Refined estimation of lake water level and storage changes on the Tibetan Plateau from ICESat/ICESat-2

CATENA ◽  
2021 ◽  
Vol 200 ◽  
pp. 105177
Author(s):  
Shuangxiao Luo ◽  
Chunqiao Song ◽  
Pengfei Zhan ◽  
Kai Liu ◽  
Tan Chen ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Level ◽  
Lake Water ◽  
The Tibetan Plateau ◽  
Lake Water Level ◽  
And Storage

scholarly journals Densified multi-mission observations by developed optical water levels show marked increases in lake water storage and overflow floods on the Tibetan Plateau

2019 ◽  
Author(s):  
Xingdong Li ◽  
Di Long ◽  
Qi Huang ◽  
Pengfei Han ◽  
Fanyu Zhao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Level ◽  
Lake Water ◽  
Water Storage ◽  
Water Levels ◽  
The Tibetan Plateau ◽  
Altimetry Data ◽  
Data Set ◽  
Lake Water Level ◽  
And Storage

Abstract. The Tibetan Plateau (TP) known as Asia's water towers is quite sensitive to climate change, reflected by changes in hydrological state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multisource remote sensing, i.e., multiple altimetric missions and Landsat archives to create dense time series (monthly and even higher such as 10 days on average) of lake water level and storage changes across 52 large lakes (> 100 km2) on the TP during 2000–2017 (the data set is available online with a DOI: https://doi.org/10.1594/PANGAEA.898411). Field experiments were carried out in two typical lakes to validate the remotely sensed results. With Landsat archives and partial altimetry data, we developed optical water levels that cover most of TP lakes and serve as an ideal reference for merging multisource lake water levels. The optical water levels show an uncertainty of ~ 0.1 m that is comparable with most altimetry data and largely reduce the lack of dense altimetric observations with systematic errors well removed for most of lakes. The densified lake water levels provided critical and accurate information on the long-term and short-term monitoring of lake water level and storage changes on the TP. We found that the total storage of the 52 lakes increased by 97.3 km3 at two stages, i.e., 6.68 km3/yr during 2000–2012 and 2.85 km3/yr during 2012–2017. The total overflow from Lake Kusai to Lake Haidingnuoer and Lake Salt during Nov 9–Dec 31 in 2011 was estimated to be 0.22 km3, providing critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.

scholarly journals High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions

2019 ◽  
Vol 11 (4) ◽  
pp. 1603-1627 ◽  
Author(s):  
Xingdong Li ◽  
Di Long ◽  
Qi Huang ◽  
Pengfei Han ◽  
Fanyu Zhao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Level ◽  
Lake Water ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Data Sets ◽  
The Tibetan Plateau ◽  
Altimetry Data ◽  
And Storage ◽  
Storage Change

Abstract. The Tibetan Plateau (TP), known as Asia's water tower, is quite sensitive to climate change, which is reflected by changes in hydrologic state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multiple altimetric missions and Landsat satellite data to create high-temporal-resolution lake water level and storage change time series at weekly to monthly timescales for 52 large lakes (50 lakes larger than 150 km2 and 2 lakes larger than 100 km2) on the TP during 2000–2017. The data sets are available online at https://doi.org/10.1594/PANGAEA.898411 (Li et al., 2019). With Landsat archives and altimetry data, we developed water levels from lake shoreline positions (i.e., Landsat-derived water levels) that cover the study period and serve as an ideal reference for merging multisource lake water levels with systematic biases being removed. To validate the Landsat-derived water levels, field experiments were carried out in two typical lakes, and theoretical uncertainty analysis was performed based on high-resolution optical images (0.8 m) as well. The RMSE of the Landsat-derived water levels is 0.11 m compared with the in situ measurements, consistent with the magnitude from theoretical analysis (0.1–0.2 m). The accuracy of the Landsat-derived water levels that can be derived in relatively small lakes is comparable with most altimetry data. The resulting merged Landsat-derived and altimetric lake water levels can provide accurate information on multiyear and short-term monitoring of lake water levels and storage changes on the TP, and critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.

Lake water level modeling using newly developed hybrid data intelligence model

2020 ◽  
Vol 141 (3-4) ◽  
pp. 1285-1300 ◽  
Author(s):  
Zaher Mundher Yaseen ◽  
Shabnam Naghshara ◽  
Sinan Q. Salih ◽  
Sungwon Kim ◽  
Anurag Malik ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Lake Water Level ◽  
Hybrid Data

Groundwater level assessment and prediction in the Nebraska Sand Hills using LIDAR-derived lake water level

2021 ◽  
pp. 126582
Author(s):  
Nawaraj Shrestha ◽  
Aaron Mittelstet ◽  
Aaron R. Young ◽  
Troy E. Gilmore ◽  
David C. Gosselin ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Groundwater Level ◽  
Lake Water Level ◽  
Nebraska Sand Hills ◽  
Sand Hills

scholarly journals Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records

2021 ◽  
Vol 25 (3) ◽  
pp. 1643-1670
Author(s):  
Song Shu ◽  
Hongxing Liu ◽  
Richard A. Beck ◽  
Frédéric Frappart ◽  
Johanna Korhonen ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Small Lakes ◽  
Radar Altimetry ◽  
Lake Water Level ◽  
Systematic Biases ◽  
Data Missing ◽  
Satellite Radar ◽  
Satellite Radar Altimetry

Abstract. A total of 13 satellite missions have been launched since 1985, with different types of radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the root mean square error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.

