scholarly journals Discharge Estimates for Ungauged Rivers Flowing over Complex High-Mountainous Regions based Solely on Remote Sensing-Derived Datasets

2020 ◽  
Vol 12 (7) ◽  
pp. 1064 ◽  
Author(s):  
Mulugeta Genanu Kebede ◽  
Lei Wang ◽  
Kun Yang ◽  
Deliang Chen ◽  
Xiuping Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
River Discharge ◽  
Equation Model ◽  
Roughness Coefficient ◽  
The Tibetan Plateau ◽  
Efficiency Coefficient ◽  
Ongoing Research ◽  
Mountainous Regions ◽  
Lhasa River ◽  
Discharge Estimation

Reliable information about river discharge plays a key role in sustainably managing water resources and better understanding of hydrological systems. Therefore, river discharge estimation using remote sensing techniques is an ongoing research goal, especially in small, headwater catchments which are mostly ungauged due to environmental or financial limitations. Here, a novel method for river discharge estimation based entirely on remote sensing-derived parameters is presented. The model inputs include average river width, estimated from Landsat imagery by using the modified normalized difference water index (MNDWI) approach; average depth and velocity, based on empirical equations with inputs from remote sensing; channel slope from a high resolution shuttle radar topography mission digital elevation model (SRTM DEM); and channel roughness coefficient via further analysis and classification of Landsat images with support of previously published values. The discharge of the Lhasa River was then estimated based on these derived parameters and by using either the Manning equation (Model 1) or Bjerklie equation (Model 2). In general, both of the two models tend to overestimate discharge at moderate and high flows, and underestimate discharge at low flows. The overall performances of both models at the Lhasa gauge were satisfactory: comparisons with the observations yielded Nash–Sutcliffe efficiency coefficient (NSE) and R2 values ≥ 0.886. Both models also performed well at the upper gauge (Tanggya) of the Lhasa River (NSE ≥ 0.950) indicating the transferability of the methodology to river cross-sections with different morphologies, thus demonstrating the potential to quantify streamflow entirely from remote sensing data in poorly-gauged or ungauged rivers on the Tibetan Plateau.

Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau

2020 ◽  
Author(s):  
Mulugeta Genanu Kebede ◽  
Lei Wang ◽  
Xiuping Li ◽  
Zhidan Hu
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
River Discharge ◽  
Equation Model ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Mountain Regions ◽  
Discharge Estimation ◽  
Academy Of Sciences ◽  
Beijing China

<p><strong>Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau </strong></p><p>Mulugeta Genanu Kebede <sup>1, 2, 3</sup>, Lei Wang<sup>1, 2*</sup>, Xiuping Li<sup>1</sup> and Zhidan Hu<sup>4</sup></p><p><sup>1 </sup>Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China</p><p><sup>2 </sup>University of Chinese Academy of Sciences, Beijing, China</p><p><sup>3 </sup>Arba Minch University, Water Technology Institute, Faculty of Meteorology and Hydrology, Arba Minch, Ethiopia</p><p><sup>4 </sup>Information Center, Ministry of Water Resources, Beijing 100053, China</p><p><strong>* </strong>Correspondence to: Dr. Lei Wang, Professor</p><p>Email: [email protected];     Tel.: +86-10-8409-7107; Fax: +86-10-8409-7079</p><p><strong>ABSTRACT</strong></p><p>River discharge, as one of the most essential climate variables, plays a vital role in the water cycle. Small-scale headwater catchments including high-mountain regions of Tibetan Plateau (TP) Rivers are mostly ungauged. Satellite technology shows its potential to fill this gap with high correlation of satellite-derived effective river width and corresponding in-situ gauged discharge. This study is innovative in estimating daily river discharge using modified Manning equation (Model 1), Bjerklie equation (Model 2), and Rating curve approach (Model 3) by combining river surface hydraulic variables directly derived from remote sensing datasets with other variables indirectly derived from empirical equations, which greatly contributes to the improvement of river flow measurement information especially over small rivers of TP. We extracted the effective width from Landsat image and flow depth via hydraulic geometry approach. All the input parameters directly or indirectly derived from remote sensing were combined and substituted into the fundamental flow equations/models to estimate discharges of Lhasa River. The validation of all three models’ results against the in-situ discharge measurements shows a strong correlation (the Nash–Sutcliffe efficiency coefficient (NSE) and the coefficient of determination (R<sup>2</sup>) values ≥ 0.993), indicating the potentiality of the models in accurately estimating daily river discharges. Trends of an overestimation of discharge by Model 1 and underestimation by Model 2 are observed. The discharge estimation by using Model 3 outperforms Model 1 and Model 2 due to the uncertainties associated with estimation of input parameters in the other two models. Generally, our discharge estimation methodology performs well and shows a superior result as compared with previously developed multivariate empirical equations and its application for other places globally can be the focus of upcoming studies.    </p><p><strong>Keywords:</strong> River discharge estimation, remote sensing, effective width, hydraulic relationship, Tibetan Plateau</p>

