scholarly journals Assessing Hydrological and Sedimentation Effects from Bottom Topography Change in a Complex River–Lake System of Poyang Lake, China

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1489 ◽  
Author(s):  
Xuchun Ye ◽  
Qiang Guo ◽  
Zengxin Zhang ◽  
Chongyu Xu

In recent years, a dramatic decline in Poyang Lake water levels and a shrinking water surface have raised concerns about water security and the wetland ecosystem. Changes in bottom topography due to sand mining activities in the lake was supposed to be one of the influencing factors of these changes. In response to this issue, the current study analyzed the change of lake bottom topography from observed digital elevation model (DEM) data, and quantitatively assessed the spatial and temporal responses of lake hydrology based on the framework of the neural network and the sediment effect was examined afterward. Results showed a total volume of 11.54 × 108 m3/year (about 0.96 × 108 m3/year or 1.58 × 108 t/year sediment) in net change of lake bottom topography in recent years, among which 97% was directly exported by commercial sand mining. During the study period, 2000–2011, intensive sand mining extended the central part of Poyang Lake and widened and deepened the outflow channel of the northern lake. This great change of lake bottom topography caused an average annual increase of 182.74 m3/s of lake outflow and a decline of 0.23 m–0.61 m in water levels across the lake. However, lake water levels are not consistent and show remarkable spatial and seasonal differences. The effects of changes in lake bottom topography on lake hydrological processes continue to grow as sand mining activities in the lake continue. More research on the environmental impacts is required for sustainable management of the lake ecosystem.

2019 ◽  
Vol 117 ◽  
pp. 00014
Author(s):  
Jian-Zhao Guan ◽  
Lei Zhang ◽  
Chun-Ming Fang ◽  
Jun Feng

The drastic decline in the water level of Poyang Lake during the dry season has close connection with the water environment and lake ecology. The drastic decline has attracted considerable attention, and has led to intense scientific discussions regarding its cause. However, the importance of the different causes of the low water level decline has not been clearly illustrated. To improve the understanding of the reasons for the decline of low water levels in the Poyang Lake Waterway, this paper investigated the contributions of river channel erosion and sand mining to the water level decline. The results show that sand mining mainly occurred on the beaches of the Waterway, and had a relatively small effect on the change in the shape of the main river channel. It was found that the contribution of sand mining to the decline in the low water level was no more than 30%, while the average contribution by natural erosion was about 85%. This indicates that natural channel erosion of the Waterway has been significant, and plays a dominant role in the declining water levels of the Waterway.


2016 ◽  
Vol 47 (S1) ◽  
pp. 69-83 ◽  
Author(s):  
Bing Li ◽  
Guishan Yang ◽  
Rongrong Wan ◽  
Xue Dai ◽  
Yanhui Zhang

Modeling of hydrological time series is essential for sustainable development and management of lake water resources. This study aims to develop an efficient model for forecasting lake water level variations, exemplified by the Poyang Lake (China) case study. A random forests (RF) model was first applied and compared with artificial neural networks, support vector regression, and a linear model. Three scenarios were adopted to investigate the effect of time lag and previous water levels as model inputs for real-time forecasting. Variable importance was then analyzed to evaluate the influence of each predictor for water level variations. Results indicated that the RF model exhibits the best performance for daily forecasting in terms of root mean square error (RMSE) and coefficient of determination (R2). Moreover, the highest accuracy was achieved using discharge series at 4-day-ahead and the average water level over the previous week as model inputs, with an average RMSE of 0.25 m for five stations within the lake. In addition, the previous water level was the most efficient predictor for water level forecasting, followed by discharge from the Yangtze River. Based on the performance of the soft computing methods, RF can be calibrated to provide information or simulation scenarios for water management and decision-making.


