Runoff Changes Research Articles

Corrected GCM data through CMFD data to analysis future runoff changes in the source region of the Yangtze River, China

Corrected GCM data through CMFD data to analysis future runoff changes in the source region of the Yangtze River, China

Monthly Runoff Interval Prediction Based on Fuzzy Information Granulation and Improved Neural Network

High-precision monthly runoff prediction results are of great significance to regional water resource management. However, with the changes in human activity, climate, and underlying surface conditions, the runoff sequence presents highly nonlinear and random characteristics. In order to improve the accuracy of runoff prediction, this study proposed a runoff prediction model based on fuzzy information granulation (FIG) and back propagation neural network (BPNN) improved with genetic algorithm (FIG-GA-BP). First, FIG was used to process the original runoff data to generate three sequences of minimum, average, and maximum that can reflect the rule of runoff changes. Then, genetic algorithms (GA) were used to obtain the optimal initial weights and thresholds of the BPNN through selection, crossover, and mutation. Finally, BPNN was used to predict the generated three sequences separately to obtain the prediction interval. The proposed model was applied to the monthly runoff interval prediction of Linjiacun and Weijiabu hydrological stations in the main stream of the Wei River and Zhangjiashan hydrological station on Jing River, a tributary of the Wei River. Compared with the interval prediction model FIG-BP, FIG-WNN, and traditional BP model. The results show that the FIG-GA-BP interval prediction model had a good prediction effect, with higher prediction accuracy and a narrower range of prediction intervals. Therefore, this model has superiority and practicability in monthly runoff interval prediction.

Attribution and Sensitivity Analysis of Runoff Variation in the Yellow River Basin under Climate Change

The Yellow River Basin is a typical arid and semi-arid area, which is very sensitive to climate change. In recent years, it has become the area with the greatest shortage of water resources in China. In this study, a new two-way coupling model of land surface and hydrology has been explored to analyze the impacts of climate change and human activities on the runoff. It is of great theoretical and practical significance for making better management countermeasures and strategies to cope with climate change in the Yellow River Basin. The results showed that: (1) the annual average precipitation in the basin was 470.1 mm, which was higher in the lower reaches than in the middle and upper reaches. The annual average temperature is 5.8 °C. The entire basin showed a remarkable warming speed. The annual average pan evaporation is 1067.3 mm showing a downward trend throughout the basin; (2) from 1987 to 2009, the contribution rate of climate change to runoff change has not fluctuated by more than 5%. Since 2010, the precipitation caused by climate factors has increased runoff by 12~15%. The impact of land use change on runoff has been increasing annually. The influence of projects on runoff change was the leading factor of runoff reduction in the Yellow River Basin, with the contribution rate around 50%; and (3) for every 10% decrease in precipitation, the runoff decreases by 13~15.7%. When the temperature rises by 1.0 °C, the runoff decreases by 2.1~4.2%. The runoff in the upper reaches of the Yellow River was most sensitive to precipitation and temperature changes. This showed that the runoff in the plateau and mountainous areas were highly sensitive to climate change.

Factors Affecting Runoff and Sediment Load Changes in the Wuding River Basin from 1960 to 2020

To investigate changes in runoff and sediment load in the Wuding River basin under the combined influence of climate change and human activities, trends were analyzed from 1960 to 2020, and the contribution rate of climate change and human activities was calculated. It was observed that the runoff and sediment load Mann–Kendall test value ranges at eight gauging stations were −7.42 to −3.88 and −9.28 to −3.34, respectively, indicating a significant decreasing trend in both. During the period of 1970–2000, the contribution of human activities to the reduction in runoff and sediment load was 69.9% and 75.3%, respectively. However, the impact of human activities intensified after 2001 due to the implementation of the policy of returning farmland to forests in the Wuding River basin, which contributed to 118.4% and 114.5% of the reduction in runoff and sediment load, respectively. Check dam and reservoir construction, reforestation, water diversion, and other human activities were all important factors in runoff and sediment load reduction. In particular, the total sediment retention by reservoirs in the Wuding River basin was approximately 879 million tons until 2010, and the total sediment retention by check dams was approximately 2747 million t until 2017. This study can provide support for the utilization of water resources and the construction of ecological civilization in the Wuding River basin, and can also provide a reference for the study of water and sediment changes in other basins.

