Results of Seepage Meter and Mini-Piezometer Study, Lake Mead, Nevada

The seepage meter and the mini-piezometer were utilized in an attempt to evaluate ground-water reservoir interactions over a 12-month period at Echo Bay in Lake Mead. In conjunction with these techniques three standard piezometers, refraction seismic data, and water chemistry data were utilized to interpret seepage device results. During a four-month period, from December 1979 to March 1980, an 8 ft (2.5 m) rise in reservoir stage, the reservoir contributed water to Echo Wash bank storage at rates of up to 0.29 gpd/ft² (12 lpd/m²). Ground-water discharge occurred for the remainder of the project, during a stage decline from April 1980 to May 1980, a rise in June 1980, and leveling off and slight decline for the remainder of the year, July 1980 to December 1980. The maximum seepage meter ground-water discharge rate of 3.0 gpd/ft² (122 lpd/m²) was recorded in December 1980. Seepage meter water chemistry data for June were similar to Lake Mead water chemistry and were interpreted to be previously recharged Lake Mead water. September water chemistry data showed two possible components of ground-water discharge, a high SpC calcium sulfate Echo Wash ground water and a lower SpC Lake Mead recharged bank storage water. December ground-water chemistry data showed discharge to be a high SpC calcium sulfate water similar to Echo Wash ground-water quality which was apparently unaffected by Lake Mead inflow. Mini-piezometer data were collected at each seepage meter site. However, these data usually did not provide correlative results with seepage meter data probably because of suspended sediment in the piezometer water column and plugging of the perforated tip. Seepage meters were successfully utilized to characterize reservoir ground-water interaction in Echo Bay.     

极端干旱事件中洞庭湖水面变化过程及成因

干旱是洞庭湖区长期以来面临的严重自然灾害之一,给周边人们的生产生活造成了极大的影响.针对2006和2011年洞庭湖区发生的极端干旱事件,借助遥感影像大范围、时空连续的优势,结合湖区水文气象等观测资料,从时空两方面阐释了洞庭湖在典型干旱年份水域分布及变化过程,进一步从温度、降水、径流以及蓄水量等方面对比分析不同干旱事件发生、发展过程的一致性和差异性.研究结果表明:2006年干旱大致从7月开始,至12月结束.水面淹没范围由湖心向周边扩展,到7月达到最大值,8月提前进入枯水期,减小范围主要集中在东洞庭湖外围和南洞庭湖的北边.2006年干旱属于由入湖径流减少主导的水文干旱事件;2011年的干旱则从4月开始,至11月结束,在9月以后干旱继续加重.水面淹没范围在6月急剧增大且一直到8月都维持在较高的水平,涨水期水面由中心向四周淹没,退水期水面变化范围与涨水期相反.2011年干旱是由流域降水减少引起的水文和气象干旱事件.研究结果揭示了洞庭湖区干旱成因的多样性和复杂性,对于制定科学合理的干旱灾害防范措施,减缓区域的生态环境问题等具有一定的指导和借鉴意义.     

1986-2017年太湖出、入湖水量变化分析

作为流域内水资源调蓄和调度的中枢,太湖的出、入湖水量格局随着一系列工程、非工程措施的实施已然改变.基于1986-2017年近30年的环湖出、入湖水量资料,采用Mann-Kendall趋势检验法、突变检验法和滑动t检验法,对环湖及地区出、入湖水量变化进行了定性、定量研究,并讨论了产生变化的可能原因.结果表明:1986-2017年,环湖年入湖水量增加趋势显著,在20世纪90年代后期突变增加,年出湖水量增加趋势显著,在21世纪初后期突变增加;多年平均年入湖总量突变后较突变前增加了29.66亿m3,多年平均年出湖总量增加了18.63亿m3;江苏入湖水量增长率、增长贡献率分别为53%和84%,出湖水量增长率、增长贡献率分别为31%和48%;浙江入湖水量增长率、增长贡献率无明显改变,出湖水量增长率、增长贡献率分别为26%和31%;望虞河出入湖增长率最大,但增长贡献率不大;太浦河出湖增长率、增长贡献率无明显变化;出、入湖水量的变化抬升了太湖年平均水位和年最低水位,对年最高水位影响较小;水利工程调度对出、入湖水量的影响逐渐占据主导作用.     

