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Thousands of lakes on the Tibetan Plateau (TP) play a critical role in the regional water cycle, weather, and climate. In recent years, the areas of TP lakes underwent drastic changes and have become a research hotspot. However, the characteristics of the lake-atmosphere interaction over the high-altitude lakes are still unclear, which inhibits model development and the accurate simulation of lake climate effects. The source region of the Yellow River (SRYR) has the largest outflow lake and freshwater lake on the TP and is one of the most densely distributed lakes on the TP. Since 2011, three observation sites have been set up in the Ngoring Lake basin in the SRYR to monitor the lake-atmosphere interaction and the differences among water-heat exchanges over the land and lake surfaces. This study presents an eight-year (2012–19), half-hourly, observation-based dataset related to lake–atmosphere interactions composed of three sites. The three sites represent the lake surface, the lakeside, and the land. The observations contain the basic meteorological elements, surface radiation, eddy covariance system, soil temperature, and moisture (for land). Information related to the sites and instruments, the continuity and completeness of data, and the differences among the observational results at different sites are described in this study. These data have been used in the previous study to reveal a few energy and water exchange characteristics of TP lakes and to validate and improve the lake and land surface model. The dataset is available at National Cryosphere Desert Data Center and Science Data Bank.

Under the intensification of global warming, the characteristics of the Three Rivers source region (TRSR; i.e., headwaters of the Yellow River, the Yangtze River, and the Lancang River) in China were diagnosed in the summer season from 1979 to 2015 using observations and reanalysis data. The diagnoses indicate that summer precipitation decreased from 1979 to 2002 [by 9.01 mm day−1 (10 yr)−1; p < 0.05 by Student’s t test] and increased significantly after 2002 [by 5.52 mm day−1 (10 yr)−1]. This abrupt change year (2002) was further confirmed by the cumulative anomaly method, the moving t-test method, and the Yamamoto method. By compositing the thermodynamics before and after the abrupt change year (2002), the results reveal that increased water vapor and more substantial lower-level convergence were present over the TRSR during 2003–15. This marked interdecadal variability in the TRSR summer precipitation responded to the interdecadal position and intensity of the large-scale forcing East Asian westerly jet (EAWJ), which is significantly modulated by the low-frequency variability associated with Southern Oscillation index. The connection between the interannual TRSR precipitation and the location and intensity of EAWJ was also explored. The position index of the EAWJ is negatively (with correlation coefficient R of −0.446; p < 0.05 by Student’s t test) correlated with the precipitation over the TRSR, implying that southward and northward years of EAWJ are respectively associated with intensifying and weakening the TRSR summer precipitation, whereas the intensity of EAWJ is insignificantly correlated with the TRSR summer precipitation.

Model and data are essential for current geoscientific research. Too many hydrological models are available for potential modelers, plus too much spatial terrestrial data related to modeling is accessible to users. More importantly, reproducibility is one of the key features in science, which is barely discussed in hydrological models. Two significant reasons are that (1) the various hydrological models are incompatible since they require different variables, even if some of them share the same terminology, and (2) the complexity of model structure makes it impossible to deploy a model swiftly in any new research area. Our project is to establish a Global Hydrological Data Cloud (GHDC, https://shuddata.com) providing essential terrestrial variables for generic hydrological modeling, as modelers provide the watershed boundary and model requests. The data retrieved from the GHDC covers terrain, topology, soil/geology, landuse, hydraulic parameters and meteorological time-series data. The demonstration of three watershed examples with the Simulator of Hydrologic Unstructured Domains (SHUD), can be a standard paradigm for physically-based hydrological modeling and instructive for other modeling processes, as the procedures are transferable to other hydrological models and regions.

