ORCID Profile
0000-0002-5298-9573
Current Organisation
Wuhan University
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Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2016
Publisher: Elsevier BV
Date: 11-2020
Publisher: Springer Science and Business Media LLC
Date: 23-10-2014
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 08-2018
Publisher: Springer Science and Business Media LLC
Date: 25-04-2016
DOI: 10.1038/NCLIMATE3004
Publisher: MDPI AG
Date: 12-02-2020
DOI: 10.3390/W12020508
Abstract: Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.
Publisher: Elsevier BV
Date: 12-2022
Publisher: Copernicus GmbH
Date: 19-08-2019
DOI: 10.5194/HESS-23-3405-2019
Abstract: Abstract. Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. Many existing studies model the time-varying parameters as functions of physically based covariates however, a major challenge remains in finding effective information to control the large uncertainties that are linked to the additional parameters within the functions. This paper formulated the time-varying parameters for a lumped hydrological model as explicit functions of temporal covariates and used a hierarchical Bayesian (HB) framework to incorporate the spatial coherence of adjacent catchments to improve the robustness of the projection performance. Four modeling scenarios with different spatial coherence schemes and one scenario with a stationary scheme for model parameters were used to explore the transferability of hydrological models under contrasting climatic conditions. Three spatially adjacent catchments in southeast Australia were selected as case studies to examine the validity of the proposed method. Results showed that (1) the time-varying function improved the model performance but also lified the projection uncertainty compared with the stationary setting of model parameters, (2) the proposed HB method successfully reduced the projection uncertainty and improved the robustness of model performance, and (3) model parameters calibrated over dry years were not suitable for predicting runoff over wet years because of a large degradation in projection performance. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.
Publisher: Elsevier BV
Date: 03-2019
Publisher: American Geophysical Union (AGU)
Date: 02-02-2017
DOI: 10.1002/2016JD025936
Publisher: IOP Publishing
Date: 14-04-2021
Abstract: Economic development, resource scarcity and climate change pose enormous challenges to the food–energy–water (FEW) nexus, calling for integrative resources governance to improve the synergy between subsystems. However, it is unclear about the synergy evolution of the FEW nexus in temporal and spatial scales. This paper uses the network analysis to explore the FEW nexus in China’s Yangtze River Economic Belt. First, the comprehensive index system containing subsystems, order parameters and eigenvectors are determined in causal paths. Second, the synergetic network among order parameters is developed, and the centrality analysis is then conducted to identify the influencing factors. Third, the Bayesian network among eigenvectors is constructed to analyze the sensitivity of the dominant influencing factors. The results show that: (a) Energy subsystem has the highest centralities and dominates the FEW nexus. (b) From the perspective of time variability, the network centralization reaches the highest in 2007, but reaches the lowest in 2013, showing a downward trend, so we should adhere to the national strategy of synergetic development to realize the resource sustainability. (c) From the perspective of spatial sensitivity, upper reach (UR) is sensitive to food-related factors while lower reach (LR) is sensitive to energy-related factors. Therefore, the development of agriculture in upper UR should focus on protection, and the development of industry in LR should focus on remediation. The significance of the research is to construct a network analysis framework for better understanding the spatio-temporal variability of the FEW nexus in Yangtze River Economic Belt.
Publisher: Copernicus GmbH
Date: 20-12-2022
DOI: 10.5194/HESS-26-6379-2022
Abstract: Abstract. Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether this change can occur in catchments that have also experienced vegetation change and whether it invalidates the most widely used methods for estimating impacts of vegetation change – i.e., the paired-catchment method (PCM), the time–trend method (TTM), and the sensitivity-based method (SBM) – on runoff is still unknown and rarely discussed. Estimated inconsistent afforestation impacts were 32.8 %, 93.5 %, and 76.1 % of total runoff changes in the Red Hill paired experimental catchments in Australia during the period of 1990–2015 by the PCM, TTM, and SBM, respectively. In addition to afforestation, the Red Hill paired experimental catchments have experienced a 10-year drought (2000–2009) and have been demonstrated to lead to non-stationary rainfall–runoff relationships of paired catchments. Estimated impacts of vegetation change by the PCM (32.8 %) is still reliable and is not invalided by multiyear drought-induced non-stationarity, because the PCM can eliminate all impacts by different factors on paired catchments (multiyear drought and climate variability), except the purposed treatment (afforestation). For the TTM and SBM, traditional application did not further differentiate different drivers of non-stationary rainfall–runoff relationship (i.e., multiyear drought and vegetation change), which led to significant overestimation of afforestation effects. A new framework was further proposed to separate the effects of three factors on runoff changes, including vegetation change, climate variability, and hydroclimatic non-stationarity (i.e., multiyear drought). Based on the new framework, impacts of multiyear drought and climate variability on runoff of the control catchment (Kileys Run) were 87.2 % and 12.8 %, respectively. Impacts of afforestation, multiyear drought, and climate variability on runoff of the treated catchment (Red Hill) were 32.8 %, 54.7 %, and 23.9 %, respectively. Impacts of afforestation on runoff were 38.8 % by the TTM and 21.4 % by the SBM, agreeing well with that by the PCM (32.8 %). This study not only demonstrated that multiyear drought can induce non-stationary rainfall–runoff relationship using field observations, but also proposed a new framework to better separate the impact of vegetation change on runoff under climate-induced non-stationary condition. More importantly, it is shown that non-stationarity induced by multiyear drought does not invalidate the PCM, and PCM is still the most reliable method even though the control catchment experienced climate-induced shift in the rainfall–runoff relationship.
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.JENVMAN.2018.12.040
Abstract: Baseflow is the portion of streamflow that originates from groundwater. It is pivotal to groundwater supply as well as the interactions between groundwater and surface water. In the Loess Plateau of China, the baseflow plays a fundamental role in sustaining the aquatic ecosystem. Rational estimation of baseflow is of critical importance for understanding the functioning of the groundwater system and informing management of regional water resources. In this study, a two-well parameterised digital filter was used to separate baseflow from observed daily total streamflow on the Weihe River Basin. Two parameters (maximum baseflow index (BFI
Publisher: Elsevier BV
Date: 10-2019
Publisher: Elsevier BV
Date: 12-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2019
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: MDPI AG
Date: 04-07-2019
DOI: 10.3390/RS11131596
Abstract: Drought is one of the most widespread and threatening natural disasters in the world, which has terrible impacts on agricultural irrigation and production, ecological environment, and socioeconomic development. As a critical ecologically fragile area located in southwest China, the Yarlung Zangbo River (YZR) basin is sensitive and vulnerable to climate change and human activities. Hence, this study focused on the YZR basin and attempted to investigate the spatiotemporal variations of drought and associated multi-scale response to climate change based on the scPDSI (self-calibrating Palmer drought severity index) and CRU (climate research unit) data. Results showed that: (1) The YZR basin has experienced an overall wetting process from 1956 to 2015, while a distinct transition period in the mid 1990s (from wet to dry) was detected by multiple statistical methods. (2) Considering the spatial variation of the scPDSI, areas showing the significantly wetting process with increasing scPDSI values were mostly located in the arid upstream and midstream regions, which accounted for over 48% area of the YZR basin, while areas exhibiting the drying tendency with decreasing scPDSI values were mainly concentrated in the humid southern part of the YZR basin, dominating the transition period from wet to dry, to which more attention should be paid. (3) By using the EEMD (ensemble empirical mode decomposition) method, the scPDSI over the YZR basin showed quasi-3-year and quasi-9-year cycles at the inter-annual scale, while quasi-15-year and quasi-56-year cycles were detected at the inter-decadal scale. The reconstructed inter-annual scale showed a better capability to represent the abrupt change characteristic of drought, which was also more influential to the original time series with a variance contribution of 55.3%, while the inter-decadal scale could be used to portray the long-term drought variation process with a relative lower variance contribution of 29.1%. (4) The multi-scale response of drought to climate change indicated that changes of precipitation (PRE) and diurnal temperature range (DTR) were the major driving factors in the drought variation at different time scales. Compared with potential evapotranspiration (PET), DTR was a much more important climate factor associated with drought variations by altering the energy balance, which is more obvious over the YZR basin distributed with extensive snow cover and glaciers. These findings could provide important implications for ecological environment protection and sustainable socioeconomic development in the YZR basin and other high mountain regions.
