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Climate change scenarios of precipitation and temperature were divided into three time windows of 30 years each from 2011 to 2099. The new version of Soil and Water Assessment Tool (QSWAT v2.6.1) was used to simulate the hydrological response and it was first calibrated and validated using observed data as an input for assessing the hydrological responses. The results showed that the QSWAT calibration and validation reveals a good agreement (R²=0.77) during calibration and validation. Whereas nash and Sutcliffe simulation efficiency (NSE) was found to be 0.76 during calibration and 0.73 during validation. Based on changes of precipitation, maximum and minimum temperature, the monthly flow volume did not show systematic trends i.e. increases non-rainy months and decreases in the wet-months. Thus, the hydrology of Megech River is highly vulnerable to climate change which causes water stress for domestic use and environmental flow. [ABSTRACT FROM AUTHOR]

Following the declaration of the UN Decade on Ecosystem Restoration, nature-based solutions (NbS) are at the forefront of the sustainability discourse. However, this solution needs operational clarity to avoid the commonly mentioned vagueness of the concept. This paper highlighted application of the ecohydrological principles to guide the conception, planning, designing, implementation, and monitoring of nature-based solutions. The paper proposed an ecohydrological nature-based solution that is emanated from the natural sequence of self-regulating patch-interpatch at the hillslope scale to restore highly degraded hillslope in Lake Hawassa sub-basin of Ethiopian Rift Valley Basin. The active restoration site is found to have a landscape organization index value of 0.94 (= 94% of the gradsect is consisting of resources conserving patches) as compared to 0.16 at the passive site. In terms of landscape functionality, the active site showed significant stability (p(x≤T) = 0.01), infiltration (p(x≤T) = 0.001), and nutrient cycling (p(x≤T)=0.005). It also exhibited significant improvement in soil moisture (p(x≤T) = 0.001). Ecologically, the active site is found to be more diverse (richness index 18 (active) vs. 8 (passive); heterogeneous (Shannon diversity index=1.22 (active) vs. 0.44 (passive)); well distributed (Simpson's index= 0.62 (active) vs. 0.28 (passive)); less dominance of few species (Evenness index (0.99 (passive) vs. 0.96 (active)). Limitation of this study is linked with the short span of the restoration period which tends to be not adequate to observe the full 'dual' regulation between hydrology and biota. For this, the research can be considered as a prerequisite towards full restoration of the landscape. [ABSTRACT FROM AUTHOR]

This modeling study intended to solve a part of the global scientific problem related to increased concentrations of carbon dioxide in the atmosphere via emissions from terrestrial ecosystems that, along with anthropogenic emissions, make notable contributions to the processes of climate change on the planet. The main stream of CO2 from natural terrestrial ecosystems is related to the activation of biological processes, such as the production/destruction of plant biomass. In this study, the Wetland-DNDC computer simulation model with a focus on nitrogen and carbon biogeochemical cycles was used to study the effect of hydrothermal conditions on greenhouse gas fluxes in West Siberian peatlands. The study was implemented on the site of the world's largest pristine wetland/peatland system, the Great Vasyugan Mire (GVM). The study was carried out based on data from permanent measurements at meteo stations and our own in situ measurements of hydrological and thermal parameters on sites, which allowed for testing different scenarios of changes in environmental conditions (temperature, precipitation, groundwater level) together with a change in GHG fluxes. The study revealed the air temperature and the level of groundwater as the main drivers controlling CO2 fluxes. The study of different scenarios of change in annual air temperature revealed the threshold of change in the wetland/peatland ecosystem from carbon sink to carbon source to the atmosphere to happen with an increase in the average annual air temperature by 3 °C with reference to the average annual air temperature values in 2019. Also, we found that the wetland/peatland ecosystem turned to act as an active carbon sink with about 7 cm increase in annual groundwater level, compared with its base level of −21 cm. [ABSTRACT FROM AUTHOR]

Under the background of climate change, vegetation restoration in arid area ecosystem is faced with great challenges, which has important research value and is also an important research direction of ecology. In this paper, CiteSpace software was used to carry out data mining and econometric analysis on the research progress of vegetation restoration in arid area ecosystem. Besides, the number of papers published under this topic, the trend of change, the main research strength and the development path of the research topic were presented. The study found that (1) the overall volume of papers showed a significant growing tendency on the whole, and generally experienced three growth stages of slow, steady and rapid growth. The research hotspots were different at different stages. At present, the research mainly focuses on clustering topics such as “soil moisture”, “abandoned farmland”, “biological soil skinning” and “layered soil”, and the cross-study of engineering, hydrology, geosciology and other related disciplines is increasing day by day. (2) China, the United States and Spain were the countries with the largest number of publications, and the Chinese Academy of Sciences was the research institution with the largest number of publications. Li Xinrong and others constituted the core group of authors under the research topic. (3) The strategies of vegetation restoration in response to drought stress and the changing rules of the structure and function of different restored ecosystems under the background of climate change may be the research hotspots of vegetation restoration in arid areas in the near future. [ABSTRACT FROM AUTHOR]

Considering the sensitivity and importance of water resources in the Himalayan uplands, this study intended to assess the hydrological responses to climate change in the Jhelum basin. Representative concentration pathway (RCP)–based projections from six dynamically downscaled global circulation models (GCMs) were bias-corrected for developing the climatic projections over the twenty-first century. The uncertainty associated with GCM outputs was addressed by using multi-model ensemble projections developed through Bayesian model averaging (BMA) technique. The assessment reveals that compared to the baseline (1980–2010) values, the annual mean maximum temperature in the basin will rise by 0.41–2.31 °C and 0.63–4.82 °C, and the mean minimum temperature will increase by 1.39–2.37 °C and 2.14–4.34 °C under RCP4.5 and RCP8.5, respectively. While precipitation is expected to decrease by 7.2–4.57% and 4.75–2.47% under RCP4.5 and RCP8.5, correspondingly. BMA ensemble projections were coupled with the Soil and Water Assessment Tool (SWAT) to simulate the future hydrological scenarios of the drainage basin. With the changing climate, the discharge of rivers in the Jhelum basin is expected to witness reductions by about 23–37% for RCP4.5 and 19–46% for RCP8.5. Moreover, the water yield of the basin may also exhibit decreases of 17–25% for RCP4.5 and 18–42% for RCP8.5. The projected scenarios are likely to cause water stress, affect the availability of water for diverse uses, and trigger transboundary water-sharing-related conflicts. The impact of climate change on discharge demands early attention for the formulation of mitigation and adaptive measures at the regional level and beyond. [ABSTRACT FROM AUTHOR]

Drought is a recurring natural hazard that has substantial human and environmental impacts. Given continued global warming and associated climate change, there is concern that droughts could become more severe and longer lasting. To better monitor and understand drought development and persistence, it is helpful to understand the development and climatic drivers of past droughts. In this study we use monthly runoff percentiles to identify five major drought events in the conterminous United States (CONUS) from 1901 through 2020. For each drought event we examined spatial patterns of departures of mean monthly precipitation, temperature, soil moisture storage, and runoff for 2,107 hydrologic units (HUs) across the CONUS. Results indicated that precipitation deficits have been the primary driver of past major‐drought events and temperature a secondary driver, even of the most recent drought event (September 1999 through September 2015) when positive temperature anomalies occurred over most of the CONUS. Additionally, negative soil moisture storage departures were more negative than runoff departures during the five drought events we examined, which emphasizes the importance of measuring both runoff and soil moisture to monitor drought conditions. We also examined the use of statistical persistence to develop short‐term (i.e., 1 month) forecasts of runoff drought conditions in the CONUS by developing autoregressive integrated moving average (ARIMA) models for each HU. Results indicated that persistence can be used to predict short‐term changes in the spatial pattern of drought and the areal extent of drought, but that predictions of runoff magnitude for any particular site are often poor. [ABSTRACT FROM AUTHOR]

