Monthly Evaporation Research Articles

Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

The heat storage changes (Qt) can be a significant component of the energy balance in lakes, and it is important to account for Qt for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Qt has been often neglected in many studies due to the lack of required water temperature data. A simple hysteresis model (Qt = a*Rn + b + c*dRn/dt) has been demonstrated to reasonably estimate Qt from the readily available net all wave radiation (Rn) and three locally calibrated coefficients (a–c) for lakes and reservoirs. As a follow-up study, we evaluated whether this hysteresis model could enable energy balance-based evaporation models to yield good evaporation estimates. The representative monthly evaporation data were compiled from published literature and used as ground-truth to evaluate three energy balance-based evaporation models for five lakes. The three models in different complexity are De Bruin-Keijman (DK), Penman, and a new model referred to as Duan-Bastiaanssen (DB). All three models require Qt as input. Each model was run in three scenarios differing in the input Qt (S1: measured Qt; S2: modelled Qt from the hysteresis model; S3: neglecting Qt) to evaluate the impact of Qt on the modelled evaporation. Evaluation showed that the modelled Qt agreed well with measured counterparts for all five lakes. It was confirmed that the hysteresis model with locally calibrated coefficients can predict Qt with good accuracy for the same lake. Using modelled Qt as inputs all three evaporation models yielded comparably good monthly evaporation to those using measured Qt as inputs and significantly better than those neglecting Qt for the five lakes. The DK model requiring minimum data generally performed the best, followed by the Penman and DB model. This study demonstrated that once three coefficients are locally calibrated using historical data the simple hysteresis model can offer reasonable Qt to force energy balance-based evaporation models to improve evaporation modelling at monthly timescales for conditions and long-term periods when measured Qt are not available. We call on scientific community to further test and refine the hysteresis model in more lakes in different geographic locations and environments.

Estimation of the Water Balance in the Basin ofWadi Al Hassa

This study addresses the estimation of water balance in the basin of Wadi Al Hassa through the analysis of climatic elements that controls water balance. The study made use of the monthly data of rainfall and temperatures between the period of 1980 to 2015 at the various stations of the study area (Al Hassa, Jurf Ed Darawish, Prince Hassan Nursery (Abur), and Almazar). This study relied on the model of Thornthwaite and Madre (TM) to identify the general water situation in the basin and to determine the areas of water surplus and shortage in the study areas. The study showed that most of the area suffering from water shortage had reach its peak in July and August, where it drained the soil of an aqueous stock water. Aqueous stock water year is divided into: 1) The season of a water surplus that starts from January until March. In this season, the soil takes the moisture they lost during the dry season. 2) The water shortage season starts from April until November. During this season, the amount of the monthly evaporation exceeds the amount of precipitation.

Estimating the evaporation from irrigation reservoirs of greenhouses using satellite imagery

The agricultural system in south‐eastern Spain is based on intensive horticulture in greenhouses. Public and private organizations have spent substantial resources on optimizing irrigation, due to the scant annual precipitation (close to 250 mm). In order to preserve natural water resources, avoiding overexploitation and salinization aquifers, the water loss has to be minimized. Farmers save water in irrigation reservoirs, which are open to the atmosphere most of the time. In this work, the loss to evaporation from open water reservoirs was estimated in a typical agricultural greenhouse area in Almeria province, south‐eastern Spain. The data source was both a high‐resolution satellite image, and a set of climatic data from the Agro‐climatic Information Network of Andalusia (AINA) and from a Class‐A pan evaporimeter. The image was used for detecting and delineating open water bodies applying a supervised classification algorithm based on an artificial neural network. The climatic data were used to estimate the distribution of monthly evaporation. It was concluded that irrigation water reservoirs can evaporate 3.76% of the input water used for crops. If all of the water bodies were covered with shade materials and if the precipitation intercepted by the roofs of greenhouses were saved in the irrigation water reservoirs, 49.87% of water annually consumed by greenhouse crops could be saved. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1750–1757, 2016

Modeling Pan Evaporation for Kuwait using Multiple Linear Regression and Time-Series Techniques

