查看更多>>摘要：The composition of suspended particles is a key factor in determining the underwater light field, which is of great significance for understanding the variability in the optical properties of water bodies. In this study, the ratio of the phytoplankton absorption coefficient to the backscattering coefficient at wavelength of 681 nm (a(ph)(681)/ b(b)(681)) was found to be an optimal optical indicator of the ratio of chlorophyll-a to the total suspended matter concentration (Chla/TSM), a parameter indicating the particulate composition. Therefore, a semianalytical algorithm was proposed to estimate Chla/TSM from remote sensing reflectance (Rrs(lambda)) at 681 nm and 754 nm on Sentinel-3 Ocean and Land Color Instrument (OLCI) images. The validation dataset collected from 11 inland lakes and 3 reservoirs in China and 2 inland lakes in America was used to evaluate the algorithm's performance. The evaluation results demonstrated that the proposed algorithm could have favorable performance in inland waters. Furthermore, comparison with two other state-of-the-art algorithms (Sun_13 and NTD675) showed that this proposed algorithm had higher estimation accuracy, with an overall winning rate (OWR) of 60%, an unbiased mean absolute percentage error (UMAPE) reduction from 72.95% to 46.44%, a root mean square error (RMSE) decline from 1.42 mu g/mg to 0.83 mu g/mg and a normalized root mean square error (NRMSE) decline from 11.36% to 6.62%. This algorithm was successfully applied to acquire the Chla/TSM tempo-spatial variation using the OLCI images of Lake Taihu from 2016 to 2019. It was found that the algorithm developed based on OLCI images can be applied to satellite sensors with similar bands, such as Medium-Resolution Imaging Spectrometer (MERIS), and Sentinel-2 multispectral instrument (MSI), etc. As a simple and effective algorithm, the proposed algorithm has the potential to monitor changes in Chla/TSM in inland waters on a global scale.
查看更多>>摘要：The migration of salt marshes into forests along coastal regions is nowadays well documented. Sea level rise and storms threaten coastal forests by increasing groundwater levels and salinity. Salinization is the main cause of forest conversion to salt marsh in North America. In this paper we study groundwater levels and salinity in two wells installed at the border between forest and salt marsh in the lower Delmarva peninsula, USA. The upper well is located in the regenerative forest, where recruitment is still possible, while the lower well is located in the persistent forest, where only mature trees survive. Groundwater in the upper well is fresh at the root depth, while in the lower well the mean salinity is 8 ppt. Our data suggest that rainfall has an instantaneous effect on salinity and groundwater levels, but it does not affect salinity and groundwater levels on longer periods (weeks to months). Groundwater levels and salinity reflect the hydraulic gradient toward the marsh (a proxy for outgoing water fluxes), the uphill hydraulic gradient (a proxy for incoming water fluxes) and temperature (a proxy for evapotranspiration). Salinity increases when groundwater levels are high. To explain this result, we put forward the hypothesis that a high water table favors the flux of surficial, fresh water to the marsh, and loss of freshwater by evapotranspiration. These losses are likely replenished by saltier water moving at depth.
查看更多>>摘要：It is shown that the imbalance between the valley slope and the regime channel slope is the primary cause of river meandering when the sediment load is less than the load transporting capacity and if bank erodibility permits. When a river reach is confronted by a steep valley-slope it tries to maintain uniformity in energy-expenditure by expending the excess energy through channel curvature. Novel equations are analytically developed for the channel radius of curvature, sinuosity, wave length, arc length, initial arc angle, the meander path and a modified sine-generated curve based on width, depth, flow, sediment load, and roughness. These equations are more general than geometrical correlations between meander variables and width that were previously proposed in the literature. The developed channel sinuosity and wave length equations compare well with the available field data. Meandering in both alluvial and tidal channels, as well as in sediment-less environments (supraglacial channels) could be explained by the theory.
查看更多>>摘要：The surface flow is significantly affected by catchment geomorphological characteristics, which have been widely used in the empirical equations in hydrograph predictions. Previous studies have explored the relation-ship between streamflow and geomorphology however mostly based on local observations, which are site-specific and unconvincing to be used as a universal principle. Here we adopted a robust approach by creating over 2000 virtual catchments from the Brue catchment in the UK using a well-trained distributed model, SHE -TRAN. The virtual catchments were allocated with a range of values in slope, drainage length and different shapes with a spatially uniform rainfall. We calculated the time to peak and the peak streamflow of unit hydrographs to explore the effect of catchment geomorphology on streamflow generation. The results present a consistent agreement with hydrological principles, i.e. shorter time to peak and higher peak values are observed with larger slope while longer time to peak and lower peak are experienced with longer drainage path. It was found that the shape of catchments can affect the streamflow characteristics. We found the officially used empirical UH equation in the UK represent the catchment geomorphology poorly. In addition, we found the streamflow properties are different when receiving varied intensity and temporal pattern of the storms. This study comprehensively explores the effect of geomorphology on streamflow avoiding the issues caused by catchment limitations in previous studies and imported different types of storms. Although it is away from generating an equation that can be generally adopted, more importantly it provides a feasible approach to investigate the unit hydrograph for different catchments with the virtual catchments.
