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Soil Moisture in the Climate System

The moisture held within the top meter or two of soil is a very tiny fraction (less than 0.01) of the Earthstotal water (Eagleson, 1970). Nevertheless, its presence at the interface of the land and atmosphere gives it inordinateimportance in the context of climate variability. Simply put, soil moisture variations can help determine meteorologicalvariations. Consider, for example, an anomalously high evapotranspiration rate induced by a high soil moisture content.The high evapotranspiration can lead to an anomalously cooled land surface and thus cooler air temperatures(Seneviratne et al. 2010), and it can also lead to modifications in the evolution of the boundary layer, with concomitantimpacts on the generation of convective rainfall (Betts et al., 1994).Given this potential for feedback on the atmosphere,soil moisture is particularly important in the context of prediction. Atmospheric physics and dynamics are fast andcontribute little to the lifetime of an atmospheric anomaly, as reflected in the well-known time scale of typical weatherforecaststhese rely heavily on atmospheric initialization and are valid for only a week or so. Soil moisture processes, incontrast, are relatively slow. A soil moisture anomaly may persist for a month or more and is thus predictable at such timescales. As a result, and because (as noted above) the atmosphere may respond in a predictable way to a given soilmoisture anomaly, aspects of the atmosphere may also be predictable at the monthly time scale (NRC, 2010).

Koster, Randal↗

Uncooled Doped-Si Thermopiles for Thermal Land Imaging Applications

Sustained and enhanced land imaging is crucial for providing high-quality science data on change in land use, forest health, environment, and climate. Future thermal land imaging instruments operating in the 10-12 micron band will provide essential information for furthering our hydrologic understanding at scales of human influence, and producing field-scale moisture information through accurate retrievals of evapotranspiration (ET). To address the need for cost-effective future thermal land imaging missions we are developing novel uncooled doped-silicon thermopile detectors, an extension of a detector design concept originally developed at NASA-Goddard for planetary science applications. These doped-Si thermopile detectors have the potential to offer superior performance in terms of sensitivity, speed, and customization, when compared to current commercial-off-the-shelf uncooled detector technologies. Because cryocooler technology does not need to be fielded on the instrument, these and other uncooled detectors offer the benefit of greatly reduced instrument cost, mass, and power at the expense of some acceptable loss in detector sensitivity. We present the motivation for an uncooled thermal imaging instrument, our doped-Si thermopile detector concept, and performance expectations and comparisons. We also provide an update on the current status of this detector technology development.

Thermopiles↗

Uncooled Doped-Si Thermopiles for Thermal Land Imaging Applications

Sustained and enhanced land imaging is crucial for providing high-quality science data on change in land use, forest health, environment, and climate. Future thermal land imaging instruments operating in the 10-12 micron band will provide essential information for furthering our hydrologic understanding at scales of human influence, and producing field-scale moisture information through accurate retrievals of evapotranspiration (ET). To address the need for cost-effective future thermal land imaging missions we are developing novel uncooled doped-silicon thermopile detectors, an extension of a detector design originally developed at NASA-Goddard for planetary science applications (Lakew et al. 2016). These doped-Si thermopile detectors have the potential to offer superior performance in terms of sensitivity, speed and customizability, when compared to current commercial-off-the-shelf uncooled detector technologies. Because cryocooling technology does not need to be fielded on the instrument, these and other uncooled detectors offer the benefit of greatly reduced instrument cost, mass, and power at the expense of some acceptable loss in detector sensitivity. We present an overview of our thermal imaging instrument concept, our doped-Si thermopile detector concept, and performance expectations and comparisons. We also provide an update on the current status of this detector technology development

Barrentine, Emily M.↗

Towards Effective Drought Monitoring in the Middle East and North Africa (Mena) Region: Implications From Assimilating Leaf Area Index and Soil Moisture Into the Noah-Mp Land Surface Model for Morocco

