查看更多>>摘要：Climate is changing in ways that may significantly affect the provision of hydrologic ecosystem services in arid or semi-arid regions. To answer this challenge, there has been an effort to increase the adaptive capacity of organizations that manage water and the land-uses water supports. Governmental and non-governmental organizations (NGOs) managing large landscapes in the United States Northern Rockies region have access to a variety of water decision-support tools, such as indicators of precipitation and snowpack, which could increase their adaptive capacity to manage hydrologic ecosystem services under changing conditions. Yet little is known about the use of decision-support tools in this region and how tools could be improved. With the aim of informing future tool development and addressing information-use gaps, we conducted semi-structured interviews with representatives of federal and state agencies and NGOs to 1) identify which tools are being used, 2) describe tool supported management actions across different types of organizations, and 3) determine "usability" criteria managers consider when adopting a climate tool. Through qualitative analysis, we found multiple types of tools being used, including processes and frameworks, data and models, and geospatial or web-based tools. We also identified several criteria that study participants used to assess whether or not to use a tool within their organization, including tool accuracy, robustness, extendibility, interpretability, capacity, and institutional fit. This study suggests that increased communication between tool developers and end-users, with a focus on tools' relevance and ability to support management actions, could improve tools and increase the adaptive capacity of users. This research also points to the need for multiple lines of future research including how to improve the fit between organizational goals and water tools.
Kjellman, Sofia E. E.Thomas, Elizabeth K. K.Schomacker, Anders
16页
查看更多>>摘要：High-latitude lakes are sensitive to climate change and store information about large-scale circulation changes and catchment-integrated processes. Lakes are mainly recharged by meteoric water, meaning that some lake sediment proxies may indirectly archive the stable isotopic composition of hydrogen (delta H-2) and oxygen (delta O-18) of past precipitation. Yet, despite similar precipitation input, lakes within a region may exhibit a wide range of isotopic values due to the varying influence of inflow seasonality and evaporation. Moreover, the relative sensitivity of each lake to these controls may vary through time, something that is difficult to account for. Here, we evaluate the impact of variable inflow delta H-2 and evaporation on the lake water isotopic composition across northern Fennoscandia (Norway, Finland, and Sweden). We measured lake water delta H-2 and delta O-18 of 135 lakes spanning from the north Norwegian coast along a 460 km transect to the Bothnian Bay, sampled from 2018 to 2020. Our data show that both coastal and inland lakes are sensitive to distillation during moisture transport, and that lakes farther from the Atlantic Ocean are additionally impacted by evaporation. We estimated the isotopic composition of lake water inflow values for evapo-concentrated transect lakes (delta H-2(I)) using a Bayesian method. Resampled transect lakes had more depleted delta H-2(I) in 2020 than in 2019, indicating either that precipitation was H-2-depleted or that more winter precipitation contributed inflow to the lakes in 2020 compared to in 2019. We suggest that the more & nbsp;H-2-depleted values in 2020 were a response to a snow-rich winter, associated with extremely positive Arctic Oscillation (AO+) conditions and increased moisture supply from the North Atlantic. We find evidence that lake water isotopic variability in this region reflects a combination of seasonal precipitation changes associated with atmospheric circulation changes, and catchment-integrated evaporation. Careful consideration of the variable sensitivity to these processes is essential when making inferences about past climate based on lake water isotope proxies.
查看更多>>摘要：Actual evapotranspiration (AET) is a critical component of hydrological processes. Accurate estimation of AET variation and its driving hydrological factors is vital for natural hazard adaptation and water resource management. This study first used AET observations from FLUXNET at 12 flux tower sites representing four different land cover types and three climate zones over Northeast Asia. Then the relationships and seasonal patterns among AET and seven hydrological variables of gross primary production (GPP), wind speed (WS), air temperature (T-a), net radiation (R-N), soil moisture (S-M), precipitation (P), and air pressure (P-a) were assessed using Bayesian model averaging (BMA). Finally, the performance of BMA was examined at all flux tower sites, and the impact of factor importance to predicting performance was analyzed. Generally, the results demonstrated higher AET values at sites associated with temperate and cropland areas. Analysis of the contributions of key elements to AET based on BMA suggested that RN and GPP were the two most sensitive factors for AET variation over all the selected sites. With the exception of RN and GPP, WS strongly influenced AET estimations in the wetland and cold regions. AET variation in the cropland and grassland regions was significantly affected by SM. Regardless of landscape type and climate zone, RN was the most important variable in each season, followed by GPP, WS, T-a, and SM. T-a was found to be important in spring, while WS showed a strong influence on AET in winter. In terms of prediction performance, the mean correlation coefficient and root mean square error (RMSE) of the BMA model was 0.92 and 0.49 mm/day, respectively. Using more factors with a posterior inclusion probability larger than 0.9 improved the performance of BMA. Overall, the strong correlation and low error demonstrate that BMA is an effective approach to capturing AET and exploring its interaction with climatological anomalies across different regions, especially under varied agricultural conditions, which could improve crop water management.