Quantifying the impact of climate change and human activities on runoff at a tropical watershed in South China

Different regions exhibit different response patterns of hydrological process changes under changing environments. The hydrological response mechanism of underlying surface changes in tropical rainforest regions remains uncertain, so there is an urgent need to study the causes of hydrological changes in typical tropical watersheds. The sequential clustering analysis and Pettitt-Mann-Whitney test were employed to detect abrupt change points of runoff series for the Wanquan River Basin in the tropics, and the series was then divided into pre-impact period (1967–1990) and post-impact period (1991–2014). And the Soil and Water Assessment Tool (SWAT) model was used to simulate the runoff to quantify the impact of climate change, land use change and other human activities on runoff, which the latter two collectively referred to as “human activities” in this study. The findings reveal: 1) runoff series showed an abrupt change and a downward trend around the year 1990; the SWAT model has a good simulation in the Wanquan River Basin during the pre-impact period; the coefficients of determination (R2) for the calibration and validation periods are both 0.91, and the Nash-Sutcliffe model efficiency coefficients (NSE) for the calibration and validation periods are 0.89 and 0.86, respectively. 2) There was a considerable change in land use between 1967 and 2014, as evidenced by a decrease of 29.54% in natural forest and an increase of 54.90% in rubber. These land use changes were mostly caused by the transformation of tropical rainforests into rubber forests and orchards. 3) Runoff declined in the post-impact period from the pre-impact period, with climate change, land use change, and other human activities contributing 44.05%, 10.83%, and 45.12% to the runoff change, respectively. The conversion of tropical rain forests to rubber forests and orchards has indirectly led to a reduction in runoff. These results can provide a reference for understanding the evolution of water cycle for other tropical rivers.

Decomposing the impacts of climate change and human activities on runoff changes in the Yangtze River Basin: Insights from regional differences and spatial correlations of multiple factors

On large scales, runoff changes are complex due to the regional differences in basin characteristics and interactions among multiple influencing factors. Accurately and quantitatively decomposing the impacts of climate change and human activities on runoff changes in large basins with significant spatial heterogeneity remains a challenge. In this paper, the fuzzy C-means (FCM) algorithm was used to identify the regional differences in hydrological processes of the Yangtze River Basin (YZRB) based on multiple factors. Then, regional Budyko equations with synthetic parameters were constructed for runoff decomposition using the hierarchical Bayesian model, considering the spatial correlations of multiple factors among basins. Results showed that 44 subbasins in the YZRB can be clustered into five clusters based on 10 factors including precipitation, temperature, precipitation seasonality, vegetation coverage, saturated hydraulic conductivity, elevation, slope, topographic wetness index, irrigation water consumption, and proportion of built-up area per unit area. From Cluster 1 to 5, P, T, IRR, and B decreased from about 1400 mm, 17 °C, 57.9 mm, and 1.59 % to about 870 mm, 12 °C, 15.6 mm, and 0.40 %, respectively, while ELEV and SLP increased from about 300 m and 3° to about 3500 m and 10°, respectively. Hierarchical Bayesian models can improve the performance of Budyko equations by better-simulating n, compared with linear regression models. Their R2, RB, and RMSE for the whole YZRB were as follows: 0.9104 versus 0.7591, 4.33 % versus 8.21 %, and 0.06 versus 0.11, respectively. Runoff decomposition from 1982 to 2018 showed that precipitation led to more than 34 % change in runoff in Cluster 2, while the influence of potential evapotranspiration on runoff changes was less than 3.00 % in each cluster. Rising temperature caused runoff to decrease by more than 7.90 % in Cluster 1, 3, and 4. In addition, precipitation seasonality, vegetation, and irrigation water consumption had different influences in different clusters. This study improves the ability of the Budyko equation to quantitatively decompose the impacts of multiple factors on regional runoff changes and provides more reasonable suggestions for water resource management.