Author(s):  
Qiyue Li ◽  
Geying Lai ◽  
Adam Thomas Devlin

Abstract The recession of water levels of natural lakes and their associated impacts on wetland ecosystems is a serious issue worldwide. Poyang Lake (the largest freshwater lake in China) has experienced a heightened and prolonged water decline since the year 2000, which causes concern for associated ecological impacts. In particular, climate change, operation of the Three Gorges Dam (TGD), and high magnitude sand mining appear to be well-correlated with the occurrence of water decline in Poyang Lake. Though the above factors have been analyzed in previous studies, a comprehensive summary has never been compiled. This paper provides a detailed literary review highlighting the driving forces and possible impacts of the consistent water decline in Poyang Lake. We conclude here that the operation of TGD is a fundamental cause for the lake water decline, aggravated by climate change and sand mining. The water decline has caused a deterioration of water quality, as well as having given rise to a potential threat to the habitat of migratory birds and Yangtze finless porpoises. The paper intends to offer constructive references that can be used in decision-making for effective protection of water resources and lake ecosystems.


2019 ◽  
Author(s):  
Yunliang Li ◽  
Qi Zhang ◽  
Hui Tao ◽  
Jing Yao

Abstract This study outlines a framework for examining potential impacts of future climate change in Poyang Lake water levels using linked models. The catchment hydrological model (WATLAC) was used to simulate river runoffs from a baseline period (1986–2005) and near-future (2020–2035) climate scenarios based on eight global climate models (GCMs). Outputs from the hydrological model combined with the Yangtze River's effects were fed into a lake water-level model, developing in the back-propagation neural network. Model projections indicate that spring–summer water levels of Poyang Lake are expected to increase by 5–25%, and autumn–winter water levels are likely to be lower and decrease by 5–30%, relative to the baseline period. This amounts to higher lake water levels by as much as 2 m in flood seasons and lower water levels in dry seasons in the range of 0.1–1.3 m, indicating that the lake may be wet-get-wetter and dry-get-drier. The probability of occurrence for both the extreme high and low water levels may exhibit obviously increasing trends by up to 5% more than at present, indicating an increased risk in the severity of lake floods and droughts. Projected changes also include possible shifts in the timing and magnitude of the lake water levels.


2015 ◽  
Vol 46 (6) ◽  
pp. 912-928 ◽  
Author(s):  
Y. L. Li ◽  
Q. Zhang ◽  
A. D. Werner ◽  
J. Yao

Lake hydrological simulations using physically based models are cumbersome due to extensive data and computational requirements. Despite an abundance of previous modeling investigations, real-time simulation tools for large lake systems subjected to multiple stressors are lacking. The back-propagation neural network (BPNN) is applied as a first attempt to simulate the water-level variations of a large lake, exemplified by the Poyang Lake (China) case study. The BPNN investigation extends previous modeling efforts by considering the Yangtze River effect and evaluating the influence of the Yangtze River on the lake water levels. Results indicate that the effects of both the lake catchment and the Yangtze River are required to produce reasonable BPNN calibration statistics. Modeling results suggest that the Yangtze River plays a significant role in modifying the lake water-level changes. Comparison of BPNN models to a 2D hydrodynamic model (MIKE 21) shows that comparable accuracies can be obtained from both modeling approaches. This implies that the BPNN approach is well suited to long-term predictions of the water-level responses of Poyang Lake. The findings of this work demonstrate that BPNN can be used as a valuable and computationally efficient tool for future water resource planning and management of the Poyang Lake.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1135
Author(s):  
Carolyn Payus ◽  
Lim Ann Huey ◽  
Farrah Adnan ◽  
Andi Besse Rimba ◽  
Geetha Mohan ◽  
...  

For countries in Southeast Asia that mainly rely on surface water as their water resource, changes in weather patterns and hydrological systems due to climate change will cause severely decreased water resource availability. Warm weather triggers more water use and exacerbates the extraction of water resources, which will change the operation patterns of water usage and increase demand, resulting in water scarcity. The occurrence of prolonged drought upsets the balance between water supply and demand, significantly increasing the vulnerability of regions to damaging impacts. The objectives of this study are to identify trends and determine the impacts of extreme drought events on water levels for the major important water dams in the northern part of Borneo, and to assess the risk of water insecurity for the dams. In this context, remote sensing images are used to determine the degree of risk of water insecurity in the regions. Statistical methods are used in the analysis of daily water levels and rainfall data. The findings show that water levels in dams on the North and Northeast Coasts of Borneo are greatly affected by the extreme drought climate caused by the Northeast Monsoon, with mild to the high risk recorded in terms of water insecurity, with only two of the water dams being water-secure. This study shows how climate change has affected water availability throughout the regions.


