Water Level Stations Research Articles

Reflection of Storm Surge and Tides in Convergent Estuaries With Dams, the Case of Charleston, USA

AbstractConvergent estuaries have been shortened by dam‐like structures worldwide. Here, we evaluate 31 long‐term water level stations and use a semi‐analytical tide model to investigate how landward‐funneling and a dam influence tidal and storm surge propagation in the greater Charleston Harbor region, South Carolina, where three rivers meet: the Ashley, Cooper, and Wando. Results show that the phase speed and amplification of the principal tidal harmonic (M2) is larger than other long waves such as storm surge (∼1–4 days) and setup‐setdown (∼4–10 days). Further landward, all waves attenuate, but, as they approach the dam on the Cooper River, a frequency dependent response in amplitude and phase progression occurs. A semi‐analytical tidal model shows that funneling and the presence of a dam amplify tidal waves through wave interference from partial and full reflection, respectively. The different phase progressions of the reflected waves interact with the incident wave to increase or decrease the summed overall wave amplitude. Using a friction‐convergence parameter space, we demonstrate that dominant tides in 23 estuaries and the tidal, storm surge, and setup‐setdown waves in the Cooper River can be delineated into three regimes that describe landward amplification or attenuation associated with funneling, a dam, or both. The regime of each tidal constituent is consistent but can change with the duration and height of each storm surge event; dam associated wave interference can attenuate long‐duration events, while the most intense events (short duration, high water) are amplified by dams more than funneling and greatly increase flood exposure.

Spatial diversion and coordination of flood water for an urban flood control project in Suzhou, China

Suzhou City, located in the Yangtze River Delta in China, is prone to flooding due to a complex combination of natural factors, including its monsoon climate, low elevation, and tidally influenced position, as well as intensive human activities. The Large Encirclement Flood Control Project (LEFCP) was launched to cope with serious floods in the urban area. This project changed the spatiotemporal pattern of flood processes and caused spatial diversion of floods from the urban area to the outskirts of the city. Therefore, this study developed a distributed flood simulation model in order to understand this transition of flood processes. The results revealed that the LEFCP effectively protected the urban areas from floods, but the present scheduling schemes resulted in the spatial diversion of floods to the outskirts of the city. With rainstorm frequencies of 10.0% to 0.5%, the water level differences between two representative water level stations (Miduqiao (MDQ) and Fengqiao (FQ)) located inside and outside the LEFCP area, ranged from 0.75 m to 0.24 m and from 1.80 m to 1.58 m, respectively. In addition, the flood safety margin at MDQ and the duration with the water level exceeding the warning water level at FQ ranged from 0.95 m to 0.43 m and from 4 h to 22 h, respectively. Rational scheduling schemes for the hydraulic facilities of the LEFCP in extreme precipitation cases were developed according to flood simulations under seven scheduling scenarios. This helps to regulate the spatial flood diversion caused by the LEFCP during extreme precipitation.

Trends? Complicated answers to a simple question

ABSTRACT Trend significance of time series that are serially correlated is once more addressed. Most conventional techniques to “pre-whiten” the series prior to calculating trends rely on the assumption of autoregressive residual noise, AR(1). Monthly recordings of 40 water level stations in Germany are investigated, revealing strong memory up to lag 2. A new scheme (PW(p) ) is introduced that extends pre-whitening to AR(p) with p > 1. It performs well on surrogate series with prescribed trend and memory. For seven series the estimated trends are unrealistically off, raising doubts about the validity of the basic assumptions of short-memory noise. The series are characterized by a hockey stick pattern from which any pre-whitening produces trends that are all but plausible. The pattern also reveals that pre-whitening is not invariant under time reversal. Regardless of the validity of the noise model, these special cases serve as a warning for using pre-whitening in general.

Estimating terrestrial water storage variations in Chile with the effects of earthquakes deducted

ABSTRACT Chile has unevenly distributed water resources, limited water level stations and earthquake-prone geological conditions, making it difficult to accurately and comprehensively monitor Chile’s terrestrial water storage (TWS) variations. The Gravity Recovery and Climate Experiment (GRACE) has been widely used to estimate TWS variations. This study uses GRACE solutions and a method of eliminating earthquake effects to estimate TWS variations. The estimation results with earthquake effects deducted show that the rate of TWS variation in Chile is generally a decreasing trend of −0.16 ± 0.096 cm year−1. Furthermore, in the target period, precipitation mainly decreased and evapotranspiration increased. Correlation coefficients between TWS variations, precipitation and evapotranspiration are less than 0.4, suggesting that the factors in TWS are more complex. Temperature also shows an increasing trend of 0.06°C year−1 in Chile. This information will help to understand the characteristics of the TWS variation in Chile and its response to climate change.

