scholarly journals Spatiotemporal Evolution of Evapotranspiration in China after 1998

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3250
Author(s):  
Qi Guo ◽  
Jiening Liang ◽  
Xianjie Cao ◽  
Zhida Zhang ◽  
Lei Zhang
Keyword(s):  
Control Region ◽  
Large Scale ◽  
Water Cycle ◽  
East Asian Monsoon ◽  
Water Control ◽  
Energy Control ◽  
The Difference ◽  
Local Weather

Changes in water circulation and uneven distributions of water resources caused by global warming are prominent problems facing the world at present. It is important to understand the influencing factors, and evapotranspiration (ET) is a key parameter for measuring the water cycle. However, understanding of spatiotemporal changes in actual evapotranspiration and its mechanism is still limited by a lack of long-term and large-scale in situ datasets. Here, the evolution of evapotranspiration in typical East Asian monsoon areas in China from 1989 to 2005 was analyzed with global land ET synthesis products. Evapotranspiration in China showed evident interdecadal variations around 1998; it decreased before 1998 and subsequently increased, which is inversely related to global ET changes. We further divided China into water-control and energy-control regions to discuss the factors influencing ET changes in each region. The interdecadal variations in increasing ET after 1998 in China were dominated by increasing potential evaporation in the energy-control region. An analysis using the empirical orthogonal function (EOF) method found that this occurred because ET is mainly manifested as decadal changes controlled by climate warming in the energy-control region and as interannual variations in the water-control region. The different feedbacks of ET on climate change in the two regions were also reflected in the difference in energy partition. The change in the Bowen rate (BR) did not increase climatic differences between energy- and water-control zones, but increases in the BR in arid summers significantly affected local weather and climate.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

In Situ Tests on Creep Behavior of Rock Mass with Joint or Shearing Zone in Foundation of Large-Scale Hydroelectric Projects

2004 ◽  
Vol 261-263 ◽  
pp. 1097-1102 ◽  
Author(s):  
Jian Liu ◽  
Xia Ting Feng ◽  
Xiu Li Ding ◽  
Huo Ming Zhou
Keyword(s):  
Rock Mass ◽  
Creep Behavior ◽  
Large Scale ◽  
Time Dependent ◽  
Three Gorges Project ◽  
Three Gorges ◽  
The Three Gorges ◽  
The Three Gorges Project

The time-dependent behavior of rock mass, which is generally governed by joints and shearing zones, is of great significance for engineering design and prediction of long-term deformation and stability. In situ creep test is a more effective method than laboratory test in characterizing the creep behavior of rock mass with joint or shearing zone due to the complexity of field conditions. A series of in situ creep tests on granite with joint at the shiplock area of the Three-Gorges Project and basalt with shearing zone at the right abutment of the Xiluodu Project were performed in this study. Based on the test results, the stress-displacement-time responses of the joints and basalt are analyzed, and their time-dependent constitutive model and model coefficients are given, which is crucial for the design to prevent the creep deformations of rock masses from causing the failure of the operation of the shiplock gate at the Three-Gorges Project and long-term stability of the Xiluodu arc dam.

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

scholarly journals ENVIRONMENTAL POLLUTION BY WASTEWATER FROM BROWN COAL PROCESSING ¬ A REMEDIATION CASE STUDY IN GERMANY

2014 ◽  
Vol 22 (1) ◽  
pp. 71-83 ◽  
Author(s):  
Arndt Wiessner ◽  
Jochen A. Müller ◽  
Peter Kuschk ◽  
Uwe Kappelmeyer ◽  
Matthias Kästner ◽  
...  
Keyword(s):  
Environmental Pollution ◽  
Large Scale ◽  
Pilot Scale ◽  
Wastewater Disposal ◽  
Interdisciplinary Approaches ◽  
Phenolic Wastewater ◽  
Term Monitoring

The large scale of the contamination by the former carbo-chemical industry in Germany requires new and often interdisciplinary approaches for performing an economically sustainable remediation. For example, a highly toxic and dark-colored phenolic wastewater from a lignite pyrolysis factory was filled into a former open-cast pit, forming a large wastewater disposal pond. This caused an extensive environmental pollution, calling for an ecologically and economically acceptable strategy for remediation. Laboratory-scale investigations and pilot-scale tests were carried out. The result was the development of a strategy for an implementation of full-scale enhanced in situ natural attenuation on the basis of separate habitats in a meromictic pond. Long-term monitoring of the chemical and biological dynamics of the pond demonstrates the metamorphosis of a former highly polluted industrial waste deposition into a nature-integrated ecosystem with reduced danger for the environment, and confirmed the strategy for the chosen remediation management.

