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• Multi-year drought induces changes in evapotranspiration (ET) that involve complex mechanisms of climate-soil-vegetation interactions. • The ET reduction induced by drought strength increase showed asymmetric hydrological responses in the water and energy limited regions. • The ET responses underlying mechanism suggests catchments with higher wetness could effectively mitigate effects of multi-year droughts. Multi-year droughts constitute a natural experiment for testing the hydrological legacy across different climate regimes. Evapotranspiration (ET) responses to drought have not been fully elucidated because the underlying mechanisms involve complex interactions of climate, soil, and vegetation. This study collected monthly hydrometeorological data during 1982–2011 from 1069 catchments worldwide to investigate multi-year droughts and their impacts on ET and to analyse the underlying mechanisms of ET. As expected, multi-year droughts generally induced ET reductions across different climate regimes, while ET exhibited asymmetric hydrological responses with a greater portion of precipitation (P) being partitioned into ET in water-limited regions, and a smaller portion of P being partitioned in ET in energy-limited regions. Multi-year droughts induced soil moisture droughts and leaf area index decreases, which often led to increases in the vapour pressure deficit, while inconsistent responses occurred for air temperature. Interestingly, when long-term catchment wetness [i.e., (precipitation − streamflow) / precipitation] exceeded 0.50 we found that catchment wetness played a vital role in controlling the response of catchment properties to climate changes. During the multi-year droughts, attribution analysis revealed the enhanced role of available water (represented by P) in controlling ET , followed by available energy and vegetation. Although vegetation played vital role in controlling ET in energy-limited regions, it was P that controlled ET during drought periods. Taken together, these findings indicate that ET responses and their underlying mechanisms induced by multi-year droughts vary under different climate regimes. Specifically, a two-stage mechanism drove the ET responses in wet catchments, suggesting that catchments with higher catchment wetness (>0.50) could more effectively mitigate the impact of multi-year droughts. [ABSTRACT FROM AUTHOR]

• Spatiotemporal seamless SSM and RZSM products are evaluated simultaneously. • National SM observation network of the same specifications is used to evaluate. • The feature of SM products under different precipitation conditions are identified. • The sensitivity of SM products to precipitation is validated. Accurate and timely information about soil moisture (SM) is not only critical to the study of climate change, but is also significant for agricultural production, drought monitoring, and hydrometeorological predictions. With the development of satellite remote sensing techniques, land surface models, and data assimilation techniques, a number of global seamless soil moisture products have been released with highly variable accuracy. A comprehensive evaluation of these products is necessary to select a suitable SM product for use. In this study, we provided such an evaluation of four global seamless SM products (SMAP-L4, ERA5-Land, GLDAS-Noah, and GLEAM) over China based on the stations from the automatic soil moisture observation (ASMO) system. Compared to previous studies that focused on a direct comparison between SM products and in situ SM observations, we specifically evaluated these products from the perspective of SM sensitivity to precipitation. This is because in situ precipitation observations are more spatially representative than in situ SM observations. Precipitation is a regional event, therefore in situ precipitation observations can be better scale-matched with coarse resolution SM products compared to in situ SM observations. Further, in addition to surface soil moisture (SSM), root zone soil moisture (RZSM) was evaluated in this study. The combination of all statistics illustrates that SMAP-L4 and ERA5-Land generally performed better than GLDAS-Noah and GLEAM. Regardless of the SSM or RZSM estimates, SMAP-L4 had the lowest median bias and RMSE of the four products, and ERA5-Land had the lowest median correlation coefficient (R) value. The lowest median ubRMSE was obtained by SMAP-L4 in SSM evaluation and ERA5-Land performed better than other RZSM products with the lowest median ubRMSE. From the perspective of SM sensitivity to precipitation, SMAP-L4 can capture daily precipitation dynamics most effectively, closely followed by ERA5-Land. This partially explains the superiority of SMAP-L4 and ERA5-Land over GLDAS-Noah and GLEAM for SM monitoring. The results of the metrics under different precipitation conditions varied considerably among the products. But while considering of ubRMSE alone, all products performed better under arid and humid conditions than to semi-arid and semi-humid conditions. This may be due to the fact that SM products had a limited ability to capture the SM dynamics under moderate precipitation. These findings may provide new insights into the selection of appropriate SM products and SM estimation in the future. [ABSTRACT FROM AUTHOR]

• Changes in flood risk are investigated using a bottom-up climate change assessment. • Thermodynamic and dynamic drivers of rainfall, and losses are considered. • Increases in rainfall intensity are the key driver of increased flood risk. • Smaller flood events in drier catchments are most sensitive to changes in losses. • Uncertainty in the projected changes in flood peaks between GCMs remains large. Our understanding of the key drivers of change in flood risk due to climate change remains incomplete. Here, to understand and quantify the key drivers of change in flood risk, we present a framework to undertake a 'bottom-up' ('scenario-neutral') climate change impact study on flood risk using an event-based flood model that considers non-stationarity in rainfall extremes and catchment wetness. A key advantage of this approach is that by using an event-based model, which explicitly represents key flood drivers, we can directly understand how changes in these drivers will influence changes in flood peaks. The utility of this modelling framework is demonstrated by applying it to one temperate and one tropical catchment in Australia, focusing on the sensitivity of frequent (1 in 5 annual exceedance probability, AEP) and rare (1 in 50 AEP) flood peaks to changes in thermodynamic and dynamic drivers of rainfall extremes, and changes in catchment processes, which are quantified by changes in rainfall losses. Response surfaces of the catchment sensitivity are first produced and demonstrate that increases in rainfall intensity drive increases in the flood peak. Smaller flood peaks in drier catchments are most sensitive to changes in rainfall losses, with the modulating impact of changes in losses decreasing as the runoff ratio increases. Climate model projections of these drivers are then superimposed on these surfaces to identify plausible shifts in flood risk under climate change. Several climate model ensemble members imply a decrease in future flood peaks, most notably 14 % of ensemble members suggest future decreases for the 1 in 5 AEP event for the temperate catchment. Despite large agreement on the direction of change, we found large variability in the expected magnitude of change for both frequent and rare events with flood peaks projected to increase between 0 % and 45 % for the tropical catchment and between −10 % to more than 50 % for the temperate catchment under RCP8.5 in 2085, highlighting the deep uncertainty associated with projecting flood risk under climate change. We believe this study acts as proof of concept for how a bottom-up climate change assessment can be undertaken within an event-based flood modelling framework, and provides insights to help us better understand and communicate the key drivers of changes to flood risk into the future. [ABSTRACT FROM AUTHOR]

• We evaluated physical and ML models for crop field ET modeling on the TP. • Physically-based model showed better performance compared to ML models. • Soil moisture was the most influential factor in ML-based ET modeling. • RM presented higher T/ET ratio compared to CK under future rainfall change. Accurately estimating crop evapotranspiration (ET) is key for understanding the effects of climate change on crop productivity and aiding in irrigation scheduling. This is particularly true in the arid northeastern Tibetan Plateau (TP) where has become the largest planting area of wolfberry (Lycium barbarum L.) in China to promote farmer's income. However, limited research ever focused on wolfberry ET estimation. To this end, we conducted a two-year experiment (2018-2019) in a wolfberry irrigation district within northeastern TP. We used an airflow coupled soil hydrothermal model, which incorporated the Penman-Monteith (P-M) model and the Shuttleworth-Wallace (S-W) model, along with machine learning (ML) models to simulate wolfberry ET under three cultivations: ridge-furrow planting with black plastic mulching (RM), flat planting with black plastic mulching (FM), and bare soil planting (CK). Our findings demonstrate the better performance of the physical models over ML models during the test period, with the S-W model exhibiting greater precision compared to the P-M model. Additionally, we identified soil moisture as the most influential factor in ML-based ET modeling. Using the S-W model, we further simulated ET components under future rainfall increase scenarios, indicating that RM treatment is projected to show a heightened transpiration fraction relative to CK treatment, thereby highlighting RM as a water-efficient cultivation method suitable for arid alpine croplands. [ABSTRACT FROM AUTHOR]

• Central Asia drought propagation time were longer early and late in the growing season. • Drought thresholds in Central and Western Central Asia were often below 30 mm during 1948–2022. • Soil moisture drought intensity was positively correlated with drought propagation characteristics. • VPD and AI are the main drivers of accelerated drought propagation. Drought propagation time (PT) and threshold (TR) play crucial roles in real-time monitoring of drought progression and severity under climate change, for which there is currently no unified method or standard for quantitative characterization. Central Asia (CA), a prototypical arid region, is frequently plagued by droughts that profoundly impact its ecology and socioeconomic framework, leaving a lack of comprehension about the transition from meteorological to soil moisture drought as for the complex impact of ground-atmosphere interaction. Therefore, this study revealed high-resolution PT and TR across CA based on precipitation and soil moisture datasets by employing a Bayesian causal framework for drought propagation modeling, in which the sliding window with the random forest method was integrated to investigate the dynamic changes and driving factors of drought propagation over recent decades. The conclusions drawn are as follows: (1) in the southeastern hilly and eastern plateau, a prolonged PT (i.e., longer than 100 days) was experienced during the extremities of the growing season, while most areas had a shorter mid-season PT (i.e., less than 40 days), in which the soil moisture drought intensity was positively correlated with longer PTs; (2) from 1948 to 2022, the central and western regions in CA generally displayed lower TR values than those in the northeast, seldom exceeding 30 mm, reflecting the regional precipitation gradient and the positive relationship between TR and severe soil moisture droughts; and (3) the increase in vapor pressure deficit (VPD), the decrease in aridity index (AI) for the reduced precipitation, and the considerable impact of vegetation transpiration on soil moisture consumption contributed to accelerated drought propagation. Overall, this study reveals the complex dynamics and mechanisms of drought propagation amid environmental changes, laying the foundation for innovative drought early warning systems and emergency management approaches in CA. [ABSTRACT FROM AUTHOR]

• Bidirectional dependency between 4 water resource types and vegetation was evaluated globally. • Bidirectional dependency between forest and water resources stronger than farmland/grassland. • 46.8 % area of the world existing bidirectional dependency between vegetation and water resources. • Climate types affecting bidirectional dependency between water resources and vegetation. Water resources and vegetation jointly affect almost every aspect of nature and society, such as geomorphology, biodiversity, local climate, settlement, and so on. However, our understanding of their dependency relation is incomplete, which is merely on the unidirectional impact of a single water resource on vegetation. Inversely, vegetation productivity could feed back water resources by directly affecting evapotranspiration and indirectly regulating precipitation. The bidirectional influencing mechanism between global water resources and vegetation productivity is still unknown. This study focused on revealing the bidirectional dependency relation between water resources and vegetation productivity using multi-source data and causality modeling. Our analysis showed that the unidirectional dependence of vegetation on water resources, the unidirectional dependence of water resources on vegetation, and their bidirectional dependence at the global scale accounted for 40.9 %, 12.4 %, and 46.8 %, respectively. Moreover, different types of water resources and vegetation perform varying degrees of bidirectional dependency. For instance, precipitation influences 64.9 % of the vegetation in a unidirectional way, while soil moisture, surface runoff, and groundwater interact with vegetation at the level of 74.6 %, 44.8 %, and 45.6 %, respectively. Similarly, the bidirectional dependency between forest (54.5 %) and water resources was usually higher than that of cultivated land (45.9 %) and grassland (44.5 %), due to different transpiration and water interception abilities. It has great significance on water resources management, vegetation greening, and understanding of terrestrial ecological water circulation systems in the context of global climate change by quantifying the interaction mechanism between various water resources and vegetation productivity in this study. [ABSTRACT FROM AUTHOR]

