Soil Moisture Evapotranspiration Research Articles

Shifted discharge and drier soils: Hydrological projections for a Central Asian catchment

Study RegionThe Naryn River Basin, KyrgyzstanStudy FocusWe investigate the impacts of climate change in the basin based on two families of General Circulation Models (GCMs) using the hydrological model SWAT. The forcing datasets are the widely used ISIMIP2 (I2) and the newly derived ISIMIP3 (I3) data which refer to the 5th and 6th stage of the Coupled Model Intercomparison Project (CMIP). Due to notable differences in the forcing we evaluate their impacts on various hydrological components of the basin, such as discharge, evapotranspiration (ETA) and soil moisture (SM). Besides, a partial correlation (PC) analysis is used to assess the meteorological controls of the basin with special emphasize on the SM-ETA coupling.New Hydrological Insights for the RegionAgreement in the basin’s projections is found, such as discharge shifts towards an earlier peak flow of one month, significant SM reductions and ETA increases. I3 temperature projections exceed their previous estimates and show an increase in precipitation, which differs from I2. However, the mitigating effects do not lead to an improvement in the region’s susceptibility to soil moisture deficits. The PC study reveals enhanced water-limited conditions expressed as positive SM-ETA feedback under I2 and I3, albeit slightly weaker under I3.

Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data

Although soil moisture (SM) is an important constraint factor of evapotranspiration (ET), the majority of the satellite-driven ET models do not include SM observations, especially the SM at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer SM data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM ET) algorithm by incorporating SM control into soil evaporation (Es) and canopy transpiration (T). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM ET model shows increased R2, NSE and reduced RMSE, Bias, with more improvements occurring in water-limited regions. SM incorporation into T enhanced ET estimates by increasing R2 and NSE by 4% and 18%, respectively, and RMSE and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two ET algorithms to the whole of China and found larger increases in T and Es in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual ET increased from the northwest to the southeast. The SM constraint resulted in higher transpiration estimate and lower evaporation estimate. Es was greatest in the northwest arid region, interception was a large fraction in some rainforests, and T was dominant in most other regions. Further improvements in the estimation of ET components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum.

Soil Moisture–Evapotranspiration Overcoupling and L-Band Brightness Temperature Assimilation: Sources and Forecast Implications

AbstractThe assimilation of L-band surface brightness temperature (Tb) into the land surface model (LSM) component of a numerical weather prediction (NWP) system is generally expected to improve the quality of summertime 2-m air temperature (T2m) forecasts during water-limited surface conditions. However, recent retrospective results from the European Centre for Medium-Range Weather Forecasts (ECMWF) suggest that the assimilation of L-band Tb from the European Space Agency’s (ESA) Soil Moisture Ocean Salinity (SMOS) mission may, under certain circumstances, degrade the accuracy of growing-season 24-h T2m forecasts within the central United States. To diagnose the source of this degradation, we evaluate ECMWF soil moisture (SM) and evapotranspiration (ET) forecasts using both in situ and remote sensing resources. Results demonstrate that the assimilation of SMOS Tb broadly improves the ECMWF SM analysis in the central United States while simultaneously degrading the quality of 24-h ET forecasts. Based on a recently derived map of true global SM–ET coupling and a synthetic fraternal twin data assimilation experiment, we argue that the spatial and temporal characteristics of ECMWF SM analyses and ET forecast errors are consistent with the hypothesis that the ECMWF LSM overcouples SM and ET and, as a result, is unable to effectively convert an improved SM analysis into enhanced ET and T2m forecasts. We demonstrate that this overcoupling is likely linked to the systematic underestimation of root-zone soil water storage capacity by LSMs within the U.S. Corn Belt region.

Investigating the Relationship between the Evaporative Stress Index and Land Surface Conditions in the Contiguous United States

AbstractDespite the key importance of soil moisture–evapotranspiration (ET) coupling in the climate system, limited availability of soil moisture and ET observations poses a major impediment for investigation of this coupling regarding spatiotemporal characteristics and potential modifications under climate change. To better understand and quantify soil moisture–ET coupling and relevant processes, this study takes advantage of in situ soil moisture observations from the U.S. Climate Reference Network (USCRN) for the time period of 2010–17 and a satellite-derived version of the evapotranspiration stress index (ESI), which represents anomalies in a normalized ratio of actual to reference ET. The analyses reveal strong seasonality and regional characteristics of the ESI–land surface interactions across the United States, with the strongest control of soil moisture on the ESI found in the southern Great Plains during spring, and in the north-central United States, the northern Great Plains, and the Pacific Northwest during summer. In drier climate regions such as the northern Great Plains and north-central United States, soil moisture control on the ESI is confined to surface soil layers, with subsurface soil moisture passively responding to changes in the ESI. The soil moisture–ESI interaction is more uniform between surface and subsurface soils in wetter regions with higher vegetation cover. These results provide a benchmark for simulation of soil moisture–ET coupling and are useful for projection of associated climate processes in the future.

