| 1. |
- Aad, G, et al.
(författare)
-
- 2015
-
swepub:Mat__t
|
|
| 2. |
-
- 2019
-
Tidskriftsartikel (refereegranskat)
|
|
| 3. |
- Arias-Rodriguez, Leonardo F., et al.
(författare)
-
Global Water Quality of Inland Waters with Harmonized Landsat-8 and Sentinel-2 Using Cloud-Computed Machine Learning
- 2023
-
Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 15:5
-
Tidskriftsartikel (refereegranskat)abstract
- Modeling inland water quality by remote sensing has already demonstrated its capacity to make accurate predictions. However, limitations still exist for applicability in diverse regions, as well as to retrieve non-optically active parameters (nOAC). Models are usually trained only with water samples from individual or local groups of waterbodies, which limits their capacity and accuracy in predicting parameters across diverse regions. This study aims to increase data availability to understand the performance of models trained with heterogeneous databases from both remote sensing and field measurement sources to improve machine learning training. This paper seeks to build a dataset with worldwide lake characteristics using data from water monitoring programs around the world paired with harmonized data of Landsat-8 and Sentinel-2. Additional feature engineering is also examined. The dataset is then used for model training and prediction of water quality at the global scale, time series analysis and water quality maps for lakes in different continents. Additionally, the modeling performance of nOACs are also investigated. The results show that trained models achieve moderately high correlations for SDD, TURB and BOD (R2 = 0.68) but lower performances for TSM and NO3-N (R2 = 0.43). The extreme learning machine (ELM) and the random forest regression (RFR) demonstrate better performance. The results indicate that ML algorithms can process remote sensing data and additional features to model water quality at the global scale and contribute to address the limitations of transferring and retrieving nOAC. However, significant limitations need to be considered, such as calibrated harmonization of water data and atmospheric correction procedures. Moreover, further understanding of the mechanisms that facilitate nOAC prediction is necessary. We highlight the need for international contributions to global water quality datasets capable of providing extensive water data for the improvement of global water monitoring.
|
|
| 4. |
- Arias-Rodriguez, Leonardo F., et al.
(författare)
-
Integration of remote sensing and Mexican water quality monitoring system using an extreme learning machine
- 2021
-
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:12
-
Tidskriftsartikel (refereegranskat)abstract
- Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013–2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2 =0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.
|
|
| 5. |
- Du, Shixiong, et al.
(författare)
-
Evaluating the potential benefits of float solar photovoltaics through the water footprint recovery period
- 2024
-
Ingår i: Journal of Cleaner Production. - 0959-6526. ; 446
-
Tidskriftsartikel (refereegranskat)abstract
- In the context of higher demands on the development of clean energy technologies due to the issue of water shortage in China and the implementation of the 2060 carbon-neutral objective, floating photovoltaic (FPV) systems present novel opportunities for transforming the energy structure through land conservation and enhancement of power generation efficiency compared to conventional solar systems. However, there is currently a lack of comprehensive analysis on the potential benefits of FPV. Utilizing reservoir databases and employing a professional FPV system design, a methodology for determining the water footprint recovery period was introduced, which enables the assessment of potential FPV benefits. The water footprint recovery period for constructing FPV on 909 reservoirs in China was found that ranges from 1.86 yr to 10.48 yr. It is found that reservoir evaporation, latitude, and climate are closely related to the water footprint recovery period of FPV. Furthermore, by implementing FPV panels with an optimal tilt angle, covering 30% of the area in each reservoir, the annual electricity generation can amount to 1429.19 TWh, leading to savings of 5.76 billion m3 of water. This achievement corresponds to 19.41% of the national electricity consumption and a 6.86% reduction in the national residential water consumption in 2020. The overall economic benefit is 5.61 myriads RMB, equivalent to 5.76% of the national GDP. These benefits are unevenly distributed and mainly concentrated in areas with more reservoirs. The anticipated enhancement of FPV system benefits is foreseen with the ongoing development and implementation of future reservoir power infrastructure and energy storage technology. These results demonstrate the significant potential of installing FPV systems on the reservoirs in China. This study proposes a method to comprehensively evaluate the comprehensive benefits of constructing FPV in China and conduct a thorough analysis of the feasibility of FPV, which could provide reference for the development of regional industries and the achievement of sustainable development goals (SDGs).
|
|
| 6. |
- Du, Shixiong, et al.
