Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

Kiptala, Jeremiah Kipkulei; Mohamed, Yasir A.; Mul, Marloes; Zaag, Pieter van der

doi:10.1002/2013wr014240

Cited by 68 publications

(67 citation statements)

References 70 publications

(87 reference statements)

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“…Overall, the uncertainty on the mean annual ET, as calculated by us on the land cover level, is less than 12%. This is comparable with the results of Kiptala et al [60] who used SEBAL data in the Upper Pangani River Basin (Kenya/Tanzania) and other published validation results [11].…”

Section: Discussionsupporting

confidence: 91%

“…The 95% confidence interval for basin mean annual SSEBop ET estimates is 39 mm/yr, which is comparable with 42 mm/yr using the GFET dataset. Overall, uncertainties in the mean annual ET from this study are similar with the reported uncertainties in Kiptala et al [60] using SEBAL in the Upper Pangani River Basin (Kenya/Tanzania) and with other published validation results [11]. This indicates the reliability of the ET estimates derived in this study for various hydrological applications.…”

Section: The Assessment Of the Uncertainties On The Et Estimatessupporting

confidence: 89%

“…Similarly, Alemu et al [10] showed a large difference for wetlands in the Nile Basin. The SSEBop ET (1286 mm/yr) is comparable with the SEBAL ET estimates for wetlands and swamps in the Upper Pangani Basin (Kenya/Tanzania) (1291 mm/yr) [60], suggesting the better reliability of our estimates. The overall modest agreements of SSEBop ET and MOD16-NB estimates (Table 3) are further corroborated by the Wilcoxon rank sum test that shows the means of the SSEBop and MOD16-NB ET values are similar at a 95% confidence level.…”

Section: Validationsupporting

confidence: 69%

“…Hereby, 2000 samples were generated with replacement from the annual estimates to determine the lower (2.5%) and upper (97.5%) boundaries of the confidence interval. A similar approach has been used to assess the uncertainties of water balance terms for a catchment in East Africa [60]. The robustness of the confidence interval depends on the quality of the original sample, and therefore, we considered only annual ET estimates as (i) the SEB approach generally yields reliable estimates of ET at an annual resolution [6,7,9] and (ii) annual values eliminate any potential intra-seasonal variations in the ET estimates.…”

Section: The Evaluation Of the Uncertainty Of The Ssebop Et Estimatesmentioning

confidence: 99%

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Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

et al. 2017

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Actual evapotranspiration (ET) is a major water use flux in a basin water balance with crucial significance for water resources management and planning. Mapping ET with good accuracy has been the subject of ongoing research. Such mapping is even more challenging in heterogeneous and data-scarce regions. The main objective of our research is to estimate ET using daily Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and Global Land Data Assimilation System (GLDAS) weather datasets based on the operational simplified surface energy balance (SSEBop) algorithm at a 1-km spatial scale and 8-day temporal resolution for the Mara Basin (Kenya/Tanzania). Unlike previous studies where the SSEBop algorithm was used, we use a seasonally-varying calibration coefficient for determining the "cold" reference temperature. Our results show that ET is highly variable, with a high inter-quartile range for wetlands and evergreen forest (24% to 29% of the median) and even up to 52% of the median for herbaceous land cover and rainfed agriculture. The basin average ET accounts for about 66% of the rainfall with minimal inter-annual variability. The basin scale validation using nine-years of monthly, gridded global flux tower-based ET (GFET) data reveals that our ET is able to explain 64% of the variance in GFET while the MOD16-NB (Nile Basin) explains 72%. We also observe a percent of bias (PBIAS) of 1.1% and 2.8%, respectively for SSEBop ET and MOD16-NB, indicating a good reliability in the ET estimates. Additionally, the SSEBop ET explains about 52% of the observed variability in the Normalized Difference Vegetation Index (NDVI) for a 16-day temporal resolution and 81% for the annual resolution, pointing to an increased reliability for longer aggregation periods. The annual SSEBop ET estimates are also consistent with the underlying primary (i.e., water and energy) and secondary (i.e., soil, topography, geology, land cover, etc.) controlling factors across the basin. This paper demonstrated how to effectively estimate and evaluate spatially-distributed and temporally-varying ET in data-scarce regions that can be applied elsewhere in the world where observed hydro-meteorological variables are limited.

