LAKE EVAPORATION STUDIES USING SATELLITE THERMAL INFRARED DATA1

Thermal infrared radiation data were acquired by the Heat Capacity Mapping Mission (HCMM) satellite over the surface area (385 km²) of Utah Lake during periodic overpasses in 1978 and 1979. The thermal infrared data were converted to lake surface temperatures which were subsequently used in correlations with lake evaporation. Correlations between HCMM surface temperature and pan-derived evaporation exceeded r = 0.90 when HCMM night and day/night average temperatures and two-day average evaporation values were tested. Similar regression studies were done using monthly data from a conceptual evaporation model and the evaporation pan versus monthly HCMM temperature data. In this test both the HCMM day and night monthly temperature versus the monthly model or pan evaporation had correlations exceeding r = 0.95. Empirical estimates of both short and long term lake evaporation using satellite thermal infrared data seem feasible. Attempts to use the HCMM thermal information as direct input to a theoretical approach to calculating evaporation were inconclusive; however, a definite potential seems to exist.     

ESTIMATING AVERAGE MONTHLY LAKE EVAPORATION IN THE NORTHEAST UNITED STATES1

ABSTRACT: A methodology to estimate the average monthly lake evaporation, E(τ), (month τ=1,12) for fresh water bodies located in the northeast United States is presented. The approach combines analysis of at‐site, lake‐specific vertical water temperature profile data and a previously developed regional air temperature based model approximation of the widely accepted modified Penman energy budget estimate of mean monthly potential evaporation, E_p(τ) (mm/day). The paper presents procedures to develop site‐specific estimates of E_p(τ) and to convert water temperature data to average monthly conductive heat flux, G(τ). With monthly estimates of G(τ), the average monthly potential evaporation, E_p(τ), is then convertible to estimates of the average monthly lake evaporation, E(τ). This new method permits a good estimate of site‐specific lake evaporation rates without the data and computational requirements of the Penman energy budget procedure nor the comparatively expensive, time consuming field eddy correlation approach.     

Preliminary comparison of landscape pattern-normalized difference vegetation index (NDVI) relationships to Central Plains stream conditions

We explored relationships of water quality parameters with landscape pattern metrics (LPMs), land use-land cover (LULC) proportions, and the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) or NDVI-derived metrics. Stream sites (271) in Nebraska, Kansas, and Missouri were sampled for water quality parameters, the index of biotic integrity, and a habitat index in either 1994 or 1995. Although a combination of LPMs (interspersion and juxtaposition index, patch density, and percent forest) within Ozark Highlands watersheds explained >60% of the variation in levels of nitrite-nitrate nitrogen and conductivity, in most cases the LPMs were not significantly correlated with the stream data. Several problems using landscape pattern metrics were noted: small watersheds having only one or two patches, collinearity with LULC data, and counterintuitive or inconsistent results that resulted from basic differences in land use-land cover patterns among ecoregions or from other factors determining water quality. The amount of variation explained in water quality parameters using multiple regression models that combined LULC and LPMs was generally lower than that from NDVI or vegetation phenology metrics derived from time-series NDVI data. A comparison of LPMs and NDVI indicated that NDVI had greater promise for monitoring landscapes for stream conditions within the study area.     

ESTIMATING REFERENCE EVAPORATION IN THE CENTRAL VALLEY OF CALIFORNIA USING THE LINACRE MODEL1

ABSTRACT: The Linacre (1988) model for calculating evaporation from open water or well-watered surfaces only requires inputs of air temperature, latitude and elevation, and windspeed if it is available. The model was developed using data collected at a large number of sites in different climatic regions of the world, while independent tests of the model have shown it to be suitable for estimating evaporation in a variety of locations. This study was intended to contribute to the broad goal of evaluating temperature-based evaporation models for use in California by testing the Linacre model in the agriculturally intensive Central Valley. Observed monthly mean reference evaporation (E_o) and meteorological data for periods ranging up to 72 months were obtained from 25 California Irrigation and Management Information System (CIMIS) stations distributed throughout the Central Valley. Uncalibrated and calibrated Linacre models were used to estimate monthly mean reference evaporation, and the performance of each model was evaluated using indices that quantified the random and systematic errors and overall model performance. The accuracy of the radiation and ventilation components of the model were evaluated separately. The uncalibrated model was found to systematically overestimate E_o with most of the model error being attributed to the ventilation component. Calibration of the radiation and ventilation components removed most of the systematic model errors, and the root mean square error for monthly mean E_o was 0.676 mm day^?1 (16.8 percent of the mean observed value). (KEY TERMS: reference evaporation; Linacre model; irrigation scheduling.)     

