Environmental management in Urmia Lake: thresholds approach

Urmia Lake is a vivid example of negligence in providing the environmental water requirement rooted in prolonged droughts and excessive upstream water withdrawal. The aim of this study is to propose a reclamation strategy for the lake by focusing on estimation of environmental requirement thresholds under various drought severity conditions. On the average, the lake will remain in a moderate hydrological drought condition if the business-as-usual scenario prevails. The shares of natural drought, water withdrawals and water resources development projects (i.e. dams) in recent lake inflow reduction are estimated at 45%, 40% and 15%, respectively; thus, the aggregated contribution of human-induced factors has a more significant impact on the current lake condition than that of natural drought, and a firm and consistent approach to reduce water consumption by the agricultural sector is required for lake reclamation.     

Environmental impacts of desalination on the ecology of Lake Urmia

Lake Urmia, the second largest hypersaline lake by area in the world, has fluctuated in salinity over time, but in recent years, it has reached a maximum of 340 g/L. The lake is the main habitat for the endemic Iranian brine shrimp, Artemia urmiana, and is a protected aquatic environment. Efforts have been made by the Iranian government to enhance the diversity of its wildlife. One approach has been to look for a method to reduce the salt content of the lake. We investigate the feasibility of this by first considering the water chemistry of Lake Urmia and then the various technologies used to extract salt from marine and brackish waters. Average concentrations of Na, Mg, K, Ca, Cl, SO₄, and HCO₃ were 125 g/L, 11.3 g/L, 2.63 g/L, 0.55 g/L, 216 g/L, 22.4 g/L, and 1.38 g/L, respectively, and cations and anions were balanced, However, Lake Urmia waters have a ‘very high’ salinity hazard and a high sodium adsorption ratio (SAR). Moreover, the saturation index (SI) for each of the major cations was greater than zero, indicating that the water in Lake Urmia is supersaturated, and precipitation is likely. The extraction of available salts from the lake for the use in petrochemical industries is economically feasible. However, technologies based on removing salts by distillation or reverse osmosis and then using this fresh water to dilute lake salinity are problematic. A better strategy would be better to allow more fresh water to reach the lake rather than creating fresh water through reverse osmosis and distillations processes. While concerns have been raised about the salinity tolerance of A.urmiana, it has successfully tolerated various salinity ranges from 166 to 340 g/L, and so the species is not threatened, unless the lake desiccates. Because the lake is saturated with salts, it seems unlikely that salinity could increase much higher.     

Reconstruction of Hydrometeorological Data in Lake Urmia Basin by Frequency Domain Analysis Using Additive Decomposition

Water Resources Management - Frequency domain analysis using an additive decomposition method is proposed to reconstruct the missing hydrometeorological data of selected sites in Lake Urmia basin...     

Spatio-Temporal Analysis of Regional Trends and Shift Changes of Autocorrelated Temperature Series in Urmia Lake Basin

Recently, the Urmia Lake located in northwestern Iran which is the second largest hyper saline in the world suffers from the significant fluctuations of water level and surface area. The current study tries to investigate the spatiotemporal trends of mean (T_mean), maximum (T_max) and minimum (T_min) temperatures of monthly, seasonal and annual time-series. To do so, the data of 15 temperature gauge stations within the Urmia Lake basin, for the period 1972–2011 was employed. The pre-whitening approach was applied to remove the effects of serial correlation in the air temperature series based on the Mann-Kendall (MK) test. The results of Ljung-Box test showed positive serial correlation in the T_mean and T_max series for all of the stations at the 0.05 significance level. In the monthly series, the significant warming trends in the T_mean series were more perceptible than the same ones in T_max series; however, T_max trend was found more than T_min series. The Mann–Whitney (MW) test detected a significance upward shift changes in the annual T_mean, T_max and T_min series of about 86, 73 and 80 % of the stations, respectively. The average magnitude of significant warming trends in annual T_mean, T_max and T_min series were (+) 0.58 °C, (+) 0.52 °C and (+) 0.69 °C per decade, respectively. Furthermore, the interpolation maps showed that warming trends in the east and west of Urmia Lake were more than southern area. Therefore, the results showed that the basin has suffered from increasing trends in the T_mean, T_max and T_min over the recent decades. Finally, significant changes were found in 1980s and 1990s based on the Mann-Kendall ranks and change point tests. In this study, it is interesting that the period of significant changes in warming trends were close to the beginning of decreasing water level of the Lake.     

