Actual Evapotranspiration Data Research Articles

Degradation trends based on MODIS-derived estimates of productivity and water use efficiency: A case study for the cultivated pastures in the Brazilian Cerrado

Understanding spatial and temporal variations of the agronomic conditions of cultivated pastures is essential for defining guidelines and actions of public and private policies to increase livestock productivity. Within this context, this study aimed to evaluate the trends of degradation of the Cerrado biome cultivated pastures found in Minas Gerais State, Brazil (as produced by the TerraClass Cerrado Landsat-based mapping project, led by the Ministry of Environment of Brazil). The study was based on water use efficiency (WUE) estimates derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2003 to 2014. WUE corresponds to the relation between net primary productivity (NPP) and actual evapotranspiration (AE). NPP values were based on enhanced vegetation index (EVI) time series obtained from the MOD/MYD13 products, while monthly AE data were obtained from the MOD16A2 product. Based on the WUE estimates, ~ 39.1% (4.6 million hectares) of the total cultivated pastures in the study area presented negative trends (p ≤ 0.20) (19.3% for p ≤ 0.05; 8.6% for 0.05 < p ≤ 0.1; and 11.2% for 0.1 < p ≤ 0.2), due to decreasing trends in precipitation and poor pasture management, suggesting different stages of degradation. Overcoming such degradation patterns can help increasing the beef production in this region and reducing the rate of conversion of natural vegetation to new pasturelands.

Spatial Estimation of Actual Evapotranspiration for Different Land Use Land Cover using MODIS Data

Accurate estimation of evapotranspiration (ET) is very essential for water resources management. In the same climatic and meteorological conditions, actual evapotranspiration (AET) may exhibit remarkable spatial variability across different vegetation covers, agricultural land uses etc. The present study was undertaken to check the feasibility of using MODerate resolution Imaging Spectroradiometer (MODIS) AET data for determining the annual and seasonal AET in Andhra Pradesh and Telangana States. Also, the spatial and temporal variation of actual evapotranspiration (AET) for different land use and land covers was also determined. The mean annual AET showed a significant spatial variation, ranged from 505 mm/year in zaid crop area to 1982 mm/year in waste land. The mean AET for the selected region was 1234 mm/year (excluding build up and water bodies). For almost all the land use land cover (LULC), the value of mean monthly AET started to rise rapidly in July, reached its peak in October, and then declined. In general, all types of LULC show similar seasonal dynamic trends for AET. Among different districts of Andhra Pradesh and Telangana, higher AET was noted from districts with more water bodies such as Krishna, East Godavari and Nellore and lower AET from Chittoor, Ananthapur, Prakasam and Vizianagaram districts. MODIS AET was found suitable for estimating the AET from different land use and land covers except build up and water bodies.

Effects of irrigation regime on the growth and yield of irrigated soybean in temperate humid climatic conditions

This research was conducted during two irrigation seasons (2014–2015 and 2015–2016) in Salto, Uruguay. This growing region is characterized by high annual precipitation and periods of soil water deficit of different intensities. This characterization casts much doubt to soybean growers regarding whether supplementary crop irrigation is useful for maximizing soybean yield, maintaining stable productivity and increasing profit margins. Three supplemental irrigation treatments in addition to a rainfed treatment were evaluated for their effects on soybean growth, development and yield with respect to the vegetative and reproductive stages. The results show that supplemental irrigation during the reproductive stage (R1–R8) has a positive effect on soybean growth and development, regardless of treatment. The total dry matter and leaf area index were between 8% and 40% higher in irrigation treatments compared with rainfed conditions. Actual evapotranspiration data, estimated with soil moisture sensors, showed that the crop coefficients (Kc) used in these experiments can be generalized for use in the region. During both cropping seasons, the rainfed treatment produced the lowest grain yield, with a 35% reduction in yield compared with that of the irrigated treatments. However, the water use efficiency values were inversely related to the amount of water applied. The profit margin showed that supplemental irrigation is useful in conditions during which the soybean price was greater than 350 U$D per ton, given the hypotheses considered. In the northwestern region of Uruguay, no irrigation would be the best option when the soybean price is less than U$D 350 or when rainfall is more stable during crop growth seasons.

