查看更多>>摘要：Excessive groundwater pumping exacerbates aquifer depletion and poses a major threat in regions all around the world that already suffer from overuse or climate change. In this situation, accurate and reliable predictions of long-term aquifer water balances are key prerequisites to manage groundwater sustainably. Compared to spatially explicit numerical models, lumped hydrological models are computationally fast, lean on data requirement and more accessable for quantifying uncertainty. However, lumped hydrological models are mainly designed to simulate river discharge only, not aquifer storage. Consequently, calibration only includes stream flow data. In this study, we hypothesize that we can extend a lumped hydrological models (here HBV) towards a lumped geohydrological model (LGhM) by additional, designated terms for water budget and groundwater storage. The model building is inspired by the geometry and hydrogeological large-scale properties of the catchment's aquifers. Underground flow routing resembles major groundwater flow paths. The model is calibrated and evaluated on both groundwater storage data and surface discharge data. We apply our LGhM to a MODFLOW-based virtual reality describing the unconfined Wairau Plain Aquifer, New Zealand. We consider and discuss specifically river-groundwater exchange processes, long-term forecast of aquifer storage dynamics, and groundwater depletion in a hypothetical, persistent drought. Our model evaluation shows very plausible predictive capabilities in 40-year forecasts with synthetic weather time series and several years of groundwater depletion in the extreme drought case.
查看更多>>摘要：Soil water and salt movement in freezing-thawing periods play an important role in the agricultural ecological environment. Field experiments show a non-synchronized movement of soil water and salt during the freezing-thawing period with no definite mechanism. In this study, the non-synchronization of water and salt movement in the frozen layer (0-1 m) was analyzed from the perspective of soil salt composition combining with the convection-diffusion theory. Field experiments were carried out during two freezing-thawing periods from 2017 to 2019 in Yonglian experimental station of Hetao Irrigation District in Inner Mongolia, China. The contents of soil moisture, salt and its components (Na, K, Ca, Mg, CO3, HCO3, Cl and SO4) were measured. The correlation analysis between storage increments of total salt and its components was carried out and the FREZCHEM model was used to calculate the soluble and solid salt components. During the freezing period, the soil water storage increased by 5.42% on average, while the soil salt storage decreased by 18.69%, showing the different migration directions of soil water and salt. The migration direction of each component of salt was not exactly the same with that of the total salt. The main components causing the storage increment of soil salt were different in the three saline soils. The solute concentration gradient of soluble salt reached 3.07 mol/(L.m), which caused stronger diffusion effect to result in downward salt migration, while the convection effect drove the soil water and salt to move upwards. This is the major reason for the non-synchronization movement of soil water and salt during the freezing-thawing period. This study provides new data and perspective to understand the soil water and salt movement during the freezing-thawing period in agricultural areas with shallow groundwater table depth.
查看更多>>摘要：This study is the first attempt to assess the accuracy of water levels measured by the Sentinel-3A altimetry at virtual stations (VS) located along Polish rivers. The studied rivers (Vistula, Odra, Warta, Bug, Narew, San) drain predominantly lowlands, and - based on width - can be classified as small and medium rivers (40-610 m in width). The accuracy assessment is based on a comparison between water level anomalies from 34 VS and water level data from the nearest adjacent gauges, acquired from April 2016 to August 2019. The time lags between water level time series (VS vs. gauge) are estimated so that pairs of hydrographs agree in phase, which enables the comparison. It is found that the root mean square error ranges from 0.12 to 0.44 m, with mean of 0.22 m. The Nash-Sutcliffe efficiency (NSE) varies between 0.40 and 0.98 (with mean of 0.84) for 67 pairs of time series, out of 68 considered. It is also argued that river width does not reveal any impact on the performance of the altimetric measurements over the study area. Likewise, land cover has not been identified as an environmental factor to constrain the data accuracy. However, it is found that complex river channel morphology and unfavourable geographical setting occur more frequently at VS with lower NSE (<= 0.8). The study confirms the usability of the Sentinel-3A altimetry along small and medium rivers, identifies factors to constrain the accuracy and - most importantly - provides yet another regional-scale investigation into quality of satellite radar measurements over inland waters.
Nguyen, Duc HaiLe, Xuan HienAnh, Duong TranKim, Seon-Ho...
