The ResNet network of dams impounding storage reservoirs across the continental United States

Alluvial corridors of ephemeral river systems provide viable opportunities for natural water storage in dry lands. Whilst alluvial corridors are widely recognized as water buffers, particularly for areas experiencing constant water scarcity, little research has been undertaken in Sub-Saharan Africa to explore their hydrological variability and water resource potential as alternative water sources for nearby communities. This study investigated the water flow behavior and storage potential of an ephemeral river system in the Mara Basin of Kenya for purposes of supporting water resources development and ecological sustainability. The water flow processes - including the recharge rates and water loss processes - from existing sand storage systems were established through monitoring of ground and surface water levels. Water samples along the alluvial corridor were collected and analyzed for major ions and isotopic signatures required to establish the water storage dynamics. The storage potential was estimated through Probing and Electrical Resistivity Tomography techniques, augmented with in-situ measurements of hydraulic conductivities and channel bed porosities. The mean annual storage volume in the alluvium of the study reach was estimated at 1.1 Mm3, potentially capable of providing for the annual domestic and livestock water demands of the area. Transmission losses into the alluvium beneath the ephemeral channel-bed were noted to attenuate the flood peak discharges, depending on the level of saturation of the alluvial bed. However, water storage in the alluvium was subject to losses through evapotranspiration and seepage through fractured bedrocks. The study demonstrated the potential of alluvial corridors as water storage buffers providing alternative water sources to communities within the dry land regions with water scarcity, thereby to supporting ecosystem sustainability.

Drought monitoring is important for characterizing the timing, extent, and severity of drought for effective mitigation and water management. Presented here is a novel satellite-based drought severity index (DSI) for regional monitoring derived using time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE). The GRACE-DSI enables drought feature comparison across regions and periods, it is unaffected by uncertainties associated with soil water balance models and meteorological forcing data, and it incorporates water storage changes from human impacts including groundwater withdrawals that modify land surface processes and impact water management. Here, the underlying algorithm is described, and the GRACE-DSI performance in the continental United States during 2002–14 is evaluated. It is found that the GRACE-DSI captures documented regional drought events and shows favorable spatial and temporal agreement with the monthly Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM). The GRACE-DSI also correlates well with a satellite-based normalized difference vegetation index (NDVI), indicating sensitivity to plant-available water supply changes affecting vegetation growth. Because the GRACE-DSI captures changes in total terrestrial water storage, it complements more traditional drought monitoring tools such as the PDSI by providing information about deeper water storage changes that affect soil moisture recharge and drought recovery. The GRACE-DSI shows potential for globally consistent and effective drought monitoring, particularly where sparse ground observations (especially precipitation) limit the use of traditional drought monitoring methods.

The climate change along with anthropogenic water use have been affecting the (re)distribution of water storage and water flux across the Continental United States (CONUS). Understanding these changes requires tools that provide a big picture of the processes that drive these changes. These processes are implemented in this study by combining remote sensing data with available modeling techniques, where the data contains a sample of hydro-climatological signals and models reflect our understanding of these processes. Time series of Terrestrial Water Storage Changes (TWSC) from the Gravity Recovery and Climate Experiment (GRACE, 2003-2017) and its Follow-on (GRACE-FO, 2018-2021) are integrated into the W3RA water balance model within CONUS, where the model is run at 9-km resolution using ERA5 forcing data. The gap in the GRACE and GRACE-FO TWSC products is filled following https://doi.org/10.3390/rs12101639. To achieve the best possible statistical combination, the Markov Chain Monte Carlo-based Data Assimilation (MCMC-DA) approach (https://doi.org/10.1016/j.scitotenv.2020.143579) is applied to use GRACE and GRACE-FO TWSC as a vertical integration constraint to update W3RA's individual water storage estimates. This approach rigorously accounts for the uncertainties of model and observations.The outputs of MCMC-DA are evaluated using in-situ USGS groundwater level data and the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture product. The results indicate changes in trend and seasonality of water storage variations, for example, in southwestern (California and Nevada), southeastern (including Florida, South and North Carolina, Virginia, and Georgia), and south-central CONUS (including Texas, New Mexico, Colorado, Kansas, and Oklahoma). MCMC-DA improves the estimation of soil water in regions with high forest intensity, where ESA CCI and models reveal difficulties in capturing the soil-vegetation-atmosphere continuum. The representation of El Nino Southern Oscillation (ENSO)-related variability in water storage are found to be considerably improved after integrating GRACE(-FO) into W3RA. This new hybrid approach is found efficient for understanding the linkage between the climate variability and large-scale hydrological processes.Keywords: CONU; Data Assimilation; Bayesian Method; MCMC; GRACE(-FO); W3RA; groundwater storage; soil water storage; USGS; ESA CCI.

