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Safety, progress, and investment risks are correlated during the construction period of large-scale water transfer projects. However, previous studies have only considered individual risk factors, overlooking the potential systemic risk posed to safety, progress, and investment, as well as any underlying common cause failures. Since traditional risk analysis methods are ill-suited to addressing common cause failure, this paper's objective was to establish a comprehensive evaluation index framework and to identify the basic events of common cause failure. To do that, we developed a risk analysis method that models common cause failure based on a Bayesian network for assessing that systemic risk. The Henan Section of the Yangtze-to-Huaihe River Water Diversion Project in China was then used as a case study. The results show that a variety of common cause failure events, such as epidemic disease, design alteration, lagged approval process, heavy rain in the flood season, renewal material and failing equipment, construction accidents, and external interference, can significantly impact the safety, progress, and investment systemic risk. Design alteration poses the greatest risk, with renewal material and failing equipment exerting the strongest influence among all common cause failure events. It is also possible to elucidate the predominant causal chains; specifically, the contributing influence of each basic failure event to the systemic risk can be clarified by adjusting their respective initial state. The failure of renewal material and failing equipment was found to significantly increase the safety risk. This study effectively simulated the complex causal relationships and uncertainties of pertinent risk factors, thereby enhancing our understanding of the systemic risk associated with safety, progress, and investment in large-scale water transfer projects. [ABSTRACT FROM AUTHOR]

The Poyang Lake Region (PLR) is well known for its ecological and economic importance. This paper first analyzed the changes in land use/land cover (LULC), followed by changes in landscape patterns and ecosystem services by landscape metrics and equivalent coefficients table method. Then, the influence of LULC change on landscape pattern and ecosystem services in both historical period (from 1990 to 2015) and future period (2030) was explored. The results showed that the area of construction land was 607.9 km2 in 1990 and 972.5 km2 in 2015. The increased construction land mainly converted from cultivated land. For the entire PLR, a higher use degree of LULC and a trend of fragmentation existed in recent years. The total ecosystem service values (ESVs) decreased by ¥2.44 × 109 from 1990 to 2015, mainly because of shrinkage of cultivated land and sharp increase in construction land. It was predicted that the areas of construction land and waterbody would increase by 34.6% and 2.2% compared with those in 2015. These changes would lead to more regular in patch shape, longer in patch edge, less connectivity of patches, and an increase of ¥6.2 × 108 ESVs in 2030. [ABSTRACT FROM AUTHOR]

The change of water resources resulting from climate warming in the Yangtze River Source Region (YRSR) has aroused wide concern in recent years. This research used the soil and water assessment tool (SWAT) to estimate the blue water (BW), green water flow (GWF), and green water storage (GWS). Then, the spatial and temporal change of BW, GWF, and GWS over the recent decades and next several decades was investigated. Results show that (1) the BW and GWF have increased by 2.3 mm/10a and 34.2 mm/10a from 1960 to 2012, while the GWG has decreased slightly by 0.19 mm/10a during the same period. (2) The spatial patterns of BW, GWF, and GWS have been changed obviously from 1980s to 2000s, especially for BW and GWF. The BW and GWF in the west and north of the YRSR where the water resource is relatively less are more sensitive to climate change; (3) the annual average temperature and precipitation in the YRSR are projected to increase by 2.2 °C and 9.8% during 2021 to 2050 compared to that during the 1961 to 1990. There is higher uncertainty in BW and GWS projection and the model-averaged BW and GWS would change little. The projected percent changes of GWF and GWS would be 15% and − 11.1% with less uncertainty. The obvious change of BW, GWF, and GWS in the future would occur in the west and north of the YRSR, which is similar with the spatial change in the historical period. [ABSTRACT FROM AUTHOR]

