Determining the causes for the dramatic recent fall of Lake Prespa (southwest Balkans)

Mediterranean lake–wetland systems are threatened by climate change and intensive human impacts. Individual lake responses to these threats are poorly known but urgently required to steer preservation strategies. The dramatic water-level fall (~8 m since 1987) of Lake Megali Prespa endangers this global biodiversity hotspot and the wider catchment’s water resources. Annual lake fluctuations are found to be strongly related to wet-season (Oct.–Apr.) precipitation variability, which is linked to the North Atlantic Oscillation. The lake primarily adjusts to sustained inflow changes through amending surface evaporation. Cumulative water abstraction since 1951 (~19 × 10⁶ m³/year: ~0.006% of lake volume) explains ~70% of the long-term decrease in surface evaporation; climate variability explains the remainder. Persistent low lake levels after 1995 are caused by water abstraction. Compared to 1952/53–1977/78, the period 1978/79–2003/04 experienced significant decreases in wet-season precipitation, snowfall and discharge; the number of very dry years increased.

EDITOR A. Castellarin; ASSOCIATE EDITOR D. Gerten     

Characterizing replenishment water,lake water and groundwater interactions by numerical modelling in arid regions: a case study of Shahu Lake

In order to maintain the scenic and eco-environmental values of a lake, we need to characterize its water interactions. Shahu Lake was used as a case study to show the interactions among replenishment water, lake water and groundwater in an arid region. Shahu Lake is located in the Ningxia Hui Autonomous Region of northwest China and has an area of 13.96 km² and an average depth of 2.2 m. The groundwater modelling software MODFLOW was used. The analysis results show that hydraulic connectivity among replenishment water, lake water and groundwater is the crucial driving factor that affects the water level in Shahu Lake. The lake water level is highly sensitive to the volume of replenishment water. The groundwater is of great importance in balancing the water level in the lake and preventing it from drying up. It was determined that 13.8 × 10⁶ m³/yr is the optimal volume of replenishment water for Shahu Lake in order to maintain the lake level at its normal state and also to make the best use of available water resources on a long-term basis. Understanding of the water interactions can promote effective management of water resources in Shahu Lake.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR D. Hughes     

Comparison of an artificial neural network and a conceptual rainfall–runoff model in the simulation of ephemeral streamflow

ABSTRACT

The rainfall–runoff process is governed by parameters that can seldom be measured directly for use with distributed models, but are rather inferred by expert judgment and calibrated against historical records. Here, a comparison is made between a conceptual model (CM) and an artificial neural network (ANN) for their ability to efficiently model complex hydrological processes. The Sacramento soil moisture accounting model (SAC-SMA) is calibrated using a scheme based on genetic algorithms and an input delay neural network (IDNN) is trained for variable delays and hidden layer neurons which are thoroughly discussed. The models are tested for 15 ephemeral catchments in Crete, Greece, using monthly rainfall, streamflow and potential evapotranspiration input. SAC-SMA performs well for most basins and acceptably for the entire sample with R² of 0.59–0.92, while scoring better for high than low flows. For the entire dataset, the IDNN improves simulation fit to R² of 0.70–0.96 and performs better for high flows while being outmatched in low flows. Results show that the ANN models can be superior to the conventional CMs, as parameter sensitivity is unclear, but CMs may be more robust in extrapolating beyond historical record limits and scenario building.

EDITOR M.C. Acreman; ASSOCIATE EDITOR not assigned     

Modelling evaporation from reservoirs / La mise en modèle de l'évaporation des réservoirs

ABSTRACT

It is shown that a numerical model for predicting the depth time variation of water temperature in a fresh water lake or reservoir can be used also for prediction of water losses due to evaporation. The seasonal change in peak evaporation from summer (in small lakes) to winter (in large lakes) is satisfactorily simulated.     