The extent and mechanisms by which precipitation extremes affect hydrological processes in the critical zone (CZ) of loess possessing a thick unsaturated zone remains poorly understood. To this end, we here employed a coupled liquid‒vapor‒heat‒airflow STEMMUS (simultaneous transfer of energy, mass, and momentum in unsaturated soil) model to investigate the impact of extreme precipitation, at both event and annual scales, on CZ hydrological processes within a semiarid loess site vegetated by apple trees on China's Loess Plateau. At the event scale, the vapor flux was two orders of magnitude lower than the liquid water flux. However, the thermal vapor flux penetrated to depths of 200 cm, whereas the isothermal liquid water flux only infiltrated to 100 cm during the study period, implying that thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR). At the annual scale, the DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry years. In contrast, extreme changes in climate had only limited impacts on evapotranspiration; the difference between extremely wet and extremely dry years averaged only 35 mm, much less than the difference in precipitation, which averaged 310 mm. However, the extremely dry years showed a higher ratio (0.58) between transpiration and evapotranspiration than did the extremely wet years (0.51). The findings reported here improve our understanding of CZ hydrological processes related to precipitation extremes in semiarid loess regions. Key Points: Thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR) in loessThe DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry yearsExtreme changes in precipitation had only limited impacts on evapotranspiration [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in agriculture, hydrology, plants’ seasonal growth cycle, and their sustainability under climate change. This letter presents a novel method for regional mapping of soil moisture with partial vegetation cover by using dual-polarized Sentinel-1 C-band SAR data. Model-based retrieval of soil moisture from radar backscatter under partial vegetation cover first necessitates the separation of the backscatter of the underlying soil from total radar backscatter and then the implementation of an inversion technique to estimate its soil moisture content from the backscattering coefficient of the underlying soil. The regional mapping of soil moisture was verified with in situ measurements along a climatic gradient (650–100 mm/year) in central Israel. A good agreement between the estimated soil moisture and the measured from ground samples was found, with an $R^{2}$ of 0.793 with an RMSE of 0.047. [ABSTRACT FROM AUTHOR]

Climate change affects the hydrological cycle of river basins and strongly impacts water resource availability. The mechanistic hydrological model PROMET was driven with an ensemble of EURO-CORDEX regional climate model projections under the emission scenarios RCP2.6 and RCP8.5 to analyze changes in temperature, precipitation, soil water content, plant water stress, snow water equivalent (SWE) and runoff dynamics in the Danube River Basin (DRB) in the near (2031–2060) and far future (2071–2100) compared to the historical reference (1971–2000). Climate change impacts remain moderate for RCP2.6 and become severe for RCP8.5, exhibiting strong year-round warming trends in the far future with wetter winters in the Upper Danube and drier summers in the Lower Danube, leading to decreasing summer soil water contents, increasing plant water stress and decreasing SWE. Discharge seasonality of the Danube River shifts toward increasing winter runoff and decreasing summer runoff, while the risk of high flows increases along the entire Danube mainstream and the risk of low flows increases along the Lower Danube River. Our results reveal increasing climate change-induced discrepancies between water surplus and demand in space and time, likely leading to intensified upstream–downstream and inter-sectoral water competition in the DRB under climate change. [ABSTRACT FROM AUTHOR]

Data assimilation (DA) of remotely sensed leaf area index (LAI) can help to improve land surface model estimates of energy, water, and carbon variables. So far, most studies have used bias-blind LAI DA approaches, i.e.\ without correcting for biases between model forecasts and observations. This might hamper the performance of the DA algorithms in the case of large biases in either observations or simulations, or both. We perform bias-blind and bias-aware DA of the Copernicus Global Land Service LAI into the Noah-MP land surface model forced by the ERA5 reanalysis over Europe in the 2002–019 period, and evaluate how the choice of bias correction affects estimates of gross primary productivity (GPP), evapotranspiration (ET), runoff, and soil moisture. In areas with a large LAI bias, the bias-blind LAI DA leads to a reduced bias between observed and modelled LAI, an improved agreement of GPP, ET, and runoff estimates with independent products, but a worse agreement of soil moisture estimates with the European Space Agency Climate Change Initiative (ESA CCI) soil moisture product. Bias-blind LAI DA can also lead to unrealistic shifts in soil moisture climatologies, for example when the assimilated LAI data in irrigated areas are much higher than those simulated without any irrigation activated. Furthermore, the bias-blind LAI DA produces a pronounced sawtooth pattern due to model drift between update steps. This model drift also propagates to short-term estimates of GPP and ET, and to internal DA diagnostics that indicate a suboptimal DA system performance. The bias-aware approaches based on a priori rescaling of LAI observations to the model climatology avoid the negative effects of the bias-blind assimilation. They retain the improvements of GPP anomalies from the bias-blind DA, but forego improvements in the root mean square deviation (RMSD) of GPP, ET, and runoff. As an alternative to rescaling, we discuss the implications of our results for model calibration or joint parameter and state update DA, which has the potential to combine bias reduction with optimal DA system performance. [ABSTRACT FROM AUTHOR]

This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second‐largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) spatiotemporal variability critically influences water resources, agriculture, and climate. However, besides site‐specific studies, little is known about how SM varies locally (1–100‐m scale). Consequently, quantifying the SM variability and its impact on the Earth system remains a long‐standing challenge in hydrology. We reveal the striking variability of local‐scale SM across the United States using SMAP‐HydroBlocks — a novel satellite‐based surface SM data set at 30‐m resolution. Results show how the complex interplay of SM with landscape characteristics and hydroclimate is primarily driven by local variations in soil properties. This local‐scale complexity yields a remarkable and unique multi‐scale behavior at each location. However, very little of this complexity persists across spatial scales. Experiments reveal that on average 48% and up to 80% of the SM spatial information is lost at the 1‐km resolution, with complete loss expected at the scale of current state‐of‐the‐art SM monitoring and modeling systems (1–25 km resolution). Plain Language Summary: Soil moisture (SM) widely varies in space and time. This variability critically influences freshwater availability, agriculture, ecosystem dynamics, climate and land‐atmosphere interactions, and it can also trigger hazards such as droughts, floods, landslides, and aggravate wildfires. Limited SM observational data constrained our understanding of this variability and its impact on the Earth system. Here, we present the first continental assessment of how SM varies at the local scales using SMAP‐HydroBlocks – the first 30‐m surface SM data set over the United States. This study maps the SM spatial variability, characterizes the landscape drivers, and quantifies how this variability persists across larger spatial scales. Results revealed striking SM spatial variability across the United States, mainly driven by local spatial variations in soil properties and less so by vegetation and topography. However, this SM variability does not persist at coarser spatial scales resulting in extensive information loss. This information loss implicates inaccuracies when predicting non‐linear SM‐dependent hydrological, ecological, and biogeochemical processes using coarse‐scale models and satellite estimates. By mapping the SM spatial variability locally and its scaling behavior, we provide a pathway toward understanding SM‐dependent hydrological, biogeochemical, and ecological processes at local (and so far unresolved) spatial scales. Key Points: 30‐m soil moisture (SM) data shows striking and complex spatial variability driven mainly by climate and local variations in soil propertiesThis variability yields a remarkable and unique multi‐scale behavior at each location that cannot be generalized across the diverse USUp to 80% of SM information is lost at the 1‐km scale, with complete loss at the scale of state‐of‐the‐art SM observation/monitoring systems [ABSTRACT FROM AUTHOR]

