Impact Of Future Climate Change Research Articles

Ecophysiological traits of seedlings from different accessions of Stipa tenacissima along a climatic gradient

Predicting the future impact of climate change on Stipa tenacissima steppes is of paramount importance to prevent desertification. From this perspective, we selected seven populations, covering a rainfall range from 100 to 600 mm/year at the sites of seed collection, and we grew the seedlings at the same site. Gas exchange measurements of CO2, light response curves, chlorophyll content and isotopic analysis were investigated. Thala and Valencia populations displayed a contrasted gas exchange response. Both populations were subjected to A-Ci curve analysis. No significant difference was detected between these two different populations in the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Stipa tenacissima exhibited a variable response in relation to different light intensities. Photosynthesis and chlorophyll fluorescence parameters proved to be significantly different among populations in response to light intensities. All populations exhibited similar chlorophyll content. The isotopic analysis highlighted a different carbon and nitrogen isotopic composition (δ13C and δ15N) and carbon content © among populations. Mesic populations presented a higher gas exchange activity and light response. The xeric populations performed a photosynthesis adjustment along with minimizing chlorophyll content. Under climate change, S. tenacissima limits productivity, which may lead to desertification.

Potential impact of future climate change on grassland cover in Burkina Faso.

The objective of this study was to analyse the potential impact of future climate change on grassland cover in Burkina Faso. MODIS NDVI 250m time series were used to monitor changes in grassland over 2000-2022. The random forest regression (RFR) model was fit by regressing reference data of grassland cover against current climatic and other environmental predictors to predict the current grassland cover map (2022). Projected climate model data of CMIP6 used under SSP 126 and SSP 585 scenarios were integrated into the fit RFR model to predict future change. The results revealed that grassland areas were largely dominated by non-significant productivity change (55%) during 2000-2022. In this period, grassland area knew more increased productivity (35%) than decrease (10%). Burkina Faso is predicted to face more decreased areas of grassland cover than increase by 2061-2080 under SSP 126 and SSP 585 scenarios. The findings of this study can help to set up appropriate adaptation measures to combat climate change in Burkina Faso.

Climate and biodiversity change constrain the flow of cultural ecosystem services to people: A case study modeling birding across Africa under future climate scenarios

Global change is currently impacting ecosystems and their contributions to people (i.e. ecosystem services). These impacts have consequences for societies and human well-being, especially in Africa. Historically, efforts have focused on assessing global change from a social or biophysical perspective, treating them as separate entities. Yet, our understanding of impacts to social-ecological systems remains limited, particularly in the Global South, due to a lack of data, tools, and approaches accounting for social and ecological aspects of ecosystem services. This is especially relevant for cultural ecosystem services as they are less tangible. We use a simple indicator and important provider of a multitude of cultural ecosystem services, birding, to understand how climate, biodiversity, and land use change will impact cultural ecosystem services across Africa. We explore how emerging tools and data can overcome limitations in mapping and modeling cultural ecosystem services, particularly in analyzing human preferences and behavior at large spatiotemporal scales and in data-poor regions. Leveraging crowdsourced data from eBird and using machine learning techniques we map and model recreational birding to assess the underlying social-ecological relationships and the impact of future climate and environmental change. We show that bird species richness, protected areas, accessibility, and max temperature contribute most to birding suitability across the continent. Further, we show spatial shifts in the suitability of birding under three future climate scenarios (SSP126, 370, and 585). Models suggest climate and biodiversity change will increasingly constrain the flow of birding related cultural ecosystem services across Africa. This has implications for human-nature interactions, development of countries, management of protected areas, and overall human well-being in the future. More generally, we highlight opportunities for crowdsourced datasets and machine learning to integrate non-material ecosystem services in models and thus, enhance the understanding of future impacts to ecosystem services and human well-being.