This study attempts to model evaporation for Kuwait under arid conditions by using a wide range of monthly evaporation data, varying from 0.1 to 40 mm/day, from January 1993 to July 2015. Owing to the reason that the well-known theoretical evaporation models presented in the literature have been justified for a much shorter data range, the paper adopts empirical approaches to fit the data. Two evaporation models are presented based on classical statistical methods, one of multiple linear regression and another of time series analysis. The regression model, which is a function of temperature, relative humidity and wind speed, allows different modifications in the independent variables for more natural evaporation data synthesis. The time series model, which is a function of time only, is convenient for producing forecasts. Both evaporation models have been shown to produce results that are in reasonable agreement with observation values. This study advocates that the specific, rather simple, classical procedures performed to model the evaporation data can be effective alternatives to other theoretical and semi-theoretical methods found in the literature.

단일 저수지 운영에서 우선 수리권 영향성 평가

Nowadays, global warming derived from urbanization makes impact on the climatical and natural environment in the world. Also, water shortage from sharp population growth has increased because of impossible condition of the new reservoir construction that is one of sustainable water resource development. Accordingly, data survey for water rights have been required for limited water resources distribution effectively. Now, Water Management Information System(WAMIS) has gathered domestic water rights data according to various criteria as follows: living, industrial, and agricultural use purposes for specific year based on watershed, basin, river size. In this study, Water Rights Analysis Package (WRAP), one component of Texas Water Availability Model (WAM) system, is applied to multi-purpose Soyang Dam with monthly flow, evaporation, and precipitation. Also, water rights data are utilized into two types: natural and priority order water rights. The application results indicated that two types of water rights provided the insight for establishing various reservoir operation plans under flood, normal, and drought periods.

Analysis of evaporation from water surface measured automatically by the EWM evaporimeter at the weather station in Ústí nad Orlicí between 2001 and 2014

Abstract Evaporation from water surface at the station in Ústí nad Orlicí was measured using an automatic EWM evaporimeter. The analysed period was from May 1st to September 30th in the years 2001 to 2014. Statistical analysis of the daily evaporation showed that the values ranged between 0.0 mm and 7.3 mm (July 17, 2007). This maximum value was analysed in detail and considered to be realistic based on the unusual weather conditions on that day. The highest average daily evaporation was observed in July (2.8 mm), followed by August (2.5 mm). On the other hand the lowest average daily evaporation was found to be in September (1.6 mm). Average monthly evaporation totals in the analysed period (2001–2014) ranged from 49.1 mm (September) to 86.1 mm (July). The absolute lowest monthly evaporation total in the analysed period was measured in September 2002 (34.4 mm), on the other end of the scale, the absolute highest monthly evaporation in the period of interest was measured in August 2003 (114.5 mm). Statistics of annual data show that out of the 14 years analysed, the lowest evaporation was observed in 2005 (263.5 mm), while the highest in 2007 (426.1 mm). Average annual (May-September) evaporation for the 14 years is 355.0 mm. The trend in evaporation for May and August is negative, in the other months it is positive. The largest change was seen in July, where the linear index value is +1.555. However, the trends in monthly values are not statistically significant.

Attributes of Lake Okanagan evaporation and development of a mass transfer model for water management purposes

Understanding the water budget of the valley lakes in the water-stressed Okanagan region of British Columbia is important for allocating resources to maximize social well-being, environmental quality and the economy. However, high uncertainty in existing estimates of lake evaporation prevents sound water resource decision making. To address this uncertainty, buoy- and shore-based eddy covariance and meteorological instrumentation were deployed on the largest of the valley lakes, Lake Okanagan, for approximately 3 years. The objectives were to address the uncertainty in existing Lake Okanagan evaporation estimates by describing seasonal cycles and annual rates and the meteorological attributes controlling evaporation, and developing an accurate and useful model suitable for water managers and policy makers. Results indicate that two sites on Lake Okanagan experienced average annual evaporation of 725 and 835 mm over the study period. The difference can be attributed to spatial differences in surface water temperatures, vapour pressure gradients and atmospheric stability across the lake. Good relationships were found between evaporation rates measured with the eddy covariance systems and meteorological conditions at the offshore buoys, specifically between wind speed and the surface–atmospheric vapour pressure differences. From these relationships, a mass transfer model was developed. Accounting for the seasonal cycle in atmospheric stability increased the accuracy of monthly and annual evaporation estimates from this mass transfer model, but it remains inappropriate to predict daily or hourly evaporation. The study period included years that were climatically typical, so the evaporation observations could represent values close to the long-term mean, but this is unknown. The findings of this study highlight that long-term observations of the atmosphere consistently conditioned to the lake surface are needed for water managers and decision makers to have sound data and information on lake evaporation.