A Spatial-Reduction Attention-Based BiGRU Network for Water Level Prediction

According to the statistics of ship traffic accidents on inland waterways, potential safety hazards such as stranding, hitting rocks, and suspending navigation are on the increase because of the sudden rise and fall of the water level, which may result in fatalities, environmental devastation, and massive economic losses. In view of this situation, the purpose of this paper is to propose a high-accuracy water-level-prediction model based on the combination of the spatial-reduction attention and bidirectional gate recurrent unit (SRA-BiGRU), which provides support for ensuring the safe navigation of ships, guiding the reasonable stowage of ships, and flood prevention. The first contribution of this model is that it makes use of its strong fitting ability to capture nonlinear characteristics, and it fully considers the time series of water-level data. Secondly, the bidirectional recurrent neural network structure makes full use of past and future water-level information in the mapping process between input and output sequences. Thirdly, and most importantly, the introduction of spatial-reduction attention on the basis of BiGRU can not only automatically capture the correlations between the hidden vectors generated by BiGRU to address the issue of precision degradation due to the extended time span in water-level-forecasting tasks but can also make full use of the spatial information between water-level stations by emphasizing the influence of significant features on the prediction results. It is noteworthy that comparative experiments gradually prove the superiority of GRU, bidirectional recurrent neural network structure, and spatial-reduction attention, demonstrating that SRA-BiGRU is a water-level-prediction model with high availability, high accuracy, and high robustness.

Deciphering the water balance of poljes: example of Planinsko Polje (Slovenia)

Poljes are flat closed karst depressions prone to regular flooding. The floods can be several meters high, last for months and damage significantly human infrastructures. To predict the maximum level reached, the polje water balance needs to be implemented. This technique encounters the difficulty that important part of the inflow and outflow flowing through many poljes is ungauged, as it is challenging to measure accurately the numerous springs and ponors activating temporarily with the rise of water level. This work aims to see whether this problem can be handled and the polje water balance reconstituted. To do so, a typical Dinaric polje is equipped with several water level stations installed over its surface and in the nearby water active caves. Combining a 1*1m digital elevation model of the polje surface with water levels and inflow records of the main two springs allowed assessing the variation of flooded volume and reconstructing the water balance. The highest total inflow values reached during the observed period were of about 140-150 m3/s, with up to a third of it being ungauged. In addition, the effect of a large estavelles group on the polje inflow and outflow could be identified, and helped to characterize the outflow, with values comprised between 65 and 75 m3/s. Finally, intense rainfall over the polje flooded surface showed to be a temporary important source of inflow. The values found by the water balance analysis have been used as input and calibration data in a numerical model reproducing the flood dynamics in the polje and its surrounding aquifer. Results validated both polje water balance and conceptual hydrogeological model. They justify the significance of combining water level measurements with a digital elevation model to monitor the floods. The method can be applied to other poljes flooding in a complex way of superposed input and output signals. Finally, the places to be equipped in priority if the polje has no measurement network or if available funding is limited are discussed.

IoT based real-time monitoring system of rainfall and water level for flood prediction using LSTM Network

Floods in recent years have frequently resulted in environmental, economic, as well as loss of human life. People are less aware of incoming floods if there is no early warning system. This proposal outlines the design of a monitoring system to obtain real-time data on rain gauge and water level. The monitoring system is based on IoT via a GSM network to provide real-time data cloud and dashboard display on Grafana platform. The rainfall forecasting model used Long Short-Term Memory (LSTM) networks to predict future rainfall and water level values which could cause floods. The result was experimented with using historical data since the current data of the monitoring system is insufficient yet to make an accurate prediction. The main findings of the research are the predicted values of streamflow and rainfall for historical data, also water level and rain gauge for new data. The primary result was experimented with using historical data on two rainfall stations and one streamflow. Also, the primary result was experimented with using new data on two water level stations and one rainfall. The forecasting method that applied LSTM showed high accuracy of the result reaching more than 90%. Based on these results, the system can be used as a non-structural solution to alleviate the damage caused by urban floods.