(författare)
-
Projection of Precipitation Extremes and Flood Risk in the China–Pakistan Economic Corridor
- 2022
-
Ingår i: Frontiers in Environmental Science. - : Frontiers Media SA. - 2296-665X. ; 10
-
Tidskriftsartikel (refereegranskat)abstract
- It is reported that the China–Pakistan Economic Corridor has been affected by extreme precipitation events. Since the 20th century, extreme weather events have occurred frequently, and the damage and loss caused by them have increased. In particular, the flood disaster caused by excessive extreme precipitation seriously hindered the development of the human society. Based on CRiteria Importance Through Intercriteria Correlation and square root of generalized cross-validation, this study used intensity–area–duration to analyze the trend of future extreme precipitation events, corrected the equidistance cumulative distribution function method deviation of different future scenario models (CESM2, CNRM-CM6-1, IPSL-CM6A-LR, and MIROC6) and evaluated the simulation ability of the revised model. The results showed that: 1) the deviation correction results of CNRM-CM6-1 in the Coupled Model Intercomparison Project Phase (CMIP) 6 could better simulate the precipitation data in the study area, and its single result could achieve the fitting effect of the CMIP5 multimodel ensemble average; 2) under CNRM-CM6-1, the frequency of extreme precipitation events under the three climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) presents interdecadal fluctuations of 3.215 times/10A, 1.215 times/10A, and 5.063 times/10A, respectively. The average impact area of extreme precipitation events would decrease in the next 30 years, while the total impact area and the extreme precipitation events in a small range would increase. Under the future scenario, the increase rate of extreme precipitation was highest in August, which increased the probability of extreme events; 3) in the next 30 years, the flood risk had an obvious expansion trend, which was mainly reflected in the expansion of the area of high-, medium-, and low-risk areas. The risk zoning results obtained by the two different flood risk assessment methods were different, but the overall risk trend was the same. This study provided more advanced research for regional flood risk, reasonable prediction for flood risk under future climate models, and useful information for flood disaster prediction in the study area and contributes to the formulation of local disaster prevention and reduction policies.
|
|
| 7. |
- Lu, Mengge, et al.
(författare)
-
Projections of thermal growing season indices over China under global warming of 1.5 °C and 2.0 °C
- 2021
-
Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 781
-
Tidskriftsartikel (refereegranskat)abstract
- Global warming may prolong and intensify the thermal growing season of vegetation. It is not yet clear how the Paris Agreement's long-term temperature goals will affect the thermal growing season of vegetation, particularly crops, in China. Based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) datasets and the Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset, we have investigated changes in spatiotemporal patterns of four thermal growing season indices (Growing Degree Days, GDD; Length of Growing Season, GSL; the Start of Growing Season, GSS; the End of Growing Season, GSE) over China under global warming scenarios of 1.5 °C and 2.0 °C with four representative concentration pathway (RCP) scenarios. Our results indicate that during the periods which achieve the global warming of 1.5 °C and 2.0 °C, only 3.82% and 29.15% of the total areas in China have higher warming levels beyond the global warming targets. For warmer RCP scenarios (except RCP2.6), there was a rising trend for GSE, GDD and GSL and a decreasing trend for GSS in China. Many crop regions in China have also shown an advance of GSS, an extension of GSL and an earlier end of GSE under the global warming of 1.5 °C and 2.0 °C, suggesting that crop planting and harvesting dates need to be adjusted accordingly in order to capture appropriate timing for crop maturity and to achieve a maximum yield.
|
|
| 8. |
- Sun, Huaiwei, et al.