In order to solve the increasingly serious water environment problems in Chinese cities, the concept of sponge city in China is being gradually applied in the process of urban construction, and needs to be optimized in practice. ABC water project in Singapore integrates three elements (water gathering elements, water treatment elements, transportation and water storage elements) into the source, path and direction of rain flood management in line with the water management strategy in the overall storm flood management. The site development of ABC water project includes urban surface environment such as circulation facilities, structures, vegetation, waterways, water bodies and other water collecting elements. Water treatment elements and water collecting elements complement each other and can be used to slow down, hold up and purify the initial rainwater. Water transport and storage elements mainly refer to water facilities such as waterways and water bodies, covering Singapore rainwater management network. Due to the different urban planning parameters and space configuration, each site will have different planning strategies. This paper takes the Singapore intersecting building as an example to study the coordination and reference role of ABC water plan in sponge city, and thus provides some enlightenment for the construction of China's sponge city.

This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster and more reliable than earlier methods. Methods are tested on 30 subbasins distributed across different terrain and climate conditions of the conterminous United States. CLC values for the 30 subbasins indicate 44–83% of the features match between the two datasets, with the majority of the mismatching features comprised of first-order features. Relatively lower CLC values result from subbasins with less than about 1.5 degrees of slope. The primary difference between the two datasets may be explained by different data capture criteria. First-order, headwater tributaries derived from the flow-accumulation model are captured more comprehensively through drainage area and terrain conditions, whereas capture of headwater features in the NHD is cartographically constrained by tributary length. The addition of missing headwaters to the NHD, as guided by the elevation-derived channels, can substantially improve the scientific value of the NHD.

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources

Over the summer of 2015, the National Water Center hosted the National Flood Interoperability Experiment (NFIE) Summer Institute. The NFIE organizers introduced a national‐scale distributed hydrologic modeling framework that can provide flow estimates at around 2.67 million reaches within the continental United States. The framework generates discharges by coupling a given Land Surface Model (LSM) with the Routing Application for Parallel Computation of Discharge (RAPID). These discharges are then accumulated through the National Hydrography Dataset Plus stream network. The framework can utilize a variety of LSMs to provide the runoff maps to the routing component. The results obtained from this framework suggested that there still exists room for further enhancements to its performance, especially in the area of peak timing and magnitude. The goal of our study was to investigate a single source of the errors in the framework's discharge estimates, which is the routing component. The authors substitute RAPID which is based on the simplified linear Muskingum routing method by the nonlinear routing component the Iowa Flood Center have incorporated in their full hydrologic Hillslope‐Link Model. Our results show improvement in model performance across scales due to incorporating new routing methodology.

We developed statistical models to generate runoff time-series at National Hydrography Dataset Plus Version 2 (NHDPlusV2) catchment scale for the Continental United States (CONUS). The models use Normalized Difference Vegetation Index (NDVI) based Curve Number (CN) to generate initial runoff time-series which then is corrected using statistical models to improve accuracy. We used the North American Land Data Assimilation System 2 (NLDAS-2) catchment scale runoff time-series as the reference data for model training and validation. We used 17 years of 16-day, 250-m resolution NDVI data as a proxy for hydrologic conditions during a representative year to calculate 23 NDVI based-CN (NDVI-CN) values for each of 2.65 million NHDPlusV2 catchments for the Contiguous U.S. To maximize predictive accuracy while avoiding optimistically biased model validation results, we developed a spatio-temporal cross-validation framework for estimating, selecting, and validating the statistical correction models. We found that in many of the physiographic sections comprising CONUS, even simple linear regression models were highly effective at correcting NDVI-CN runoff to achieve Nash-Sutcliffe Efficiency values above 0.5. However, all models showed poor performance in physiographic sections that experience significant snow accumulation.