查看更多>>摘要：Mid-winter breakups (MWBs), consisting of the early breakup of the winter river ice cover before the typical spring breakup season, are becoming increasingly common events in cold region rivers. These events can lead to potentially severe flooding, while also altering the expected spring flow regime, yet data on these events is limited. In this study, a newly released Canadian River Ice Database (CRID), containing river ice data from 196 rivers across Canada obtained from time series analysis, was used to analyse these MWBs on a previously impossible national scale. The CRID data was combined with the Natural Resources Canada (NRCan) gridded daily climate dataset to identify a list of potential hydrologic and climatic drivers for MWB events. Techniques such as correlation analysis, Least Absolute Selection Shrinkage Operator (LASSO) regression, and input omission were combined to select 20 key drivers of the severity of MWB events. A random forest model that was trained with these drivers using data-driven modelling techniques successfully classified the MWBs as either low, medium, or high severity, achieving an overall accuracy of 80%. A new threshold for the prediction of MWB initiation based on climatic conditions was subsequently proposed through the use of optimization via an exhaustive grid search and its accuracy in identifying MWBs exceeded those proposed by previous studies. The new threshold used in conjunction with the random forest model provide valuable tools for both the prediction of MWBs and the assessment of their potential severity.
查看更多>>摘要：ABSTR A C T Core-scale spontaneous imbibition experiments and numerical simulations have demonstrated that the macro-scopic imbibition performance is significantly different under different boundary conditions. However, the detailed pore-scale flow mechanisms behind these phenomena and the influence of porous media's geometric features on the imbibition behavior under different boundaries have not been addressed in depth. In this work, an optimized color-gradient lattice Boltzmann model is applied to simulate spontaneous imbibition in granular media under four boundary conditions. The influence of grain shape and packing pattern on the two-phase interface evolution and the recovery factor during spontaneous imbibition is investigated while fixing different models' porosity, grain number, and size distribution. It is found that the grain shape has little influence on the drainage interface evolution at the initial stage but it has a more significant influence on the imbibition interface during counter-current spontaneous imbibition. The grain packing pattern influences the evolution of drainage and imbibition interfaces and the recovery factor. Spontaneous imbibition with different boundary conditions has different imbibition rates and ultimate recovery factors. The fastest imbibition rate and highest ultimate recovery are obtained under all faces open and two faces open (free) boundary conditions, respectively. This research provides pore-scale insights into the complex dynamic fluid displacement mechanism between the fracture and matrix of fractured oil and gas reservoirs.
Zhuang, ChaoLi, YabingZhou, ZhifangIllman, Walter A....
12页
查看更多>>摘要：A hydrogeological unit with a considerable thickness usually demonstrates depth-decaying hydraulic conductivity (K) at the regional scale. In this study, we investigated transient well hydraulics (i.e., aquifer and aquitard drawdown) and groundwater budget (i.e., fractions of groundwater withdrawal including aquifer depletion, aquitard depletion and leakage from the unconfined aquifer) within a leaky aquifer system considering an exponentially decaying K of the aquitard, parameterized with a dimensionless decay coefficient (Ad). Relevant semi-analytical solutions were derived using the Laplace transform and Hankel transform techniques, while drawdown and groundwater budget characteristics and their sensitivities to Ad were theoretically analyzed. Theoretical analysis results suggested that a larger Ad consistently leads to a larger aquifer drawdown, a smaller aquitard drawdown, a larger fraction of aquifer depletion and a smaller fraction of leakage from the unconfined aquifer. Sensitivity analysis results also indicated critical effects of Ad on well hydraulics and groundwater budget. Comparative analysis revealed that none of the three typical mean values of depth-decaying aquitard K can perfectly characterize the well hydraulics and groundwater budget from early to intermediate times. However, the harmonic and geometric mean values can be feasibly used to calculate the final fractions of aquifer depletion and aquitard depletion at late times, respectively. Limitations of the newly developed analytical model have also been discussed. Practical investigations of vertical aquitard heterogeneity and further applications of this new model are recommended.
查看更多>>摘要：Simulation of multiphase flow in porous media is essential to manage the geologic CO2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO2 as a deep learning feature, leads to the most accurate prediction of CO2 saturation. For the post-injection period, it is key to use cumulative CO2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.
Kessler, JamesFry, LaurenRead, Laura D.Nasab, Arezoo Rafieei...