Publisher: Copernicus GmbH
Date: 26-11-2012
DOI: 10.5194/HESS-16-4447-2012
Abstract: Abstract. The goal of this paper is to explore the process controls underpinning regional patterns of variations of streamflow regime behavior, i.e., the mean seasonal variation of streamflow within the year, across the continental United States. The ultimate motivation is to use the resulting process understanding to generate insights into the physical controls of another signature of streamflow variability, namely the flow duration curve (FDC). The construction of the FDC removes the time dependence of flows. Thus in order to better understand the physical controls in regions that exhibit strong seasonal dependence, the regime curve (RC), which is closely connected to the FDC, is studied in this paper and later linked back to the FDC. To achieve these aims a top-down modeling approach is adopted we start with a simple two-stage bucket model, which is systematically enhanced through addition of new processes on the basis of model performance assessment in relation to observations, using rainfall-runoff data from 197 United States catchments belonging to the MOPEX dataset. Exploration of dominant processes and the determination of required model complexity are carried out through model-based sensitivity analyses, guided by a performance metric. Results indicated systematic regional trends in dominant processes: snowmelt was a key process control in cold mountainous catchments in the north and north-west, whereas snowmelt and vegetation cover dynamics were key controls in the north-east seasonal vegetation cover dynamics (phenology and interception) were important along the Appalachian mountain range in the east. A simple two-bucket model (with no other additions) was found to be adequate in warm humid catchments along the west coast and in the south-east, with both regions exhibiting strong seasonality, whereas much more complex models are needed in the dry south and south-west. Agricultural catchments in the mid-west were found to be difficult to predict with the use of simple lumped models, due to the strong influence of human activities. Overall, these process controls arose from general east-west (seasonality) and north-south (aridity, temperature) trends in climate (with some exceptions), compounded by complex dynamics of vegetation cover and to a less extent by landscape factors (soils, geology and topography).
Publisher: American Geophysical Union (AGU)
Date: 07-2017
DOI: 10.1002/2017WR020600
Publisher: Elsevier BV
Date: 10-2018
Publisher: IOP Publishing
Date: 23-11-2020
Abstract: Over recent decades, concern has grown regarding the effects of climate change and artificial river projects on the variability of river floods. Specifically, it has been demonstrated that the Mississippi River flood hazard has been lified by river engineering. In contrast, the world’s largest reservoir group with the Three Gorges Reservoir at its core has been built along the upper reaches of the Yangtze River, but the question of whether there has been a positive effect on flood control is worthy of discussion. Here, we revisit nine paleofloods from the ancient stone inscriptions for the first time and show that while annual peak discharge in the upper reaches of the Yangtze River is dominated by sunspot numbers and the North Atlantic Oscillation, the magnitude of flooding has been decreased by the reservoir group, which diminished flood hazard through reversing or strengthening the direction of climate control on the flood.
Publisher: American Geophysical Union (AGU)
Date: 04-2022
DOI: 10.1029/2021WR031412
Abstract: Long‐term hydrological partitioning of catchments can be well described by the Budyko framework with a parameter (e.g., Fu's equations with parameter ω ). The Budyko framework considers aridity index as the dominant control on hydrological partitioning, while the parameter represents integrated influences of catchment properties. Our understanding regarding the controls of catchment properties on the parameter is still limited. In this study, two machine learning methods, that is, boosted regression tree (BRT) and CUBIST, were used to model ω . Interpretable machine learning methods were adopted for better physical understanding including feature importance, accumulated local effects (ALE), and local interpretable model‐agnostic explanations. Among the 15 properties of 443 Australian catchments, analysis of feature importance showed that root zone storage capacity (SR), vapor pressure, vegetation coverage (M), precipitation depth, climate seasonality and asynchrony index (SAI), and water use efficiency (WUE) were the six primary control factors on ω . ALE showed that ω varied nonlinearly with all factors, and varied non‐monotonically with M, SAI, and WUE. LIME showed that the importance of the six dominant factors on ω varied between regions. CUBIST was further used to build regionally varying relationships between ω and the primary factors. Continental scale ω and evapotranspiration were further mapped across Australia based on the most robust BRT‐trained parameterization scheme with a resolution of 0.05°. Instead of using the machine learning method as a black box, we employed interpretability approaches to identify the controls. Our findings not only improved the capability of the Budyko method for hydrological partitioning across Australia, but also demonstrated that the controls of catchment properties on hydrological partitioning vary in different regions.
Publisher: Elsevier BV
Date: 11-2015
Publisher: IWA Publishing
Date: 11-06-2020
DOI: 10.2166/WCC.2018.184
Abstract: Investigating long-term streamflow changes pattern and its response to climate and human factors is of crucial significance to understand the hydrological cycle under a changing environment. Caijiazhuang catchment located within Haihe River basin, north China was selected as the study area. To detect the trend and changes in streamflow, Mann–Kendall test was used. Elasticity and hydrological simulation methods were applied to assess the relative contribution of climate change and human activities on streamflow variability under three periods (baseline (1958–1977), impact I (1978–1997), and impact II (1998–2012)). The long-term hydro-climatic variables experienced substantial changes during the whole study period, and 1977 was the breaking year of streamflow change. Attribution analysis using the two methods showed consistent results: for impact I, climate change impacts explained 65% and 68% of streamflow reduction however for impact II, it only represented 49% and 56% of streamflow reduction. This result indicated that human activities were intensifying over time. Various types of human activities presented significant effects on streamflow regimes including volumes and hydrographs. The findings of this paper could provide better insights of hydrological evolution and would thus assist water managers in sustainably managing and providing water use strategies under a changing environment.
Publisher: Wiley
Date: 24-09-2022
DOI: 10.1002/JOC.7865
Abstract: In the context of global warming and the release of projection results from the Coupled Model Intercomparison Project Phase 6 (CMIP6), it is important to conduct research on climate change on the Tibetan Plateau (TP) which exhibits unique geographic characteristics and complex climatic conditions. Using 10 general circulation models (GCMs) from CMIP6 corrected for bias by the daily translation (DT) method, we investigated the projected changes in precipitation and air temperature for the mid‐term (2031–2050) and long‐term (2061–2080) of the 21st century on the TP after evaluating the reliability of the bias correction, for four scenarios based on different combinations of shared socioeconomic pathways and representative concentration pathways. The multimodel ensembles (MMEs) indicated that the projected annual precipitation shows an increasing trend for the mid‐term and long‐term periods, with the projected increase for the long‐term primarily concentrated in areas with less precipitation. Meanwhile, the future precipitation changes exhibit a significant elevation dependency. The rate of increase of precipitation firstly fluctuates and then gradually increases along with the elevation increasing from 1,500 to 5,800 m. The valley value of rate mainly appears in two elevation zones (2,200–2,600 m and 3,400–3,800 m). The projected temporal changes in annual air temperatures reveal obvious warming over the TP. The projected warming is overall more pronounced with increase in elevation however, it reaches a peak at approximately 5,000–5,200 m and then slows down slightly, indicating that warming is not dependent on elevation in the higher elevation zones. The present results have important implications for investigating the impacts of climate change on the water cycle in alpine regions.