Quantitative Impacts of Climate Change and Human Activities on Water-Surface Area Variations from the 1990s to 2013 in Honghu Lake, China

The water-surface areas of the lakes in the mid-lower reaches of the Yangtze River, China, have undergone significant changes under the combined impacts of global climate change and local anthropogenic stress. As a typical lake in this region, the Honghu Lake features water-surface area variations that are documented in this study based on high–resolution remote sensing images from the 1990s to 2013. The impact of human activities is analyzed by a novel method based on land use data. The relative impacts of each driving force are further distinguished by the statistical analysis method. Results show that the water-surface area has significant inter-annual and seasonal variabilities, and the minimum of which generally occurs in spring. The degree to which climate factors and land use structure affect the water-surface area varies between different stages. In the April-May period, the sum of the water demands of paddies and aquaculture has a negative effect that is greater than the positive effect of the difference between the monthly precipitation and monthly evaporation. In the June–October period, the precipitation features a positive impact that is greater than the negative effect of the water demand of agriculture. Meanwhile, climate factors and human activities have no influence on the lake area in the November–March period. With the land use being altered when annual precipitations are close in value, paddy field areas decrease, ponds areas increase, and the water demand of agriculture rises in both flood and drought years. These findings provide scientific foundation for understanding the causes of water-surface area variations and for effectively maintaining the stability of the Honghu Lake area through adjustments in land use structure.

Respuesta del crecimiento radial a la evaporación, a partir de maderas temprana y tardía

La mayoría de los estudios dendrocronológicos se basan en la relación del crecimiento radial y la precipitación; sin embargo, pocos estudios han considerado las respuestas de la madera temprana (EW, por sus siglas en inglés) y tardía (LW, por sus siglas en inglés) al efecto de la evaporación. En este estudio se usaron índices residuales para evaluar la respuesta de crecimiento de EW y LW de Pinus cooperi Blanco al efecto de la evaporación en bosques del estado de Durango, México, durante el periodo 1964-2010. El software DENDROCLIM fue utilizado para correlacionar datos dendrocronológicos con la evaporación total mensual. En un análisis de intervalo simple se utilizaron datos de evaporación a partir del mes de enero del año previo a la estación de crecimiento a diciembre del año de la formación del anillo. Los coeficientes de correlación indicaron una relación negativa consistente de EW y LW con la evaporación del otoño-invierno previo a la estación de crecimiento. No obstante, el crecimiento de la madera tardía fue más consistente en términos de sensibilidad climática, lo cual puede indicar que la medición de dicha variable puede ser de utilidad en estudios dendroclimáticos.

Statistical downscaling of general circulation model outputs to evaporation, minimum temperature and maximum temperature using a key-predictand and key-station approach

A key-predictand and key-station approach was employed in downscaling general circulation model outputs to monthly evaporation, minimum temperature (Tmin) and maximum temperature (Tmax) at five observation stations concurrently. Tmax was highly correlated (magnitudes above 0.80 at p ≤ 0.05) with evaporation and Tmin at each individual station, hence Tmax was identified as the key predictand. One station was selected as the key station, as Tmax at that station showed high correlations with evaporation, Tmin and Tmax at all stations. Linear regression relationships were developed between the key predictand at the key station and evaporation, Tmin and Tmax at all stations using observations. A downscaling model was developed at the key station for Tmax. Then, outputs of this downscaling model at the key station were introduced to the linear regression relationships to produce projections of monthly evaporation, Tmin and Tmax at all stations. This key-predictand and key-station approach was proved to be effective as the statistics of the predictands simulated by this approach were in close agreement with those of observations. This simple multi-station multivariate downscaling approach enabled the preservation of the cross-correlation structures of each individual predictand among the stations and also the cross-correlation structures between different predictands at individual stations.