Analysis of river runoff in the Poyang Lake Basin of China: long-term changes and influencing factors

An analysis of the variation characteristics and evolutionary trends in the runoff of five rivers in the Poyang Lake Basin was conducted using the MK trend test, Morlet wavelet transforms, correlation analyses, and other methods. For 1956–2011, the inflow runoff displays small, statistically insignificant trends. However, for 2000–2011, significant downward trends are present. River runoff in the basin is significantly correlated with precipitation, while water intake and use is less influential; the most significant impact on river runoff is climate variability. To analyse the effects of water conservancy project scheduling and operation, we also compare the inflow and outflow runoff processes of typical large reservoirs before and after peak reservoir construction. The scheduling and operation of large reservoirs in the five rivers is known to play a supplementary role in dry season inflow runoff. The recent reduction in inflow runoff was mainly caused by basin precipitation; reasonable scheduling of water conservancy projects in the five rivers plays a positive role in safeguarding the water required by the dry season ecosystem in Poyang Lake.     

环太湖各水资源分区入出湖河流总磷浓度与负荷变化分析

入出湖总磷负荷变化是影响太湖湖体磷收支平衡的关键因素.基于2012-2018年水质水量监测资料,计算全湖及各水资源分区河流入出湖总磷负荷,并以水量加权计算其总磷年平均浓度,探明其时空变化规律;运用双累积曲线法分析不同分区水污关系的变化规律;以月为时间尺度,利用Pearson相关系数,揭示入湖总磷负荷分别与入湖水量、入湖...     

Revisiting hydrological drought propagation and recovery considering water quantity and quality

Climate extremes, in particular droughts, are significant driving forces towards riverine ecosystem disturbance. Drought impacts on stream ecosystems include losses that can be either direct (e.g., destruction of habitat for aquatic species) or indirect (e.g., deterioration of water quality, soil quality, and increased chance of wildfires). This paper combines hydrologic drought and water quality changes during droughts and represents a multistage framework to detect and characterize hydrological droughts while considering water quality parameters. This method is applied to 52 streamflow stations in the state of California, USA, over the study period of 1950–2010. The framework is assessed and validated based on two drought events declared by the state in 2002 and 2008. Results show that there are two opposite drought propagation patterns in northern and southern California. In general, northern California indicates more frequent droughts with shorter time to recover. Chronology of drought shows that stations located in southern California have not followed a specific pattern but they experienced longer drought episodes with prolonged drought recovery. When considering water quality, results show that droughts either deteriorate or enhance water systems, depending on the parameter of interest. Undesirable changes (e.g., increased temperature and decreased dissolved oxygen) are observed during droughts. In contrast, decreased turbidity is detected in rivers during drought episodes, which is desirable in water systems. Nevertheless, water quality deteriorates during drought recovery, even after drought termination. Depending on climatic and streamflow characteristics of the watersheds, it was found that it would take nearly 2 months on average for water quality to recover after drought termination.     

Evaluation, modification, and application of the Effective Drought Index to 200-Year drought climatology of Seoul, Korea

In this paper, progressive methods for assessing drought severity from diverse points of view were conceived. To select a fundamental drought index, the performances of the Effective Drought Index (EDI) and 1-, 3-, 6-, 9-, 12-, and 24-month Standardized Precipitation Indices (SPIs) were compared for drought monitoring data accumulated over 200-year period from 1807 to 2006 for Seoul, Korea. The results confirmed that the EDI was more efficient than the SPIs in assessing both short and long-term droughts.We then proposed the following methods for modifying and supplementing the EDI: (1) CEDI, a corrected EDI that considers the rapid runoff of water resources after heavy rainfall; (2) AEDI, an accumulated EDI that considers the drought severity and duration of individual drought events; and (3) YAEDI, a year-accumulated negative EDI representing annual drought severity. In addition to these indices, to more accurately measure and diagnose droughts, we proposed the utilization of (4) the Available Water Resources Index (AWRI), an existing index that expresses the actual amount of available water.Using the improved methods above, we assessed and summarized important droughts that have occurred in Seoul over the 200 years from 1807 to 2006.     