A framework for attributing runoff changes based on a monthly water balance model: An assessment across China

During the last decades, significant changes in runoff (Q) have been reported in many regions, and attributing the changes is of great significance for water resource management. The conventionally used elasticity method based on the Budyko hypothesis neglects the impacts of climate seasonality on annual Q change (ΔQ), and it is not yet well understood how the climate change and anthropogenic activities influence seasonal Q. Therefore, we propose a framework based on the ABCD model to explicitly identify the effects of climate change and anthropogenic disturbance on annual and seasonal ΔQ, and further apply it in 191 catchments across China from 1960 to 2000. The trend in annual Q exhibits a significant (α = 0.05) decreasing trend in most northern catchments and increasing trend in some catchments of the lower reaches of Yangtze River and Southeast Basin. The trend in seasonal Q in the northern catchments shows decreasing trend during all seasons, while most in the southern catchments shows increasing trend especially in summer. Regarding the causes for annual ΔQ, climate change has positive and negative effects in 60 % and 40 % catchments, respectively, and is the dominant factor in the catchments of the Yangtze River Basin, Southeast Basin and Pearl River Basin. Human activities have positive and negative effects in 20 % and 80 % catchments, respectively, and are the dominant factor in north China. Precipitation is the dominant climatic driver in 72 % catchments. For the causes for seasonal ΔQ, climate change increases Q in southeastern catchments during all seasons, while it decreases Q in northern catchments during autumn and winter. Human activities decrease Q in more than half of the catchments except in winter. The climate seasonality cannot be ignored and our proposed framework is superior to the elasticity method in capturing the impacts of climate seasonality on ΔQ. The elasticity method causes more than 5 % deviation of the contribution ratio of climate change to ΔQ in 48 catchments. In addition, this framework is reliable on multi-annual timescales and provides important reference for water resource management.

Can Model Parameterization Accounting for Hydrological Nonstationarity Improve Robustness in Future Runoff Projection?

Abstract Dominant hydrological processes of a catchment could shift due to a changing climate. This climate-induced hydrological nonstationarity could affect the reliability of future runoff projection developed using a hydrological model calibrated for the historical period as the model or parameters may no longer be suitable under a different future hydroclimate. This paper explores whether competing parameterization approaches proposed to account for hydrological nonstationarity could improve the robustness of future runoff projection compared to the traditional approach where the model is calibrated targeting overall model performance over the entire historical period. The modeling experiments are carried out using climate and streamflow datasets from southeastern Australia, which has experienced a long drought and exhibited noticeable hydrological nonstationarity. The results show that robust multicriteria calibration based on the Pareto front can provide a more consistent model performance over contrasting hydroclimate conditions, but at a slight expense of increased bias over the entire historical period compared to the traditional approach. However, the robust calibration does not necessarily result in a more reliable projection of future runoff. This is because the systematic bias in any parameterization approach would propagate from the historical period to the future period and would largely be cancelled out when estimating the relative runoff change. Ensemble simulations combining results from different parameterization considerations could produce a more inclusive range of future runoff projection as it covers the uncertainties due to model parameterization.

Separating the impact of check dams on runoff from climate and vegetation changes

Check dam is an important soil and water conservation engineering measure for the prevention and control of soil erosion on the Loess Plateau in China. However, how the check dams influence runoff at different catchments remains unclear. This study uses a modified hydrological model (SWAT-PML) to quantitatively distinguish the impact of check dams on the runoff from climate and vegetation changes and to identify the relationship between runoff reduction and check dam storage capacity for six check dam influenced catchments on the Loess Plateau. Results show that compared to the slow increase before 1997, leaf area index (LAI) significantly (p < 0.01) increased in these six catchments after 1997. The construction of check dams started before 1997 in five catchments, and reached a peak between 2005 and 2010 for all six catchments. Check dam construction and vegetation greening reduced runoff in all catchments, while climate change reduced runoff in three catchments but increased runoff in the remaining three. Among the impact factors, the check dams contributed the most to runoff change. Furthermore, the cumulative reduction amount of runoff grew rapidly with the development of check dam storage capacity before the turning point (around the year 2000), while it turned to a slow increase after the turning point. This research provides reference and guidance for the construction and management of soil and water conservation measures, as well as the planning and sustainable utilization of water resources on the Loess Plateau.