scholarly journals Vegetation Dynamics on the Tibetan Plateau (1982–2006): An Attribution by Ecohydrological Diagnostics

2015 ◽  
Vol 28 (11) ◽  
pp. 4576-4584 ◽  
Author(s):  
Danlu Cai ◽  
Klaus Fraedrich ◽  
Frank Sielmann ◽  
Ling Zhang ◽  
Xiuhua Zhu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
State Space ◽  
Weather Data ◽  
Target Area ◽  
The Tibetan Plateau ◽  
Net Radiation ◽  
Vegetation Greenness ◽  
Mountainous Regions ◽  
Second Period

Abstract Vegetation greenness distributions [based on remote sensing normalized difference vegetation index (NDVI)] and their change are analyzed as functional vegetation–climate relations in a two-dimensional ecohydrological state space spanned by surface flux ratios of energy excess (U; loss by sensible heat H over supply by net radiation N) versus water excess (W; loss by discharge Ro over gain by precipitation P). An ecohydrological ansatz attributes state change trajectories in (U, W) space to external (or climate) and internal (or anthropogenic) causes jointly with vegetation greenness interpreted as an active tracer. Selecting the Tibetan Plateau with its complex topographic, climate, and vegetation conditions as target area, ERA-Interim weather data link geographic and (U, W) state space, into which local remote sensing Global Inventory Modeling and Mapping Studies (GIMMS) data (NDVI) are embedded; a first and second period (1982–93 and 1994–2006) are chosen for change attribution analysis. The study revealed the following results: 1) State space statistics are characterized by a bimodal distribution with two distinct geobotanic regimes (semidesert and steppe) of low and moderate vegetation greenness separated by gaps at aridity D ~ 2 (net radiation over precipitation) and greenness NDVI ~ 0.3. 2) Changes between the first and second period are attributed to external (about 70%) and internal (30%) processes. 3) Attribution conditioned joint distributions of NDVI (and its change) show 38.2% decreasing (61.8% increasing) area cover with low (moderate) greenness while high greenness areas are slightly reduced. 4) Water surplus regions benefit most from climate change (showing vegetation greenness growth) while the energy surplus change is ambiguous, because ecohydrological diagnostics attributes high mountainous regions (such as the Himalayas) as internal without considering the heat storage deficit due to increasing vegetation.

scholarly journals Combining and Comparing an Unmanned Aerial Vehicle and Multiple Remote Sensing Satellites to Calculate Long-Term River Discharge in an Ungauged Water Source Region on the Tibetan Plateau

2020 ◽  
Vol 12 (13) ◽  
pp. 2155 ◽  
Author(s):  
Hezhen Lou ◽  
Pengfei Wang ◽  
Shengtian Yang ◽  
Fanghua Hao ◽  
Xiaoyu Ren ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
Unmanned Aerial Vehicle ◽  
River Discharge ◽  
The Tibetan Plateau ◽  
Aerial Vehicle ◽  
Spot 5 ◽  
Sentinel 2