A systematic review on the potential impact of future climate change on India’s biodiversity using species distribution model (SDM) studies: trends, and data gaps

A systematic review on the potential impact of future climate change on India’s biodiversity using species distribution model (SDM) studies: trends, and data gaps

Evaluating vegetation vulnerability under compound dry and hot conditions using vine copula across global lands

With global warming, climate extremes are intensifying, particularly compound dry and hot events (CDHEs), which would severely impact vegetation growth. However, quantitatively evaluating vegetation vulnerability to CDHEs remains challenging in global lands. A conditional probability model was constructed using the vine copula function to evaluate responses of vegetation to CDHEs based on the Standardized Moisture Anomaly Index (SZI), the Standardized Temperature Index (STI), and the kernel Normalized Difference Vegetation Index (kNDVI). The results show that vegetation growth is more susceptible to dry and hot conditions in arid and semi-arid regions than in sub-humid and humid regions. In terms of vegetation types, shrubs, savanna, grass, and crops are more susceptible to CDHEs than to individual dry or hot events, especially in water-limited regions. In arid regions, the vegetation vulnerability for open shrubs, closed shrubs, savanna, and grass under extreme CDHEs would correspondingly increase by 45%, 23%, 15%, and 12% compared with dry conditions, indicating the necessity to consider both dry and hot conditions simultaneously when evaluating vegetation dynamics to climatic extremes. In semi-arid and sub-humid regions, broadleaf forests show higher vulnerability to CDHEs than needleleaf forests. However, evergreen broadleaf forests show the lowest vulnerability and higher resistance to CDHEs in humid regions. The Analysis of Variance (ANOVA)-based uncertainty decomposition results show that copula combination sets in vine copula trees and vine copula structures are the two main uncertainty sources, accounting for about 60%. Despite with uncertainty, the modeling results show consistent vegetation loss probability patterns simulated with different structures of the vine copula model, indicating the robustness and reliability of the results. The findings provide a profound comprehension of ecosystems’ response mechanisms to compound extremes, which are essential to developing effective mitigation and adaptation strategies against the impact of future climate change.

Historical and projected future runoff over the Mekong River basin

Abstract. The Mekong River (MR) crosses the borders and connects six countries, including China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. It provides critical water resources and supports natural and agricultural ecosystems, socioeconomic development, and the livelihoods of the people living in this region. Understanding changes in the runoff of this important international river under projected climate change is critical for water resource management and climate change adaptation planning. However, research on long-term runoff dynamics for the MR and the underlying drivers of runoff variability remains scarce. Here, we analyse historical runoff variations from 1971 to 2020 based on runoff gauge data collected from eight hydrological stations along the MR. With these runoff data, we then evaluate the runoff simulation performance of five global hydrological models (GHMs) forced by four global climate models (GCMs) under the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Furthermore, based on the best simulation combination, we quantify the impact of future climate change on river runoff changes in the MR. The result shows that the annual runoff in the MR has not changed significantly in the past 5 decades, while the establishment of dams and reservoirs in the basin visibly affected the annual runoff distribution. The ensemble-averaged result of the Water Global Assessment and Prognosis version 2 (WaterGAP2; i.e. GHM) forced by four GCMs has the best runoff simulation performance. Under Representative Concentration Pathways (RCPs; i.e. RCP2.6, RCP6.0 and RCP8.5), the runoff of the MR is projected to increase significantly (p<0.05); e.g. 3.81 ± 3.47 m3s-1a-1 (9 ± 8 % increase in 100 years) at the upper reach under RCP2.6 and 16.36 ± 12.44 m3s-1a-1 (13 ± 10 % increase in 100 years) at the lower reach under RCP6.0. In particular, under the RCP6.0 scenario, the increase in annual runoff is most pronounced in the middle and lower reaches, due to increased precipitation and snowmelt. Under the RCP8.5 scenario, the runoff distribution in different seasons varies obviously, increasing the risk of flooding in the wet season and drought in the dry season.

Assessment of Future Climate Change Impacts on Groundwater Recharge Using Hydrological Modeling in the Choushui River Alluvial Fan, Taiwan

Assessment of Future Climate Change Impacts on Groundwater Recharge Using Hydrological Modeling in the Choushui River Alluvial Fan, Taiwan

Arsenic distribution and partitioning in multiple media in a typical catchment in the Qinghai-Tibetan plateau: A comparison between freshwater and saltwater lakes