Stage level,volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods

Lake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.     

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

Drought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.     

Joint probability of precipitation and reservoir storage for drought estimation in the headwater basin of the Huaihe River,China

Reservoir storage plays an important role in water supply during the dry season when precipitation is insufficient. In a watershed where the streams are controlled by reservoirs, drought occurrences depend on not only precipitation variations but also reservoir regulation. In this study, the joint dependence structure of the reservoir storage and its relevant variables of precipitation and/or upstream outflow were analyzed for two cascade reservoirs in a headwater basin of the Huaihe River, China. Correlation analysis indicates that the reservoir storage in October (the end of the wet season) depends highly on the regional precipitation at time scales of several months, e.g., 7 months for the upstream and 9 months for the downstream. Additionally, the downstream storage is correlated with outflow from the upstream reservoir at the 5-month timescale significantly. For estimation of the joint probability of pairs of the storage and its relevant variables, univariate marginal distributions and bivariate copula were appropriately selected in terms of statistical tests. The bivariate return period of \(T(X < x,Y < y)\) and \(T(X \le x,Y \ge y)\) and the conditional probability of \(P(Y \ge y|X \le x)\) were estimated by using the selected Clayton copula. The results from contour lines of the bivariate return period demonstrate that the probability of drought occurrences affected by both reservoir storage and precipitation/outflow is smaller than that by either of the variables. Meanwhile, the concurrent drought probability between precipitation and reservoir storage in the upstream is higher than that in the downstream. The estimated conditional probability offers useful information on how much the regular storage could be remained under some specified drought levels of precipitation/upstream outflow. Therefore, the results are helpful for improving the operation strategies of the cascade reservoirs for the adaptive management of drought under different climate variations.     

Monitoring the water balance of Lake Victoria, East Africa, from space

Using satellite gravimetric and altimetric data, we examine trends in water storage and lake levels of multiple lakes in the Great Rift Valley region of East Africa for the years 2003–2008. GRACE total water storage estimates reveal that water storage declined in much of East Africa, by as much as , while altimetric data show that lake levels in some large lakes dropped by as much as 1–2 m. The largest declines occurred in Lake Victoria, the Earth’s second largest freshwater body. Because the discharge from the outlet of Lake Victoria is used to generate hydroelectric power, the role of human management in the lake’s decline has been questioned. By comparing catchment water storage trends to lake level trends, we confirm that climatic forcing explains only about 50decline. This analysis provides an independent means of assessing the relative impacts of climate and human management on the water balance of Lake Victoria that does not depend on observations of dam discharge, which may not be publically available. In the second part of the study, the individual components of the lake water balance are estimated. Satellite estimates of changes in lake level, precipitation, and evaporation are used with observed lake discharge to develop a parameterization for estimating subsurface inflows due to changes in groundwater storage estimated from satellite gravimetry. At seasonal timescales, this approach provides closure to Lake Victoria’s water balance to within . The third part of this study uses the water balance of a downstream water body, Lake Kyoga, to estimate the outflow from Lake Victoria remotely. Because Lake Kyoga is roughly 20 times smaller in area than Lake Victoria, its water balance is strongly influenced by inflow from Lake Victoria. Lake Kyoga has been shown to act as a linear reservoir, where its outflow is proportional to the height of the lake. This model can be used with satellite altimetric lake levels to estimate a time series of Lake Victoria discharge with an rms error of about .     

ANALYSIS OF AN ISOLATED STORM EVENT HYDROGRAPH BY IDENTIFYING THE INFLOW SEQUENCE TO A NON-LINEAR CONCEPTUAL RESERVOIR

In an isolated storm event model relating gross rainfall to the flow hydrograph, the shape transformation component can be composed of a number of subsystems. It is assumed here that this component contains, along with other subsystems, a non-linear conceptual reservoir expressed in general terms. Given an isolated storm event, a procedure is described that directly identifies the particular inflow sequence that needs to be applied to this reservoir to reproduce the observed discharge hydrograph as outflow. This procedure makes use of information contained only in the observed hydrograph and does not rely on prior knowledge of the gross or net rainfall hyetographs. Nor is it necessary to identify in full the storage–outflow relation of the non-linear reservoir used. Future comparisons between the gross rainfall hyetograph and the identified inflow sequence should be facilitated by the procedure's ability to remove the long trailing recession belonging to the outflow.     