Alluvial groundwater recharge estimation in semi-arid environment using remotely sensed data

Data limitations on groundwater (GW) recharge over large areas are still a challenge for efficient water resource management, especially in semi-arid regions. Thus, this study seeks to integrate hydrological cycle variables from satellite imagery to estimate the spatial distribution of GW recharge in the Ipanema river basin (IRB), which is located in the State of Pernambuco in Northeast Brazil. Remote sensing data, including monthly maps (2011–2012) of rainfall, runoff and evapotranspiration, are used as input for the water balance method within Geographic Information Systems (GIS). Rainfall data are derived from the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7 (3B43V7) product and present the same monthly average temporal distributions from 15 rain gauges that are distributed over the study area (r=0.93 and MAE=12.7mm), with annual average estimates of 894.3 (2011) and 300.7mm (2012). The runoff from the Natural Resources Conservation Service (NRCS) method, which is based on regional soil information and Thematic Mapper (TM) sensor image, represents 29% of the TMPA rainfall that was observed across two years of study. Actual evapotranspiration data, which were provided by the SEBAL application of MODIS images, present annual averages of 1213 (2011) and 1067 (2012)mm. The water balance results reveal a large inter-annual difference in the IRB GW recharge, which is characterized by different rainfall regimes, with averages of 30.4 (2011) and 4.7 (2012)mmyear−1. These recharges were mainly observed between January and July in regions with alluvial sediments and highly permeable soils. The GW recharge approach with remote sensing is compared to the WTF (Water Table Fluctuation) method, which is used in an area of alluvium in the IRB. The estimates from these two methods exhibit reliable annual agreement, with average values of 154.6 (WTF) and 124.6 (water balance) mm in 2011. These values correspond to 14.89 and 13.53% of the rainfall that was recorded at the rain gauges and the TMPA, respectively. Only the WTF method indicates a very low recharge of 15.9mm for the second year. The values in this paper provide reliable insight regarding the use of remotely sensed data to evaluate the rates of alluvial GW recharge in regions where the potential runoff cannot be disregarded from WB equation and must be calculated spatially.

A Monthly-Step Water Balance Model to Evaluate the Hydrological Effects of Climate Change on a Regional Scale for Irrigation Design

AbstractCurrent and ongoing changes in the climate are typified by a rise in global temperatures. Climate change can have a dramatic impact on the water cycle. The aim of this paper was to develop a model based on Thornthwaite-type monthly water balance estimations. The main goals were to calibrate the model parameters using a remote sensing-based evapotranspiration dataset. The calibrated model was used for projection on the basis of four climate model datasets (remo, dmihirham5, smhirca.bcm, knmiracmo2). The four main projection periods were: 1980-2010, 2010-2040, 2040-2070, and 2070-2100. The advantage of this model is its robust structure. It can be applied if temperature and precipitation time series are available. The key parameter is the water storage capacity of the soil (SOILMAX), which can be calibrated using the actual evapotranspiration data available. If the physical properties of the soil are known, the maximal rooting depth is also projectable. The model can be primarily used at the catchment level or for areas without additional amounts of water from below. For testing the model, a mixed parcel of land that is used as a cornfield near Mosonmagyaróvár and a small, forest-covered catchment near Sopron were successfully used as the datasets. Furthermore, we determined the water stress with the calculation of the relative extractable water (REW), soil water deficit (SWD), and the water stress index (IS).

Estimation of total available water in the soil layer by integrating actual evapotranspiration data in a remote sensing-driven soil water balance

Summary The total available water ( τ ) by plants that could be stored in its root soil layer is a key parameter when applying soil water balance models. Since the transpiration rate of a vegetation stand could be the best proxy about the soil water content into the root soil layer, we propose a methodology for estimating τ by using as basic inputs the evapotranspiration rate of the stand and time series of multispectral imagery. This methodology is based on the inverted formulation of the soil water balance model. The inversion of the model was addressed by using an iterative approach, which optimizes the τ parameter to minimize the difference between measured and modeled ET. This methodology was tested for a Mediterranean holm oak savanna (dehesa) for which eddy covariance measurements of actual ET were available. The optimization procedure was performed by using a continuous dataset (in 2004) of daily ET measurements and 16 sets of 8 daily ET measurements, resulting in τ values of 325 and 305 mm, respectively. The use of these τ values in the RSWB model for the validation period (2005–2008) allowed us to estimate dehesa ET with a RMSE = 0.48 mm/day. The model satisfactorily reproduces the water stress process. The sensitivity of τ estimates was evaluated regarding two of the more uncertain parameters in the RSWB model. These parameters are the average fraction of τ that can be depleted from the root zone without producing moisture stress ( p τ ) and the soil evaporation component. The results of this analysis indicated relatively little influence from the evaporation component and the need for adequate knowledge about p τ for estimating τ .