Highlights • A couple-based interval-bistochastic programming method is proposed to address the regional water resources allocation under uncertainties. • An appropriate water allocation plan in Zhanghe Irrigation District is developed under uncertainties of reservoir inflow and local rainfall. • The independence hypothetical situation and linear relationship hypothetical situation are also discussed and compared. Abstract In regional water resources allcoation problems, the uncertainties of hydrological variables and socio-economic parameters are bringing huge challenges to water managers. So far, the stochastic programming models have difficulty in addressing uncertain problems, in which there are two correlated random variables. In order to address regional water resources allocation under two hydrological random variables and interval parameters, a couple-based interval-bistochastic programming (CIBSP) method is proposed. The CIBSP method includes several key steps: first, the marginal distributions of the two hydrological variables are analyzed and hydrological scenarios are set; then, the copula is chosen to analyze joint probability distribution of the two hydrological variables and the joint probabilities of scenarios are calculated; last, an interval-bistochastic model is formulated by incorporating two-stage stochastic programming, interval-parameter programming, and bivariate joint distribution. The CIBSP method can describe the probability of occurrence of a hydrological scenario and then make an optimized water allocation scheme under uncertainties. To demonstrate its applicability, the CIBSP method is applied to the Zhanghe Irrigation District located in China, to optimize available water allocation under the uncertainties of the annual inflow volume of the Zhanghe Reservoir and annual rainfall volume in the irrigated district. An appropriate water allocation plan can be obtained by the method, which provides a foundation to water managers for managing water resources in Zhanghe Irrigation District. Moreover, other two hypothetical situations named independence hypothetical situation and linear relationship hypothetical situation are discussed. The difference in the results between the two hypothetical situations and the case study indicates that an appropriate description of the joint probability of the annual inflow volume and annual rainfall volume by using CIBSP method is important for water resource allocation under uncertainties. [ABSTRACT FROM AUTHOR]

To gain an insight into the spatiotemporal variability of drought events and to assess trends under future climate change scenarios are fundamental for making sound mitigation and adaptation strategies. A new drought index, standardized supply-demand water index (SSDI), has been proposed in this research. The SSDI describes drought from the view of water supply-demand relations using a simple water balance model. It was used to assess historical drought events in the middle and lower Jinsha river basin (MLJRB) located in the southwest China and applied to address the drought conditions in the MLJRB under current and future climates. The results showed the following: (1) The average drought area during 2001 to 2011 reached up to 9.9 × 103 km2, accounting for 35.4% of the whole farmland area in the MLJRB, which was about twice as the drought area during 1961 to 2000. The region for greater drought severity with more drought events and longer duration was mainly distributed in Dali, Chuxiong, Kunming, and Yuxi. (2) For the period 2021 to 2050, total drought area was projected to increase by 43.2%. The drought-prone regions could move further towards the northwest of the MLJRB. [ABSTRACT FROM AUTHOR]