16页
查看更多>>摘要：Urban flooding is a global metropolitan problem; therefore, establishing reliable streamflow forecasting models is critical for flood control and planning in urban areas. Furthermore, assessing the importance and uncertainty of model predictors is useful for managers; however, these predictors are still underevaluated. To address these concerns, we developed a novel hybrid model, GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting. A case study was conducted in the Jungrang urban basin, which is located on the Han River in South Korea. The model was built and evaluated based on data collected during 39 heavy rain events from 2003 to 2020. To compare the model's forecast capability, a support vector regression model hybridized with a genetic algorithm (GA-SVR) and a multiple linear regression (MLR) model was constructed. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. The results illustrated that the GA-BART model outperformed the GA-SVR and MLR models in multistep-ahead streamflow forecasts, with improved measures of the root mean square error (RMSE), mean absolute error (MAE), relative error, Nash-Sutcliffe efficiency (NSE), time lag and correlation coefficient (CC). In addition, the GA-BART model could reasonably determine the relative importance of the input variables. This study demonstrated that, despite some disadvantages in the five- and six-hour step-ahead forecasts, the hybrid GA-BART model can be a good option among the available models for hourly streamflow forecasting.
查看更多>>摘要：Hydrodynamic features of the confluence zone of large rivers are complicated because of their three-dimensional flow structure. The confluence between the Rio Negro and the Rio Solimo similar to es, characterised by black and white waters, respectively, ranks among the largest river junctions on Earth. An Entropy-based investigation was carried out to assess the discharge and analyse the 2D structure of velocity distribution for large river flows relying on monitoring of near-surface velocity only. The estimated flow data where compared with in-situ ADCP data gathered across some transects of the Negro and Solimo similar to es rivers during both low and relatively high flow conditions. Results are illustrated through some transects at the confluence zone, upstream and downstream of the zone and in the Careiro Channel. Comparisons highlight that the Entropy-based flow velocity in terms of depth-averaged velocity, cross-sectional mean flow velocity and vertical velocity distributions, starting from the measured surface velocity, is in agreement with those determined by the ADCP measurements, with an error in mean flow velocity and discharge lower than 15%. The research highlights the potential of the Entropy method to estimate the discharge and velocity in very large rivers just relying on near-surface velocities monitoring.
查看更多>>摘要：The increasing winter streamflow of major Arctic rivers has been well documented. However, the contribution of climate change to winter streamflow and associated mechanisms of streamflow generation during early, mid- and late winter are not fully understood. Among the Arctic rivers, we selected four rivers with relatively few dam effects (Lena, Kolyma, Yukon and Mackenzie rivers) and analysed their climate change-related responses in streamflow during early, mid-, and late winter. Our results showed that the winter streamflow (Qwin) of the Lena, Kolyma, Yukon and Mackenzie rivers increased from 1980 to 2019 by approximately 43%, 72%, 16% and 16% (1.7-5.2 times greater than increases in annual streamflow), respectively. In general, the rate of streamflow increase was the greatest in early winter, followed by mid- and late winter. The streamflow in late winter was particularly sensitive to air temperature changes, and permafrost degradation due to rising temperatures is likely a major factor driving late winter streamflow increases. In contrast to late winter streamflow, the larger rate of increase in early winter streamflow can be mainly attributed to the additional influence of increased late summer precipitation on streamflow generation. The different change rates in winter streamflow among the four river basins are highly determined by permafrost degradation and related baseflow discharge processes. Under warming climate conditions, winter streamflow generation is strongly associated with the enhanced hydrological cycle that is apparent in both the surface (e.g., precipitation and river ice) and the subsurface (the active layer and groundwater discharge).
查看更多>>摘要：The latest generation of satellite precipitation estimates, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Version 06 (IMERG V06), calibrated by monthly rain gauge data, is applied to investigate the changing characteristics of precipitation in different phases (rain, snow, and sleet) over the Tibetan Plateau (TP) from 2001 to 2020. The performance of the IMERG product in capturing the characteristics of the three precipitation phases is firstly evaluated against the ground-based observation. The results show that the IMERG product performs well in capturing the spatial distribution, magnitudes, and annual cycle of the amount and frequency of precipitation in different phases. The bias of annual precipitation amount (frequency) averaged in the 90 stations used in this study is approximately 10% (20%). Comparatively, the IMERG product shows higher skill in estimating rain than snow, and performs better in the other three seasons than in winter. In addition, the performance of the IMERG product is comparable in the southern and northern TP. Both the annual amount and frequency of precipitation have increased in most parts of the TP in the last two decades, with maximal values of 50 mm and 20 days per decade, respectively, occurring in the central part of eastern TP. Changes in the amount and frequency of precipitation are dominated by rain and snow, respectively, in the study period. In addition, light and moderate precipitation contribute approximately 70% and 90% to the increases of the regional mean precipitation amount and frequency, respectively, in the central part of eastern TP. There are no significant and uniform changes in the snowy season during the last two decades, therefore, the increase in snowy days in most areas of the TP is caused by more frequent snow events in the fairly constant snowy season.