• We develop a fast physically-guided emulator of MATSIRO land surface model. • We evaluate the emulator performance at simulating key land surface quantities. • The emulator makes a tremendous improvement in computational speed. Current land surface models are useful tools to study the effects of global climate change on hydrological variables. However, these models tend to be relatively computationally expensive to run. This can hinder their widespread application in large ensemble modelling or uncertainty quantification studies. Therefore, it is necessary to build fast reduced-order emulators that approximate the dynamics of the original models. Here we build a fast physically based emulator that approximates the MATSIRO land surface model. The emulator equations are chosen based on review of the original MATSIRO equations, and on preliminary data analysis. The emulator uses minimal atmospheric input, and models snow water equivalent, wetland water storage, upper layer soil moisture, and total runoff on the daily time scale at 0.5° spatial resolution. Emulator parameters are optimized by fitting the emulator output to the original MATSIRO model. Parallelization allows lightning-fast computation of land surface evolution on the decadal scale. The emulator can work on the range of spatial scales, from local to regional to global. We validate simulated output with respect to the original MATSIRO model, and discuss global maps of parameter estimates. The emulator achieves excellent performance for snow water equivalent and wetland water storage. There are more challenges in simulating upper layer soil moisture and runoff, including systematic runoff underestimation over northern extratropics. We find that 25 years of training data are sufficient for reasonably fitting the emulator. The emulator can be further refined and coupled with river routing and/or economic models in future studies. [ABSTRACT FROM AUTHOR]

[Display omitted] • Coupling PT-JPL into DTVGM improved the hydrological simulation accuracy in UHRB. • Except for Pr, which had a high positive correlation with BW, other climatic factors correlated relatively weakly with BW and GW. • Vegetation showed a significant greening trend in UHRB, facilitating the transformation of BW to GW. • Vegetation greening will alter the original correlation between climatic factors and hydrological processes. The characteristics of water fluctuations within the basin have remained ambiguous in recent years due to climate and vegetation changes, posing a challenge to the planning and utilization of regional water resources. This study coupled the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, which can consider vegetation dynamics information and evapotranspiration physical mechanisms, into the Distributed Time Variant Gain Model (DTVGM) to improve the hydrological simulation accuracy under changing environments. Based on different simulation scenarios of the coupled model, the effects of climate and vegetation changes on hydrological processes were fully investigated using blue and green water (BW and GW) as assessment metrics. The upper Han River Basin (UHRB), as water source for the Central Line Project of China's South-North Water Diversion (CSNWD), was selected as a typical basin for the study, results indicated that: (1) The DTVGM coupled with PT-JPL could better reflect the spatiotemporal patterns of major hydrological processes (runoff, evapotranspiration, and soil moisture) in UHRB from 2001 to 2019; (2) The BW in UHRB exhibited decreasing trend from 2001 to 2019, while the GW on the contrary. Surface runoff (Rs), vegetation transpiration (Et), and soil moisture (W) contributed most in the components of BW and GW; (3) Vegetation change dominated by greening in UHRB, which facilitated the transformation of BW to GW in the basin, and it increased the proportion of GW mainly by promoting Et. BW was mainly influenced by precipitation, but vegetation change altered the original correlation between climatic factors and hydrological processes. This study can support the management of water resources in the basin under changing environments. [ABSTRACT FROM AUTHOR]

• Seasonal water uptake differed among different tree species. • Deep-rooted tree species had lower growth resistance to drought. • Shallow-rooted tree species was more adaptative to seasonal precipitation areas. • The root structure and deep soil water availability were the key factors influencing the drought resistance of trees. Understanding the water use patterns of different tree species and their adaptability to drought is urgently needed due to global warming. In this study, we investigated the seasonal water uptake patterns of Pinus tabulaeformis and Picea wilsonii on the eastern Tibetan Plateau using stable isotope methods. In addition, tree ring width data was used to evaluate the radial growth resistance of the two species to drought in 2022. The focus was on identifying species differences in water uptake patterns during drought spells and radial growth resistance to drought. The results showed that although Pinus tabulaeformis could increase water uptake from deeper soil layers during drought spells, the radial growth resistance to drought was significantly lower (p < 0.001) than that of Picea wilsonii due to the limited water content in the deep soil layers. In contrast, Picea wilsonii had higher resistance and adaptations to drought based on rapid access to water resources from seasonal precipitation with denser fine roots. Overall, shifting water sources to deeper soils during drought spells was not always effective in alleviating drought stress, but the root structure and deep soil water availability were the key factors influencing the drought resistance of trees. The findings had significant implications for decision-making on the species suitability of plantation projects under future climatic change. [ABSTRACT FROM AUTHOR]

• Most of the Euro-Mediterranean region affected by drought conditions during 2021/22. • Recursive high-pressure systems & a poleward jet shift explain rainfall deficits. • Most severe drought since at least 1891 when considering evaporative demand (AED) • Enhanced AED caused unprecedented low soil moisture & runoff since at least 1965. • Potential worst-case droughts if historic rainfall deficits occur with current AED. The Euro-Mediterranean region experienced a remarkable drought during the hydrological year 2021/22. Substantial and widespread impacts on water supply systems, agricultural crops, and the production of hydroelectric power were observed. This assessment characterises the drought from a long-term perspective using a multi-index approach and analyses the associated atmospheric circulation at the annual and monthly time scales. The main dynamical forcing of the drought was the unusual recurrence of high-pressure systems over western Europe, at least partly due to an anomalous southward shift in blocking activity and a remarkable occurrence of low-latitude blocks. This led to record-breaking positive geopotential height anomalies over western Europe and a poleward displacement of the North Atlantic eddy-driven jet. Although most of the region was affected by mild drought conditions, the 2021/22 event was not unprecedented in terms of precipitation deficits since other periods of the 20th century (e.g., in the 1920s, 1940s and 1970s) displayed moderate and severe drought conditions over larger areas. However, the 2021/22 drought has been the most intense since at least 1891 because of high atmospheric evaporative demand (AED) values associated with extreme temperatures, especially during the summer of 2022. This enhanced AED also contributed to depleting soil moisture and reducing runoff generation, leading to unprecedented deficits since at least 1965. Finally, we find important differences in the 2021/22 event as compared to other major historical droughts over the Euro-Mediterranean region. In particular, the contrasting effect of AED evidences its increasing role over the last decades and warns about the current risk of experiencing unprecedented droughts. [ABSTRACT FROM AUTHOR]

• A time-varying copula-based approach was proposed to uncover the potential regimes between antecedent drought and hot extremes. • Drier antecedent soil moisture condition would trigger a higher risk of ET. • Incorporation of trend-caused nonstationarity and tail monotonicity helps identify the temporal variations of driving mechanism. Hot extremes may adversely impact human health and agricultural production. Owing to anthropogenic and climate changes, the close and dynamic interaction between drought and hot extremes in most areas of China need to be revisited from the perspective of nonstationarity. This study therefore proposes a time-varying Copula-based model to describe the nonstationary dependence structure of summer extreme temperature (SET) and antecedent soil moisture condition to quantify the dynamic risk of hot extremes conditioned on dry/wet condition. A general statistical inspection procedure which was composed of maximum likelihood (ML)-based estimation, nonstationary Goodness-of-fit (GOF) tests, the log likelihood ratio (LR) tests and minimum corrected Akaike information criterion-based selection was promoted to select the best-fitted nonstationary models efficiently. This study proposed a new approach to identify the soil moisture driving law over extreme temperature from the point view of tail monotonicity and nonstationary risk assessment. Owing to the LTI-RTD (left tail increasing and right tail decreasing) tail monotonicity for dependence structure of these two extremes derived from most areas, two kinds of the driving laws of soil moisture over SET were detected. Because of the spatiotemporal divergence of sensitivity index derived from tail monotonicity (SITM), we can conclude that the spatial and temporal heterogeneity of response degree of ET over the variations of antecedent dry/wet conditions is evident. Incorporation of nonstationarity and tail monotonicity helps identify the changes of driving mechanism (laws) between soil moisture and hot extremes. [ABSTRACT FROM AUTHOR]

• Changes in both soil moisture and extreme rainfall influence historical flood trends. • The influence of soil moisture and extreme rainfall depends on flood severity. • The more extreme a flood event is, the less dependent it is on soil moisture changes. • Changes in soil moisture need to be considered in projections of flooding. Despite the expectation that increases in rainfall with climatic change will result in increases in pluvial flooding, there is more historical evidence for decreases in flood magnitude. In Australia, as in many other parts of the world, flood magnitudes are mostly decreasing, despite increasing rainfall extremes. Here, we show how changes in soil moisture have led to decreasing flood magnitudes while rainfall extremes have been increasing. Using gauged streamflow, catchment average rainfall, and modelled soil moisture data across Australia we confirm that streamflow peaks (or floods) that occur at least once a year are strongly related to both the peak rainfall causing the flood and the antecedent soil moisture conditions preceding the storm event. Regions where the magnitude of the peak flow has decreased are visually and statistically correlated to regions of decreasing soil moisture. Flood magnitudes are more likely to increase only for the rarest events, with increases in rainfall offset by decreases in soil moisture for more frequent events. A recurrence interval dependent tipping point is identified beyond which trends in catchment rainfall outweigh those of soil moisture trends and dominate the flood response. For regions where soil moisture has decreased, this tipping point occurs at an average recurrence interval of ten years or more. As most studies investigating trends in flooding generally use annual maxima, changes in soil moisture are likely to be the dominant mechanism behind observed flood trends. Hence changes in soil moisture conditions need to be considered when predicting catchment flood response due to climatic change. [ABSTRACT FROM AUTHOR]