Regionalization Approach for Modeling of Monthly Evaporation Based on Cluster Analysis

Among interesting Climatic Parameters (CPs) of different climates, it may be asserted that evaporation has received a particular attention. The present study, by considering 14 stations in arid central and southern parts of Iran, has tried to determine the most important factors affecting evaporation through using Factor Analysis (FA). At first, by conducting Cluster Analysis (CA) through Minitab software, Homogeneous Regions (HRs) separated at the investigating areas. Then, the relation between climatic factors and evaporation on the basis of monthly routine was obtained in each region. Finally, by the help of accomplished regression equations, evaporation was calculated and MAE or RMSE statistics were applied to determine the precision of each relation. The results show that, firstly, factor analysis is an appropriate method for determining climatic parameters affecting evaporation in the regions. Secondly, as far as the relation between independent parameters and evaporation and priority of the main factors has been proved previously, multiple regressions may be used with great confidence to calculate evaporation and consequently evapotranspiration. The results also indicate that the difference between maximum and minimum temperatures (Tmax - Tmin), Tmax and the difference between maximum and minimum relative humidity (Hmax - Hmin) are, respectively, the main factors which influence the evaporation value at the Homogeneous Region (HR1) which is spread along Iran's water borders having a warm and humid climate. Generally, the Temperature Related Parameters (TPR) including Tmax - Tmin, Tmax, Tmin and Tmean at the HR1 are found as the main factors affecting evaporation. At the HR2 and HR3, wind speed, Tmax and Hmax - Hmin are identified as the main parameters and cloudiness as the second one. The results show that the wind speed and the cloudy times of day have a more effective role in the amount of evaporation rather than the temperature related factors.

Evaporation from Water Surfaces in Arid and Semi-Arid Areas in Algeria

The evaporation from open water remains a difficult process to measure or estimate. The major source of difficulty is the fact that the required meteorological parameters are rarely measured over the water. In this study, we calculate the evaporation rate from the pan using the energy budget method which is widely considered to be the most accurate method of estimating evaporation and A CFD-based methodology to estimate monthly evaporation for the two dams. The evaporation rates calculated with the energy budget and the application of CFD were in good agreement with monthly evaporation measurements in dams located in areas of different climates in Algeria.

Thermal structure and Energy Budget for Alghadir reservoir, Iran

Knowing the rate of evaporation from surface water resources such as channels and reservoirs is essential for precise management of the water balance. Few detailed evaporation studies exist for small lakes or reservoirs in arid regions of the world. In this study, monthly evaporation was determined by Bowen Ratio Energy Budget technique (BREB) for Alghadir reservoir (Saveh, Iran) from 1995–2007 and compared with class-A pan. Daily data were obtained from IMO (Iran Meteorological Organization) weather station, located near the reservoir, for all of these years. Some variations have been observed on the estimated evaporation of the energy budget at different years, ranging from 151 cm for 1997 to 174 cm for 2006. There is no specific evaporation pattern for all the years, but evaporation rates were low in winter (January and February) and highest during the summer (July and August). However, the times and month of highest evaporation rates varied during the study period. Surveying of reservoir thermal structure showed that, inflow and outflow energy fluxes to this water volume have large variations. In addition, incoming solar shortwave radiation, incoming atmospheric longwave radiation, and longwave atmospheric radiation emitted from the water surface are largest energy fluxes for this small and deep reservoir. Results of this study could explain the importance and sensible contribution of the evaporation rates as a fundamental parameter in the hydrological cycle of reservoirs ecosystem in the arid regions of Iran.

The ENSO footprint in monthly satellite evaporation over the global ocean during 1993–2007

The spatial pattern of latent heat flux (LHF) variability associated with El Niño-Southern Oscillation (ENSO) is extracted using 15 years (1993–2007) of monthly satellite-derived LHF over the global ocean. This ENSO LHF footprint agrees well with the El Niño evaporation pattern reported previously with a 3-year (1996–1998) weekly version of this data set. LHF anomalies over the eastern tropical Pacific are positively correlated with sea surface temperature (SST) anomalies suggesting a damping effect on ENSO. Positive correlations with ENSO are also observed over the eastern mid-latitude North Pacific, western and central mid-latitude South Pacific and the equatorial Indian Ocean. Negative correlations are observed elsewhere. It is also shown that the LHF footprints of both phases of ENSO (El Niño and La Niña) present very similar spatial structure. As expected, the surface wind pattern associated with El Niño (La Niña) shows convergence (divergence) over the central and eastern tropical Pacific and divergence (convergence) around the western tropical Pacific.

