Evaluation and improvement of remote sensing-based methods for river flow management

Water and flow reductions in the channels downstream of water storage and hydropower projects have significant impacts on aquatic ecosystems. Understanding and analyzing the ecosystem status is of great significance to facilitate the protection of riverine ecosystems. A database was established based on the 2000–2017 environmental impact assessment (EIA) reports on water storage and hydropower projects in China, and corresponding analysis software was built based on an ArcGIS spatial analysis platform. The projects in China are mainly found in the Yangtze and Pearl River basins and in south-western China. The hydropower projects have a larger influence than the water storage projects on the flow of downstream rivers sections, and most of the hydropower projects, especially the water diversion projects, cause flow reductions in the downstream rivers. An ecological flow management mechanism in China implemented in 2006 provided a promising method to alleviate river flow reductions. However, there is still only one kind of ecological flow calculation method and few ecological flow regulation measures in use. Based on the advantages and problems of the existing ecological flow management system, this paper proposes a management scheme based on a regional-engineering calculation method. The results can facilitate decision making in ecological flow management.

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Ephemeral sand river flow detection using satellite optical remote sensing

Journal of Arid Environments ◽

10.1016/j.jaridenv.2019.05.006 ◽

2019 ◽

Vol 168 ◽

pp. 17-25 ◽

Cited By ~ 1

Author(s):

David Walker ◽

Magdalena Smigaj ◽

Nebo Jovanovic

Keyword(s):

Remote Sensing ◽

River Flow ◽

Optical Remote Sensing ◽

Flow Detection

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RIFMAS: River Flow Management System using Wireless Sensing Agents

2009 IEEE International Advance Computing Conference ◽

10.1109/iadcc.2009.4809126 ◽

2009 ◽

Cited By ~ 2

Author(s):

R. B. Patel ◽

Bhanu Kaushik

Keyword(s):

Management System ◽

River Flow ◽

Wireless Sensing ◽

Flow Management

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High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management

Frontiers in Ecology and the Environment ◽

10.1890/100125 ◽

2011 ◽

Vol 9 (9) ◽

pp. 494-502 ◽

Cited By ~ 773

Author(s):

Bernhard Lehner ◽

Catherine Reidy Liermann ◽

Carmen Revenga ◽

Charles Vörösmarty ◽

Balazs Fekete ◽

...

Keyword(s):

High Resolution ◽

River Flow ◽

Flow Management ◽

High Resolution Mapping ◽

Resolution Mapping

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Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data

Geoscientific Model Development ◽

10.5194/gmd-5-941-2012 ◽

2012 ◽

Vol 5 (4) ◽

pp. 941-962 ◽

Cited By ~ 41

Author(s):

B. Ringeval ◽

B. Decharme ◽

S. L. Piao ◽

P. Ciais ◽

F. Papa ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

River Flow ◽

Spatial Scales ◽

Remote Sensing Data ◽

Surface Model ◽

Global Evaluation ◽

Good Opportunity ◽

Sensing Data ◽

Basin Scale

Abstract. The quality of the global hydrological simulations performed by land surface models (LSMs) strongly depends on processes that occur at unresolved spatial scales. Approaches such as TOPMODEL have been developed, which allow soil moisture redistribution within each grid-cell, based upon sub-grid scale topography. Moreover, the coupling between TOPMODEL and a LSM appears as a potential way to simulate wetland extent dynamic and its sensitivity to climate, a recently identified research problem for biogeochemical modelling, including methane emissions. Global evaluation of the coupling between TOPMODEL and an LSM is difficult, and prior attempts have been indirect, based on the evaluation of the simulated river flow. This study presents a new way to evaluate this coupling, within the ORCHIDEE LSM, using remote sensing data of inundated areas. Because of differences in nature between the satellite derived information – inundation extent – and the variable diagnosed by TOPMODEL/ORCHIDEE – area at maximum soil water content, the evaluation focuses on the spatial distribution of these two quantities as well as on their temporal variation. Despite some difficulties in exactly matching observed localized inundated events, we obtain a rather good agreement in the distribution of these two quantities at a global scale. Floodplains are not accounted for in the model, and this is a major limitation. The difficulty of reproducing the year-to-year variability of the observed inundated area (for instance, the decreasing trend by the end of 90s) is also underlined. Classical indirect evaluation based on comparison between simulated and observed river flow is also performed and underlines difficulties to simulate river flow after coupling with TOPMODEL. The relationship between inundation and river flow at the basin scale in the model is analyzed, using both methods (evaluation against remote sensing data and river flow). Finally, we discuss the potential of the TOPMODEL/LSM coupling to simulate wetland areas. A major limitation of the coupling for this purpose is linked to its ability to simulate a global wetland coverage consistent with the commonly used datasets. However, it seems to be a good opportunity to account for the wetland areas sensitivity to the climate and thus to simulate its temporal variability.