• Enough water to the sites despite urban surroundings and different water regimes. • Groundwater contributes 30–40% of the total transpiration during the driest periods. • Transpiration is 3–16% of total daily transpiration during night-time heat stress. During the expansion of urban areas, small natural reserves have often been left intact within the built environment as central elements of biodiversity conservation, ecological connectivity, landscape sustainability, and quality of life of urban dwellers. Consequently, the surrounding urbanized landscape may impact the environmental conditions of these reserves (e.g., high temperatures, low moisture conditions), resulting in the need for extensive maintenance. This study presents an estimation of the water balance over two years (2017–2018) in three small urban reserves (between 2 and 30 ha) within the Greater Melbourne metropolitan area in Australia, for the purpose of understanding tree water use. Measurements of micrometeorological variables, soil moisture content profiles, water-table levels, sap flow velocities, and stem diameter variations were used to quantify the water sources of tree transpiration in these reserves. Results revealed that, despite the urban surroundings and the climate variations, these reserves have enough water to sustain tree transpiration. In two of the three reserves, groundwater was pivotal in sustaining transpiration rates; specifically, groundwater was estimated to contribute about 30–40% of the total transpiration amount during the driest periods of the year. Groundwater also played an essential role during nights with temperatures above 25 °C, helping trees to maintain night-time water use from 3 to 16% of the daily water use. In the third reserve, the presence of a shallow layer of heavy clay supplied water to the trees, which were able to maintain relatively constant transpiration rates throughout the year. These results demonstrate the importance of understanding the water regime of each urban reserve in order to support government authorities in preserving these ecosystems. [ABSTRACT FROM AUTHOR]

• Hydrologic impacts of climate change assessed in Manning River basin using XAJ model. • XAJ model performs satisfactorily with R2 and NSE more than 0.94 and 0.92. • Runoff is projected to increase in summer and decrease in winter. • Projected changes in water availability are largely dominated by change in rainfall. Hydrological responses of catchments to climate change require detailed examination to ensure sustainable management of both water resources and natural ecosystems. This study evaluated the impacts of climate change on water resource availability of a catchment in eastern Australia (i.e. the Manning River catchment) and analyzed climate-hydrology relationships. For this evaluation, the Xinanjiang (XAJ) model was used and validated to simulate monthly rainfall-runoff relationships of the catchment. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP8.5 scenarios were used to assess the impacts of climate changes on the Manning River catchment. Our results showed that the XAJ model was able to reproduce observed monthly rainfall-runoff relationships with an R2 ≥ 0.94 and a Nash-Sutcliffe Efficiency ≥ 0.92. The median estimates from the ensemble of downscaled GCM projections showed a slight decrease in annual rainfall and runoff for the period 2021–2060 and an increase for the period 2061–2100. Annual actual evapotranspiration was projected to increase slightly, while annual soil moisture content was predicted to decrease in the future. Our results also demonstrated that future changes in seasonal and annual runoff, actual evapotranspiration and soil moisture are largely dominated by changes in rainfall, with a smaller influence arising from changes in temperature. An increase in the values of high runoffs and a decrease in the values of low runoffs predicted from the ensemble of the 28 GCMs suggest increased variability of water resources at monthly and seasonal time-scales in the future. A trend of decreasing values in winter runoff and soil moisture content in the future is likely to aggravate possible future reductions in water availability in eastern Australia. These results contribute to the development of adaptive strategies and future policy options for the sustainable management of water resources in eastern Australia. [ABSTRACT FROM AUTHOR]

Highlights • Land use scenario in 2020 is predicted based on CA-Markov. • Forestland would increase significantly for afforestation in 2020. • Future runoff during 2020–2030 may increase due to climate change. • Land use/land cover change may lead to a slightly decrease in runoff. • Simulated lateral flow accounts for a larger proportion and determines runoff change. Abstract The Luanhe River basin, the mostly afforested river basin in North China, has exhibited significant land use/land cover change (LUCC) under climate change that could jointly affect water availability of the basin in the future. This study examines both impacts of LUCC and climate change on runoff over the upper reaches of the Luanhe River basin. First, the land use in 2020 is predicted based on the Cellular Automata-Markov (CA-Markov). Second, a hydrological model (Soil Water Assessment Tools, SWAT) is set up for the baseline period 1961–1979 and driven primarily by outputs from five general circulation models (GCMs) under four representative concentration pathways (RCPs) (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) for the period 2020–2030. Results show that the ensemble mean annual precipitation may increase under four RCPs for the period 2020–2030, with the maximum (470 mm/yr) and minimum (444 mm/yr) for RCP8.5 and RCP6.0, respectively, 1–7% higher than the observed mean annual precipitation (441 mm/yr) during 1961–1979. The relationship between the runoff simulations and the RCPs under the 2020 land use scenario is nonlinear, with the maximum (57 mm/yr) and minimum (50 mm/yr) mean annual runoff depths under the RCP4.5 and RCP6.0 scenarios, respectively, ∼58% and ∼39% higher than the mean annual observed runoff depth (36 mm/yr) for the baseline period. The increase in forestland (∼56%) and decrease in agriculture land (∼−30%) are remarkable for the period 1970–2020, driven primarily by afforestation implemented in the Luanhe River basin. LUCC would lead to a slight decrease in mean annual runoff, and the runoff only increases in summer but decreases in other three seasons. The decrease in surface runoff and groundwater discharge jointly results in the overall decrease in runoff due to LUCC. In general, the climate change impact will dominate runoff change for the study basin, though marked afforestation has taken place and is likely to continue in the future. [ABSTRACT FROM AUTHOR]

Highlights • CRNPs were used in 3 different soil textures and compared with buried SWC sensors. • CRNPs estimate SWC in three soil textures with RMSE is 0.05, 0.10, 0.03 respectively. • Silt loam dam plot had the highest rates of change but held more water than others. Abstract The cosmic-ray neutron probe (CRNP) is a new tool for continuously monitoring mean soil–water content (SWC) on a hectometer scale, but the performance of CRNPs in highly heterogeneous distributions of SWC, vegetation and especially soil texture caused by the broken surface on the Loess Plateau in China remains uncertain. The study evaluated the application and accuracy of the method for three soil textures in a small watershed on the plateau to provide a reference and scientific basis for its application. Three CRNPs were installed in a loamy sand hills (LSH) plot, a silty loam dam (SLD) plot, and a sandy loam slope (SLS) plot, soil moisture sensors were buried at various depths in three plots. The footprints of the CRNPs for SWC observation had radii of 127–170, 126–174 and 148–174 m in SLD, SLS and LSH, respectively, and the mean measuring depth was about 20 cm for SLD and SLS and 40 cm for LSH based on general calculation equations. The accuracy of the CRNP method was high when validated using oven-dried method (RMSE = 0.068 cm3 cm−3). The mean SWCs estimated from the other types of sensors were consistent with the mean SWCs from the CRNP probes in the three plots. The coefficient of determination of the linear relationship was in the order: SLS > LSH > SLD. The coefficient of variations (CV) were higher in LSH than SLD and SLS, indicating that SWC varied most in LSH. During periods of rain, the variations were larger for SLD than SLS and LSH, with a CV of 32.2%. The CRNP for SLD had the highest rates of change during periods with and without rain for both increasing and decreasing SWC, but this plot held more water than LSH and SLS, consistent with the high clay and organic-matter contents in SLD. The rates of change were significantly correlated with the antecedent SWCs (P < 0.01), and the higher the antecedent SWC, the faster the rate of change for each plot. This study verified the application of the CRNP for monitoring field-average SWC of the broken surface on the Loess Plateau and represents a new approach for the study of the spatial distribution of SWC on the plateau. CRNP can measure SWC of the complex underlying surface accurately, so as to provide a more reliable assessment of the impacts of landscapes and vegetation changes, such as conversion of cropland to forest and grassland on the Loess Plateau on water resources. [ABSTRACT FROM AUTHOR]

• Globally, RZSM showed a decreasing trend over 1981–2017. • RZSM over 50% of global land areas decreased. • Globally, decreased RZSM was mainly induced by the rising temperature. Root zone soil moisture (RZSM) has a direct impact on ecosystem function, vegetation growth and food security, and plays a vital role in global climate system, water and carbon cycles. However, large variations and uncertainties still exist in RZSM across the globe under the warming climate. In this study, we applied comparison map profile (CMP), Theil-Sen regression and partial correlation analysis to investigate the spatial and temporal changes of RZMS and its driving factors from 1981 to 2017 by using three soil moisture products–ERA5, GLDAS and MERRA-2. Results showed that RZSM derived from three products presented a similar spatial pattern that the highest RZSM values occurred in tropical forest and cold areas, followed by subtropical, while the relatively low RZSM values were observed in arid and semiarid regions. Globally, RZSM decreased in all of three datasets with a rate of −0.14 × 10-3 m3 m−3 yr−1 on average (p < 0.001), which was largely correlated with temperature anomalies. Spatially, the RZSM trends greatly varied, with 21–31% of global land areas experiencing a significant decreasing trend and 7–24% for an increasing trend, respectively, confirming their different sensitivities to climate change. Temperature-driven RZSM dominated 19–29% of global land areas and was primarily distributed in northern high-latitude areas. The areas dominated by evapotranspiration were mainly in arid and semiarid areas, accounting for 29–44% of global land areas. Precipitation dominates the remaining 36–45% of global land areas mainly in eastern America and Europe, suggesting variations in the dominance of environmental factors on the spatial patterns of RZSM trend. Our findings will deepen our understanding of the impacts of climate change on the long-term trend of global soil moisture, and will be greatly critical to global soil water resource protection and management under the warming climate. [ABSTRACT FROM AUTHOR]

• OpenKarHydro with multilayer soil water interactions was proposed. • OpenKarHydro reveals how climate and land use affect water budget and cause dry soil. • OpenKarHydro performs well in simulating the soil water content and runoff dynamics. • OpenKarHydro is a useful tool for land use optimization and controlling dry soil. In water-limited areas, soil water content (SWC) is a critical factor for plant growth and ecosystem stability. To understand the long-term effects of three different land uses (Vigna radiata : VR, Stipa bungeana : SB, and Medicago sativa : MS) and two climate scenarios (representative concentration pathway 4.5 (RCP45) and nonclimate change (Non_CC)) on water budgets and the mechanisms of dried soil layer (DSL) formation, a new complete multilayered model, OpenKarHydro, was developed. The results showed that the model adequately captured the water budget for different land uses, with root mean square errors (RMSEs) of 0.058, 0.046, and 0.046 and coefficients of determination (R2) of 0.615, 0.605, and 0.582, respectively, for SWC dynamics. This model performance was also demonstrated by the verification of runoff. Sensitivity analysis indicated that the soil porosity (n) was the most sensitive parameter in all land uses. The DSL was primarily caused by higher evapotranspiration (VR: 83.16% vs. 82.48%, SB: 80.62% vs. 77.69%, and MS: 79.93% vs. 76.26%) and canopy interception (VR: 11.92% vs. 11.99%, SB: 17.56% vs. 23.15% and MS: 22.60% vs. 26.19%) in the Non_CC climate pattern than in the RCP45 climate pattern. Climate change has caused an increase in evapotranspiration and interception for all land uses, reducing bottom leakage. Rainfall is sufficient to meet the water demand in the VR plot regardless of climate change; however, the additional water consumption caused by climate warming cannot be offset by the increased rainfall for the SB and MS plots. Compared to Non_CC, RCP45 resulted in increases of 0%, 54.19%, and 57.62% in proportion with extreme drought and decreases of 4.70%, 38.74%, and 5.24% in proportion with no drought for the soil profiles of VR, SB, and MS, respectively. For MS, RCP45 (2026) caused the DSL to penetrate the soil profile (>400 cm) 4 years earlier than in the Non_CC (2030), which should take no more than 5 and 9 years, respectively. OpenKarHydro is a useful tool for optimal water resource management and ecological restoration in water-limited areas. [ABSTRACT FROM AUTHOR]

