Prediction of evapotranspiration variance in the Budyko framework with the incorporation of soil storage and runoff.

Water availability needs to be accurately assessed to understand and effectively manage hydrologic environments. However, the estimation of evapotranspiration (ET) is prone to errors due to the complex interactions that occur between the atmosphere, the Earth's surface, and vegetation cover. This paper proposes a novel approach for analyzing the sources of inaccuracy in estimating the annual ET using the Budyko framework (BF), particularly temporal variability in precipitation (P), potential evapotranspiration (EP), runoff (R), and the change in soil storage (ΔS). Error decomposition is employed to determine the individual contributions of P, R, EP, and ΔS to the ET error variance at 12 locations in the state of Illinois using a dataset covering a 22-year period. To the best of our knowledge, this study represents the first BF-based investigation that considers R in the error decomposition of the predicted ET variance. The ET error variance increases with the variance in the P and R in Illinois and decreases with the covariance between these two variables. In addition, when accounting for ΔS in the BF, the scenario in which ΔS affects the total available water (i.e., P) is reliable, with a low prediction error and a 13.87 % lower root mean square error compared with the scenario in which the effect of ΔS is negligible. We thus recommend the inclusion of ΔS and R as key variables in the BF to improve water budget estimations.

Divergent spatiotemporal variability of terrestrial water storage and eight hydroclimatic components over three different scales of the Yangtze River basin.

Terrestrial water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on was first exacted by using the forward modeling (FM) method at three different scales over the Yangtze River basin (YRB): whole basin, three middle sub-basins, and eleven small sub-basins (total 15 basins). The spatiotemporal variability of eight hydroclimatic variables, snow water storage change (SnWS), canopy water storage change (CnWS), surface water storage anomaly (SWSA), soil moisture storage anomaly (SMSA), groundwater storage anomaly (GWSA), precipitation (P), evapotranspiration (ET), and runoff (R), and their contribution to TWSA were comprehensively investigated over the YRB. The results showed that the root mean square error of TWS change after FM improved by 17 %, as validated by in situ P, ET, and R data. The seasonal, inter-annual, and trend revealed that TWSA over the YRB increased during 2003-2018. The seasonal TWSA signal increased from the lower to the upper of YRB, but the trend, sub-seasonal, and inter-annual signals receded from the lower to the upper of YRB. The contribution of CnWS to TWSA was small over the YRB. The contribution of SnWS to TWSA occurs mainly in the upper of YRB. The main contributors to TWSA were SMSA (~36 %), SWSA (~33 %), and GWSA (~30 %). GWSA can be affected by TWSA, but other hydrological elements may have a slight impact on groundwater in the YRB. The primary driver of TWSA over the YRB was P (~46 %), followed by ET and R (both ~27 %). The contribution of SMSA, SWSA, and P to TWSA increased from the upper to the lower of YRB. R was the key driver of TWSA in the lower of YRB. The proposed approaches and results of this study can provide valuable new insights for water resource management in the YRB and can be applied globally.

Anthropogenic climate change exacerbates the risk of successive flood-heat extremes: Multi-model global projections based on the Inter-Sectoral Impact Model Intercomparison Project.

The successive flood-heat extreme (SFHE) event, which threatens the securities of human health, economy, and building environment, has attracted extensive research attention recently. However, the potential changes in SFHE characteristics and the global population exposure to SFHE under anthropogenic warming remain unclear. Here, we present a global-scale evaluation of the projected changes and uncertainties in SFHE characteristics (frequency, intensity, duration, land exposure) and population exposure under the Representative Concentration Pathway (RCP) 2.6 and 6.0 scenarios, based on the multi-model ensembles (five global water models forced by four global climate models) within the Inter-Sectoral Impact Model Intercomparison Project 2b framework. The results reveal that, relative to the 1970-1999 baseline period, the SFHE frequency is projected to increase nearly globally by the end of this century, especially in the Qinghai-Tibet Plateau (>20 events/30-year) and the tropical regions (e.g., northern South America, central Africa, and southeastern Asia, >15 events/30-year). The projected higher SFHE frequency is generally accompanied by a larger model uncertainty. By the end of this century, the SFHE land exposure is expected to increase by 12 % (20 %) under RCP2.6 (RCP6.0), and the intervals between flood and heatwave in SFHE tend to decrease by up to 3 days under both RCPs, implying the more intermittent SFHE occurrence under future warming. The SFHE events will lead to the higher population exposure in the Indian Peninsula and central Africa (<10 million person-days) and eastern Asia (<5 million person-days) due to the higher population density and the longer SFHE duration. Partial correlation analysis indicates that the contribution of flood to the SFHE frequency is greater than that of heatwave for most global regions, but the SFHE frequency is dominated by the heatwave in northern North America and northern Asia.