Evaporation estimation on Lake Titicaca: a synthesis review and modelling

The aim of this study was to validate evaporation models that can be used for palaeo‐reconstructions of large lake water levels. Lake Titicaca, located in a high‐altitude semi‐arid tropical area in the northern Andean Altiplano, was the object of this case study. As annual evaporation is about 90% of lake output, the lake water balance depends heavily on the yearly and monthly evaporation flux. At the interannual scale, evaporation estimation presents great variability, ranging from 1350 to 1900 mm year^?1. It has been found that evaporation is closely related to lake rainfall by a decreasing relationship integrating the implicit effect of nebulosity and humidity. At the seasonal scale, two monthly evaporation data sets were used: pan observations and estimations derived from the lake energy budget. Comparison between these data sets shows that (i) there is one maximum per year for pan evaporation and two maxima per year for lake evaporation, and (ii) pan evaporation is greater than lake evaporation by about 100 mm year^?1. These differences, mainly due to a water depth scale factor, have been simulated with a simple thermal model θ_w(h, t) of a free‐surface water column. This shows that pan evaporation (h = 0·20 m) is strongly correlated with direct solar radiation, whereas the additional maximum of lake evaporation (h = 40 m) is related to the heat restitution towards the atmosphere from the water body at the end of summer. Finally, five monthly evaporation models were tested in order to obtain the optimal efficiency/complexity ratio. When the forcing variables are limited to those that are most readily available in the past, i.e. air temperature and solar radiation, the best results are obtained with the radiative Abtew model (r = 0·70) and with the Makkink radiative/air temperature model (r = 0·67). Copyright © 2007 John Wiley & Sons, Ltd.     

Water balance of Lake Victoria: update to 2000 and climate change modelling to 2100 / Bilan hydrologique du Lac Victoria: mise à jour jusqu’en 2000 et modélisation des impacts du changement climatique jusqu’en 2100

Abstract

Abstract An annual water balance model of Lake Victoria is derived for the period 1925–2000. Regression techniques are used to derive annual inputs to the water balance, based on lake rainfall data, measured and derived inflows and estimated evaporation during the historical period. This approach acknowledges that runoff is a nonlinear function of lake rainfall. A longer inflow series is produced here which is representative of the whole inflow to the lake, rather than just from individual tributaries. The results show a good simulation of annual lake levels and outflows and capture the high lake level in 1997–1998. Climate change scenarios, from a recent global climate model experiment, are applied to the lake rainfall inflow series and evaporation data to estimate future water balances of the lake. The scenarios produce a potential fall in lake levels by the 2030s horizon, and a rise by the 2080s horizon. A discussion of the application of climate change data to this complex hydrological system is presented.     

Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment,Terengganu, Malaysia

ABSTRACT

This paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is trained with a representative set of hourly data, with optimal time delay for both the input and output. The network trained using 120-day data is able to produce simulations that are in excellent agreement with field observations. We show that for application with one-step-ahead predictions, the loss in network performance is marginal. Inclusion of additional tidal observations does not improve predictions, suggesting that the river stage stations under consideration are not sensitive to tidal backwater effects despite the claim commonly made.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR F. Pappenberger     

A comparative study for water temperature modelling in a small basin,the Fourchue River,Quebec, Canada

Analysis and forecasting of water temperature are important for water ecological management. The objective of this study is to compare models for water temperature during the summer season for an impounded river. In a case study, we consider hydro-climatic and water temperature data for the Fourchue River (St-Alexandre-de-Kamouraska, Quebec, Canada) between 2011 and 2014. Three different models are applied, which are broadly characterized as deterministic (CEQUEAU), stochastic (Auto-regressive Moving Average with eXogenous variables or ARMAX) and nonlinear (Nonlinear Autoregressive with eXogenous variables or NARX). The efficiency of each model is analysed and compared. The results show that the ARMAX is the best performing water temperature model for the Fourchue River and the CEQUEAU model also simulates water temperature adequately without the overfitting issues that seem to plague the autoregressive models.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

Application of a spreadsheet hydrological model for computing the long-term water balance of Lake Awassa,Ethiopia

