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Seasonal variation and influencing factors of river water isotopes were investigated in the Xiangjiang River basin located in the East Asian monsoon region. This investigation involved comprehensive sampling of daily precipitation and river water with a 5 d interval as well as observing hydrometeorological factors spanning 13 hydrological years from January 2010 to December 2022, combined with the temporal and spatial correlation analyses based on linear regression and the isotopic Atmospheric Water Balance Model. Key findings are as follows: river water δ2H (δ2H R) exhibited significant seasonal variation, with the most positive and negative values occurring in the spring flood period and summer drought period, respectively, in alignment with those observed in precipitation. The correlations of the δ2H R with corresponding hydrometeorological factors with a 5 d interval were commonly weak due to the seasonality of precipitation isotopes and mixing of various water bodies within the basin, but the changes in the runoff (ΔR) and δ2H R (Δδ2HR) between two contiguous samplings with 5 d or higher intervals showed significant responses to the corresponding accumulated precipitation and evaporation. Prolonged rainless intervals with high evaporation rates in 2013 and 2022 as well as significant precipitation events in major flood periods in 2011 and 2017 had a significant impact on the δ2H R and runoff discharge. However, the most positive δ2H R values were primarily influenced by precipitation input with the most enriched isotopes in the spring flood period, while the moderately isotope-depleted precipitation during limited wetness conditions led to the most negative δ2H R. The spatial correlation analysis between water isotopes and hydrometeorological factors at the observing site and in the surrounding regions supported the representation of the Changsha site in the Xiangjiang River basin. These results underscore the potential of Δδ2HR as a proxy that reflects the seasonal variations in local environments, while caution is advised when interpreting extreme isotopic signals in river water. Overall, this study provides insights into the seasonal variation, extreme signal interpreting, and controlling factors of δ2H R in the study area, which was valuable for paleoclimate reconstruction and establishment of isotope hydrologic models. [ABSTRACT FROM AUTHOR]

In this study, temporal variations of pan evaporation (PE) and its optimal combination of controlling factors are investigated in the subregions of Yangtze River Basin (YRB) by using multiple wavelet coherence (MWC). For this purpose, the YRB is firstly divided into nine relatively homogeneous PE subregions by combining empirical orthogonal functions with fuzzy C‐means clustering. After regionalization, temporal variations of regional PE are analysed in each of subregions. Results reveal that regional annual PE has an upward trend in all subregions, and seasonal PE in almost the subregions for four different seasons. The wavelet transform coherence (WTC) analysis shows that vapour pressure deficit (VPD) is the primary controlling factor of PE variations in all subregions. In single factor analysis, VPD, sunshine duration (SSD) and 0 cm ground temperature (ZGT) have a higher covariance with PE than other influencing factors. For two‐factor analysis, the APS (air pressure)‐VPD combination, and for three‐factor analysis, the AWS (average wind speed)‐ ZGT‐VPD combination are the most common best explanatory variables on PE variations. A comparison of the results from the WTC and MWC indicates that PE variations can be explained more accurately by one, two, or three controlling factors. The combination of factors that optimally explains PE variations largely varies with subregions but with VPD as a dominant factor either alone or in combination for all subregions. Moreover, the optimal factor combination for a subregion is not necessarily combined by the first, second and/or third dominant factors for that subregion. Our results can provide useful insights into how multiple temporal dependency of PE is linked with meteorological factors in subregions of the YRB, particularly for PE modelling under changing climate conditions. [ABSTRACT FROM AUTHOR]

Numerous crucial paleoclimate records in monsoon regions depend on past precipitation isotopes as proxies for hydroclimate; however, the relationship between climatic variability and precipitation isotopes remains poorly understood. In this study, we investigated key climatic drivers from local to regional scales using 7-year-long daily summer precipitation isotopes in the Qinghai Lake watershed of the northeast Tibetan Plateau, located in the margin of summer monsoon extent. Results showed that daily precipitation δ18O and δ2H exhibited intra-seasonal fluctuation from 2012 to 2018 characterized by low isotopic values in July (e.g., δ18O = − 10‰) and high values in June (e.g., δ18O = − 6.7‰). Moisture source analysis via Hybrid Sing-Particle Lagrangian Trajectory indicated that the primary moisture of Qinghai Lake was mainly derived from northwestern inland regions, North China, and South China across seasons with high specific humidity and trajectory frequency, having a great influence on the isotopic patterns in precipitation across seasons. Moreover, convective activities in the primary moisture source regions, shown by outgoing longwave radiation and specific humidity along back trajectory, played a crucial role in controlling the seasonal variability of precipitation isotopes. These effects could be closely associated with the upstream convective intensity over the moisture sources or the changes of moisture sources during the observation periods. Interannual precipitation δ18O variation was significantly correlated with the indices of the El Niňo Southern Oscillation (r = 0.63, p < 0.1), with high precipitation δ18O value in the dry El Niňo year of 2015. Our findings suggested that precipitation isotopes in the Qinghai Lake watershed represented a spatial–temporal integrative indicator of precipitating processes and convection activity, providing the interpretation of paleo-isotope data in the regional hydroclimate variability across monsoon-affected regions. [ABSTRACT FROM AUTHOR]