The Middle East and North Africa (MENA) region has experienced more frequent and severe drought events in recent decades, leading to increasingly pressing concerns over already strained food and water security. An effective drought monitoring and early warning system is thus critical to support risk mitigation and management by countries in the region. Here we investigate the potential for assimilation of leaf area index (LAI) and soil moisture observations to improve the representation of the overall hydrological and carbon cycles and drought by an advanced land surface model. The results reveal that assimilating soil moisture does not meaningfully improve model representation of the hydrological and biospheric processes for this region, but instead it degrades the simulation of the interannual variation in evapotranspiration (ET) and carbon fluxes, mainly due to model weaknesses in representing prognostic phenology. However, assimilating LAI leads to greater improvement, especially for transpiration and carbon fluxes, by constraining the timing of simulated vegetation growth response to evolving climate conditions. LAI assimilation also helps to correct for the erroneous interaction between the prognostic phenology and irrigation during summertime, effectively reducing a large positive bias in ET and carbon fluxes. Independently assimilating LAI or soil moisture alters the categorization of drought, with the differences being greater for more severe drought categories. We highlight the vegetation representation in response to changing land use and hydroclimate as one of the key processes to be captured for building a successful drought early warning system for the MENA region.

Wanshu Nie↗

Lidar Observations of Atmospheric CO2 Column During 2014 Summer Flight Campaigns

Advanced knowledge in atmospheric CO2 is critical in reducing large uncertainties in predictions of the Earth' future climate. Thus, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) from space was recommended by the U.S. National Research Council to NASA. As part of the preparation for the ASCENDS mission, NASA Langley Research Center (LaRC) and Exelis, Inc. have been collaborating in development and demonstration of the Intensity-Modulated Continuous-Wave (IM-CW) lidar approach for measuring atmospheric CO2 column from space. Airborne laser absorption lidars such as the Multi-Functional Fiber Laser Lidar (MFLL) and ASCENDS CarbonHawk Experiment Simulator (ACES) operating in the 1.57 micron CO2 absorption band have been developed and tested to obtain precise atmospheric CO2 column measurements using integrated path differential absorption technique and to evaluate the potential of the space ASCENDS mission. This presentation reports the results of our lidar atmospheric CO2 column measurements from 2014 summer flight campaign. Analysis shows that for the 27 Aug OCO-2 under flight over northern California forest regions, significant variations of CO2 column approximately 2 ppm) in the lower troposphere have been observed, which may be a challenge for space measurements owing to complicated topographic condition, heterogeneity of surface reflection and difference in vegetation evapotranspiration. Compared to the observed 2011 summer CO2 drawdown (about 8 ppm) over mid-west, 2014 summer drawdown in the same region measured was much weak (approximately 3 ppm). The observed drawdown difference could be the results of the changes in both meteorological states and the phases of growing seasons. Individual lidar CO2 column measurements of 0.1-s integration were within 1-2 ppm of the CO2 estimates obtained from on-board in-situ sensors. For weak surface reflection conditions such as ocean surfaces, the 1- s integrated signal-to-noise ratio (SNR) of lidar measurements at 11 km altitude reached 376, which was equivalent to a 10-s CO2 error 0.33 ppm. For the entire processed 2014 summer flight campaign data, the mean differences between lidar remote sensed and in-situ estimated CO2 values were about -0.013 ppm. These results indicate that current laser absorption lidar approach could meet space measurement requirements for CO2 science goals.

Lin, Bing↗

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

A Comparison of Groundwater Storage Using GRACE Data, Groundwater Levels, and a Hydrological Model in Californias Central Valley

The Gravity Recovery and Climate Experiment (GRACE) measures changes in total water storage (TWS) remotely, and may provide additional insight to the use of well-based data in California's agriculturally productive Central Valley region. Under current California law, well owners are not required to report groundwater extraction rates, making estimation of total groundwater extraction difficult. As a result, other groundwater change detection techniques may prove useful. From October 2002 to September 2009, GRACE was used to map changes in TWS for the three hydrological regions (the Sacramento River Basin, the San Joaquin River Basin, and the Tulare Lake Basin) encompassing the Central Valley aquifer. Net groundwater storage changes were calculated from the changes in TWS for each of the three hydrological regions and by incorporating estimates for additional components of the hydrological budget including precipitation, evapotranspiration, soil moisture, snow pack, and surface water storage. The calculated changes in groundwater storage were then compared to simulated values from the California Department of Water Resource's Central Valley Groundwater- Surface Water Simulation Model (C2VSIM) and their Water Data Library (WDL) Geographic Information System (GIS) change in storage tool. The results from the three methods were compared. Downscaling GRACE data into the 21 smaller Central Valley sub-regions included in C2VSIM was also evaluated. This work has the potential to improve California's groundwater resource management and use of existing hydrological models for the Central Valley.