Arsenic (As) has been widely detected in surface media on the Qinghai-Tibetan Plateau (QTP); however, the differences in the As distribution and partitioning characteristics between freshwater and saltwater lakes remain poorly understood. To determine the distribution and partitioning characteristics of As, multimedia environmental samples were collected from a typical small watershed consisting of a river, wetland, and both freshwater and saltwater lakes on the QTP. Results showed that freshwater systems, represented by Hurleg Lake, were high in particulate arsenic (PAs) and low in dissolved arsenic (DAs), whereas the saltwater system represented by Tosen Lake, exhibited the reverse distribution. This discrepancy in As distribution was primarily attributed to evaporation enrichment, competitive adsorption of HCO3− and pH variations, as suggested by correlation analysis and stable isotopic composition of water. In the stratified Tosen Lake, an increasing trend of DAs in the water column was observed, potentially driven by the reductive dissolution of Fe (hydr)oxides and bacterial sulfate reduction in the anoxic bottom hypolimnion. Conversely, Hurleg Lake maintained oxic conditions with stable DAs concentrations. Notably, PAs was elevated in the bottom layer of both lakes, possibly due to uptake/adsorption by biogenic particles, as indicated by high levels of chl.α and suspended particulate matter. These findings offer insights into the potential future impact of climate change on As mobilization/redistribution in arid plateau lakes, with implications for management policies that regulate As pollution.

Impact of Future Climate Change on the Yield of Spring Maize and the Effect of Resilient Measures on it Under Different Parameters in the Major Agro-Ecosystems in China and Kenya

Impact of Future Climate Change on the Yield of Spring Maize and the Effect of Resilient Measures on it Under Different Parameters in the Major Agro-Ecosystems in China and Kenya

Assessing the Impacts of Future Climate and Land-Use Changes on Streamflow under Multiple Scenarios: A Case Study of the Upper Reaches of the Tarim River in Northwest China

Climate change and land use/cover change (LUCC) are two major factors that alter hydrological processes. The upper reaches of the Tarim River, situated in the northwest region of China, experience a dry and less rainy climate and are significantly influenced by human activities. This study comprehensively assessed the impacts of individual and combined climate changes and LUCCs on streamflow. Three general circulation models (GCMs) were utilized to predict future climate changes under three shared socioeconomic pathways (SSP119, SSP245, and SSP585). Cellular Automata–Markov (CA–Markov) was employed to predict future LUCC under three scenarios (i.e., ecological protection, historical trend, and farmland development). Streamflow for the period 2021–2050 was simulated using the calibrated MIKE SHE model with multiple scenarios. The results showed that from 2021 to 2050, increments in both average annual precipitation and average annual temperature under the three SSPs were predicted to lead to an increased streamflow. In comparison to the conditions observed in 2000, under three LUCC scenarios for 2030, the grassland area decreased by 1.04% to 1.21%, while the farmland area increased by 1.97% to 2.26%, resulting in reduced streamflow. The related changes analysis indicated that the variation in streamflow during winter is most significant, followed by spring. The study predicted that climate change would increase streamflow, while LUCC would decrease it. Due to the greater impact of LUCC, considering the combined effect of both factors, runoff would decrease. The contribution analysis indicated that climate change contributed between −7.16% and −18.66%, while LUCC contributed between 107.16% and 118.66%.

Enhancing Understanding of the Impact of Climate Change on Malaria in West Africa Using the Vector-Borne Disease Community Model of the International Center for Theoretical Physics (VECTRI) and the Bias-Corrected Phase 6 Coupled Model Intercomparison Project Data (CMIP6)