Drought is projected to become more severe and widespread as global warming continues in the twenty-first century, but hydroclimatic changes and their drivers are not well examined in the latest projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer drought severity index with Penman–Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the twenty-first century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia, although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ∼25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the twenty-first century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm, while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Intermodel spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections. SIGNIFICANCE STATEMENT: Drought may become more severe and widespread under greenhouse gas (GHG)-induced global warming in the twenty-first century based on model projections. However, there are still large uncertainties in projected future drought changes, especially regarding the extent to which drought changes depend on drought indices and the future emissions scenarios analyzed. The latest projections from CMIP6 models reaffirm the widespread drying and increases in agricultural drought by up to 200% over most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, Southeast Asia, and Australia under moderate-to-high emissions scenarios in the twenty-first century, despite large uncertainties in individual projections partly due to internal variability. Ubiquitous increases in atmospheric demand for moisture under rising temperatures and precipitation decreases over many subtropical regions are the main driver of the projected drying and drought increases. [ABSTRACT FROM AUTHOR]

Comparative hydrology has been hampered by limited availability of geographically extensive, intercompatible monitoring data on comprehensive water balance stores and fluxes. These limitations have, for example, restricted comprehensive assessment of multiple dimensions of wetting and drying related to climate change and hampered understanding of why widespread changes in precipitation extremes are uncorrelated with changes in streamflow extremes. Here, we address this knowledge gap and underlying data gap by developing a new data synthesis product and using that product to detect trends in the frequencies and magnitudes of a comprehensive set of hydroclimatic and hydrologic extremes. CHOSEN (Comprehensive Hydrologic Observatory Sensor Network) is a database of streamflow, soil moisture, and other hydroclimatic and hydrologic variables from 30 study areas across the United States. An accompanying data pipeline provides a reproducible, semi‐automated approach for assimilating data from multiple sources, performing quality assurance and control, gap‐filling and writing to a standard format. Based on the analysis of extreme events in the CHOSEN dataset, we detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida and Alaska. Extreme streamflow wetting and drying trends exhibited regional coherence. Drying trends in the Pacific Northwest and Southeast were often associated with trends in soil moisture and precipitation (Pacific Northwest) and evapotranspiration‐related variables (Southeast). In contrast, wetting trends in the upper Midwest and the Rocky Mountains showed few univariate associations with other hydroclimatic extremes, but their latitudes and elevations suggested the importance of changing snowmelt characteristics. On the whole, observed trends are incompatible with a 'drying‐in‐dry, wetting‐in‐wet' paradigm for climate‐induced hydrologic changes over land. Our analysis underscores the need for more extensive, longer‐term observational data for soil moisture, snow and evapotranspiration. [ABSTRACT FROM AUTHOR]

Climate change affects the hydrological cycle of river basins and strongly impacts water resource availability. The mechanistic hydrological model PROMET was driven with an ensemble of EURO-CORDEX regional climate model projections under the emission scenarios RCP2.6 and RCP8.5 to analyze changes in temperature, precipitation, soil water content, plant water stress, snow water equivalent (SWE) and runoff dynamics in the Danube River Basin (DRB) in the near (2031–2060) and far future (2071–2100) compared to the historical reference (1971–2000). Climate change impacts remain moderate for RCP2.6 and become severe for RCP8.5, exhibiting strong year-round warming trends in the far future with wetter winters in the Upper Danube and drier summers in the Lower Danube, leading to decreasing summer soil water contents, increasing plant water stress and decreasing SWE. Discharge seasonality of the Danube River shifts toward increasing winter runoff and decreasing summer runoff, while the risk of high flows increases along the entire Danube mainstream and the risk of low flows increases along the Lower Danube River. Our results reveal increasing climate change-induced discrepancies between water surplus and demand in space and time, likely leading to intensified upstream–downstream and inter-sectoral water competition in the DRB under climate change.

The Niwot Ridge and Green Lakes Valley (NWT) long‐term ecological research (LTER) site collects environmental observations spanning both alpine and subalpine regimes. The first observations began in 1952 and have since expanded to nearly 300 available datasets over an area of 99 km2 within the north‐central Colorado Rocky Mountains that include hydrological (n = 101), biological (n = 79), biogeochemical (n = 62), and geographical (n = 56) observations. The NWT LTER database is well suited to support hydrologic investigations that require long‐term and interdisciplinary data sets. Experimentation and data collection at the NWT LTER are designed to characterize ecological responses of high‐mountain environments to changes in climate, nutrients, and water availability. In addition to the continuation of the many legacy NWT datasets, expansion of the breadth and utility of the NWT LTER database is driven by new initiatives including (a) a catchment‐scale sensor network of soil moisture, temperature, humidity, and snow‐depth observations to understand hydrologic connectivity and (b) snow‐albedo alteration experiments using black sand to evaluate the effects of snow‐disappearance on ecosystems. Together, these observational and experimental datasets provide a substantial foundation for hydrologic studies seeking to understand and predict changes to catchment and local‐scale process interactions. [ABSTRACT FROM AUTHOR]

Soil moisture and evapotranspiration (ET) are important components of boreal forest hydrology that affect ecological processes and land‐atmosphere feedbacks. Future trends in soil moisture in particular are uncertain. Therefore, accurate modeling of these dynamics and understanding of concomitant sources of uncertainty are critical. Here, we conduct a global sensitivity analysis, Monte Carlo parameterization, and analysis of parameter uncertainty and its contribution to future soil moisture and ET uncertainty using a physically based ecohydrologic model in multiple boreal forest types. Soil and plant hydraulic parameters and LAI have the largest effects on simulated summer soil moisture at two contrasting sites. In future scenario simulations, the selection of parameters and global climate model (GCM) choice between two GCMs influence projected changes in soil moisture and ET about as much as the projected effects of climate change in the less sensitive GCM with a late‐century, high‐emissions scenario, though the relative effects of parameters, GCM, and climate vary among hydrologic variables and study sites. Saturated volumetric water content and sensitivity of stomatal conductance to vapor pressure deficit have the most statistically significant effects on change in ET and soil moisture, though there is considerable variability between sites and GCMs. The results of this study provide estimates of: (a) parameter importance and statistical significance for soil moisture modeling, (b) parameter values for physically based soil‐vegetation‐atmosphere transfer models in multiple boreal forest types, and (c) the contributions of uncertainty in these parameters to soil moisture and ET uncertainty in future climates. Plain Language Summary: Future changes in soil water content and evapotranspiration (ET) in boreal regions will influence forest dynamics, permafrost thaw rates and have the potential to alter feedbacks between the land surface and the atmosphere, potentially influencing regional climate dynamics. These changes are uncertain and difficult to model because of the complexity of the boreal ecological and hydrological systems. In this study, we conduct experiments with a hydrological model to better understand which parameters most influence soil water content and ET, how much uncertainty these parameters contribute, and how specific parameter values affect whether soils become wetter or drier and by how much. We find that the parameters that control how tightly soils retain water and how much plants close their stomata and hence reduce transpiration in response to dry conditions, have the largest influences. Interactions between parameters are also important. Even when these parameter values are constrained by model performance in comparison with observations, parameter choice can determine whether soils become wetter or drier in future conditions. These findings suggest that modelers should carefully consider how parameter selection influences simulated future hydrologic conditions and highlight specific parameters that are worthy of further attention. Key Points: Modeled summer soil moisture at rooting depth is most sensitive to soil and plant hydraulic parameters and parameter interactions.Parameter uncertainty affects projected change in evapotranspiration and θVWC about as much as climate change or choice between two global climate models.We present parameter values useful for hydrologic modeling in multiple boreal forest types while quantifying the impacts of equifinality. [ABSTRACT FROM AUTHOR]