Publisher: Elsevier BV
Date: 06-2017
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 02-2023
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2018
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 09-2022
Publisher: Wiley
Date: 20-03-2015
DOI: 10.1111/GCB.12873
Abstract: Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2) mm(-1) yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2) mm(-1) yr(-1) ), which differs from process-model (0.0064 g C m(-2) mm(-1) yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt , GPP×VPD/TR) in response to rising CO2 , climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change.
Publisher: Elsevier BV
Date: 06-2021
Publisher: American Society of Civil Engineers (ASCE)
Date: 08-2021
Publisher: MDPI AG
Date: 20-08-2020
DOI: 10.3390/W12092338
Abstract: Global warming has a profound influence on global and regional water cycles, especially in the cold mountainous area. However, detecting and quantifying such changes are still difficult because noise and variability in observed streamflow are relatively larger than the long-term trends. In this study, the impacts of global warming on the catchment water cycles in the Yarlung Zangbo River Basin (YZRB), one of most important catchments in south of the Tibetan Plateau, are quantified using a climatic approach based on the relationship between basin-scale groundwater storage and low flow at the annual time scale. By using a quantile regression method and flow recession analysis, changes in low flow regimes and basin-scale groundwater storage at the Nuxia hydrological station are quantified at the annual time scale during 1961–2000. Results show annual low flows (10th and 25th annual flows) of the YZRB have decreased significantly, while long-term annual precipitation, total streamflow, and high flows are statistically unchanged. Annual lowest seven-day flow shows a significantly downward trend (2.2 m3/s/a, p 0.05) and its timing has advanced about 12 days (2.8 day/10a, p 0.1) during the study period. Estimated annual basin-scale groundwater storage also shows a significant decreasing trend at a rate of 0.079 mm/a (p 0.05) over the study period. Further analysis suggests that evaporation increase, decreased snow-fraction, and increased annual precipitation intensity induced by the rising temperature possibly are the drivers causing a significant decline in catchment low flow regimes and groundwater storage in the study area. This highlights that an increase in temperature has likely already caused significant changes in regional flow regimes in the high and cold mountainous regions, which has alarming consequences in regional ecological protection and sustainable water resources management.
Publisher: Springer Science and Business Media LLC
Date: 15-09-2017
DOI: 10.1038/S41598-017-11063-W
Abstract: Non-forest ecosystems (predominant in semi-arid and arid regions) contribute significantly to the increasing trend and interannual variation of land carbon uptake over the last three decades, yet the mechanisms are poorly understood. By analysing the flux measurements from 23 ecosystems in Australia, we found the the correlation between gross primary production (GPP) and ecosystem respiration (R e ) was significant for non-forest ecosystems, but was not for forests. In non-forest ecosystems, both GPP and R e increased with rainfall, and, consequently net ecosystem production (NEP) increased with rainfall. In forest ecosystems, GPP and R e were insensitive to rainfall. Furthermore sensitivity of GPP to rainfall was dominated by the rainfall-driven variation of LAI rather GPP per unit LAI in non-forest ecosystems, which was not correctly reproduced by current land models, indicating that the mechanisms underlying the response of LAI to rainfall should be targeted for future model development.
Publisher: American Meteorological Society
Date: 02-2020
Abstract: A generalized implementation of the complementary principle was applied to estimate global land surface evaporation and its spatial distribution. The single parameter in the method was calibrated as a function of aridity index, mainly on the basis of runoff and precipitation data for 524 catchments in different parts of the world. The spatial distribution of annual evaporation from Earth’s land surfaces for 2001–13 was then calculated at a spatial resolution of 0.5°, by means of an available global net radiation dataset (commonly referred to as CERES SYN1deg-Day) and a global forcing dataset (referred to as CRU-NCEP v7) for near-surface temperature, humidity, wind speed, and air pressure. The results are shown to agree with reliable previous estimates by more elaborate methods. The global average evaporation for 2001–13 was found to be 472.65 mm a −1 or 36.96 W m −2 . The present method should allow not only future updates but also retroactive historical analyses with routine data of net radiation, near-surface air temperature, humidity, wind speed, and precipitation its main advantage is that the environmental aridity is deduced from atmospheric conditions and requires no knowledge of surface characteristics, such as soil moisture, vegetation, and terrain, which are highly variable and often difficult to quantify at larger spatial scales. Because they are strictly measurement based, the results can serve also as a reality check for different aspects of climate and related models.
Publisher: MDPI AG
Date: 16-11-2022
DOI: 10.3390/RS14225785
Abstract: Urban water bodies are critical for sustainable urban ecological and social development. However, the complex compositions of urban land cover and small water bodies pose considerable challenges to urban water surface delineation. Here, we propose a novel urban water extraction algorithm (UWEA) that is efficient in distinguishing water and other low-reflective objects by combining the modified normalized difference water index (mNDWI) and HSV transformation. The spectral properties of urban land covers were analyzed and the separability of objects in different color spaces was compared before applying the HSV transformation. The accuracy and robustness of the UWEA were validated in six highly urbanized subregions of Beijing, Tokyo, and New York, and compared with the mNDWI and HIS methods. The results show that the UWEA had the fewest total errors (sum of omission and commission errors) for all the validation sites, which was approximately 3% fewer errors than those of the mNDWI and 17% fewer errors than those of the HIS method. The UWEA performed best because it was good at identifying small water bodies and suppressing reflective surfaces. The UWEA is effective in urban water monitoring and its thresholds are also robust in various situations. The resulting highly accurate water map could support water-related analyses. This method is also useful for scientists, managers, and planners in water resource management, urban hydrological applications, and sustainable urban development.
Publisher: Springer Science and Business Media LLC
Date: 25-04-2016
DOI: 10.1038/NCLIMATE3004
Publisher: Elsevier BV
Date: 07-2018
Publisher: Copernicus GmbH
Date: 02-05-2022
Abstract: Abstract. Multiyear drought has been proved to cause non-stationary rainfall-runoff relationship. But whether this change can occur in catchments that have also experienced vegetation change and whether it invalidates the most widely used methods (the paired-catchment method (PCM), the time-trend method (TTM), and the sensitivity-based method (SBM)) for estimating impacts of vegetation change on runoff is still unknown and rarely discussed. In the Red Hill paired experimental catchments in Australia, which has experienced a 10-year drought (2000–2009) and afforestation, estimated inconsistent afforestation impacts were 32.8 %, 93.5 %, and 76.1 % of total runoff changes by the PCM, TTM and SBM, respectively. In addition to afforestation, multiyear drought has also led to the non-stationary rainfall-runoff relationship of the paired catchments. For the TTM and SBM, traditional application did not further differentiate different drivers of non-stationary rainfall-runoff relationship, which led to significant overestimation of afforestation effects. A new framework was proposed to separate the effects of three factors on runoff changes including vegetation change, climate variability and multiyear drought caused non-stationarity. Based on the new framework, impacts of afforestation on runoff were 38.8 % by the TTM and 21.4 % by the SBM, agreeing well with that by the PCM (32.8 %). Using paired-catchment observations, this study proved multiyear drought can induce non-stationary rainfall-runoff relationship and proposed a new framework to better separate the impact of vegetation changes on runoff under climate-induced non-stationary condition. More importantly, paired-catchment method is proven to be still the most reliable method even the control catchment experienced climate-induced shift in rainfall-runoff relationship.
Publisher: American Meteorological Society
Date: 20-03-2018
Abstract: Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any in idual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land-use types.