13页
查看更多>>摘要：Reliable precipitation estimates are a crucial component for hydrologic modeling and hydro-climate applica-tions. However, watersheds that extend across international boundaries or those that contain large bodies of water pose particular challenges to the acquisition of consistent and accurate precipitation estimates. The North American Great Lakes basin is characterized by both of these features, which has led to long-standing challenges to water budget analysis and hydrologic prediction. In order to provide optimal conditions for hydrologic model calibration, retrospective analyses, and real-time forecasting, this study comprehensively evaluates four gridded datasets over the Great Lakes basin, including the Analysis of Record for Calibration (AORC), Canadian Pre-cipitation Analysis (CaPA), Multi-sensor Precipitation Estimate (MPE), and a merged CaPA-MPE. These products are analyzed at multiple spatial (overland, overlake, sub-basin, country) and temporal (daily, monthly, annual) scales using station observations and a statistical water balance model. In comparison with gauge observations from the Global Historical Climatology Network Daily (GHCN-D), gridded datasets generally agree with ground observations, however the international border clearly delineates a decrease in gridded precipitation accuracy over the Canadian portion of the basin. Analysis reveals that rank in gridded precipitation accuracy differs for overland and overlake regions, and between colder and warmer months. Overall, the AORC has the lowest variance compared to gauge observations and has greater performance over temporal and spatial scales. While CaPA and AORC may better capture atmospheric dynamics between land and lake regions, comparison with a statistical water balance model suggests that AORC and MPE provide the best estimates of monthly overlake precipitation.
查看更多>>摘要：Iron (Fe) (oxyhydr)oxides and organic matter (OM) are important hosts of geogenic phosphorus (P) in groundwater systems. However, the coupled influence of Fe (oxyhydr)oxides and OM on the occurrence and mobility of P in groundwater remains unclear. In this study, we shed light on the underlying mechanisms of the control of Fe (oxyhydr)oxides and OM on P mobilization in the alluvial-lacustrine aquifers at the Dongting Plain (DTP), central China, using tracing techniques of isotopes (delta C-13-DIC and delta Fe-56), characterization of dissolved organic matter (DOM), and groundwater geochemistry. The results suggest that high concentrations of geogenic P up to 3.58 mg/L as total dissolved phosphorus (TDP) tend to occur in relatively reducing and sluggish hydrogeological environments experiencing longer time of water-rock interactions, and are closely related to the reductive dissolution of P-rich Fe(III) (oxyhydr)oxides as well as the mineralization of organic P. Our observations suggest that two different processes between Fe(III) (oxyhydr)oxides and OM contribute to the high concentrations of TDP in groundwater. Firstly, under moderately reducing conditions, labile OM is oxidized, with amorphous Fe(III) (oxyhydr)oxides acting as electron acceptors. Subsequently, the adsorbed and/or occluded P on/into OM or amorphous Fe(III) (oxhydr)oxides is concomitantly released into groundwater. Secondly, under strongly reducing conditions, the degradation of recalcitrant OM depends on the concurrent roles of crystalline Fe(III) (oxyhydr)oxides as electron acceptors and conduits, which further influence the mobility of P. The latter P-mobilizing redox processes were identified to prevail over the former in the groundwater of DTP. This study provides new insights into the anomalous concentration of P in groundwater of alluvial-lacustrine sandy aquifer systems.
Wang, HengKou, ZuhaoBagdonas, Davin A.Phillips, Erin H. W....
14页
查看更多>>摘要：Integration of petrophysical and geological information is critical to simulation of subsurface carbon storage (GCS). In this sense, two depositional facies were identified from the core description and well-log interpretation, namely massive (MS) and cross-bedded (CB) facies groups. Additionally, pore-scale characteristics were studied by a combination of techniques, e.g. Nuclear Magnetic Resonance (NMR) and mercury intrusion capillary pressure (MICP). Scanning electron microscope (SEM) and petrographic analyses show that the pore structure is dominantly controlled by the depositional environment and dolomite cementation. NMR-T-2 distributions of MS and CB facies show triple and quadruple modes, respectively. In addition, MICP of high-and low-permeability MS facies samples, and their CB facies group mixtures were collected. The MS sample pore-throat size distribution is uni-modal, while the triple-modal characteristic of the mixtures indicates heterogeneous pore structures at the sub-core scale for CB facies. The reliably estimates of porosity and permeability for both facies groups via NMR techniques and the MLR (Multiple Linear Regression) approach demonstrate the applicability of these techniques to eolian sandstone. Moreover, irreducible water saturation via the T-2-cutoff method correlates strongly with T-2LM instead of porosity. Finally, the rock quality index and flow zone indicator were calculated based on Combinable Magnetic Resonance (CMR) log interpretations. This provides direct connection to properties measured in the well. Four flow units were classified for both facies groups. Results show that better reservoir quality with significant heterogeneities is observed in the CB facies. This study highlights the importance integrating multiscale petrophysical properties including facies, pore architecture and diagenesis analysis with core-to log-scale property characterization. The results herein validate our reservoir characterization and flow unit classification in eolian reservoirs.
NSTL
Elsevier