Research and Application of the Mutual Feedback Mechanism of a Regional Natural-Social Dualistic Water Cycle: A Case Study in Beijing–Tianjin–Hebei, China

With the intensification of human activities, the natural water cycle has a significant nature-society dual feature, and identifying the mutual feedback mechanism between natural and social water cycles is an important basis for a more accurate simulation of the dualistic water cycle. In this study, two indexes of cumulative runoff change rate and social water cycle feedback rate are put forward, representing the degree of change in socio-hydrological unit runoff under the mutual feedback of the natural social water cycle in all upstream regions, and the degree influence of the water intake, consumption, and discharge process of the social water cycle on the natural water cycle in the socio-hydrological unit, respectively. Taking the Beijing–Tianjin–Hebei region, which is marked by strong human activities, as the study area, the 2035 natural-social dualistic water cycles were simulated by a water allocation and simulation (WAS) model. Different water supply types and use structures cause the social water cycle to increase or decrease local runoff in different areas. The social water cycle feedback rate is greater than 1 in Beijing and Tianjin, and less than 0.25 in the mountainous areas and the Hebei plain, indicating that the social water cycle of each unit in the Beijing–Tianjin–Hebei region increases or decreases local runoff due to different water supply types and use structures. The cumulative runoff change rate in this region was 0.66, indicating that the overall runoff was attenuated due to the social water cycle, and runoff attenuation was greater in the south than the north.

Helheim Glacier ice velocity variability responds to runoff and terminus position change at different timescales

The Greenland Ice Sheet discharges ice to the ocean through hundreds of outlet glaciers. Recent acceleration of Greenland outlet glaciers has been linked to both oceanic and atmospheric drivers. Here, we leverage temporally dense observations, regional climate model output, and newly developed time series analysis tools to assess the most important forcings causing ice flow variability at one of the largest Greenland outlet glaciers, Helheim Glacier, from 2009 to 2017. We find that ice speed correlates most strongly with catchment-integrated runoff at seasonal to interannual scales, while multi-annual flow variability correlates most strongly with multi-annual terminus variability. The disparate time scales and the influence of subglacial topography on Helheim Glacier’s dynamics highlight different regimes that can inform modeling and forecasting of its future. Notably, our results suggest that the recent terminus history observed at Helheim is a response to, rather than the cause of, upstream changes.

Quantitative hydrological response to climate change and human activities in North and South Sources in upper stream of Qiantang River Basin, East China

Study regionThe North and South Sources in the upper stream of Qiantang River Basin, China. Study focusIdentifying the relative contribution of climate change and human activities to runoff variation is essential for an enhanced understanding on efficient management of regional water resources. We used multiplied abrupt change testing methods to determine the baseline period (BP) and two variation periods (VP1 and VP2) and used six Budyko-based methods to detect the quantitative hydrological response to climate change and human activities. New hydrological insights for the regionThe annual mean runoff of North Source witnessed a decrease in VP1 before it increased during VP2, while it continued to increase in South Source. The climate change dominated the runoff variation in the North Source, while it was human activities that was the main driver for South Source.The human-induced effect contributed to runoff decline in North Source, while it led to the continuous runoff increasing in South Source. It shows that the runoff change due to climate was more sensitive to precipitation than potential evapotranspiration. The land use analysis illustrates that human-induced runoff changes were composed of two aspects: 1) the increased proportion of woodland and decreased ratio of farmland reduced runoff; 2) the increased percentage of town-and-country-land increased runoff. The former influence was relatively limited compared to the latter, as well as the climate change.

