•Establish explainable machine learning models of glacio-hydrological processes.•Depict hysteresis of controlling factors affecting glacio-hydrological processes.•Explore the mechanism of the extreme ...events of glacio-hydrological processes.
The glacio-hydrological process is essential in the global water cycle but is complex and poorly understood. In this study, we couple the deep Shapley additive explanation (SHAP) with a long short-term memory (LSTM) model to construct a machine-learning (XAI) framework that describes the glacio-hydrological process in Urumqi Glacier No. 1, China. The XAI framework reveals 1) the dominant hydro-meteorological factors have a five-month lead time, and each factor has its own active time and degree of contribution; 2) the temperature and precipitation within the lead time dominate the process; 3) identifiable combination of the factors, instead of extreme events themselves, creates the extreme glacio-hydrological phenomena.
Generally, the glacial meltwater replenishes the glacial stream runoff, which is influenced by many environmental factors. In particular, the runoff responds to the change in the glacier mass balance with hysteresis within five months. Overall, the temperature and precipitation within the lead time (4–5 months) dominate the runoff processes. This study quantifies the Contribution of each input in the glacio-hydrological process and provides valuable insight into the interaction of various hydro-meteorological factors.
Rivers are the main water source for the oases, and rivers are essential for the wellbeing of the human inhabitants in the desert areas. The Keriya River flows through the south–central Taklimakan ...desert, the second largest mobile desert on Earth, in northwest China. The earliest archaeological site in the interior of the Taklimakan Desert together with the remains of several ancient cities are located along the Keriya River. Accurately dating the dry watercourses and ancient sites in this region is critical for understanding the changes in fluvial hydrology and their relationship with human activities in desert areas. Specially, the interactions between the hydrological processes of the Keriya River, and human activities are poorly understood due to the lack of a reliable chronology for this river associated with these ancient sites. In this study, we collected 18 samples from 12 fluvial and lacustrine sedimentary sequences for optically stimulated luminescence (OSL) dating, and we also, reviewed 23 dating results from previous studies to reconstruct the hydrological processes of the Keriya River since the early Holocene. Additionally, we also tested 28 14C dates from three ancient sites, combined with 33 14C dates from previous studies to reconstruct a timeline of human migration within the desert. The results show that the Keriya River retreated continuously from the early Holocene onward, due to the decreased supply of glacial meltwater and precipitation in the surrounding mountains, and this process triggered human migrations from north to south in the Taklimakan Desert after ∼3.5 ka. Overall, our findings reveal that variations in fluvial hydrological processes can trigger human migration in desert areas under the background of the global climate change.
•We established the hydrological processes and human migration history along the Keriya River since the early Holocene.•The retreat of the river was synchronized with the human migration to the southern Taklimakan Desert.•The decreased supply of glacial meltwater and precipitation in the Kunlun Mountains triggered the river retreat.•The hydrological status and human settlements in the desert/arid area were sensitive to climate changes.
Variations in vegetation are influenced by regional climate regimes and, in turn, control the water balance behavior in water-limited regions. Owing to its role in ecohydrological processes, ...vegetation is an essential link in modeling the relationships among climate conditions, vegetation patterns, and dynamic water balance behavior. However, previous ecohydrological models have been empirical and complex, without physically significant parameters. Here, we propose a novel ecohydrological model (a Budyko model–coupled vegetation model) that combines the impacts of climate change and vegetation variations, featuring simple and deterministic parameters. In addition to accounting for the fundamental water balance model and its factors, mean precipitation, potential evapotranspiration, runoff, and variations in water storage (δS), the model showed better performance when incorporating δS (RMSE = 2.72 mm yr−1) and its parameter ε -, which is mechanically and quantitively subject to the vegetation coverage (R2 = 0.95, p < 0.01). This was estimated as a function of vegetation potential canopy conductance, mean rainstorm depth, mean time between storms, and potential rate of evapotranspiration in a semi-arid watershed with impulsive precipitation in China (R2 = 0.80, p < 0.01). The model also found that vegetation growth was mainly controlled by soil water content and decoupled the impact of the total amount of precipitation on vegetation in the northeastern area of the watershed. Hence, our method presents a new tool for building an ecohydrological model that includes deterministic parameters of mechanical significance.