Department of Water Resources↗

Remote Sensing of Evaporation

Evaporation of water from the Earth's surface into the atmosphere is central to the terrestrial energy, water and carbon cycle. Remote sensing approaches to measure evaporation (ET) combine observable inputs to the energy and water balance within statistical or process-based methodologies. These ET products draw on satellite observations from across the electro-magnetic spectrum. The ET retrievals are grouped in two main categories. One category includes approaches that combine meteorological descriptions of potential evaporation with a range of strategies to estimate evaporative stress. A second category includes surface energy balance approaches that retrieve latent heat from the thermal signatures. For each category a practical implementation example is described, including an outlook on progress towards multi-model assessment of global evaporation.

Transpiration↗

Chapter Five - Remote sensing techniques for estimating evaporation

Evaporation of water from the Earth’s surface into the atmosphere is central to the terrestrial energy, water, and carbon cycle. Remote sensing approaches to measure evaporation (ET) combine observable inputs to the energy and water balance within statistical or process-based methodologies. These ET products draw on satellite observations from across the electromagnetic spectrum. The ET retrievals are grouped in two main categories. One category includes approaches that combine meteorological descriptions of potential evaporation with a range of strategies to estimate evaporative stress. A second category includes surface energy balance approaches that retrieve latent heat from the thermal signatures. For each category a practical implementation example is described, including an outlook on progress towards multimodel assessment of global evaporation.

Evaporation↗

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Soil Moisture↗

Past and Future Drought in Mongolia

The severity of recent droughts in semiarid regions is increasingly attributed to anthropogenic climate change, but it is unclear whether these moisture anomalies exceed those of the past and how past variability compares to future projections. On the Mongolian Plateau, a recent decade-long drought that exceeded the variability in the instrumental record was associated with economic, social, and environmental change. We evaluate this drought using an annual reconstruction of the Palmer Drought Severity Index (PDSI) spanning the last 2060 years in concert with simulations of past and future drought through the year 2100 CE. We show that although the most recent drought and pluvial were highly unusual in the last 2000 years, exceeding the 900-year return interval in both cases, these events were not unprecedented in the 2060-year reconstruction, and events of similar duration and severity occur in paleoclimate, historical, and future climate simulations. The Community Earth System Model (CESM) ensemble suggests a drying trend until at least the middle of the 21st century, when this trend reverses as a consequence of elevated precipitation. Although the potential direct effects of elevated CO2 on plant water use efficiency exacerbate uncertainties about future hydroclimate trends, these results suggest that future drought projections for Mongolia are unlikely to exceed those of the last two millennia, despite projected warming.

drought projection↗

Understanding land surface evapotranspiration with satellite multispectral measurements

Quantitative use of remote multispectral measurements to study and map land surface evapotranspiration has been a challenging issue for the past 20 years. Past work is reviewed against process physics. A simple two-layer combination-type model is used which is applicable to both vegetation and bare soil. The theoretic analysis is done to show which land surface properties are implicitly defined by such evaporation models and to assess whether they are measurable as a matter of principle. Conceptual implications of the spatial correlation of land surface properties, as observed by means of remote multispectral measurements, are illustrated with results of work done in arid zones. A normalization of spatial variability of land surface evaporation is proposed by defining a location-dependent potential evaporation and surface temperature range. Examples of the application of remote based estimates of evaporation to hydrological modeling studies in Egypt and Argentina are presented.

Menenti, M.↗

Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa

West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite-based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003–2016 and used to initialize 6-month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE-DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE-DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast, and water-related disaster warning systems for Africa.

Augusto Getirana↗

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗

Cherokee Water Resources Project Summary - Mapping Forest Composition and Health in the Southern Appalachians Using NASA Earth Observations to Enhance Drought and Watershed Health-Related Forest Management for the Eastern Band of the Cherokee Indians