In sub-Saharan Africa, temperatures are generally conducive to malaria transmission, and rainfall provides mosquitoes with optimal breeding conditions. The objective of this study is to assess the impact of future climate change on malaria transmission in West Africa using community-based vector-borne disease models, TRIeste (VECTRI). This VECTRI model, based on bias-corrected data from the Phase 6 Coupled Model Intercomparison Project (CMIP6), was used to simulate malaria parameters, such as the entomological inoculation rate (EIR). Due to the lack of data on confirmed malaria cases throughout West Africa, we first validated the forced VECTRI model with CMIP6 data in Senegal. This comparative study between observed malaria data from the National Malaria Control Program in Senegal (Programme National de Lutte contre le Paludisme, PNLP, PNLP) and malaria simulation data with the VECTRI (EIR) model has shown the ability of the biological model to simulate malaria transmission in Senegal. We then used the VECTRI model to reproduce the historical characteristics of malaria in West Africa and quantify the projected changes with two Shared Socio-economic Pathways (SSPs). The method adopted consists of first studying the climate in West Africa for a historical period (1950–2014), then evaluating the performance of VECTRI to simulate malaria over the same period (1950–2014), and finally studying the impact of projected climate change on malaria in a future period (2015–2100) according to the ssp245 ssp585 scenario. The results showed that low-latitude (southern) regions with abundant rainfall are the areas most affected by malaria transmission. Two transmission peaks are observed in June and October, with a period of high transmission extending from May to November. In contrast to regions with high latitudes in the north, semi-arid zones experience a relatively brief transmission period that occurs between August, September, and October, with the peak observed in September. Regarding projections based on the ssp585 scenario, the results indicate that, in general, malaria prevalence will gradually decrease in West Africa in the distant future. But the period of high transmission will tend to expand in the future. In addition, the shift of malaria prevalence from already affected areas to more suitable areas due to climate change is observed. Similar results were also observed with the ssp245 scenario regarding the projection of malaria prevalence. In contrast, the ssp245 scenario predicts an increase in malaria prevalence in the distant future, while the ssp585 scenario predicts a decrease. These findings are valuable for decision makers in developing public health initiatives in West Africa to mitigate the impact of this disease in the region in the context of climate change.

The effects of climate change on the natural rate of interest: A critical survey

AbstractThis survey reviews the literature about the possible impacts of climate change on the natural rate of interest (r*), an important yardstick for monetary policy. Prima facie, economic, and financial developments can lower r* in scenarios with increasing climate‐related damages and uncertainty that reduce productivity growth and raise precautionary savings. Orderly climate policies have a pivotal role in facilitating the transition to a carbon‐neutral economy and supporting a steady investment flow. We discuss the main models used to simulate the effects of climate change on r* and summarize the outcomes. However, in scenarios that assume innovations and investments induced by transition policies, r* could be affected positively. Overall, the downward effects of climate change on r* can be substantial, even considering the high degree of uncertainty about the outcomes, with tipping points and nonlinear effects aggravating the economic impacts. The downward pressure on r* will further challenge monetary policy in the long run, by limiting its policy space.This article is categorized under: Climate Economics > Economics and Climate Change Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change

Impact of recent and future climate change on vectorborne diseases: viruses analyses

Climate directly impacts health through climatic extremes, air quality, sea-level rise, and multifaceted influences on food production systems and water resources. Climate also affects infectious diseases, which have played a significant role in human history, impacting the rise and fall of civilizations and facilitating the conquest of new territories. This review highlights significant regional changes in vector and pathogen distribution , changes that have been anticipated by scientists worldwide . Further future changes are likely if we fail to mitigate and adapt to climate change. Many key factors affect the spread and severity of human diseases, including mobility of people , animals , and goods; control measures in place; availability of effective drugs; quality of public health services; human behavior; and political stability and conflicts.

Fluctuations of discharge and hydropower potential in the upper Amu Darya under the background of climate change

Study RegionUpper Amu Darya (UAD). Study FocusThe UAD has abundant hydropower potential (HP). This study focuses on the potential sites of small hydropower stations (sHPs) and explores the impact of future climate change on discharge and HP. New Hydrological Insights for the RegionThe conflict between water resources and hydropower in Central Asia is a key issue affecting regional development. Developing sHPs provides a new direction for alleviating energy shortages in Central Asia. Combining the hydrological model with the geographic information decision-making method, we have determined the potential sites for ten sHPs in the UAD and calculated the HP for each station. Based on future climate data from two shared socioeconomic pathways and four global climate models, we found that future precipitation and temperature are projected to increase, with precipitation increasing mainly in spring and winter. The average discharge will increase by 19.1∼36.6% in the near-term (2031–2050) and by 29.7∼106.8% in the long-term (2071–2090). In addition, climate change has significantly increased HP in winter, and the increase of HP in relatively high altitudes is higher than that in low altitudes. This implies that the HP development prospect of UAD is broad in future, but for sHPs construction schemes, it is necessary to further consider the impact on both environment and society.