Research into global water resources is challenged by the lack of ground-based hydrometric stations and limited data sharing. It is difficult to collect good quality, long-term information about river discharges in ungauged regions. Herein, an approach was developed to determine the river discharges of 24 rivers in ungauged regions on the Tibetan Plateau on a long-term scale. This method involved coupling the Manning–Strickler formula, and data from an unmanned aerial vehicle (UAV) and the Gaofen-2, SPOT-5, and Sentinel-2 satellites. We also compared the discharges calculated by using the three satellites’ data. Fundamental information about the rivers was extracted from the UAV data. Comparison of the discharges calculated from the in-situ measurements and the UAV data gave an R2 value of 0.84, an average NSE of 0.79, and an RMSE of 0.11 m3/s. The river discharges calculated with the GF-2 remote sensing data and the in-situ experiments for the same months were compared and the R2, RMSE, and the NSE were 0.80, 1.8 m3/s, and 0.78, respectively. Comparing the discharges calculated over the long term from the measured in-situ data and the SPOT-5 and Sentinel-2 data gave R2 values of 0.93 and 0.92, and RMSE values of 2.56 m3/s and 3.16 m3/s, respectively. The results showed that the GF-2 and UAV were useful for calculating the discharges for low-flow rivers, while the SPOT-5 or the Sentinel-2 satellite gave good results for high-flow river discharges in the long-term. Our results demonstrate that the discharges in ungauged tributaries can be reliably estimated in the long-term with this method. This method extended the previous research, which described river discharge only in one period and provided more support to the monitoring and management of the tributaries in ungauged regions.

scholarly journals An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

2016 ◽  
Vol 52 (6) ◽  
pp. 4527-4549 ◽  
Author(s):  
M. Durand ◽  
C. J. Gleason ◽  
P. A. Garambois ◽  
D. Bjerklie ◽  
L. C. Smith ◽  
...  
Keyword(s):  
Remote Sensing ◽  
River Discharge ◽  
Estimation Algorithms ◽  
Discharge Estimation

scholarly journals Remote Sensing Investigation of the Offset Effect between Reservoir Impoundment and Glacier Meltwater Supply in Tibetan Highland Catchment

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1307
Author(s):  
Jingying Zhu ◽  
Chunqiao Song ◽  
Linghong Ke ◽  
Kai Liu ◽  
Tan Chen
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Average Rate ◽  
Shuttle Radar Topography Mission ◽  
Glacier Mass Balance ◽  
The Tibetan Plateau ◽  
Joint Research ◽  
Glacier Meltwater ◽  
Reservoir Impoundment ◽  
Lhasa River

This article presents multi-source remote sensing measurements to quantify the water impoundment and regulation of the Zhikong Reservoir (ZKR) and Pangduo Reservoir (PDR), together with the estimation of the glacier mass balance to explore whether the increased glacier meltwater supply can buffer the influences of the reservoir impoundment to some degree in the Tibetan highland catchment. The ZKR and PDR are two reservoirs constructed on the upper Lhasa River that originate from the Nyainqentanglha glaciers in the remote headwater in the Tibetan Plateau (TP) and lacks historical in situ hydrological observations in the long term. Therefore, the Joint Research Center (JRC) Global Surface Water dataset (GSW), and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data were used for estimating the total amount of water storage of the two reservoirs, and the SRTM and TanDEM-X DEMs were used for estimating the glacier mass balance. The result shows that the total amount of water impounded by reservoirs is 0.76 Gt, roughly 54% of their design capacities. The mass balance of the glaciers is estimated by comparing the elevation changes between the SRTM and TanDEM-X DEMs. The glaciers in this region melt at an average rate of 0.09 ± 0.02 Gt·year−1 from 2000 to circa 2013, and the impounded water of these reservoirs is comparable to the amount of glacier-fed meltwater in eight years.