The Eastern Band of Cherokee Indians (EBCI) owns and manages more than 55,000 acres of land in the Southern Appalachian Mountains of western North Carolina. Most of these lands reside within the Oconaluftee River watershed. In this region and watershed, hemlock trees are a culturally significant foundation species that contribute to habitat biodiversity, regulate temperature and evapotranspiration of riparian environments, and provide economic value for tourism and recreation. The hemlock woolly adelgid (HWA), an invasive insect, has caused widespread hemlock mortality in recent decades, raising concerns about hemlock decline. Hemlock mortality leads to standing dead trees and increased evapotranspiration which can abet the spread of wildfires, especially during periods of drought. The DEVELOP team used satellite imagery from Landsat 5 Thematic Mapper (TM) to quantify and map possible hemlock decline by comparing changes in the normalized difference vegetation index (NDVI) values of winter season between 2003 and 2010. The project utilized the Shuttle Radar Topography Mission (SRTM) along with imagery from Landsat 8 Operational Land Imager (OLI) to create a weighted suitability analysis that maps topographic and environmental conditions favorable for hemlock habitat. This study found that 67%of evergreen and mixed forest cover in the Oconaluftee River valley exhibited a decrease in winter NDVI from 2003 to 2010. Additionally, the two-example weighted suitability analyses showed 4.5-9.5% of hemlock suitable land in 2018 in the Oconaluftee. The partners of this project can use the outputs to identify the extent of potential hemlock decline in the Oconaluftee and establish benchmark metrics for assessing changes in hemlock suitable areas over time.

DEVELOP Project Summary↗

Cherokee Water Resources - Mapping Hemlock Tree Composition and Health in the Southern Appalachians Using NASA Earth Observations to Enhance Drought and Watershed Health-Related Forest Management for the Eastern Band of the Cherokee Indians

The Eastern Band of Cherokee Indians (EBCI) owns and manages more than 55,000 acres of land in the Southern Appalachian Mountains of western North Carolina. Most of these lands reside within the Oconaluftee River watershed. In this region and watershed, hemlock trees are a culturally significant foundation species that contribute to habitat biodiversity, regulate temperature and evapotranspiration of riparian environments, and provide economic value for tourism and recreation. The hemlock woolly adelgid (HWA), an invasive insect, has caused widespread hemlock mortality in recent decades, raising concerns about hemlock decline. Hemlock mortality leads to standing dead trees and increased evapotranspiration which can abet the spread of wildfires, especially during periods of drought. The DEVELOP team used satellite imagery from Landsat 5 Thematic Mapper (TM) to quantify and map possible hemlock decline by comparing changes in the normalized difference vegetation index (NDVI) values of winter season between 2003 and 2010. The project utilized the Shuttle Radar Topography Mission (SRTM) along with imagery from Landsat 8 Operational Land Imager (OLI) to create a weighted suitability analysis that maps topographic and environmental conditions favorable for hemlock habitat. This study found that 67% of evergreen and mixed forest cover in the Oconaluftee River valley exhibited a decrease in winter NDVI from 2003 to 2010. Additionally, the two-example weighted suitability analyses showed 4.5-9.5% of hemlock suitable land in 2018 in the Oconaluftee. The partners of this project can use the outputs to identify the extent of potential hemlock decline in the Oconaluftee and establish benchmark metrics for assessing changes in hemlock suitable areas over time.

Richard Murray↗

Evapotranspiration Based Irrigation Trials Examine Water Requirement, Nitrogen Use, and Yield of Romaine Lettuce in the Salinas Valley

Cool season vegetables require adequate soil moisture to assure that maximum yield and quality are achieved. On California’s central coast, where the majority of cool season vegetables are produced in the US, long-term overpumping of irrigation water has reduced groundwater levels and led to environmental degradation. Two evapotranspiration (ET) based irrigation field trials were performed near Salinas CA (USA) to determine if ET-based irrigation scheduling could conserve water while producing romaine lettuce (cv. Sun Valley) of commercially viable yield. Sprinklers were used for seed germination and crop establishment. Four drip irrigation treatments were then imposed using a randomized complete block design with six replications. The CropManage decision support model was used to estimate the full (100%) crop water requirement based mainly on ET replacement. Other treatments included 50% 75% and 150% of the full water requirement. The 100% treatment received 185 mm of water in 2015 and 247 mm in 2016, both of which were well below prior guidance and grower reports. Yields from the 100% and 150% treatments were not significantly different and were similar to industry average, while yields were significantly lower for the 50% and 75% treatments. The 100% treatment had the highest water use efficiency, and the 100% and 150% treatments together had the highest nitrogen recovery efficiency. Irrigation of romaine near the 100% ET replacement level can potentially reduce environmental impacts associated with nitrate leaching and surface runoff.

CropManage decision support system↗

The Simulation and Subseasonal Forecasting of Hydrological Variables: Insights from a Simple Water Balance Model

Past work has shown that a land surface model’s (LSM’s) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the U.S., and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in-situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in Nature and can serve as potentially useful targets for further LSM development.

Water Balance Model↗