Daily Water Level Research Articles

REPIQUETES Y RIESGO EN EL CULTIVO DE ARROZ EN LA LLANURA INUNDABLE DEL RÍO AMAZONAS CERCA DE IQUITOS, PERÚ

Las llanuras inundables del río Amazonas poseen un gran potencial para la agricultura, pero no están exentas de riesgos para los agricultores que cultivan en esas tierras fértiles muy propensas a inundaciones. Estas inundaciones repentinas, que ocurren a medida que el nivel del río disminuye entre mayo y noviembre, son conocidas como «repiquetes» y representan una amenaza seria para los cultivos en llanuras inundables, especialmente para el arroz comercial. En este artículo se analiza el registro diario de los niveles de agua del río Amazonas en Iquitos de los últimos 45 años (entre 1968 y 2012), para determinar la frecuencia y magnitud de los repiquetes y su impacto en la temporada de crecimiento del cultivo. Las entrevistas y los estudios de campo realizados en cuatro comunidades ribereñas, cerca del archipiélago Muyuy, revelan el impacto de los repiquetes y otros riesgos en la producción de arroz, así como la disposición de los agricultores al pago por los instrumentos apropiados para disminuir el riesgo de las inundaciones. Nuestros hallazgos apuntan a un seguro basado en índices climáticos, como una nueva estrategia para reducir el riesgo y promover el desarrollo agrícola en las llanuras inundables del Amazonas.

Hydrologic Changes over 60 Years (1959-2019) in an Old-Growth Bald Cypress Swamp on a Rapidly Developing Landscape by Shawn E. Clem and Michael J. Duever

National Audubon Society’s Corkscrew Swamp Sanctuary (Naples, Florida, USA), an ecological relic of Old Florida, protects the largest remaining old-growth bald cypress swamp in the world. A 60-year record of daily water level measurements revealed substantial changes in Corkscrew Swamp’s hydrology as agricultural and residential development have grown to dominate the landscape surrounding the sanctuary. Between 1959 and 2019, surface water data indicate no decadal change in the timing or magnitude of peak wet season water levels or in the hydroperiods (days inundated per water year) of upland hammock and pine forests or wet prairies. Despite little change in rainfall patterns between the 1960s and 2010s, hydroperiods decreased 29% in marshes, 18% in old-growth bald cypress, and 17% in ponds, with the most notable change occurring between the 1990s and 2000s. Average dry season water level recession rate (decrease in water level over time) was 6.3 mm/d in the 2000s and 5.7 mm/d in the 2010s, 47% and 32% higher, respectively, than those seen in earlier decades. Analyses of groundwater data indicated a similar dry season decline between the 1990s and 2000s to that seen in surface water. Analyses of cumulative hydroperiod in surface and groundwater suggested markedly drier conditions began in the 2006 water year. While causes of the observed hydrologic changes are uncertain, likely interacting causes include reduced upstream wet season surface and groundwater storage, increased residential and agricultural extraction, increased downstream drainage, and increased evapotranspiration rates across the region as more deeply-rooted shrubs and trees replace more shallowly-rooted herbaceous plant communities. We discuss significant implications for plant and animal communities, particularly the historic Corkscrew wood stork colony, and discuss the role of long-term hydrologic monitoring for detecting and documenting ecological change.

An Integrated Novel Approach to Understand the Process of Groundwater Recharge in Mountain and Riparian Zone Aquifer System of Tamil Nadu, India