Hydrologic modeling is an essential strategy for understanding and predicting natural flows, particularly where observations are lacking in either space or time or where complex terrain leads to a disconnect in the characteristic time and space scales of overland and groundwater flow. However, significant difficulties remain for the development of efficient and extensible modeling systems that operate robustly across complex regions. This paper introduces the Simulator for Hydrologic Unstructured Domains (SHUD), an integrated, multiprocess, multiscale, flexible-time-step model, in which hydrologic processes are fully coupled using the finite volume method. SHUD integrates overland flow, snow accumulation/melt, evapotranspiration, subsurface flow, groundwater flow, and river routing, thus allowing physical processes in general watersheds to be realistically captured. SHUD incorporates one-dimensional unsaturated flow, two-dimensional groundwater flow, and a fully connected river channel network with hillslopes supporting overland flow and baseflow. The paper introduces the design of SHUD, from the conceptual and mathematical description of hydrologic processes in a watershed to the model's computational structures. To demonstrate and validate the model performance, we employ three hydrologic experiments: the V-catchment experiment, Vauclin's experiment, and a model study of the Cache Creek Watershed in northern California. Ongoing applications of the SHUD model include hydrologic analyses of hillslope to regional scales (1 m2 to 106 km2), water resource and stormwater management, and interdisciplinary research for questions in limnology, agriculture, geochemistry, geomorphology, water quality, ecology, climate and land-use change. The strength of SHUD is its flexibility as a scientific and resource evaluation tool where modeling and simulation are required.

The newly developed WRF-Hydro model is a fully coupled atmospheric and hydrological processes model suitable for studying the intertwined atmospheric hydrological processes. This study utilizes the WRF-Hydro system on the Three-River source region. The Nash-Sutcliffe efficiency for the runoff simulation is 0.55 compared against the observed daily discharge amount of three stations. The coupled WRF-Hydro simulations are better than WRF in terms of six ground meteorological elements and turbulent heat flux, compared to the data from 14 meteorological stations located in the plateau residential area and two flux stations located around the lake. Although WRF-Hydro overestimates soil moisture, higher anomaly correlation coefficient scores (0.955 versus 0.941) were achieved. The time series of the basin average demonstrates that the hydrological module of WRF-hydro functions during the unfrozen period. The rainfall intensity and frequency simulated by WRF-Hydro are closer to global precipitation mission (GPM) data, attributed to higher convective available potential energy (CAPE) simulated by WRF-Hydro. The results emphasized the necessity of a fully coupled atmospheric-hydrological model when investigating land-atmosphere interactions on a complex topography and hydrology region.

Extreme snowfall events have been increasing in the Tibetan Plateau, causing greater variations in the snow cover conditions. However, the soil water-heat transfer under different snow conditions has rarely been characterized in detail. Here, by using the multi-source observation data of five years, we analyzed the influences of snow cover on water-heat transfer in alpine meadows of the source region of the Yellow River. The main findings are as follows: In the deep soil, the yearly warming rate from spring to summer was much faster than the cooling rate from autumn to winter, while in the shallow soil, conversely, the former was slower than the latter. Snow cover not only decreased the average soil temperature but also inhibited the occurrence of extremely low temperatures in the soil. The insulation effect of snow was mainly in the mid-frozen period. It was insufficient to balance out the heat lost by the high albedo during early and late frozen periods. In years with more snow, different depths of the soil featured similar thawing dates and plenty of soil voids due to small solid water content and high gravel content, together creating favorable conditions for the snowmelt infiltration, which passed through the frozen layer and infiltrated into the soil of 3.20 m or deeper. In years with less snow, the long-term freezing-thawing cycles aggravated the evaporation and loss of surface soil water in spring. Under different snow cover conditions, the difference in the sensible heat flux was much larger than the latent heat flux in winter and early spring. This study provides a refined physical image of soil water-heat transfer under extreme snow cover conditions in the Tibetan Plateau, which is expected to light the snow cover-frozen soil interaction in the mid-latitude and high-elevation areas.