Development and Evaluation of an Agricultural Drought Index by Harnessing Soil Moisture and Weather Data

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.

Elucidating observed land surface feedbacks across sub-Saharan Africa

This study examines the role of terrestrial forcings on the regional climate of sub-Saharan Africa through the application of a multivariate statistical method, stepwise generalized equilibrium feedback assessment, to an array of observational, reanalysis, and remote sensing data products. By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered. The approach from our 2017 study is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration (ET) partitioning in terrestrial feedbacks; and compare land surface feedbacks among four key regions, namely the Sahel, Greater Horn of Africa, West African monsoon region, and Congo. ET partitioning differs notably among sub-Saharan regions and between available observational datasets. Across sub-Saharan Africa as a whole, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions. The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions. Moisture recycling is the dominant mechanism in these regions, with positive soil moisture–vegetation–rainfall feedbacks. The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies. There is a clear need for more extensive observations of ET, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture–ET feedbacks, particularly across the Sahel.

Soil Moisture–Evapotranspiration Coupling in CMIP5 Models: Relationship with Simulated Climate and Projections

Soil moisture–atmosphere coupling is a key process underlying climate variability and change over land. The control of soil moisture (SM) on evapotranspiration (ET) is a necessary condition for soil moisture to feed back onto surface climate. Here we investigate how this control manifests itself across simulations from the CMIP5 ensemble, using correlation analysis focusing on the interannual (summertime) time scale. Analysis of CMIP5 historical simulations indicates significant model diversity in SM–ET coupling in terms of patterns and magnitude. We investigate the relationship of this spread with differences in background simulated climate. Mean precipitation is found to be an important driver of model spread in SM–ET coupling but does not explain all of the differences, presumably because of model differences in the treatment of land hydrology. Compared to observations, some land regions appear consistently biased dry and thus likely overly soil moisture–limited. Because of ET feedbacks on air temperature, differences in SM–ET coupling induce model uncertainties across the CMIP5 ensemble in mean surface temperature and variability. We explore the relationships between model uncertainties in SM–ET coupling and climate projections. In particular over mid-to-high-latitude continental regions of the Northern Hemisphere but also in parts of the tropics, models that are more soil moisture–limited in the present tend to warm more in future projections, because they project less increase in ET and (in midlatitudes) greater increase in incoming solar radiation. Soil moisture–atmosphere processes thus contribute to the relationship observed across models between summertime present-day simulated climate and future warming projections over land.

Multiscale Land–Atmosphere Coupling and Its Application in Assessing Subseasonal Forecasts over East Asia

Abstract The land surface, with a memory longer than the atmosphere in nature, has been recognized as an important source for Subseasonal to Seasonal (S2S) predictability through land–atmosphere coupling at multiple time scales. Understanding of the land–atmosphere coupling is important for improving subseasonal forecasting that is expected to fill the gap between medium-range weather forecasts and seasonal forecasts. Based on reanalysis and S2S reforecast datasets, land–atmosphere coupling is investigated over East Asia from daily to monthly time scales during summertime. Reanalysis results show that soil moisture–evapotranspiration (ET) coupling is closely related to the monsoonal rain belt shift. The coupling can be significant over humid regions (e.g., south China) during postmonsoon periods, where soil is usually drier, but insignificant over semiarid regions (e.g., north China) after the arrival of a monsoon, where soil is wetter. The dependence of soil moisture–ET coupling on soil wetness conditions decreases as the time scale increases, indicating more significant coupling at longer time scales. Similar sensitivities to time scales are found between ET and lifting condensation level (LCL), and between ET and precipitation, especially over land–atmosphere coupling hotspots. Monthly coupling strength analysis shows that ET–LCL coupling is a key process that determines the soil moisture–precipitation coupling, and the response of convective instability to ET is stronger at longer time scales. Subseasonal forecasting models also show more significant land–atmosphere coupling at monthly than daily time scales, where the ECMWF and NCEP models that best reproduce the coupling and its changes with monsoonal rain belt shifts have the best precipitation forecast skill among S2S models.

