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Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]

Increasing variability of precipitation induced by climate change raises uncertainties for ecosystem services and agricultural production in the Poyang Lake Basin (PLB), China. Reanalysis precipitation datasets (RPDs) are attractive alternatives for monitoring the hydro‐climate cycles. However, their applicability in China has mainly been evaluated at the national scale, while less attention has been paid to the PLB or southeastern China. Here, we apply various metrics to evaluate the magnitude and spatial similarity of annual, monthly, different intensities and the spatial structure of precipitation from four reanalysis—the fifth global atmospheric analysis dataset of the European Center for Medium‐Range Weather Forecasts (ECMWF) (ERA5), Interim ECMWF Reanalysis (ERA‐Interim), Japanese 55‐year Reanalysis project (JRA55) and Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2), against the rain‐gauges over the PLB during 1980–2018. The results showed that the detection capacity of ERA5 and MERRA2 shifted around 2002, whereas that of ERA‐Interim and JRA55 did not substantially change. Before 2002, ERA‐Interim had the lowest biases for the magnitude of annual, monthly and different intensities of precipitation (except for heavy rain), while ERA5 and MERRA2 had strengths in capturing spatial correlation. Notably, ERA5 and MERRA2 had region‐wide wet and dry biases, respectively, before 2002, which can be attributed mainly to the estimation of flood season precipitation (from April to June) and heavy rain. In contrast, the fractional contribution of light–moderate rain was underestimated and overestimated by ERA5 and MERRA2, respectively. However, after 2002, because of the improved reproducibility of flood season precipitation and heavy rain magnitude, the systematic biases of ERA5 and MERRA2 significantly decreased, especially for ERA5, which outperformed other RPDs on all aspects of precipitation. The conclusions of this paper suggest that the variation of applicability over time should be seriously tested before the utilization of RPDs in hydro‐climate analyses. [ABSTRACT FROM AUTHOR]

Projecting precipitation changes is essential for researchers to understand climate change impacts on hydrological cycle. This study projected future precipitation over the Hanjiang River Basin (HRB) based on the multimodel ensemble (ME) of six global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). An ME method using the fusion of four machine learning (ML) algorithms (random forest [RF], K‐nearest neighbors [KNN], extra tree [ET], and gradient boosting decision tree [GBDT]) was proposed in this study. The future precipitation changes were investigated during 2023–2042 (Near‐term), 2043–2062 (Mid‐term), and 2081–2100 (Long‐term) periods, with reference to the base period 1995–2014, under three integrated scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5) of the Shared Socioeconomic Pathways (SSPs) and the representative concentration pathways (RCPs). The results show that: (1) the proposed ME method performs better than the ME mean and individual ML algorithms, with a correlation coefficient value reaching 0.88 and Taylor skill score reaching 0.764. (2) The precipitation under SSP5‐8.5 has the largest upward trend with the annual precipitation variation range of −9.27% to 112.84% from 2023 to 2100, followed by SSP2‐4.5 with −30.48% to 44.67%, and the smallest under SSP1‐2.6 with −37.19% to 37.78%, which show a significant trend of humidification over the HRB in the future. (3) The precipitation changes over the HRB are projected to increase over time, with the largest in the Long‐term, followed by Mid‐term, and the smallest in the Near‐term. (4) The northeastern parts of the HRB are projected to experience a large precipitation in the future, and the southeastern parts are smaller. (5) Uncertainties in the projected precipitation over the HRB still exist, which can be reduced by ME. The findings obtained in this study have important implications for hydrological policymakers to make adaptive strategies to reduce the risks of climate change. [ABSTRACT FROM AUTHOR]