Drought impacts on water quality and potential implications for agricultural production in the Maipo River Basin,Central Chile

ABSTRACT

Droughts can have serious negative impacts on the water quality needed for irrigated agriculture. The Metropolitan region of Chile is a relevant producer of high-value crops and is prone to droughts. Standardized Drought Indices were used to characterize meteorological and hydrological droughts for the period from 1985 to 2015. To understand the relationship between droughts and water quality, we evaluated the correlations between daily discharge and surface water quality observations. The threshold level method was used to compare physicochemical parameters during hydrological drought periods with the Chilean water quality thresholds for agricultural uses. A significant (p < 0.05) negative relationship between discharge and electrical conductivity and major ions was found in most of the basin. Hydrological stations located in irrigation districts exceeded the official thresholds for these parameters during hydrological drought periods seriously threatening irrigated agriculture of the region.     

Improving drought predictability in Arkansas using the ensemble PDSI forecast technique

Drought prediction is important for improved water resources management and agriculture planning. Although Arkansas has suffered severe droughts and economic loss in recent years, no significant study has been done. This study proposes a local nonparametric autoregressive model with designed stochastic residual-resampling approach to produce ensemble drought forecasts with associated confidence. The proposed model utilizes historical climate records, including drought indices, temperature, and precipitation to improve the quality of the short-term forecast of drought indices. Monthly forecasts of Palmer Drought Severity Index (PDSI) in Arkansas climate divisions show remarkable skills with 2–3 month lead-time based on selected performance measure such as, Normalized Root Mean Square Error (NRMSE) and the Kuiper Skill Score (KSS). Rank histograms also show that the model captures the natural variability very well in the produced drought forecasts. The incorporation of categorical long-term precipitation prediction significantly enhances the performance of the monthly drought forecasts.     

Reducing uncertainty in stochastic streamflow generation and reservoir sizing by combining observed,reconstructed and projected streamflow

Reservoir sizing is one of the most important aspects of water resources engineering as the storage in a reservoir must be sufficient to supply water during extended droughts. Typically, observed streamflow is used to stochastically generate multiple realizations of streamflow to estimate the required storage based on the Sequent Peak Algorithm (SQP). The main limitation in this approach is that the parameters of the stochastic model are purely derived from the observed record (limited to less than 80 years of data) which does not have information related to prehistoric droughts. Further, reservoir sizing is typically estimated to meet future increase in water demand, and there is no guarantee that future streamflow over the planning period will be representative of past streamflow records. In this context, reconstructed streamflow records, usually estimated based on tree ring chronologies, provide better estimates of prehistoric droughts, and future streamflow records over the planning period could be obtained from general circulation models (GCMs) which provide 30 year near-term climate change projections. In this study, we developed paleo streamflow records and future streamflow records for 30 years are obtained by forcing the projected precipitation and temperature from the GCMs over a lumped watershed model. We propose combining observed, reconstructed and projected streamflows to generate synthetic streamflow records using a Bayesian framework that provides the posterior distribution of reservoir storage estimates. The performance of the Bayesian framework is compared to a traditional stochastic streamflow generation approach. Findings based on the split-sample validation show that the Bayesian approach yielded generated streamflow traces more representative of future streamflow conditions than the traditional stochastic approach thereby, reducing uncertainty on storage estimates corresponding to higher reliabilities. Potential strategies for improving future streamflow projections and its utility in reservoir sizing and capacity expansion projects are also discussed.     