Publisher: American Geophysical Union (AGU)
Date: 09-2011
DOI: 10.1029/2011WR010636
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 2021
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-10055
Abstract: & & Yangtze River and Yellow River are the two most important rivers in China. Long-term observation shows that runoff ratio (i.e., runoff recipitation, denoted as RR) in the headwater of both Yangtze River (HYZR) and Yellow River (HYER) has experienced significant decrease and then increase trend (referred as V-change) during the period 1980-2015. Over the whole period, RR of the HYER shows significant decreasing trend (-0.02/10a, p & 0.05), while it is not significant for the HYZR. Changes in RR in both HYZR and HYER pose great challenge on runoff predication and water management in the downstream. However, driven mechanisms underlying the V-change of RR are still unclear. Here, based on ground-based and remote sensing datasets, both terrestrial and atmospheric water budgets are investigated to understand the evolution of RR in the headwater regions of Yangtze River and Yellow River. Terrestrial water budgets are for evaporation estimation and water cycle analysis. Atmospheric water budgets are used to calibrate the estimated evaporation. Results show that TWS-REC agrees well with observed total water storage (TWS-GRACE) in both HYZR (r = 0.94, NSE = 0.83) and HYER (r = 0.93, NSE = 0.83) over the period of 2003-2012. Estimated evaporation from both terrestrial water balance and atmospheric water balance method also agree well with each other in the HYZR (r = 0.89, NSE = 0.80) and in the HYER (r = 0.88, NSE = 0.79) over the period of 2000-2015. It suggests that reconstructed TWS and estimated evaporation are reliable for analyzing long-term water cycle in the study areas. Both the ratio of the estimated evaporation to precipitation (ER) in two basin increase first and then decreased during the study period. The correlation coefficients between ER and RR in the HYZR and HYER are -0.63 and -0.79, respectively, presenting that RR variability could be mainly caused by the evolution ER. Meanwhile it also indicates the nonignored role of total water storage (TWS) changes in RR variability in the two basin. TWS-REC in both regions have experienced significant increasing with rate of 26 mm/10a (HYZR, p & 0.05) and 17mm/10a (HYER, p & 0.05), later of which is the main reason of downward trend of RR in HYER. Further analysis indicates that changes in ER are resulted from comprehensive effects of precipitation variability (26.4mm/10a, p & 0.05 in HYZR and 3.5mm/10a p & 0.1 in HYER) and of dramatic climate warming (0.6& #8451 /10a, p & 0.05 in HYZR and 0.5& #8451 /10a, p & 0.05 in HYER). TWS changes in both basin are positively related with dramatic temperature rising and significant vegetation greening. It means that annual fluctuation of precipitation-runoff process (i.e., V-change RR) has affected negatively by climate warming and vegetation greening in the HYZR and HYER. These findings can advance our understanding of the runoff ratio evolution and water cycle in the headwater of Yangtze River and Yellow River and it is also important for ecological conservation strategy and downstream water resources management.& &
Publisher: Copernicus GmbH
Date: 18-02-2020
Publisher: Wiley
Date: 07-2021
DOI: 10.1002/HYP.14289
Abstract: It is widely recognized that multi‐year drought can induce changes in catchment hydrological behaviours. However, at present, our understanding about multi‐year drought‐induced changes in catchment hydrological behaviours and its driving factors at the process level is still very limited. This study proposed a new approach using a data assimilation technique with a process‐based hydrological model to detect multi‐year drought‐induced changes in catchment hydrological behaviours and to identify driving factors for the changes in an unimpaired Australian catchment (Wee Jasper) which experienced prolonged drought from 1997 to 2009. Modelling experiments demonstrated that the multi‐year drought caused a significant change in the catchment rainfall‐runoff relationship, indicated by significant step changes in the estimated time‐variant hydrological parameters SC (indicating catchment active water storage capacity) and C (reflecting catchment evapotranspiration dynamics), whose average values increased 23.4% and 10.2%, respectively, due to drought. The change in the rainfall‐runoff relationship identified by the data assimilation method is consistent with that arrived at by a statistical examination. The proposed method provides insights about the drivers of the changes in the rainfall‐runoff relationship at the processes level. Increasing catchment water storage capacity and decreasing ratio of rainfall to soil moisture for supplying actual evapotranspiration during drought are the main driving factors for the catchment behaviours change in the Wee Jasper catchment in terms of model structure. And they are related to decrease in catchment groundwater level and deep soil moisture. The proposed new method can be used as an effective technique for detecting both the change of hydrological behaviours induced by prolonged drought and its driving factors at the process level.
Publisher: Copernicus GmbH
Date: 08-09-2022
Abstract: Abstract. Soil moisture storage capacity (SMSC) links the atmosphere and terrestrial ecosystems, which is required as spatial parameters for geoscientific models. However, there are currently no available common datasets of the SMSC on a global scale, especially for hydrological models since conventional evapotranspiration-derived estimates cannot represent the extra storage capacity for the lateral flow and runoff generation. Here, we produce a dataset of the SMSC parameter for global hydrological models. Joint parameter calibration of three commonly used monthly water balance models provides the labels for a deep residual network. The global SMSC is constructed based on the deep residual network at 0.5° resolution by integrating 15 types of meteorological forcings, underlying surface properties, and runoff data. SMSC products are validated with the spatial distribution against root zone depth datasets and validated in the simulation efficiency on global grids and typical catchments from different climatic regions. We provide the global SMSC parameter dataset as a benchmark for geoscientific modelling by users.
Publisher: Copernicus GmbH
Date: 04-02-2019
DOI: 10.5194/HESS-2019-6
Abstract: Abstract. Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce the performance degradation. Many existing literatures model the time-varying parameters as functions of physically-based covariates however, a major challenge remains finding effective information to control the large uncertainties that are linked to the additional parameters within the functions. This paper formulated the time-varying parameters for a lumped hydrological model as explicit functions of temporal covariates and used a hierarchical Bayesian (HB) framework to incorporate the spatial coherence of adjacent catchments to improve the robustness of the projection performance. Four modeling scenarios with different spatial coherence schemes, and one scenario with a stationary scheme for model parameters, were used to explore the transferability of hydrological models under contrasting climatic conditions. Three spatially adjacent catchments in southeast Australia were selected as case studies to examine validity of the proposed method. Results showed that (1) the time-varying function improved the model performance but also lified the projection uncertainty compared with stationary setting of model parameters (2) the proposed HB method successfully reduced the projection uncertainty and improved the robustness of model performance and (3) model parameters calibrated over dry periods were not suitable for predicting runoff over wet periods because of a large degradation in projection performance. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.
Publisher: Wiley
Date: 05-03-2014
DOI: 10.1002/ECO.1478
Publisher: Wiley
Date: 20-12-2019
DOI: 10.1111/JFR3.12586
Publisher: Elsevier BV
Date: 09-2018
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 06-2013
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 07-2022
Publisher: Copernicus GmbH
Date: 18-02-2020
Abstract: Abstract. Understanding the propagation process of prolonged meteorological droughts (i.e., decade) helps solve the problem of increasing water scarcity around the world. Historical literature studied the propagation between different drought types (e.g., from meteorological to hydrological drought) with mainly statistical approaches, however, little attention has been paid to the causality between the meteorological drought with potential changes in the Catchment Water Storage Capacity (CWSC) where the latter plays a critical role in catchment response behavior to former. This study used the temporal variation in the estimated value of a model parameter that denotes the CWSC in its model structure to reflect the potential changes in real CWSC. The most likely Change points of the CWSC were determined based on the Bayesian Change point analysis. Also, the possible association and linkage between the shift in the CWSC and the time-lag of the catchment (i.e., time-lag between the occurrence of the drought with the Change point) with multiple catchment properties and climate characteristics have been studied. Catchments from southeastern Australia were used as a study area to verify the effectiveness of the proposed approach. Results indicated that (1) in 62.7 % of the catchments, the sustained drought causes significant shifts in the CWSC. The shift led to the opposite response in two subsets of catchments, i.e., 48.2 % of catchments had lower runoff generation rates for a given rainfall while 14.5 % of catchments had higher runoff generation rate. (2) Catchments with larger elevation and slope, lower forest coverage of Evergreen Broadleaf Forest are more likely to have increase in the CWSC during a chronic drought while smaller catchments with lower elevation, lower coverage of the Evergreen Broadleaf Forest are more likely to have a decrease in the CWSC. (3) The changed catchments were not equally susceptible to the pressure due to persistent meteorological drought. Catchments with a lower proportion of Evergreen Broadleaf Forest usually have longer time-lag and are more resilient. This study improves our understanding of possible changes in CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system.
