On the use of satellite, gauge, and reanalysis precipitation products for drought studies

Golian, Saeed; Javadian, Mostafa; Behrangi, Ali

doi:10.1088/1748-9326/ab2203

Cited by 64 publications

(45 citation statements)

References 39 publications

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“…PP trend shows that PP is increasing in the Amazon rainforest and Southeastern Asia. Moreover, the PP trend is negative over Central Africa (Figure 2c), consistent with the monthly trend analysis by Anabalón and Sharma [13] using 15 years (2000 to 2014) of PP data and [18] using different satellite and reanalysis precipitation products. The AET trends of [12] which are from 1981 to 2012 show consistent results with this study.…”

Section: Global Changes In Aet Pet and Ppsupporting

confidence: 86%

Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions

et al. 2020

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Irrigated croplands require large annual water inputs and are critical to global food production. Actual evapotranspiration (AET) is a main index of water use in croplands, and several remote-sensing products have been developed to quantify AET at the global scale. In this study, we estimate global trends in actual AET, potential ET (PET), and precipitation rate (PP) utilizing the MODIS Evapotranspiration product (2001–2018) within the Google Earth Engine cloud-computing environment. We then introduce a new index based on a combination of AET, PET, and PP estimates—the evapotranspiration warning index (ETWI)—which we use to evaluate the sustainability of observed AET trends. We show that while AET has not considerably changed across global natural lands, it has significantly increased across global croplands (+14% ± 5%). The average ETWI for global croplands is −0.40 ± 0.25, which is largely driven by an extreme trend in AET, exceeding both PET and PP trends. Furthermore, the trends in water and energy limited areas demonstrate, on a global scale, while AET and PET do not have significant trends in both water and energy limited areas, the increasing trend of PP in energy-limited areas is more than water-limited areas. Averaging cropland ETWI trends at the country level further revealed nonsustainable trends in cropland water consumptions in Thailand, Brazil, and China. These regions were also found to experiencing some of the largest increases in net primary production (NPP) and solar-induced fluorescence (SIF), suggesting that recent increases in food production may be dependent on unsustainable water inputs. Globally, irrigated maize was found to be associated with nonsustainable AET trends relative to other crop types. We present an online open access application designed to enable near real-time monitoring and improve the understanding of global water consumption and availability.

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Section: Global Changes In Aet Pet and Ppsupporting

confidence: 86%

Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions

et al. 2020

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“…Some studies use lumped or semi-distributed models, therefore averaging the rainfall amount over large areas (e.g. Duan et al, 2019;Tang et al, 2019;Tobin and Bennett, 2014;Gosset et al, 2013;Shawul and Chakma, 2020), which reduces the bias effect that could occur at the pixel level with a fully distributed model. Often, the model is not recalibrated for each precipitation dataset (e.g.…”

Section: Introductionmentioning

confidence: 99%

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Dembélé

Schaefli

Giesen

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. This study evaluates the ability of different gridded rainfall datasets to plausibly represent the spatio-temporal patterns of multiple hydrological processes (i.e. streamflow, actual evaporation, soil moisture and terrestrial water storage) for large-scale hydrological modelling in the predominantly semi-arid Volta River basin (VRB) in West Africa. Seventeen precipitation products based essentially on gauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP, PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5, PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared as input for the fully distributed mesoscale Hydrologic Model (mHM). To assess the model sensitivity to meteorological forcing during rainfall partitioning into evaporation and runoff, six different temperature reanalysis datasets are used in combination with the precipitation datasets, which results in evaluating 102 combinations of rainfall–temperature input data. The model is recalibrated for each of the 102 input combinations, and the model responses are evaluated by using in situ streamflow data and satellite remote-sensing datasets from GLEAM evaporation, ESA CCI soil moisture and GRACE terrestrial water storage. A bias-insensitive metric is used to assess the impact of meteorological forcing on the simulation of the spatial patterns of hydrological processes. The results of the process-based evaluation show that the rainfall datasets have contrasting performances across the four climatic zones present in the VRB. The top three best-performing rainfall datasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE and CMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC and PGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC for the spatial patterns of soil moisture; ARC, RFE and GSMaP-std for the temporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for the spatial patterns of actual evaporation. No single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes. A dataset that is best in reproducing the temporal dynamics is not necessarily the best for the spatial patterns. In addition, the results suggest that there is more uncertainty in representing the spatial patterns of hydrological processes than their temporal dynamics. Finally, some region-tailored datasets outperform the global datasets, thereby stressing the necessity and importance of regional evaluation studies for satellite and reanalysis meteorological datasets, which are increasingly becoming an alternative to in situ measurements in data-scarce regions.

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“…1). This makes understanding water resource availability difficult in many regions on land and hinders the improvement of water resource management, weather forecasting, and the detection of natural hazards such as floods and droughts (Hossain and Anagnostou 2004;Wu et al 2012;Zhan et al 2016;Golian et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure

Hobeichi

Abramowitz

Contractor

et al. 2020

Journal of Hydrometeorology

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Evaluation of global gridded precipitation datasets typically entails using the in situ or satellite-based data used to derive them, so that out-of-sample testing is usually not possible. Here we detail a methodology that incorporates the physical balance constraints of the surface water and energy budgets to evaluate gridded precipitation estimates, providing the capacity for out-of-sample testing. Performance conclusions are determined by the ability of precipitation products to achieve closure of the linked budgets using adjustments that are within their prescribed uncertainty bounds. We evaluate and compare five global gridded precipitation datasets: IMERG, GPCP, GPCC, REGEN, and MERRA-2. At the spatial level, we show that precipitation is best estimated by GPCC over the high latitudes, by GPCP over the tropics, and by REGEN over North Africa and the Middle East. IMERG and REGEN appear best over Australia and South Asia. Furthermore, our results give insight into the adequacy of prescribed uncertainties of these products and shows that MERRA-2, while being less competent than the other four products in estimating precipitation, has the best representation of uncertainties in its precipitation estimates. The spatial extent of our results is not only limited to grid cells with in situ observations. Therefore, the approach enables a robust evaluation of precipitation estimates and goes some way to addressing the challenge of validation over observation scarce regions.

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On the use of satellite, gauge, and reanalysis precipitation products for drought studies

Cited by 64 publications

References 39 publications

Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions

Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions

Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa

Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure

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