The effects of hydrologic cycle change (caused by human activity and global climate change) on ecosystems attract the increasing attention around the world. As a result of impounding of the Three Gorges Dam (TGD), climate change and sand mining, the dry season of Poyang Lake and Dongting Lake (China’s two largest freshwater lakes) came early after the TGD impoundment. It was the primary cause of the increasing need for sluice/dam construction to store water in the Lakes and attracted increasing attention. In this paper, we compared the landscape pattern between three hydrologic years with early dry season (EY) and three normal hydrologic years (NY) of each lake by remote sensing technology, to reveal the effect of early dry season on landscape pattern. The results showed that early dry season caused expanding of Phalaris to mudflat zone in Poyang Lake, while caused expanding of Carex to Phalaris zone and expanding of Phalaris to mudflat zone in Dongting Lake. In landscape level, there was no significant difference in landscape grain size, landscape grain shape, habitat connectivity and landscape diversity between EY and NY in the two lakes. While in habitat class level, there were significant changes in area of mudflat and Phalaris and grain size of mudflat in Poyang Lake, and in area of Carex , grain size of Phalaris and grain shape of Carex and Phalaris in Dongting Lake. These changes will impact migrating birds of East Asian and migratory fishes of Yangtze River. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, drought is causing devastating impacts on the balance of the regional water resources system. Hydrological drought assessment is critical for drought prevention and water resources management. However, in China to assess hydrological drought at national scale is still challenging basically because of the difficulty of obtaining runoff data. In this study, we used the state-of-the-art passive microwave remote sensing techniques in river runoff modelling and thus assessed hydrological drought in Mainland China in 1996–2016. Specifically, 79 typical hydrological stations in 9 major basins were selected to simulate river runoff using the M/C signal method based on a high-resolution passive microwave bright temperature dataset. The standardized runoff index (SRI) was calculated for the spatial and temporal patterns of hydrological drought. Results show that passive microwave remote sensing can provide an effective way for runoff modelling as 92.4% and 59.5% of the selected 79 stations had the Pearson correlation coefficient (R) and the Nash-Sutcliffe efficiency coefficient (NS) scores greater than 0.5. Especially in areas located on Qinghai-Tibet Plateau in the Inland and the Southwest River Basin, the performance of the M/C signal method is quite outstanding. Further analysis indicates that stations with small rivers in the plateau areas with sparse vegetation tend to have better simulated results, which are usually located in drought-prone regions. Hydrological drought assessment shows that 30 out of the 79 stations present significant increasing trends in SRI-3 and 18 indicate significant decreasing trends. The duration and severity of droughts in the non-permanent dry areas of the Hai River Basin, the middle reaches of the Yangtze River Basin and the Southwest of China were found out to be more frequent and severe than other regions. This work can provide guidance for extending the applications of remote sensing data in drought assessment and other hydrological research. [ABSTRACT FROM AUTHOR]

Changes in rainfall and streamflow due to climate change have an adverse impact on hydropower generation reliability and scheduling of cascade hydropower stations. To estimate the impact of climate change on hydropower, a combination of climate, hydrological, and hydropower scheduling models is needed. Here, we take the Jinsha River as an example to estimate the impact of climate change on total power generation of the cascade hydropower stations and residual load variance of the power grid. These two goals are solved by applying an improved multi-objective cuckoo search algorithm, and a variety of strategies for the optimal dispatch of hydropower stations are adopted to improve the efficiency of the algorithm. Using streamflow prediction results of CMIP5 climate data, in conjunction with the Xinanjiang model, the estimated results for the next 30 years were obtained. The results indicated that the negative correlation between total power generation and residual load variance under the RCP 2.6 scenario was weaker than that under the RCP 8.5. Moreover, the average power generation and the average residual load variance in RCP 2.6 was significantly larger than that in RCP 8.5. Thus, reducing carbon emissions is not only beneficial to ecological sustainability, but also has a positive impact on hydropower generation. Our approaches are also applicable for cascade reservoirs in other river catchments worldwide to estimate impact of climate change on hydropower development. [ABSTRACT FROM AUTHOR]

• Nonlinear responses of water quality to landscape pattern were modeled. • Three types of landscape thresholds were defined and identified based on nonlinear relations. • The landscape thresholds can act as targets of landscape pattern management. Investigating the relationship between landscape pattern and water quality is essential for making sustainable landscape development policies. A clear understanding of such relationship remains elusive partly due to ubiquitous nonlinearity, behind which the landscape threshold can potentially act as quantifiable target of landscape conservation. In the upper Huai River Basin in China, six landscape metrics were quantified for forested, agricultural, and residential land use categories at broad sub-basin and finer riparian buffer scales. Five water quality indicators were collected from 24 monitoring stations during the period of 2006–2012. On the basis of nonlinear regression models, including power, exponential, quadratic, and segmented regressions, one-to-one relations between landscape metrics and water quality variables were fitted with R 2 generally varying between 0.32 and 0.74. Meanwhile, three types of defined landscape thresholds were also identified on the basis of the fitted nonlinear relations. From the perspective of spatial scale dependence, the percentage of landscape area and largest patch index could well explain water quality variables at a broad sub-basin scale; the opposite could be said for patch density. The type-1 and type-2 landscape thresholds can act as the long-term targets where landscape pattern management strategy should be timely adjusted. By contrast, the type-3 landscape threshold can be set as a short-term target of landscape conservation to ensure water quality up to a certain management requirement. This study suggests that considering nonlinearity and threshold effect could provide insights into the complicated landscape pattern–water quality relations and thus provide a scientific basis for balancing the coupled socioecological system of landscape development and water quality protection. [ABSTRACT FROM AUTHOR]