Runoff Regime, Change, and Attribution in the Upper Syr Darya and Amu Darya, Central Asia

Abstract The upper Syr Darya (USD) and Amu Darya (UAD) basins are the two biggest flow formation zones in central Asia and the only water supply sources for the Aral Sea. Upstream snow and ice reserves of those two basins, important in sustaining seasonal water availability, are highly sensitive and prone to climate change, but their importance and changes are still uncertain and poorly understood due to data scarcity, inaccessibility, harsh climate, and even geopolitics. Here, an improved forcing dataset of precipitation and temperature was developed and used to drive a physically based hydrological model, which was thoroughly calibrated and validated to quantify the contributions of different runoff components to total flow and the controlling factors for total runoff variations for 1961–2016. Our analysis reveals divergent flow regimes exist across the USD and UAD and an ongoing transition from nival–pluvial toward a volatile pluvial regime along with rising temperatures. Annual total runoff has weakly increased from 1961 to 2016 for the entire USD and UAD, while the subbasins displayed divergent flow changes. Spring runoff significantly increased in all the USD and UAD basins primarily due to increased rainfall and early snow melting, tending to shift the peak flow from June–July to April–May. In contrast, distinct runoff changes were presented in the summer months among the basins primarily due to the trade-off between the increase in rainfall and the decrease in snowmelt and glacier runoff. These findings are expected to provide essential information for policymakers to adopt strategies and leave us better poised to project future runoff changes in ongoing climate change.

Evolutionary effect separation of watershed characteristics for the multi-source contributions to runoff changes in the Yellow River, China

• Evolutionary effect of watershed characteristics (EE WC ) to runoff change is proven. • Runoff-change multisource contributions are separated with a theoretical framework. • EE WC has an important contribution to areal change of watershed characteristics. • EE WC is more stable than climate change and human activity. • Traditional runoff-change two-source rationale is improved to three-source effect. Traditionally, consideration of the contributors to runoff change includes only climate change and human activity. Furthermore, the runoff change effects of traditional climate change include non-climate change components. This could cause a problem of two-source unclosed calculation that total runoff change doesn’t equal the dual contributions from climate change and anthropogenic influences. This study uncovers that the two-source unclosed problem is related to the natural evolution in the watershed characteristics (WCs), which is called the evolutionary effect of WCs (EE WC ). A theoretical framework was proposed to separate the three-source areal changes of WCs from climate change, two types of anthropogenic influence, and EE WC . The three-source contributions to runoff changes were quantified through three hydrological models and the observability and controllability model of periphery. The EE WC was innovatively proven and demonstrated in the upper and middle Yellow River of Northwest China. The WCs were expressed by land use/land cover (LULC) and soil/water conservation measures (SWCMs) in this study. Hydrometeorological data, water utilization data from different sectors, and areal data of LULC and SWCMs on the annual scale during 1956–2015 were employed. The contribution of climate change on runoff changes was innovatively divided into the one from the changing area of WCs and the other one from the unchanged area of WCs. Two non-climate change components from traditional climate change contributions were separated. The EE WC has an important influence on areal change of WCs and is more stable in comparison with meteorological elements and anthropogenic influences. The framework is flexible regarding the use of referenced/change periods. The results overcome the shortcomings of traditional approaches and further improve the traditional two-source rationale to the three-source effects of climate change, anthropogenic influence, and EE WC .

Understanding the hydrological regime based on the runoff events in a mountainous catchment with seasonally frozen soil in the Qinghai‐Tibet plateau

AbstractSeasonal thawing of frozen soil will significantly affect the hydrological regime, water storage capacity and ecosystem services in the future, which contributes to the uncertainty of regional water resources. However, based on the scale of runoff events, the mechanism of seasonal frozen soil thawing on the hydrological regime are still unclear. In this study, we systematically analysed the runoff characteristics and interactive effects of environmental factors and pre‐event catchment state on runoff processes based on the runoff event scale, using data sets of air temperature, precipitation, runoff, soil moisture, and soil temperature observed in a mountainous catchment with seasonally frozen soil distribution on the Qinghai‐Tibet Plateau from 2010 to 2019. It was found that the event runoff coefficient did not increase significantly with the increase of precipitation. Event runoff coefficients exhibited strong seasonality. The catchment exhibited a gradual increase in the event runoff coefficient with increasing pre‐event baseflow and antecedent soil moisture, especially during stable period (August to November). Event runoff generation through infiltration excess as the result of intensive rainfall seemed to be only possible in the stable period, while heavy precipitation events were common during this period. Normalized event peak discharge and event runoff coefficient showed positive trends with changes in pre‐event catchment state indicators, which were commonly observed phenomena in runoff events. For this catchment, the increased storage capacity pre‐event saturation may be the main mechanism of event runoff generation, as it was unlikely that a single precipitation event would lead to catchment saturation. Soil temperature affects runoff processes through both direct effects on runoff processes and indirect effects on pre‐event catchment state. Temperature indicators were the most important predictors of runoff changes in the Qinghai‐Tibet Plateau.