Seasonal to interannual variability of the tide in the Amazon estuary

The Amazon River exports the largest volume of fresh water to the ocean worldwide. Although previous studies have revealed the spatiotemporal tidal variability of the estuary, its hydrodynamics is still poorly understood. Here we evaluate the seasonal and interannual variability of the tide from Óbidos (800 km upstream) to the Atlantic Ocean and show how it is affected by the hydrological regime of the Amazon River. A high-resolution 2D hydrodynamic model was applied in this region at the scale of the whole estuary. The tide model is validated using data from 14 water level stations and shows an average complex error of 16 cm in the low flow season and 23 cm in the high flow season. The semi-diurnal tide is highly variable at seasonal timescales, and the seasonality of the discharge affects the tidal amplitude, the geographic extent of tidal influence, the tidal wave celerity, and the tidal flow reversal. Notably, the tidal influence on water level remains detectable up to Óbidos during the low flow season while during the high flow season it extends from the ocean to only 300 km downstream of Óbidos. On the other hand, the upstream limit of the domain where the tide induces a periodic flow reversal is different from the limit of tidal influence on the water level. The upstream limit of this flow reversal is shifted by 170 km (from 500 km to 670 km downstream of Óbidos) along the year due to the seasonality of the discharge. At interannual scale, anomalous hydrological discharges affect the tidal amplitude by up to 30% in the central reach of the estuary. Our findings open unprecedented opportunities to understand biogeochemical and geomorphological processes, help navigation, and assess flooding hazards.

Dynamic water level changes in Qinghai Lake from integrating refined ICESat-2 and GEDI altimetry data (2018–2021)

The water levels of inland lakes on the Tibetan Plateau are extremely sensitive to global climate change and can objectively reflect the temporal and spatial changes in local water resources. However, monthly and seasonal variations in lake water levels are difficult to monitor due to the lack of sufficient in situ gauges across mountainous areas. Moreover, GEDI products exhibit large uncertainties in mountainous surroundings. In this paper, taking Qinghai Lake as an example, we first refined the raw data of the GEDI and ICESat-2 missions by implementing a quality control procedure involving outlier removal tailored to the characteristics of each mission; then, we analyzed the accuracy of each mission, especially targeting factors that affect the water level retrievals in the GEDI products. Third, the bias between the two missions was adjusted by selecting the overlapping or adjacent observation dates. Finally, we constructed dense temporal water-level data by integrating the refined ICESat-2 and GEDI data. Data from water level stations and the DAHITI and Hydroweb datasets were also utilized for validation. The results show that (1) very accurate results can be obtained from the ICESat-2 ATL13 product, and the standard deviations of most observed days are under 0.05 m; (2) the GEDI products derived from algorithm 2 can offer more effective footprints than those from algorithm 1, with an improvement of approximately 9.78 %. Moreover, large differences exist among the different GEDI beams, and beams 1 and 2 are recommended for further analysis. Overall, most beams overestimated the lake levels with a bias of 0.264 ± 0.357 m; (3) the long-time-series water levels showed a mean increasing trend of 0.243 m/yr from 2018 to 2021. The relatively high-water-level periods were distributed mostly in August and September, while the low-water-level periods were distributed mostly in February and March. The combined water levels were very correlated with the DAHITI and Hydroweb datasets, with R values larger than 0.8, and highly consistent with the observations from hydrological stations (the inter-year change range spanned from 0.015 m to 0.327 m, and the intra-year difference range varied from 0.03 m to 0.16 m); and (4) Integrating the GEDI and ICESat-2 missions allowed us to capture the monthly, seasonal and annual dynamics of the lake water level, and the results indicate that the combined dataset presents a valuable resource for hydrological and climatic change studies.