Climate Adaptation Planning: Developing a Methodology for Evaluating Future Climate Change Impacts on Museum Environments and Their Collections

As organisations, museums are responsible for conserving, protecting, and displaying artwork and artefacts. Museum buildings must deliver an environment that will continue to provide this facility for both current and future generations. This research focused on presenting a museum with quantifiable and measurable data to help with climate adaptation planning. A methodology was developed using monitored data. Subhourly data for both indoor and outdoor temperature and humidity spanning the years 2012–2021 was used to produce a daily maximum, daily minimum, and daily average dataset. A sensitivity analysis determined which years to use to derive the indoor-outdoor relationships used in climate modelling. Future impacts were calculated using UK Climate Projections 2018 (UKCP18) data (12 models on a 2.2 km scale), as published by the Met Office Hadley Centre. The data contained within the 12 models was overlayed with the relationships derived to calculate the projected indoor temperature and humidity conditions within the museum. The results presented indicate that temperature and humidity conditions are projected to exceed design conditions more frequently in the coming decades. Consequently, adaptation plans must consider the potential impacts that include indoor environmental deterioration, leading to discomfort and health implications, increased energy costs, and system upgrade costs, as well as the potential for accelerated degradation of artwork and artefacts.

Two crops are better than one for nutritional and economic outcomes of Zambian smallholder farms, but require more labour

Sustainable intensification practices suitable for smallholders in southern Africa will be needed to counteract the impact of future climate change and soil fertility decline in the region. Diversification of maize-based farming systems with grain legumes could play a key role. Here, we compared the performance of different maize-legume diversification strategies (single-row intercropping, strip cropping, and crop rotation) with sole cropped maize under conventional ploughing and Conservation Agriculture in four Zambian districts in the Eastern and Southern Provinces. These options were assessed using the Sustainable Intensification Assessment Framework (SIAF), with metrics representing productive, economic, human, social, and environmental dimensions. Data were collected from on-farm trials over three growing seasons. We found no significant effect of cropping systems on individual maize and legume grain yield across growing seasons, but substantial nutritional and economic benefits of intercropping systems due to simultaneously growing two crops. In particular, maize-legume intercropping strategies (single-row intercropping and strip cropping) resulted in higher energy and protein yield at cropping system level than sole maize and maize-legume rotation, which had positive implications for human nutrition. Although there were increased labour requirements to manage the intercrops, and particularly the strip crops, these cropping systems had much higher net benefits and returns to labour and inputs than the other cropping systems tested. Farmer evaluations however did not show a preference for the intercropping systems over the maize-legume rotation or sole maize, most likely because labour and its availability may be as or more important for farmers than overall cropping system benefits. Soil organic carbon content and soil pH did not differ between the tested cropping systems at the start of the trials and after three cropping seasons, but decreased over this period independently of the cropping system. Overall, the results indicate that maize-legume strip cropping, and single-row intercropping can increase food and nutrition security as well as gross benefits from farming, but this comes at the expense of greater labour requirements throughout the growing season. The latter may be addressed through, e.g., appropriate-scale farm mechanization, if intercropping or strip cropping systems are to become a viable option for labour, not land, constrained farms in Southern Africa.

Global predictions of topsoil organic carbon stocks under changing climate in the 21st century

The organic carbon (OC) stored in global topsoil (0–30 cm) will be the most active participant in the carbon cycle under future climate change. Due to differences in focus regions or research methods, the spatio-temporal changes of future global topsoil OC stocks and how they will be affected by climate change are not systematically understood, which needs to be further explored. In this study, we developed data-driven models to predict the spatio-temporal dynamics of global topsoil OC stocks by combining 32,579 soil profiles with environmental variables and comprehensively explored the impact of future climate change on topsoil OC. It was found that the topsoil OC stocks were 1249.29 Pg in the baseline period (1971–1990). By 2100, under the normal and high representative concentration paths, it is predicted that the global topsoil OC stocks will decrease by 113.67 ± 25.93 Pg and 193.71 ± 39.76 Pg, respectively. In the future, the largest global topsoil carbon loss will occur in boreal forest areas, which are expected to lose 17.03–27.90 % (66.01–108.13Pg) of their carbon stocks. The influence of climate on topsoil OC stocks is mainly manifested in temperature, which has a negative influence on the global topsoil OC stock, and the contribution rate of temperature to the effect on the global topsoil OC stock is about 26.96 %. Overall, our results provide a high spatio-temporal resolution assessment of global topsoil OC stocks and their relationship to environmental factors, and highlight the spatial heterogeneity, which has been generally ignored in many experimental frameworks and prediction models. These results will help governments to make appropriate management decisions to mitigate climate change.