Background and aims: Desert environments are characterized by limited and highly variable rainfall, which is an intermittent source of water critical to the evolution of the structure and functioning of desert ecosystems. The present study was the first to assess the effects of different amounts of rainfall received through discrete rainfall events and of their seasonality on two little-studied desert shrubs, namely Reaumurica soongorica and Nitria sphaerocarpa, in an arid inland river basin in north-western China.Materials and methods: Pulse rainfall events were simulated at the following magnitudes (amount of water in millimeters per rainfall event): 0, 5, 10, 15, 25, and 40 mm on two days in 2016, 24th June (early growing season) and 4th August (middle growing season), respectively. The rainfall effects were measured in terms of the following parameters: plant uptake of rainwater by plants as assessed by δ18O in the water within plant tissue, pre-dawn plant water potential, and the rates of photosynthesis and stomatal conductance.Results: N. sphaerocarpa shows faster response to simulated pulse rainfall events than R. soongorica, and the response of both species was quicker in the middle- than in early- growing season. Water uptake increased non-linearly with the amounts of rainfall, reaching a plateau at about 25 mm in R. soongorica and 20 mm in N. sphaerocarpa. The accumulative carbon gain relative to the controlled experiment increased with the amounts of rainfall, the increase being greater in the middle growing season.Conclusion: Our results clearly show that both the seasonality and the amounts of rainfall in discrete rainfall events took great impacts on response of plant ecophysiological activities and such responses are species dependent. The challenge ahead is to understand the consequences of long-term variability in rainfall for the physiology of desert plants and species dynamics in desert ecosystems. [ABSTRACT FROM AUTHOR]

• A new PDSI with improved hydrological modeling is calculated. • The PDSI hydrological components are assessed globally. • The new PDSI performs better in capturing hydrologic droughts than original PDSI. • Original PDSI largely overestimates drought increases under warming. With the ongoing climate warming, changes in drought and the adverse effects on water resources, food production and ecosystem functioning have been key research topics of ever-increasing interest. The Palmer Drought Severity Index (PDSI) is among the most widely used indicators for drought monitoring and research. However, the two-layer bucket water balance model embedded in the original PDSI model has been criticized for being over-simplified to accurately quantify the surface water balance and therefore raising uncertainties in the subsequent PDSI estimates (PDSI original). Here we improve the water balance calculations in the PDSI model by using direct hydrological outputs from physically-based, more sophisticated global hydrological models (GHMs) participated in the Inter-Sectoral Impact Model Inter-Comparison Project (ISIMIP). Validation results show that the estimated runoff (Q) and evapotranspiration (ET) from ISIMIP GHMs perform much better than those from the original PDSI two-layer bucket model in capturing the long-term trend and monthly variabilities of Q and ET, especially in cold regions and relatively dry areas, using observed Q (at 2191 catchments) and an independent satellite-based ET product (the Global Land Evaporation Amsterdam Model, GLEAM; over the entire terrestrial environment) as the reference. In addition, the new PDSI estimates with improved hydrological modeling (PDSI ISIMIP) exhibit a significantly stronger correlation with observed Q than PDSI original in nearly all studied catchments, suggesting that PDSI ISIMIP is superior to PDSI original in capturing hydrological droughts. We further compare the long-term PDSI trends and changes in drought using PDSI original and PDSI ISIMIP under both historical climate (1900–2005) and future climate change scenarios (2006–2099). We find that PDSI original and the PDSI original -identified land areas under drought generally show a larger trend than those based on PDSI ISIMIP. For future climate change scenarios, the PDSI original -projected increasing trend of land proportion under drought is about two times larger than that assessed with PDSI ISIMIP , implying that PDSI original may largely overestimate future drought increases, as commonly done in existing studies. In this light, our approach of directly using hydrological outputs from physically-based, more sophisticated GHMs provide an effective, yet relatively simple approach to reduce uncertainties in PDSI estimates thereby achieving a better prediction of drought changes under warming. [ABSTRACT FROM AUTHOR]

A diagram illustrating distribution and evolution model of soil water isotopic differences in the studied catchment. [Display omitted] • The immobile soil water showed high deviation from the LMWL in summer than in spring. • The mobile soil water was controlled by the precipitation input and less influenced by evaporation fractionation. • The mobile/immobile soil waters showed large isotopic differences and different mobility in summer. • Soil thawing provided important soil water sources and influenced the subsurface mixing processes. Recently studies postulate that there are two distinct soil water pools, i.e., mobile and immobile soil water (MSW and IMSW), and different soil waters have different mobility to generate runoff. Evaluating the influences of soil thawing on the subsurface mixing between different soil waters is important for understanding subsurface hydrological processes. In this study, the isotopic differences between different soil waters were evaluated in a permafrost-underlain headwater catchment by comparing the variations of stable isotopes and seasonal origin of MSW and bulk soil water (BSW), including both IMSW and MSW. BSW was sampled using soil augering and cryogenic vacuum distillation in thawed and frozen soil layers, and MSW was collected using a zero-tension lysimeter in thawed soil layers. The results show the following: (1) The average δ2H values of MSW, thawed BSW, and frozen BSW were similar during the spring snowmelt period (SSP), this can be attributed to weak evaporation and their similar origin, which is supported by the high line-conditioned excess values and their similar seasonal origin index values. (2) The enriched MSW collected during the SRP compared to the spring MSW and was associated with enriched summer precipitation, and the IMSW experienced strong evaporation during the period from the SSP to the SRP, both leading to enriched summer BSW compared to the spring BSW. (3) The frozen and thawed BSW had very similar isotopic compositions and seasonal origin, indicating the close hydrological connection between them and the important recharge of the melting frozen soil to soil water or runoff. The different freeze–thaw stages and soil moisture conditions controlled the stable isotope variations and mixing of different soil waters, this results in the different mobility of the mobile/immobile soil waters involved in the runoff generation processes during the SRP and the SSP, and therefore these features are useful to verify the isotopes-aided precipitation–runoff models applied in such catchments. [ABSTRACT FROM AUTHOR]