On the variation of LAT resulting from predictions computed using different tidal constituent sets

ABSTRACT While the Lowest Astronomical Tide (LAT) has a clear definition as the lowest water level caused by astronomical attractions at a water level station, there are variations in the implementation schemes for practically deriving LAT from a time series of tides. This article explores the variation resulting from different tide constituent sets, as named by the numbers, 25, 37, or 60 constituents. Hourly observations of 34 stations around Taiwan were examined in this study. Using LAT-60, the LAT with 60 constituents, as the reference, when the nodal correction is applied, the average deviation of LAT-25 is −2.12 cm, LAT-37 is 0.70 cm, and ISLW is 22.44 cm. Based on the experiments conducted, it is found that the difference between LAT-25 and LAT-60 is 1.18 cm as measured by the third quartile without nodal correction, and 0.89 cm with nodal correction. Nodal correction will lower the water level about 2 cm on average and maximum about 6.7 cm. ISLW is higher and has less influence by nodal correction than LAT so it is difficult to be regarded as a fairly stable water level for chart datum.

Evaluation of Agricultural Water Supply and Selection of Deficient Districts in Yeongsan River Basin of South Korea Considering Supply Priority

Considering the priority of water supply, agricultural water supply capacity downstream of the Yeongsan River Basin was evaluated in this study. The water balance was analyzed using the Please check all author names carefullyMODSIM-decision support system (MODSIM-DSS) to evaluate the agricultural water supply capacity. MODSIM-DSS can also be used to analyze the watershed demand status and agricultural water supply facilities. In this study, the watershed inflow and agricultural reservoir inflow (supply) data for each watershed were obtained using the SWAT outflow data. SWAT was calibrated and validated using 16-years (2005–2020) of daily streamflow data from one water level station and two weirs, by considering water withdrawal and return flows from agricultural, domestic, and industrial water use. The coefficient of determination (R2) was analyzed as 0.50 to 0.80 at three stations. Then, water balance analyses were performed for 41 years (1980–2020) by applying the SWAT outflow results to MODSIM-DSS. The results showed that agricultural water shortages of 517.8 × 106 m3, 520.0 × 106 m3, 579.8 × 106 m3, and 517.5 × 106 m3, occurred in 1992, 1994, 1995, and 2015, respectively. The efficiencies of agricultural water supply for these years were 58.2%, 58.0%, 53.2%, and 58.2%, respectively, which were lower than the 40-year average of 84.5%.

Study on water level correlation of key nodes in the north line of East Zhejiang Water Diversion Project

Eastern Zhejiang is an important area for the economic development of Zhejiang Province. However, water resources in eastern Zhejiang are relatively poor. After the completion of the north line of East Zhejiang Water Diversion Project, the catchment and drainage connecting rivers of all counties and cities have been dredged, the flood control and drainage capacity of all counties and cities has been improved, the river channels along the line have also been comprehensively renovated, the river network water environment of Shangyu City, Yuyao City and Cixi City along the water diversion line has been significantly improved, and the environmental quality of the area around Hangzhou Bay on the South Bank of Qiantang River has been improved. In order to find out the correlation between the water levels of key nodes of the project and provide more targeted guidance for future scheduling, this paper uses the partial least square method to calculate the relationship between the water levels of each node. It is found that there is a significant correlation between the upper water level of Sanxing sluice and the water level under Xinsan sluice and Mashan sluice, and there is a certain correlation with the upper water level of xinsanjiang sluice and Mashan sluice. The correlation between the upstream water level of Xiaoshan hydroproject and the water levels under xinsanjiang sluice, Heshan sluice and Mashan sluice is obvious; There is the most significant linear correlation between the water level of Hengjiang River in xisantang and the water level of Lingshan, Lingshan, Qitang, Sitou and Sitou. The correlation between the water level of Yangxun bridge, Puqian gate and Qitang gate is also significant, and the correlation of other water level stations is poor. In addition, there is a great correlation between the water level of Yangxun bridge and the downstream water level. Attention should be paid to observing the water level of Yangxun bridge during the dispatching process.

Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea

In our intelligent society, water resources are being managed using vast amounts of hydrological data collected through telemetric devices. Recently, advanced data quality control technologies for data refinement based on hydrological observation history, such as big data and artificial intelligence, have been studied. However, these are impractical due to insufficient verification and implementation periods. In this study, a process to accurately identify missing and false-reading data was developed to efficiently validate hydrological data by combining various conventional validation methods. Here, false-reading data were reclassified into suspected and confirmed groups by combining the results of individual validation methods. Furthermore, an integrated quality control process that links data validation and reconstruction was developed. In particular, an iterative quality control feedback process was proposed to achieve highly reliable data quality, which was applied to precipitation and water level stations in the Daecheong Dam Basin, South Korea. The case study revealed that the proposed approach can improve the quality control procedure of hydrological database and possibly be implemented in practice.