The ecosystem services provided by forests modulate runoff generation processes, nutrient cycling and water and energy exchange between soils, vegetation and atmosphere. Increasing atmospheric CO2 affects many linked aspects of forest and catchment function in ways we do not adequately understand. Global levels of atmospheric CO2 will be around 40% higher in 2050 than current levels, yet estimates of how water and solute fluxes in forested catchments will respond to increased CO2 are highly uncertain. The Free Air CO2 Enrichment (FACE) facility of the University of Birmingham's Institute of Forest Research (BIFoR) is the only FACE in mature deciduous forest. The site specializes in fundamental studies of the response of whole ecosystem patches of mature, deciduous, temperate woodland to elevated CO2 (eCO2). Here, we describe a dataset of hydrological parameters – seven weather parameters at each of three heights and four locations, shallow soil moisture and temperature, stream hydrology and CO2 enrichment – retrieved at high frequency from the BIFoR FACE catchment. [ABSTRACT FROM AUTHOR]

The capture and use of water are critically important in drylands, which collectively constitute Earth's largest biome. Drylands will likely experience lower and more unreliable rainfall as climatic conditions change over the next century. Dryland soils support a rich community of microphytic organisms (biocrusts), which are critically important because they regulate the delivery and retention of water. Yet despite their hydrological significance, a global synthesis of their effects on hydrology is lacking. We synthesized 2,997 observations from 109 publications to explore how biocrusts affected five hydrological processes (times to ponding and runoff, early [sorptivity] and final [infiltration] stages of water flow into soil, and the rate or volume of runoff) and two hydrological outcomes (moisture storage, sediment production). We found that increasing biocrust cover reduced the time for water to pond on the surface (−40%) and commence runoff (−33%), and reduced infiltration (−34%) and sediment production (−68%). Greater biocrust cover had no significant effect on sorptivity or runoff rate/amount, but increased moisture storage (+14%). Infiltration declined most (−56%) at fine scales, and moisture storage was greatest (+36%) at large scales. Effects of biocrust type (cyanobacteria, lichen, moss, mixed), soil texture (sand, loam, clay), and climatic zone (arid, semiarid, dry subhumid) were nuanced. Our synthesis provides novel insights into the magnitude, processes, and contexts of biocrust effects in drylands. This information is critical to improve our capacity to manage dwindling dryland water supplies as Earth becomes hotter and drier. [ABSTRACT FROM AUTHOR]

Cold region hydrology is conditioned by distinct cryospheric and hydrological processes. While snowmelt is the main contributor to both surface and subsurface flows, seasonally frozen soil also influences the partition of meltwater and rain between these flows. Cold regions of the Northern Hemisphere midlatitudes have been shown to be sensitive to climate change. Assessing the impacts of climate change on the hydrology of this region is therefore crucial, as it supports a significant amount of population relying on hydrological services and subjected to changing hydrological risks. We present an exhaustive review of the literature on historical and projected future changes on cold region hydrology in response to climate change. Changes in snow, soil, and streamflow key metrics were investigated and summarized at the hemispheric scale, down to the basin scale. We found substantial evidence of both historical and projected changes in the reviewed hydrological metrics. These metrics were shown to display different sensitivities to climate change, depending on the cold season temperature regime of a given region. Given the historical and projected future warming during the 21st century, the most drastic changes were found to be occurring over regions with near-freezing air temperatures. Colder regions, on the other hand, were found to be comparatively less sensitive to climate change. The complex interactions between the snow and soil metrics resulted in either colder or warmer soils, which led to increasing or decreasing frost depths, influencing the partitioning rates between the surface and subsurface flows. The most consistent and salient hydrological responses to both historical and projected climate change were an earlier occurrence of snowmelt floods, an overall increase in water availability and streamflow during winter, and a decrease in water availability and streamflow during the warm season, which calls for renewed assessments of existing water supply and flood risk management strategies. [ABSTRACT FROM AUTHOR]

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010–2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon–climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes. [ABSTRACT FROM AUTHOR]

Stratospheric sulfate aerosol geoengineering has been proposed as a potential strategy to reduce the impacts of climate change. Here we investigate the impact of stratospheric aerosol geoengineering on the terrestrial hydrological cycle. We use the Geoengineering Large Ensemble, which involves a 20‐member ensemble of simulations using the Community Earth System Model with the Whole Atmosphere Community Climate Model, in which sulfur dioxide (SO2) was injected into the stratosphere at four different locations, to maintain global mean surface temperature, and also the interhemispheric and equator‐to‐pole temperature gradients at values representative of 2020 ("baseline") under the Representative Concentration Pathway 8.5. In our simulations, annual mean land precipitation and evapotranspiration (ET) increase by 12% each under Representative Concentration Pathway 8.5. Under the Geoengineering Large Ensemble, the hydrological cycle is suppressed compared to the baseline, with end‐of‐century decreases of 1.4% (12 ± 5 mm/year) and 3.3% (18 ± 2 mm/year) in global mean, annual mean precipitation, and ET over land, respectively. Geoengineering effectively maintains global mean soil moisture under a high CO2 scenario, although there is significant regional variability. Summertime soil moisture is reduced by 42 ± 11 kg/m2 (3.5%) and 27 ± 16 kg/m2 (2.1%) in India and the Amazon, respectively, which is dominated by the decrease in precipitation. We also compare these regional changes in soil moisture under the Geoengineering Large Ensemble with an equatorial‐only SO2 injection case and find a similar sign in residual changes, although the magnitude of the changes is larger in the equatorial run. Key Points: In our simulations, geoengineering effectively maintains global mean soil moisture under a high CO2 scenario, but some regional changes remainSummertime soil moisture is reduced in India and the Amazon under geoengineering; this change is dominated by the change in precipitationGeoengineering using multiple injection locations yields smaller magnitude of changes in soil moisture than equatorial‐only injection [ABSTRACT FROM AUTHOR]