The ecological environment and water resources of the Han River Basin (HRB) are incredibly susceptible to global warming. Naturally, the analysis of future runoff in HRB is believed to offer a theoretical basis for water resources management and ecological protection in HRB. The purpose of this study is to investigate and forecast the effects of climate change and land use change on runoff in the HRB. This study uses CMIP6 data to simulate three future climate change scenarios (SSP126, SSP245 and SSP585) for changes in precipitation and temperature, a CA-Markov model to simulate future land use change scenarios, and the Budyko framework to predict future runoff changes. The results show that: (1) Between 1974 and 2014, annual runoff ( R ) and annual precipitation ( P ) in the HRB decline not so significantly with a rate of 1.3673 mm/a and 1.2709 mm/a, while maximum temperature ( Tmax ) and minimum temperature ( Tmin ) and potential evapotranspiration ( E 0 ) show a non-significantly increasing trend with 0.0296 °C/a, 0.0204 °C/a and 1.3313 mm/a, respectively. Precipitation is considered as main contributor to the decline in Han River runoff, accounting for 54.1%. (2) In the HRB, overall precipitation and temperature are estimated to rise in the coming years, with all other hydrological variables. The comparison of precipitation rise under each scenario is as follows: SSP126 scenario > SSP585 scenario > SSP245 scenario. The comparison of the temperature increase under each scenario is as follows: SSP585 scenario > SSP245 scenario > SSP126 scenario. (3) In the HRB, farmland and grassland land will continue to decline in the future. The amount of forest acreage is projected to decline but not so significantly. (4) The future runoff of the HRB shows an increasing trend, and the future runoff varies in different scenarios and periods. Under the land use scenarios of maintaining LUCC1992-2014 and LUCC2040 and LUCC2060, the R change rates in 2015-2040 are 8.27-25.47% and -8.04-19.35%, respectively, and the R in 2040-2060 are 2.09-13.66% and 19.35-31.52%. At the same time, it is very likely to overestimate the future runoff of the HRB without considering the changes in the land use data of the underlying surface in the future.

Projecting future changes in extreme flood is critical for risk management. This paper presented an analysis of the implications of the Fifth Coupled Model Intercomparison Project Phase (CMIP5) climate models on the future flood in the Jinsha River Basin (JRB) in Southwest China, using the Xinanjiang (XAJ) hydrologic model. The bias-corrected and resampled results of the multimodel dataset came from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Relatively optimal general circulation models (GCMs) were selected with probability density functions (PDFs)-based assessment. These GCMs were coupled with the XAJ model to evaluate the impact of climate change on future extreme flood changes in the JRB. Two scenarios were chosen, namely: a midrange mitigation scenario (Representative Concentration Pathway 4.5, RCP4.5) and a high scenario (RCP8.5). Results show that: (1) The XAJ model performed well in simulating daily discharge and was suitable for the study area, with E NS and R ² higher than 0.8; (2) IPSL-CM5A-LR and MIROC-ESM-CHEM showed considerable skill in representing the observed PDFs of extreme precipitation. The average skill scores across the total area of the JRB were 0.41 to 0.66 and 0.53 to 0.67, respectively. Therefore, these two GCMs can be chosen to analyze the changes in extreme precipitation and flood in the future; (3) The average extreme precipitation under 20- and 50-year return period across the JRB were projected to increase by 1.0⁻33.7% under RCP4.5 and RCP8.5 during 2020 to 2050. The Upper basin is projected to experience the largest increase in extreme precipitation indices, possibly caused by a warmer climate. The extreme flood under 20- and 50-year return period will change by 0.8 to 23.8% and -6.2 to 28.2%, respectively, over this same future period. Most of scenarios projected an increase during the near future periods, implying the JRB would be likely to undergo more flooding in the future.