Guo, ShanshanZhang, FanEngel, Bernard A.Wang, Youzhi...
17页
查看更多>>摘要：Sustainable agricultural development covers all aspects of agricultural production involving the water-foodenergy nexus (WFEN) and considers the effects of agricultural activities on society, economy and ecology. Multi-objective optimization models play an important role in making tradeoff among multiple interests of stakeholders. Aimed at canal-based irrigated agricultural areas, water allocation highly depends on canal distribution, and the spatial location of irrigation regions determines their water-intake order, which usually induces serious water allocation inequality. The social, economic and ecological problems resulting from water inequality would deteriorate without intervention and seriously impact sustainable development. Thus, optimization models must consider water use equity, water-intake order as well as water equilibrium simultaneously. However, this will greatly increase computational efforts and solution difficulty. The problem becomes worse when uncertain factors are involved. In order to overcome these difficulties, a distributed multi-objective uncertain optimization model was established to help develop comprehensive strategies for agricultural sustainability. A novel robust solution method was proposed to offer an efficient way to handle stochastic and fuzzy uncertainties from the perspective of feasibility and optimality robustness. Finally, a case study was conducted to demonstrate the practical application of the developed model. The results offer managers insights on agricultural sustainable development.
查看更多>>摘要：Compound flooding caused by high rainfalls and tides may salinize the soil, deteriorate the water quality, and damage the ecosystems in coastal areas. Traditionally, compound flood risk is estimated using the joint probabilities of a rainfall and a tide level when they are simultaneously or individually exceeded. This results in bias because flood risk should represent the exceeding probability of a flood magnitude, not of the triggers' values. In this study, a new approach is proposed to determine the exceedance probability for a flood depth induced by the compound effects of rainfall and tide through the combination of copula analysis, numerical simulation, multiple regression, and Monte Carlo integration. A frequently flooded coastal area in Chiayi, Taiwan, was selected as the study subject. The results show that realistic flood risk should range between the joint probabilities of rainfall and tide levels being simultaneously or individually exceeded. Thus, when the joint probabilities are used to determine the thresholds of rainfall and tide for flood warning and hydraulic design, the misestimation of flood risk will result in errors such as incorrect alarms and inaccurate protections with a ratio of 37% in a case study with 10-year return period. These errors can be reduced using a hybrid cumulative probability function developed in this study for selecting the best rainfall and tide thresholds with local maximum or minimum cumulative flood probabilities. The proposed approach is efficient and general, so it can be promoted in different fields for risk assessment influenced by bivariate variables.
查看更多>>摘要：An integrated simulation-optimization framework is developed under uncertainty to enhance irrigation water productivity and control salinity in an arid area. A full fuzzy dependent linear fractional programming approach is formulated by incorporating fuzzy dependent-chance programming, fuzzy credibility-constrained programming and linear fractional programming within a general framework of irrigation planning. Then, simulation module concerning water, salt balance process and crop water-salt production functions enables to quantify daily physical process of water and salt movement among the soil water, crop root zone and groundwater aquifers. Thus, this study can readily handle fuzzy uncertainty existing concurrently in the ratio objective (i.e., economic water productivity) through the concept of fuzzy dependent chance and double-sided constraints. It can also simultaneously provide the maximum credibility level that the objective is achievable and credibility levels implying that optimal solutions are believable. Besides, daily variations of simulated physical parameters are illustrated corresponding to management strategies. To demonstrate its applicability, it's then applied to a case study of irrigation planning in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, northwest China. Results can clearly analyze tradeoffs among satisfaction degree of fuzzy objective, fuzzy constraints and optimal solutions. Moreover, by examining different management targets and salt accumulation constraints, this study demonstrates the merits and importance of the work to promote irrigation water productivity and control salinity. Dynamic decision making of irrigation planning is possibly made by coupling daily simulation and optimization modules. Therefore, these findings can support decision makers to identify appropriate solutions for irrigation planning.
NSTL
Elsevier