State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering

The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community.

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.

In this paper we develop a conceptual and observational case in which soil water patterns in temperate regions of Australia switch between two preferred states. The wet state is dominated by lateral water movement through both surface and subsurface paths, with catchment terrain leading to organization of wet areas along drainage lines. We denote this as nonlocal control. The dry state is dominated by vertical fluxes, with soil properties and only local terrain (areas of high convergence) influencing spatial patterns. We denote this as local control. The switch is described in terms of the dominance of lateral over vertical water fluxes and vice versa. When evapotranspiration exceeds rainfall, the soil dries to the point where hydraulic conductivity is low and any rainfall that occurs essentially wets up the soil uniformly and is evapotranspired before any significant lateral redistribution takes place. As evapotranspiration decreases and/or rainfall increases, areas of high local convergence become wet, and runoff that is generated moves downslope, rapidly wetting up the drainage lines. In the wet to dry transitional period a rapid increase in potential evapotranspiration (and possibly a decrease in rainfall) causes drying of the soil and “shutting down” of lateral flow. Vertical fluxes dominate and the “dry” pattern is established. Three data sets from two catchments are presented to support the notion of preferred states in soil moisture, and the results of a modeling exercise on catchments from a range of climatic conditions illustrate that the conclusions from the field studies may apply to other areas. The implications for hydrological modeling are discussed in relation to methods for establishing antecedent moisture conditions for event models, for distribution models, and for spatially distributing bulk estimates of catchment soil moisture using indices.

Evapotranspiration is a major component of the global water cycle and provides a critical nexus between terrestrial water, carbon and surface energy exchanges. Evapotranspiration is inherently difficult to measure and predict especially at large spatial scales. Remote sensing provides a cost‐effective method to estimate evapotranspiration at regional to global scales. In the past three decades a large number of studies on remote sensing based evapotranspiration estimation have emerged. This review summarizes the basic theories underpinning current remote sensing based evapotranspiration estimation methods. It also lays out the development history of these methods and compares their advantages and limitations. Several key directions for further study are identified and discussed, including identification of uncertainty sources in remote sensing evapotranspiration models, merging of different remote sensing methods, application of data assimilation and fusion techniques in producing robust evapotranspiration estimates, and utilization of multi‐source remote sensing data and latest sensor technologies. Further advances in the remote sensing of evapotranspiration will enhance capabilities for monitoring of the global water and energy cycles, including water availability and ecosystem responses and feedbacks to climate change and human impacts. WIREs Water 2016, 3:834–853. doi: 10.1002/wat2.1168 This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods

Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance.

Accurate estimation of the gross primary production (GPP) of terrestrial vegetation is vital for understanding the global carbon cycle and predicting future climate change. Multiple GPP products are currently available based on different methods, but their performances vary substantially when validated against GPP estimates from eddy covariance data. This paper provides a new GPP dataset at moderate spatial (500 m) and temporal (8-day) resolutions over the entire globe for 2000-2016. This GPP dataset is based on an improved light use efficiency theory and is driven by satellite data from MODIS and climate data from NCEP Reanalysis II. It also employs a state-of-the-art vegetation index (VI) gap-filling and smoothing algorithm and a separate treatment for C3/C4 photosynthesis pathways. All these improvements aim to solve several critical problems existing in current GPP products. With a satisfactory performance when validated against in situ GPP estimates, this dataset offers an alternative GPP estimate for regional to global carbon cycle studies.

ABSTRACT The Standardized Precipitation Evapotranspiration Index ( SPEI ) was computed based on the monthly precipitation and air temperature values at 609 locations over China during the period 1951–2010.Various characteristics of drought across China were examined including: long‐term trends, percentage of area affected, intensity, duration, and drought frequency. The results revealed that severe and extreme droughts have become more serious since late 1990s for all of China (with dry area increasing by ∼3.72% per decade); and persistent multi‐year severe droughts were more frequent in North China, Northeast China, and western Northwest China; significant drying trends occurred over North China, the southwest region of Northeast China, central and eastern regions of Northwest China, the central and southwestern parts of Southwest China and southwestern and northeastern parts of western Northwest mainly due to a decrease in precipitation coupled with a general increase in temperature. In addition, North China, the western Northwest China, and the Southwest China had their longest drought durations during the 1990s and 2000s. Droughts also affected western Northwest, eastern Northwest, North, and Northeast regions of China more frequently during the recent three decades. The results of this article could provide certain references and triggers for establishing a drought early warning system in China. © 2013 Royal Meteorological Society

