
hydrological features under LUCC and climate changes, aiding regional ood mitigation
in the TGRR.
Keywords Hydrological responses · Water depth · Runo · Climate changes · LUCC ·
Three gorges reservoir regions
1 3
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... However, the construction and operation of dams have significant ecological consequences, and these negative impacts are well documented (Coerver et al. 2018). The ecological disruptions caused by dam projects have raised substantial concerns, particularly in transboundary river basins (Gutenson et al. 2020;Sun et al. 2024). In regions with substantial riparian populations, monitoring reservoirs becomes not only important but also critical for ensuring the well-being of these communities. ...
Article
Full-text available
Accurate parameter estimation of reservoir operation models is crucial for effective reservoir management but is hampered by limited in situ data for calibration. Here, we show that satellite altimetry can be effectively used to estimate model parameters and improve reservoir operation modelling. Specifically, we enhance the target storage parameter estimate of a reservoir model using altimetry-derived seasonal patterns. Four case study reservoirs were analysed to assess reservoir storage and outflow simulations. The satellite-derived water levels agree well with the observations, despite minor biases during low-water periods. The reservoir model with satellite-derived parameters outperforms the default model, with improvements in Nash–Sutcliffe efficiency and Kling–Gupta efficiency ranging from 0.02 to 0.3. An analysis of the model sensitivity reveals that the simulation accuracy strongly depends on the inflow data quality, whereas the optimal initial storage values vary across reservoirs. Our findings demonstrate that integrating satellite altimetry data can substantially improve reservoir operation modelling, offering a promising solution for regions with limited ground observations.
Article
Ecosystem service quality is closely linked to human well‐being, and sustainable provision of ecosystem service is essential for ensuring regional ecological security and achieving sustainability goals. An innovative valuation framework is introduced that combines land use/cover change (LUCC) analysis, supply and demand matrices and Gini coefficient calculations to assess the supply and demand of ecosystem services (ES‐S and ES‐D). Unlike traditional static methods, this approach captures intricate spatial and temporal mismatches, offering new insights into the impacts of LUCC on ES balance within the framework of sustainable development goals (SDGs). Taking the Three Gorges Reservoir Area (TGRA) as a case study, the findings indicate a significant decrease in cultivated land, accompanied by expansion of forest and built‐up area, driven by farmland‐to‐forest policies and urbanization. These shifts have improved the balance of provisioning and supporting services but have also intensified regional disparities, particularly in Chongqing, where demand outpaces supply. Furthermore, LUCC have altered the capacity of ecosystems in the TGRA to provide essential services, such as soil retention and water regulation, thereby supporting progress toward SDGs related to ecosystem sustainability. However, imbalances in cultural services persist, highlighting the need for targeted management strategies to optimize ES provision and support regional sustainability. This study underscores the importance of ongoing ES‐S and ES‐D assessments to inform sustainable land management policies in ecologically sensitive areas like the TGRA.
Article
Full-text available
The changing climate and intensifying human activities have made an impact on the hydrological processes in the upper Yangtze River (UYR), but quantifying their effects remains uncertain. This study used the Budyko framework to investigate the response of runoff (Q) to climate change and human activities during 1956–2017 and evaluate the impacts of human activities, including land use/cover change, water use, dam construction, and vegetation change, on watershed characteristic. Results show that climate change is the dominant driver of Q variations in the Wujiang River (WJR), Jialing River (JLR), and Jinsha River (JSR) watersheds, with contributions of 58.6%, 66.9%, and 67.6%, respectively. However, in Mingjiang River (MJR) and UYR watersheds, human activities contribute more to Q variations with 55.2% and 51.2%, respectively. Human activities play important roles in variation of watershed characteristics, and they can explain 22%, 26%, 36%, 25%, and 53% of the watershed character change in UYR, WJR, JLR, MJR, and JSR, respectively. This study conducts a comprehensive analysis of the causes of Q change in UYR, and provides a new perspective to explore the effects of specific human activities on watershed characteristics.
Article
Full-text available
The Three Gorges Reservoir (TGR) is one of the world's largest hydropower projects and plays an important role in water resources management in the Yangtze River. For the sake of disaster prevention and catchment management, it is crucial to understand the regulation capacity of the TGR on extreme hydrological events and its impact on flow regime in a changing climate. This study obtains historical inflows of the TGR from 1961 to 2019 and uses a distributed hydrological model to simulate the future inflows from 2021 to 2070. These data are adopted to drive a machine learning‐based TGR operation model to obtain the simulated outflow with TGR operation, which are then compared with the natural flow without TGR operation to assess the impact of TGR. The results indicate that the average flood peaks and total flooding days in the historical period could have been reduced by 29.2% and 53.4% with the operation of TGR. The relative declines in drought indicators including duration and intensity were generally less than 10%. Faced with more severe extreme hydrological events in the future, the TGR is still expected to alleviate floods and droughts, but cannot bring them down to historical levels. The impact of TGR operation on flow regime will also evolve in a changing climate, potentially altering the habitats of river ecosystems. This study proposes feasible methods for simulating the operation of large reservoirs and quantifying the impact on flow regime, and provides insights for integrated watershed management in the upper Yangtze River basin.