This study details climate change assessment of the hydrological regime of Indrawati basin of Nepal. The study uses Soil and Water Assessment Tool (SWAT) model to delineate, discretize and parameterize the Indrawati basin to compute model's input parameters. The model was then run for 1990–2014 to simulate the discharge at the outlet (Dholalghat). The coefficient of determination R2 and Nash-Sutcliffe (ENS) were used to evaluate model calibration and validation. The results found were satisfactory for the gauging station R2 = 0.951 and ENS = 0.901 for calibration and R2 = 0.937 and. ENS = 0.906 for validation. The calibrated hydrological model was run for the future climate change scenario using the RegCM4-LMDZ4 data and the relative changes with the baseline scenarios were analyzed. The comparison suggests that the historical trend of flow is decreasing at the rate of 0.55 m3/s per year. According to RegCM4-LMDZ4 simulations, the trend is going to continue but at a flatter rate. The decreasing trend is observed to be very less. The characteristic peak flow month in the historical scenario is August but the RegCM4-LMDZ4 led simulated flows suggest a shift in monthly peak to October suggesting decrease in monsoon flows and a subsequent significant increase in flows from October to January. [ABSTRACT FROM AUTHOR]

Permafrost is an important indicator of climate change that affects, e.g., ecosystems, hydrology, and infrastructure in cold regions. Interactions between the surface and atmosphere in permafrost regions are complex and vary seasonally due to the contrasting energy and moisture conditions of frozen versus unfrozen ground. Differences in surface‐atmosphere connections have been documented between permafrost types, with significantly increased moisture feedbacks in areas of continuous Eurasian permafrost, but no such relationship in other regions. This study elucidates the processes responsible for these observed land‐atmosphere feedbacks in Eurasian permafrost regions. The Weather Research and Forecasting model is used to determine the varying effects of discontinuous versus continuous permafrost on different weather scenarios. For two 72‐hour periods, surface fluxes, boundary layer characteristics, and corresponding meso‐to‐synoptic scale meteorological features varied when comparing the two experiments: one with a saturated active layer representing continuous permafrost, and another witht1 a drier surface layer representing discontinuous permafrost. Depending on the weather regime, an increase in boundary layer moisture in response to increased latent heat fluxes over continuous permafrost increases precipitation and low‐level cloudiness. The effects of changing soil conditions are evident as far aloft as 500 hPa, as a mid‐level low over continuous permafrost is stronger and moves southward. Incipient moisture associated with continuous permafrost allows for different land‐atmosphere interactions than over discontinuous permafrost. Continued permafrost degradation as a result of climate change may lead to increased dryness in the region, altering the surface energy balance and associated weather and climate feedbacks. Key Points: Changes in soil characteristics consistent with different permafrost (PF) types lead to modifications of lower troposphere moisture profileSimulations over discontinuous PF show decreased low‐level cloudiness and decreased precipitation relative to continuous PFGeophysical impacts of degrading PF, including atmospheric feedbacks, should be a devoted focus of research in the future [ABSTRACT FROM AUTHOR]

The objective of this study is to assess future changes in meteorological, hydrology and agricultural droughts under the impact of changing climate in the Srepok River Basin, a subbasin of LMB, using three drought indices; standardized precipitation index (SPI), standardized runoff index (SRI) and standardized soil moisture index (SSWI). The well‐calibrated Soil and Water Assessment Tool (SWAT) is used as a simulation tool to estimate the features of meteorological, hydrological and agricultural droughts. The climate data for the 2016–2040 period is obtained from four different regional climate models; HadGEM3‐RA, SNU‐MM5, RegCM4 and YSU‐RSM, which are downscaled from the HadGEM2‐AO GCM. The results show that the severity, duration and frequency of droughts are predicted to increase in the near future for this region. Moreover, the meteorological drought is less sensitive to climate change than the hydrological and agricultural droughts; however, it has a stronger correlation with the hydrological and agricultural droughts as the accumulation period is increased. These findings may be useful for water resources management and future planning for mitigation and adaptation to the climate change impact in the Srepok River Basin. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security. Key Points: Recent soil moisture measurement and monitoring techniques and estimation models from the point to the global scales and their limitations are presentedThe importance and application of soil moisture information for various Earth and environmental sciences disciplines such as forecasting weather and climate variability, modeling hydrological processes, and predicting and monitoring extreme events and their impacts on the environment and human society are presented [ABSTRACT FROM AUTHOR]

Adaptation to climate change is a major challenge facing the agricultural sector worldwide. Olive (Olea europaea L.) is a global, high value crop currently cultivated in 28 countries worldwide. Global data to assess the vulnerability of the crop to climate variability are scarce, and in some notable cases, such the United Nations Food and Agricutlure Organization database (FAO, 2006), qualitative assessments rather than quantitative indicators are provided. The aim of this study is to demonstrate a new approach to help overcome these constraints toward a globally applicable method to assess the adaptability of olive cultivars. The adaptability of 11 cultivars, widely used in 11 countries worldwide, was studied using a new generic approach based on the evaluation of soil hydrological regime against cultivar-specific hydrological requirements. The approach requires local data, notably on soil hydrological properties, but it is easily transferable to other countries and regions. We applied an agrohydrological model in 60 soil units to determine hydrological indicators both in a reference (1961-1990) and a future (2021-2050) climate case. We compared indicators with cultivar-specific requirements to achieve the target yield; requirements were established using experimental yield response curves. We estimated the probability of adaptation, i.e., the probability that a given cultivar attains the target yield, and we used it to evaluate the cultivar potential distribution in the study area. At the locations where soil hydrological conditions were favorable, the probabilities of adaptation of the cultivars were high in both climate cases. The results show that the area with suitable conditions for the target yield (area of adaptability) decreased under future climate for all the cultivars, with higher reduction for Frantoio and Maiatica and smaller reduction for Itrana, Nocellara, Ascolana, and Kalamata. These cultivars are currently grown in Argentina, United States (US), Australia, France, Greece, and Italy. Our results indicate also that these cultivars require higher available soil water to attain the target yield, i.e., we may expect similar vulnerability in other parts of the world. Based on these findings, we provide some specific recommendations for enrichment of global databases and for further developments of our approach, to increase its potential for global application. [ABSTRACT FROM AUTHOR]