Abstract The performance of 24 GCMs available in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) is evaluated over the eastern Tibetan Plateau (TP) by comparing the model outputs with ground observations for the period 1961–2005. The twenty-first century trends of precipitation and temperature based on the GCMs’ projections over the TP are also analyzed. The results suggest that for temperature most GCMs reasonably capture the climatological patterns and spatial variations of the observed climate. However, the majority of the models have cold biases, with a mean underestimation of 1.1°–2.5°C for the months December–May, and less than 1°C for June–October. For precipitation, the simulations of all models overestimate the observations in climatological annual means by 62.0%–183.0%, and only half of the 24 GCMs are able to reproduce the observed seasonal pattern, which demonstrates a critical need to improve precipitation-related processes in these models. All models produce a warming trend in the twenty-first century under the Representative Concentration Pathway 8.5 (rcp8.5) scenario; in contrast, the rcp2.6 scenario predicts a lower average warming rate for the near term, and a small cooling trend in the long-term period with the decreasing radiative forcing. In the near term, the projected precipitation change is about 3.2% higher than the 1961–2005 annual mean, whereas in the long term the precipitation is projected to increase 6.0% under rcp2.6 and 12.0% under the rcp8.5 scenario. Relative to the 1961–2005 mean, the annual temperature is projected to increase by 1.2°–1.3°C in the short term; the warmings under the rcp2.6 and rcp8.5 scenarios are 1.8° and 4.1°C, respectively, for the long term.

Alternative water resources (seawater, brackish water, atmospheric water, sewage, etc.) can be converted into clean freshwater via high-efficiency, energy-saving, and cost-effective methods to cope with the global water crisis. Herein, we provide a comprehensive and systematic overview of various solar-powered technologies for alternative water utilization (i.e., “sunlight–energy–water nexus”), including solar-thermal interface desalination (STID), solar-thermal membrane desalination (STMD), solar-driven electrochemical desalination (SED), and solar-thermal atmospheric water harvesting (ST-AWH). Three strategies have been proposed for improving the evaporation rate of STID systems above the theoretical limit and designing all-weather or all-day operating STID systems by analyzing the energy transfer of the evaporation and condensation processes caused by solar-thermal conversion. This review also introduces the fundamental principles and current research hotspots of two other solar-driven seawater or brackish water desalination technologies (STMD and SED) in detail. In addition, we also cover ST-AWH and other solar-powered technologies in terms of technology design, materials evolution, device assembly, etc. Finally, we summarize the content of this comprehensive review and discuss the challenges and future outlook of different types of solar-powered alternative water utilization technologies.

Recent studies showed that anomalous dry conditions and limited moisture supply roughly between 1998 and 2008, especially in the Southern Hemisphere, led to reduced vegetation productivity and ceased growth in land evapotranspiration (ET). However, natural variability of Earth's climate system can degrade capabilities for identifying climate trends. Here we produced a long-term (1982-2013) remote sensing based land ET record and investigated multidecadal changes in global ET and underlying causes. The ET record shows a significant upward global trend of 0.88 mm yr(-2) (P < 0.001) over the 32-year period, mainly driven by vegetation greening (0.018% per year; P < 0.001) and rising atmosphere moisture demand (0.75 mm yr(-2); P = 0.016). Our results indicate that reduced ET growth between 1998 and 2008 was an episodic phenomenon, with subsequent recovery of the ET growth rate after 2008. Terrestrial precipitation also shows a positive trend of 0.66 mm yr(-2) (P = 0.08) over the same period consistent with expected water cycle intensification, but this trend is lower than coincident increases in evaporative demand and ET, implying a possibility of cumulative water supply constraint to ET. Continuation of these trends will likely exacerbate regional drought-induced disturbances, especially during regional dry climate phases associated with strong El Niño events.

Under the double pressures of both the energy crisis and environmental pollution, the exploitation and utilization of hydrogen, a clean and renewable power resource, has become an important trend in the development of sustainable energy-production and energy-consumption systems. In this regard, the electrocatalytic hydrogen evolution reaction (HER) provides an efficient and clean pathway for the mass production of hydrogen fuel and has motivated the design and construction of highly active HER electrocatalysts of an acceptable cost. In particular, graphene-based electrocatalysts commonly exhibit an enhanced HER performance owing to their distinctive structural merits, including a large surface area, high electrical conductivity, and good chemical stability. Considering the rapidly growing research enthusiasm for this topic over the last several years, herein, a panoramic review of recent advances in graphene-based electrocatalysts is presented, covering various advanced synthetic strategies, microstructural characterizations, and the applications of such materials in HER electrocatalysis. Lastly, future perspectives on the challenges and opportunities awaiting this emerging field are proposed and discussed.