Publisher: Copernicus GmbH
Date: 26-11-2012
DOI: 10.5194/HESS-16-4467-2012
Abstract: Abstract. Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental United States, 331 of the 428 catchments studied are seen to fall into only six dominant classes.
Publisher: American Geophysical Union (AGU)
Date: 03-2012
DOI: 10.1029/2011WR011799
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2016
Publisher: Elsevier BV
Date: 02-2022
Publisher: Springer Science and Business Media LLC
Date: 24-07-2017
DOI: 10.1038/S41467-017-00114-5
Abstract: Quantifying the responses of the coupled carbon and water cycles to current global warming and rising atmospheric CO 2 concentration is crucial for predicting and adapting to climate changes. Here we show that terrestrial carbon uptake (i.e. gross primary production) increased significantly from 1982 to 2011 using a combination of ground-based and remotely sensed land and atmospheric observations. Importantly, we find that the terrestrial carbon uptake increase is not accompanied by a proportional increase in water use (i.e. evapotranspiration) but is largely (about 90%) driven by increased carbon uptake per unit of water use, i.e. water use efficiency. The increased water use efficiency is positively related to rising CO 2 concentration and increased canopy leaf area index, and negatively influenced by increased vapour pressure deficits. Our findings suggest that rising atmospheric CO 2 concentration has caused a shift in terrestrial water economics of carbon uptake.
Publisher: Elsevier BV
Date: 10-2021
Publisher: Wiley
Date: 23-12-2015
DOI: 10.1111/GEB.12411
Publisher: Copernicus GmbH
Date: 20-01-2021
DOI: 10.5194/HESS-2021-5
Abstract: Abstract. The most widely used approaches for estimating impacts of vegetation changes on runoff are the paired-catchment method, the time-trend analysis method, and the sensitivity-based method. These three methods have yielded consistent results in many paired-catchment studies, except at the Red Hill experimental site in Australia. However, reasons for the inconsistency have not yet been identified. The objective of this study was to identify the reasons for the inconsistency amongst results using observations of two paired catchments from 1990 to 2015. Results from these three methods showed that afforestation accounted for 32.8 %, 93.5 %, and 76.1 % of total runoff changes, respectively. The inconsistency in results were still apparent even the longest available observation record was used. The rainfall-runoff relationship of the control catchment has been used only in the paired-catchment method. This relationship was confirmed to become non-stationary during the pre- and post-calibration periods due to a 10-year prolonged drought, leading to the inconsistency amongst results. By eliminating drought's effects on the rainfall-runoff relationship of the control catchment, afforestation’s contribution to runoff reduction was 73.4 % using the paired-catchment method, agreeing well the other two methods. This study not only revealed the reason for the inconsistent results that had long been observed at the famous experimental site, but also proved, using experimental observations, that prolonged drought can induce non-stationary rainfall-runoff relationship in catchment. It also demonstrated that the stationarity test is vital for correct use of historical time series and effective research on ecological hydrology in the case of frequent extreme climate.
Publisher: Copernicus GmbH
Date: 26-11-2012
DOI: 10.5194/HESS-16-4483-2012
Abstract: Abstract. The paper reports on a four-pronged study of the physical controls on regional patterns of the flow duration curve (FDC). This involved a comparative analysis of long-term continuous data from nearly 200 catchments around the US, encompassing a wide range of climates, geology, and ecology. The analysis was done from three different perspectives – statistical analysis, process-based modeling, and data-based classification – followed by a synthesis, which is the focus of this paper. Streamflow data were separated into fast and slow flow responses, and associated signatures, and both total flow and its components were analyzed to generate patterns. Regional patterns emerged in all aspects of the study. The mixed gamma distribution described well the shape of the FDC regression analysis indicated that certain climate and catchment properties were first-order controls on the shape of the FDC. In order to understand the spatial patterns revealed by the statistical study, and guided by the hypothesis that the middle portion of the FDC is a function of the regime curve (RC, mean within-year variation of flow), we set out to classify these catchments, both empirically and through process-based modeling, in terms of their regime behavior. The classification analysis showed that climate seasonality and aridity, either directly (empirical classes) or through phenology (vegetation processes), were the dominant controls on the RC. Quantitative synthesis of these results determined that these classes were indeed related to the FDC through its slope and related statistical parameters. Qualitative synthesis revealed much ersity in the shapes of the FDCs even within each climate-based homogeneous class, especially in the low-flow tails, suggesting that catchment properties may have become the dominant controls. Thus, while the middle portion of the FDC contains the average response of the catchment, and is mainly controlled by climate, the tails of the FDC, notably the low-flow tails, are mainly controlled by catchment properties such as geology and soils. The regime behavior explains only part of the FDC to gain a deeper understanding of the physical controls on the FDC, these extremes must be analyzed as well. Thus, to completely separate the climate controls from the catchment controls, the roles of catchment properties such as soils, geology, topography etc. must be explored in detail.
Publisher: Copernicus GmbH
Date: 09-09-2020
DOI: 10.5194/HESS-24-4369-2020
Abstract: Abstract. Understanding the propagation of prolonged meteorological drought helps solve the problem of intensified water scarcity around the world. Most of the existing literature studied the propagation of drought from one type to another (e.g., from meteorological to hydrological drought) with statistical approaches there remains difficulty in revealing the causality between meteorological drought and potential changes in the catchment water storage capacity (CWSC). This study aims to identify the response of the CWSC to the meteorological drought by examining the changes of hydrological-model parameters after drought events. Firstly, the temporal variation of a model parameter that denotes that the CWSC is estimated to reflect the potential changes in the real CWSC. Next, the change points of the CWSC parameter were determined based on the Bayesian change point analysis. Finally, the possible association and linkage between the shift in the CWSC and the time lag of the catchment (i.e., time lag between the onset of the drought and the change point) with multiple catchment properties and climate characteristics were identified. A total of 83 catchments from southeastern Australia were selected as the study areas. Results indicated that (1) significant shifts in the CWSC can be observed in 62.7 % of the catchments, which can be ided into two subgroups with the opposite response, i.e., 48.2 % of catchments had lower runoff generation rates, while 14.5 % of catchments had higher runoff generation rate (2) the increase in the CWSC during a chronic drought can be observed in smaller catchments with lower elevation, slope and forest coverage of evergreen broadleaf forest, while the decrease in the CWSC can be observed in larger catchments with higher elevation and larger coverage of evergreen broadleaf forest (3) catchments with a lower proportion of evergreen broadleaf forest usually have a longer time lag and are more resilient. This study improves our understanding of possible changes in the CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system under climate change.