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ANALYSIS OF SOIL DEGRADATION AND DESERTIFICATION IN SOUTHERN BALKASH DESERT BASED ON GIS

REPORTS ◽

10.32014/10.32014/2020.2518-1483.30 ◽

2020 ◽

Vol 2 (330) ◽

pp. 41-48

Author(s):

A.G. Gabdykadyr ◽

G.T. Issanova ◽

Y.Kh. Kakimzhanov ◽

Long Ma

Keyword(s):

Remote Sensing ◽

Land Cover ◽

River Flow ◽

Remote Sensing Data ◽

Geological Structure ◽

Anthropogenic Factors ◽

Economic Activities ◽

Spectral Bands ◽

Indirect Sign ◽

Tasseled Cap Transformation

Desertification and degradation provide a clear picture of global environmental and socio-economic issues. Most of Kazakhstan is located in a desert region, including the suburbs of South Balkhash. The reason is that desertification of the region has a strong influence on natural and anthropogenic factors. To consider the geomorphological state of the region and the problem of desertification of the territory, it is necessary to determine the importance of the process of relief of geological structure and relief of tectonics. In recent years, the environmental situation in Balkhash has deteriorated sharply not only as a result of river flow regulation, but also as a result of non-commercial economic activities. Therefore, it is very important to assess the situation of desertification and degradation in the Balkhash region. Desert vegetation has been identified, since information in the spectral range is often insufficient to describe the state of plants, plant indices often develop by combining two or more spectral bands. Land cover index is the percentage of vegetation over a given surface area. Remote sensing information was used to detect the entire land cover. Remote sensing with time and space limitations is widely used to classify vegetation cover. In this work, the proportion of vegetation was estimated by NDVI. The proportion of land cover is based on the relationship between NDVI (NDVIS) and NDVI (NDVIV) in the soil. Using the NDVI index, land cover zones were determined based on satellite images of 2006 and Landsat-5 from 2011. TCT (Tasseled Cap Transformation) coefficients are used in the widest range of problems solved using Earth remote sensing data: from recognition of the coastline of water bodies to determination of forest disturbances. Stressful vegetation may be an indirect sign of the presence of salt in soils. Saline soils are usually characterized by poorly planted areas. A normalized differential salinity index (NDSI) was also determined.

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Impacts of Regional Groundwater Flow and River Fluctuation on Floodplain Wetlands in the Middle Reach of the Yellow River

Water ◽

10.3390/w12071922 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1922

Author(s):

Yunmei Fu ◽

Yanhui Dong ◽

Yueqing Xie ◽

Zhifang Xu ◽

Liheng Wang

Keyword(s):

Remote Sensing ◽

Groundwater Flow ◽

River Flow ◽

Yellow River ◽

Hydrological Processes ◽

The Yellow River ◽

Floodplain Wetlands ◽

Middle Reach ◽

Groundwater Levels ◽

Regional Groundwater

Floodplain wetlands are of great importance in the entire river and floodplain ecosystems. Understanding the hydrological processes of floodplain wetlands is fundamental to study the changes in wetlands caused by climate change and human activities. In this study, floodplain wetlands along the middle reach of the Yellow River were selected as a study area. The hydrological processes and the interactions between the river and the underlying aquifer were investigated by combining remote sensing, hydraulic monitoring, and numerical modeling. Wetland areas from 2014 to 2019 were extracted from Landsat 8 remote sensing images, and their correlation with the river runoff was analyzed. The results indicate that the river flow had a limited impact on the wetland size and so did groundwater levels, due to the strong reliance of wetland vegetation on water levels. Based on hydrological and hydrogeological conditions, a surface water–groundwater coupled numerical model was established. The comparison and correlation analysis between the monitored groundwater head and the simulated river stage also show that river flow did not play a first-order role in controlling the groundwater levels of wetlands in the study area. The simulation results also suggest that it is the regional groundwater flow that mainly sustains shallow groundwater of floodplain wetlands in the study area. The floodplain wetland of the study area was dynamic zones between the regional groundwater and river, the contrasting pattern of hydrological regimes on both banks of the Yellow River was due to a combination of regional groundwater flow and topography.

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An Assessment of the Spatial and Temporal Distribution of Soil Salinity in Combination with Field and Satellite Data: A Case Study in Sujawal District

Agronomy ◽

10.3390/agronomy9120869 ◽

2019 ◽

Vol 9 (12) ◽

pp. 869 ◽

Cited By ~ 1

Author(s):

Kashif Ali Solangi ◽

Altaf Ali Siyal ◽

Yanyou Wu ◽

Bilawal Abbasi ◽

Farheen Solangi ◽

...