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland.

The hydrological regimes for the major river basins in the Tibetan Plateau (TP), including the source regions of the Yellow (UYE), Yangtze (UYA), Mekong (UM), Salween (US), Brahmaputra (UB), and Indus (UI) rivers, were investigated through a land surface model and regression analyses between climate variables and runoff data. A hydrologic modeling framework was established across the TP to link the Variable Infiltration Capacity (VIC) land surface hydrology model with a degree‐day glacier‐melt scheme (VIC‐glacier model) at a 1/12° × 1/12°. The model performance was evaluated over the upper basins of the six rivers. The heterogeneity and scarcity of the meteorological stations are the major limitation for hydrological modeling over the TP. The relative contributions to streamflow from rainfall, snowmelt, and glacier melt for the six basins were quantified via the model framework and simulation. The results suggest that monsoon precipitation has a dominant role in sustaining seasonal streamflow over southeastern regions, contributing 65–78% of annual runoff among the UYE, UYA, UM, US, and UB basins. For the UI, the runoff regime is largely controlled by the glacier melt and snow cover in spring and summer. The contribution of glacier runoff is minor for the UYE and UM (less than 2% of total annual flow), and moderate for the UYA and US basins (5–7% of yearly flow), while glacier melt makes up about 12% and 48% of annual flow for the UB and UI basins, respectively.

ABSTRACT: The simple, empirical degree‐day approach for calculating snowmelt and runoff from mountain basins has been in use for more than 60 years. It is frequently suggested that the degree‐day method be replaced by the more physically‐based energy balance approach. The degree‐day approach, however, maintains its popularity, applicability, and effectiveness. It is shown that the degree‐day method is reliable for computing total snowmelt depths for periods of a week to the entire snowmelt season. It can also be used for daily snowmelt depths when utilized in connection with an adequate snowmelt runoff model for computing the basin runoff. The degree‐day ratio is shown to vary seasonally as opposed to being constant as is often assumed. Additionally, in order to evaluate the degree‐day ratio correctly, the changing snow cover extent in a basin during the snowmelt season must be taken into account. It is also possible to combine the degree‐day approach with a radiation component so that short time interval (&lt;24 hours) computations of snowmelt depth can be made. When snowmelt input is transformed to basin output (runoff) by a snowmelt runoff model, there is little difference between the degree‐day approach and a radiation‐based approach. This is fortuitous because the physically‐based energy balance models will not soon displace the degree‐day methods because of their excessive data requirements.