scholarly journals River Discharge Estimation based on Satellite Water Extent and Topography: An Application over the Amazon

2019 ◽  
Vol 20 (9) ◽  
pp. 1851-1866 ◽  
Author(s):  
Dinh Thi Lan Anh ◽  
Filipe Aires
Keyword(s):  
River Discharge ◽  
Amazon Basin ◽  
Water Cycle ◽  
Large River ◽  
Water Volume ◽  
Discharge Estimation ◽  
Three Rivers ◽  
Storage Change

Abstract River discharge (RD) estimates are necessary for many applications, including water management, flood risk, and water cycle studies. Satellite-derived long-term GIEMS-D3 surface water extent (SWE) maps and HydroSHEDS data, at 90-m resolution, are here used to estimate several hydrological quantities at a monthly time scale over a few selected locations within the Amazon basin. Two methods are first presented to derive the water level (WL): the “hypsometric curve” and the “histogram cutoff” approaches at an 18 km × 18 km resolution. The obtained WL values are interpolated over the whole water mask using a bilinear interpolation. The two methods give similar results and validation with altimetry is satisfactory, with a correlation ranging from 0.72 to 0.89 in the seven considered stations over three rivers (i.e., Wingu, Negro, and Solimoes Rivers). River width (RW) and water volume change (WVC) are also estimated. WVC is evaluated with GRACE total water storage change, and correlations range from 0.77 to 0.88. A neural network (NN) statistical model is then used to estimate the RD based on four predictors (SWE, WL, WVC, and RW) and on in situ RD measurements. Results compare well to in situ measurements with a correlation of about 0.97 for the raw data (and 0.84 for the anomalies). The presented methodologies show the potential of historical satellite data (the combination of SWE with topography) to help estimate RD. Our study focuses here on a large river in the Amazon basin at a monthly scale; additional analyses would be required for other rivers, including smaller ones, in different environments, and at higher temporal scale.

scholarly journals The decline and conservation management of the threatened endemic palms of the Mascarene Islands

Oryx ◽  
2002 ◽  
Vol 36 (1) ◽  
pp. 56-65 ◽  
Author(s):  
Mike Maunder ◽  
Wayne Page ◽  
John Mauremootoo ◽  
Richard Payendee ◽  
Yousoof Mungroo ◽  
...  
Keyword(s):  
Large Scale ◽  
Conservation Management ◽  
Conservation Status ◽  
Iucn Red List ◽  
Ex Situ ◽  
Population Fragmentation ◽  
Wild Populations ◽  
Mascarene Islands

Abstract The conservation status of the five genera and 11 species of palm endemic to the Mascarene Islands (Mauritius, La Réunion and Rodriques) are reviewed. All species are threatened with extinction; nine taxa are classified as Critically Endangered and four as Endangered on the 2000 IUCN Red List. Two taxa survive as single wild specimens (Hyophorbe amaricaulis and Dictyosperma album var. conjugatum); an additional seven taxa have wild populations of 100 or fewer. Although the historical phase of large-scale forest clearance has passed, the remaining palm populations in the Mascarenes are under threat from the effects of population fragmentation, invasive plants and animals, and high levels of seed predation that prevent natural regeneration. The advantages of in situ management for the recovery of these palm populations are discussed. Without a long-term conservation programme, utilising both in situ and ex situ management, extinction of wild populations will occur.

Influence of Intrinsic Factors on Erosive Tooth Wear in a Large-Scale Epidemiological Study

2016 ◽  
Vol 50 (5) ◽  
pp. 508-516 ◽  
Author(s):  
Viivi Alaraudanjoki ◽  
Marja-Liisa Laitala ◽  
Leo Tjäderhane ◽  
Paula Pesonen ◽  
Adrian Lussi ◽  
...  
Keyword(s):  
Large Scale ◽  
Erosive Wear ◽  
Tooth Wear ◽  
Risk Indicators ◽  
Health Examination ◽  
Convenience Sample ◽  
Erosive Tooth Wear ◽  
Intrinsic Factors ◽  
The Difference

