LONG-TERM REMOTE MONITORING OF THREE TYPICAL LAKE AREA VARIATIONS IN THE NORTHWEST CHINA OVER THE PAST 40 YEARS

water resources management and sustainable development strategy, but also provide reference for assessing the impact of climate change and human activities. This paper selects three inland lakes in Northwest China, using Landsat MSS/TM/ETM+/OLI data from 1970 to 2015, Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) were used to extract lake area and analysed the dynamic trends. Meteorological station rainfall, evaporation and other meteorological data of the lakes were used to analyse reasons for the area change. The results showed that area of Hongjiannao Lake in the past 40&thinsp;a was reduced, the groundwater impoundment and underground coal mining are the main cause of area reduction; the area of Bosten Lake in recent 40&thinsp;a showed a decreasing trend after the first increase, the area was mainly affected by the surface runoff and snowmelt; the area of Qinghai Lake in the past 40&thinsp;a shows a trend of decreasing first and then increasing, the change of its area is mainly affected by regional precipitation and the inflow.

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AUTOMATED GIS-BASED TECHNIQUE FOR EVALUATION OF INDIRECT GROWING SEASON ESTIMATIONS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w14-209-2019 ◽

2019 ◽

Vol XLII-4/W14 ◽

pp. 209-211

Author(s):

I. Rykin ◽

E. Panidi ◽

V. Tsepelev

Keyword(s):

Meteorological Data ◽

Growing Season ◽

Google Earth ◽

Water Quantity ◽

Special Significance ◽

Water Index ◽

Atmospheric Scattering ◽

The Past ◽

Normalized Difference Water Index ◽

Automated Technique

Abstract. This article is based on NDWI (Normalized Difference Water Index) which is automatically computed from the daily MODIS data. The main purpose of the article is to tell how the evaluation of NDWI-based growing season estimations can be automated. The NDWI is used as an indicator of liquid water quantity in vegetation, which is less sensitive to atmospheric scattering effect then the famous growing index (NDVI). The NDWI is computed using cloud-based platform (Google Earth Engine was applied) and compared with the daily meteorological data. The available meteorological data is collected for the past 130 years and NDWI data is collecting for the past 20 years. An automated technique has been probated on the example of republic of Komi, as it has a different climate forming factors. This approach can be used to evaluate growing season estimations for other territories that contain vegetation. Due to the accumulated amount of data, the study is relevant and has a special significance for areas with sparse hydrometeorological network.

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The Dynamic Change of Bosten Lake Area in Response to Climate in the Past 30 Years

Water ◽

10.3390/w12010004 ◽

2019 ◽

Vol 12 (1) ◽

pp. 4 ◽

Cited By ~ 2

Author(s):

Xiaoai Dai ◽

Xingping Yang ◽

Meilian Wang ◽

Yu Gao ◽

Senhao Liu ◽

...

Keyword(s):

Climate Change ◽

Surface Area ◽

Water Body ◽

Meteorological Factors ◽

Lake Basin ◽

Bosten Lake ◽

Water Index ◽

The Past ◽

Normalized Difference Water Index

The widely distributed lakes, as one of the major components of the inland water system, are the primary available freshwater resources on the earth and are sensitive to accelerated climate change and extensive human activities. Lakes play an important role in the terrestrial water cycle and biogeochemical cycle and substantially influence the health of humans living in the surrounding areas. Given the importance of lakes in the ecosystem, long-term monitoring of dynamic changes has important theoretical and practical significance. Here, we extracted water body information and monitored the long-term dynamics of Bosten Lake, which is the largest inland lake in China. We quantified the meteorological factors of the study area from the observation data of meteorological stations between 1988 and 2018. The characteristics of climate change and its correlation with the change of area in the Bosten Lake Basin in the past 30 years were analyzed. The major contributions of this study are as follows: (1) The initial water body was segmented based on the water index model Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) with a pre-assigned threshold value. The results were evaluated with the area extracted through artificial visual interpretation. Then we conducted mathematical morphology operators, opening and closing operations, and median filter to eliminate noise to ensure the accuracy of water body information extraction from the Bosten Lake. A long-term water surface area database of the Bosten Lake was established from high-resolution remote sensing images during 1988–2018. (2) Due to the seasonal difference of snow, ice content, and other objects on images, the areadynamics of Bosten Lake in the recent 30 years were analyzed separately in dry season and rainy season. The water surface area of Bosten Lake showed large inter-annual variations between 1988–2018. (3) Based on the assumption that climatic change has more direct effects on lake than human activities, six meteorological factors were selected to analyze the impacts of climate change on the annual mean lake surface area. The result indicated that in the past 30 years, climate conditions in the Bosten Lake Basin fluctuated greatly. We conducted correlations analysis between the areal dynamics of the Bosten Lake and the meteorological factors. Here, the annual average evaporation had the highest correlation with the areal dynamics of Bosten Lake followed by air temperature, precipitation, sunshine hours, and relative humidity, while the annual average wind speed had the weakest correlation.

