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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]

Graphical abstract Highlights • Water storage change occupies a large proportion in the precipitation partitioning at monthly scale. • Estimate monthly evapotranspiration by combining GRACE data into extended Budyko framework. • Budyko-E represents GRACE-E in arid regions comparatively better than it in humid regions. • Budyko monthly evapotranspiration outperforms four other global evapotranspiration products. Abstract The estimates of actual evapotranspiration (E) across basins and/or regions are still facing some difficulties because of the complex interactions amongst the components of the land-plant-atmosphere system, even though the basic physical mechanism of E is well understood. Presenting as a nonlinear relationship constrained by physical limits, the Budyko framework serves as a powerful tool used to estimate the averaged E at long-term scale. Given the ability of Gravity Recovery And Climate Experiment (GRACE) in effectively simulating the terrestrial water storage change (Δ TWS) at monthly scale, a model to estimate E was developed based on the Budyko framework with mean monthly parameter of multi-years, and was applied to the estimation of E for the 24 selected catchments in different climatic regions across China. Results indicate that for the majority of 24 catchments, the positive or negative trends in precipitation (P), potential evapotranspiration (E 0), runoff (R) and Δ TWS were not statistically significant during 2003–2013 at both annual and monthly scales, but the Δ TWS occupied a large proportion in the partitioning of P into R and E at monthly scale. The monthly Budyko parameter showed large variation within the year and also across these 24 catchments. The Budyko-modeled monthly E (Budyko-E) represented the GRACE-derived ones (GRACE-E) across these catchments well with both modeled E volumes and hydrograph shapes which were also consistent with GRACE-E series except some underestimation for peak E. Overall, the Budyko-E represented GRACE-E in the arid and semi-arid catchments comparatively better than it in the humid and semi-humid catchments due to the larger proportion of Δ TWS in the P partition. Among all the 24 selected catchments, the monthly Budyko-type E model represented the GRACE-E across Shixiali catchment (located in the Hai River basin) best, with the correlation coefficient (r), Nash-Sutcliffe coefficient (NSCE) and relative error (RE) between GRACE-E and simulated results being 0.996, 0.988, −0.033 in calibration and 0.994, 0.951, −0.111 in validation, respectively. Furthermore, using GRACE-E as the benchmark values, the Budyko-E outperformed four other global E products from the newly published Global Land Data Assimilation System with Noah Land Surface Model-2 (GLDAS_E), MODIS (MODIS_E), Japanese 25-year reanalysis product (JRA_E), and Zhang's method (Zhang_E). GLDAS_E was the best of four global E products at reproducing monthly variations, with relatively high r and NSCE values, small RE. While MODIS_E showed the poorest performance in reproducing the inter-annual E variations of these catchments, which was reflected by low r and NSCE values. This extended Budyko-E model can apply in other similar climatic regions and also may provide skill in evaluating the water resources since the preferable accuracy of E estimate. [ABSTRACT FROM AUTHOR]

It has become increasingly important to quantify carbon and water fluxes due to their roles in global warming and climate change, particularly for the agroecosystems. However, the dynamics of carbon and water fluxes have not been clearly recognized in rotation croplands with complex and changeable climate. Here, the variations of net ecosystem productivity (NEP), evapotranspiration (ET) and the water use efficiency (WUE, defined as NEP/ET), and their responses to the environmental factors were investigated in a wheat-maize rotation cropland across the Huaibei Plain of China over 2013–2015. The total average NEP, ET and average WUE respectively were 489.1 gC m-2, 315.8 kgH 2 O m-2, 4.4 gC kg-1H 2 O for wheat and 192.5 gC m-2, 249.0 kgH 2 O m-2, 3.6 gC kg-1H 2 O for maize, implying that wheat season sequestered more CO 2 than maize season. Spring drought and summer flood affected WUE of wheat and maize, respectively. Daily wheat WUE seemed to be more sensitive to changes in photosynthetically active radiation (PAR), vapor pressure deficit (VPD), soil water content (SWC) and canopy conductance (G c). PAR was the dominant factor controlling diurnal dynamics of NEP and ET, while the opposite effect of VPD on NEP was recognized. NEP increasing with PAR was limited by high VPD, which obviously when VPD exceeded 2 kPa during the maize season. Maize NEP was limited with VPD under high solar radiation (> 500 μmol m-2 s-1). WUEs of wheat and maize were negatively related to SWC and G c , and the sensitivity of WUE response to SWC and G c increased with the increase of PAR or VPD range. Sub-diurnal NEP against PAR, VPD or temperature showed clockwise hysteresis but ET against PAR or windspeed showed counter-clockwise hysteresis, and these hystereses were mainly caused by the interplay between evaporative demand and moisture supply, photosynthesis and carbon allocation of the agroecosystems. [Display omitted] • The wheat season sequestered more CO2 than the maize season. • Spring drought and summer flood affected WUE of wheat and maize, respectively. • Wheat WUE seemed to be more sensitive to changes in environmental factors. • PAR was the dominant factor controlling diurnal dynamics of NEP and ET. [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]