Soil moisture data are critical to understanding biophysical and societal impacts of climate change. However, soil moisture data availability is limited due to sparse in situ monitoring, particularly in mountain regions. Here we present methods, specifications, and initial results from the interactive Roaring Fork Observation Network (iRON), a soil, weather, and ecological monitoring system in the Southern Rocky Mountains of Colorado. Initiated in 2012, the network is currently composed of nine stations, distributed in elevation from 1,890 to 3,680 m, that continually collect and transmit measurements of soil moisture at three depths (5, 20, and 50 cm), soil temperature (20 cm), and meteorological conditions. Time‐lapse cameras for phenological observations, snow depth sensors, and periodic co‐located vegetation surveys complement selected stations. iRON was conceived and designed with the joint purpose of supporting bioclimatic research and resource management objectives in a snow‐dominated watershed. In the short term, iRON data can be applied to assessing the impact of temperature and precipitation on seasonal soil moisture conditions and trends. As more data are collected over time, iRON will help improve understanding of climate‐driven changes to soil, vegetation, and hydrologic conditions. In presenting this network and its initial data, we hope that the network's elevational gradient will contribute to bioclimatic mountain research, while active collaboration with partners in resource management may provide a model for science‐practice interaction in support of long‐term monitoring. Plain Language Summary: As climate change drives shifts in temperature and precipitation, researchers and resource managers can benefit from improved monitoring of soil moisture. Understanding the relationship between soil moisture and other system components is crucial to improving water availability projections and understanding ecosystem responses to climate change. Despite their significance, in‐ground soil‐moisture measurements are often not available across multiple elevations within a single watershed. This paper presents a network in the Southern Rocky Mountains intended to help address this data gap and compliment data from other networks. The interactive Roaring Fork Observation Network consists of nine locations across an 1,800‐m change in elevation. Each station measures soil moisture at three depths, soil temperature, air temperature, humidity, and precipitation. Some stations are equipped with cameras or snow depth gauges, and for eight sites vegetation surveys are conducted. The data are available through a simple data portal. The network was established with local resource manager support, and one of its guiding purposes is to support management and restoration planning efforts. Because of the network's ongoing monitoring across multiple elevations and habitats, interactive Roaring Fork Observation Network will provide researchers and resource managers with access to valuable information about changes in soil conditions in a changing climate. Key Points: Soil moisture is key to understanding and predicting change in hydrology and ecology amid climate variability and changeIn situ soil moisture and weather monitoring data are now available across an 1,800‐m elevation span in a mountain watershedThe network is supported and guided by resource managers and supports both research and resource management goals [ABSTRACT FROM AUTHOR]

Extreme temperatures are responsible for damages to society and ecosystems. There is evidence that severe episodes of extreme heat have been occurring more frequently and more severely in recent periods. Driven primarily by oceanic and atmospheric effects as well as land‐climate feedbacks, those extreme events are expected to increase with climate change. Vegetation, which regulates the energy, water, and carbon cycles, is a key player of land‐atmosphere interactions that has been proven to be determinant in recent extreme events. Using an ensemble of Earth System Models simulations, we show that physiological effects globally increase the annual daily maximum temperature (Txx) with rising [CO2], accounting globally for around 13% of the full Txx trend. Due to physiological effects, Txx can reinforce (e.g., central Europe) or reduce (e.g., central North America) the mean temperature increase. Plain Language Summary: Heat waves cause damages to society and natural environment. We observed a trend of increasing frequency and intensity of extreme temperature episodes in recent years. Climate change on one side and the complex feedbacks of the climate with the land on the other side are the main drivers of this trend. Vegetation is an important factor of the feedback as it connects the land surface and the atmosphere, regulating the exchanges of water and heat. Using an ensemble of Earth System Models simulations, we show that the effects of vegetation globally increase extreme temperatures with rising [CO2], accounting globally for around 13% of the full trend. This effect can, however, regionally be larger (e.g., central Europe) or smaller (e.g., central North America) than the mean temperature increase. Key Points: Physiological effects increase the annual daily maximum temperature (Txx) with rising [CO2], accounting globally for around 15% of its trendThe Txx increasing trends can be reinforced by vegetation physiological feedbacks, especially in regions like Europe or the AmazonIn several regions, such as North America, vegetation physiological feedbacks can oppositely mitigate the radiatively driven increase in Txx [ABSTRACT FROM AUTHOR]

Soil moisture is projected to decrease in many regions in the 21st century, exacerbating local temperature extremes. Here, we use sensitivity experiments to assess the potential of keeping soil moisture conditions at historical levels in the 21st century by "recycling" local water sources (runoff and a reservoir). To this end, we develop a "land water recycling" (LWR) scheme which applies locally available water to the soil if soil moisture drops below a predefined threshold (a historical climatology), and we assess its influence on the hydrology and extreme temperature indices. We run ensemble simulations with the Community Earth System Model for the 21st century and show that our LWR scheme is able to drastically reduce the land area with decreasing soil moisture. Precipitation responds to LWR with increases in mid-latitudes, but decreases in monsoon regions. While effects on global temperature are minimal, there are very substantial regional impacts on climate. Higher evapotranspiration and cloud cover in the simulations both contribute to a decrease in hot temperature extremes. These decreases reach up to about -1 ∘ C regionally, and are of similar magnitude to the regional climate changes induced by a 0.5 ∘ C difference in the global mean temperature, e.g. between 1.5 and 2 ∘ C global warming. [ABSTRACT FROM AUTHOR]

Many parts of the world are experiencing a drying climatic trend with significant implications for water resources, especially where there is interaction between surface water and groundwater. Where drying leads to a shift in a catchment's hydrological regime, hydrological models may display bias in predictions and therefore degradation in their predictive capacity. We present two modifications to GR4J, a commonly used rainfall–run‐off model, that (a) allow the sensitivity of storage dependant evaporation and streamflow production to differ significantly, effectively mimicking "catchment memory" and (b) account for temporal variation in catchment vegetation cover, for example, due to land use change. We test the original and two modified models on a forested headwater catchment in the south‐west of Australia. In this catchment, a data set of more than 21,000 individual groundwater records collected over a period of more than 40 years chronicles a significant decline in catchment groundwater storage, resulting in a nonstationary streamflow regime. These longer‐term changes were overlaid with a shorter‐term hydrological response to clearing for bauxite mining and subsequent revegetation. The model structural modifications led to substantially improved streamflow prediction when compared with the original model, related to improved ability in the revised models' production store to match changes in the observed groundwater storage within the catchment. The performance of all three models and hence the apparent effectiveness of the modified models was dependent on the hydrological conditions in the calibration period. Best model fits were obtained when the calibration period encompassed both wetter and drier conditions in the hydrological record. The modified models presented here may reduce prediction bias for catchments in other parts of the world where long‐term shifts in hydrologic regime are being experienced and improve prediction for catchments with significant changes in vegetation cover. [ABSTRACT FROM AUTHOR]

Planet Earth is undergoing significant changes which are driven by natural and anthropogenic factors. However, it is difficult to identify the drivers and their effect on the environment and ecosystems because there are many interdependencies. In this study we present a multi-parameter approach to assess the effect of changes in human-induced and natural drivers on a wetland ecosystem. The study area is one of the most prominent European wetlands: the Biebrza Basin, located in north-eastern Poland. We analysed long-term (ca. 1960-2000) changes in meteorology, hydrology, soil and vegetation, and also conservation history. This approach enabled us to identify interactions between environmental change and management. We found significant trends (1960-2012) indicating climate change: increases in temperature, evapotranspiration and earlier start of spring floods. We identified (1970-2000) a shift towards drier vegetation types after drainage. However, we also found that restoration measures that were implemented have mitigated climate change effects and have led to increases in soil moisture and wetter vegetation types. We conclude that, if carried out sufficiently frequently, the management measures implemented in the Biebrza Basin, which are a combination of different restoration measures (blocking drainage, not clearing aquatic vegetation, bush removal, mowing), can to some extent mitigate the effects of climate change. [ABSTRACT FROM AUTHOR]

The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods. [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]

Abstract: Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency. [ABSTRACT FROM AUTHOR]