• The first study to comprehensively analyze and compare the long-term variations of global surface soil moisture among multiple datasets. • Pervasive surface soil moisture drying is found across the globe, especially in humid-arid transitional regions, in most datasets. • Warming plays a primary role in global surface soil moisture drying in most datasets, especially GLEAM. Accurate soil moisture datasets are essential to understand the impacts of climate change. However, few studies have evaluated the consistency and drivers of long-term trends in soil moisture among different dataset types (satellite, assimilation, reanalysis, and climate model) at the global scale. Here we analyze the spatio-temporal variations of global surface soil moisture and associated climate dynamics over 1980–2020 using multiple soil moisture datasets, i.e., multi-satellite assimilated remote sensing datasets (ESA CCI), simulated soil moisture based on LSMs (GLDAS, GLEAM, CMIP6), and reanalysis (ECMWF ERA5, MERRA2, CRA-Land). Most of these datasets indicate pervasive drying of global surface soil moisture over the last four decades. Prominent soil moisture drying is detected in North America, Europe, northeastern Asia, North Africa, and the Arabian Peninsula. The cross-correlations among the five synthetic soil moisture datasets are the highest between GLEAM and the reanalysis datasets. Using the Aridity Index (AI, the ratio between annual total precipitation and potential evapotranspiration), we find that soil moisture drying is the most intensive in the humid-arid transitional regions with AI ranging 0.8–1.2. Surface soil moisture drying is primarily driven by increases in temperature, followed by ENSO, as indicated by Maximum Covariance Analysis (MCA). However, the significance of the impact of ENSO on soil moisture variability is sensitive to the choice of soil moisture dataset used in the MCA. [ABSTRACT FROM AUTHOR]

• Established a precipitation manipulation experiment under a plantation (∼ 4000 m2). • Investigated DSLs response to precipitation gradients in the 21-m soil profiles. • Rainfall accession alleviated mean DSLFD (1.8 m compared with interception's 1 m). • Mean DSL-SWC responsed greater under the PAT (0.2%–0.9%) than under the PIT (0.1%–0.3%). • Increased rainfall in turn exacerbated DSLs during the transition period. Ongoing climate change alters the amount and frequency of precipitation, deteriorating the water status of soils and the ecosystem services that they provide. The decline of soil water formed the dried soil layers (DSLs), which is particularly relevant for dryland ecosystems like the forests planted on the Chinese Loess Plateau (CLP), because there is an increased water demand for vegetation transpiration. To assess the impacts of precipitation changes on DSLs, we conducted a large throughfall manipulation experiment comprising seven precipitation gradients, ranging from 30%, 50%, and 65% precipitation interception treatments (PIT) to the ambient condition and then to 30%, 50% and 65% precipitation accession treatments (PAT), under a Robinia pseudoacacia planting forest on the CLP. We measured changes in soil water content (SWC) and examined the development of DSLs for over a year. We found that: (1) mean SWC in the 0–2100 cm soil profile and in DSLs decreased by 0.44%–0.77% and 0.13%–0.36% under the PIT, respectively, while increasing by 0.13%–0.36% and 0.16%–0.92% under the PAT, respectively; (2) DSLs were observed c. 100 cm and c. 100–180 cm below the soil surface under the PIT and PAT, respectively; (3) DSLs varied seasonally, with the largest reduction occurring during the transition period between the dry and rainy seasons, while the reduction developed more rapidly under the PAT than the PIT; (4) the incremental rate of SWC in DSLs increased linearly (p < 0.05) with increasing precipitation, while the increase was faster when precipitation was above (PAT) than below the ambient conditions (PIT), indicating greater precipitation sensitivity of DSLs under enriched than limited water supply. These changes in DSLs provide experimental evidence for the effects of climate change on soil water, and may have strong effect on the sustainable development management of drylands. [ABSTRACT FROM AUTHOR]

• Soil moisture, GWSC, and TWSC in the YRB increased during 2003 to 2019. • A new weighted GRACE drought standardisation index (WGDSI) was reconstructed. • The interannual variability was beneficial for detecting drought in the YRB. • The recovery times were 30 and 39 months in 2006 and 2011 droughts in the YRB. • Different signal spectrums components of TWSC are useful for drought monitoring. With the intensification of global climate change, droughts have frequently been occurring in the Yangtze River Basin (YRB), significantly affecting the production patterns, lives, and socioeconomic development of humans. Drought characteristics must be comprehensively identified and quantified to reduce the damage caused by droughts in the YRB. The spatiotemporal variability of precipitation, runoff, soil moisture, groundwater change (GWSC) and terrestrial water storage change (TWSC) in the YRB was comprehensively estimated using the Gravity Recovery and Climate Experiment (GRACE), hydrological and in situ observations by decomposing the variabilities into seasonal, sub-seasonal, trend, and interannual. The new weighted GRACE drought standardized index (WGDSI) and weighted groundwater standardized index (WGWSI) were reconstructed by weighing the seasonal, trend, interannual and sub-seasonal of TWSC and GWSC. They were compared with the standardized soil moisture index (SSI06), standardized precipitation index (SPI06), and standardized runoff index (SRI06). Additionally, the drought characteristics identified based on the observations of the water storage deficit, severity, peak, duration, and recovery time in the YRB were also quantified using the WGDSI/WGWSI over the YRB. The results indicated that soil moisture, TWSC, and GWSC in the YRB increased from 2003 to 2019, mainly based on seasonal and interannual signals. The correlation coefficients between the WGDSI and the SSI06, SPI06, and SRI06 at the monthly were 0.84, 0.56, and 0.75, respectively, representing increases of 9 %, 14 %, and 21 % compared to that with the unweighted GRACE drought standardized index, respectively. The interannual variability of the hydrologic variables was more consistent with the drought events in the YRB, which was beneficial for detecting droughts. Two severe serious droughts occurred in the YRB from 2003 to 2019. In 2006, a continuous seven-month-long drought occurred, with a peak at − 28.974 km3, a severity of − 174.767 km3∙month, an average drought recovery rate of 0.83 km3/month, and a recovery time of 30 months, while in 2011, a continuous five-month-long drought occurred, with a peak at − 18.384 km3, a severity of − 78.106 km3∙month, an average drought recovery rate of 0.40 km3/month, and a recovery time of 39 months. The results indicated that the WGDSI could effectively identify drought events and measure their severity accurately, offering a more holistic understanding of drought conditions compared to other available indices. The index proposed in this study can be applied to generate new datasets and methods for quantifying and detecting droughts on a global scale. [ABSTRACT FROM AUTHOR]

• Rainfall losses are a key input to event-based flood models widely used in practice. • Relationship between rainfall losses and antecedent soil moisture are quantified. • Climate change projections of soil moisture are used to project rainfall losses. • Both the magnitude and variance of future rainfall losses are projected to increase. • Climate change will affect rainfall losses and hence flood responses. Climate change is expected to impact the severity and frequency of floods, which has implications for flood risk management. Design floods and derived flood frequency curves obtained using event-based rainfall-runoff models are widely used in industry to assess flood risks for planning and design purposes. For these approaches it is necessary to have (a) rainfall inputs, and (b) rainfall losses specified, the latter representing the amount of rainfall that is either intercepted, stored on the surface, or infiltrated into the soil and does not contribute to the flood hydrograph. There is extensive research on changes in flooding under climate change that focus on projections of rainfall. However, there is little research into projections of rainfall losses under climate change, despite the knowledge that their changes will modulate the flood response. Here, we present one of the first studies seeking to quantify how rainfall losses, as represented by estimates of initial and continuing losses used in event-based models, are projected to change under climate change. We identify dependencies between rainfall losses and antecedent soil moisture in around half (over 200) of the largely unregulated catchments (i.e. watersheds) in Australia analysed in this study and use these relationships to project rainfall losses under climate change. Near universal increases in both the mean and variance of both initial losses and continuing losses are projected in these catchments, suggesting that increased rainfall losses could offset the impact of increased rainfalls for frequently occurring floods and result in an increased variance in flood responses. [ABSTRACT FROM AUTHOR]

Highlights • Hydrological Models and GCMs were used to simulate runoff in the selected Basin. • The daily scale factors performed better than monthly scale factors. • Findings showed multiple models should be employed to best simulate actual runoff. • Multiple models are necessary for management of water resources in the basin. Abstract The Songhua River Basin (SRB) plays a vital role in supplying water resources to northeast China. This river has a substantial effect on agricultural grain producing region. Therefore, the current study was carried out to evaluate the performances of multiple hydrological models driven by bias corrected precipitation estimates from a group of General Circulation Models (GCMs). The variations in discharge obtained from multiple hydrological models were also analyzed. For this purpose, bias correction methods for GCMs and five hydrological models, lumped rainfall runoff (Nedbor Afstromnings Model (NAM), GRJ4), semi-distributed (the Water Evaluation and Planning tool (WEAP), HBV), and the distributed (Soil Water Assessment Tool (SWAT)) were used in the SRB. Before applying the bias correction method, raw GCMs were also plotted against observational data. The results revealed that none of GCM performed well against observational data. The results also showed that quantile mapping method corrects the biases of GCMs better than daily and monthly scale factors. Distributed and semi-distributed hydrological models performed better than lumped rainfall runoff models in the selected study area of SRB. By forcing hydrological models with bias corrected precipitation data, the differences in the simulated discharge by SWAT, HBV, NAM, GR4J and WEAP were −3%, −2%, −4%, −7 and +3, respectively, when compared with observed discharge. The results also show that the overall performance of SWAT, HBV, NAM, and WEAP was better than GRJ4. The results also suggest that the application of multiple hydrological models is necessary to make improvements in the planning and management of agricultural and water resources in the SRB region. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A particle detachment rate equation with delay due to salinity variation. • Detachment rate equation with instant mobilisation due to velocity change. • Semi-analytical solution is derived. • Determination of the model coefficients from laboratory corefloods. • Using obtained coefficients for well injectivity decline prediction. Abstract Colloidal-suspension flows in porous media occur in numerous areas of environmental, chemical and petroleum engineering. The main processes are capture and detachment of particles, yielding permeability decline. We developed a governing system of transport equations with particle detachment kinetics, where the detachment by high velocities is instant, due to flow incompressibility, and the detachment by decreasing the fluid salinity is delayed, due to micro-scale diffusion. The system allows for a semi-analytical solution for axi-symmetric low-salinity water injection with fines migration. The model exhibits instant fines mobilization at the beginning of injection by drag force, fines release with delay behind the salinity front by electrostatic force, and the interaction of two concentration waves. The model can be used for laboratory-based injectivity decline prediction during injection of water in aquifers and oilfields, where the injected and formation water compositions are different, and also for fines-migration during drilling fluid invasion. [ABSTRACT FROM AUTHOR]