Summary As the indicator of atmospheric evaporative demand over a hypothetical reference surface, reference evapotranspiration (ET 0 ) is an important input to hydrological models. Future projections of ET 0 are of great importance in assessing the potential impacts of climate change on the hydrologic regime as well as water resources systems. Different estimating formulations and different input data reliabilities existing in practice determine there may be potential uncertainty in projection of future ET 0 change. Here we investigated the difference of future ET 0 response to climate change based on three approaches, i.e., more physically based Penman–Montieth equation with relatively uncertain downscaled data quality, more empirical temperature-based Hargreaves equation with more reliable downscaled input data, and statistical downscaling method with directly selecting ET 0 as predictands. The Hanjiang River Basin, a headwater source of famous South to North Water Diversion Project (SNWDP) in China was chosen as example to illustrate this issue. Although similar increase processes of ET 0 in the Hanjiang River Basin were suggested by three methods, the magnitude of ET 0 increase differs substantially, indicating that uncertainty still exist despite of approximate performance of these methods in simulating general trends. Whilst increasing aridity index and decreasing water surplus over the period of 2011–2099 would inevitably cause negative impacts on the implementation of the SNWDP and effective adapting measures are thus expected. [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]

Abstract Phosphorus (P) is an indispensable resource for plant growth, and under the background with P consumption increase in crop system, the agriculture and crop production may be affected through the changes of phosphorus use efficiency (PUE) due to the human interference and climate change. Therefore, it is of great importance to investigate the responses of PUE to human interference and climate change from the perspectives of historical simulation and future projection. In this study, the changes of PUE from 2001 to 2015 in the middle and lower reaches of the Yangtze River (MLRYR) of China were evaluated by means of empirical PUE-model based on the substance flow analysis (SFA) method. Their responses to future human interference and climate scenarios during 2016–2030 were investigated by driving PUE-model with three neural networks (BP, GA-BP and PSO-BP) as well as the multiple downscaling climatic data (HadGEM2-ES, BCC-CSM1.1 (m) and GFDL-ESM2M) with the help of a statistical downscaling method (SDSM). The results showed that the PUE values of the three crops (rice, wheat and maize) were 53.61%, 36.22%, and 32.56%, respectively, during the period from 2001 to 2015 and 54.11%, 38.92% and 32.78%, respectively, during the period from 2016 to 2030. Consequently, the PUE showed an increasing trend from history to future. However, the overall PUE level was not high, with a value of not more than 60%, and notably for wheat and maize, the PUE was less than 40%. Meanwhile, the precipitation affected the leaching of P because increasing in precipitation may result in a relatively high increase in the probability of low-PUE. Moreover, great potential exists for enhancing the PUE in this region, and measures to improve PUE management practices have been proposed, such as, raising the crop yield, keeping the arable area and balancing the fertilization, etc. The present study provides a beneficial reference to comprehensively understand the impacts of human interference and climate change on the PUE and further improves regional sustainable strategies for future P resource management. Highlights • Evaluating the responses of PUE to human interference and climate change from historical simulation and future projections. • Predicting the future PUE by driving PUE-model with the multiple neural networks and GCMs. • Besides the rice, the PUE values of wheat and maize were less than 40% during 2001–2030. [ABSTRACT FROM AUTHOR]