Hydrologic Effects of NDVI Time Series in a Context of Climatic Variability in an Upstream Catchment of the Minjiang River1

Abstract: Increasing regional vegetation activity has been frequently found especially in middle and high latitude and alpine areas, but the effects of which on regional hydrology is still highly uncertain. The Upstream Catchment of Minjiang River is a large mountainous catchment covering 22,919 km² with a diverse vegetation distribution pattern, including alpine group (A), subalpine group (SA), and temperate and subtropical group (T/ST). The Seasonal Mann‐Kendall test, a nonparametric trend test method, detected consistent upward trends in all groups in monthly accumulated growing degree days (AGDD_M) time series from 1982 to 2003, but no significant trend in mean monthly precipitation (MMP) time series in any group. The alpine group had a significant (p = 0.024) upward trend in monthly Normalized Difference of Vegetation Index (NDVI) time series from 1982 to 2003, in contrast, the SA and T/ST groups had decreasing (although not significant) trends. AGDD_M plays more important role than MMP in affecting NDVI change in alpine areas, indicating temperature was the main climatic driver. In contrast, water was the main driver for the T/ST group, as indicated by the significant correlation between NDVI and MMP and a weak correlation with AGDD_M. Correlation coefficients of NDVI and river flow varied with seasons, mostly negative, especially during the growing season (April to October). A significant (p = 0.025) correlation was found only in August, indicating that an increase in peak‐NDVI decreased high flow significantly. TI‐NDVI_c, which was developed in an attempt to track the vegetation change at the catchment scale, accounted for more than 40% of the evapotranspiration increase (r² = 0.43).     

Predicting RUSLE (Revised Universal Soil Loss Equation) Monthly Erosivity Index from Readily Available Rainfall Data in Mediterranean Area

Summary Seasonal rainerosivity is important in the structure and dynamics of Mediterranean ecosystems. The present paper contributes to the quantitative assessment of RUSLE's monthly erosion index in a data-scarce Mediterranean region. Therefore, a regionalized relationship for estimating monthly erosion index (EI_30-month) from only three rainfall parameters has been obtained. Knowledge of the seasonal and annual distribution of erosivity index, permit soil and water conservationists to make improved designs for erosion control, water harvesting or small hydraulic structures. Although a few long data sets were used in the analysis, validation with established monthly erosivity index values from other Italian locations, suggest that the model presented (r² = 0.973) is robust. It is recommended to monthly erosivity estimates when experimental data-scarce rainfall become available.     

基于SPOT VGT/NDVI的陕西省关中地区冬小麦遥感估产

冬小麦是关中地区的主要粮食作物之一。对冬小麦产量估算的研究可使国家有关部门及时掌握粮食生产状况,对国家制定粮食政策和经济计划,及时进行宏观调控有着重要的意义。以陕西省关中地区为研究区域,利用1999—2007年的SPOT VGT/NDVI遥感数据对冬小麦产量进行预测。首先,选取冬小麦关键生长期内0.2—0.8范围内的旬NDVI数据,利用最大值合成法合成后的月NDVI数据建立与冬小麦产量之间的关系;其次,使用相关分析方法筛选出冬小麦关键期内与产量相关性较好的月份和旬,分别建立这些月份、旬与冬小麦产量之间的回归关系模型,最后对模型进行精度验证。结果显示,NDVI与产量之间有很好的相关性,其中4月上旬的相关性最好,其相关系数R2为0.605,即利用4月份上旬的数据预测冬小麦产量最好。在预测产量与实际产量对比的基础上,得出估产的相对误差为-5.2%—-7.9%,表明估产精度良好,可运用于冬小麦的实际估产。     

Utility of Gridded Rainfall for IHACRES Daily River Flow Predictions in Southern California Watersheds1