The nature of groundwater recharge along the mountain front (MF) and riparian zone (RZ) was discerned by multiple tools involving rain/water level relationship, geophysical of subsurface, seasonal hydrochemistry and environmental isotopic signatures. The proposed study has been carried out in Courtallam Hills, the north-western part of Tirunelveli District, South India. The study area is a hilly terrain with narrow valleys endowed with steep slopes. The relationship between water-level fluctuation and precipitation were evaluated by observing daily water level in 8-h interval at three piezometer zones and regular rainfall data. It was inferred that the RZ played a role in storage zone and gets recharged from mountain block (MB) and lateral flow. The seasonal geochemistry of the groundwater was studied to determine the sources of recharge in MF and RZ. Geostatistical treatment of factor analysis revealed that weathering was the dominant recharge process along the foothill. The geophysical studies reveal good quality of groundwater observed in the northern part along with low conductance and high resistivity. The increased level of groundwater conductivity and lower resistivity was noted in southern part of the study area due to the irrigation activities. The isotopic tracers range from − 2.5 to − 12.6‰ for δ18O and from − 91.2 to − 15.5‰ for δ2H. Moreover, the groundwater recharge was evaluated by source of rainfall moisture. High-altitude recharge from MB along the MF was clearly indicated by depleted isotopic content of the water samples. It was also supported by hydrogeochemical and statistical evidences, showing that rainfall over both MB and MF zones provided the recharge to foothill aquifers, while the RZ zone was mainly recharged by local precipitation with less contribution from regional flows.

RFim: A Real-Time Inundation Extent Model for Large Floodplains Based on Remote Sensing Big Data and Water Level Observations

The real-time flood inundation extent plays an important role in flood disaster preparation and reduction. To date, many approaches have been developed for determining the flood extent, such as hydrodynamic models, digital elevation model-based (DEM-based) methods, and remote sensing methods. However, hydrodynamic methods are time consuming when applied to large floodplains, high-resolution DEMs are not always available, and remote sensing imagery cannot be used alone to predict inundation. In this article, a new model for the highly accurate and rapid simulation of floodplains, called “RFim” (real-time inundation model), is proposed to simulate the real-time flooded area. The model combines remote sensing images with in situ data to find the relationship between the inundation extent and water level. The new approach takes advantage of remote sensing images, which have wide spatial coverage and high resolution, and in situ observations, which have continuous temporal coverage and are easily accessible. This approach has been applied in the study area of East Dongting Lake, representing a large floodplain, for inundation simulation at a 30 m resolution. Compared with the submerged extent from observations, the accuracy of the simulation could be more than 90% (the lowest is 93%, and the highest is 96%). Hence, the approach proposed in this study is reliable for predicting the flood extent. Moreover, an inundation simulation for all of 2013 was performed with daily water level observation data. With an increasing number of Earth observation satellites operating in space and high-resolution mappers deployed on satellites, it will be much easier to acquire large quantities of images with very high resolutions. Therefore, the use of RFim to perform inundation simulations with high accuracy and high spatial resolutions in the future is promising because the simulation model is built on remote sensing imagery and gauging station data.

Development of Whale Optimization Neural Network for Daily Water Level Forecasting

Development of Whale Optimization Neural Network for Daily Water Level Forecasting

Performance comparison of continuous Wavelet-Fuzzy and discrete Wavelet-Fuzzy models for water level predictions at northern and southern boundary of Bosphorus

In this study, combined Discrete Wavelet Transform-Fuzzy (DWT-Fuzzy) and combined Continuous Wavelet Transform-Fuzzy (CWT-Fuzzy) models are developed for predicting the daily water levels at northern and southern boundary of Bosphorus Strait. The observed daily water level data is decomposed into spectral bands (sub-series) by using wavelet transformation as a pre-processing tool in order to achieve more accurate daily water level predictions with extended lead-times up to 7 days. The time series of daily water level data is decomposed into spectral bands, which are used as inputs into the Fuzzy model and the daily water levels are predicted from the sum of the predicted components (spectral bands). A predictive model is developed using combined DWT-Fuzzy and combined CWT-Fuzzy models to predict water level fluctuations. It is found that CWT-Fuzzy model performed better than DWT-Fuzzy and stand-alone Fuzzy models for prediction lead-times up to 7 days at northern and southern boundary of Bosphorus based on RMSE and CE evaluation criteria. It is concluded that CWT is a better pre-processing technique as it yields more accurate daily water level predictions with improved prediction lead-times than DWT.