Coupled water and salt balance models for Lake Urmia: Salt precipitation and dissolution effects

Investigating the dynamic evolution of storage volume and salinity of Lake Urmia (LU), which is crucial to present more reliable estimations of water balance components, needs to be furthur studied. We aimed to fill this gap by developing a coupled lumped mathematical model that considered the two-way effect of salt and water balance components on each other. Through the coupled water and salt balance model, salt precipitation and dissolution components were incorporated, and vaporation was calculated dynamically based on the lake’s salinity. The final model was then used as a tool to estimate the groundwater flux. Results indicated that during the lake shrinkage period (2009–2015), substantial salt precipitation with an average rate of 6.79 g/100 g/year (6.79 g of salt per 100 g water per year) occurred. In this period, the lake’s salinity increased to more than 450 g/l, and a negative trend of −0.200 km³/year in evaporation was detected. From 2016 to 2019, LU’s water level rose, and although great salt dissolution with an average rate of 4.27 g/100 g/year occurred, the lake’s salinity decreased. In 2019, with the least lake's salinity values (annual average of 266.1 g/l), the evaporation rate was 1.45 times greater than the average evaporation rate through the rest of the simulation period. While LU’s connection with groundwater resources varied temporally, the average groundwater flux (-0.203 km³/year) was higher than it could be neglected. Results of this study are expected to enhance the understanding of LU crisis and to improve the plan to prevent further shrinkage of the lake.     

Prediction of Water Level using Monthly Lagged Data in Lake Urmia,Iran

Water Resources Management - Prediction of water level fluctuations in lakes is a necessary task in hydrological and limnological studies. Lake Urmia, a hyper-saline lake in the North Western part...     

Investigation Anthropogenic Impacts and Climate Factors on Drying up of Urmia Lake using Water Budget and Drought Analysis

The water level of Urmia Lake, the largest inland lake in Iran with maximum water surface area of about 6000 km², has been shrinking for the last two decades. Although a number of study have been performed to determine drought condition and coastline changes of Urmia Lake, there has not been a detailed study to distinguish anthropogenic effects from climate impacts on the drying of Urmia Lake. In this study, water budget of Urmia Lake and the intensity of drought in the basin were analyzed in the period from 1985 to 2010 and a new hypothesis is proposed to quantify anthropogenic and climate impacts in reducing the volume of Urmia Lake. The results of this study indicate that human impacts on the Lake and its basin are more important than climate factors. Though previous studies assumed that ground water output from Urmia Lake is negligible, the results of this study show the presence of significant groundwater seepage from Urmia Lake. Major changes in the variables that reduced the water level of Urmia Lake were observed since 1998. Anthropogenic impacts and climate factors have roughly 80% and 20% effects on the drying up of Urmia Lake, respectively. Hence, the first step to recover Urmia Lake could be the revision of management surface water, operation of dams and groundwater resources. The second step could be the review and classification of agricultural products grown in the region in terms of water consumption and teach local people the best practice methods for irrigation.     

东平湖水体环境容量分析

东平湖是山东省第二大淡水湖,具有防洪、调蓄、灌溉、生态保护等多种功能。应用狄尤模型对东平湖水环境容量进行了计算,并结合总磷、总氮现状污染负荷量,分别计算了其削减量和削减率。结果表明:东平湖总磷、总氮的现状污染负荷量大于目标要求的水环境容量,为了达到水环境保护的目标,需要削减排入东平湖的总磷、总氮;东平湖的主要污染指标为总氮,在农业生产中需要合理施肥。     

Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach

Predicting the dynamics of water-level in lakes plays a vital role in navigation, water resources planning and catchment management. In this paper, the Extreme Learning Machine (ELM) approach was used to predict the daily water-level in the Urmia Lake. Daily water-level data from the Urmia Lake in northwest of Iran were used to train, test and validate the employed models. Results showed that the ELM approach can accurately forecast the water-level in the Urmia Lake. Outcomes from the ELM model were also compared with those of genetic programming (GP) and artificial neural networks (ANNs). It was found that the ELM technique outperforms GP and ANN in predicting water-level in the Urmia Lake. It also can learn the relation between the water-level and its influential variables much faster than the GP and ANN. Overall, the results show that the ELM approach can be used to predict dynamics of water-level in lakes.     