Keyword(s):

Remote Sensing ◽

Seawater Intrusion ◽

Soil Salinity ◽

River Flow ◽

Temporal Distribution ◽

Soil Samples ◽

Control Measures ◽

Normal Range ◽

Barren Land ◽

The Impact

Soil salinization is a serious environmental issue that significantly influences crop yield and soil fertility, especially in coastal areas. Numerous studies have been conducted on the salinity status in Pakistan. Information about the geospatial and temporal distribution of salinity in the Sujawal district is still lacking. The present study examines the soil salinity status and the impact of seawater intrusion in the entire district from 1990 to 2017 using field and remote sensing (RS) data. In addition, 210 soil samples at different depths (0–20, 20–40, and 40–60 cm) were collected from randomly selected locations for lab measurements of physiochemical properties. The results showed that the soil texture classes were mainly fine to medium particles. The samples collected at the 0–20 cm depth were mostly dominated by three textural classes of soil: clay at 19.5%, clay loam at 25.6%, and loam at 32.9%. The electrical conductivity (EC) of 65.7% soil samples collected from the top layer exceeded the normal range. The quantitative results indicated that the exchangeable sodium percentage (ESP) ranged between 1.38 and 64.58, and 72.2% of the top layer soil samples had ESP >15, while 81.5% of soil samples were in the normal range of soil pH. Furthermore, the results indicated that the vegetation decreased by 8.6% from 1990 to 2017, while barren land and water bodies increased significantly, by approximately 4.4% and 4.2%, respectively. The extreme and high salinity classes were characterized by high contents of soluble salt on the surface in the Jati and Shah Bandar subdistricts. In addition, the soil EC values at the 0–20 cm depth were significantly correlated with the salinity index (S1). Therefore, it was concluded that more than 50% of the top layer of soil was affected by salinity due to seawater intrusion, low rainfall, climate change, and erratic river flow. It is suggested that remote sensing (RS) data are more suitable for the detection of the soil salinity status of a region and impose a lower cost compared to other conventional approaches. However, this study could provide significant knowledge to land managers, policymakers, and government officials to allow them to take action to implement salinity control measures in the study area.

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The hydrological cycle in the high Pamir Mountains: how temperature and seasonal precipitation distribution influence stream flow in the Gunt catchment, Tajikistan

Earth Surface Dynamics Discussions ◽

10.5194/esurfd-2-1155-2014 ◽

2014 ◽

Vol 2 (2) ◽

pp. 1155-1215 ◽

Cited By ~ 4

Author(s):

E. Pohl ◽

M. Knoche ◽

R. Gloaguen ◽

C. Andermann ◽

P. Krause

Keyword(s):

Remote Sensing ◽

Stream Flow ◽

River Flow ◽

Climate Model ◽

Hydrological Cycle ◽

Climatic Variability ◽

Glacier Mass Balance ◽

In Situ Data ◽

Glacier Melt

Abstract. Complex climatic interactions control hydrological processes in high mountains that in their turn regulate the erosive forces shaping the relief. To unravel the hydrological cycle of a glaciated watershed (Gunt River) considered representative of the Pamirs' hydrologic regime we developed a remote sensing-based approach. At the boundary between two distinct climatic zones dominated by Westerlies and Indian summer monsoon, the Pamir is poorly instrumented and only a few in situ meteorological and hydrological data are available. We adapted a suitable conceptual distributed hydrological model (J2000g). Interpolations of the few available in situ data are inadequate due to strong, relief induced, spatial heterogeneities. Instead we use raster data, preferably from remote sensing sources depending on availability and validation. We evaluate remote sensing-based precipitation and temperature products. MODIS MOD11 surface temperatures show good agreement with in situ data, perform better than other products and represent a good proxy for air temperatures. For precipitation we tested remote sensing products as well as the HAR10 climate model data and the interpolation-based APHRODITE dataset. All products show substantial differences both in intensity and seasonal distribution with in-situ data. Despite low resolutions, the datasets are able to sustain high model efficiencies (NSE &geq;0.85). In contrast to neighbouring regions in the Himalayas or the Hindukush, discharge is dominantly the product of snow and glacier melt and thus temperature is the essential controlling factor. 80% of annual precipitation is provided as snow in winter and spring contrasting peak discharges during summer. Hence, precipitation and discharge are negatively correlated and display complex hysteresis effects that allow to infer the effect of inter-annual climatic variability on river flow. We infer the existence of two subsurface reservoirs. The groundwater reservoir (providing 40% of annual discharge) recharges in spring and summer and releases slowly during fall and winter. A not fully constrained shallow reservoir with very rapid retention times buffers melt waters during spring and summer. This study highlights the importance of a better understanding of the hydrologic cycle to constrain natural hazards such as floods and landslides as well as water availability in the downstream areas. The negative glacier mass balance (−0.6 m w.e. yr−1) indicates glacier retreat, that will effect the currently 30% contribution of glacier melt to stream flow.

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