Abstract

The water balance of the closed freshwater Lake Awassa was estimated using a spreadsheet hydrological model based on long-term monthly hydrometeorological data. The model uses monthly evaporation, river discharge and precipitation data as input. The net groundwater flux is obtained from model simulation as a residual of other water balance components. The result revealed that evaporation, precipitation, and runoff constitute 131, 106 and 83 × 10⁶ m³ of the annual water balance of the lake, respectively. The annual net groundwater outflow from the lake to adjacent basins is 58 × 10⁶ m³. The simulated and recorded lake levels fit well for much of the simulation period (1981–1999). However, for recent years, the simulated and recorded levels do not fit well. This may be explained in terms of the combined effects of land-use change and neotectonism, which have affected the long-term average water balance. With detailed long-term hydrogeological and meteorological data, investigation of the subsurface hydrodynamics, and including the effect of land-use change and tectonism on surface water and groundwater fluxes, the water balance model can be used efficiently for water management practice. The result of this study is expected to play a positive role in future sustainable use of water resources in the catchment.     

Comparative performance analysis of climate re-analysis approaches in Angola

This paper examines the performance of three climate re-analysis datasets in Angola, namely the ERA-40, NCEP-r1 and JRA-55, by comparing annual and seasonal estimates of precipitation, surface air temperature and evaporation with ground observation measurements. The observational dataset describes a region poorly covered by international climate databases and it is believed that most of its data have not been used in the data assimilation procedures of the climate models. This paper therefore provides a fresh look at the performance of these climate re-analysis datasets in a vast area where distance and civil war have hindered ground monitoring efforts. The re-analysis exercises offer better temperature estimates than precipitation estimates. When offered, the evaporation estimates from all three products are very poor. The three products are able to describe the main features of the spatial distribution of average annual precipitation and temperature, but struggle to reproduce the temporal changes of these variables. The results from a set of performance criteria show that the correlation between the observed ground measurements and re-analysis estimates is poor overall and the NSE values indicate that the average measured value at each location is usually a better estimate than the re-analysis estimate.

EDITOR A. Castellarin

ASSOCIATE EDITOR S. Kanae     

On the importance of training methods and ensemble aggregation for runoff prediction by means of artificial neural networks

ABSTRACT

Artificial neural networks (ANNs) become widely used for runoff forecasting in numerous studies. Usually classical gradient-based methods are applied in ANN training and a single ANN model is used. To improve the modelling performance, in some papers ensemble aggregation approaches are used whilst in others, novel training methods are proposed. In this study, the usefulness of both concepts is analysed. First, the applicability of a large number of population-based metaheuristics to ANN training for runoff forecasting is tested on data collected from four catchments, namely upper Annapolis (Nova Scotia, Canada), Biala Tarnowska (Poland), upper Allier (France) and Axe Creek (Victoria, Australia). Then, the importance of the search for novel training methods is compared with the importance of the use of a very simple ANN ensemble aggregation approach. It is shown that although some metaheuristics may slightly outperform the classical gradient-based Levenberg-Marquardt algorithm for a specific catchment, none performs better for the majority of the tested ones. One may also point out a few metaheuristics that do not suit ANN training at all. On the other hand, application of even the simplest ensemble aggregation approach clearly improves the results when the ensemble members are trained by any suitable algorithms.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR E. Toth     

Analysing individual recession events: sensitivity of parameter determination to the calculation procedure

ABSTRACT

This study assesses the sensitivity to model fitting methods and segment selection of the estimated parameters A and B of the model dQ/dt = ?AQ^B for individual events. We investigated about 750 recession events observed at 25 US Geological Survey gauges in the Iowa and Cedar river basins in the United States, with drainage areas ranging from 7 to 17 000 km². The parameters of these recession events were estimated using three commonly adopted methods and recession segments with different extraction criteria. The results showed that the variations of the parameter estimates for the same recession event were comparable to the variations of parameters between different events due to using different model fitting methods and recession segments. This raises cautions for comparative analysis of individual recessions. The result also implies that the nonlinear direct fitting method is the most robust among the three model fitting methods compared.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR T. Okruszko     

On the feasibility of using a lake water balance model to infer rainfall: an example from Lake Victoria

Abstract

A water balance model of Lake Victoria that can be used to assess rainfall from lake level, is derived. The model utilizes satellite estimates of rainfall directly over the lake. The model, initially derived and calibrated for the period 1956–1978, is reformulated here in such a way that all water balance terms except evaporation can be calculated from a combination of catchment rainfall and level of the lake. The reformulated model is validated and used to predict lake level fluctuations during the period 1931–1994. An error analysis is also performed. The model is then “inverted” to solve for mean rainfall conditions during various intervals of changing lake levels. For modern periods with known rainfall conditions, the error in model estimates is of the order of 1%.     