Understanding and exploring hydrological (H) or soil moisture (SM) drought due to meteorological (M) drought under changing climate is crucial for drought early warning. Previously, different methods were used to calculate drought propagation from one state (M to another [H or SM]). However, each method has its pros and cons and thus cannot describe appropriate propagation attributes. In this study, a time series analysis is carried out to explore the propagation process in the Yellow River Basin (YRB) and Hai River Basin (HRB) of China. Standardized Streamflow Index (SSI), Standardized SM Index (SSMI), and Standardized Precipitation Index (SPI) 1‐month time series were calculated using streamflow, satellite‐based SM, and precipitation from 1979 to 2016. The time series framework identifies the average drought propagation as 3.4–8.3 months (M–H) and 2.3–5 months (M–SM) in YRB, while 2.8–7.7 months (M–H) and 2.3–8.5 months (M–SM) in HRB. Cross‐wavelet analysis indicated that periodic characteristics of M drought are responsible for these droughts. Overall, the findings of this study may help to minimize the drought hazards posed by M droughts. [ABSTRACT FROM AUTHOR]

Many studies found that land use change (LUC) had great impacts on regional precipitation, due to thermodynamic and dynamic responses. However, the relative contributions of these two factors to changes in precipitation due to LUC are rarely investigated. This study quantifies the relative contributions of thermodynamic and dynamic to the changes of mean and extreme precipitation due to LUC based on simulations of the Weather Research and Forecasting (WRF) model. The Yangtze River Basin (YRB) is used as a case study, as it has experienced great LUC during the past decades. Four land use scenarios (two factual cases and two hypothetical reforestation scenarios) were used to test the sensitivity of precipitation changes to LUC. Changes in mean and extreme precipitation over the YRB for all seasons are attributed to thermodynamic and dynamic changes using 500‐hPa geopotential height and precipitation data derived from the simulations of WRF. The results show that the factual process of LUC results in a decrease in summer mean daily precipitation and precipitation extremes in most areas of the YRB (except for the middle reaches of the YRB), while the hypothetical reforestation contributes to an increase in summer mean and extreme precipitation, and the impacts of reforestation on increasing precipitation are limited. The thermodynamic change contributes to an increase in seasonal mean daily precipitation, extreme precipitation totals and occurrence frequency of precipitation extremes with contributions ranging from 94 to 102%, which is the main contributor of changes in precipitation due to LUC. The dynamic change only makes a small contribution to the change of precipitation. Because the contributions of thermodynamic can be offset by dynamic changes to changes in precipitation, it could result in minimal changes in precipitation and occurrences of precipitation extremes. [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]

The current study investigates the variability of vertical structure of precipitation in the Huaihe River Basin (HRB) of China. The precipitation characteristics have been revealed by the long-term observations of vertical profile of reflectivity (VPR) from the first spaceborne precipitation radar (PR) onboard the National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission (TRMM) satellite. This study has statistically analyzed the latest TRMM 2A-23 and 2A-25 products (version 7, released in 2012) with ∼15 years time span (from 11 December 1997 to 19 August 2012). First, the spatial and seasonal variations of storm height and freezing level have been investigated. The results show a climatological relation connecting the storm height with the rainfall rate in HRB. Second, mean VPRs have been studied for the stratiform and convective precipitation. The VPR variability has been analyzed for different seasons and rain intensities. Third, the characteristics of rain intensification and weakening in the vertical direction have been examined by the statistical analysis of VPR slope below the melting layer. The results show that the rainfall tends to be reduced (or intensified) with the height changing downward in the light (or moderate and heavy) precipitating clouds, no matter stratiform or convection. Finally, the S-band climatological VPRs have been characterized by converting the VPR from Ku-band to S-band. Considering the wide application of national radar network for weather surveillance in China, the developed S-band climatological VPRs can be potentially applied in a VPR correction scheme to improve the ground radar-based quantitative precipitation estimation (QPE) in this river basin. [ABSTRACT FROM AUTHOR]