scholarly journals Multiple Pathways: The Influence Mechanism of Greenspace Exposure on Mental Health—A Case Study of Hangzhou, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 339
Author(s):  
Jiancheng Lu ◽  
Xiaolong Luo ◽  
Ningning Yang ◽  
Yang Shen
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Remote Sensing ◽  
Structural Equation ◽  
Positive Impact ◽  
Personal Information ◽  
Image Interpretation ◽  
Remote Sensing Data ◽  
Equation Model ◽  
Influence Mechanism

Greenspace exposure (GSE) may have a positive impact on mental health. However, existing research lacks a classification analysis of the influence pathways of different GSE on mental health. Meanwhile, the research method is limited to the measurement of the green space ratio (GSR) based on remote sensing data, which ignores people’s real perception of greenspace. This paper aims to further expand the measurement method of GSE, taking Hangzhou, China as an example, and to reveal the influence mechanism of different GSE modes on mental health. We obtained the personal information, mental health, physical activity, and other data of the interviewees through a questionnaire (n = 461). Combined with a remote sensing satellite and the Baidu Street view database, the method of image interpretation and deep learning was used to obtain the GSR, green visual ratio (GVR), and green visual exposure (GVE). The structural equation model is used to analyze the relationship between different variables. The results showed that: (1) GSE has a certain positive effect on mental health; (2) there are differences in the influence mechanism of multiple measures of GSE on mental health—the GVR and GVE measures based on the interaction perspective between human and greenspace make the influence mechanism more complicated, and produce direct and indirect influence paths; and (3) greenspace perception, sense of community, and physical activity can act as mediators, and have indirect effects. Finally, we call for expanding the measurement index and methods of GSE and integrating them into the management and control practices of urban planning to promote the healthy development of communities and even cities.

scholarly journals Elevational Movement of Vegetation Greenness on the Tibetan Plateau: Evidence from the Landsat Satellite Observations during the Last Three Decades

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 161
Author(s):  
Liheng Lu ◽  
Xiaoqian Shen ◽  
Ruyin Cao
Keyword(s):  
Tibetan Plateau ◽  
Spatial Resolution ◽  
Climate Warming ◽  
Vertical Movement ◽  
The Tibetan Plateau ◽  
Upward Movement ◽  
Vegetation Growth ◽  
Vegetation Greenness ◽  
Mountainous Regions ◽  
Vegetation Activities

The Tibetan Plateau, the highest plateau in the world, has experienced strong climate warming during the last few decades. The greater increase of temperature at higher elevations may have strong impacts on the vertical movement of vegetation activities on the plateau. Although satellite-based observations have explored this issue, these observations were normally provided by the coarse satellite data with a spatial resolution of more than hundreds of meters (e.g., GIMMS and MODIS), which could lead to serious mixed-pixel effects in the analyses. In this study, we employed the medium-spatial-resolution Landsat NDVI data (30 m) during 1990–2019 and investigated the relationship between temperature and the elevation-dependent vegetation changes in six mountainous regions on the Tibetan Plateau. Particularly, we focused on the elevational movement of the vegetation greenness isoline to clarify whether the vegetation greenness isoline moves upward during the past three decades because of climate warming. Results show that vegetation greening occurred in all six mountainous regions during the last three decades. Increasing temperatures caused the upward movement of greenness isoline at the middle and high elevations (>4000 m) but led to the downward movement at lower elevations for the six mountainous regions except for Nyainqentanglha. Furthermore, the temperature sensitivity of greenness isoline movement changes from the positive value to negative value by decreasing elevations, suggesting that vegetation growth on the plateau is strongly regulated by other factors such as water availability. As a result, the greenness isoline showed upward movement with the increase of temperature for about 59% pixels. Moreover, the greenness isoline movement increased with the slope angles over the six mountainous regions, suggesting the influence of terrain effects on the vegetation activities. Our analyses improve understandings of the diverse response of elevation-dependent vegetation activities on the Tibetan Plateau.

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