Highlights • Modification of equivalent cross-section approach for catchment modelling. • Comparison of semi-distributed and lumped conceptual modelling. • Reduction of computational units in distributed hydrological modelling. • Analysis of impact of climate and land use on soil moisture dynamics. Abstract Physically based distributed hydrological models are useful for simulating the spatial distribution of hydrologic fluxes across the catchment under various climate and land cover change scenarios. However, complexities associated with their implementation at large scales make their applications limited. Previously, an equivalent cross-section (ECS) based distributed hydrological modelling approach was developed for first order sub-basins to reduce the computational time/effort. Here, the ECS approach is modified for semi-distributed hydrological modelling at the catchment scale. The modelling approach is implemented for a 314 km2 McLaughlin catchment located in south-eastern New South Wales (NSW), Australia that consists of 822 first order sub-basins. A 26 year long streamflow record simulated using an ECS based modelling approach are compared against daily observed streamflow and four calibrated lumped conceptual hydrologic models, and found to be consistent. Further, the simulated actual evapotranspiration and soil moisture from the ECS approach are compared against the Australian Water Availability Project (AWAP) model simulations and results found to be consistent. In addition, the temporal dynamics of simulated soil moisture from the ECS approach is consistent with the satellite derived European Space Agency Climate Change Initiative (ESA CCI) surface soil moisture data. In the ECS based semi-distributed modelling, all parameters are derived from the actual topographic and physiographic information of the catchment and none of the parameters is calibrated. Therefore, this approach has the advantage of simulating streamflow in ungauged catchments compared to lumped conceptual models. The impact of spatially distributed climatic forcing and land cover on soil moisture is investigated across four landforms (upslope, midslope, footslope and alluvial-flats) and at various soil depths. Our results show increase of mean soil moisture in shallow layers of upslope toward alluvial-flats. However, mean soil moisture in deeper horizons remained almost constant across all landforms. The variability of daily soil moisture at surface soil layers is higher than the deeper soil layers for all landforms. Our results illustrated that disaggregation of a catchment to a series of ECS at the scale of first order sub-basins, captures dynamics of soil moisture and actual evapotranspiration across the landscape and results are consistent with the climatology, land cover type, topography and soil hydraulic properties. Further, the use of ECS approach in the McLaughlin catchment reduced the number of computational units by 40 times in comparison to 3-d grid based distributed modelling setup. [ABSTRACT FROM AUTHOR]

Highlights • A non-parametric evolutionary algorithm for root zone soil moisture dynamics. • Validated the new approach in different hydro-climates, Illinois and Oklahoma. • Alternative for forecasting root zone soil moisture using climate change scenarios. • Soil moisture predictions at shallow depth have more uncertainties. Abstract Prediction of soil moisture is critical for water resources management. With Global Precipitation Measurement (GPM) and Soil Moisture Active Passive (SMAP) satellites by NASA, spatio-temporal interrelation between rainfall and soil moisture fields (at different extents) will be of great value for satellite product calibration/validation and other hydrologic science investigations. In this study, we explored a non-parametric evolutionary algorithm for prediction of soil moisture from a time series of spatially-distributed rainfall across multiple weather locations under two different hydro-climatic regions. A new genetic algorithm-based hidden Markov model (HMMGA) was developed to estimate long-term soil moisture dynamics at different soil depths using precipitation data as a proxy. Also, we tested transposability of our approach across time under different climatic conditions. To test the new approach, we selected two different soil moisture fields, Oklahoma (130 km × 130 km) and Illinois (300 km × 500 km), during 1995–2009 and 1994–2010, respectively. We found that the newly developed framework performed well in predicting soil moisture dynamics at different spatial extents. Although our approach has limitations in predicting daily values, it estimates well the weekly soil moisture across the spatial and temporal domains with predictable uncertainties. Furthermore, this approach could provide advantages for good transposability under different weather conditions compared to those of physically-based hydrological models. Overall, our suggested approach could predict weekly soil moisture estimates with precipitation and soil moisture histories and showed the potential of transposability under different weather and land surface conditions. Since the proposed algorithm requires only precipitation (and historical soil moisture data) from existing, established weather stations, it can serve an attractive alternative that can forecast soil moisture using climate change scenarios. [ABSTRACT FROM AUTHOR]

Highlights • We propose a Lattice Boltzmann model to solve 2D fractional advection-dispersion equation. • The model is verified against the analytical solution of a benchmark problem. • We apply the model to simulate Cl− movement in a tracer experiment. • We discuss the pros and cons of the model in comparison with other numerical models. Abstract Natural soils and aquifers are inherently heterogenous and chemical transport through them is anomalous characterized by an early arrival followed by a persistent tail. How to describe such anomalous phenomena has been an interest and, as a result, a number of approaches have been proposed over the past few decades. Among others, the fractional advection-dispersion equation (FADE) is a model able to describe anomalous transport when the dispersion is regional rather than local as presumed in the classical advection-dispersion equation. Practical application of FADE needs numerical solutions, which is challenging because its spatial discretization gives rise to a full coefficient matrix. In this paper, we propose a Lattice Boltzmann model to solve the two-dimensional FADE. Given that the anomalous dispersion in soils and aquifers is hydrodynamic and caused by spatial variation in water velocity across the pore space and that the chemical plume spreads preferentially along the mean water-flow direction, the dispersion coefficient and the order of the fractional derivative should be both anisotropic. The anisotropies are solved by the two-relaxation time Lattice Boltzmann model using different relaxation parameters in different directions. Compared with existing numerical methods for the FADE, the proposed model has advantages that it is explicit, second-order accurate in both time and space, mass-conservative, and free of numerical dispersion; its stability is independent of dispersion coefficient. We verify the model against the analytical solution of a benchmark problem and then apply it to simulate Cl− movement in a tracer experiment conducted on an up-catchment hillslope. The results show that the FADE with backward skewness can reproduce the breakthrough curves measured from the experiment. [ABSTRACT FROM AUTHOR]

Highlights • Different data worth indices are investigated for nonlinear soil water flow. • Data worth analysis for soil moisture retrieval is more difficult than that for parameter estimation. • More prior data can improve data worth analysis but cannot compensate the model structural error. • The large data worth of shallow soil moisture observation may not exist for covariance- and mean-covariance-type indices. • Small measurement error does not always lead to improved data worth estimation. Abstract Given the high cost of data acquisition in soil water problems, it is becoming increasingly essential to collect the measurements as cost-efficient as possible. By introducing the data-worth analysis framework coupled with Ensemble Kalman Filter (EnKF), this real-world case study attempts to assess the worth of potential soil moisture observations before data collection. A field experiment was implemented to demonstrate the feasibility of quantifying the effect of future data on uncertainty reduction under real circumstances in a sequential way. The data worth of future observations is defined regarding soil hydraulic parameter estimation or soil moisture profile retrieval. Four information measures, including the trace (T r), Shannon entropy difference (SD) , relative entropy (RE) and degrees of freedom for signal (DFS), are introduced to quantify the information content. The sequential data worth analysis framework is examined by a number of cases, including under different irrigation intensities, with different prior data (existing observations that have already been collected), and with data of various depths and different measurement errors. We demonstrated the ability, and the challenge as well, of quantifying the data worth sequentially. Our results showed that data worth assessment regarding soil moisture profile retrieval is more difficult than that regarding parameter identification. Variance-type and covariance-type metrics have relatively loose accuracy requirement on potential observations (future possible observations to be collected), while mean-covariance-type metrics require higher accuracy. The vertical covariance of soil moisture is susceptible to the effect of atmospheric boundary condition, which eventually imposes a challenge on the quantification of data worth with covariance involved indices. The match between the expected and reference data worth can be improved by assimilating more prior data. However, more prior data cannot compensate for the damage from possible model structural error due to the changed scenarios between the prior stage and the posterior or preposterior stage. Shallow soil moisture data generally has larger data worth than deep observations in our study, but evaluating data worth with shallow data is subject to considerable uncertainty if covariance-type or mean-covariance-type index is employed. Smaller measurement error does not always lead to improved data worth estimation. [ABSTRACT FROM AUTHOR]

Highlights • A nonstationary HMM model is employed to spatially downscale the soil moisture data. • Rainfall predictor plays a substantial role in achieving the overall predictability. • Climate data are effective in picking up the predictability of local soil moisture. • The proposed model preserves the spatial coherence across stations reasonably well. Abstract A multivariate stochastic soil moisture (SM) estimation approach based on a Gaussian-mixture nonstationary hidden Markov model (GM-NHMM) is introduced in this study to spatially disaggregate the AMSR2 SM data for multiple locations in the Yongdam dam watershed in South Korea. Rainfall and air temperature are considered as additional predictors in the proposed modeling framework. In GM-NHMM, a six-state model is constructed with three predictors representing an unobserved state associated with SM. It is clearly seen that the rainfall predictor plays a substantial role in achieving the overall predictability. Using weather variables (i.e., rainfall and temperature) can be effective in picking up some of the predictability of local SM that is not captured by the AMSR2 data. On the other hand, larger scale dynamic features identified from the AMSR2 data seem to facilitate the identification of regional spatial patterns of SM. The efficiency of the proposed model is compared with that of an ordinary regression model (OLR) using the same predictors. The mean correlation coefficient of the proposed model is about 0.78, which is significantly greater than that of the OLR at about 0.49. The proposed GM-NHMM method not only provides a better representation of the observed SM than the OLR model but also preserves the spatial coherence across all stations reasonably well. [ABSTRACT FROM AUTHOR]

To address certain limitations with their current operational model, Environment and Climate Change Canada recently developed the Soil, Vegetation, and Snow (SVS) land surface model and the representation of subsurface hydrological processes was targeted as an area for improvement. The objective of this study is to evaluate the ability of HydroSVS, the component of SVS responsible for the vertical redistribution of water, to simulate soil moisture under snow-free conditions when using flux-tower observations of evapotranspiration as forcing data. We assessed (1) model fidelity by comparing soil moisture modelled with HydroSVS to point-scale measurements of volumetric soil water content and (2) model complexity by comparing the performance of HydroSVS to that of HydroGeoSphere, a state-of-the-art integrated surface and subsurface hydrologic model. To do this, we performed one-dimensional soil column simulations at four sites of the AmeriFlux network. Results indicate that under Mediterranean and temperate climates, HydroSVS satisfactorily simulated soil moisture (Nash-Sutcliffe efficiency between 0.26 and 0.70; R 2  ≥ 0.80), with a performance comparable to HydroGeoSphere (Nash-Sutcliffe efficiency ≥0.60; R 2  ≥ 0.80). However, HydroSVS performed weakly under a semiarid climate while HydroGeoSphere performed relatively well. By decoupling the magnitude and sourcing of evapotranspiration, this study proposes a powerful diagnostic tool to evaluate the representation of subsurface hydrological processes in land surface models. Overall, this study highlights the potential of SVS for hydrological applications. [ABSTRACT FROM AUTHOR]