•Variations in vegetation, climate, and water balance are linked.•We derive a simple, novel ecohydrological model based on vegetation.•The model performed well for six sub-watersheds in a semi-arid region.
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•We simulated the eco-hydrological process of the TSGC from 1901 to 2016.•LAI, GPP, and WUE showed significant increasing trends, dominated by rising CO2.•Water yield showed a ...decreasing trend, dominated by warming and rising CO2.•Changes in vegetation and water resources were more prominent in sandy grassland.•Warming was a suppressant of vegetation growth in typical steppe regions.
As an important part of global semi-arid grassland, adequately understanding how eco-hydrological processes in the Temperate Semi-Arid Grassland of China (TSGC) respond to environmental change over a century-long time scale is of critical importance to environmental change adaptation and mitigation policy in the semi-arid region. We investigated the dynamics and driving forces of key eco-hydrological variables (leaf area index (LAI), gross primary production (GPP), evapotranspiration (ET), water yield (WY), and water use efficiency (WUE)) of 8 typical locations within the TSGC during the period 1901–2016, using a well-tested mechanistic eco-hydrological model, seamlessly integrating land-surface energy balance, hydrological and carbon cycle, vegetation dynamics, and soil biogeochemistry. Results show that dominated by the elevated CO2, the annual LAI, GPP, and WUE increased significantly during 1901–2016, indicating that the environmental conditions were conducive to vegetation growth. Warming conditions were a promoter of vegetation growth in sandy grassland but a suppressant in typical steppe due to water stress increase. For the same reason, ET of sandy grassland exhibited a significant increasing trend, in response to warming, while that of typical steppe had an insignificant decreasing trend, controlled by the precipitation decline. Warming and the vegetation growth acceleration due to the elevated CO2 negatively influenced WY, which showed a decreasing trend, especially in the sandy grassland, suggesting the reduction of available water resources. Overall, our results revealed that this region, especially sandy grassland, exhibited an “enhanced vegetation but decreased water yield” trend under environmental changes occurred in the past century.
Evaporation is a major factor controlling the hydrological dynamics of surface water reservoirs in dry environments, therefore quantification with minimal uncertainties is desired. The aim of this ...paper is to assess the spatial variability and impact of riparian vegetation on reservoir evaporation by remote sensing. Eight reservoirs located in subhumid and semi-arid climates in the Brazilian Drylands were studied. Scenes from Landsat 5 and Landsat 8 satellites (1985 and 2018) supplied the data for four evaporation models. For reference evaporation, the Class A Pan and Piché Evaporimeter closest to the reservoirs were considered. The occurrence/density of riparian vegetation was associated with the Normalized Difference Vegetation Index (NDVI) and its influence on evaporation was assessed. The Surface Energy Balance System for Water (AquaSEBS) model presented the best average performance (Nash-Sutcliffe Efficiency coefficient 0.40 ± 0.19). Evaporation was observed to be higher at the reservoirs' margins and near the dams, due to the contact of exposed soil and rock/concrete, respectively, which transfer heat to the water. Marginal areas near the riparian forest presented low evaporation rates with decreases between 18% and 31% in relation to the average. This interdependence was evidenced by the high negative correlation (R2 0.87–0.96) between NDVI and evaporation; vegetation reduces radiation because of the shading of the reservoir margin and changes local aerodynamics, reducing evaporation. Depending on the spatial variability of evaporation, it was found that the volumes transferred to the atmosphere may have variations of up to 30%. On average, the evaporated volume in all the studied reservoirs is 450,000 m3/day, a quantity enough to supply more than two million people. Overall, the results of this study contribute not only to a better understanding of the spatial variability of evaporation in surface reservoirs, but also of the interdependence between riparian vegetation and evaporation rates.