A Complicated Karst Spring System: Identified by Karst Springs Using Water Level, Hydrogeochemical, and Isotopic Data in Jinan, China

The Jinan karst spring system, discharged by 108 springs in 2.6 km2 city center area of Jinan, China, has been suffering lower regional groundwater levels, which threatens the karst springs outflowing and aquatic ecological civilization. For better spring protection, monthly hydrogeochemical and isotopic investigations were conducted in four representative karst springs (Baotu Spring (BTQ), Heihu Spring (HHQ), Zhenzhu (ZZQ), and Wulongtan Springs (WLT)) in 2016. Results showed that the BTQ, WLT, and ZZQ had similar hydrogeochemical and isotopic behaviors, which were different with that of HHQ. By combining the daily water level data with monthly hydrogeochemical and isotopic data of BTQ and HHQ, the hydrogeological processes of the two neighboring karst springs (470 m apart) are distinguished. (a) BTQ is recharged by two sources of precipitation and river water, while HHQ is recharged mainly by precipitation. (b) Hydrogeochemical characteristics of Baotu Spring are mainly controlled by calcite, dolomite, and gypsum dissolution mixture with river water and agricultural activity, while the hydrogeochemical characteristics of Heihu Spring are mainly controlled by calcite, dolomite, and gypsum dissolution in dry season, and dilution in wet season. (c) The discharge component of both springs is storage water by diffuse flow which is pressured by new infiltration rain water. The ratio of rain water is 14% in Baotu Spring and 9% in Heihu Spring calculated by a binary mixture model. Overall, this study puts forward the standpoint that neighboring karst springs with the same geological condition, can show different hydrogeological characteristics, which is a useful evidence for understanding the heterogeneity/complexity of karst aquifers.

Impacts of anthropogenic activity on the response of water level to rainfall in the urbanized plain river network: A case study in the Hangzhou-Jiaxing-Huzhou region of Taihu Basin

太湖流域快速城镇化、水利工程等一系列人类活动对流域水文过程产生了深刻影响.本文以快速城镇化的杭嘉湖地区为例，基于1961-2014年逐日降雨、水位观测资料，构建了水位涨幅（ΔZ）、水位增长速率（k₁）和退水速率（k₂）等指标，旨在揭示变化环境下该地区降雨过程中水位的变化特征及可能的驱动因素.结果表明：1）变化环境下杭嘉湖地区近54年降雨量呈微弱的增加趋势，但降雨过程中的水位涨幅呈下降趋势，尤其是平均水位涨幅呈显著下降趋势，且于2000年左右发生明显变化；突变后水位涨幅下降主要集中在10~50 mm/d的降雨过程中，而大于50 mm/d的降雨过程中突变后水位涨幅较突变前有所升高.2）从空间分布上来看，各站降雨量与水位涨幅存在明显的空间差异，降雨量总体呈增加趋势，增加趋势东强西弱；大部分站点的水位涨幅却呈下降趋势，其中位于区域南部站点的平均水位涨幅下降趋势较东北部更为明显，水位涨幅呈显著下降站点的空间分布与杭嘉湖南排工程等水利工程的分布较为一致.3）通过对杭嘉湖地区降雨过程中水位增长速率和退水速率的变化分析发现，突变后较突变前退水速率有所提高，说明近年来水利工程等设施的完善和有序调度使得杭嘉湖地区的排洪能力有所提高，该变化可能是导致杭嘉湖地区地区突变后一定强度的降雨过程中水位涨幅下降的主要原因.而杭嘉湖地区强降雨过程中水位涨幅依然较高，可能是该地区洪峰水位居高不下的主要原因.此外，由于该地区近年来起涨水位抬升明显，对洪峰水位的抬升也有一定影响.;Rapid urbanization and human activities have a profound impact on the hydrological process in Taihu Basin. This paper constructed three indices include the water level rising (ΔZ), the rate of water level rising (k₁) and the rate of water level recession (k₂). Based on the observation data of daily rainfall and water level during 1961-2014, we try to reveal the variation characteristics of the water level and possible driving factors in the rainfall process in the Hangzhou-Jiaxing-Huzhou region. The results indicate that:(1) The rainfall shows an increasing trend, but the ΔZ shows a decreasing trend during the rainfall process. Especially, the average water level rising shows a significant decreasing trend and the abrupt change occurs in the year 2000 AD. The decreased ΔZ mainly occurs in the rainfall intensity ranged from 10 mm/d to 50 mm/d after 2000 AD. The ΔZ shows an increased trend in heavy rainfall process above 50 mm/d. (2) The rainfall in the east shows a significantly increasing trend than in the west. However, ΔZ in many stations is declining, which is more significant in the south. These changes is inseparable from the flood discharge project in the Hangzhou-Jiaxing-Huzhou region. (3) Through the analysis of the k₁ and k₂ in the rainfall process, k₂ is increased, which indicates that the development of water conservancy facilities and orderly scheduling has improved the flood discharge capacity in recent years. This change may be the main cause for the declined k₂ in a certain intensity of rainfall after 2000 AD. The ΔZ remained high in the heavy rainfall process, which can be related to that the current flood discharge capacity that cannot resist the increase of ΔZ. In addition, the incipient rising water level has increased significantly in recent years, which also makes a certain impact on the flood in the study area.