Article
Full-text available
The hydrological model calibration is a challenging task, especially in ungauged catchments. The regionalization calibration methods can be used to estimate the parameters of the model in ungauged sub-catchments. In this article, the model of ungauged sub-catchments is calibrated by a regionalization approach based on automatic clustering. Under the clustering procedure, gauged and ungauged sub-catchments are grouped based on their physical characteristics and similarity. The optimal number of clusters is determined using an automatic differential evolution algorithm-based clustering. Considering obtained five clusters, the value of the silhouette measure is equal to 0.56, which is an acceptable value for goodness of clustering. The calibration process is conducted according to minimizing errors in simulated peak flow and total flow volume. The Storm Water Management Model is applied to calibrate a set of 53 sub-catchments in the Gorganrood river basin. Comparing graphically and statistically simulated and observed runoff values and also calculating the value of the silhouette coefficient demonstrate that the proposed methodology is a promising approach for hydrological model calibration in ungauged catchments. HIGHLIGHTS The model of ungauged sub-catchments is calibrated by a regionalization approach based on automatic clustering.; The optimal number of clusters is determined using an automatic differential evolution algorithm-based clustering.; Comparing graphically and statistically simulated and observed runoff values and also calculating the value of silhouette coefficient proved the superiority of automatic clustering differential evolution in clustering.;
Article
Full-text available
Future rainfall extremes are projected to increase with global warming according to theory and climate models, but common (annual) and rare (decennial or centennial) extremes could be affected differently. Here, using 25 models from the Coupled Model Intercomparison Project Phase 6 driven by a range of plausible scenarios of future greenhouse gas emissions, we show that the rarer the event, the more likely it is to increase in a future climate. By the end of this century, daily land rainfall extremes could increase in magnitude between 10.5% and 28.2% for annual events, and between 13.5% and 38.3% for centennial events, for low and high emission scenarios respectively. The results are consistent across models though with regional variation, but the underlying mechanisms remain to be determined.
Article
Although the vegetation-greening-induced water supply reduction has been widely recognized, little is known about the impacts of vegetation greening on hydrological drought. Here Standardized Water Availability Index (SWAI, based on surface water-balance), driven by evapotranspiration (ET, with vegetation dynamics), was developed to quantify the impacts of vegetation greening on hydrological drought at multiple timescales over China from 1982 to 2015. The ET with vegetation dynamics was modeled by the improved PT-JPL model, and was validated with in-situ observed data from 8 flux tower sites and 4 on-site field experiments (covered with 12 different land-cover types in China). SWAI was also validated with monthly runoff records (from 59 gauging stations over different climatic regimes in China), and proved to effectively capture the response of water surplus/ deficit to vegetation dynamics. Results reveal that percentage drought-affected areas increased (increased by 2 % to 9 %) and drought intensity enhanced in two-thirds of Chinese river basins due to vegetation greening. Moreover , in nearly half of the river basins in China, drought duration increased by 0.035-0.131 months, and drought frequency increased by 0.016-0.085 months/34-year. Hydrological drought accelerated by vegetation greening mainly occurred in arid and semi-arid river basins (water-limited areas), while it was not obvious in humid and sub-humid river basins due to limited energy for ET in these areas. Our work and findings provide new insights for understanding the vegetation-induced water resource shortage and have potential applications for government and water managers to timely monitor and assess the balance between ecological restoration and water resources .
Article
Climate change has led to anomalous fluctuations in extreme streamflow from global river systems, and the su-perposition of human activities such as damming has compounded the changes in extreme streamflow, affecting floods and river ecosystems. However, muti-temporal scale variations of extreme streamflow and the dominant driving factors were limitedly understood. In this study, we examined the changing patterns of inter-and intra-annual extreme (maximum 1-day, consecutive 3-days and 7-days) streamflow (including magnitude and timing) in the Yangtze River Basin (YRB) from the 1940 s to 2020. Furthermore, the roles of ENSO events and dams on temporal anomalies of extreme streamflow at inter-and intra-annual scales were identified in the whole basin. We found that the annual streamflow extremes increased in the source YRB and the middle and lower YRB but decreased in the upper YRB. The extreme streamflow during spring and autumn was characterized by increasing trends in the source and decreasing trends in other reaches. The occurrence timing of winter extreme streamflow in the upper and middle YRB was significantly delayed. The inter-annual extreme streamflow in the source and upper YRB had a negative relationship with ENSO, while the positive relationship held in the middle and lower YRB. The major anomalies (>50 %) of annual extreme streamflow generally occurred in ENSO (1+2) yrs, while precipitation contributes to the seasonal distribution of extreme streamflow. There was a good correlation between precipitation and both annual and summer extreme streamflow in the lower YRB, but the relationship completely shifted in the upper YRB after 2003. Further, the construction of dams has severely affected extreme streamflow, leading to a stepwise drop in annual and summer/autumn flows and a sudden rise in spring/winter flows. This study facilitates the prediction of extreme streamflow and the development of sustainable basin management strategies.
Article
Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.
Article
Distortion of the water cycle, particularly of its extremes (droughts and pluvials), will be among the most conspicuous consequences of climate change. Here we applied a novel approach with terrestrial water storage observations from the GRACE and GRACE-FO satellites to delineate and characterize 1,056 extreme events during 2002–2021. Dwarfing all other events was an ongoing pluvial that began in 2019 and engulfed central Africa. Total intensity of extreme events was strongly correlated with global mean temperature, more so than with the El Niño Southern Oscillation or other climate indicators, suggesting that continued warming of the planet will cause more frequent, more severe, longer and/or larger droughts and pluvials. In three regions, including a vast swath extending from southern Europe to south-western China, the ratio of wet to dry extreme events decreased substantially over the study period, while the opposite was true in two regions, including sub-Saharan Africa from 5° N to 20° N. How will climate change affect wet and dry extreme events around the world? On the basis of terrestrial water storage observations and a novel clustering algorithm, this study shows that the intensity of such events has been increasing with global warming.