Regional Features and Seasonality of Land–Atmosphere Coupling over Eastern China

Land–atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture (SM) on evapotranspiration (ET) and further surface temperature (ST) is an important aspect of such coupling. Using ERA-Interim data and CLM4.0 offline simulation results, this study further explores the relationships between SM/ST and ET to better understand the complex nature of the land–atmosphere coupling (i.e., spatial and seasonal variations) in eastern China, a typical monsoon area. It is found that two diagnostics of land–atmosphere coupling (i.e., SM–ET correlation and ST–ET correlation) are highly dependent on the climatology of SM and ST. By combining the SM–ET and ST–ET relationships, two “hot spots” of land–atmosphere coupling over eastern China are identified: Southwest China and North China. In Southwest China, ST is relatively high throughout the year, but SM is lowest in spring, resulting in a strong coupling in spring. However, in North China, SM is relatively low throughout the year, but ST is highest in summer, which leads to the strongest coupling in summer. Our results emphasize the dependence of land–atmosphere coupling on the seasonal evolution of climatic conditions and have implications for future studies related to land surface feedbacks.

Effects of micro-topography and vegetation type on soil moisture in a large gully on the Loess Plateau of China

Abstract Large gullies occur globally and can be classified into four main micro-topographic types: ridges, plane surfaces, pipes and cliffs. Afforestation is an effective method of controlling land degradation worldwide. However, the combined effects of afforestation and micro-topography on the variability of soil moisture remain poorly understood. The primary objectives of this study were to determine whether afforestation affects the spatial pattern of the root-zone (0–100 cm) soil moisture and whether soil moisture dynamics differ among the micro-topographic types in gully areas of the Chinese Loess Plateau. The results showed that in the woodland regions, the spatial mean moisture values decreased by an average of 6.2% and the spatial variability increased, as indicated by the standard deviation (17.1%) and the coefficient of variation (22.2%). In general, different micro-topographic types exerted different influences on soil moisture behavior. The plane surface presented the largest average soil moisture values and the smallest spatial variability. The lowest soil moisture values were observed in the ridge, mainly due to the rapid drainage of these areas. Although pipe woodland region can concentrate surface runoff during and after rainfall, the larger trees growing in these areas can lead to increased soil moisture evapotranspiration.

Irrigation Effects on Land–Atmosphere Coupling Strength in the United States

Abstract Land–atmosphere coupling strength describes the degree to which the atmosphere responds (e.g., via changes in precipitation) to changes in the land surface state (e.g., soil moisture). The Midwest and Great Plains of the United States have been shown to be “hot spots” of coupling by many climate models and some observations. However, very few of the modeling studies have reported whether the climate models applied irrigation in the Midwest and Great Plains, where 24%–27% of farmland is irrigated, leaving open the question of whether irrigation affects current estimates of coupling strength. This study used a regional climate model that incorporated dynamic crop growth and precision irrigation (WRF3.3–CLM4crop) to investigate irrigation effects on land–atmosphere coupling strength. Coupling strength was quantified using multiple indices and the irrigated land-induced precipitation was tracked using a back trajectory method. The indices showed a consistent and significant decline in local coupling strength with irrigation in the Midwest and northern Great Plains. These reductions were due to increased soil moisture but decreased local precipitation and lower sensitivity of latent heat flux to soil moisture over irrigated regions. The back trajectories of water vapor transport confirmed that irrigation largely did not contribute to local precipitation. Water vapor from irrigated land was transported to the Midwest and U.S. Northeast where it fell as precipitation, suggesting that irrigation has a broader spatial impact on soil moisture–precipitation coupling than simply through local soil moisture–evapotranspiration coupling. The present study suggests that climate models without irrigation schemes may overestimate the land–atmosphere coupling strength over irrigated agricultural regions but underestimate coupling strength over neighboring nonirrigated regions.

A comparison of estimates of basin-scale soil-moisture evapotranspiration and estimates of riparian groundwater evapotranspiration with implications for water budgets in the Verde Valley, Central Arizona, USA

Population growth in the Verde Valley in Arizona has led to efforts to better understand water availability in the watershed. Evapotranspiration (ET) is a critical factor in estimating groundwater recharge in the area and a substantial component of the groundwater budget. In this study, two estimates of soil-moisture ET and two estimates of groundwater ET in the Verde Valley are presented and discussed. Basin-scale soil-moisture potential ET (PET) estimates from the soil-water balance (SWB) and basin characteristics model (BCM) groundwater recharge models are compared. Separately, riparian groundwater ET estimated from a method that uses MODIS-EVI remote sensing data and geospatial information, and from the MODFLOW-EVT ET package as part of a regional groundwater-flow model that includes the study area, are also discussed. Somewhat higher PET rates from the SWB recharge model resulted in an average annual ET volume about 17% greater than for PET from the BCM recharge model. For groundwater ET estimates, annual ET volumes were about the same for upper-bound MODIS-EVI ET for perennial reaches of streams as for the MODFLOW ET estimates, with the small differences between the two methods having minimal impact on annual or longer groundwater budgets for the study area.