Quantifying the hydrological implications of pre- and post-installation willowed engineered log jams in the Pennine Uplands, NW England

Nature Based Solutions (NBS), including Natural Flood Management (NFM) schemes are becoming an important component of many governmental and organisation responses to increases in flood and aridity risk. NFM structures may take multiple forms to slow, store, disconnect and filter distributed overland flow pathways within a catchment that coalesce to generate a flood-wave downstream and runoff rather than infiltrate groundwaters. To date few studies have conducted observations pre- and post-installation monitoring at river reach-scales, despite widespread and frequent installation, to investigate the efficacy of willowed engineered log jams (WELJs) interventions used in abating flood-flows, through backing-up flood-pulses with consequent reductions in downstream discharges. This paper examines the efficiency, before and after installation of five 1 m high WELJs incorporating 1,000 Bay willow (Salix pentandra) saplings supporting the dead horizontal timber, across a total of 130 linear metres spanning the floodplain of a decommissioned reservoir. One rain gauge, two fixed point time-lapse wildlife cameras and three water level stations were installed: upstream-of, within, and downstream-of all WELJs. The findings demonstrate a substantial reduction is achieved for most events, with an average of 27.3% reduction in peak discharge being achieved post-installation. The time to peak is little impacted, however there is demonstrable evidence of a longer and higher recessional limb to the events. These findings quantify for the first time the role that WELJs can play in a move towards re-naturalisation of water level regimes, with lower peak water flows achieved, and waters released from the river-reach more slowly. Furthermore, baseflow during dry periods is also elevated by 27.1%, offering greater resilience to dry periods and droughts. Consequently, over the river-reach scale (0–130 m), WELJs play an important role in alleviating flood and drought risk through suppressing flood peaks and increasing baseflow during low flows; steps towards improved hydro-morphological quality overall.

Modeling of tide in the Java sea coastal area between Jakarta and Cirebon, Indonesia: bathymetric data source and sensitivity tests due to bottom roughness and boundary condition

With the on-going construction of deep water port in Patimban area, a more dense marine traffic is expected to occur in the coastal belt between the ports of Jakarta and Cirebon. Precise prediction of tide is inevitably becoming more important in order to maintain safe navigation. The purpose of this work is carrying out a dedicated tidal simulation for the area in question. The presented result contains primarily the selection of bathymetric data for the development of computational domain and sensitivity tests due to bottom roughness and the quantity of elevation points along the model’s open boundaries. For the purpose of constructing computational domain, we assess the suitability of global and national bathymetry data. Data from two water level stations in Sunda Kelapa and Cirebon ports are used to verify the model output, for example surface elevation due to tide. The simulation of tide is carried out using two-dimensional horizontal numerical model facilitated by Delft3D software. Sensitivity tests considering two bottom roughness values and three scenarios of boundary conditions are carried out. It is found that the short-term tidal simulation indicates reasonable agreement against tidal data from Sunda Kelapa and Cirebon stations. It seems that bottom roughness does not provide significant control to the resulting magnitude. We have learned that an optimum number of tidal elevation points along the boundary condition must be set. Despite of the demands in improving the tidal phase, our present results indicate promising milestones toward a precise tidal simulation for the domain in question.

Wavelet decomposition and deep learning of altimetry waveform retracking for Lake Urmia water level survey

Lake Urmia is located in the northwest of Iran and shared between the provinces of West Azarbaijan and East Azarbaijan. In the last two decades, there has been a considerable decline in the lake’s water level. Satellite altimetry (SA) together with the advanced precise orbital positioning system has reached a high accuracy in the measurement of the water level height, but increasing the accuracy of waveform retracking (WR) is a challenging issue. In this study, wavelet decomposition and convolutional neural network were used for the WR with 50%, 55%, and 60% training scenarios and the threshold method was used for the 1992–2019 period. The training of 55% has the best result with a ± 0.027 m root mean square error. The water level has decreased by approximately 7 m from 1994 to 2018 and its overall trend is downward. The proposed method has been able to increase the WR accuracy by up to 30%. The gravity recovery and climate experiment and the annual monitoring of the water level station have also been used for the SA verification, which have a significant correlation of 0.66 and 0.96 with SA, respectively.