Application of the HEC-HMS model for runoff simulation in a tropical catchment

Hydrologic simulation employing computer models has advanced rapidly and computerized models have become essential tools for understanding human influences on river flows and designing ecologically sustainable water management approaches. The HEC-HMS is a reliable model developed by the US Army Corps of Engineers that could be used for many hydrological simulations. This model is not calibrated and validated for Sri Lankan watersheds and need reliable data inputs to check the suitability of the model for the study location and purpose. Therefore, this study employed three different approaches to calibrate and validate the HEC-HMS 3.4 model to Attanagalu Oya (River) catchment and generate long term flow data for the Oya and the tributaries.Twenty year daily rainfall data from five rain gauging stations scattered within the Attanagalu Oya catchment and monthly evaporation data for the same years for the agro meteorological station Henarathgoda together with daily flow data at Dunamale from 2005 to 2010 were used in the study. GIS layers that were needed as input data for the flow simulation were prepared using Arc GIS 9.2 and used in the HEC-HMS 3.4 calibration of the Dunamale sub catchment using daily flow data from 2005 to 2007. The model was calibrated adjusting three different methods. The model parameters were changed and the model calibration was performed separately for the three selected methods, the Soil Conservation Service Curve Number loss method, the deficit constant loss method (the Snyder unit hydrograph method and the Clark unit hydrograph method) in order to determine the most suitable simulation method to the study catchment. The calibrated model was validated with a new set of rainfall and flow data (2008–2010). The flows simulated from each methods were tested statistically employing the coefficient of performance, the relative error and the residual method. The Snyder unit hydrograph method simulates flows more reliably than the Clark unit hydrograph method. As the loss method, the SCS Curve Number method does not perform well.

Effects of Climate Variability on Evaporation in Dongping Lake, China, during 2003–2010

Based on two long-term, hourly (10:30–11:30 and 13:10–14:10) meteorological over-lake observations and data from Shenxian meteorological station, nearby Dongping Lake, the Penman-Monteith equation and reference evaporation ratio algorithm were used to calculate lake evaporation in Dongping Lake, China, from 2003 to 2010. The variation trend of evaporation of Dongping Lake was analyzed, and the influences that caused changes in lake evaporation were also discussed. The results show that (1) the total annual evaporation in Dongping Lake increased at 18.24 mm/a during 2003–2010. The major climatic factors accounting for this increase are the rising net radiation and the rising air temperature; (2) the total annual evaporation in a particular hour (13:10–14:10) in Dongping Lake increased at 4.55 mm/a during 2003–2010—the major climate factors that accounted for this increase are rising net radiation, followed by air temperature, wind velocity, and air humidity; (3) against the background of global warming, the climate of Dongping Lake tended to be dry during 2003–2010; the largest contribution to this comes from air temperature, followed by wind velocity and relative humidity; and (4) the monthly evaporation in Dongping Lake has seasonal variability.

A Conceptual Rainfall-Runoff Model Using the Auto Calibrated NAM Models in the Sarisoo River

This paper describes the application of a conceptual rainfall runoff model to investigate the peak and monthly flows at the Sarisoo River Basin on the North West of Iran. The model was calibrated using measured stream flow data and then validated for three years. Calculations of level and time of peak flows are vital for designing structures downstream in the catchment areas. The simulated peak flows were occurring in the months of February in 2003, 2006 and 2007 with approximate values of 6.32, 9.35 and 6.13 m3s-1 respectively. After calibrating 9 NAM parameters using record data of daily rainfall, monthly evaporation and daily discharge in the period of 1th October 2003 to 31th March 2006 and validating the model daily discharges were calculated for 12 years. The outputs of the calibrated model are able to be used in the assessment of water resources management models like Mike Basin, WEAP… because they normally work based on monthly flows with a large time horizon. The results show that monthly averages of mean, maximum and minimum flows are about 10%, 2% and 33% less than daily computed Nash–Sutcliffe coefficients, all calculated over a period of 12 years. The optimum values of the 9 NAM parameters obtained during the calibration procedure are presented. The reliability of MIKE11 NAM was evaluated based on the Nash–Sutcliffe coefficient (R2), Root Mean Square Error (RMSE), peak flow (RMSE) and low flow (RMSE). The R2 obtained during this study is 0.74.