Application of geochemical and stable isotopic tracers to investigate groundwater salinity in the Ochi-Narkwa Basin,Ghana

Rainwater, groundwater and soil-water samples were analysed to assess groundwater geochemistry and the origin of salinity in the Ochi-Narkwa basin of the Central Region of Ghana. The samples were measured for major ions and stable isotopes (δ¹⁸O, δ²H and δ¹³C). The Cl^? content in rainwater decreased with distance from the coast. The major hydrochemical facies were Na-Cl for the shallow groundwaters and Ca-Mg-HCO₃, Na-Cl and Ca-Mg-Cl-SO₄ for the deep groundwaters. Groundwater salinization is caused largely by halite dissolution and to a minor extent by silicate weathering and seawater intrusion. Stable isotope composition of the groundwaters followed a slope of 3.44, suggesting a mixing line. Chloride profiles in the soil zone revealed the existence of salt crusts, which support halite dissolution in the study area. A conceptual flow model developed to explain the mechanism of salinization showed principal groundwater flow in the NW–SE direction.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR K. Heal     

Hydrological modelling of the Vistula and Odra river basins using SWAT

This paper presents a large-scale application of the SWAT model for water balance and natural streamflow simulation in the entire basins of the Vistula and the Odra, covering most of the territory of Poland. A tailored calibration approach was designed to achieve satisfactory goodness-of-fit across a range of catchment sizes. Model calibration and evaluation driven by high-resolution climate data showed overall good behaviour for 80 benchmark catchments divided into eight clusters, and spatial evaluation for 30 gauges showed that the designed regionalization scheme performed well (median KGE of 0.76). Basin-averaged estimates of blue and green water flow and green water storage estimated using the calibrated model were 185, 517 and 206 mm, respectively. This study provides a basis for future work, such as assessing climate change impacts on hydrology, assessing flow alterations, and water quality simulation. The model output is publicly available through an online research data archive (doi:10.4121/uuid:b8ab4f5f-f692-4c93-a910-2947aea28f42).

EDITOR A. Castellarin

ASSOCIATE EDITOR G. Thirel     

Projections of future deterioration in UK river quality are hampered by climatic uncertainty under extreme conditions

ABSTRACT

A modelling study was undertaken to quantify effects that the climate likely to prevail in the 2050s might have on water quality in two contrasting UK rivers. In so doing, it pinpointed the extent to which time series of climate model output, for some variables derived following bias correction, are fit for purpose when used as a basis for projecting future water quality. Working at daily time step, the method involved linking regional climate model (HadRM3-PPE) projections, Future Flows Hydrology (rainfall–runoff modelling) and the QUESTOR river network water quality model. In the River Thames, the number of days when temperature, dissolved oxygen, biochemical oxygen demand and phytoplankton exceeded undesirable values (>25°C, <6 mg L^?1, >4 mg L^?1 and >0.03 mg L^?1, respectively) was estimated to increase by 4.1–26.7 days per year. The changes do not reflect impacts of any possible change in land use or land management. In the River Ure, smaller increases in occurrence of undesirable water quality are likely to occur in the future (by 1.0–11.5 days per year) and some scenarios suggested no change. Results from 11 scenarios of the hydroclimatic inputs revealed considerable uncertainty around the levels of change, which prompted analysis of the sensitivity of the QUESTOR model to simulations of current climate and hydrology. Hydrological model errors were deemed of less significance than those associated with the derivation and downscaling of driving climatic variables (rainfall, air temperature and solar radiation). Errors associated with incomplete understanding of river water quality interactions with the aquatic ecosystem were found likely to be more substantial than those associated with hydrology, but less than those related to climate model inputs. These errors are largely a manifestation of uncertainty concerning the extent to which phytoplankton biomass is controlled by invertebrate grazers, particularly in mid-summer; and the degree to which this varies from year to year. The quality of data from climate models for generating flows and defining driving variables at the extremes of their distributions has been highlighted as the major source of uncertainty in water quality model outputs.