The circumpolar expansion of woody deciduous shrubs in arctic tundra alters key ecosystem properties including carbon balance and hydrology. However, landscape-scale patterns and drivers of shrub expansion remain poorly understood, inhibiting accurate incorporation of shrub effects into climate models. Here, we use dendroecology to elucidate the role of soil moisture in modifying the relationship between climate and growth for a dominant deciduous shrub, Salix pulchra, on the North Slope of Alaska, USA. We improve upon previous modeling approaches by using ecological theory to guide model selection for the relationship between climate and shrub growth. Finally, we present novel dendroecology-based estimates of shrub biomass change under a future climate regime, made possible by recently developed shrub allometry models. We find that S. pulchra growth has responded positively to mean June temperature over the past 2.5 decades at both a dry upland tundra site and an adjacent mesic riparian site. For the upland site, including a negative second-order term in the climate-growth model significantly improved explanatory power, matching theoretical predictions of diminishing growth returns to increasing temperature. A first-order linear model fit best at the riparian site, indicating consistent growth increases in response to sustained warming, possibly due to lack of temperature-induced moisture limitation in mesic habitats. These contrasting results indicate that S. pulchra in mesic habitats may respond positively to a wider range of temperature increase than S. pulchra in dry habitats. Lastly, we estimate that a 2°C increase in current mean June temperature will yield a 19% increase in aboveground S. pulchra biomass at the upland site and a 36% increase at the riparian site. Our method of biomass estimation provides an important link toward incorporating dendroecology data into coupled vegetation and climate models. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) content is one of the most important environmental variables in relation to land surface climatology, hydrology, and ecology. Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions. The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data. The study area is Tuv (48°40′30″N and 106°15′55″E) province in the forest steppe zones in Mongolia. In addition to this, land surface temperature (LST) and normalized difference vegetation index (NDVI) from Landsat satellite images were integrated for the assessment. Furthermore, we used a digital elevation model (DEM) from ASTER satellite image with 30-m resolution. Aspect and slope maps were derived from this DEM. The soil moisture index (SMI) was obtained using spectral information from Landsat satellite data. We used regression analysis to develop the model. The model shows how SMI from satellite depends on LST, NDVI, DEM, Slope, and Aspect in the agricultural area. The results of the model were correlated with the ground SM data in Tuv province. The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area. Further research is focused on moisture mapping for different natural zones in Mongolia. The innovative part of this research is to estimate SM using drivers which are vegetation, land surface temperature, elevation, aspect, and slope in the forested steppe area. This integrative methodology can be applied for different regions with forest and desert steppe zones. [ABSTRACT FROM AUTHOR]

Increasing concentrations of atmospheric carbon dioxide are expected to affect carbon assimilation and evapotranspiration (ET), ultimately driving changes in plant growth, hydrology, and the global carbon balance. Direct leaf biochemical effects have been widely investigated, whereas indirect effects, although documented, elude explicit quantification in experiments. Here, we used a mechanistic model to investigate the relative contributions of direct (through carbon assimilation) and indirect (via soil moisture savings due to stomatal closure, and changes in leaf area index) effects of elevated CO2 across a variety of ecosystems. We specifically determined which ecosystems and climatic conditions maximize the indirect effects of elevated CO2. The simulations suggest that the indirect effects of elevated CO2 on net primary productivity are large and variable, ranging from less than 10% to more than 100% of the size of direct effects. For ET, indirect effects were, on average, 65% of the size of direct effects. Indirect effects tended to be considerably larger in water-limited ecosystems. As a consequence, the total CO2 effect had a significant, inverse relationship with the wetness index and was directly related to vapor pressure deficit. These results have major implications for our understanding of the CO2 response of ecosystems and for global projections of CO2 fertilization, because, although direct effects are typically understood and easily reproducible in models, simulations of indirect effects are far more challenging and difficult to constrain. Our findings also provide an explanation for the discrepancies between experiments in the total CO2 effect on net primary productivity. [ABSTRACT FROM AUTHOR]

Increasing concentrations of atmospheric carbon dioxide are expected to affect carbon assimilation and evapotranspiration (ET), ultimately driving changes in plant growth, hydrology, and the global carbon balance. Direct leaf biochemical effects have been widely investigated, whereas indirect effects, although documented, elude explicit quantification in experiments. Here, we used a mechanistic model to investigate the relative contributions of direct (through carbon assimilation) and indirect (via soil moisture savings due to stomatal closure, and changes in leaf area index) effects of elevated CO2 across a variety of ecosystems. We specifically determined which ecosystems and climatic conditions maximize the indirect effects of elevated CO2. The simulations suggest that the indirect effects of elevated CO2 on net primary productivity are large and variable, ranging from less than 10% to more than 100% of the size of direct effects. For ET, indirect effects were, on average, 65% of the size of direct effects. Indirect effects tended to be considerably larger in water-limited ecosystems. As a consequence, the total CO2 effect had a significant, inverse relationship with the wetness index and was directly related to vapor pressure deficit. These results have major implications for our understanding of the CO2 response of ecosystems and for global projections of CO2 fertilization, because, although direct effects are typically understood and easily reproducible in models, simulations of indirect effects are far more challenging and difficult to constrain. Our findings also provide an explanation for the discrepancies between experiments in the total CO2 effect on net primary productivity. [ABSTRACT FROM AUTHOR]

Multiple drought episodes over the Volta basin in recent reports may lead to food insecurity and loss of revenue. However, drought studies over the Volta basin are rather generalised and largely undocumented due to sparse ground observations and unsuitable framework to determine their space-time occurrence. In this study, we examined the utility of standardised indicators (standardised precipitation index (SPI), standardised runoff index (SRI), standardised soil moisture index (SSI), and multivariate standardised drought index (MSDI)) and Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water storage to assess hydrological drought characteristics over the basin. In order to determine the space-time patterns of hydrological drought in the basin, Independent Component Analysis (ICA), a higher order statistical technique was employed. The results show that SPI and SRI exhibit inconsistent behaviour in observed wet years presupposing a non-linear relationship that reflects the slow response of river discharge to precipitation especially after a previous extreme dry period. While the SPI and SSI show a linear relationship with a correlation of 0.63, the correlation between the MSDIs derived from combining precipitation/river discharge and precipitation/soil moisture indicates a significant value of 0.70 and shows an improved skill in hydrological drought monitoring over the Volta basin during the study period. The ICA-derived spatio-temporal hydrological drought patterns show Burkina Faso and the Lake Volta areas as predominantly drought zones. Further, the statistically significant negative correlations of pacific decadal oscillations (0.39 and 0.25) with temporal evolutions of drought in Burkina Faso and Ghana suggest the possible influence of low frequency large scale oscillations in the observed wet and dry regimes over the basin. Finally, our approach in drought assessment over the Volta basin contributes to a broad framework for hydrological drought monitoring that will complement existing methods while looking forward to a longer record of GRACE observations. [ABSTRACT FROM AUTHOR]