Testing the hypothesis on the relationship between aerodynamic roughness length and albedo using vegetation structure parameters.

Surface albedo (α) and aerodynamic roughness length (z(0)), which partition surface net radiation into energy fluxes, are critical land surface properties for biosphere-atmosphere interactions and climate variability. Previous studies suggested that canopy structure parameters influence both α and z(0); however, no field data have been reported to quantify their relationships. Here, we hypothesize that a functional relationship between α and z(0) exists for a vegetated surface, since both land surface parameters can be conceptually related to the characteristics of canopy structure. We test this hypothesis by using the observed data collected from 50 site-years of field measurements from sites worldwide covering various vegetated surfaces. On the basis of these data, a negative linear relationship between α and log(z(0)) was found, which is related to the canopy structural parameter. We believe that our finding is a big step toward the estimation of z(0) with high accuracy. This can be used, for example, in the parameterization of land properties and the observation of z(0) using satellite remote sensing.

Responses of vegetation to changes in terrestrial water storage and temperature in global mountainous regions.

As an important component of terrestrial ecosystem, vegetation acts as a sensitive recorder of changes in hydroclimatic conditions. Long-term time series of remote sensing-based vegetation indices and their influencing environmental driving factors, such as human activities and climate change, have been widely discussed in the literature. Globally, however, little is known about the hydroclimatic processes controlling vegetation changes in mountainous regions, which are conceived as more sensitive to climate change than other landscapes. The present study aims to quantify the respective roles of two dominant hydroclimatic factors, namely, TWS (i.e., terrestrial water storage) and Tair (i.e., temperature), in the spatio-temporal changes of mountainous vegetation over global six contrasting climate zones (i.e., tropical, arid, subtropical, temperate, sub-frigid, and frigid zones) during the period 2003-2016 based on EVI (i.e., enhanced vegetation index), TWS, Tair, and elevation data. Results indicate that the mean EVI shows a larger increasing trend (+0.85 %/decade, p-value < 0.01) and a larger decreasing trend in TWS (-85 mm/decade, p-value < 0.01) across the global mountainous regions than other global regions combined together (+0.61 %/decade, p-value < 0.01), particularly over high latitudes. With the increasing latitudes, the positive effect of temperature more dominates mountainous vegetation growth than moisture, as evidenced by the increasing trends of EVI with warming. However, in certain low-latitude mountainous regions (e.g., East Africa, South Asia, the western Tibetan Plateau, Brazil Plateau, and the southern Rocky Mountains), mountainous vegetation may face degradation due to water deficit induced by increased snowmelt, especially among the high-elevation ecosystems. The water availability controls vegetation activities more than Tair in the mid- and low-latitude regions, including the tropical, arid, and subtropical climate zones. These findings indicate that the potential shifts in mountainous vegetation may occur under the notable interactions with hydroclimatic factors, as the high-latitudes are experiencing ongoing warming and the mid- and low-latitudes are getting dryer.

Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers.

Groundwater provides critical freshwater supply, particularly in dry regions where surface water availability is limited. Climate change impacts on GWS (groundwater storage) could affect the sustainability of freshwater resources. Here, we used a fully-coupled climate model to investigate GWS changes over seven critical aquifers identified as significantly distressed by satellite observations. We assessed the potential climate-driven impacts on GWS changes throughout the 21st century under the business-as-usual scenario (RCP8.5). Results show that the climate-driven impacts on GWS changes do not necessarily reflect the long-term trend in precipitation; instead, the trend may result from enhancement of evapotranspiration, and reduction in snowmelt, which collectively lead to divergent responses of GWS changes across different aquifers. Finally, we compare the climate-driven and anthropogenic pumping impacts. The reduction in GWS is mainly due to the combined impacts of over-pumping and climate effects; however, the contribution of pumping could easily far exceed the natural replenishment.