博斯腾湖水环境污染成因分析

博斯腾湖曾是我国最大的吞吐内陆淡水湖。随着工农业的迅猛发展和人口数量不断上升,目前博斯腾湖处于"淡水-微咸"转换期湖泊,IV类水质的"贫-中富营养湖泊",其水环境状况不容乐观。从湖泊面积、咸化程度、入湖河流水质、湖滨湿地等4个方面阐述了湖体水环境的变化趋势,并提出相应治理措施,以期对制定健全的法规监管体系、提出合理有效的水环境综合治理方案提供参考。     

Satellite based lake bed elevation model of Lake Urmia using time series of Landsat imagery

This study presents a lake bed elevation model of Lake Urmia. In the course of model generation, a time series of the extent of the lake surface was derived from 129 satellite images with different acquisition dates based on the Landsat sensors Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI). Due to the rapid shrinking of the lake during the last two decades, lake surface areas ranging from 890 km² to 6125 km² could be covered. The water edge of the various lake extents was then linked to the observed water level on the day of the satellite image acquisition. The resulting contour lines, covering water levels between 1270.04 m and 1278.42 m a.s.l. and thus representing the lakebed morphology in its shallow parts, were merged with existing data (deeper parts) and interpolated to generate a lake bed elevation model. Finally, Lake Urmia’s Level-Area-Volume relationships were derived from the lake bed elevation model and compared to bathymetric data previously published.     

Potential Strategies for Recovery of Lake Whitefish and Lake Herring Stocks in Eastern Lake Erie

Lake Erie sustained large populations of ciscoes (Salmonidae: Coregoninae) 120 years ago. By the end of the 19^th century, abundance of lake whitefish (Coregonus clupeaformis) had declined drastically. By 1925, the lake herring (a cisco) population (Coregonus artedii) had collapsed, although a limited lake herring fishery persisted in the eastern basin until the 1950s. In the latter part of the 20^th century, the composition of the fish community changed as oligotrophication proceeded. Since 1984, a limited recovery of lake whitefish has occurred, however no recovery was evident for lake herring. Current ecological conditions in Lake Erie probably will not inhibit recovery of the coregonine species. Recovery of walleye (Sander vitreus) and efforts to rehabilitate the native lake trout (Salvelinus namaycush) in Lake Erie will probably assist recovery because these piscivores reduce populations of alewife (Alosa psuedoharengus) and rainbow smelt (Osmerus mordax), which inhibit reproductive success of coregonines. Although there are considerable spawning substrates available to coregonine species in eastern Lake Erie, eggs and fry would probably be displaced by storm surge from most shoals. Site selection for stocking or seeding of eggs should consider the reproductive life cycle of the stocked fish and suitable protection from storm events. Two potential sites in the eastern basin have been identified. Recommended management rocedures, including commercial fisheries, are suggested to assist in recovery. Stocking in the eastern basin of Lake Erie is recommended for both species, as conditions are adequate and the native spawning population in the eastern basin is low. For lake herring, consideration should be given to match ecophenotypes as much as possible. Egg seeding is recommended. Egg seeding of lake whitefish should be considered initially, with fingerling or yearling stocking suggested if unsuccessful. Spawning stocks of whitefish in the western basin of Lake Erie could be utilized.     

Prediction of Urmia Lake Water-Level Fluctuations by Using Analytical, Linear Statistic and Intelligent Methods

Undoubtedly, the most significant factor with wise decision making and designing hydrological structures along the lake coasts is an accurate model of lake level changes. This issue becomes more and more important as recent global climate changes have completely reformed the behavior of traditional lake level fluctuations. Subsequently, estimating lake levels becomes more important and at the same time more difficult. This paper deals with modeling lake level changes of Lake Urmia located in north-west of Iran, in terms of both simulator and predictor models. According to this, two traditional simulator models based on water budget are developed which benefit from most effective components on water budget namely precipitation, evaporation, inflow and the lake level antecedents, as model inputs. Most famous linear modeling tools, Autoregressive with exogenous input (ARX) and Box-Jenkins (BJ) models are employed with the same mentioned inputs for prediction purpose. In addition, two other methods that are, Multi-Layer Perceptron (MLP) neural network and also Local Linear Neuro-Fuzzy (LLNF) are applied to investigate capability of intelligent nonlinear methods for lake level changes prediction. All models performances are indicated using both graph and numerical illustrations and results are discussed. Comparative results reveal that the intelligent methods are superior to traditional models for modeling lake level behavior as complex hydrological phenomena.     

Estimating the Ungauged Natural Flow Regimes for Environmental Flow Management

Regime-based approach recently becomes an important strategy while considering aquatic ecosystems in environmental flow management. The key element for supporting this strategy is long streamflow data which is usually not available for determining natural flow regimes. This study uses a back-propagation network to estimate ungauged natural flow regimes. A set of the upper reaches of Taiwan’s 42 flow stations with non-human control streamflow and at least 20 years daily flow data is used to quantify the natural flow regimes using 31 Indicators of Hydrologic Alteration (IHA). Watershed geomorphologic characteristic factors and rainfall parameters are used to classify homogeneous flow regime areas. The results show that there are three types of flow regimes from the flow stations, and each group of indicators in the IHA has different correlations with different geomorphologic characteristic factors and rainfall parameters. The results of using an artificial neural network model to estimate IHA show that the group average percent error fell from 21 % to 8 % and the average correlation coefficient was over 0.7, indicating that the model presented in this study is able to accurately estimate the natural flow regime in ungauged stations. Instead of predicting daily streamflow, this study estimates indicator values for ease of ecological water resources management.     