A multiscale investigation of ground water flow at Clear Lake, Iowa

Ground water flow was investigated at Clear Lake, a 1468-ha glacial lake in north-central Iowa, as part of a comprehensive water quality study. A multiscale approach, consisting of seepage meters (and a potentiomanometer), Darcy's law, and an analytic element (AE) model, was used to estimate ground water inflow to and outflow from the lake. Estimates from the three methods disagreed. Seepage meters recorded a median-specific discharge of 0.25 mum/s, which produced a lake inflow rate between 90,750 and 138,200 m3/d, but no detectable outflow. A wave-induced Bernoulli effect probably compromised both inflow and outflow measurements. Darcy's law was applied to 11 zones around the lake, producing inflow and outflow values of 10,500 and 5000 m3/d, respectively. The AE model, GFLOW, coupled with the parameter estimation model, UCODE, simulated ground water flow in a 700-km2 region using 31 hydraulic head and base flow measurements as calibration targets. The model produced ground water inflow and outflow rates of 14,300 and 9200 m3/d, respectively. Although not a substitute for field data, the model's ability to simulate ground water flow to the lake and the region, estimate uncertainty for model parameters, and calculate a lake stage and associated lake water balance makes it a powerful tool for water quality management and an attractive alternative to the traditional methods of ground water/lake investigation.     

2009年环太湖入出湖河流水量及污染负荷通量

通过对2009年环太湖水文巡测及同步水质监测数据整理,得到2009年环太湖河流入出湖水量以及污染负荷,并将之与前期文献资料数据进行对比.结果表明,2009年环太湖河道入出湖水量分别为88.40×108 m3、93.27×108m3.入湖水量超过5×108m3的依次为陈东港、大浦港、梁溪河、太滆运河、望虞河.出湖水量最大...     

Management of an aquifer with artificial recharge using water balance

Abstract

This study considers the management of an aquifer with artificial recharge whose water resources are mainly used for irrigation and where the irrigation return flows and natural discharge are considerable. These two variables are dependent on the use and increase of water resources. The interaction between some inflow and outflow variables is taken into account in the computation of the actual volume of water available, there being a pre-established artificial recharge of the aquifer. Conversely, the artificial recharge for a given water demand may be calculated. The most important inflow and outflow variables are used in an equation system (the water balance for each period of time) for these interactions and the total inflow and outflow. An iterative procedure is developed that solves the equation and with it the computation of the actual availability of water and storage.     

Modelling lake stage and water balance of Lake Tana,Ethiopia

The level of Lake Tana, Ethiopia, fluctuates annually and seasonally following the patterns of changes in precipitation. In this study, a mass balance approach is used to estimate the hydrological balance of the lake. Water influx from four major rivers, subsurface inflow from the floodplains, precipitation, outflow from the lake constituting river discharge and evapotranspiration from the lake are analysed on monthly and annual bases. Spatial interpolation of precipitation using rain gauge data was conducted using kriging. Outflow from the lake was identified as the evaporation from the lake's surface as well as discharge at the outlet where the Blue Nile commences. Groundwater inflow is estimated using MODular three‐dimensional finite‐difference ground‐water FLOW model software that showed an aligned flow pattern to the river channels. The groundwater outflow is considered negligible based on the secondary sources that confirmed the absence of lake water geochemical mixing outside of the basin. Evaporation is estimated using Penman's, Meyer's and Thornwaite's methods to compare the mass balance and energy balance approaches. Meteorological data, satellite images and temperature perturbation simulations from Global Historical Climate Network of National Oceanographic and Atmospheric Administration are employed for estimation of evaporation input parameters. The difference of the inflow and outflow was taken as storage in depth and compared with the measured water level fluctuations. The study has shown that the monthly and annually calculated lake level replicates the observed values with root mean square error value of 0·17 and 0·15 m, respectively. Copyright © 2009 John Wiley & Sons, Ltd.     

Drought forecasting using stochastic models

Drought is a global phenomenon that occurs virtually in all landscapes causing significant damage both in natural environment and in human lives. Due to the random nature of contributing factors, occurrence and severity of droughts can be treated as stochastic in nature. Early indication of possible drought can help to set out drought mitigation strategies and measures in advance. Therefore drought forecasting plays an important role in the planning and management of water resource systems. In this study, linear stochastic models known as ARIMA and multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to forecast droughts based on the procedure of model development. The models were applied to forecast droughts using standardized precipitation index (SPI) series in the Kansabati river basin in India, which lies in the Purulia district of West Bengal state in eastern India. The predicted results using the best models were compared with the observed data. The predicted results show reasonably good agreement with the actual data, 1–2 months ahead. The predicted value decreases with increase in lead-time. So the models can be used to forecast droughts up to 2 months of lead-time with reasonably accuracy.