Soil water and its efficient use are critical to sustainable productivity of rainfed orchards under the context of climate change in water-limited areas. Here, we combined micro-catchments for collecting hillslope runoff, named fish-scale pits, with mulches to examine water infiltration and water consumption of fruit trees using in situ soil moisture monitoring, the micro-lysimeter and sap flow methods via a two-year experiment in a rainfed jujube orchard on China’s Loess Plateau. This experiment included four treatments: fish-scale pit with branch mulching (FB), fish-scale pit with straw mulching (FS), fish-scale pit without mulching (F), and bare land treatment (CK). The results showed that only about 50% of the rainfall infiltrated the soil for CK during the 2014 and 2015 growing seasons. The fish-scale pit without mulching experienced significantly increased rainfall infiltration by 41.38 and 27.30%, respectively, but also increased evaporation by 42.28 and 65.59%, respectively, compared to CK during the two growing seasons. The jujube transpiration significantly increased by 45.64–53.10% over CK, and the evaporation decreased by 42.47–53.50% when fish-scale pits were mulched with branches or straw. Taken together, the results show that the fish-scale pits and mulching combinations efficiently increased rainfall infiltration and jujube evapotranspiration in the experimental jujube orchard. The findings here provide an insight into the field water management for hillslope orchards in water-limited regions. [ABSTRACT FROM AUTHOR]

Climate and land cover are two major factors affecting the water fluxes and balance across spatiotemporal scales. These two factors and their impacts on hydrology are often interlinked. The quantification and differentiation of such impacts is important for developing sustainable land and water management strategies. Here, we calibrated the well-known Hydrus-1D model in a data-rich boreal headwater catchment in Scotland to assess the role of two dominant vegetation types (shrubs vs. trees) in regulating the soil water partitioning and balance. We also applied previously established climate projections for the area and replaced shrubs with trees to imitate current land use change proposals in the region, so as to quantify the potential impacts of climate and land cover changes on soil hydrology. Under tree cover, evapotranspiration and deep percolation to recharge groundwater was about 44% and 57% of annual precipitation, whilst they were about 10% lower and 9% higher respectively under shrub cover in this humid, low energy environment. Meanwhile, tree canopies intercepted 39% of annual precipitation in comparison to 23% by shrubs. Soils with shrub cover stored more water than tree cover. Land cover change was shown to have stronger impacts than projected climate change. With a complete replacement of shrubs with trees under future climate projections at this site, evapotranspiration is expected to increase by ∼39% while percolation to decrease by 21% relative to the current level, more pronounced than the modest changes in the two components (<8%) with climate change only. The impacts would be particularly marked in warm seasons, which may result in water stress experienced by the vegetation. The findings provide an important evidence base for adaptive management strategies of future changes in low-energy humid environments, where vegetation growth is usually restricted by radiative energy and not water availability while few studies that quantify soil water partitioning exist. [ABSTRACT FROM AUTHOR]

Cosmic-ray neutron probes (CRNPs) have footprint radii for measuring soil-water content (SWC). The theoretical radius is much larger at high altitude, such as the northern Tibetan Plateau, than the radius at sea level. The most probable practical radius of CRNPs for the northern Tibetan Plateau, however, is not known due to the lack of SWC data in this hostile environment. We calculated the theoretical footprint of the CRNP based on a recent simulation and analyzed the practical radius of a CRNP for the northern Tibetan Plateau by measuring SWC at 113 sampling locations on 21 measuring occasions to a depth of 30 cm in a 33.5 ha plot in an alpine meadow at 4600 m a.s.l. The temporal variability and spatial heterogeneity of SWC within the footprint were then analyzed. The theoretical footprint radius was between 360 and 420 m after accounting for the influences of air humidity, soil moisture, vegetation and air pressure. A comparison of SWCs measured by the CRNP and a neutron probe from access tubes in circles with different radii conservatively indicated that the most probable experimental footprint radius was >200 m. SWC within the CRNP footprint was moderately variable over both time and space, but the temporal variability was higher. Spatial heterogeneity was weak, but should be considered in future CRNP calibrations. This study provided theoretical and practical bases for the application and promotion of CRNPs in alpine meadows on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

• Stones in the soil reduce the duration of stage-1 and the cumulative evaporation. • Stones mainly affects the hydraulic conductivity function, less the water retention. • The size of the stones has a minor effect on evaporation. Stones and rock fragments are typically found within soil profiles across various landscapes. However, knowledge on, and understanding of, their impact on hydraulic functions and processes are still lacking. Specifically, the presence of stones within the soil profile may increase water storage and availability to vegetation and reduce plant mortality in drylands. However, physically-based testing of stones effect on soil water budget components is overlooked. Experiments under laboratory conditions from soil columns, with two volume content t levels and two sizes of stones, were carried out in this research. Our results reveal that stoniness reduces the duration of stage-1 evaporation (S1) and consequently the overall cumulative evaporation, proportionally to their volumetric content and to the initial soil water content. The effect of stone size on evaporation was minor during S1 but was more pronounced during stage-2 (S2) — when the evaporation front migrates downward — with smaller stones reducing evaporation more than the larger ones. A recent evaporation model, assuming that transient evaporation is a succession of steady state solutions, was applied to explain the 2-phases evaporation process in a stony profile. The model results indicate that apart from changing the effective porosity of the soil profile by replacing a soil volume by stones, stoniness affects mainly the hydraulic conductivity function but practically not the water retention curve. Stoniness induced an increase in the tortuosity-related parameters compared with those of the stone-free soil. This observation was strengthened by the fact that both measured and modelled data reveal that stoniness has not affected the downward movement of the water table level during drying. Although we tested two stone sizes only and further experiments are required for a broader understanding, we suggest that the outcoming insights may improve estimates of water budget components in stony soil profiles and their response to global climatic changes. [ABSTRACT FROM AUTHOR]

• Precipitation, NDVI, and LUCC dominated recipitation the spatial heterogeneity of SM. • Precipitation changes caused up to 40% of the drying up of SM. • SM anomalies at 28–289 cm mainly caused by one-month-old precipitation. • The influences of climate and vegetation were observed to decrease with soil depth. As an essential state variable of the earth's terrestrial system, soil moisture (SM) is highly significant regarding hydrological processes, agricultural production, land management in response to issues like soil erosion etc. However, the net effects of different environmental factors on the heterogeneity and variations of SM remain unclear, due to the complex interactions between variables. Indeed, investigating such effects in the highly climate-vulnerable Mongolian Plateau is imperative for water resource management and climate change adaptation. In this study, we analyzed the contributions of different environmental factors on the spatial heterogeneity and variations of SM in the Mongolian Plateau between 1982 and 2020, using a geographic detector model (GDM) and a novel nonlinear Granger causality model. The results of the GDM analysis demonstrated that precipitation and vegetation were the main controls relevant to SM heterogeneity, with their explanatory powers (Q statistics of GDM) found to be higher than 0.67. In two breakpoints—one in the early 1990′s and another in 2007—SM demonstrated a pattern of increase, then a decrease, subsequently followed by an increase (insignificant decrease in SM at 100–289 cm depth only). Precipitation was identified as the Granger causal of SM variations over 33.39–97.65% of the plateau's vegetated area, leading to the drying up of 40% of its SM. The greatest contribution to SM in 28–289 cm of the plateau was observed as coming from one-month-old precipitation, due to the lag in the manifestation of effects. Further, rising temperatures were found to have an immediate influence (2.73–5.23%) on SM in 14.61–54.90% of the whole plateau's vegetated area, an impact which was relatively high (>14%) in its northeastern wetting zone. Vegetation change posed a relatively weak effect (<2%) on SM over a limited area of the plateau (27.75–35.42%). Although lesser than the impacts of general climate changes, the contributions of climatic extremes could not be neglected, ultimately accounting for up to 10% of SM changes. In summary, this study provides new insights into the individual contributions of various environmental factors on the spatial heterogeneity and variations of SM in the Mongolian Plateau, offering vital information for policymaking regarding climate change mitigation and adaptation, sustainable use of water resources, and ecological restoration for arid and semi-arid region. [ABSTRACT FROM AUTHOR]

Monitoring water status near the soil surface is a prerequisite for studying hydrological processes at the soil-atmosphere boundary and an option for calibrating remotely sensed water content data, for instance. As the water status of the uppermost soil layer is highly variable in space and time, adequate sensors are required to enable accurate measurements. Therefore, a sensor setup was tested and evaluated in the laboratory and in the field for such a purpose. The arrangement included Hydra Probe and MPS-2 sensors to measure water content and matric potential, respectively. Performance of the MPS-2 was validated in the laboratory by comparing sensor readings with the water potential of a soil, drained to equilibrium for certain pressure steps inside a pressure plate apparatus. Afterwards, six Hydra Probes and twelve MPS-2 sensors were installed in bare soil at a small field plot of about 9 m 2 . The measurements represented soil water status to a depth of 6 cm from surface. Core samples were repeatedly excavated around the measurement spots. Their water content was determined and the samples were further utilized to analyze water retention characteristics. The tested setup properly reflected changes of near-surface soil water status due to rainfall and evaporation. However, some shortcomings weakened the potential of the chosen arrangement. Site-specific calibration of the Hydra Probes – implemented by relating sensor readings to the water content values of the core samples – confirmed the applicability of the recommended standard calibration parameters for the respective soil texture. The derived user calibration enabled a measurement accuracy of 0.02 cm 3 ·cm −3 . Further improvement was restrained by the spatial variability of soil moisture. In this context, spots that were permanently drier or wetter than the others were discovered by means of a temporal stability approach. Performance of MPS-2 sensors was more critical with respect to the objectives. Sensor-to-sensor variation was small at the applied pressure steps of −20, −50, and −100 kPa, but the respective averaged readings were −18, −37, and −57 kPa. At matric potentials of −200 and −300 kPa, the MPS-2 revealed substantial sensor-to-sensor variation. The large deviation of the sensor readings in the field confirmed that the calibration of the MPS-2 should be improved. However, in spite of this inaccuracy, the wide measuring range of the MPS-2 offers suitability to a wide range of potential applications. As an example, water retention functions were calculated from the in-situ data and compared to retention data from the core samples. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) change is an indicator of climate change. Therefore, it is helpful to understand how climate change impacts water systems. In this study, the influence of climate change on TWS in Central Asia over the past decade was analyzed using the Gravity Recovery and Climate Experiment satellites and Climatic Research Unit datasets. Results indicate that TWS experienced a decreasing trend in Central Asia from 2003 to 2013 at a rate of −4.44 ± 2.2 mm/a, and that the maximum positive anomaly for TWS (46 mm) occurred in July 2005, while the minimum negative anomaly (−32.5 mm) occurred in March 2008–August 2009. The decreasing trend of TWS in northern Central Asia (−3.86 ± 0.63 mm/a) is mainly attributed to soil moisture storage depletion, which is driven primarily by the increase in evapotranspiration. In the mountainous regions, climate change exerted an influence on TWS by affecting glaciers and snow cover change. However, human activities are now the dominant factor driving the decline of TWS in the Aral Sea region and the northern Tarim River Basin. [ABSTRACT FROM AUTHOR]