Water level characteristics of Lake Caizi, lower reaches of the Yangtze River during wintering period based on long-term hydrological alteration

湖泊生态水位过程对维持湖泊生态系统结构、过程和功能的完整性具有重要意义，也是当今湖泊科学领域面临的重要科学问题.基于菜子湖湖区水位站（车富岭水位站）1956-2018年日水位资料，采用pettitt突变检验法分析水位的突变性特征.结合年保证率法得到菜子湖车富岭水位站低水位值，并在此基础上分析了低水位发生时间及历时、候鸟越冬期水位变化速率及其生态水位的区间阈值.主要结论有：菜子湖车富岭水位站1956-2018年年均水位无显著突变.菜子湖车富岭水位站低水位发生时间均值为年内的344 d，年际标准差为27 d，低水位的年均历时为69 d，标准差为49 d，有6年（1978、1997、2015-2018年）未发生低水位事件.菜子湖候鸟越冬期水位变化速率的均值为-0.009 m/d，年均值为-0.034~0.009 m/d，日均值为-0.051~0.016 m/d.菜子湖低水位发生时间的区间阈值为332~351 d，历时的区间阈值为33~98 d，变化速率的区间阈值为-0.070~0.020 m/d.加强菜子湖候鸟越冬期湿地生境保护适应性调度试验研究及生态环境监测，为菜子湖输水水位优化控制和菜子湖湿地生态保护提供科学依据.;The ecological water level process of lakes is of great significance for maintaining the integrity of the lake ecosystem structures, processes and functions, and is also an important scientific issue of lake science field nowadays. Based on the daily water level data, pettitt test was used to analyze the abrupt change characteristics of water level of Lake Caizi at Chefuling Station from 1956-2018. The low water level of Lake Caizi at Chefuling Station was obtained using the annual guaranteed frequency method. The starting time and duration of low water level, the water level change rate during the overwintering period of migratory birds and the interval threshold of ecological water level were analyzed accordingly. The main conclusions are as follows:there is no significant abrupt change point in the average annual water level of Lake Caizi at Chefuling Station from 1956 to 2018. The average occurrence time of low water level of Lake Caizi at Chefuling Stations is day 344, with the inter-annual standard deviation 27 days. The average duration time of annual low water level is 69 days with the standard deviation 49 days. Among the calculated 63 years, there are 6 years (1978, 1997, 2015-2018) without low water level event. The average rate of water level change during the overwintering period of migratory birds is -0.009 m/d, the annual average rate is -0.034-0.009 m/d, and the daily average rate is -0.051-0.016 m/d. The interval threshold of the occurrence of low water level of Lake Caizi is 332-351 d, the interval threshold of the duration time is 33-98 d, and the interval threshold of water level change rate is -0.070-0.020 m/d. Strengthening experimental study on habitat adaptation and ecological environment monitoring during the overwintering period of migratory birds to provide scientific basis for water level regulation and wetland protection of the Lake Caizi.