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Quantifying recent lake level changes in Patagonia (Argentina and Chile): Back to the future?

10.5194/egusphere-egu21-8467 ◽

2021 ◽

Author(s):

Daniel Ariztegui ◽

Clément Pollier ◽

Andrés Bilmes

Keyword(s):

Water Level ◽

Lake Level ◽

Satellite Images ◽

Meteorological Data ◽

Tierra Del Fuego ◽

Water Level Fluctuations ◽

Lake Levels ◽

The Past ◽

Rainfall Variations ◽

The Impact

Lake levels in hydrologically closed-basins are very sensitive to climatically and/or anthropogenically triggered environmental changes. Their record through time can provide valuable information to forecast changes that can have substantial economical and societal impact.Increasing precipitation in eastern Patagonia (Argentina) have been documented following years with strong El Ni&#241;o (cold) events using historical and meteorological data. Quantifying changes in modern lake levels allow determining the impact of rainfall variations while contributing to anticipate the evolution of lacustrine systems over the next decades with expected fluctuations in ENSO frequencies. Laguna Carrilaufquen Grande is located in the intermontane Maquinchao Basin, Argentina. Its dimension fluctuates greatly, from 20 to 55 km2 water surface area and an average water depth of 3 m. Several well-preserved gravelly beach ridges witness rainfall variations that can be compared to meteorological data and satellite images covering the last ~50 years. Our results show that in 2016 lake level was the lowest of the past 44 years whereas the maximum lake level was recorded in 1985 (+11.8 m above the current lake level) in a position 1.6 km to the east of the present shoreline. A five-years moving average rainfall record of the area was calculated smoothing the extreme annual events and correlated to the determined lake level fluctuations. The annual variation of lake levels was up to 1.2 m (e.g. 2014) whereas decadal variations related to humid-arid periods for the interval 2002 to 2016 were up to 9.4 m. These data are consistent with those from other monitored lakes and, thus, our approach opens up new perspectives to understand the historical water level fluctuations of lakes with non-available monitoring data.&#160;Laguna de los Cisnes in the Chilean section of the island of Tierra del Fuego, is a closed-lake presently divided into two sections of 2.2 and 11.9 km2, respectively. These two water bodies were united in the past forming a single larger lake. The lake level was&#160; ca. 4 m higher than today as shown by clear shorelines and the outcropping of large Ca-rich microbialites. Historical data, aerial photographs and satellite images indicate that the most recent changes in lake level are the result of a massive decrease of water input during the last half of the 20th century triggered by an indiscriminate use of the incoming water for agricultural purposes. The spectacular outcropping of living and fossil microbialites is not only interesting from a scientific point of view but has also initiated the development of the site as a local touristic attraction. However, if the use of the incoming water for agriculture in the catchment remains unregulated the lake water level might drop dangerously and eventually the lake might fully desiccate.These two examples illustrate how recent changes in lake level can be used to anticipate the near future of lakes. They show that ongoing climate changes along with the growing demand of natural resources have already started to impact lacustrine systems and this is likely to increase in the decades to come.

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Impact of climate change and human activity on the runoff in the upper reaches of the Shiyang River, Northwest China

10.7287/peerj.preprints.187 ◽

2014 ◽

Author(s):

Peng Li ◽

Jianhua Xu ◽

Zhongsheng Chen ◽

Benfu Zhao

Keyword(s):

Climate Change ◽

Human Activity ◽

Climatic Factors ◽

Meteorological Data ◽

Northwest China ◽

Potential Evaporation ◽

The Past ◽

Shiyang River Basin ◽

Runoff Change ◽

Increasing Trend

Based on the hydrological and meteorological data of the upper reaches of Shiyang River basin in Northwest China from 1960 to 2009, this paper analyzed the change in runoff and its related climatic factors, and estimated the contribution of climate change and human activity to runoff change by using the moving T test, cumulative analysis of anomalies and multiple regression analysis. The results showed that temperature revealed a significant increasing trend, and potential evaporation capacity decreased significantly, while precipitation increased insignificantly in the past recent 50 years. Although there were three mutations in 1975, 1990 and 2002 respectively, runoff presented a slight decreasing trend in the whole period. The contributions of climate change and human activity to runoff change during the period of 1976-2009 were 45% and 55% respectively.