Cost-effectiveness analysis of extensive green roofs for urban stormwater control in response to future climate change scenarios

Green roof, as a popular low impact development practice, has become important to mitigate adverse impacts of future climate change on urban stormwater. However, there is limited information regarding assessment of the effectiveness of green roofs in response to uncertain future climate change challenges. In this study, the validated model was used to simulate the reduction performance of green roofs on urban catchment outflow and assess their cost-effectiveness in response to design storms under climate change scenarios. Results showed that the median runoff volume of urban catchments increased by 12.5 %–14.6 % and 15.5 %–18.1 % and the median peak flow rate increased by 14.4 %–17.8 % and 17.9 %–22.1 % under SSP2-4.5 and SSP5-8.5 scenarios, respectively. This indicated the variability of runoff volume and peak flow changes for short return storm events caused by climate change was relatively high. Green roof implementation had reasonable mitigation effects on runoff volume and peak flow amplification in urban catchments caused by climate change. The median runoff volume reduction of green roofs for the 1-year storm was 15.2 % under SSP2-4.5 scenario. As rainfall intensity increased, the median runoff volume reduction of green roofs significantly declined to 5.6 % for the 100-year storm. However, the variations of runoff volume and peak flow reduction of green roofs were relatively smaller for longer return periods under climate change scenarios. Runoff reduction percentages of green roofs increased linearly with their implementation cost. The average value of the cost-effectiveness (C/E) index for green roofs was 91.2 %/million $ under base climate condition, and it decreased to 88.9 %/million $ and 88.4 %/million $ for SSP2-4.5 and SSP5-8.5 scenarios, respectively. The C/E values decreased with increasing storm return period, and the values were relatively lower in SSP5-8.5 scenarios. These results could help to understand the potential role of green roofs to mitigate the impacts of future climate change.

Analysis of runoff variation and driving factors in the Minjiang River Basin over the last 60 years

Abstract An absolute essential for effective water resource management and ecological restoration is knowing the temporal and spatial variation of runoff. The objective of this study was to determine the spatial and temporal changes in runoff at the main hydrological stations along the Minjiang River and the Dadu River between 1961 and 2016 using the non-parametric Mann-Kendall test and annual variation analysis. Canonical correspondence analysis and regression analysis were used to determine the contribution of anthropogenic disturbance, vegetation, and climatic conditions to runoff change. The runoff at each station of the Minjiang River showed a clear decreasing trend, whereas the decreasing trend of the Dadu River was not significant. Moreover, the discharge at the Shawan (SW) station upstream of the Dadu River and the Gaochang (GC) station downstream of the Minjiang River have changed significantly during the flood and non-flood seasons since 2000, while the discharge at other stations has not changed significantly. The average annual runoff in the non-flood season at SW and GC in 2011–2016 increased by approximately 26.21 and 36.47%, respectively, compared with 1961–2010. Anthropogenic disturbance, vegetation, and climatic conditions in the Minjiang River Basin accounted for 76.24, 13.62, and 10.14%, respectively, of the runoff change in the basin. Water consumption and total reservoir capacity were the specific factors most affecting runoff change in the basin, accounting for 15.10 and 13.94%, respectively, of the changes in runoff. The research can provide important support for the ecological restoration of Minjiang River Basin and Yangtze River Basin.