Evaluation of dike-type causeway impacts on the flow and salinity regimes in Urmia Lake,Iran

Urmia Lake, located in a closed basin in north-west Iran, is the largest lake (5000–6000 km²) in the Middle East. It is very saline with total dissolved salts reaching 200 g/l compared with a normal seawater salinity of about 35 g/l. The construction of a causeway, which was initiated in 1979 but then abandoned until the early 2000s, is near completion and will provide road access between the western and eastern provinces. The causeway has an opening 1.25 km long and divides Urmia Lake into a northern and southern basin and restricts water exchange. The flow and salinity regimes are affected by the presence of this new causeway, and there are concerns over the well being of the Artemia population. This study investigates the effects of the construction of the causeway on flow and salinity regimes, considers remedial actions, and examines the effects of climatic variability on salinity and flow. Flow and salinity regimes were numerically simulated by using a commercially available two and three-dimensional (2D and 3D) MIKE model. The validity of the numerical model was assessed through sensitivity analysis of the model and comparing the simulated results against field measurements; the 3D model provided the higher correlation between simulated and actual data. Wind input was the main climatic and hydrologic factor influencing flow regime while river discharge, evaporation and rainfall were the key parameters affecting salinity distribution in the lake models. The 3D model was subsequently used to predict lake conditions in typical dry, wet and normal climates, to examine the environmental impacts from the new causeway, and to evaluate possible improvements that some remedial measures may provide.     

强化管理意识规范水利资金的使用

水利作为国家重要的基础性行业,国家历来十分重视,投入大量的资金用于水利的建设,特别是1998年大水之后,国家采取积极的财政政策,发行国债加强基础设施建设,水利投资成倍增加。如何管好、用好水利资金,使之发挥更大的效益,是一项十分重要的工作。     

再论洪泽湖的治理与改造

洪泽湖是我国第四大淡水湖，是一典型的过水性湖泊，无论是洪水（水灾）或是枯水（旱灾）均应当引起同等重要的关注，泄与蓄要兼顾兼施，必须从资源水利的角度来审视和研讨洪泽湖的治理和改造，因此，开辟了海水道是治理淮河与洪泽湖的根本举措，蓄泄兼施，淮水在湖外分流；清淤掘底，增加蓄水量；整治湖口，淮河洪水畅流入湖，防治污染，保护水环境。     

跨流域调水对恢复白洋淀生态环境重要性分析

近几十年来,由于气候变化和和人类活动的影响,白洋淀入淀水量逐年减少,造成多次干淀现象。水利部和河北省先后组织多次本流域调水和外流域调水,以缓解白洋淀供水不足的问题。通过对白洋淀供水水源与耗水量分析,为保护和恢复白洋淀生态环境,跨流域调水是一项重要措施。南水北调中线工程总干渠通水后,将能实现引江水补淀,从根本上解决白洋淀生态环境危机。     

洞庭湖区综合治理战略及对策

洞庭湖地处长江中游,天然湖白面积2625km2,比新中国成立初期的4350km2减少近40%,是我国最大的调蓄湖泊,担负着调蓄长江和湘、资、沅、澧四水洪水的重要任务,每年蓄调长江洪水约30%～40%.湖区是我国重要的农产品基地.     

城市湖泊生态修复及水生植物群落构建研究进展

介绍了经典的湖泊生态修复理论在国内外的应用及发展现状,并总结了在该理论指导下实施城市湖泊生态修复过程中,内源及外源性营养盐、光照、浮游植物、底泥、生物扰动等因子对水生植物群落恢复的影响,及其应对策略。针对外源性点源、面源污染多的问题,通过修建污水管网以及人工湿地等水利设施进行控制;内源性污染如底泥,则可采用原位以及异位等处理技术进行控制;对水质产生较大影响的浮游植物可采用物理、化学、生物-生态学方法进行调控;人类干扰、鱼类牧食及其他水生动物、浮游植物等综合作用共同影响水生植物生长、分布。因此,在利用水生植物修复湖泊水体时,必须综合考虑多方面生态因子对其所造成的影响。