The hydrologic model is ideal for experimenting and understanding the water movement and storage in a watershed from the upper mountain to the river outlet. Nevertheless, the model's performance, suitability, and data availability are the primary challenge for a modeler. This study introduces the Simulator for Hydrologic Unstructured Domains (SHUD), a surface-subsurface integrated hydrological model using the semi-discrete Finite Volume Method. Though the SHUD applies a fine time-step (in minutes) and flexible spatial domain decomposition (m to km) to simulate the fully coupled surface-subsurface hydrology, the model can solve the watershed-scale problem efficiently and dependably. Plenty of applications in the USA proved the SHUD model's performance and suitability in the humid and data-rich watersheds. In this research, we demonstrate the SHUD model deployment in two data-scarce watersheds in the northwest of China with global datasets, validate the simulations against local observational data, and assess the SHUD model's efficiency and suitability. The one is the Upstream Heihe River (UHR), which is a typical semi-arid mountainous watershed. The other is Yellow River Source (YRS), the upstream of Yellow River, contributing more than 50% of total discharge. The results, figures, and analysis based on SHUD simulations under global datasets highlight the model's suitability and efficiency in data-limited watersheds, even ungaged ones. The SHUD model is a useful modeling platform for hydrology and water-related coupling studies.

Understanding how the biological invasion is driven by environmental factors will improve model prediction and advance early detection, especially in the context of accelerating anthropogenic ecological changes. Although a large body of studies has examined how favorable environments promote biological invasions, a more comprehensive and mechanistic understanding of invasive species response to unfavorable/stressful conditions is still developing. Grass invasion has been problematic across the globe; in particular, C4 grass invaders, with high drought tolerance, adaptations to high temperatures, and high water use efficiency, could become more severe. Here, we conducted a rigorous microcosm experiment, with one of the most damaging invasive C4 grass - cogongrass (Imperata cylindrica), to explore how cogongrass responds to soil water and nutrient stress. We further integrated the results of the microcosm study with a species distribution model to (1) corroborate greenhouse results with field observations and (2) validate the robustness of our findings at sub-continental scales. Both the microcosm experiments and species distribution model agreed that soil water stress had a stronger impact on cogongrass than the nutrient one. New vegetative growth of cogongrass continued to be inhibited by the prior water stress. The significant water effect on cogongrass total biomass was supported by the finding that both allometric and biochemical traits of cogongrass did not show significant responses to the changes in water treatment. Different to the conventional wisdom that nutrient enrichment plays a bigger role in facilitating biological invasions, this study highlighted the possibility that water conditions may have a more substantial effect on some aggressive invaders. Therefore, an important implication of this study on biological conservation is that field managers might take advantage of the negative effect of global drought on some invasive species to increase the efficiency of their controlling efforts because invasive species may become more vulnerable under drought effect.

The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic-ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50-60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region. NSF ABI development grant [DBI 1759865]; NSF CNH grant [1517823]; NSFNational Science Foundation (NSF) [DEB 1753639, DEB 1753657] The project was funded through an NSF ABI development grant (#DBI 1759865), an NSF CNH grant (#1517823), as well as NSF grants DEB 1753639 and DEB 1753657.

Integrated modeling is a critical tool to evaluate the behavior of coupled human–freshwater systems. However, models that do not consider both fast and slow processes may not accurately reflect the feedbacks that define complex systems. We evaluated current coupled human–freshwater system modeling approaches in the literature with a focus on categorizing feedback loops as including economic and/or socio-cultural processes and identifying the simulation of fast and slow processes in human and biophysical systems. Fast human and fast biophysical processes are well represented in the literature, but very few studies incorporate slow human and slow biophysical system processes. Challenges in simulating coupled human–freshwater systems can be overcome by quantifying various monetary and non-monetary ecosystem values and by using data aggregation techniques. Studies that incorporate both fast and slow processes have the potential to improve complex system understanding and inform more sustainable decision-making that targets effective leverage points for system change. Electronic supplementary material The online version of this article (10.1007/s13280-018-1136-6) contains supplementary material, which is available to authorized users.

The Solver of Hydrological Unstructured Domain (SHUD) is an integrated multi-process, multi-scale, multi-timestep hydrologic model where the dominant hydrological processes are fully coupled using ...