Abstract: Studies to regionalize conceptual hydrologic models generally require rainfall and river flow data from multiple watersheds. Besides the considerable time (cost) to assemble and process rainfall data for many watersheds, investigators often need to choose from a number of candidate gauges, subjectively weighing the relative importance of proximity and elevation to select a representative rainfall dataset. The Unified Raingauge Dataset (URD) is a gridded daily rainfall dataset that covers the conterminous United States at 0.25 × 0.25 degrees spatial resolution and is available from 1948 to present. The objective of this study was to determine whether uncertainty in daily river flow predictions using the conceptual hydrologic model IHACRES in small to moderate size watersheds (50‐400 km²) in southern California would increase if URD gridded rainfall data were used in place of single rain gauge data to calibrate the model. Rain gauge data were obtained from the gauge nearest the watershed centroid and the gauge closest in elevation to the watershed mean elevation. Results from 20 randomly selected watersheds indicated that IHACRES calibration performance was similar using rainfall data from the URD grids and rain gauge data. There was some evidence of greater uncertainties associated with the URD calibrations in areas where topography may affect rainfall amounts. In contrast to the URD data, monthly gridded data produced by the Parameter‐Elevation Regressions on Independent Slopes Model (PRISM) includes adjustments for elevation and produces gridded values at a finer spatial resolution (4 km²). A limited test on two watersheds demonstrated that scaling the URD daily rainfall estimates to match the PRISM monthly values may improve rainfall estimates and model simulation performance.     

EVAPOTRANSPIRATION MEASUREMENT AND ESTIMATION OF THREE WETLAND ENVIRONMENTS IN THE UPPER ST. JOHNS RIVER BASIN,FLORIDA1

ABSTRACT: Accurate estimates of evapotranspiration from areas dominated by wetland vegetation are needed in the water budget of the Upper St. Johns River Basin. However, local data on evapotranspiration rates, especially in wetland environments, were lacking in the project area. In response to this need, the St. Johns River Water Management District collected evapotranspiration field data in Fort Drum Marsh Conservation Area over the period 1996 through 1999. Three large lysimeters were installed to measure the evapotranspiration from different wetland environments: sawgrass (Cladium jamaicense), cattail (Typha domingensis), and open water. In addition, pan evaporation was measured with a standard class “A” pan. Concurrently, meteorological data including rainfall, solar radiation, wind speed, relative humidity, air temperature, and atmospheric pressure were collected. By comparing computed evapotranspiration rates with those measured in the lysimeters, parameters in the Penman‐Monteith, the Priestley‐Taylor, and Reference‐ET methods, and evaporation pan coefficients were estimated for monthly and seasonal cycles. The results from the data collected in this study show that mean monthly evapotranspiration rates, computed by the different methods, are relatively close. From a practical point of view, results indicate that the evaporation pan can be used equally well as the more complex and data‐intensive methods. This paper presents the measured evapotranspiration rates, evaporation pan coefficients, and the estimated parameter values for three different methods to compute evapotranspiration in the project area. Since local data on evaporation are often scarce or lacking, this information may be useful to watershed hydrologists for practical application in other project regions.     

WATER BALANCE OF PACIFIC ATOLLS1

ABSTRACT: This study presents an estimate of water balance components for Pacific atolls under average dimatological conditions. Figures show annual potential evapotranspiration, annual recharge for rain-fed and aquifer-fed vegetated areas, and the number of months that potential evapotranspiration exceeds actual evapotranspiration (indicating water stress) under average conditions. The method relies on the assumption that small islands have minimal influence on cloudiness and precipitation. The potential evapotranspiration is computed using the equilibrium evaporation concept, and estimates of monthly soil water storage and recharge follow Thornthwaite's bookkeeping method. Gradients in potential evapotranspiration run primarily north-south, though for the equatorial zone potential evapotranspiration declines from east to west, opposing the trend in rainfall. Recharge estimates range from 250 mm in the central Tuamotu Archipelago and zero in eastern Kiribati to over 2000 mm per year in the southern Caroline Islands (U.S. Trust Territory) and Solomon Islands. The sensitivity of the model to intra-month rainfall variability and a range of available soil moisture values is discussed.     