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•Remote sensing was used to assess the spatial variation of evaporation.•Impact of riparian vegetation in evaporation was assessed in dryland reservoirs.•Evaporation was higher near exposed soil/dam, which transfer more heat to the water.•Evaporation near riparian vegetation is lower (18%–31%) comparing to the average.•The evaporated volume in all reservoirs is enough to supply over two million people.
Biological soil crusts (BSCs), composed of lichens, cyanobacteria, mosses, liverworts and microorganisms, are key biotic components of arid and semi-arid ecosystems worldwide. Despite they are ...widespread in Spain, these organisms have been historically understudied in this country. This trend is beginning to change as a recent wave of research has been identifying BSCs as a model ecological system. Many studies and research projects carried out in Spain have explored the role of BSCs on water, carbon and nitrogen fluxes, the interactions between BSCs and vascular plants, their dynamics after disturbances, and their response to global change, among other topics. In this article we review the growing body of research on BSCs available from semi-arid areas of Spain, highlighting its importance for increasing our knowledge on this group of organisms. We also discuss how it is breaking new ground in emerging research areas on the ecology of BSCs, and how it can be use to guide management and restoration efforts. Finally, we provide directions for future research on the ecology of BSCs in Spain and abroad.
► Biological soil crusts (BSCs) are key components, but historically understudied, of Spanish semi-arid ecosystems. ► We review the growing body of research on BSCs available from these ecosystems. ► BSCs are proving to be an excellent model system to foster new ways of thinking about key community and ecosystem ecology topics. ► The study of these organisms is opening new and highly promising research lines.
•The use of SIF to provide information on hydrological processes is reviewed.•Remote sensing of SIF may improve early detection of drought stress.•Remote sensing of SIF holds potential to improve ...transpiration monitoring.•Integrating fluorescence in hydrological models may improve model estimations and predictions.
Predictions of hydrological states and fluxes, especially transpiration, are poorly constrained in hydrological models due to large uncertainties in parameterization and process description. Novel technologies like remote sensing of sun-induced chlorophyll fluorescence (SIF)—which provides information from the photosynthetic apparatus—may help in constraining water cycle components. This paper discusses the nature of the plant physiological basis of the fluorescence signal and analyses the current literature linking hydrological states and fluxes to SIF. Given the connection between photosynthesis and transpiration, through the water use efficiency, SIF may serve as a pertinent constraint for hydrological models. The FLuorescence EXplorer (FLEX) satellite, planned to be launched in 2023, is expected to provide spatially high-resolution measurements of red and far-red SIF complementing the products from existing satellite missions and the high-temporal resolution products from upcoming geostationary missions. This new data stream may allow us to better constrain plant transpiration, assess the impacts of water stress on plants, and infer processes occurring in the root zone through the soil-plant water column. To make optimal use of this data, progress needs to be made in 1) our process representation of spatially aggregated fluorescence signals from spaceborne SIF instruments, 2) integration of fluorescence processes in hydrological models—particularly when paired with other satellite data, 3) quantifying the impact of soil moisture on SIF across scales, and 4) assessment of the accuracy of SIF measurements—especially from space.
•Evaluation of 12 gridded actual evaporation datasets for hydrological modelling.•Comparison of four distinct model calibration strategies.•Process-diagnostic of model outputs with multiple ...independent variables.•Calibration only on spatial patterns of evaporation improves the model responses.•Model calibration strategy determines the utility of the evaporation data.
Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012.
Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes.