Accounting for over 70% of global water withdrawals, irrigation plays a crucial role in the development of agriculture. Irrigation water requirement ( WIRR ) will be influenced by climate change due to the alteration in soil water balances, evapotranspiration, physiology and phenology under global warming. This is particularly true for rice, a high water-consuming crop. Therefore, exploring the impact of climate change on rice WIRR is of great significance for the sustainable utilization of water resources and food security. This paper aims to investigate spatially and temporally the responses of rice WIRR to climate change in the middle and lower reaches of the Yangtze River (MLRYR), which is one of the most important rice farming districts in China. With the help of the specially developed rice growing period calculation method and water balance model coupled with rice irrigation scheduling, the impacts of climate change on WIRR for early rice, late rice and single cropping rice during the historical (1961–2012) and future (2011–2100) periods were evaluated. Meanwhile, to consider the uncertainty from climate models in future projection, four GCMs under RCP2.6, RCP4.5 and RCP8.5 emission scenarios from the 5th Coupled Model Intercomparison Project (CMIP5) were employed as the input of the water balance model. The results indicate the following: (1) The days of growing period ( DGP ) for all three types of rice display shortened trends in historical and most future periods. However, in the middle region of the MLRYR, the DGP for early rice and late rice would increase by up to10 days in 2080s under RCP8.5 scenario. (2) Over the past 50 years, the WIRR significantly decreased by 1.58 and 2.10 mm yr −1 for late rice and single cropping rice, respectively. While for early rice, the WIRR only slightly decreased by 0.13 mm yr −1 . (3) Projected future WIRR would increase for all three types of rice in the whole region under RCP4.5 and RCP8.5 scenarios (up to 100 mm), but decrease for single cropping and late rice in the southeast region (up to 40 mm). The results can provide beneficial reference and comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization and agricultural management in the middle and lower reaches of the Yangtze River. [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]

As one of the most important crops cultivated in China, rice contributes to approximately 28% of total yield. In despite of the substantial production, rice productivity is gravely affected by ongoing climate change and reduction of available water resources. Thus, assessing the responses of rice water consumption and productivity to more pronounced climate change is of great significance to water resources management in terms of relieving the resources shortage and meeting the food demand. In this study, the yield and water resources utilization during 1961–2010 in two typical rice plantation regions of China were evaluated using validated rice model ORYZA2000. Subsequently, their responses to future climate scenarios of 21 century were investigated through driving ORYZA2000 with downscaling climatic projections from GCMs under four RCPs emission scenarios. To quantify the water resources utilization in rice production from multiple perspectives, the water footprint (WF) and three water productivity indices (WP I , WP U and WP ET) were integrated for assessing the regional agricultural water stress in this paper. The results revealed that the annual average linear inclining rates of WF in two stations (Kaifeng and Kunshan) were 3.86 m3/ t and 2.62 m3/ t, respectively. Moreover, compared with the green water footprint (WF g), the blue water footprint (WF b) is projected to significantly increase in future. The water productivity (WP) would decrease in two stations under four RCPs scenarios except that the WP u and WP ET of Kunshan under RCP2.6 and RCP4.5 scenario in 2020s, 2050s and 2080s. Hence, this study provides insights into comprehensively understand the influences of climate change on food security and sheds lights on the regional strategy for future water resource management. Unlabelled Image • The study pioneers the use of ORYZA model along with GCM outputs in rice WF assessment under climate change. • The rice WFs of two stations are projected to increase in future. • Decrease in CWU green of Kunshan does not affect incremental WF g due to the decline in future rice yield. • Compared with WF b , the WF g of study area play a dominant role in the growth of future rice WF. [ABSTRACT FROM AUTHOR]