Objective: To assess the influence of self-reported intrinsic factors [gastroesophageal reflux disease (GERD), long-term alcoholism, long-term heavy use of alcohol and multiple pregnancies] on erosive tooth wear in a middle-aged cohort sample. Materials and Methods: Of the total Northern Finland Birth Cohort (NFBC 1966), a convenience sample (n = 3,181) was invited for an oral health examination in 2012-2013, of which 1,962 participated, comprising the final study group. Erosive tooth wear was assessed by sextants using the Basic Erosive Wear Examination Index (BEWE, 0-18). Clinical data were supplemented by questionnaires conducted in 1997/1998 and 2012/2013. The participants were divided into severe (BEWE sum ≥9) and no-to-moderate (BEWE sum 0-8) erosive wear groups, and the logistic regression model was applied. Results: Selected intrinsic factors were quite rare in this cohort sample and explained only 5.9% of the difference in the prevalence and severity of erosive wear. Daily symptoms of GERD [odds ratio (OR) 3.8, confidence interval (CI) 1.2-12.0] and hyposalivation (OR 3.8, CI 1.2-11.8) were the strongest risk indicators for severe erosive wear. Additionally, variables associated with an elevated risk for severe erosive wear were diagnosed alcoholism at any point (OR 2.5, CI 0.7-9.7) and self-reported heavy use of alcohol in both questionnaires (OR 2.0, CI 0.6-6.2). Even low-dose long-term consumption of alcohol was associated with erosive wear. Conclusions: In this cohort sample, intrinsic factors such as GERD or alcoholism alone are relatively uncommon causes of erosive tooth wear. The role of long-term use of alcohol in the erosion process may be bigger than presumed.

scholarly journals Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

2011 ◽  
Vol 15 (2) ◽  
pp. 533-546 ◽  
Author(s):  
M. Becker ◽  
B. Meyssignac ◽  
L. Xavier ◽  
A. Cazenave ◽  
R. Alkama ◽  
...  
Keyword(s):  
Large Scale ◽  
Amazon Basin ◽  
Hydrological Modeling ◽  
Water Cycle ◽  
Southern Oscillation ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Direct Estimate ◽  
Terrestrial Water

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-D TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

Permeability characterization of the Soultz and Ogachi large‐scale reservoir using induced microseismicity

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 204-211 ◽  
Author(s):  
Pascal Audigane ◽  
Jean‐Jacques Royer ◽  
Hideshi Kaieda
Keyword(s):  
Large Scale ◽  
Pressure Oscillation ◽  
Data Sets ◽  
Active Volume ◽  
Common Procedure ◽  
Order Of Magnitude ◽  
Different Depths ◽  
The Difference

Hydraulic fracturing is a common procedure to increase the permeability of a reservoir. It consists in injecting high‐pressure fluid into pilot boreholes. These hydraulic tests induce locally seismic emission (microseismicity) from which large‐scale permeability estimates can be derived assuming a diffusion‐like process of the pore pressure into the surrounding stimulated rocks. Such a procedure is applied on six data sets collected in the vicinity of two geothermal sites at Soultz (France) and Ogachi (Japan). The results show that the method is adequate to estimate large‐scale permeability tensors at different depths in the reservoir. Such an approach provides permeability of the medium before fracturing compatible with in situ measurements. Using a line source formulation of the diffusion equation rather than a classical point source approach, improvements are proposed for accounting in situation where the injection is performed on a well section. This technique applied to successive fluid‐injection tests indicates an increase in permeability by an order of magnitude. The underestimates observed in some cases are attributed to the difference of scale at which the permeability is estimated (some 1 km3 corresponding to the seismic active volume of rock compared to a few meters around the well for the pumping or pressure oscillation tests). One advantage of the proposed method is that it provides permeability tensor estimates at the reservoir scale.

scholarly journals Variability of seasonal and annual rainfall in the River Nile riparian countries and possible linkages to ocean–atmosphere interactions

2015 ◽  
Vol 47 (1) ◽  
pp. 171-184 ◽  
Author(s):  
Charles Onyutha
Keyword(s):  
Large Scale ◽  
Equatorial Region ◽  
Annual Rainfall ◽  
River Nile ◽  
Short Term ◽  
Ocean Atmosphere ◽  
Data Points ◽  
The Difference ◽  
Term Data

Variability analyses for the rainfall over the Nile Basin have been confined mostly to sub-basins and the annual mean of the hydroclimatic variable based on observed short-term data from a few meteorological stations. In this paper, long-term country-wide rainfall over the period 1901–2011 was used to assess variability in the seasonal and annual rainfall volumes in all the River Nile countries in Africa. Temporal variability was determined through temporal aggregation of series rescaled nonparametrically in terms of the difference between the exceedance and non-exceedance counts of data points such that the long-term average (taken as the reference) was zero. The co-occurrence of the variability of rainfall with those of the large-scale ocean–atmosphere interactions was analyzed. Between 2000 and 2012, while the rainfall in the equatorial region was increasing, that for the countries in the northern part of the River Nile was below the reference. Generally, the variability in the rainfall of the countries in the equatorial (northern) part of the River Nile was found to be significantly linked to occurrences in the Indian and Atlantic (Pacific and Atlantic) Oceans. Significant linkages to Niño 4 regarding the variability of both the seasonal and annual rainfall of some countries were also evident.

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