The Potential Long-Term Impacts of Climate Change on the Hydrologic Regimes of North Carolina’s Coastal Plain Non-Riverine Wetlands

HighlightsBased on current emissions, mean water table decline in these wetlands will likely range from 25 to 65 cm by 2100.Projected changes could lead to a decline or loss of the important ecosystem services that wetlands provide to society.Results indicate a potential need to allocate more resources to developing strategies for managing wetlands.Abstract. Wetlands are especially at risk from climate change because of their intermediate landscape position (i.e., transition between upland and aquatic environments), where small changes in precipitation and/or evapotranspiration can have substantial impacts on wetland hydrology. Because hydrology is the primary factor influencing wetland structure and function, the important ecosystem services that wetlands provide may be altered or lost as a result of climate change. While a great deal of uncertainty is associated with the projected impacts of climate change on wetlands, hydrologic models and downscaled climate model projections provide tools to reduce this uncertainty. DRAINMOD is one such process-based hydrologic model that has been successfully adapted to simulate the daily water level fluctuations in natural wetlands. The objective of this project was to determine the range of possible impacts of climate change on the hydrologic regimes of non-riverine, non-tidal Coastal Plain wetlands in North Carolina. DRAINMOD models were calibrated and validated for two minimally disturbed, natural wetland sites using observed water table and local weather data. Two representative concentration pathway (RCP) scenarios were evaluated: RCP4.5 and RCP8.5. Nine models were selected from an ensemble of 32 climate models to represent the range of possible changes in mean precipitation and temperature. Downscaled climate projections were obtained from the U.S. Bureau of Reclamation. Simulations were run from 1986 to 2099, and results were evaluated by comparing the projected mean water table levels between the base period (1986-2015) and two future evaluation periods: 2040-2069 and 2070-2099. The model simulation results indicated that the projected mean water table level may decline by as much as 25 to 84 cm by the end of this century (2070-2099) for the RCP8.5 scenario and may decline by 4 to 61 cm for the RCP4.5 scenario. In Coastal Plain wetlands, declines in water tables can lead to the subsidence of organic soils, which can lead to the loss of stored carbon and increased risk of peat fires. Lower mean water levels can also lead to shifts in vegetation community composition and loss of habitat functions for wetland-dependent fauna. These results provide an overview of the potential impacts of climate change on North Carolina wetlands, and they provide a range of scenarios to inform and guide possible changes to water management strategies in wetland ecosystems that can be implemented now to limit the loss of ecosystem services over the long term. Keywords: Climate change, DRAINMOD, Hydrology, Modeling, North Carolina, Wetlands.

Application of the maxima distribution to the evaluation of the variability of flood risks in the Odra River basin on the basis of quarterly maxima of daily water levels

Application of the maxima distribution to the evaluation of the variability of flood risks in the Odra River basin on the basis of quarterly maxima of daily water levels

An Improved LSSVM Model for Intelligent Prediction of the Daily Water Level

Daily water level forecasting is of significant importance for the comprehensive utilization of water resources. An improved least squares support vector machine (LSSVM) model was introduced by including an extra bias error control term in the objective function. The tuning parameters were determined by the cross-validation scheme. Both conventional and improved LSSVM models were applied in the short term forecasting of the water level in the middle reaches of the Yangtze River, China. Evaluations were made with both models through metrics such as RMSE (Root Mean Squared Error), MAPE (Mean Absolute Percent Error) and index of agreement (d). More accurate forecasts were obtained although the improvement is regarded as moderate. Results indicate the capability and flexibility of LSSVM-type models in resolving time sequence problems. The improved LSSVM model is expected to provide useful water level information for the managements of hydroelectric resources in Rivers.

Water level variation characteristics under the impacts of extreme drought and the operation of the Three Gorges Dam

Under the influence of a climate of extreme drought and the Three Gorges Dam (TGD) operation, the water levels in the middle and lower reaches of the Yangtze River in 2006 and 2011 changed significantly compared with those in the extreme drought years of 1978 and 1986. To quantitatively analyze the characteristics of water level variations in 2006 and 2011, a new calculation method was proposed, and the daily water level and discharge from 1955–2016 were collected in this study. The findings are as follows: in 2006 and 2011, the water level in the dry season significantly increased, but that in the flood season obviously decreased compared with the levels in 1978 and 1986. Here, we described this phenomenon as “no low-water-level in dry season, no high-water-level in flood season”. Based on the calculation method, the contributions of climate variability and the Three Gorges Dam operation to water level variations in the middle and lower reaches of the Yangtze River were calculated, and the contributions indicated that climate variability was the main reason for the phenomenon of “no low-water-level in dry season, no high-water-level in flood season” instead of flood peak reduction in the flood season and drought runoff implementation in the dry season, which are both induced by TGD.