The global solar radiation estimation and analysis of solar energy: Case study for Osmaniye,Turkey

This paper investigates the prediction of solar radiation model and actual solar energy in Osmaniye, Turkey. Four models were used to estimate using the parameters of sunshine duration and average temperature. In order to obtain the statistical performance analysis of models, the coefficient of determination (R²), mean absolute percentage error (MAPE), mean absolute bias error (MABE), and root mean square error (RMSE) were used. Results obtained from the linear regression using the parameters of sunshine duration and average temperature showed a good prediction of the monthly average daily global solar radiation on a horizontal surface. In order to obtain solar energy, daily and monthly average solar radiation values were calculated from the five minute average recorded values by using meteorological measuring device. As a result of this measurement, the highest monthly and yearly mean solar radiation values were 698 (April in 2013) and 549 (2014 year) W/m² respectively. On an annual scale the maximum global solar radiation changes from 26.38 MJ/m²/day by June to 19.19 MJ/m²/day by September in 2013. Minimum global solar radiation changes from 14.05 MJ/m²/day by October to 7.20 MJ/m²/day by January in 2013. Yearly average energy potential during the measurement period was 16.53 MJ/m²/day (in 2013). The results show that Osmaniye has a considerable solar energy potential to produce electricity.     

CALIBRATION OF A WATER-BALANCE MODEL FOR SMALL WATERSHEDS IN EASTERN OREGON1

ABSTRACT: The BURP water-balance model was calibrated for 13 small (0.46 to 7.00 mi²), forested watersheds in the Blue Mountains of eastern Oregon where snowmelt is the dominant source of runoff. BURP is the model name and is not an acronym. Six of the 16 parameters in BURP were calibrated. The subsurface recession coefficient and three subsurface water-storage parameters were most sensitive for simulating monthly flow. Calibrated subsurface recession coefficients ranged from 0.988 to 0.998. The subsurface-water storage parameters were calibrated at between 20 to 120 percent of their initial values obtained from a category III soil survey. That reconnaissance-level survey was apparently too broad to accurately reflect subsurface-water storage in small watersheds. Tests of model performance showed BURP is capable of producing accurate simulations of monthly flow for mountainous, snow-dominated watersheds with shallow (< 4 ft) soils when calibrated with 2 to 4 years of streamflow data. A regression of observed versus simulated monthly flows with data from all watersheds combined showed that BURP accounted for 85 percent of the variability in observed flows, which ranged from 0.01 to 20.8 inches, but underpredicted high flow months, with a slope of 1.15 that is significantly different from 1.0 (p = 0.05). Without prior calibration, subsurface-water storage parameters appeared to be the greatest source of potential error.     

CLIMATOLOGICAL WATERSHED CALIBRATION1

ABSTRACT: This study tests the hypothesis that climatic data can be used to develop a watershed model so that stream flow changes following forest harvest can be determined. Measured independent variables were precipitation, daily maximum and minimum temperature, and concurrent relative humidity. Computed variables were humidity deficit, saturated vapor pressure, and ambient vapor pressure. These climatic variables were combined to compute a monthly evaporation index. Finally, the evaporation index and monthly precipitation were regressed with measured monthly stream flow and the monthly estimates of stream flow were combined for the hydrologic year. A regression of predicted versus measured annual stream flow had a standard error of 1.5 inches (within 6.1 percent of the measured value). When 10, 15, and 20 years of data were used to develop the regression equations, predicted minus measured stream flow for the last 7 years of record (1972–1978) were within 16.8, 11.5, and 9.7 percent of the measured mean, respectively. Although single watershed calibration can be used in special conditions, the paired watershed approach is expected to remain the preferred method for determining the effects of forest management on the water resource.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

Watershed Evapotranspiration Increased due to Changes in Vegetation Composition and Structure Under a Subtropical Climate1

Abstract: Natural forests in southern China have been severely logged due to high human demand for timber, food, and fuels during the past century, but are recovering in the past decade. The objective of this study was to investigate how vegetation cover changes in composition and structure affected the water budgets of a 9.6‐km² Dakeng watershed located in a humid subtropical mountainous region in southern China. We analyzed 27 years (i.e., 1967‐1993) of streamflow and climate data and associated vegetation cover change in the watershed. Land use/land cover census and Normalized Difference of Vegetation Index (NDVI) data derived from remote sensing were used to construct historic land cover change patterns. We found that over the period of record, annual streamflow (Q) and runoff/precipitation ratio did not change significantly, nor did the climatic variables, including air temperature, Hamon’s potential evapotranspiration (ET), pan evaporation, sunshine hours, and radiation. However, annual ET estimated as the differences between P and Q showed a statistically significant increasing trend. Overall, the NDVI of the watershed had a significant increasing trend in the peak spring growing season. This study concluded that watershed ecosystem ET increased as the vegetation cover shifted from low stock forests to shrub and grasslands that had higher ET rates. A conceptual model was developed for the study watershed to describe the vegetation cover‐streamflow relationships during a 50‐year time frame. This paper highlighted the importance of eco‐physiologically based studies in understanding transitory, nonstationary effects of deforestation or forestation on watershed water balances.     