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Section: Discussionsupporting

confidence: 91%

Section: The Assessment Of the Uncertainties On The Et Estimatessupporting

confidence: 89%

Section: Validationsupporting

confidence: 69%

Section: The Evaluation Of the Uncertainty Of The Ssebop Et Estimatesmentioning

confidence: 99%

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Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

et al. 2017

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“…The Terra earth observation system was launched in the year 1999 and the Aqua earth observation system in the year 2002 [50]. The Terra satellite goes from north to south across the equator and Aqua passes south to north over the equator [3].…”

Section: Modis Et Data and Pre-processingmentioning

confidence: 99%

Evaluation of Spatio-Temporal Patterns of Remotely Sensed Evapotranspiration to Infer Information about Hydrological Behaviour in a Data-Scarce Region

Wambura

Dietrich

Lischeid

2017

Water

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Information about the hydrological behaviour of a river basin prior to setting up, calibrating and validating a distributed hydrological model requires extensive datasets that are hardly available for many parts of the world due to insufficient monitoring networks. In this study, the focus was on prevailing spatio-temporal patterns of remotely sensed evapotranspiration (ET) that enabled conclusions to be drawn about the hydrological behaviour and spatial peculiarities of a river basin at rather high spatial resolution. The prevailing spatio-temporal patterns of ET were identified using a principal component analysis of a time series of 644 images of MODIS ET covering the Wami River basin (Tanzania) between the years 2000 and 2013. The time series of the loadings on the principal components were analysed for seasonality and significant long-term trends. The spatial patterns of principal component scores were tested for significant correlation with elevations and slopes, and for differences between different soil texture and land use classes. The results inferred that the temporal and spatial patterns of ET were related to those of preceding rainfalls. At the end of the dry season, high ET was maintained only in areas of shallow groundwater and in cloud forest nature reserves. A region of clear reduction of ET in the long-term was related to massive land use change. The results also confirmed that most soil texture and land use classes differed significantly. Moreover, ET was exceptionally high in natural forests and loam soil, and very low in bushland and sandy-loam soil. Clearly, this approach has shown great potential of publicly available remote sensing data in providing a sound basis for water resources management as well as for distributed hydrological models in data-scarce river basins at lower latitudes.

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Improving a distributed hydrological model using evapotranspiration‐related boundary conditions as additional constraints in a data‐scarce river basin

Wambura

Dietrich

Lischeid

2018

Hydrological Processes

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Many hydrological models have been calibrated and validated using hydrographs alone. Because streamflow integrates water fluxes in space, many distributed hydrological models tend to have multiple feasible descriptions of hydrological processes. This equifinality usually leads to substantial prediction uncertainty. In this study, additional constraints—namely, the spatial patterns of long‐term average evapotranspiration (ET), shallow groundwater level, and land cover change—were used to investigate the reduction of equifinality and prediction uncertainty in the Soil and Water Assessment Tool (SWAT) in the Wami River basin in Tanzania. The additional constraints were used in the set‐up, parameter emulation and calibration of the SWAT model termed an improved hydrological model (IHM). The IHM was then compared with a classical hydrological model (CHM) that was also developed using the SWAT model but without additional constraints. In the calibration, the CHM used only the hydrograph, but the IHM used the hydrograph and the spatial pattern of long‐term average ET as an additional constraint. The IHM produced a single, unique behavioural simulation, whereas the CHM produced many behavioural simulations that resulted in prediction uncertainty. The performance of the IHM with respect to the hydrograph was more consistent than that of the CHM, and the former clearly captured the mean behaviour of ET in the river basin. Therefore, we conclude that additional constraints substantially reduce equifinality and prediction uncertainty in a distributed hydrological model.

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Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

Cited by 68 publications

References 70 publications

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

Evaluation of Spatio-Temporal Patterns of Remotely Sensed Evapotranspiration to Infer Information about Hydrological Behaviour in a Data-Scarce Region

Improving a distributed hydrological model using evapotranspiration‐related boundary conditions as additional constraints in a data‐scarce river basin

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