Epiphytes, including bryophytes and lichens, can significantly change the water interception and storage capacities of forest canopies. However, despite some understanding of this role, empirical evaluations of canopy and bole community water storage capacity by epiphytes are still quite limited. Epiphyte communities are shaped by both microclimate and host plant identity, and so the canopy and bole community storage capacity might also be expected to vary across similar spatial scales. We estimated canopy and bole community cover and biomass of bryophytes and lichens from ground-based surveys across a temperate-boreal ecotone in continental North America (Minnesota). Multiple forest types were studied at each site, to separate stand level and latitudinal effects. Biomass was converted into potential canopy and bole community storage on the basis of water-holding capacity measurements of dominant taxa. Bole biomass and potential water storage was a much larger contributor than outer canopy. Biomass and water storage capacity varied greatly, ranging from 9 to >900kg ha–1 and 0.003 to 0.38 mm, respectively. These values are lower than most reported results for temperate forests, which have emphasized coastal and old-growth forests. Variation was greatest within sites and appeared to reflect the strong effects of host tree identity on epiphyte communities, with conifer-dominated plots hosting more lichen-dominated epiphyte communities with lower potential water storage capacity. These results point to the challenges of estimating and incorporating epiphyte contributions to canopy hydrology from stand metrics. Further work is also needed to improve estimates of canopy epiphytes, including crustose lichens.

Feature pruning by upstream drainage area to support automated generalization of the United States National Hydrography Dataset

Annual peak discharge records from 50 stations in the continental United States with at least 100 years of record are used to investigate stationarity of flood peaks during the 20th century. We examine temporal trends in flood peaks and abrupt changes in the mean and/or variance of flood peak distributions. Change point analysis for detecting abrupt changes in flood distributions is performed using the nonparametric Pettitt test. Two nonparametric (Mann‐Kendall and Spearman) tests and one parametric (Pearson) test are used to detect the presence of temporal trends. Generalized additive models for location, scale, and shape (GAMLSS) are also used to parametrically model the annual peak data, exploiting their flexibility to account for abrupt changes and temporal trends in the parameters of the distribution functions. Additionally, the presence of long‐term persistence is investigated through estimation of the Hurst exponent, and an alternative interpretation of the results in terms of long‐term persistence is provided. Many of the drainage basins represented in this study have been affected by regulation through systems of reservoirs, and all of the drainage basins have experienced significant land use changes during the 20th century. Despite the profound changes that have occurred to drainage basins throughout the continental United States and the recognition that elements of the hydrologic cycle are being altered by human‐induced climate change, it is easier to proclaim the demise of stationarity of flood peaks than to prove it through analyses of annual flood peak data.

The 9.1 km2 Moores Run watershed in Baltimore, Maryland, experiences floods with unit discharge peaks exceeding 1 m3 s−1 km−2 12 times yr−1, on average. Few, if any, drainage basins in the continental United States have a higher frequency. A thunderstorm system on 13 June 2003 produced the record flood peak (13.2 m3 s−1 km−2) during the 6-yr stream gauging record of Moores Run. In this paper, the hydrometeorology, hydrology, and hydraulics of extreme floods in Moores Run are examined through analyses of the 13 June 2003 storm and flood, as well as other major storm and flood events during the 2000–03 time period. The 13 June 2003 flood, like most floods in Moores Run, was produced by an organized system of thunderstorms. Analyses of the 13 June 2003 storm, which are based on volume scan reflectivity observations from the Sterling, Virginia, WSR-88D radar, are used to characterize the spatial and temporal variability of flash flood producing rainfall. Hydrology of flood response in Moores Run is characterized by highly efficient concentration of runoff through the storm drain network and relatively low runoff ratios. A detailed survey of high-water marks for the 13 June 2003 flood is used, in combination with analyses based on a 2D, depth-averaged open channel flow model (TELEMAC 2D) to examine hydraulics of the 13 June 2003 flood. Hydraulic analyses are used to examine peak discharge estimates for the 13 June flood peak, propagation of flood waves in the Moores Run channel, and 2D flow features associated with channel and floodplain geometry.

Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of ‘perennial’ and ‘non-perennial’ are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future.

Water resource evaluation and management rely heavily on detailed and well-classified data on water supply, demand, consumption, and withdrawals. The Water Accounting Plus (WA+) framework provides an effective platform to anticipate water flows by integrating remote sensing data to analyze water flows within a basin while accounting for land use. For the Mahi River, we used the WA+ framework to get insights about water inflows, outflows, consumption, withdrawals, and storage changes. The WaterPix (soil moisture water balance) model was employed to simulate hydrological processes at the pixel level. Here, we also employed blue and green water estimates to classify between irrigated and rainfed regions. The present state of the basin's water resources was also computed using performance indicators. As per our study, the Mahi River basin experiences water scarcity and heavily depends on groundwater (GW) for agriculture. From 2012-2020, there has been an average annual outflow of 20.65 BCM, with average annual flows of exploitable and available water being 34.07 BCM/year and 30.38 BCM/year, respectively. Furthermore, the average vertical GW recharge and outflow were 17.47 BCM/year and 21 BCM/year, respectively. Though, the average surface water (SW) withdrawal was lower and concentrated in a few regions. The outcomes from the GW sheets demonstrated a considerable dependence on GW, with 95% of the used flow coming from GW. Notably, over the study period, there was a 25% reduction in water storage, emphasizing the challenges of excessively using GW for irrigation and the decrease in water storage within the Mahi River basin. The conclusions of our study give local and national authorities important new information that they can use to spot regions with poor water management practices and create water management strategies and programs that are suitable for the basin's requirements.   

Water management in proton-exchange membrane fuel cells plays an important role in device operation, especially at lower temperatures where liquid water exists. Key to understanding water management is determining the mechanisms of water movement through the various fuel-cell components. Traditionally, continuum-scale mathematical modeling has been used to optimize and understand fuel-cell water and thermal management. However, it is increasingly become apparent that there is a need for more detailed lower lengthscale information to feed into the models due to microscale and mesoscale heterogeneities. In this talk, we will examine these issues with a focus on liquid-water movement in fuel-cell diffusion media and in water and ion transport in fuel-cell membranes including both proton and alkaline varieties. It is well known that continuum models use a volume-averaged approach to model liquid-water transport. This strategy is suitable for higher operating temperatures and homogeneous gas-diffusion-layer (GDL) morphologies, but, such structures are not realistic. To handle the complexity of the GDL morphology and access the expected capillary-fingering type of water transport in these porous media, pore-network models (PNMs) are utilized. However, while PNMs models capture the water transport through the GDL, they do not contain suitable descriptions of the other layers, complex nonlinear transport, and electrochemical phenomena. Here, we combine the advantage of both models in an iterative scheme integrating continuum and PN models to describe the multiphase and multiscale water transport properly. The coupling is achieved through an iterative scheme wherein the 2-D continuum PEFC model passes the calculated, heat and mass fluxes to the PNM, where they act as spatially varying source terms. Subsequently, the PNM returns to the continuum model a set of effective properties, such as thermal conductivity, effective diffusivity, and permeability, which are discretized along the electrode|GDL interface. This talk will discuss the work-flow between the coupled models including utilization of X-ray CT inputs and how such an approach can explain nonintuitive experimental data. For an ion-exchange membrane, mathematical modeling is ideally suited to explore the genesis of the observed water profiles and subsequently the mechanisms of water movement. Recently, such modeling has been receiving increased attention as new knowledge on the impact and control of the membrane/environment interface is elucidated. To model such effects requires the use of a multiscale framework involving mesoscale networks and microscale ion-transport information. The linking between these scales will be discussed including appropriate ways to incorporate molecular-level information into a physically consistent framework that still allows for easy incorporation into cell-level fuel-cell models. Acknowledgement I would like to acknowledge the various graduate students, postdocs, and collaborators who have worked on this research over the years. This work was supported by The Office of Energy Efficiency and Renewable Energy, Fuel Cell Technologies Office of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.