Abstract Quantitative evaluation of the effect of climate variability and human activities on runoff is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and sustaining the society development. In this paper, hydro‐climatic data from four catchments (i.e. Luanhe River catchment, Chaohe River catchment, Hutuo River catchment and Zhanghe River catchment) in the Haihe River basin from 1957 to 2000 were used to quantitatively attribute the hydrological response (i.e. runoff) to climate change and human activities separately. To separate the attributes, the temporal trends of annual precipitation, potential evapotranspiration (PET) and runoff during 1957–2000 were first explored by the Mann–Kendall test. Despite that only Hutuo River catchment was dominated by a significant negative trend in annual precipitation, all four catchments presented significant negative trend in annual runoff varying from −0.859 (Chaohe River) to −1.996 mm a −1 (Zhanghe River). Change points in 1977 and 1979 are detected by precipitation–runoff double cumulative curves method and Pettitt's test for Zhanghe River and the other three rivers, respectively, and are adopted to divide data set into two study periods as the pre‐change period and post‐change period. Three methods including hydrological model method, hydrological sensitivity analysis method and climate elasticity method were calibrated with the hydro‐climatic data during the pre‐change period. Then, hydrological runoff response to climate variability and human activities was quantitatively evaluated with the help of the three methods and based on the assumption that climate and human activities are the only drivers for streamflow and are independent of each other. Similar estimates of anthropogenic and climatic effects on runoff for catchments considered can be obtained from the three methods. We found that human activities were the main driving factors for the decline in annual runoff in Luanhe River catchment, Chaohe River catchment and Zhanghe River catchment, accounting for over 50% of runoff reduction. However, climate variability should be responsible for the decrease in annual runoff in the Hutuo River catchment. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Two standard Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products, 3B42RT and 3B42V6, were quantitatively evaluated in the Laohahe basin, China, located within the TMPA product latitude band (50°NS) but beyond the inclined TRMM satellite latitude band (36°NS). In general, direct comparison of TMPA rainfall estimates to collocated rain gauges from 2000 to 2005 show that the spatial and temporal rainfall characteristics over the region are well captured by the 3B42V6 estimates. Except for a few months with underestimation, the 3B42RT estimates show unrealistic overestimation nearly year round, which needs to be resolved in future upgrades to the real‐time estimation algorithm. Both model‐parameter error analysis and hydrologic application suggest that the three‐layer Variable Infiltration Capacity (VIC‐3L) model cannot tolerate the nonphysical overestimation behavior of 3B42RT through the hydrologic integration processes, and as such the 3B42RT data have almost no hydrologic utility, even at the monthly scale. In contrast, the 3B42V6 data can produce much better hydrologic predictions with reduced error propagation from input to streamflow at both the daily and monthly scales. This study also found the error structures of both RT and V6 have a significant geo‐topography‐dependent distribution pattern, closely associated with latitude and elevation bands, suggesting current limitations with TRMM‐era algorithms at high latitudes and high elevations in general. Looking into the future Global Precipitation Measurement (GPM) era, the Geostationary Infrared (GEO‐IR) estimates still have a long‐term role in filling the inevitable gaps in microwave coverage, as well as in enabling sub‐hourly estimates at typical 4‐km grid scales. Thus, this study affirms the call for a real‐time systematic bias removal in future upgrades to the IR‐based RT algorithm using a simple scaling factor. This correction is based on MW‐based monthly rainfall climatologies applied to the combined monthly satellite‐gauge research products.

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

Abstract The ‘range of variability approach’ (RVA) and mapping technique are used to investigate the spatial variability of hydrologic alterations (HA) due to dam construction along the middle and lower Yellow River, China, over the past five decades. The impacts of climate variability on hydrological process have been removed during wet and dry periods and the focus is on the impacts of human activities, such as dam construction, on hydrological processes. Results indicate the following: (1) The impacts of the Sanmenxia reservoir on the hydrologic alteration are relatively slight with a mean HA value of 0·48, ranking in the last place among the four large reservoirs. (2) Xiaolangdi reservoir has significantly changed the natural flow regime downstream with mean HA value of 0·56, ranking it in first place among the large reservoirs. (3) The results of ranked median degrees of 33 hydrologic alteration indicators for 10 stations in the Yellow River show that the hydrologic alteration of Huayuankou ranks the highest among 10 stream gauges. (4) Impacts of reservoirs on hydrological processes downstream of the dams are closely associated with the regulating activities of the reservoirs. At the same time, alterations of streamflow regimes resulting from climatic changes (e.g. precipitation variability) make the situation more complicated and more hydrological observations will be necessary for further analysis. The results of the current study will be greatly beneficial to the regional water resources management and restoration of eco‐environmental systems in the middle and lower Yellow River characterized by intensified dam construction under a changing environment. Copyright © 2008 John Wiley &amp; Sons, Ltd.

Metal–organic framework/polypyrrole hybrids are synthesized and directly used in capacitive deionization for the first time.

The Northwest India Aquifer (NWIA) has been shown to have the highest groundwater depletion (GWD) rate globally, threatening crop production and sustainability of groundwater resources. Gravity Recovery and Climate Experiment (GRACE) satellites have been emerging as a powerful tool to evaluate GWD with ancillary data. Accurate GWD estimation is, however, challenging because of uncertainties in GRACE data processing. We evaluated GWD rates over the NWIA using a variety of approaches, including newly developed constrained forward modeling resulting in a GWD rate of 3.1 ± 0.1 cm/a (or 14 ± 0.4 km(3)/a) for Jan 2005-Dec 2010, consistent with the GWD rate (2.8 cm/a or 12.3 km(3)/a) from groundwater-level monitoring data. Published studies (e.g., 4 ± 1 cm/a or 18 ± 4.4 km(3)/a) may overestimate GWD over this region. This study highlights uncertainties in GWD estimates and the importance of incorporating a priori information to refine spatial patterns of GRACE signals that could be more useful in groundwater resource management and need to be paid more attention in future studies.