• Extreme rainfall events that lead to floods in large rivers are expected to decrease. • Antecedent soil moisture is expected to be reduced in most of South America. • Soil moisture seems more impactful than precipitation regarding ordinary floods. A warmer atmosphere is able to hold more water which consequently intensifies the hydrological cycle. The projected increase in extreme precipitation has been associated with greater floods; however, most recent studies have argued that the reduced soil moisture could be causing the opposite effect. We aim to understand how the hydrometeorological variables affect flood discharge and what the projections are for South America, a vulnerable continent that has been barely studied regarding flood trends. We used climate data from Eta simulations nested in 4 global climate models (BESM, CanESM2, HadGEM2-ES, MIROC5) as input for the MGB-SA hydrological model to yield flood discharge estimates. Then we were able to project the climate impacts on extreme precipitation, antecedent soil moisture, and flood discharge for large rivers (>1,000 km2) and understand how these variables are related. Our results showed a strong sign that antecedent soil moisture is expected to be reduced in most of the continent except in Southeastern South America (SESA). On the other hand, there are mixed signs for rarer precipitation and a clear spatial pattern for 2-year precipitations (RP2), which is expected to increase on the SESA and west Amazon and decrease on Central South America (CSA). For basins>100,000 km2, results indicate a negative change sign for 2-year precipitations, meaning that rainfall events that generate ordinary floods in large South American rivers are expected to decrease in the XXI century due to climate change. The change signs for flood discharge and extreme precipitation are spatially similar but more basins show a decrease for flooding than for rainfall. While only half of the South American basins are expected to present reduced 2-year precipitations, nearly 70 % of the rivers present a negative sign for 2-year floods, which can be attributed to the reduced antecedent soil moisture. [ABSTRACT FROM AUTHOR]

• Future change in global extreme meteorological droughts. • Two climate model large ensembles were used to assess the change of frequency. • Changes in meteorological droughts are mostly correlated to mean precipitation. • Projected increases in frequency are much more severe for short-term droughts. • Total area affected by a worsening of droughts gets larger with the return periods. Several studies have looked at the evolution of droughts in a changing climate in various locations and have typically found that droughts are expected to become more severe in the future. However, relatively little work has been done on extreme droughts. This study focuses on the evolution of extreme meteorological droughts over near (2036–2065) and far (2071–2100) future time periods. Monthly precipitation from two large multi-member climate model ensembles: the Canadian Earth System Model (CanESM2) 50-member ensemble and the Community Earth System Model (CESM1) 40-member ensemble, was used to calculate the Standard Precipitation Index (SPI) to quantify and explore the evolution of future meteorological droughts. The use of these large ensembles allows for the calculation of the 20- and 100-year droughts return period and offers a unique perspective into those rare events. Both climate models project increases in extreme meteorological drought frequency over many of the world's regions. The spatial patterns of regions with worsening droughts generally match those of projected change in mean annual precipitation, although the former is more extensive, indicating that changes in internal variability will increase drought frequency even in some regions projected to see increased mean annual precipitation. The projected increase in meteorological drought frequency is more significant for short-term JJA droughts, and for the larger return periods. Large increases in frequency are observed in many regions, all the way up to 20 times for the historical100-year JJA drought indicating a return period shift from 100 to 5 year. Considering the significant predicted increases in temperature, it follows that future changes for both agricultural (soil water deficit) and hydrological droughts (low stream levels), which result from the interaction between precipitation deficit and temperature (as well as other variables), will be even more severe. [ABSTRACT FROM AUTHOR]

Identifying the relationship between the stochastic daily rainfall regime and the dynamics of plants and soil moisture is fundamental for the sustainable management of dryland ecosystems in a context of global climate change. An eco-hydrological model that couples the dynamics of woody vegetation cover and deep soil moisture (typically with a depth interval of 30–150 cm) was used to investigate the effect of stochastic intensity and the intermittency of precipitation on soil moisture in this deep interval, which affects woody vegetation cover. Our results suggest that the precipitation intensity and intermittency play an important role in the dynamics of wood vegetation cover and deep soil moisture. In arid and semiarid regions, as the annual precipitation increased, the rate of woody vegetation cover increased as a power-law function, and the deep soil moisture increased exponentially. For a given annual rainfall, there were positive correlations between the rainfall intensity (or rainfall intermittency) and both the woody vegetation cover and deep soil moisture. The positive correlations between wood vegetation cover and both rainfall intensity and intermittency may decrease with increases in the precipitation intensity or precipitation intermittency. The positive correlations between deep soil moisture and both rainfall intensity and rainfall intermittency increase as the precipitation intensity or precipitation intermittency increases. Moreover, these positive correlations may increase with increases in the mean annual rainfall. Our results emphasize the importance of daily precipitation variations in controlling the responses of woody vegetation cover and deep soil moisture to climate variations in arid and semiarid regions. Our model can aid the understanding of rainfall processes and indicates that increases in rainfall intensity or rainfall intermittency may lead to an increase in woody vegetation cover and deep soil moisture given an invariable annual rainfall regime in dryland ecosystems. [ABSTRACT FROM AUTHOR]

• Soil moisture (SM) is a key component of global hydrological cycles. • SM sensitivity (ΔSM) was investigated as an indicator of SM response to climate change. • SM sensitivity to temperature (ΔSM_T) and precipitation (ΔSM_P) were studied. • Both the ΔSM_T and ΔSM _P of the Loess Plateau has been declining over the past 20 years. • The contribution of vegetation variation to ΔSM_P was higher than that to ΔSM_T. Soil moisture is a key component of global hydrological cycles and is closely linked to climate and vegetation. However, exactly how vegetation affects the response of soil moisture to climate remains unclear. In this study, soil moisture sensitivity was investigated as an indicator of soil moisture response to climate change (including temperature and precipitation). Twenty years of data from the GLEAM (Global Land Evaporation Amsterdam Model), meteorological station, and remote sensing of the Loess Plateau of China were used to estimate the impact of the vegetation regulatory action on soil moisture sensitivity. The results show that soil moisture sensitivity to both temperature and precipitation exhibits distinct spatiotemporal patterns. With increasing Enhanced Vegetation Index (EVI), soil moisture sensitivity to temperature decreased at first and increased subsequently, while that to precipitation decreased continuously, reaching a stable value. The overall level of soil moisture sensitivity to both temperature and precipitation in the Loess Plateau was declining. Specifically, vegetation variation contributed 23.78% and −78.57% of the soil moisture sensitivity to precipitation in the surface and root zone, respectively, which is higher than it contributed to the soil moisture sensitivity to temperature (11.4% and 17.23%). The results of this study provide a scientific basis for the effective implementation of the 'Grain for Green' Program and the sustainable management of water resources on the Loess Plateau. [ABSTRACT FROM AUTHOR]

• The raw CMIP6 ensemble overestimates precipitation while underestimating temperature for the Yangtze River basin. • Under the SSP5-8.5 (2061–2100), averaged annual flood magnitude, timing, frequency, and duration are projected to increase 66.6 %, arrive 1.9 days earlier, increase 27.5 %, and prolong 19.1 days, respectively. • The most drastic changes in future floods are likely to occur in spring, followed by summer, autumn, and winter. • Strong spatial heterogeneities of Yangtze future flooding require the coordination of strategies from different stakeholders at the regional scale. Climate change is altering flood risk globally. The nature of those alterations varies locally, creating the need for regional assessments to inform flood-risk management and planning. This study projects future changes in flood regime in the Yangtze River basin. To characterize flood regimes, we use a multi-attribute approach that measures the relative change in flood magnitude, timing, frequency, and duration between historical and future periods. We use climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to force the Soil and Water Assessment Tool (SWAT), and generate daily streamflow projections along the Yangtze River network for two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. We use seasonal maxima, annual maxima, and peaks-over-threshold to determine the different flood attributes. Results show that downscaled CMIP6 precipitation and near-surface temperature are both projected to increase substantially in the future, with a consequent surge in floods across the basin. In the far future (years 2061–2100), under SSP5-8.5, average annual flood magnitude, timing, frequency, and duration are projected to increase 66.6 %, arrive 1.9 days earlier, increase 27.5 %, and prolong 19.1 days, respectively. Projected changes in flood attributes at annual timescale are generally higher in the basin's northern tributaries than in the southern ones. Changes in flood magnitude and frequency tend to resemble each other, whereas flood timing and duration exhibit distinct change patterns. Our multi-attribute approach to flood regime characterization provides a systematic way for translating raw CMIP6 projections into informative future flood projections. This approach can help inform flood-risk planning and improve the reliability of climate change impact assessment. [ABSTRACT FROM AUTHOR]

• An increasing trend of winter baseflow was found in upper parts of both the Lena River basin and the Aldan River basin. • The increased winter discharge was strongly associated with warming-enhanced permafrost thawing and increased net precipitation. • Thinning river ice induced by warming temperatures contributed to the increase of winter river discharge. Winter discharge of the Lena River (Russia) has increased over the previous several decades. However, the impact of permafrost thawing and of changing hydrological processes induced by climate change on the river's winter discharge is not well-quantified. Here, using a coupled land surface model and a distributed discharge model, we conducted trend analyses to examine the sensitivity of winter discharge to permafrost thawing and water budget change in the Lena River basin during 1979–2016. An increasing trend of winter baseflow was found in upper parts of both the Lena River basin and the Aldan River basin, where summer net precipitation showed a statistically significant increase. The increased summer net precipitation resulted in higher soil moisture in the deepened active layer in late summer and early autumn, which was linked to autumn and winter baseflow. These implications were examined from the perspective of interrelations among the trends of active layer thickness, soil moisture, and baseflow in the cold season by identifying regions in which all the variables exhibited positive trends. The identified source regions were primarily in the lower Lena River basin and upper basins of the Lena and Aldan rivers, although winter baseflow was more dominant in the latter regions owing to the freezing effect of the active layer. Thinning of river ice induced by warming temperatures also contributed to the increase of winter river discharge. These results suggest that the increased winter discharge was strongly associated with climate-change-related enhancement of permafrost thawing and increase in net precipitation that affected soil hydrological processes, which will be strengthened further in the context of global warming. [ABSTRACT FROM AUTHOR]