A model-aided satellite-altimetry-based flood forecasting system for the Mekong River

A freely accessible model-aided satellite altimeter-based daily water level forecasting system using simple regression analysis is proposed for the Mekong River with feasibility study being performed. In the Mekong Delta (MD), where Regional Flood Management and Mitigation Center (RFMMC) does not provide forecasting, ocean tides strongly impact river levels and were specifically addressed by the sum of 5-term sinusoidal function. Forecasting skills of our system are quite promising in the MD, although RFMMC's forecasting system has better skills than ours in the Mekong mainstem upstream of MD. In contrast to current operational system, our system circumvents the need of frequent altimeter samplings in the upstream by using the Variable Infiltration Capacity (VIC) macroscale hydrologic model with 0.1° resolution. The proposed forecasting system is computationally efficient without the need of complex hydrodynamic modeling, making such approach globally applicable for river basins and deltas with comparable forecasting skill and minimal computational cost.

An Attempt to Quantify the Lag Time of Hydrodynamic Action Based on the Long-Term Monitoring of a Typical Landslide, Three Gorges, China

Hydrodynamic action plays an important role in the development of reservoir bank accumulational landslides. Despite recent concern over hydrodynamic action’s hysteresis effects, there is still no unified efficient method for quantifying lag time, which is a critical input to landslide prediction and early warning systems. To address this shortcoming, we selected a typical landslide, located in Three Gorges Reservoir, China, as a case study. On the basis of long-term monitoring data, we suggest that correlation analysis may work and attempt to use linear correlation first to quantify the lag time. We conclude that, from the macroscopic behavior point of view, linear correlation analysis does not work; neither the daily reservoir water level and its variation nor the daily rainfall and its accumulation exhibit a linear relationship with the surface accumulative displacement. Future studies will use nonlinear correlation analysis to analyze data by different time segments as the hydrodynamic factors have different effects in different periods.

Dongting Lake Water Level Forecast and Its Relationship with the Three Gorges Dam Based on a Long Short-Term Memory Network

To study the Dongting Lake water level variation and its relationship with the upstream Three Gorges Dam (TGD), a deep learning method based on a Long Short-Term Memory (LSTM) network is used to establish a model that predicts the daily water levels of Dongting Lake. Seven factors are used as the input for the LSTM model and eight years of daily data (from 2003 to 2012) are used to train the model. Then, the model is applied to the test dataset (from 2011 to 2013) for forecasting and is evaluated using the root mean squared error (RMSE) and the coefficient of determination (R2). The test shows the LSTM model has better accuracy compared to the support vector machine (SVM) model. Furthermore, the model is adjusted to simulate the situation where the TGD does not exist to explore the dam’s impact. The experiment shows that the water level of Dongting Lake drops conspicuously every year from September to November during the TGD impounding period, and the water level increases mildly during dry seasons due to TGD replenishment. Additionally, the impact of the TGD results in a water level decline in Dongting Lake during flood peaks and a subsequent lagged rise. This research provides a tool for flood forecasting and offers a reference for TGD water regulation.

Recent ground deformation around lake Nasser using GPS and InSAR, Aswan, Egypt

The rate of seismic activity around lake Nasser rapidly increased after the creation of the High Dam. The largest earthquake was of magnitude ML 5.6 ; it occurred on November 14th 1981, 60 km southwest of the Aswan High Dam. We use 16 years of GPS measurements collected around the northern part of lake Nasser, represented by 27 GPS sites, plus eight years of Envisat SAR scenes, 35 descending scenes, to estimate the recent ground movement of this area. GPS and InSAR showed a land subsidence localized around lake Nasser. The subsidence has a magnitude of 1–2 mm/yr. Therefore, we model the Earth's response to water level changes, using full daily water level variations starting from 1982 to 2016. Our loading model captures a similar deformation pattern, like ones estimated from GPS and InSAR, around the lake with comparable amplitudes. With respect to stable Nubia, most of GPS sites around the lake show a negligible North to Northeast motion of <1 mm/yr. Along Kalabsha fault, we estimate a strike-slip motion with an extension component of 0.6 mm/yr. GPS sites around Sayal fault do not show any differential motion along the fault in both fault-parallel and fault-normal components. The InSAR result would not be able to capture the deformation at Kalabsha and Sayal region, since the deformation in this area is <1 mm/yr.

