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• Biome-BGC model was improved by modifying the ET and canopy multilayers modules. • The increasing trends of GPP, ET and WUE were more pronounced during 1999–2018. • Increasing NDVI mitigated the negative effect of precipitation. Extreme climate occurred frequently in subtropical region, which seriously affects carbon and water fluxes such as evapotranspiration (ET) and gross primary productivity (GPP) of terrestrial ecosystems. The process-based biome biogeochemical cycles (Biome-BGC) model is widely used for simulating carbon and water fluxes of forest ecosystems. However, the lack of the interaction information of climate, vegetation and soil, such as the hysteresis effect, canopy stratification on photosynthesis, impedes better simulations of the ecohydrological processes. Here, we tended to improve the simulation accuracy of Biome-BGC model at a subtropical forest on the Xin'an River in Southeastern China by reconstructing the precipitation series, modifying the ET and canopy multilayers modules, and optimizing the parameters. The spatiotemporal patterns of GPP, ET, water use efficiency (WUE) and their response to environmental factors across the Xin'an River Basin from 1982 to 2018 were further explored. The results showed that the improved model performed well, with the determination coefficient, root means square error and mean absolute error being 0.730, 1.522 gC/m2/d and 1.218 gC/m2/d for GPP, 0.857, 1.082 mm/d and 0.838 mm/d for ET, respectively. Basin-averaged GPP, ET and WUE increased during 1982–2018 and these increasing trends were more pronounced during 1999–2018. Significant positive trends of WUE occurred in the northeast corner. The increasing air temperature and precipitation respectively dominated the increase in GPP and ET, the increasing CO 2 concentration and NDVI mitigated the negative effect of extreme precipitation on WUE. Given that human activities such as afforestation have effectively reduced the extent of damage to forest ecosystems from extreme precipitation, we highlight an urgent need to formulate adaptation strategies aimed at reducing the risk of extreme climate in humid regions. [ABSTRACT FROM AUTHOR]

As one of the most influential oceanic and atmospheric oscillations in the Earth system, El Niño‐Southern Oscillation (ENSO) has modulated numerous geophysical processes. This is particularly true for the Yangtze River Basin (YRB), which is vulnerable to Asian Monsoon and faces serious hydrological hazards. In this study, the co‐variability between lag–lead precipitation and sea surface temperature anomalies was evaluated utilizing singular value decomposition (SVD) method. Moreover, certain teleconnections between ENSO and streamflow were identified by wavelet methods. In addition, the contribution of related atmospheric variables was revealed by composite analysis. Results indicate that there are strong associations in lag–lead seasons between the wet condition (dry condition) and September–November (December–February) mature ENSO phase. Significant common power and coherence signals between the ENSO indices and the streamflow occur in the 4–8, 8–16 and 16–32 seasonal scales. Meanwhile, the activity cycle of the ENSO indices ahead of streamflow increases from the mid‐lower reaches to the source region. In addition, the Western Pacific Subtropical High is strengthened during the mature ENSO phase. Anomalous sinking motions and divergent water vapour flux occupy the YRB, reducing the precipitation and leading to the dry condition in the source region until the following March–May. On the other hand, ascending movements and abundant water vapour flux coming from northern Pacific, equatorial western Pacific and the Bay of Bengal result in the wet condition in the mid‐lower reaches. [ABSTRACT FROM AUTHOR]

Quantifying precipitation (P) partition into evapotranspiration (E) and runoff (Q) is of great importance for global and regional water availability assessment. Budyko framework serves as a powerful tool to make simple and transparent estimation for the partition, using a single parameter, to characterize the shape of the Budyko curve for a “specific basin”, where the single parameter reflects the overall effect by not only climatic seasonality, catchment characteristics (e.g., soil, topography and vegetation) but also agricultural activities (e.g., cultivation and irrigation). At the regional scale, these influencing factors are interconnected, and the interactions between them can also affect the single parameter of Budyko-type equations’ estimating. Here we employ the multivariate adaptive regression splines (MARS) model to estimate the Budyko curve shape parameter ( n in the Choudhury’s equation, one form of the Budyko framework) of the selected 96 catchments across China using a data set of long-term averages for climatic seasonality, catchment characteristics and agricultural activities. Results show average storm depth (ASD), vegetation coverage (M), and seasonality index of precipitation (SI) are three statistically significant factors affecting the Budyko parameter. More importantly, four pairs of interactions are recognized by the MARS model as: The interaction between CA (percentage of cultivated land area to total catchment area) and ASD shows that the cultivation can weaken the reducing effect of high ASD (>46.78 mm) on the Budyko parameter estimating. Drought (represented by the value of Palmer drought severity index < -0.74) and uneven distribution of annual rainfall (represented by the value of coefficient of variation of precipitation > 0.23) tend to enhance the Budyko parameter reduction by large SI (>0.797). Low vegetation coverage (34.56%) is likely to intensify the rising effect on evapotranspiration ratio by IA (percentage of irrigation area to total catchment area). The Budyko n values estimated by the MARS model reproduce the calculated ones by the observation well for the selected 96 catchments (with R = 0.817, MAE = 4.09). Compared to the multiple stepwise regression model estimating the parameter n taken the influencing factors as independent inputs, the MARS model enhances the capability of the Budyko framework for assessing water availability at regional scale using readily available data. [ABSTRACT FROM AUTHOR]