查看更多>>摘要：Transpiration (T) is a key hydrological process, delivering water essential for plant metabolism and thus affecting productivity. A major challenge in estimating stand T is how to accurately scale sap flow data from individual trees to the stand. In shrub ecosystems, various scaling up methods have been used to extrapolate tree-level sap flow measurements to stand-level T, these include leaf area, cross-sectional area and number of branches. However, the performances of different scaling up methods have not been fully explored for shrubs. In this study, we measured sap flow of a xerophytic shrub (Salix psammophila) and scaled up using measures of leaf area, crosssectional area and numbers of branches in order to estimate stand T during the rainy seasons in 2019 and 2020 on the northern Loess Plateau, China. In addition, we measured precipitation, throughfall, stemflow, soil evaporation, surface runoff and 0-200 cm soil water content to calculate actual stand T on the basis of soil water balance method. The results revealed that daily stand T differed according to the scaling up methods used for the estimation. Daily estimated stand T based on measures of leaf area (0.1-13.1 mm d(-1)) was consistently higher than those based on cross-sectional area (0.2-8.6 mm d(-1)) and number of branches (0.4-8.9 mm d(-1)) (p < 0.05). During the two rainy seasons, the actual daily mean stand T (2.5 +/- 1.6 mm d(-1)) was significantly lower than the estimation by the three scaling up methods (p < 0.05). The method based on cross-sectional area appeared to be most suitable for scaling up because it had the lowest root mean square error and bias values (0.939 mm d-1 and 0.633 mm d(-1), respectively). This study highlights the wide variations of stand T upon which scaling up method was chosen, and these differences need to be considered when converting tree-level sap flow to stand-level T in shrub and other ecosystems.
查看更多>>摘要：Soil moisture (SM) is the most direct and important source of crop water requirement. The change in SM levels and the maize water requirement (MWR) will, under the influence of climate change, lead to changes in the areas that are suitable for maize cultivation in Northeast China (NEC). To quantitatively investigate these changes, the study analyzed the spatiotemporal changes in the SM and MWR in NEC from 1961 to 2010 using Global Land Data Assimilation System (GLDAS) SM products, meteorological data and land use data. The following conclusions were reached: 1) In the past 50 years, there has been an obvious trend of soil drying in NEC, and the equivalent water thickness at the depth of 0-200 cm has decreased by 71.06 mm (12.78%), which is more serious in agricultural areas (77.09 mm, 13.86%). 2) From 1961 to 2010, the air temperature in NEC increased by about 1.8 degrees C in 50 years.. 3) The shortage in maize water calculated by SM and MWR showed that areas unsuitable for maize cultivation increased by approximately 66,250 km(2), an area close to one-third of the dry farmland area in NEC; and 4) the slightly decreased precipitation and increased air temperature were the major driving factors for the decrease in the suitable maize cultivation area. If the maize was planted in unsuitable areas for a long time, it may lead to excessive use of groundwater and surface water. Therefore, these results provide a base for decisionmaking regarding adjustments to the cultivation structure in NEC.
查看更多>>摘要：This corrigendum is related to Bretreger et al. (2020) where a range of Landsat 5, 7 and 8 observations were used to monitor irrigated cropping conditions and using these observations in three modelling approaches with meteorological data to quantify the irrigation-area level water use (i.e., actual evapotranspiration (AET))., One of the remote sensing AET methods was CMRSET (Guerschman et al., 2009) and in a response to Bretreger et al. (2020) the authors Pena-Arancibia et al. (2021) clarified the implementation of CMRSET by using the Landsat SWIR2 band (2090 - 2350 nm wavelength). Using this Landsat band matched the naming of the band used in the CMRSET development with MODIS (i.e., SWIR2) despite having a different wavelength (1628 - 1652 nm wavelength) between the two remote sensing instruments. The SWIR bands from MODIS and Landsat may match in naming but their wavelengths differ. This means that the Landsat SWIR1 band (1550 - 1750 nm wavelength) should have been used when implementing CMRSET with Landsat to optimally represent the CMRSET method rather than using Landsat SWIR2 (2090 - 2350 nm wavelength) as performed in Bretreger et al. (2020). The analysis contained in this corrigendum acknowledges this mistake and shows the impact of this on the estimated irrigation results, demonstrating that CMRSET is a viable option for the AET component of methodologies that are attempting to quantify regional irrigation water use. Other results originally documented in Bretreger et al. (2020), specifically those generated using the IrriSat and Kamble AET methods, were not impacted by the sub-optimal use of the Landsat SWIR2 band.