Publisher: American Geophysical Union (AGU)
Date: 08-2021
DOI: 10.1029/2020WR029529
Abstract: Catchment baseflow is jointly controlled by climate and landscape properties. Previous studies have recognized that spatial variability of mean annual baseflow coefficient (BFC = , ratio of baseflow to precipitation) is primarily controlled by aridity index and storage capacity. However, an analytical solution of BFC in terms of the dominant controlling factors has not yet been established. The objective of this study was to develop an analytical BFC curve to depict spatial variability of BFC based on the “limit” concept of the Budyko framework. The BFC curve relates the baseflow coefficient to aridity index and storage capacity without resolving complex interactions between evapotranspiration and baseflow generation. The proposed BFC curve showed that, in the arid catchments, baseflow coefficient was primarily limited by available water (precipitation, P ) and, in the humid catchments, was jointly controlled by both the available energy (potential evapotranspiration, E p ) and catchment retention capability (ratio of catchment storage capacity to P , i.e., S p / P ). Observed hydrological data from 950 catchments in Australia, the conterminous United States and the United Kingdom with erse hydro‐climatic conditions (BFC = 0.001–0.650) were collected to demonstrate the capability of the developed curve. Results showed that the BFC curve captured the spatial variability of observed BFC in the 950 study catchments ( R 2 = 0.75, RMSE = 0.058). Mean annual baseflow estimated by the BFC curve agreed well with observed baseflow ( R 2 = 0.86, RMSE = 0.19 mm). The developed analytical curve provides an analytical solution for understanding how aridity index and storage capacity control mean annual catchment baseflow, and will improve predictability of baseflow at ungauged basins.
Publisher: IWA Publishing
Date: 16-06-2020
DOI: 10.2166/NH.2020.158
Abstract: In medium/long-term reservoir operation, the hydropower output is calculated from k × q × h, where q is the power discharge, h is the water head, and k is the comprehensive hydropower coefficient. k indicates the conversion efficiency from water power to electricity, however, it is standard practice to use a constant k. We developed a novel method to derive the varying k based on observed big data. The operational frequencies of different units for time (multiple periods) and space (multiple units) were accounted based on the observed big data from each unit, and then weights were obtained. Finally, k was derived by integrating the efficiency curves (hill charts) of the different units with their weights. The Three Gorges Project, China, was selected for a case study. Results indicated that: (1) the varying k value can improve hydropower simulation accuracy, (2) simulations using 10-day intervals have a higher accuracy for hydropower calculation than daily and monthly scales, (3) the evaluation of hydropower plant benefits is sensitive to k, and there is potential for producing more hydropower. These findings are highly relevant to the operation of hydropower plants and to the evaluation of medium/long-term hydropower generation for a hydropower plant.
Publisher: Authorea, Inc.
Date: 25-05-2023
DOI: 10.22541/ESSOAR.168500285.54555879/V1
Abstract: Understanding the partitioning of runoff into baseflow and quickflow is crucial for informed decision-making in water resources management, guiding the implementation of flood mitigation strategies, and supporting the development of drought resilience measures. Methods that combine the physically-based Budyko framework with machine learning (ML) have shown promise in estimating global runoff. However, such ‘hybrid’ approaches have not been used for baseflow estimation. Here, we develop a Budyko-constrained ML approach for baseflow estimation by incorporating the Budyko-based baseflow coefficient (BFC) curve as a physical constraint. We estimate the parameters of the original Budyko curve and the newly developed BFC curve based on 13 climatic and physiographic characteristics using boosted regression trees (BRT). BRT models are trained and tested in 1226 catchments worldwide and subsequently applied to the entire global land surface at a 0.25° grid scale. The catchment-trained models exhibit strong performance during the testing phase, with R2 values of 0.96 and 0.88 for runoff and baseflow, respectively. Results reveal that, on average, 30.3% (spatial standard deviation std=26.5%) of the continental precipitation is partitioned into runoff, of which 20.6% (std=22.1%) is baseflow and 9.7% (std=10.3%) is quickflow. Among the 13 climatic and physiographic characteristics, topography and soil-related characteristics generally emerge as the most important drivers, although significant regional variability is observed. Comparisons with previous datasets suggest that global runoff partitioning is still highly uncertain and warrants further research.
Publisher: Wiley
Date: 21-11-2016
DOI: 10.1002/HYP.10704
Publisher: Copernicus GmbH
Date: 21-12-2017
Abstract: Abstract. Estimating baseflow at a large spatial scale is critical for water balance budget, water resources management, and environmental evaluation. To predict baseflow index (BFI, the ratio of baseflow to total streamflow), this study introduces a multilevel regression approach, which is compared to two traditional approaches: hydrological modelling (SIMHYD, a simplified version of the HYDROLOG model, and Xinanjiang models) and classic linear regression. All of the three approaches were evaluated against ensemble average estimates from four well-parameterised baseflow separation methods (Lyne–Hollick, UKIH (United Kingdom Institute of Hydrology), Chapman–Maxwell and Eckhardt) at 596 widely spread Australian catchments in 1975–2012. The two hydrological models obtain BFI from three modes: calibration and two regionalisation schemes (spatial proximity and integrated similarity). The classic linear regression estimates BFI using linear regressions established between catchment attributes and the ensemble average estimates in four climate zones (arid, tropics, equiseasonal and winter rainfall). The multilevel regression approach not only groups the catchments into the four climate zones, but also considers variances both within all catchments and catchments in each climate zone. The two calibrated and regionalised hydrological models perform similarly poorly in predicting BFI with a Nash–Sutcliffe Efficiency (NSE) of −8.44 ~ −2.58 and an absolute percenrate bias (Bias) of 81 146 the classic linear regression is intermediate with the NSE of 0.57 and bias of 25 the multilevel regression approach is best with the NSE of 0.75 and bias of 19. Our study indicates the multilevel regression approach should be used for predicting large-scale baseflow index such as Australian continent where sufficient catchment predictors are available.
Publisher: Wiley
Date: 03-2021
DOI: 10.1002/HYP.14069
Publisher: Wiley
Date: 22-09-2014
DOI: 10.1002/HYP.10307
Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 10-2019
Publisher: Wiley
Date: 06-04-2018
DOI: 10.1002/ECO.1974
Publisher: Elsevier BV
Date: 07-2019
Publisher: American Chemical Society (ACS)
Date: 03-11-2020
Publisher: Wiley
Date: 23-03-2016
DOI: 10.1111/GCB.13180
Abstract: Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2 . The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt , the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 , and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has lified the effect of CO2 in increasing WUE by more than 0.005 gC m(-2) mm(-1) yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.
Publisher: Elsevier BV
Date: 07-2019
Publisher: American Geophysical Union (AGU)
Date: 30-08-2022
DOI: 10.1029/2021WR030629
Abstract: Partitioning evapotranspiration (ET) into evaporation ( E ) and transpiration ( T ) is essential for understanding the global hydrological cycle and improving water resource management. However, ecosystem‐level ET partitioning remains challenging. Here we proposed a novel ET partitioning method that uses the unified stomatal conductance model to estimate T :ET by calculating the ratio of the ecosystem water use efficiency (WUE eco ) to leaf WUE (WUE leaf ) using half‐hourly flux data. The WUE leaf values estimated by the unified stomatal conductance model agree with an independently measured ratio of hourly photosynthetic rate to T rate ( R 2 = 0.69). The sensitivity of T :ET to the key parameter g 1 varied among different plant functional types (PFTs), but the T :ET variations for each PFT were all controlled within 20% when g 1 altered within its 95% confidence interval. The mean annual T :ET was highest for evergreen broadleaf forests (0.63), followed by deciduous broad forests (0.62), grasslands (0.52), evergreen needleleaf forests (0.43) and woody savannas (0.40). C 3 croplands had higher T :ET (0.65) than C 4 croplands (0.48). Seasonal variations in T :ET varied across PFTs and the leaf area index explained about 50% of the variation in seasonal T :ET. Our method is not only consistent with other three EC‐based methods: Z16, N18, and L19 ( R = 0.92, 0.94, and 0.68), but also shows high correlations to sap flow‐based T ( R = 0.70) at three different forest sites. The method developed in this study provides a feasible and universal approach for ET partitioning of global EC sites, improving the understanding of ecosystem T characteristics across climates and PFTs.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 07-2021
Publisher: Wiley
Date: 08-01-2015
DOI: 10.1111/GCB.12795
Abstract: The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 11-2021
Publisher: Informa UK Limited
Date: 04-11-2010
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 09-2018
Publisher: Wiley
Date: 29-11-2021
Abstract: The underlying mechanisms by which soil moisture might affect precipitation are essential for weather prediction and climate change projection. Process‐based models that are capable of providing physical explanation are often tripped in concerns about model uncertainty in structure, data, and parameters, etc. The information theory has provided a new paradigm to explain the feedback system. This study focused on to identify the soil moisture–precipitation feedback based on direct long‐term observations using an information‐based method, Temporal Information Partitioning Networks (TIPNets). Normalized transfer entropy was proposed to describe feedback strength. In comparison with Granger causality and correlation, the TIPNets method was independent of parameterizations and spatiotemporal resolution effects, also elucidate information‐theoretic insights. The results in the case study of Illinois, indicated that soil moisture–precipitation feedback existed and was significant during May to mid‐July. The bidirectional dominant lags of 3–10 and 6–17 days were both shorter in summer. Areas with strong feedback were located in south‐central Illinois. Besides, the wooded grassland coverage was the most related land use type to feedback strength, which could be one kind of the positive feedback mechanism in Illinois.