2020 is the year of wildfire records. California experienced its three largest fires early in its fire season. The Pantanal, the largest wetland on the planet, burned over 20% of its surface. More ...than 18 million hectares of forest and bushland burned during the 2019–2020 fire season in Australia, killing 33 people, destroying nearly 2500 homes, and endangering many endemic species. The direct cost of damages is being counted in dozens of billion dollars, but the indirect costs on water‐related ecosystem services and benefits could be equally expensive, with impacts lasting for decades. In Australia, the extreme precipitation (“200 mm day −1 in several location”) that interrupted the catastrophic wildfire season triggered a series of watershed effects from headwaters to areas downstream. The increased runoff and erosion from burned areas disrupted water supplies in several locations. These post‐fire watershed hazards via source water contamination, flash floods, and mudslides can represent substantial, systemic long‐term risks to drinking water production, aquatic life, and socio‐economic activity. Scenarios similar to the recent event in Australia are now predicted to unfold in the Western USA. This is a new reality that societies will have to live with as uncharted fire activity, water crises, and widespread human footprint collide all‐around of the world. Therefore, we advocate for a more proactive approach to wildfire‐watershed risk governance in an effort to advance and protect water security. We also argue that there is no easy solution to reducing this risk and that investments in both green (i.e., natural) and grey (i.e., built) infrastructure will be necessary. Further, we propose strategies to combine modern data analytics with existing tools for use by water and land managers worldwide to leverage several decades worth of data and knowledge on post‐fire hydrology.
Wildfires are a source of socio‐hydrological extremes that increasingly threaten water security across the world; this situation may be referred to as wildfire‐watershed risks (WWR). WWR geographically vary and require locally‐adapted governance for efficient disaster risk reduction. A combination of watershed protection, forest restoration (including fire reintroduction), and adaptation of water infrastructures is the answer to reduce water supply vulnerability to wildfires.
•Height of water pouring effects on infiltration were tested repeatedly in a loam soil.•High runs described a less sorptive, conductive and variable soil than low runs.•Height effects were smaller in ...the wetter and little sorptive and conductive soil.•Soil perturbation was impulsive with the high runs and more gradual with the low runs.•The experimental methodology could be adapted to obtain hydrologically useful data.
Performing beerkan infiltration runs with different heights of water pouring could help to obtain saturated soil sorptivity, S, and hydraulic conductivity, Ks, data usable to explain and simulate hydrological processes. However, most of the available information on the L (low height of water pouring, nearly 3 cm) – H (high height, 1–2 m) methodology refers to runs making use of a relatively limited number of water volumes and there is some sign that a few water volumes could yield an incomplete description of soil alteration phenomena induced by wetting. For a loam soil, the objective of this investigation was to determine water pouring height effects on the S and Ks values obtained in different sampling dates with more than usual amounts of applied water. Soil alteration due to the mechanical impact of the applied water appeared almost completed by the end of the runs in all cases but in a more advanced stage when the soil was initially more sorptive and conductive. Overall, the H runs yielded 2.3–2.8 times smaller S values and 8.5–14.5 times smaller Ks values than the L runs but differences between the L and H methodologies varied during the sampling period. In particular, these differences were smallest when the soil was initially relatively wet and little sorptive and conductive (S and Ks values differing with the experiment by no more than two times) and largest in the opposite conditions (S and Ks values differing by 3 and 17–21 times, respectively). The L runs yielded coefficients of variations, CV, of 14–60 % for S and 45–171 % for Ks, depending on the sampling date, and a ratio between the highest and the lowest mean of 2.5 for S and 11.8 for Ks. With the H runs, the corresponding CV values were 14–38 % for S and 35–107 % for Ks and two means differed at the most by 1.3 times for S and 2.2 times for Ks. Therefore, the H runs described a soil that was less sorptive, less conductive, more spatially homogeneous and more temporally stable than the L runs. Less runs could be enough to parameterize the soil in a disturbed condition as compared with the undisturbed one. Further testing the L-H methodology in other environmental conditions is recommended in the perspective to develop simple field methods to determine the hydrodynamic properties of both a nearly undisturbed soil and an intensively disturbed soil.
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