Khodaei, BehshidHashemi, HosseinNaghibi, Seyed Amir
14页
查看更多>>摘要：Land subsidence is an increasing human-induced disaster that not only damages building and transportation structures but also diminishes the water storage capacity of the aquifers. Land subsidence is a very complex phenomenon impacted by various geo-environmental and hydrological factors. Application of the interferometric synthetic aperture radar (InSAR) is becoming a common approach to detect land subsidence rates, though, it suffers from the lack of continuity over the spatial surfaces due to the vegetation decorrelation, coverage alterations (cultivation and non-cultivation seasons), in the agricultural areas, and rough topography. The lack of continuity can, however, be resolved using artificial intelligence. In our case study, while InSAR deformation data only covered ~ 2% of the plain's surface, we employed boosted regression trees (BRT) and extreme gradient boosting (XGB) algorithms to provide a full coverage map of the groundwater-induced land subsidence based on the InSAR analysis. For this, a set of topographical, hydrological, hydrogeological, and anthropogenic factors was selected. The InSAR and input factors' resolution data were resampled to a 100-by-100 m to match. The implemented models predicted the long-term deformation rate with the acceptable performances of the BRT (RMSE = 3.3 mm/year, MAE = 2.0 mm/year, R-2 = 0.985) and the XGB with linear booster (RMSE = 3.5 mm/ year, MAE = 2.1 mm/year, R-2 = 0.983). Considering the substantial ground deformation in the studied area (from-216 to 49 mm/year), RMSE values of 3.3, and 3.5 mm/year between the InSAR measurement and model predictions show great potential for combined InSAR-machine learning technique for pumping-driven land subsidence studies. Thus, the introduced approach is suggested for other areas being damaged by excessive pumping and agricultural development to produce an accurate full coverage map of subsidence.
查看更多>>摘要：Accurate and effective assessment of groundwater vulnerability is very important for ensuring a healthy groundwater ecosystem. We evaluate the vulnerability of shallow porous aquifers by modifying the DRASTIC model and verify the effectiveness of the variable weight model (VWM). Firstly, topography, aquifer media, and the impact of the vadose zone are replaced by land-use type, aquifer thickness, and the hydraulic resistance of the vadose zone. Second, the weighting is optimized using the analytical hierarchy process (AHP) and variable weight theory (VWT). Thirdly, the original and the improved DRASTIC methods were used to evaluate groundwater vulnerability. Finally, three sets of samples hydrochemical parameters ( NO3-, Mg2+,COD) were used to verify the improved frameworks using the Receiver Operating Curve (ROC) method. The improved model increases the dispersion degree of groundwater vulnerability. Compared with the original DRASTIC method, the correlation of the VWM is significantly improved in terms of the area under curve (AUC) for NO3- (0.786), COD (0.753), and Mg2+ (0.831). In short, it is necessary to optimize the parameters and weights of the model in order to realize reliable estimations of groundwater vulnerability. In particular, the use of VWM brings the results in line with the actual situation by changing the weights.
查看更多>>摘要：Virtual scarce water (VSW) is an improved indicator of virtual water, enabling meaningful comparisons between water use of products from regions with different water resources and water scarcity. This study considers virtual water for comprehensive water pressures (VWCP) as an improvement to VSW, adding a more thorough consideration of available water resources, including the consideration of ecological water demand, like aesthetic water demand, shipping water demand, and unusable flood water. An input-output (IO) model is built to calculate the VWCP contained in the final product of industrial sectors. The Pearl River Basin (PRB) and Haihe River Basin (HRB) in China are used as study cases to evaluate the model. The results show that the pressure of water resource consumption in HRB has exceeded its carrying capacity, and the pressure of water resource consumption in the PRB, which is rich in water resources, is greater than current models report. These findings support the observations that VWCP can reveal more pressures of water resource usage than traditional VSW. Thus the new VWCP model can account for and improve environmental and social ethics in VW management and trading.
NSTL
Elsevier