Publisher: Wiley
Date: 28-02-2021
DOI: 10.1002/JOC.7055
Abstract: General circulation models (GCMs) are indispensable for climate change adaptive study over the Tibetan Plateau (TP), which is the potential trigger and lifier in global climate fluctuations. With the release of Coupled Model Intercomparison Project Phase 6 (CMIP6), 24 GCMs from CMIP5 and CMIP6 were comparatively evaluated for precipitation and air temperature simulations based on the China Meteorological Forcing Dataset (CMFD). Rank score results showed that CMIP6 models generally performed better than CMIP5 for precipitation and surface air temperature over the TP. According to multimodel ensembles (MMEs) of the optimal GCMs for each climate variable, the overestimation of precipitation was both present in CMIP5 and CMIP6, but the results of CMIP6 MMEs were relatively lower in the mid‐west and northern edge of the TP. Furthermore, CMIP6 offered a better performance of precipitation in summer and autumn. For temperature, CMIP6 MMEs were able to reduce the relatively large cold bias that appeared in CMIP5 MMEs in northwest areas to about 1°C and had a smaller bias in spring and winter. Moreover, the investigation into the simulation effects of precipitation at different elevation zones demonstrated that the improved ability of CMIP6 MMEs to reduce bias was mainly concentrated in the elevation zones of 2,000–3,000 m and over 5,000 m, where the precipitation bias was more than 200%. Additionally, CMIP6 MMEs of temperature were able to reduce the bias to less than 2°C in each elevation zone, with the minimum bias of −0.22°C distributed in the region with altitudes from 3,000 to 4,000 m, while the biases of CMIP5 MMEs in the region of 4,000–5,000 m and over 5,000 m were smaller than those of CMIP6 MMEs. Findings obtained in this study could provide a scientific reference for related climate change research over the TP. GCMs of CMIP6 perform better than those of CMIP5 for precipitation and temperature over the TP. Multimodel ensembles (MMEs) of CMIP6 effectively reduce the overestimation of precipitation from CMIP5 MMEs by 40 mm at the annual scale. Improved ability of CMIP6 MMEs shows a significant elevation dependency, especially in elevation zones of 2,000–3,000 m and over 5,000 m for precipitation.
Publisher: Elsevier BV
Date: 03-2023
Publisher: MDPI AG
Date: 12-10-2022
DOI: 10.3390/RS14205097
Abstract: Climate change is a significant force influencing catchment hydrological processes, such as baseflow, i.e., the contribution of delayed pathways to streamflow in drought periods and is associated with catchment drought propagation. The Weihe River Basin is a typical arid and semi-arid catchment on the Loess Plateau in northwest China. Baseflow plays a fundamental role in the provision of water and environmental functions at the catchment scale. However, the baseflow variability in the projected climate change is not well understood. In this study, forcing meteorological data were derived from two climate scenarios (RCP4.5 and RCP8.5) of three representative general circulation models (CSIRO-Mk3-6-0, MIROC5, and FGOALSg2) in CMIP5 and then were used as inputs in the Soil and Water Assessment Tool (SWAT) hydrological model to simulate future streamflow. Finally, a well-revised baseflow separation method was implemented to estimate the baseflow to investigate long-term (historical (1960–2012) and future (2010–2054) periods) baseflow variability patterns. We found (1) that baseflow showed a decreasing trend in some simulations of future climatic conditions but not in all scenarios (p 0.05), (2) that the contribution of baseflow to streamflow (i.e., baseflow index) amounted to approximately 45%, with a slightly increasing trend (p ≤ 0.001), and (3) an increased frequency of severe hydrological drought events in the future (2041–2053) due to baseflows much lower than current annual averages. This study benefits the scientific management of water resources in regional development and provides references for the semi-arid or water-limited catchments.
Publisher: The Royal Society
Date: 08-10-2018
Abstract: Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land–atmosphere CO 2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4–0.7 PgC yr −1 (inversions) and by 1.0 PgC yr −1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.
Publisher: Elsevier BV
Date: 08-2022
Publisher: American Geophysical Union (AGU)
Date: 20-08-2021
DOI: 10.1029/2020JD033756
Abstract: The dependence of inter‐annual ecosystem evapotranspiration (ET) partitioning on vegetation dynamics is crucial for understanding the long term coupling relationship between the water and carbon cycles. The objective of this study was to determine the spatial variation of ET partitioning ( T /ET) and the inter‐annual dependencies of T /ET on vegetation gross primary productivity (GPP). The investigation was conducted at the global scale based on seven global datasets and at the point scale at 37 flux sites. The spatial variations of T /ET were ided into three phases, that is, the rapidly increasing phase (P1), slowly increasing phase (P2), and decreasing phase (P3), which were located in arid and cold regions, temperate regions, and tropical rainforest regions, respectively. The three‐phase spatial variations were primarily driven by the different spatial variations of the two water use pathways (i.e., transpiration, T and evaporation, E ) in ecosystems with different productivity levels. In P1 and P2 ecosystems, the inter‐annual dependencies of T /ET on GPP were mostly positive, and in P3 ecosystems, it was mostly negative. This revealed a significantly decreased dependence as GPP increased, which was attributed to the different dependencies of T and E on GPP. Based on the effects of GPP on ET under climate variations (represented by precipitation, P ), ET had the smallest inter‐annual variations in most of global vegetated grid cells due to the joint regulation of T and E by GPP and P . This study highlights the significant role of vegetation productivity in regulating inter‐annual ET partitioning, and improves understandings on the coupled water‐carbon cycles.
Publisher: Elsevier BV
Date: 06-2019
Publisher: Copernicus GmbH
Date: 26-11-2012
DOI: 10.5194/HESS-16-4435-2012
Abstract: Abstract. The flow duration curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of streamflow. In this sense it represents a compact signature of temporal runoff variability that can also be used to diagnose catchment rainfall-runoff responses, including similarity and differences between catchments. This paper is aimed at extracting regional patterns of the FDCs from observed daily flow data and elucidating the physical controls underlying these patterns, as a way to aid towards their regionalization and predictions in ungauged basins. The FDCs of total runoff (TFDC) using multi-decadal streamflow records for 197 catchments across the continental United States are separated into the FDCs of two runoff components, i.e., fast flow (FFDC) and slow flow (SFDC). In order to compactly display these regional patterns, the 3-parameter mixed gamma distribution is employed to characterize the shapes of the normalized FDCs (i.e., TFDC, FFDC and SFDC) over the entire data record. This is repeated to also characterize the between-year variability of "annual" FDCs for 8 representative catchments chosen across a climate gradient. Results show that the mixed gamma distribution can adequately capture the shapes of the FDCs and their variation between catchments and also between years. Comparison between the between-catchment and between-year variability of the FDCs revealed significant space-time symmetry. Possible relationships between the parameters of the fitted mixed gamma distribution and catchment climatic and physiographic characteristics are explored in order to decipher and point to the underlying physical controls. The baseflow index (a surrogate for the collective impact of geology, soils, topography and vegetation, as well as climate) is found to be the dominant control on the shapes of the normalized TFDC and SFDC, whereas the product of maximum daily precipitation and the fraction of non-rainy days was found to control the shape of the FFDC. These relationships, arising from the separation of total runoff into its two components, provide a potential physical basis for regionalization of FDCs, as well as providing a conceptual framework for developing deeper process-based understanding of the FDCs.