Pathways between soil moisture and precipitation in southeastern South America

AbstractSoutheastern South America (SESA) is found to be the main hot spot of soil moisture–evapotranspiration coupling of South America during a dry summer. However, only its eastern part is a soil moisture–precipitation hot spot. Pathways between soil moisture and precipitation are evaluated through studying the coupling of soil moisture with surface and boundary layer variables. The outcome suggests that both the moist static energy and its vertical gradient are important for the development of precipitation, as a result of the total surface heat fluxes that are affected by soil moisture only in the eastern part of SESA.

Effect of land cover on atmospheric processes and air quality over the continental United States – a NASA Unified WRF (NU-WRF) model study

Abstract. The land surface plays a crucial role in regulating water and energy fluxes at the land–atmosphere (L–A) interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL) evolution, and precipitation through soil-moisture–evapotranspiration coupling. In turn, it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L–A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF) modeling system couples NASA's Land Information System (LIS) with the community WRF model and allows users to explore the L–A processes and feedbacks. Three commonly used satellite-derived land cover datasets – i.e., from the US Geological Survey (USGS) and University of Maryland (UMD), which are based on the Advanced Very High Resolution Radiometer (AVHRR), and from the Moderate Resolution Imaging Spectroradiometer (MODIS) – bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g., stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.

Land Surface Controls on Hydroclimatic Means and Variability

Abstract Hydroclimatic means and variability are determined in large part by the control of soil moisture on surface moisture fluxes, particularly evapotranspiration and runoff. This control is examined here using a simple water balance model and multidecadal observations covering the conterminous United States. Under the assumption that the relevant soil moisture–evapotranspiration and soil moisture–runoff relationships are, to first order, universal, the simple model illustrates the degree to which they interact to determine spatial distributions of hydroclimatic means and variability. In the process, the simple model provides estimates for the underlying relationships that operate in nature. The hydroclimatic sensitivities established with the simple water balance model can be used to evaluate more complex land surface models and to guide their further development, as demonstrated herein with an example.

Frequency of Sahelian storm initiation enhanced over mesoscale soil-moisture patterns

Evapotranspiration of soil moisture can affect temperature and humidity in the lower atmosphere, and thereby the development of convective rain storms. Climate models have illustrated the importance of soil-moisture–precipitation feedbacks for weekly rainfall totals in semi-arid regions, such as the Sahel1. However, large variations exist between model feedbacks, and the mechanisms governing the strength and sign of the feedback are uncertain. Here, we use satellite observations of land surface temperatures and convective cloud cover over West Africa—collected during the wet seasons between 2006 and 2010—to determine the impact of soil moisture on rainfall in the Sahel. We show that variations in soil moisture on length scales of approximately 10–40 km exert a strong control on storm initiation—as evidenced by the appearance of convective cloud. The probability of convective initiation is doubled over strong soil-moisture gradients compared with that over uniform soil-moisture conditions. We find that 37% of all storm initiations analysed occurred over the steepest 25% of soil-moisture gradients. We conclude that heterogeneities in soil moisture on scales of tens of kilometres have a pronounced impact on rainfall in the Sahel, and suggest that similar processes may be important throughout the semi-arid tropics.

Summer soil—precipitation coupling in South America

The soil moisture memory contributes to atmospheric variability and seasonal predictability and could potentially affect the development of the South American Monsoon System. The relative importance of the local land surface feedbacks and the large-scale dynamical processes during the different phases of the monsoon are still largely unknown. We examine the impacts of land surface conditions during the mature monsoon phase with the Rossby Centre Atmospheric regional model through calculating the coupling strength between soil moisture, evapotranspiration and precipitation. Regions of high coupling strength (hotspots) are identified and analysed focusing on the link between soil moisture—evapotranspiration coupling and soil moisture—precipitation coupling, the relation between the coupling strength and seasonal predictability and the hotspots importance for extreme precipitation events. La Plata Basin and northeastern Brazil are identified as hotspots due to evapotranspiration recycling. A region within the South Atlantic Convergence Zone is identified as a hotspot of precipitation explained by moisture advection. Extreme precipitation events are repressed in parts of La Plata Basin when the link between precipitation and soil moisture is cut through using prescribed soil moisture.