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Study on the Spatial and Temporal Pattern of Qinghai Lake Area in the Past 50 Years

Communications in Computer and Information Science - Geo-Spatial Knowledge and Intelligence ◽

10.1007/978-981-13-0896-3_19 ◽

2018 ◽

pp. 178-191

Author(s):

Baokang Liu ◽

Yu’e Du ◽

Weiguo He ◽

Shuiqiang Duan ◽

Tiangang Liang

Keyword(s):

Temporal Pattern ◽

Qinghai Lake ◽

Lake Area ◽

The Past

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Monitoring of Inland Surface Water Quality Using Remote Sensing on the Example of Wigry Lake

E3S Web of Conferences ◽

10.1051/e3sconf/20186300017 ◽

2018 ◽

Vol 63 ◽

pp. 00017

Author(s):

Michał Lupa ◽

Katarzyna Adamek ◽

Renata Stypień ◽

Wojciech Sarlej

Keyword(s):

Water Quality ◽

Surface Water ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Surface Water Quality ◽

Lake Area ◽

Landsat Images ◽

Secchi Disc ◽

Water Index ◽

Normalized Difference Water Index

The study examines how LANDSAT images can be used to monitor inland surface water quality effectively by using correlations between various indicators. Wigry lake (area 21.7 km2) was selected for the study as an example. The study uses images acquired in the years 1990–2016. Analysis was performed on data from 35 months and seven water condition indicators were analyzed: turbidity, Secchi disc depth, Dissolved Organic Material (DOM), chlorophyll-a, Modified Normalized Difference Water Index (MNDWI), Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI). The analysis of results also took into consideration the main relationships described by the water circulation cycle. Based on the analysis of all indicators, clear trends describing a systematic improvement of water quality in Lake Wigry were observed.

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Lake Phenology of Freeze-Thaw Cycles Using Random Forest: A Case Study of Qinghai Lake

Remote Sensing ◽

10.3390/rs12244098 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4098

Author(s):

Weixiao Han ◽

Chunlin Huang ◽

Hongtao Duan ◽

Juan Gu ◽

Jinliang Hou

Keyword(s):

Surface Water ◽

Random Forest ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Qinghai Lake ◽

Water Index ◽

Freeze Thaw ◽

Normalized Difference Water Index ◽

Break Up

Lake phenology is essential for understanding the lake freeze-thaw cycle effects on terrestrial hydrological processes. The Qinghai-Tibetan Plateau (QTP) has the most extensive ice reserve outside of the Arctic and Antarctic poles and is a sensitive indicator of global climate changes. Qinghai Lake, the largest lake in the QTP, plays a critical role in climate change. The freeze-thaw cycles of lakes were studied using daily Moderate Resolution Imaging Spectroradiometer (MODIS) data ranging from 2000–2018 in the Google Earth Engine (GEE) platform. Surface water/ice area, coverage, critical dates, surface water, and ice cover duration were extracted. Random forest (RF) was applied with a classifier accuracy of 0.9965 and a validation accuracy of 0.8072. Compared with six common water indexes (tasseled cap wetness (TCW), normalized difference water index (NDWI), modified normalized difference water index (MNDWI), automated water extraction index (AWEI), water index 2015 (WI2015) and multiband water index (MBWI)) and ice threshold value methods, the critical freeze-up start (FUS), freeze-up end (FUE), break-up start (BUS), and break-up end (BUE) dates were extracted by RF and validated by visual interpretation. The results showed an R2 of 0.99, RMSE of 3.81 days, FUS and BUS overestimations of 2.50 days, and FUE and BUE underestimations of 0.85 days. RF performed well for lake freeze-thaw cycles. From 2000 to 2018, the FUS and FUE dates were delayed by 11.21 and 8.21 days, respectively, and the BUS and BUE dates were 8.59 and 1.26 days early, respectively. Two novel key indicators, namely date of the first negative land surface temperature (DFNLST) and date of the first positive land surface temperature (DFPLST), were proposed to comprehensively delineate lake phenology: DFNLST was approximately 37 days before FUS, and DFPLST was approximately 20 days before BUS, revealing that the first negative and first positive land surface temperatures occur increasingly earlier.

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Modelling water yield with the InVEST model in a data scarce region of northwest China

Water Science & Technology Water Supply ◽

10.2166/ws.2020.026 ◽

2020 ◽

Vol 20 (3) ◽

pp. 1035-1045 ◽

Cited By ~ 1

Author(s):

Xu Yang ◽

Ruishan Chen ◽

Michael E. Meadows ◽

Guangxing Ji ◽

Jianhua Xu

Keyword(s):

Temporal Dynamics ◽

Northwest China ◽

Reanalysis Data ◽

Water Yield ◽

Lake Basin ◽

Lake Area ◽

Bosten Lake ◽

Invest Model ◽

Unused Land ◽

Integrated Valuation

Abstract The Bosten Lake basin is an important arid region of northwest China, and has exhibited a declining trend in both lake area and level of water during recent decades. Reliable information on water yield, an important attribute of available water resources in a region, is vital to assess the potential for socio-economic development. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model is applied here to simulate water yield in the Bosten Lake basin. The spatial and temporal dynamics of water yield, and the response of water yield to land use and precipitation change, are analysed for the period 1985 to 2015. The results show that, overall, water yield increased during 1985–2015, and that the magnitude of change was greater in the eastern part of the region. The water yield capacity, positively correlated with precipitation, is highest under grassland vegetation and lowest in cultivated and unused land. The paper demonstrates that statistical downscaling and climate reanalysis data can be used in the InVEST model to improve the accuracy of simulated water yield in data scarce regions.

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