2017 ◽  
Vol 14 (3) ◽  
pp. 251
Author(s):  
Rita Yulianti ◽  
Emi Sukiyah ◽  
Nana Sulaksana

Daerah penelitian terletak di desa Muaro Limun, Kecamatan Limun Kabupaten Sarolangun Provinsi Jambi. Sungai limun, salah satu sungai besar di daerah kabupaten sarolangun yang dimanfaatkan oleh mayarakat sekitarnya sebagai sumber penghidupan. Penelitian bertujuan untuk mengetahui pengaruh kegiatan penambangan terhadap kualitas air sungai Batang Limun, dan perubahan sifat fisik dan  kimia yang diakibatkan   kegiatan penambangan.Metode yang digunakan adalah  metode grab sampel, serta stream sedimen untuk dianalis di laboratorium. Sejumlah sampel diambil di beberapa lokasi Penambangan Emas berdasarkan Aliran Sub-DAS dan dibandingkan dengan beberapa sampel lain yang diambil pada lokasi yang belum terkontaminasi oleh kegiatan penambangan. Analisis kualitas air mengacu pada  SMEWWke 22 tahun 2012 dan standar baku mutu air kelas II dalam PP No 82 yang dikeluarkan oleh Menteri Kesehatan No. 492/Menkes/Per/IV/2010. Diketahui sungai Batang Limun telah mengalami perubahan karakteristik fisika dan kimia. Dari grafik  kosentrasi kekeruhan, pH, TSS, TDS  Cu, Pb, Zn, Mn, Hg terlihat bahwa penambang emas tanpa izin (PETI) dengan cara amalgamasi yang menyebabkan terjadinya penurunan kualitas air sungai. Sejak tahun 2009 sampai tahun 2015  sungai Limun dan sekitarnya terus mengalami penurunan kualitas air. Penurunan kualitas yang cukup tinggi terjadi  yaitu peningkatan nilai Rata-rata konsentrasi merkuri pada sungai Batang Limun dari 0,18ppb (0,00018 mg/l)  menjadi 0,3ppb (0,0003 mg/l), peningkatan tersebut dipengaruhi oleh proses kegiatan penambangan dan nilai tersebut masih dibawah standar baku mutu air kelas II  pp nomor 82 tahun 2010.Kata kunci :   Kualitas Air, Sungai Limun,TSS, Merkuri, PETI Limun river is one of the major rivers in the area of Sarolangun, which utilized by the society as a source of livelihood. The aim of study  to analyze the effect of mining activities on  the water quality of Batang Limun River, and the changes of physical and chemical properties of water. The method used are grab  and stream samples to  sediment analyzed in the laboratory. A number of samples were taken at several locations based Flow Gold Mining Sub-watershed and compared to some other samples taken at the location that has not been contaminated by mining activities. Water quality analysis referring to SMEWW, 22nd edition 2012 and refers to Regulation No 82 that issued by Minister of Health No. 492 / Menkes / Per / IV / 2010.The results showed that the Limun river has undergone chemical changes in physical characteristics. These symptoms can be seen from the discoloration of clear water in the river before the mine becomes brownish after mining, based on graphic of muddiness concentration: pH, TSS, TDS Cu, Pb, Zn, Mn, Hg have seen that  the illegal miner which used amalgamation caused deterioration in water quality, data from 2009 to 2015 Limun river and surrounding areas continue to experience a decrease in water quality. The decreasing of water quality showed in the TSS parameter which found in the area is to high based on  the standard of water quality class II pp number 82 of 2010. An increase in the value of average concentrations of mercury in the Batang Limun river before mine 0,18ppb (0.00018 mg / l) into 0,3ppb (0.0003 mg / l) on the river after the mine. The increase was affected by the mining activities and the value is still below the air quality standard Grade II pp numbers 82 years 2010, although the value is still below with the standards quality standard, the mercury levels in water should still be a major concern because if it accumulates continuously in the water levels will increase and will be bad for health. In contrast to the concentration of mercury in sediments that have a higher value is 153 ppb (0,513ppm ) .Key Words :   Water Quality, Limun River, Mercury, Illegal gold mining


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