Metabarcoding of modern sedimentary DNA from the Tibetan Plateau and Siberia as a training dataset for vegetation reconstructions

2021 ◽  
Author(s):  
Weihan Jia ◽  
Kathleen Stoof-Leichsenring ◽  
Sisi Liu ◽  
Kai Li ◽  
Sichao Huang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Lake Sediments ◽  
Plant Diversity ◽  
Lake Water ◽  
Aquatic Plant ◽  
Freshwater Ecosystems ◽  
The Tibetan Plateau ◽  
Plant Dna ◽  
Continental Scale ◽  
Dna Metabarcoding

<p>Lake sedimentary DNA (<em>sed</em>DNA) is an established tool to trace past changes in vegetation composition and plant diversity. However, little is known about the relationships between sedimentary plant DNA and modern vegetational and environmental conditions. In this study, we investigate i) the relationships between the preservation of sedimentary plant DNA and environmental variables, ii) the modern analogue of ancient plant DNA assemblages archived in lake sediments, and iii) the usability of sedimentary plant DNA for characterization of terrestrial and aquatic plant composition and diversity based on a large dataset of PCR-amplified plant DNA data retrieved from 259 lake surface sediments from the Tibetan Plateau and Siberia. Our results indicate the following: i) Lake-water electrical conductivity and pH are the most important variables for the preservation of plant DNA in lake sediments. We expect the best preservation conditions for sedimentary plant DNA in small deep lakes characterized by high water conductivities (≥100 μS cm<sup>-1</sup>) and neutral to slightly alkaline pH conditions (7–9). ii) Plant DNA metabarcoding is promising for palaeovegetation reconstruction in high mountain regions, where shifts in vegetation are solely captured by the <em>sed</em>DNA-based analogue matching and fossil pollen generally has poor modern analogues. However, the biases in the representation of some taxa could lead to poor analogue conditions. iii) Plant DNA metabarcoding is a reliable proxy to reflect modern vegetation types and climate characteristics at a sub-continental scale. However, the resolution of the <em>trn</em>L P6 loop marker, the incompleteness of the reference library, and the extent of <em>sed</em>DNA preservation are still the main limitations of this method. iv) Plant DNA metabarcoding is a suitable proxy to recover modern aquatic plant diversity, which is mostly affected by July temperature and lake-water conductivity. Ongoing warming might decrease macrophyte richness in the Tibetan Plateau and Siberia, and ultimately threaten the health of these important freshwater ecosystems. To conclude, sedimentary plant DNA presents a high correlation with modern vegetation and may therefore be an important proxy for reconstruction of past vegetation.</p>

Lake water level response to drought in a lake-rich region explained by lake and landscape characteristics

2020 ◽  
Vol 77 (11) ◽  
pp. 1836-1845
Author(s):  
K. Martin Perales ◽  
Catherine L. Hein ◽  
Noah R. Lottig ◽  
M. Jake Vander Zanden
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Lake Water ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Lake Area ◽  
Lake Water Level ◽  
Landscape Characteristics ◽  
Lake Ecology ◽  
Coarse Woody Habitat

Climate change is altering hydrologic regimes, with implications for lake water levels. While lakes within lake districts experience the same climate, lakes may exhibit differential climate vulnerability regarding water level response to drought. We took advantage of a recent drought (∼2005–2010) and estimated changes in lake area, water level, and shoreline position on 47 lakes in northern Wisconsin using high-resolution orthoimagery and hypsographic curves. We developed a model predicting water level response to drought to identify characteristics of the most vulnerable lakes in the region, which indicated that low-conductivity seepage lakes found high in the landscape, with little surrounding wetland and highly permeable soils, showed the greatest water level declines. To explore potential changes in the littoral zone, we estimated coarse woody habitat (CWH) loss during the drought and found that drainage lakes lost 0.8% CWH while seepage lakes were disproportionately impacted, with a mean loss of 40% CWH. Characterizing how lakes and lake districts respond to drought will further our understanding of how climate change may alter lake ecology via water level fluctuations.

scholarly journals Bathymetry Development and Flow Analyses Using Two-Dimensional Numerical Modeling Approach for Lake Victoria

Fluids ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 182 ◽  
Author(s):  
Seema Paul ◽  
Jesper Oppelstrup ◽  
Roger Thunvik ◽  
John Mango Magero ◽  
David Ddumba Walakira ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Lake Victoria ◽  
State Level ◽  
Linear Measurement ◽  
Two Dimensional ◽  
Mean Flow ◽  
Lake Water Level ◽  
Outflow Boundary Condition ◽  
Outflow Boundary

This study explored two-dimensional (2D) numerical hydrodynamic model simulations of Lake Victoria. Several methods were developed in Matlab to build the lake topography. Old depth soundings taken in smaller parts of the lake were combined with more recent extensive data to produce a smooth topographical model. The lake free surface numerical model in the COMSOL Multiphysics (CM) software was implemented using bathymetry and vertically integrated 2D shallow water equations. Validated by measurements of mean lake water level, the model predicted very low mean flow speeds and was thus close to being linear and time invariant, allowing long-time simulations with low-pass filtered inflow data. An outflow boundary condition allowed an accurate simulation to achieve the lake’s steady state level. The numerical accuracy of the linear measurement of lake water level was excellent.

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