• Projections show a clear reduction of soil moisture through the entire annual cycle. • Soil moisture deficits up to 6x (7x) are projected to occur for mid- (end-) of-century. • Semi-arid climate is expected to cover almost 2/3 of the mainland in the RCP8.5. Climate change constitutes a major threat for all the Mediterranean countries due to the combination of large precipitation reductions and temperature increases and the higher frequency of climate extremes, especially driving water scarcity and all the derived multi-sectoral impacts. Portugal, as most of the Mediterranean countries, already endures larger frequencies of droughts and deficits in soil moisture and water storage. In the current study, the future projections of soil moisture are examined using a multi-model EURO-CORDEX regional climate ensemble, in agreement with three future emission scenarios (RCP2.6, 4.5 and 8.5). The drivers of future soil moisture dynamics are also analysed and its effect on relative humidity and evaporation rates. As expected, the projections show a clear reduction of soil moisture through the entire annual cycle, in response to the large decrease in precipitation and temperature increase, via a massive growth of potential evapotranspiration. The overall total soil moisture decreases ranges from −5% for the RCP2.6 to −20% (-10%) for the RCP8.5 (RCP4.5), w.r.t. the present climate. In the historical period, soil moisture deficits rarely reach values 3x over the standard deviation, but projections reveal that for the RCP4.5 (RCP8.5) for the mid-century deficits up to 5x (6x) are projected to occur, and for the end-of-century even 7x for the RCP8.5. The annual cycle of soil moisture is in present and future climate determined by precipitation and potential evapotranspiration, and deficit is both enhanced and covers a wider monthly window in the future, especially for the RCP8.5. The surface humidity also decreases importantly, up to −4% and −8% in spring and summer in the end-of-the-century, in agreement with RCP4.5 and RCP8.5, respectively. Resulting from the projected changes in precipitation and potential evapotranspiration, the typical semi-arid climate, which in present climate is confined to a small south-eastern region of Portugal, is expected to cover almost 2/3 of the mainland in the case of RCP8.5. Finally, this study was developed in the framework of the National Roadmap for Adaptation XXI - Portuguese Territorial Climate Change Vulnerability Assessment for XXI Century (RNA2100) project and aims at delivering a deeper and different featuring of terrestrial water for adaptation purposes in a Mediterranean country. [ABSTRACT FROM AUTHOR]

• We assessed spatiotemporal dynamics of hydrological processes and water retention. • The negative impact of increasing ET can offset the impact of rising rainfall on WR. • The degradation risk of water retention deserves much attention along this Century. Identifying the dynamics of water retention (WR) is critical for developing adaptive strategies for effective water resources management under climate change. However, our understanding about the responses of WR to climate change is still limited, which hinders risk assessment and warning of WR under future climate trajectories. In this study, we used the Soil and Water Assessment Tool (SWAT) to quantify the impact of climate change on WR in the upper Heihe River Basin (UHRB), a typical inner headwater basin, and predicted the future trends and potential degradation risks of WR based on climate scenarios under three Representative Concentration Pathways (RCP2.6, RCP4.5, and RCP8.5). Our results showed that the historical (1971–2020) average WR in the UHRB was approximately 91.1 mm, with high WR occurring in the middle and west of the basin and low WR in the north and southeast. Our prediction suggested that the WR may remain stable during the near future (2021–2060) under the RCP2.6 scenario; however, WR may decrease by 23 % and 32 % during this period under the RCP4.5 and RCP8.5, respectively. By the end of this century (2061–2099), the WR may decrease by 10 %, 40 %, and 69 % under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, due to the substantially enhanced evapotranspiration in the warming context, though a slight increase in precipitation may partly offset this negative impact. In brief, this study provides a paradigm for assessing the dynamics and future degradation risk of water retention at watershed scale, and this can be valuable and applicable for other areas. [ABSTRACT FROM AUTHOR]

• Temperature has a negative effect on SSM under drought conditions. • Higher temperature accelerates SSM drying even across different land covers. • Temperature has a greater effect on scaling than land cover across different land covers. Understanding the dynamic response of surface soil moisture (SSM; 0–7 cm) drying to rising temperature is vital to predict future changes in agricultural and hydrological drought. Here we use quantile regression to explore the scaling effects of 2-m air temperature on SSM (%/°C) of the driest month in 8 different land cover types in the Yellow River Basin by using temperature intervals and a sliding window approach. SSM decreases significantly with air temperature and decreases more rapidly in warmer conditions, except for plain field, suggesting that temperature has a greater effect on SSM-temperature scaling than land cover. For warmer conditions, scaling exhibits larger spatial heterogeneity, indicating that it is mainly affected by local factors. When SSM is moderate, the scaling is constrained by various factors, but mainly by temperature. Comparatively, the scaling is close to 0 when SSM is very high or very low. The study highlights that global warming effects on drought may be underestimated. The findings provide an important theoretical basis for effects of temperature on soil moisture and future drought prediction. [ABSTRACT FROM AUTHOR]

• PRE-VI associations were greater in the Southern hemisphere drylands. • Moderate soil moisture enhanced the PRE-VI association in global dryland. • Decreased soil moisture weakened the PRE-VI association during 1982–2015. Vegetation growth is critical in characterizing ecosystem carbon sequestration. Water availability profoundly affects the interaction between climate change and vegetation dynamics in drylands. However, the associations of the precipitation–vegetation index (PRE-VI) and temperature–vegetation index (TEM-VI) as well as whether and how the soil moisture modulates PRE-VI and TEM-VI are still unclear. Precipitation contributed substantially much more to vegetation dynamics than temperature, and PRE-VI associations were greater in the Southern Hemisphere than those in the Northern Hemisphere in global drylands. The traceability effects of soil moisture on PRE-VI and TEM-VI were investigated, and a convex shape was observed for PRE-VI as soil moisture increased, but not significant trend for TEM-VI. It showed that moderate soil moisture enhanced PRE-VI associations through the maintenance of reasonable surface–atmosphere feedback to counteract the balance of plant growth and energy collocation. In the past three decades, PRE-VI associations decreased with the increase in soil moisture, suggesting the consistency of the spatial and temporal pattern of the effect of soil moisture on PRE-VI associations in water-limited ecosystems. Our results implied that changes in soil moisture reflect changes in climate–vegetation associations and can guide nature-based solutions to improve ecosystem carbon sink. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is an essential climate variable of greater relevance in the monsoon scenario, hence validation and understanding of its spatio-temporal variability over the Indian region is of high significance. In the present study, five SM products are evaluated against in situ SM measurements conducted by India Meteorological Department and the selected data product is used for spatio-temporal characterization of SM in relation to monsoon rainfall. The data products evaluated are: European Space Agency’s merged satellite SM, Modern-Era Retrospective analysis for Research and Applications (MERRA) Land SM, ECMWF’s ERA interim SM, Climate Forecast System Reanalysis SM, and Global Land Data Assimilation System Noah Land Surface Model SM. Comparisons show that seasonal SM patterns in all products generally follow the characteristics of rainfall, even though there are certain differences in details. The statistical estimates indicate fairly good agreement between in situ and the five products, with some variations among them and over the homogeneous rainfall regions. On comparison, MERRA SM is found appropriate for further analyses on spatio-temporal characteristics, which are then carried out with the 20 year (1993–2012) SM data. Stability analyses revealed SM patterns indicative of relative SM variability as well as persistence. The spatial stability analysis depicts dry and wet patterns and their seasonal variations over different geographical locations in relation to all India spatial average. Large temporal variations are found over central, western and northern Indian regions caused by large intraseasonal variability in rainfall. In brief, intraseasonal and interannual soil moisture variations broadly follow the rainfall pattern, with long-term influences attributed to SM memory effects. The soil moisture persistence and dominant scales of variability are explored with autocorrelation and wavelet transform techniques. Seasonal persistence is large over regions receiving excessive rainfall, while drought years are noted to have large intraseasonal SM persistence compared to that of surplus year. Wavelet decomposition demonstrates that low periodicity (2–10 days) SM modes match that of rainfall during initial periods of monsoon. The occurrence of significant higher periodicity modes are dominant in drought years compared to surplus, which also vary with geographical locations. [ABSTRACT FROM AUTHOR]

Summary Landslides are frequent and widespread geomorphological phenomena causing loss of human life and damage to property. The main tool for assessing landslide risk relies on rainfall thresholds and thus, many countries established early warning systems aimed to landslide hazard assessment. The Umbria Region Civil Protection Centre developed an operational early warning system for landslide risk assessment, named PRESSCA, based on the soil saturation conditions to identify rainfall thresholds. These thresholds, currently used by the Civil Protection operators for the day-by-day landslide hazard assessment, provided satisfactory results with more than 86% of the landslides events correctly identified during the period 1990–2013. In this study, the PRESSCA system was employed for the assessment of climate change impact on landslide hazard in Central Italy. The outputs of five different Global Circulation Models (GCMs) were downscaled and weather generators were used for obtaining hourly rainfall and temperature time series from daily GCMs projection. Then, PRESSCA system was employed to estimate the number of landslide occurrence per year. By comparing results obtained for three different periods (1990–2013 (baseline), 2040–2069 and 2070–2099), for the Umbria territory a general increase in events occurrence was expected (up to more than 40%) in the future period, mainly during the winter season. The results also revealed that the effect of climate change on landslides was not straightforward to identify and the close interaction between rainfall magnitude/intensity, temperature and soil moisture should be analysed in depth. Overall, soil moisture was projected to decrease throughout the year but during the wet season the variations with respect to the present period were very small. Specifically, it was found that during the warm-dry season, due to the strong decrease of soil moisture, even for a sensible increase in rainfall intensity, the landslide occurrence was unchanged. Conversely, during the cold-wet season, the number of landslide events increased considerably if a positive variation in rainfall amount, more significant than rainfall intensity, was coupled with small negative variations in soil moisture. [ABSTRACT FROM AUTHOR]

Summary Shallow saturated subsurface flow is a dominant runoff mechanism on hillslopes of headwater catchments under humid temperate climate. Its timing and magnitude is significantly affected by the presence of preferential pathways. Reliable prediction of runoff from hillslope soils under such conditions remains a challenge. In this study, a quantitative relationship between rainfall, stormflow, and leakage to bedrock for hillslopes, where lateral preferential runoff represents a dominant part of the overall response, was sought. Combined effects of temporal rainfall distribution and initial hillslope saturation (antecedent moisture conditions) on stormflow, leakage to bedrock, and overall water balance were evaluated by conducting simulations with synthetic rainfall episodes. A two-dimensional dual-continuum model was used to analyze hydrological processes at an experimental hillslope site located in a small forested headwater catchment. Long-term seasonal simulations with natural rainfall indicated that leakage to bedrock occurred mostly as saturated flow during major runoff events. The amount of rainfall needed to initiate stormflow appeared as a dynamic hillslope property, depending on temporal rainfall distribution, initial hillslope storage, and the spatial distribution of soil water within the hillslope. No single valued rainfall threshold responsible for triggering stormflow was found. Rainfall–stormflow as well as rainfall–leakage relationships were found highly nonlinear for low initial hillslope saturations. Temporal rainfall distribution affected the amount of rainfall necessary to initiate stormflow more than it did the amounts of stormflow or leakage to bedrock. In spite of a simple hillslope geometry with constant slope and parallel soil–atmosphere and soil–bedrock interfaces considered in the analysis, the applied model predicted a hysteretic behavior of storage–discharge relationship. The results showed a mutual interplay of components of hillslope water balance exposing a nonlinear character of the hillslope response. The study provided a quantitatively coherent insight in the hydraulic functioning of hillslopes where preferential flow constitutes a dominant part of stormflow. [ABSTRACT FROM AUTHOR]