This study aims to determine temporal trends and spatial distribution of the annual and monthly precipitation in the Haihe River Basin, China, during 1951-2008. A significant decreasing trend was observed for the annual precipitation, mainly attributed to the abrupt decrease in the flood-season precipitation (June-September) around the year of 1979. No significant trend was revealed for precipitation within Period I of 1951-1979 and Period II of 1980-2008. Results of this study indicated that the relative contributions of the flood-season precipitation decreased temporally with time and spatially with elevation. This study also identified a potential movement of storm centers from east to west portions of the basin. In addition, analysis on the precipitation anomalies also suggested a redistribution of the non-flood season precipitation over the study area. Compared with the west portion of the basin, generally, the east received relatively more precipitation during the non-flood season, while similar trend of precipitation redistribution was not observed in the flood season. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Soil moisture is a consideration for soil conservation, agricultural production and climate modelling. This article presents a simple method for estimating soil moisture storage under water stress and storage depletion conditions. The method is driven by the common agro-hydrologic variables of precipitation (PPT), irrigation (IRR) and evapotranspiration (ET). The proposed method is successfully tested for the 152 000 km2 floodplain region of Hai River Basin using 48 consecutive months (2003-2006) of data. Soil moisture data from global land data assimilation system/Noah land surface model are validated with ground-truth data from 102 soil moisture monitoring sites. The validated soil moisture is used in combination with in situ groundwater data to quantify total water storage change (TWSC) in the region. The estimated storage change is in turn compared with gravity recovery and climate experiment-derived TWSC for the study area. The soil moisture and TWSC terms show favourable agreements, with discrepancies of <10% on the average. While there is no consistent seasonal trend in soil moisture, TWSC shows a strong seasonality. It is low in spring and high in summer. This trend corresponds with the IRR-PPT season in the study area. Change in groundwater and total water storage indicates storage depletion in the basin. Storage depletion in the region is driven mainly by groundwater IRR and ET loss. Despite the low PPT and high ET, there is narrowing seasonal trend in soil moisture. This is achieved at the expense of groundwater storage. IRR pumping has induced extensive groundwater depletion in the basin. It is therefore vital to develop cultivation strategies that aim at limiting IRR pumping and ET loss. Water management practices that not only reduce waste but also ensure high productivity and ecological sustainability could also mitigate storage depletion in the region. These measures could reduce further not only the seasonal trend in soil moisture but also that in groundwater storage. [ABSTRACT FROM AUTHOR]

The article presents a study on the long-term monotonic trend and abrupt changes for major climate variables at 23 meteorological stations in the headwater catchment of the Yellow River basin in China from 1960 to 2001 on the basis of mean air temperature, precipitation, sunshine duration and pan evaporation. It states that the abrupt changes have been examined in terms of a five-year moving averaged annual series using the moving t-test (MTT) method, Yamamoto method and Mann-Kendall method. The results indicated that the annual air temperature has increased by 0.80 degrees Celsius in the headwater catchment of the Yellow River basin during the past 42 years.

Water budget plays an important role in ecological functions and biogeochemical cycles on the Qinghai‐Tibet Plateau (QTP). However, the key factors that govern the water budget across spatiotemporal scales in natural conditions are poorly understood, especially in the alpine region. To advance our understanding of how and why the water budget varies at the ecosystem and catchment scales, this study measured and modeled the main water budget components in the Qinghai Lake Basin (QLB) and further investigated the key factors for evapotranspiration and streamflow. The results showed that most monthly precipitation from June to September was greater than the corresponding evapotranspiration from the high‐altitude Kobresia meadow (KMd.) and Potentilla fruticosa shrub (PFSh.) ecosystem, and vice versa for the low‐altitude Achnatherum splendens steppe (ASSt.) ecosystem. The mean annual proportions of evapotranspiration of precipitation for the KMd., PFSh., and ASSt. ecosystems were 0.83, 1.06, and 1.02, respectively, from 2014 to 2015. The study highlights that the high‐altitude KMd. ecosystem is the main contributing area for runoff generation in the QLB. From ASSt. to PFSh. and then to the KMd. ecosystem, the key factors for evapotranspiration switched from water conditions to temperature conditions with the increase in elevation. The future scenario of climate warming and precipitation increase may cause a rise in evapotranspiration and streamflow in the QLB. Moreover, the increasing precipitation may be consumed mainly by evapotranspiration in the high altitude with low slope and by transfer into streamflow in the area with high slope. Key Points: The high‐altitude Kobresia meadow ecosystem is the main runoff‐producing area in the Qinghai Lake BasinThe key controlling factor for evapotranspiration changed from water conditions to temperature conditions with an increase in elevationThe increasing precipitation will be mainly consumed by evapotranspiration in the high altitude with low slope and by transfer into streamflow in the area with high slope [ABSTRACT FROM AUTHOR]