(författare)
-
Drivers of the water use efficiency changes in China during 1982–2015
- 2021
-
Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 799
-
Tidskriftsartikel (refereegranskat)abstract
- This study investigates the drivers of water use efficiency (WUE), a key metric of water resources management, and its changes over eight regions across China from 1982 to 2015 based on gross primary production (GPP) and actual evapotranspiration (AET) datasets. The order of seasonal change of WUE from large to small is autumn, summer, spring and winter. The drivers include seven variables, air temperature, specific humidity, precipitation, short-wave radiation, Normalized Difference Vegetation Index (NDVI), soil moisture and CO2. Our analysis suggests that the sensitivity of annual average NDVI to WUE changes was high nationwide, but there were some differences in seasonal scales. The annual average contribution of air temperature and CO2 affecting WUE change was relatively high in China's largest area (SW, SE, E, NP). Other influencing factors were only relatively high in the local area. Seasonally, NDVI is the driving factor with the highest contribution rate in summer and autumn for NC and NW region. The seasonal contribution rates of driving factors in other regions are significantly different. For the study period (1982–2015), the shrubland ecosystem had the highest annual WUE followed by forest and cropland. The WUE of the farmland ecosystem was higher than that of the grassland ecosystem in most areas.
|
|
| 9. |
- Sun, Huaiwei, et al.
(författare)
-
The altered drivers of evapotranspiration trends around the recent warming hiatus in China
- 2022
-
Ingår i: International Journal of Climatology. - : Wiley. - 0899-8418 .- 1097-0088. ; 42:16, s. 8405-8422
-
Tidskriftsartikel (refereegranskat)abstract
- This study focuses on the trends and the causes of variation in actual evapotranspiration (AET) around the warming hiatus over China by a comprehensive analysis applying various temporal–spatial methods. It is observed that the annual AET showed a different trend around 2000 for China as a whole. By employing segmented regression analysis for detecting warming hiatus points, high temporal inconsistency can be found in eight climatic regions of China. The impacts of meteorological variables on AET were further identified by affecting the intensity and relative change of meteorological factors. AET was highly correlated (p <.01) with solar radiation in the southeast (R = 0.80) and air specific humidity in the northwest areas (R = 0.83). AET changes presented the highest sensitivity to specific humidity in Northwest before 2006 and in north central China after 2003, with sensitivity coefficients of 1.48 and 1.74, respectively. Three variables, including air specific humidity (with an average contribution rate of ~17% in the northwest), short-wave radiation and air temperature, can be the main factors that lead to the changes in AET. The specific meteorological factors varied from region to region: the changes in AET can be ascribed to the increased wind and short-wave radiation in north central China and east China, the decreased air temperature in Tibetan Plateau, the increased specific humidity in southeast China during warming hiatus, and so on. After the warming hiatus occurred, the dominant factor of AET trends changed from air specific humidity to short-wave radiation and other factors. Generally, air specific humidity and air temperature have played leading roles in AET trends during the past 30 years.
|
|
| 10. |
- Yan, Dong, et al.
(författare)
-
Allocation of ecological water rights considering ecological networks in arid watersheds : A framework and case study of Tarim River basin
- 2022
-
Ingår i: Agricultural Water Management. - : Elsevier BV. - 0378-3774. ; 267
-
Tidskriftsartikel (refereegranskat)abstract
- A robust water supply system is significant to the local ecosystem of riparian vegetation in the arid basin. Considering the elasticity and relative importance of ecological water use in different regions of the basin, this study defines the ecological water rights on a multi-year scale, divides the priority of those rights based on the ecological network, and proposes a rights allocation method. The application of the method to the mainstream watershed of Tarim River in China shows that when the overall available ecological water is only 77% of the ecological water demand, it can ensure that the ecological water demand of vegetation in important areas is fully met and the growth condition is good. However, the demand in non-important areas must be less than 50% and the growth condition will deteriorate. This method expands the existing definition and distribution of water rights, and the approach of coupling ecological networks can be used for the efficient management of ecological water supply in other arid basins.
|
|