Influence of cascade reservoir operation in the Upper Mekong River on the general hydrological regime: A combined data-driven modeling approach

Cross-border impact assessment of cascade reservoir operation on hydrological regimes is a vital prerequisite for the sustainable development and management of transboundary waters. However, assessment based on traditional hydrological modeling for transboundary rivers is limited by the availability of meteorological and hydrological data. In this study, a combined data-driven model (CV-LSTM) was built to simulate natural runoff without dam construction in the Upper Mekong River. Then, the simulated natural runoff was compared against the observation runoff influenced by dam operation to assess the impacts of reservoirs on flood and drought events. The research results are as follows: (1) CV-LSTM improved simulation performance by effectively utilizing spatial information from more extensive and diversified data, and it could overcome the limitation of classic data-driven models in that the spatial heterogeneity of input variables cannot be sufficiently considered. (2) Reservoir operation decreased the annual streamflow of the Upper Mekong River by 1.07% during the 2001–2016. In particular, with the operation of two mega reservoirs (Xiaowan and Nuozadu) after 2008, the annual streamflow decreased by 3.95%. (3) The upstream reservoirs exerted significant runoff regulative effects on the Lower Mekong during 2001–2016. Drought duration and severity significantly decreased at the Chiang Sean hydrological station, flood frequency decreased by 11%, and the mean day of flood occurrence decreased by 30%. This study developed an innovative approach, CV-LSTM, based on open-source spatial information, which could effectively analyze the cross-border impact of cascade reservoir operation. The results provide new insights into the quantitative assessment of the transboundary influence of upstream-downstream runoff change induced by cascade dams in international rivers.

Runoff response to changing environment in Loess Plateau, China: Implications of the influence of climate, land use/land cover, and water withdrawal changes

The influence of climate change and human interference bring high nonstationary characteristics that are different from the original long-term stable state. So that, investigating runoff variation and attribution under changing environments is important for implementing adaptive management of global water resources, especially on the interannual scale. In this study, the attribution of measured runoff change in the Wuding River Basin (WRB) of the Loess Plateau, China, was studied using the elasticity method based on the Budyko framework and groundwater storage change analysis on an interannual scale. The change in the measured runoff driven factors was divided into three categories: climate change, human-induced land use/land cover (HI-LULC) change, and water withdrawal change. The results show that the contribution rate of climate change was the largest (with the mean value 54.07%), followed by the HI-LULC change (with the mean value 43.85%), and the minimum is WW change (with the mean value 2.08%). Climate change had a maximum contribution to runoff change, of which precipitation was dominant, followed by relative humidity, net radiation, and wind speed; air temperature had a minimal impact. In addition, the ecological change tendency was analyzed by combining HI-LULC and NDVI data. The analysis results of ecological change tendency indicate that the policy implementation of soil and water erosion control caused the ecological restoration to some extent, but also led to a decrease in runoff. This study provides scientific and useful information for the conservation of water and soil, runoff prediction, and sustainable water resource management in the WRB, and enriches the knowledge of contribution analysis of runoff variation which can be referenced by other basins across the globe.

Exploring the impact of landscape changes on runoff under climate change and urban development: Implications for landscape ecological engineering in the Yangmei River Basin

The increase in impervious surfaces caused by urbanization and the frequency of precipitation events resulting from climate change significantly impact the hydrological and geomorphological processes of urban watersheds. Landscape changes caused by urban development may affect surface/groundwater generation and circulation processes. In-depth research on the relationship between landscape changes and runoff is a precondition of urban watershed restoration and stormwater management. Taking the Yangmei River Basin as the study area, the storm water management model (SWMM), landscape index, correlation analysis, and the random forest importance measure were integrated to simulate the runoff process under urban development and climate change scenarios and analyze the direction and contribution of landscape composition and configuration to runoff changes. Results indicated that the runoff change rate relative to the reference period under the RCP 4.5 and RCP 8.5 scenarios gradually decreased as the return period increased. Landscape composition and configuration were significantly correlated with runoff change. Specifically, woodland could reduce runoff, while farmland and water bodies positively impacted runoff changes. The higher fragmented landscape pattern was likely to have altered the runoff, while landscape patterns of a larger size, higher concentrations, and a declining richness typically reduced runoff. The random forest importance evaluation demonstrated the significant contributions of Patch Density, Shannon's Diversity Index, and Large Path Index to runoff. By exploring the potential relationship between landscape changes and runoff, urban planners can better understand the runoff process and find feasible ecological landscape optimization schemes, thus strengthening the sustainable management of water resources and enhancing the resilience of cities to climate change.