An Investigation on Changes and Prediction of Urmia Lake water Surface Evaporation by Chaos Theory

Chaos theory discusses unstable and non-periodic behavior of non-linear fluctuating dynamicsystems. Since evaporation level variations of lakes have a dynamic identity, chaos theory can have a uniquerole in collecting data of these variations. Therefore it is an important and challenging problem in the field ofplanning and qualitative and quantitative management of Urmia Lake to verify whether the evaporation timeseries are stochastic or chaotic that is discussed in the present study. In addition to introduction of differentutilities of chaos theory, the monthly evaporation amounts of Urmia Lake in the past 40 years have beenstudied and predicted in the present research. So after calculating the delay time (T=7.5) by using averagemutual information method (AMI) and embedding dimension (d=3) by using false nearest neighbor algorithm(FNN), the slope of correlation dimension diagram has been computed. The non-integer amount of the slope(2.47) represents that the system is chaotic. Lyapunov exponent and broad band in Fourier power spectrumare other indexes reported in the present study and their provided results ensures that the system is chaotic.Thus the amount of Urmia Lake evaporation is predictable. Therefore the amount of evaporation in the recent10 years (1997-2007) have been predicted by means of false nearest neighbor algorithm and verified with theobserved data. The results agree with the high accuracy of chaos theory predictions so the amount of evaporationof the Lake is predicted for 10 following years (2007-2017).

Estimation of the evaporative losses from Lake Nasser, Egypt using optical satellite imagery

Water shortage in the arid region is an existing and future severe problem that threatens this part of the world. Egypt has a limited budget of 55 BM3 per year from the river Nile basin that has always been stored in the Lake Nasser reservoir, southern Egypt. It has been estimated that the water losses from the lake ranges from 10 to 20 BM3 a year−1. This paper discusses the possibility of estimating the surface evaporation from Lake Nasser using optical remotely sensed data. The surface energy balance algorithm for land (SEBAL) algorithm was used to estimate the monthly evaporation rate using National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images based on the energy balance components. The main variable within these components is the surface temperature, which was calculated by a calibrated split window equation from the remotely sensed data. Twenty-four satellite images during the year 2008 were used to estimate the maximum and minimum evaporative losses from the lake at 16.3 and 12.5 BM3 year−1, respectively. When compared with the Penman-Monteith mathematical formula, a high correlation was obtained with r 2=0.78. The study demonstrated that remotely sensed data can provide a robust estimate of evaporative losses from Lake Nasser that can aid decision makers in better management and Digital Earth studies.

Projecting and hindcasting potential evaporation for the UK between 1950 and 2099

Evaporation estimation is important for the assessment of a wide range of potential impacts of climate change, yet there are significant questions concerning the relevance of alternative methods for climate change studies, and the uncertainty associated with downscaled driving variables. Using principal components analysis, climate variables related to evaporation have been examined; results show significant differences in correlation structures between observed UK data and climate outputs from a Hadley Centre Global Climate Model (HadCM3). Although employing the GCM data directly in the Penman-Monteith combination equation appears to be practical for estimating current potential evaporation, this approach does not project realistic potential evaporation in the 2080s. A local calibration approach is taken to the derivation of an alternative empirical model for estimating potential evaporation based on GCM outputs, using the Generalised Linear Model (GLM) framework. This appears to provide a robust method for impacts assessment. From the GLM projections, the envisaged change in evaporation will be spatially variable across the UK. It is expected that the southern part of the UK will be more sensitive to the change in evaporation than the north. Moreover, in the 2080s, the range (variance) of the monthly potential evaporation appears to change more than the mean.