Abstract: As the most excellent indicator for hydrological cycle and a central link to water-balance calculations, the reference evapotranspiration (ET0) is of increasing importance in assessing the potential impacts of climate change on hydrology and water resources systems since the climate change has been becoming more pronounced. In this study, we conduct an investigation on the spatial and temporal changes in ET0 of the Haihe River Basin in present and future stages. The ET0 in the past five decades (1961–2010) are calculated by the Penman–Monteith method with historical climatic variables in 40 sites while the ET0 estimation for the future period of 2011–2099 is based on the related climatic variables projected by Coupled General Circulation Model (CGCM) multimodel ensemble projections in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) using the Bayesian Model Average (BMA) approach. Results can be summarized for the present and future as follows. (1) No coherent spatial patterns in ET0 changes are seen in the whole basin. Half of the stations distributed mainly in the eastern and southeastern plain regions present significant negative trends, while only 3 stations in the western mountainous and plateau basin show significant positive trends. Radiation is mainly responsible for the ET0 change in the southern and eastern basin, whereas relative humidity and wind speed are the leading factors in the eastern coastal and north parts. (2) BMA ensemble method is competent to produce lower bias in comparison with other common methods in this basin. Future spatiotemporal ET0 pattern analysis by means of the BMA method based on the ensembles of four CGCMs suggested that although the spatial patterns under three scenarios are different in the forthcoming two decades, generally increasing trends can be found in the 21st century, which is mainly attributed to the significant increasing temperature. In addition, the implication of future ET0 change in agriculture and local water resources is discussed as an extension of this work. The results can provide beneficial reference and comprehensive information to understand the impact of climate change on the future water balance and improve the regional strategy for water resource and eco-environment management in the Haihe River Basin. [Copyright &y& Elsevier]

The statistical characteristics of precipitation on the daily resolution play an important role not only in the risk assessment of floods and droughts but also in the land use management. In this study, spatial and temporal patterns of the precipitation concentration in the Yangtze River Basin are investigated by using three indices, i.e. precipitation concentration index (CI), precipitation concentration degree (PCD) and precipitation concentration period (PCP). Based on meteorological data of 147 stations for the period of 1960-2008, non-parametric trend analysis and wavelet transformation analysis are employed to detect the temporal variation of these indices. Spatial variability of precipitation concentration indices and their trends are analysed and demonstrated with the help of GIS tools. The results indicate the following: (i) The high precipitation CI values mainly distribute in the middle region of the Yangtze River Basin, whereas the lower and lowest CI values are found in the lower and upper regions, respectively. A roughly east-west gradient for PCD value and PCP value varies from 0.26 to 0.77 and from 123 to 197, respectively. (ii) The analysis results of precipitation CI trends for different periods (i.e. recent 40, 30 and 20 years) show that the middle region of the Yangtze River Basin experienced a transition from decreasing precipitation CI to increasing precipitation CI during the last two decades, although the decreasing long-term trends in the precipitation CI are not significant in most areas during the period of 1960-2008. (iii) The upper basin, middle basin and lower basin are, respectively, dominated by the significant decreasing, increasing and no significant trends in PCD. A dominance of insignificant PCP trends is observed in the entire basin during 1960-2008 despite that a few areas in the upper region are characterized by significant decreasing trends. (iv) Interdecadal oscillations can be found for three precipitation indices, but with no constant periodicity. Furthermore, good positive correlations have been detected between precipitation CI and PCD, whereas insignificant correlation coefficients of PCP with precipitation are common in the basin. The results can provide beneficial reference to water resource and eco-environment and mitigation to flood or drought hazards in the Yangtze River Basin for policymakers and stakeholders. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann-Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959-1983 and 1984-2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

The concept of elasticity has been widely employed to quantify the hydrological response to changes in climate and catchments properties. To separate the effect of different climatic variables on runoff, the potential evaporation (E 0 ) elasticity of runoff needs to be presented in term of observed climate variables. To fully reflect the effects of maximum and minimum temperatures and reduce the influence of the correlations of radiation with sunshine duration and relative humidity on the assessment results, we decompose the E 0 elasticity into five evaporation-related elasticities (i.e., sunshine duration, maximum and minimum temperature, wind speed and relative humidity) via the first-order differentiation of the FAO 56 Penman equation. As the catchment runoff is frequently affected by the land use/cover change, we also consider changes in catchment characteristics and derive a catchment alteration elasticity based on the Budyko framework. An application was carried out in 30 catchments with widespread climatic types in China. For the two periods (i.e., the baseline period and the changed period) divided by the Pettitt test, the contributions of different climatic variables and land use/cover conditions to runoff change were quantified. In general, the alteration of catchment characteristics and climatic change should be mainly responsible for changes in runoff in water-limited and humid basins, respectively. Although the elasticity of maximum temperature are usually higher than that of minimum temperature, the contributions to runoff change present the opposite direction. Furthermore, additional analysis indicated some overestimation in relative humidity elasticities in the previous studies, further emphasizing the necessity of our extension to alleviate the influence of correlation between climatic variables to the assessment results. Moreover, the results of model performance versus model complexity showed that the choice of model complexity still depends on the goal in the climatic and anthropogenic effects on runoff. If the climatic effect as a whole was of interest, the method based on two parameters elasticities would be more applicable compared to that based on multi-parameter elasticities because the simple model provides higher confidence in modelling the overall change in runoff. [ABSTRACT FROM AUTHOR]