Different approaches to analyze the impact of future climate change on the exploitation of wave energy

The increment of the share of renewable energies in the global mix implies that all renewable energies must be exploited. In this sense, it is necessary to make significant research and investment effort in the particular case of wave energy to reach the degree of maturity of other marine energies in the near future. Apart from the inherent factors that hinder the development of wave energy, such as the non-existence of a market-leading type of capturing device, uncertainties about the available future resource also hamper its growth. In this article, a review of the procedures followed in the literature to deal with the future wave energy resources and their subsequent exploitation is described. These procedures include the evaluation of the best future atmospheric models to drive wave models, the different downscaling techniques to evaluate the resource in large regions with high spatial resolution, and the analysis of the variability of the future energy resource and its future exploitability in a certain region taking into account different types of devices. Additionally, the current state of the art of previous studies dealing with future wave energy resources for different locations worldwide is described. Despite the difficulties involved in studying future wave energy resources, the high technological readiness level of the offshore wind industry, the creation of power generation farms with combined technologies, and the growth of marine aquaculture in the coming years could generate synergies that provide the definitive impulse to achieve the necessary technological development.

Hydroclimatic Impact Assessment Using the SWAT Model in India—State of the Art Review

The Soil and Water Assessment Tool (SWAT) has been widely employed to assist with decision making and management planning for assessing and mitigating the impact of climate change. This model has gained popularity in India as the country is facing increasing water issues under projected climate changes. However, a systematic review of the literature that discusses the applicability of the model, the impact assessment process, and the interpretation of the modeling results in India remains lacking. We synthesized and reviewed 110 recent SWAT modeling studies (published from 2012 to 2022) that evaluated the impact of future climate change on water resources in India to identify research gaps that need to be filled to advance SWAT modeling practices for impact assessments. The review revealed that the SWAT model provided acceptable accuracy statistics in most (90%) of the studies reviewed. Half of these studies identified the base curve number (CN2) as the parameter to which the water balance is the most sensitive; thus, this parameter was included in the calibration process. The accuracy of SWAT modeling is closely associated with the accuracy of the weather data fed to the model. However, extreme events, including heavy storm events and severe droughts, were rarely considered in climate change impact assessments using the SWAT model. Most studies downscaled global-scale climate modeling outputs to local weather stations when applying the SWAT model using various methods, such as the delta change method, multiple linear regression method, gamma–gamma transformation, fitted histogram equalization, and quantile mapping. Further, most studies investigated the performance of the SWAT model before applying the model to quantify the future hydrological consequences of projected climate change in a subsequent scenario analysis. This review suggests that further evaluations of the characteristics and development processes of existing climate data products are needed to effectively consider extreme events in impact assessments. In addition, this review finds that climate change impact modeling has been improved with advances in climate projection preparation, including ensemble averaging, bias correction, and downscaling methods. This regional review of current SWAT modeling practices for climate change impact assessments can be used to create reliable future hydrological projections in India.

Impact of Climate Change on Reservoir Operation during the Dry Season in the Pearl River Basin

Climate change has far-reaching impacts that have created new challenges for water resource management. As an important measure to coordinate the relationship between society, economy, and environment, reservoir scheduling can reduce the future impact of climate change. It is, therefore, important to investigate the impacts of scheduling on reservoir operation. In this study, a reservoir system in the Pearl River Basin was selected to explore these impacts. Results show that the basin temperature significantly and abruptly increased in 2000, and precipitation and streamflow changed abruptly in 1983 and 1992. Historically, climate change has increased power generation, increased the risks to water supply security and ecological protection, and altered the relationship between power generation and ecological protection objectives. Based on 28 global climate models, the rank scoring method, Delta statistical downscaling, and the SWAT model, three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) in CMCC-CM were evaluated to assess the climate change impact. In the future, the temperature will continue to exhibit an increasing trend, and the amount and distribution of streamflow will be altered. Although climate change will increase power generation in the dry season, it will also bring about new challenges for ecological protection and water supply security. Accordingly, the Datengxia Reservoir operating rules may require significant amendments.