Frequency analysis of representative flood control water level stations in Puyang River

Puyang river basin is located in the north central part of Zhejiang Province, which is one of the most important river basins in Zhejiang Province. The lower reaches of Puyang River are easily influenced by tide in Hangzhou Bay and flood in Qiantang River. When Puyang river floods, it often meets Fuchun River and floods occur at the same time. The flood discharge of Puyang river is blocked and the water level rises and rises, which makes the Puyang River vulnerable to disaster. Water level frequency analysis is the basis of Puyang river planning and flood control plan. The representative flood control water level stations of Puyang River include Zhuji station and wenjiayan station. The frequency analysis of these representative stations is helpful to determine the water level of these key nodes under different frequencies, and to provide basic data for accurate flood control of Puyang River and ensure the safety of flood control.

Developing a Rainfall Impact Forecasting Model for Disaster Mitigation around the River

Impact forecasting has been applied to estimate flood damage in many different countries based on accurate weather forecasts. This study develops a model forecasting the impact of rainfall on riverside flood risks in the Busan Metropolitan City. The rainfall impact forecasting equations were obtained on a 1km x 1km grid with respect to water levels and critical rainfall thresholds. Critical rainfall was determined based on the end point of river and the discharge-water level relationship between design flood discharge and design flood level by analyzing water-rainfall in 3-hour critical rainfall. Model verification was performed using a heavy rain event with a total of 283.3 mm from July 22 to 24, 2020. According to the rainfall impact forecasting, 60 to 70% of the design flood level (“MEDIUM” alert) was issued on rivers between 10-11pm on July 23. In the rivers where the rainfall impact alert was issued, actual damages were found such as flooded roads and floodplain, which confirmed the appropriateness of the model. The high model accuracy was also validated by comparing the alert standard for water level with forecasted rainfall impact at the water level station in Suyeong River.

Flood inundation modeling and hazard assessment in Lower Ping River Basin using MIKE FLOOD

Annual fluvial and pluvial floods happened in Lower Ping River Basin, Thailand. A flood hazard assessment approach was performed in the present study to evaluate flood impacts. The coupled 1D-2D hydrodynamic (HD) modeling package was applied for different return periods to investigate and classify the flood hazards. The 1D hydrodynamic model was calibrated for flood year 2011 at discharge and water level stations. The 2D hydrodynamic model was calibrated using observed flood map. Flood hazards were categorized based on critical flood depths for flooding scenarios of 2-, 5-, 10-, 25-, 50-, and 100-year return periods. The results showed that 28.8% of the total basin area (2423.8 km2) was flooded during the 100-year return period, and the maximum flood inundation area was observed in Kamphaengphet and Nakhon Sawan provinces. Mostly, the flooded area under each return period was categorized under high hazard, followed by low and medium, and the least area was classified under a very high hazard level. More than 40% of sub-districts’ area of Kamphaengphet and Nakhon Sawan provinces were flooded, which is located along the Ping River, while less than 20% sub-districts’ area was flooded in Tak Province. The government and local stakeholders need to consider structural and nonstructural measures to reduce flood impacts in three provinces, and priority-based areal flood management approaches should be considered during the implementation of flood mitigation measures.

Evaluation of Instream Flow in the Imjingang River according to the Operation of Hwanggang Dam in North Korea

This study evaluated the instream flow of the existing dams and major water-level stations in the Imjingang river basin by the operation of Hwanggang Dam in North Korea and proposed a solution for securing instream flows. First, stream flow, basin inflow, and dam releases were reasonably estimated by water balance analysis using daily averaged data in the Imjingang river basin. Second, streamflows at major water-level stations in the Imjingang river basin decreased significantly after the Hwaggang dam operation, which confirmed that the Hwanggang Dam in North Korea had a significant effect on the streamflows of the Imjingang river basin in South Korea. Third, the instream flow analysis for the Imjingang river basin confirmed that instream flows were not consistently satisfied in all water-level stations. Finally, the Hwanggang Dam operation was one of the main reasons for the lack of instream flow, since the total amount and period of shortage increased up to 14,156% and 16,800%, respectively after the Hwanggan dam operation. We then suggested how to utilize the existing dams and shared river basins to secure instream flow. In the future, various long-term and well-planned strategies would be needed.