EDITOR A. Castellarin; ASSOCIATE EDITOR X. Fang     

Spatial and temporal variability of groundwater quality of an Algerian aquifer: the case of Soummam Wadi

ABSTRACT

Five-year monitoring of physicochemical parameters was performed with two campaigns in low and high water periods of the Lower Soummam catchment. Data from 18 wells were processed by multivariate statistical tools in order to identify the principal factors influencing groundwater chemistry. Two matrices of 14 and 8 physicochemical parameters with 18 groundwater samples collected in wells were obtained. The correlation matrix showed strong associations between nine variables: K⁺, Ca²⁺, Na⁺, SO₄^2?, Cl^?, Mg²⁺, NO₂^?, Zn²⁺ and Sr²⁺. Principal component analysis and factor analysis showed that the cumulated variance of high and low water periods was of 83.19% and 78.55%, respectively. The variables assigned to the mineralization effect or to pollution indicators were presented by the factor analysis. The bivariate plots confirmed a mineralization model, ascribed to dissolution of geological materials, and to high levels of saline contamination attributed to leakages from sanitary systems. They also showed an increase “upstream to downstream” of the mineralization, visualization of temporal variations, and a dilution process identification of the natural mineralization during the recharge of the aquifer.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR X. Chen     

Assessment of future Syrian water resources supply and demand by the WEAP model

Abstract

Water availability is one of the most important factors for economic development in the Middle East. The Water Evaluation And Planning (WEAP) model was used to assess present and future water demand and supply in Syria till 2050. Nonconventional water resources, climate change, development, industrial growth, regional cooperation, and implementation of new water saving techniques/devices were considered important factors to include in the analysis using the WEAP model. Six scenarios were evaluated depending on the actual situation, climate change, best available technology, advanced technology, regional cooperation, and regional conflict. The results display a vital need for new water resources to balance the unmet water demands. Climate change will have a major effect on Syrian water resources; possible regional conflict will also to a major extent affect water balance. However, regional cooperation and using the best available technology can help in minimizing the gap between supply and demand.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned     

Derivation of water and power operating rules for multi-reservoirs

ABSTRACT

Water operating rules have been universally used to operate single reservoirs because of their practicability, but the efficiency of operating rules for multi-reservoir systems is unsatisfactory in practice. For better performance, the combination of water and power operating rules is proposed and developed in this paper. The framework of deriving operating rules for multi-reservoirs consists of three modules. First, a deterministic optimal operation module is used to determine the optimal reservoir storage strategies. Second, a fitting module is used to identify and estimate the operating rules using a multiple linear regression analysis (MLR) and artificial neural networks (ANN) approach. Last, a testing module is used to test the fitting operating rules with observed inflows. The Three Gorges and Qing River cascade reservoirs in the Changjiang River basin, China, are selected for a case study. It is shown that the combination of water and power operating rules can improve not only the assurance probability of output power, but also annual average hydropower generation when compared with designed operating rules. It is indicated that the characteristics of flood and non-flood seasons, as well as sample input (water or power), should be considered if the operating rules are developed for multi-reservoirs.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR not assigned     

Hydrological simulation of the Betwa River basin (India) using the SWAT model

A seasonal water budget analysis was carried out to quantify various components of the hydrological cycle using the Soil and Water Assessment Tool (SWAT) model for the Betwa River basin (43?500 km²) in central India. The model results were satisfactory in calibration and validation. The seasonal water budget analysis showed that about 90% of annual rainfall and 97% of annual runoff occurred in the monsoon season. A seasonal linear trend analysis was carried out to detect trends in the water balance components of the basin for the period 1973–2001. In the monsoon season, an increasing trend in rainfall and a decreasing trend in ET were observed; this resulted in an increasing trend in groundwater storage and surface runoff. The winter season followed almost the same pattern. A decreasing trend was observed in summer season rainfall. The study evokes the need for conservation structures in the study area to reduce monsoon runoff and conserve it for basin requirements in water-scarce seasons.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR F. Hattermann