Hydrological modeling is an essential strategy for understanding natural flows, particularly where observations are lacking in either space or time, or where topographic roughness leads to a disconnect in the characteristic timescales of overland and groundwater flow. Consequently, significant opportunities remain for the development of extensible modeling systems that operate robustly across regions. Towards the development of such a robust hydrological modeling system, this paper introduces the Solver for Hydrological Unstructured Domain (SHUD), an integrated multi-process, multi-scale, multi-timestep hydrological model, in which hydrological processes are fully coupled using the Finite Volume Method. The SHUD integrates overland flow, snow accumulation/melting, evapotranspiration, subsurface and groundwater flow, and river routing, while realistically capturing the physical processes in a watershed. The SHUD incorporates one-dimension unsaturated flow, two-dimension groundwater flow, and river channels connected with hillslopes via overland flow and baseflow. This paper introduces the design of SHUD, from the conceptual and mathematical description of hydrological processes in a watershed to computational structures. To demonstrate and validate the model performance, we employ three hydrological experiments: the V-Catchment experiment, Vauclin's experiment, and a study of the Cache Creek Watershed in northern California, USA. Possible applications of then SHUD model include hydrological studies from the hillslope scale to regional scale, water resource and stormwater management, and coupling research with related fields such as limnology, agriculture, geochemistry, geomorphology, water quality, and ecology, climatic and landuse change. In general, SHUD is a valuable scientific tool for any modeling task involving simulating and understanding the hydrological response.

Summarization: Submarine groundwater discharge (SGD) contributes to the physical and chemical characters of coastal waters by discharging nutrients and contaminants, significantly impacting regional marine ecosystems and contributing to ocean chemical budgets. However, such groundwater discharge varies dramatically across scales and is often not comparable due to different model assumptions and field designs. We used a hydrologic model with integration of fundamental surface and subsurface processes to simulate the coastline level fresh SGD for the Crete Island in the Mediterranean Sea. The modeled hydrological processes suggested that fresh SGD substantially contributes to water flow entering the Mediterranean Sea (2.3 × 108 m3/yr), amounting to 31% of river discharge and 14% of precipitation. Spatially, fresh SGD varied from 2.4 m3/yr/m to 13.4 × 104 m3/yr/m, with an average of 2.6 × 103 m3/yr/m. The local maxima were commonly associated with river mouths reflecting larger hydraulic gradients and higher permeable structures. Temporally, fresh SGD was impacted by episodic precipitation in a delayed and prolonged pattern. We found that fresh SGD variability at the coastline segment level was compared to point measurements and fresh SGD magnitudes summered up to the catchment level were consistent with global products. Our results suggest the coupled surface–subsurface hydrologic modeling approach is a promising strategy to quantify and partition large-scale water budgets down to point observations that typically do not capture the full range of fresh SGD dynamics. Presented on: Journal of Hydrology

Environmental and water issues are essentially complex interdisciplinary problems. Multiple models from different disciplines are usually integrated to solve those problems. Integrated modeling environment is an effective technical approach to model integration. Although a number of modeling environments worldwide are available, they cannot meet current challenges faced. Their old-fashion designs and original development purposes constrain their possible applications to the domain of hydrologic or land surface modeling. One of the challenges is that we intend to link knowledge database or ontology system to the modeling environment in order to make the modeling support more intelligent and powerful. In this paper, we designed and implemented an integrated modeling environment (HIME) for hydrological and land surface modeling purpose in a much extendable, efficient and easy use manner. With such design, a physical process was implemented as a module, or component. A new model can be generated in an intuitive way by linking module icons together and establishing their relationships. Following an introduction to the overall architecture, the designs for module linkage and data transfer between modules are described in details. Using XML based meta-information, modules in either source codes or binary form can be utilized by the environment. As a demonstration, with the help of HIME, we replaced the evaporation module of TOPMODEL with the evapotranspiration module from the Noah land surface model which explicitly accounts for vegetation transpiration. This example showed the effectiveness and efficiency of the modeling environment on model integration.