Comparing approaches for modeling spatially distributed direct recharge in a semi-arid region (Okanagan Basin, Canada)

Spatially distributed recharge is compared at two different scales using three different modeling approaches within the semi-arid Okanagan Basin, British Columbia, Canada. Regional recharge was modeled by mapping results for one-dimensional soil columns from the water-balance code HELP (Hydrologic Evaluation of Landfill Performance, V3.80D). The regional model was then compared to two, independently derived, local-scale models to ensure local trends were captured in the regional model, and to compare modeling methods. Average annual recharge, predicted by the regional model, varied from no recharge to 186 mm/yr. For the north Okanagan (Vernon area), regional estimates were compared to Richards’ equation-based MIKE-SHE (V2007) estimates, which showed a significant difference in average annual recharge: 7 mm/yr (MIKE-SHE) and 109 mm/yr (HELP). In the south Okanagan (Oliver area), regional estimates were compared to high-resolution, local HELP estimates. Similar values of average annual recharge were obtained: 34 mm/yr (local) and 42 mm/yr (regional). A comparison with measured actual evapotranspiration data in the north Okanagan, showed HELP over-predicted recharge compared to MIKE-SHE by under-predicting evapotranspiration during summer months. Thus, the use of HELP in semi-arid areas may be limited if accurate estimates of recharge are needed. However, results may give satisfactory groundwater model calibrations results because of high uncertainty in hydraulic properties.

Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia

We developed a new algorithm for estimating monthly actual evapotranspiration (AET) based on surface reflectance from MODIS-Terra and interpolated climate data. The algorithm uses monthly values of the Enhanced Vegetation Index (EVI) and the Global Vegetation Moisture Index (GVMI) derived from the MODIS nadir bidirectional reflectance distribution function – adjusted reflectance product (MOD43B4) to scale Priestley-Taylor potential evapotranspiration derived from the climate surfaces. The EVI is associated with evapotranspiration through its relationship with leaf area index. The GVMI allows separation between surface water and bare soil when EVI is low and provides information on vegetation water content when EVI is high. The model was calibrated using observed AET data from seven sites in Australia, including two forests, two open savannas, a grassland, a floodplain and a lake. Model outputs were compared with four year average difference between precipitation and streamflow (a surrogate for mean AET) in 227 unimpaired catchments across Australia. We tested four different model configurations and found that the best results both in the calibration and evaluation datasets were obtained when a precipitation interception term ( E i ) and the GVMI were incorporated into the model. The E i term and the GVMI improved AET estimates in the forest, savanna and grassland sites and in the lake and floodplain sites respectively. The most comprehensive model estimated monthly AET at the seven calibration sites with a RMSE of 18.0 mm mo −1 (22% of the mean AET, r 2 = 0.84). In the evaluation dataset, mean annual AET was estimated with a RMSE of 137.44 mm y −1 (19% of the mean AET, r 2 = 0.61). The model was able to reproduce the main spatial and temporal patterns in AET across Australia. The main advantages of the proposed model are that it uses a single set of parameters (i.e. does not need an auxiliary land cover map) and that it is able to estimate AET in areas with significant direct evaporation, including lakes and floodplains.

Validation of the hydrologic evaluation of landfill performance (HELP) model for simulating the water balance of cover systems

Simulation models can be efficient tools for several tasks especially in planning. In the USA, the HELP model was developed to simulate the water balance of landfill liner systems, especially of cover systems. HELP version 3 was examined in a German climate in an extensive validation study, and a German adaptation was developed. The validation study consists of three parts: a methodological part (meaning, aims and procedure of validation), a theoretical part (comparison of the modelling approach with the state of science, comparison of documentation, literature and source code), and a practical part (sensitivity analyses and operational validation). In the operational validation, measured and simulated discharges and actual evapotranspiration data of test fields on the landfill Hamburg-Georgswerder from 1988 to 1995 were compared. Limitations, weak points, and errors of the HELP model are shown. The HELP model is a suitable tool for experts in hydrology; but good knowledge of the model and its behaviour and critical review of the simulation results are essential.

PREDICTING ABOVE-GROUND NET PRIMARY PRODUCTIVITY OF TROPICAL RAINFORESTS FROM EVAPOTRANSPIRATION DATA

The relationship between above-ground net primary productivity (ANPP) and actual evapotranspiration (AE) has been previously shown by Rosenzweig (1968) to be significant for a variety of mainly temperate terrestrial ecosystems. Our study of ANPP and AE data from the humid tropics showed that AE remains a useful predictor of ANPP in tropical rainforest environments. However, we also noted that 80% of the tropical rainforest data points were depressed below Rosenzweig's original regression line. We attribute these lower-than-predicted ANPP values to transpiration losses and rainfall interception losses that do not result in a corresponding production of biomass.