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models ( AOGCMs) ( CCSM3, Had CM3, PCM, and GFDL- CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model Pn ET- BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays a fundamental role for many hydrological applications including water resources, drought analysis, agriculture, and climate variability and extremes. SM is not measured in most parts of Iran and limited measurements do not meet sufficient temporal and spatial resolution. Hence, due to ease of operation, their global coverage and demonstrated accuracy, use of remote sensing SM products is almost the only way for deriving SM information in Iran. In the present research, surface SM (SSM) datasets at six subregions of Iran with different climate conditions were extracted from two satellite-based passive (SMOSL3) and active + passive (ESA CCI SM) microwave observations, and two reanalysis (ERA-Interim and ERA-Interim/Land) products. Time series of averaged monthly mean SSM products and in situ ground precipitation and temperature measurements were derived for each subregion. Results revealed that, generally, all SSM products were in good agreement with each other with correlation coefficients higher than 0.5. The better agreement was found in the Northeast and Southwest region with average correlation values equal to 0.88 and 0.91, respectively. It should be noted that the SSM datasets are characterized by different periods and lengths. Hence, results should be assessed with cautious. Moreover, most SSM products have strong correlations with maximum, minimum and average temperature as well as with total monthly precipitation. Also, trend analysis showed no trend for time series of monthly SSM over all subregions in the two periods 1980–1999 and 2000–2014. The only exceptions were the Southeast subregion for ERA-Interim and Center and Northwest subregions for the ESA CCI SM for which a negative trend was detected for the period 2000–2014. Finally, the Standardized Soil Moisture Index (SSI) calculated from ERA-Interim, ERA-I/Land and ESA CCI SM datasets showed that the Center and Southeast regions suffered from the most severe and longest-lasting drought events in the last decade. [ABSTRACT FROM AUTHOR]

The soil-water interaction is crucial for effective hydrological processes determination. The soil moisture (SM) is an important parameter to provide priori information for the interactions imparting and affecting the energy fluxes response for such kind of processes. This work investigated the effects of climatic, geophysical and hydrological parameters on SM at 9 stations within Utah State, USA, for daily data recorded between 2010 and 2012 at 5 different soil depths (approximately 5, 10, 20, 50, and 100 cm). A high correlation was found for soil temperature, evapotranspiration (ET), and surface temperature, respectively, in most of the stations at either α = 5 % or 1 %. All stations exhibited a downward trend in SM for the top three soil depths, whereas, for other depths some stations depicted an upward trend. From time series analysis, it was found that surface average temperature, ET and soil temperature varied on seasonal basis with maximum in June and minimum in January of each year. In addition, SM availability in the top 5 cm of soil depth showed more significance for having strong correlation with hydroclimatic variables and were essential in interpreting many hydrological processes. From analyses at shallow soil depths (5 and 10 cm), the spatial SM variability across the stations was consistent during winter and spring whereas inconsistent during summer and autumn. In addition, the SM exhibited a temporal cyclic variability for almost all stations. [ABSTRACT FROM AUTHOR]

Soil moisture plays an integral role in multi-scale hydrologic modeling, agricultural decision analysis, climate change assessments, and drought prediction/prevention. The broad availability of soil moisture estimates has only occurred within the past decade through a combination of in situ networks and satellite-driven remote sensing. The U.S. Climate Reference Network (USCRN) has provided a nationwide in situ resource since 2009. The Advanced Microwave Scanning Radiometer (AMSR-E), launched in 2002, is one of the satellite products available for comparison, but there are a limited number of years where the data records overlap. This study compares the results of modeled historical soil moisture estimates derived using USCRN precipitation data to the remotely sensed estimates provided by the AMSR-E satellite between 2002 and 2011. First, this work assesses the calibrated model's similarity to in situ estimates. Next, the model estimates and in situ measurements are shown to perform comparably well against the AMSR-E satellite product, suggesting that it may be possible to utilize modeled estimates at times and locations where satellite estimates are unavailable and further extend the soil moisture record spatially and temporally. [ABSTRACT FROM AUTHOR]

Soil and Water Assessment Tool (SWAT) is widely used for watershed-scale assessment of climate change impacts, but post-processing of model outputs is a tedious job. An R tool was developed in this study for batch processing of SWAT output results. A case study was then performed in the Double Mountain Fork Brazos watershed in the Texas Panhandle using an improved SWAT model with the R tool to evaluate the simulated future changes in water balance components, total nitrogen (TN) load, and crop growth over the watershed. The results showed that the average annual future surface runoff increased by 8.9–17.9 mm and 11.5–22.6 mm in the irrigated and dryland cotton areas, respectively. Similarly, future TN load in irrigated and dryland cotton areas increased by approximately 0.4–0.9 kg ha−1 and 1.9–2.4 kg ha−1. The yields of irrigated and dryland cotton increased by 91.1%–122.1% and 47.5%–84.0% under the future climate scenarios, respectively. [Display omitted] • An algorithm for rapidly post-processing SWAT output.hru data was developed. • SWAT-MAD model was driven by bias-corrected CMIP6 data for impact assessments. • Future CO 2 , temperatures, radiation, runoff, and N loss were projected to increase. • Decreases in irrigation and actual ET were found for 2071–2100 SSP5-8.5 scenario. • Both irrigated and dryland cotton yields were projected to increase in the future. [ABSTRACT FROM AUTHOR]

Integrated hydrologic models coupled to land surface models link water and energy movement among the subsurface, land surface, and atmosphere. These connections are especially important when estimating a complex, nonlinear process like evaporation. A comprehensive sensitivity study of an evaporation parameterization was conducted using the integrated ParFlow-Common Land Model (PF-CLM). Estimates of ground evaporation using three forms of the same equation, two simplified closed-form solutions and one fully-coupled PF-CLM equation, are systematically compared. The parameterizations vary in complexity, coupling strength, and nonlinearity. Forcing data from three climate regions (alpine, plains, and tropical) are used to compare estimates of bare ground evaporation across all three formulations, thus exploring the process and coupling sensitivity in a novel way. The overall behavior of ground evaporation is consistent throughout the year for all parameterizations, but magnitudes vary with respect to parameterization complexity during energy-limited and water-limited times of the year. A relationship between ground evaporation and ground temperature is shown to exist across all climates and aggregate by pressure, wind speed, and air temperature in the plains climate. Furthermore, results show how increasing complexity through the addition of land surface conditions, atmospheric conditions, and atmospheric stability uniquely compound to influence the relationship between bare ground evaporation and subsurface pressure. Identification of sensitive interactions and unique relationships is necessary to further understand and predict hydrologic processes like evaporation. [ABSTRACT FROM AUTHOR]

Advances in Earth Observation (EO) technology, particularly over the last two decades, have shown that soil moisture content (SMC) can be measured to some degree or other by all regions of the electromagnetic spectrum, and a variety of techniques have been proposed to facilitate this purpose. In this review we provide a synthesis of the efforts made during the last 20 years or so towards the estimation of surface SMC exploiting EO imagery, with a particular emphasis on retrievals from microwave sensors. Rather than replicating previous overview works, we provide a comprehensive and critical exploration of all the major approaches employed for retrieving SMC in a range of different global ecosystems. In this framework, we consider the newest techniques developed within optical and thermal infrared remote sensing, active and passive microwave domains, as well as assimilation or synergistic approaches. Future trends and prospects of EO for the accurate determination of SMC from space are subject to key challenges, some of which are identified and discussed within. It is evident from this review that there is potential for more accurate estimation of SMC exploiting EO technology, particularly so, by exploring the use of synergistic approaches between a variety of EO instruments. Given the importance of SMC in Earth’s land surface interactions and to a large range of applications, one can appreciate that its accurate estimation is critical in addressing key scientific and practical challenges in today’s world such as food security, sustainable planning and management of water resources. The launch of new, more sophisticated satellites strengthens the development of innovative research approaches and scientific inventions that will result in a range of pioneering and ground-breaking advancements in the retrievals of soil moisture from space. [ABSTRACT FROM AUTHOR]