GENERALIZED WATERSHED LOADING FUNCTIONS FOR STREAM FLOW NUTRIENTS1

ABSTRACT: Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km² watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.     

A SENSITIVITY AND ERROR ANALYSIS CF PROCEDURES USED FOR ESTIMATING EVAPORATION1

ABSTRACT: Sensitivity and error analyses were used to examine the following objectives: (1) analyze the structure of commonly used evaporation models; (2) provide estimates of the effect of variation in meteorological factors on observed evaporation rates; and (3) estimate the effect of error in measurements of the meteorological factors. The results indicate error in evaporation estimates resulting from measurement error in meteorological factors is probably much less than five percent of the computer evaporation rate. Variation with both time and space of the importance of the different meteorological factors is demonstrated. The sensitivity analysis indicates that the Fractional-Evaporation Equivalent method is structurally inadequate and the Weather Bureau model is more flexible than the Penman model. However, the Penman model appears to provide more realistic estimates of the importance of the various meteorological factors.     

Differences in Evaporation Between a Floating Pan and Class A Pan on Land1

Abstract: Research was conducted to develop a method for obtaining floating pan evaporation rates in a small (less than 10,000 m²) wetland, lagoon, or pond. Floating pan and land pan evaporation data were collected from March 1 to August 31, 2005, at a small natural wetland located in the alluvium of the Canadian River near Norman, Oklahoma, at the U.S. Geological Survey Norman Landfill Toxic Substances Hydrology Research Site. Floating pan evaporation rates were compared with evaporation rates from a nearby standard Class A evaporation pan on land. Floating pan evaporation rates were significantly less than land pan evaporation rates for the entire period and on a monthly basis. Results indicated that the use of a floating evaporation pan in a small free‐water surface better simulates actual physical conditions on the water surface that control evaporation. Floating pan to land pan ratios were 0.82 for March, 0.87 for April, 0.85 for May, 0.85 for June, 0.79 for July, and 0.69 for August.     

WEST AFRICA: VOLTA DISCHARGE DATA QUALITY ASSESSMENT AND USE1

ABSTRACT: Water resource management in West Africa is often a complicated process due to inadequate resources, climatic extremes, and insufficient hydrological information. Insufficient data hinder sustainable watershed management practices, one of the top priorities in the Volta River Basin. This research properly fills in missing data by modeling the hydrological distribution in the Volta River Basin. On average, discharge gages across the basin are missing 20 percent of their monthly data over 20 years. Two methods were used to supplement missing data: a statistically linear model and a conceptual hydrological model. A linear equation, developed from the regression of precipitation and runoff, was used to evaluate the quality of existing data. The hydrological model separates the system into root and groundwater zones. Measured values were used to calibrate the hydrological model and to validate the statistical model. The quality of existing data was analyzed and organized for usability. Accuracy of the hydrological model was also evaluated for its effectiveness using R² and standard error. It was found that the hydrological model was an improvement from the linear model on a monthly basis; R² values improved by as much as 0.5 and monthly error decreased. Monthly predictions of the hydrological model were used to fill gaps of measured data sets.     

TESTS OF THE CREAMS MODEL ON AGRICULTURAL FIELDS IN VERMONT1

ABSTRACT: The computer model, CREAMS, has been developed for field-sized agricultural areas to aid in best management practices evaluation and planning. A test of CREAMS was performed by comparing monthly observed and simulated values for runoff, sediment, and phosphorus exports from two agricultural fields in Vermont to determine the applicability of the model in cold climates. Water quality samples were collected from field runoff and analyzed for both total suspended solids and total phosphorus. Generally, exports were overestimated during low flow months and underestimated during high flow months. Significant r²values (p <0.05), ranging from 0.78 to 0.90, between simulated and observed data were found for all comparisons except for sediment export from one field. Comparisons of the slopes of the regressions between observed and simulated values and the ideal slope of one using t-tests revealed significant differences between simulated and observed monthly runoff, sediment, and phosphorus exports. It is postulated that this lack of adequate prediction could be attributed to the use of average monthly, instead of daily, temperature and solar radiation in calculations of evapotranspiration and snowmelt, and the use of static parameter values for parameters that vary seasonally.