Deriving daily water levels from satellite altimetry and land surface temperature for sparsely gauged catchments: A case study for the Mekong River

Space borne radar altimeters often complement in-situ water levels to provide greater insights to hydrodynamic models in sparsely gauged catchments. However, 10-day or 35-day water levels derived from satellite radar altimetry are generally too infrequent for flood forecasting or hydrodynamic modelling purposes. This paper proposes a new approach to find daily water levels for areas where in-situ river heights are not available. The new approach is based on the relationship between river height and difference between daytime and night time land surface temperatures (LST). This relationship is first demonstrated using in-situ gauge data to explore appropriate statistical models to predict river height using LST differences. The approach is then applied to a number of virtual stations at the intersections between the Mekong River and the ground-tracks of Jason-2 satellite altimetry which gives 10-day water level time series.The LST difference from the thermal infrared (TIR) observations of Moderate Resolution Imaging Spectro-radiometer (MODIS) is shown to have a strong relationship with in-situ water levels and a good relationship with the Jason-2 water levels. The models included a simple linear regression model which was then extended to firstly include seasonal terms and secondly assimilate satellite altimetry data. A regression model tree (M5) was also considered but was found to be inferior to the seasonal linear model. The developed regression models were used to predict daily water levels to infill the 10-day Jason-2 altimeters. RMSE of modelled daily water levels at gauges is between 0.3 m to 0.6 m, while RMSE of modelled daily water levels without using in-situ data is higher varying from 1.4 m to 1.9 m. The temporal correlation between the modelled water levels using satellite altimeters at virtual stations and in-situ water levels at adjacent gauges ranged from 0.72 to 0.86. These results show the potential of the proposed approach to produce high temporal resolution water levels for flood models or other applications using only remotely sensed data.

Quantification of groundwater recharge and river bed clogging by daily water level measurements in a check dam

Check dams are one of the methods of managed aquifer recharge to augment groundwater storage in regions with non-perennial rivers. The objectives of this study were to quantify the groundwater recharge from a check dam in the Arani River, north of Chennai, India, and to assess the clogging of the riverbed. The water level in the check dam was measured daily for 3 years from 2010 to 2013. Other field investigations carried out include measurement of the topographic elevation of the riverbed using the differential global positioning system. Based on the water balance method, the quantity of water evaporated and recharged was estimated. A comparison of 3-year daily water level measurements indicated that there is no clogging in the riverbed during the study period, as this check dam is fitted with a sluice gate which is operated at appropriate times to flush out the sediments.

Possibility of reusing Al-Machraya River for feeding Hawizeh marsh

Al Machraya River was considered as one of the water feeders of Hawizeh Marsh. In 1986, the outlet of this river into the marsh was blocked and the river was used as a main channel for the East Tigris Irrigation Project near Kalat Salih. This causes significant decrease in the available water supply sources, deterioration in the water quality distribution patterns and increasing the stagnation areas within the marsh. This research aims to study the possibility of reusing this river for feeding Hawizeh Marsh. A frequency analysis study was carried out to study the maximum and minimum probable water level (MMPWL) of Tigris River at the upstream of Kalat Salih Barrage. Six statistical models; Normal distribution, Log-Normal type II, Log-Normal type III, Pearson type III, Log- Pearson type III and Gumbel type I distribution were used to estimate the MMPWL. The results show that Pearson type III and Gumbel type I distribution models are the best to fit the maximum and minimum daily water level (WL), respectively, at the upstream of the Barrage. The estimated MMPWL were compared to the required WL in Hawizeh Marsh. The difference between Tigris River and Hawizeh Marsh water levels were found to be not operative to cause a significant flow toward the marsh. Therefore, Al Machraya River cannot be used to feed Hawizeh Marsh.