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 12-2021
Publisher: American Geophysical Union (AGU)
Date: 29-06-2022
DOI: 10.1029/2021MS002653
Abstract: Irrigation is the dominant section of human water use, exerting essential impacts on hydrological processes and water resources. To more realistically simulate irrigation processes in water‐rich regions, an irrigation scheme is incorporated into a land surface‐hydrological model. It calculates the irrigation water requirement according to meteorological conditions, cropping area and growing stage, and root‐zone soil moisture, and determines the irrigation water withdrawal based on the available water resources as well as describing water extraction and irrigation processes in the model. The coupled model is applied to the Yangtze River Basin (YRB) in China, and verified using the observed daily river discharge from 1987 to 1990, evapotranspiration and irrigation amounts from 1999 to 2003. The results first show that the model can well reproduce hydrological processes within the basin, and the simulated irrigation largely agrees with the observation, in terms of annual irrigation and its spatial pattern. Second, inclusion of irrigation processes allows the model to better estimate evapotranspiration, with relative biases decreased from about −10% to −3%. It is also found that in comparison to arid/semi‐arid areas, although presenting a less effect on river discharge and groundwater, the irrigation in the YRB significantly alters hydrological processes through water redistribution. The irrigation‐induced evapotranspiration increment and runoff decrease indicate a shift in the surface water and energy balance, implying a potential effect on the atmosphere. Therefore, representing irrigation processes properly is important, particularly for understanding the coupling effect of the nature‐human system and improving the hydrological prediction accuracy.
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 03-2022
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier BV
Date: 05-2023
Publisher: MDPI AG
Date: 08-12-2022
DOI: 10.3390/W14244007
Abstract: Stream networks are the transportation channels of pollutants that can significantly influence water environment risk (WER). However, the influences of stream network structure and connectivity (SC) on WER at the national scale and its regional variability have been rarely investigated in China. In this study, the WER was assessed from the grey water footprint of nitrogen and phosphorus in 214 catchments in China. The relationship between WER and SC and its regional variability were analyzed using correlation and grey relational analysis. Results showed that the water environment risk index (RI) in some catchments located in the Hai and Liao River Basins was the highest in China (RI 0.8). On national scale, longitudinal connectivity (Cl) and cyclical connectivity (Cc) had the strongest influences on WER with grey relational degree index (GRAI) of 0.68 and 0.67, respectively. The average slope (Sr) was the most important in humid zones, whereas Cl and water surface ratio (Rw) had a stronger influence in arid zones. In zones with intensive human activities, Cc, river density (Rd), and the node connection ratio (Rnc) mostly affected WER. The main influenced factors varied significantly among nationwide and different zones, which indicated that climate and human activities played an important role in the spatial variation of the relationship between WER and SC. This study highlights the important role of SC on WER and that the relationship between WER and SC varies with climate and human activities.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-8896
Abstract: Partitioning runoff accurately into baseflow and quickflow is crucial for our understanding of the water cycle and for the management of droughts and floods. However, global datasets of long-term mean runoff partitioning are rare, even more so datasets relying on physically-based methods. Here, we present a new global 0.25& #176 dataset of runoff, baseflow and quickflow using a hybrid approach of Budyko-based methods and machine learning (ML). The parameters in the Budyko curve and Budyko-based baseflow curve (BFC curve) are estimated with ML (boosted regression trees, BRT) as a function of catchment characteristics. The BRT models are trained and tested in 1226 catchments worldwide, and then applied globally at grid scale. The catchment-trained models show good performance during the testing phase with R2 equal to 0.96 and 0.87 for runoff and baseflow, respectively. The dataset developed in this study shows that 30.3& #177 .5% (mean & #177 standard deviation) of the precipitation is partitioned into runoff of which 20.6& #177 .1% is baseflow and 9.7& #177 .3% is quickflow. The global long-term mean baseflow in this study (151& #177 mm yr& #8211 ) is lower than that from the Global Streamflow Characteristics Dataset (GSCD, 241& #177 mm yr& #8211 ) and higher than that from ERA5-Land (79& #177 mm yr& #8211 ). This study provides a unique, physically and observationally constrained global dataset of the long-term runoff partitioning. The large differences among different datasets suggest that global runoff partitioning is highly uncertain and requires further investigation.
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 2021
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-10521
Abstract: & & The growing water extraction due to the economic development and population growth has caused over-utilization of water resources worldwide, especially in semiarid regions. In these regions, the sustainable water availability has often been sought and maintained by managing land, but it is highly uncertain in future climate conditions. Besides, prediction of water availability in such region is still challenging due to non-stationary rainfall-runoff relationship caused by intensive human interferences and poor ET simulation by hydrological models. Therefore, accurate estimation and maintaining of sustainable water availability under future climate conditions are important for the ecological conservation and social development of semiarid regions. In this study, impacts of land use and climate changes on vegetation dynamics (canopy LAI) and water cycle (ET and runoff) of the Xiong& #8217 an New Area (XNA) are investigated using an ecohydrological model (i.e., WAVES). The XNA, a typical semiarid region located in North China, is expected to need more water in order to increase the vegetation coverage from 10% to 40% by 2035. The WAVES model is chosen because it can simulate ET well by coupling water-carbon-heat. Here, water use (ET) and water yield (runoff) of three typical ecosystems (i.e., cropland, grassland and forestland) in different future periods (i.e., near-future: 2030s (2021-2040), mid-future: 2050s (2041-2060) and far-future: 2080s (2061-2100)) are assessed using projected future climate forcing from 18 GCMs under three RCPs (i.e., RCP2.6, RCP4.5 and RCP8.5). Projected precipitation (& em& P& /em& ) and air temperature (& em& T& sub& a& /sub& & /em& ) indicate the XNA will become warmer and wetter in the future. The WAVES model is capable to simulate the ecohydrological process well in the XNA with NSE & #8805 0.62, R& sup& & /sup& & #8805 0.65, RMSE & #8804 0.86 in LAI and NSE & #8805 0.61, R& sup& & /sup& & #8805 0.66, RMSE & #8804 0.71 mm& #183 d& sup& -1& /sup& in ET. During the baseline period of 1982-2012, modeling results show that the forested land evaporates more water (32 mm a& sup& & #8722 & /sup& & sup& & /sup& ) than cropland while grassland use almost same water as cropland. Under future climate conditions, both cropland and the grassland will have more water use and water yield due to increased precipitation and suppressed vegetation growth due to warming. Forested land will use more than 20% water (76 mm a& sup& & #8722 & /sup& & sup& & /sup& ) compared with that during the baseline period in the XNA, but it will generate more than 10% (12 mm a& sup& & #8722 & /sup& & sup& & /sup& ) water yield in the 2050s and 2080s under RCP4.5 and RCP8.5 due to greater increases in precipitation. For the purpose of land management, it is recommended to plant crop or grass in the near-future and to plant forest in the mid-future and far-future to expand vegetation coverage in the XNA. This study highlights that both climate change and land management are of critical importance for sustaining water yield in semiarid regions with over-utilized water resources.& &
Location: United States of America
No related grants have been discovered for Lei Cheng.