nasa-gesdisc/es-publications-researchareas huggingface dataset:
Estimating spatially explicit irrigation water use based on remotely sensed evapotranspiration and modeled root zone soil moisture (2021)

Estimation of irrigation water use (IWU) is critical to assessing water use efficiency and optimizing water resource allocation. However, diversity in irrigation scheduling, irrigation system, and crop type has imposed restrictions on deriving the accurate spatial distribution of IWU. Existing approaches of deriving IWU may have large uncertainty, due mostly to methodological limitations, inadequate inputs, and the mismatch in spatiotemporal scale between IWU estimates and in situ counterparts. Remote sensing has the potential to provide valuable information on moisture transport, which could unravel water consumption by crops. First, we developed a robust relationship between root zone soil moisture (RZSM) and the ratio of actual evapotranspiration (ET<SUB>a</SUB>) to reference ET from the land components of European ReAnalysis-5 (ERA5L) without an irrigation module across the Contiguous United States (CONUS). Second, RZSM under irrigation was derived from the developed relationship and remotely sensed ET<SUB>a</SUB> from the operational Simplified Surface Energy Balance (SSEB<SUB>op</SUB>) model during 2000-2020. Third, IWU over the two decades was derived based on increases in RZSM and ET<SUB>a</SUB> due to irrigation using remotely sensed and model-based variables, along with our derived formulas considering groundwater recharge originating from irrigation. The IWU estimates were fairly reliable compared with reported IWU from the Farm and Ranch Irrigation Survey at the state-level in four years, with the coefficient of determination ranging from 0.74 to 0.84, root mean square error ranging from 1.90 to 2.33 km<SUP>3</SUP>/yr, and bias ranging from -0.11 to 0.15 km<SUP>3</SUP>/yr. Integration of remotely sensed ET<SUB>a</SUB> with ERA5L output resulted in IWU estimates of much higher accuracy than published studies. The IWU estimates across the CONUS reflected an increasing trend (∼2.71 km<SUP>3</SUP>/yr<SUP>2</SUP>) during 2000-2007 but a decreasing trend (∼0.90 km<SUP>3</SUP>/yr<SUP>2</SUP>) during 2008-2020, due to efficient irrigation practices and increased precipitation.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators
Large scale tropical deforestation drives extreme warming (2020)

Accelerating deforestation rates in Earth's tropical rainforests have dramatic impacts on local public health, agricultural productivity, and global climate change. We used satellite observations to quantify the local temperature changes in deforested patches of rainforests across the tropics and found local warming larger than that predicted from more than a century of climate change under a worst-case emissions scenario. We show that the most extreme warming is typically found in large patches of deforestation; the combined effects of deforestation and climate change on tropical temperatures present a uniquely difficult challenge to the long term public health, occupational safety, and economic security of tropical populations.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators, Atmospheric/Ocean Indicators
Giving credit to reforestation for water quality benefits (2019)

While there is a general belief that reforesting marginal, often unprofitable, croplands can result in water quality benefits, to date there have been very few studies that have attempted to quantify the magnitude of the reductions in nutrient (N and P) and sediment export. In order to determine the magnitude of a credit for water quality trading, there is a need to develop quantitative approaches to estimate the benefits from forest planting in terms of load reductions. Here we first evaluate the availability of marginal croplands (i.e. those with low infiltration capacity and high slopes) within a large section of the Ohio River Basin (ORB) to assess the magnitude of the land that could be reforested. Next, we employ the Nutrient Tracking Tool (NTT) to study the reduction in N, P and sediment losses from converting corn or corn/soy rotations to forested lands, first in a case study and then for a large region within the ORB. We find that after reforestation, N losses can decrease by 40 to 80 kg/ha-yr (9597% reduction), while P losses decrease by 1 to 4 kg/ha-yr (9699% reduction). There is a significant influence of local conditions (soils, previous crop management practices, meteorology), which can be considered with NTT and must be taken into consideration for specific projects. There is also considerable interannual and monthly variability, which highlights the need to take the longer view into account in nutrient credit considerations for water quality trading, as well as in monitoring programs. Overall, there is the potential for avoiding 60 million kg N and 2 million kg P from reaching the streams and rivers of the northern ORB as a result of conversion of marginal farmland to tree planting, which is on the order of 12% decrease for TN and 5% for TP, for the entire basin. Accounting for attenuation, this represents a significant fraction of the goal of the USEPA Gulf of Mexico Hypoxia Task Force to reduce TN and TP reaching the dead zone in the Gulf of Mexico, the second largest dead zone in the world. More broadly, the potential for targeted forest planting to reduce nutrient loading demonstrated in this study suggests further consideration of this approach for managing water quality in waterways throughout the world. The study was conducted using computational models and there is a need to evaluate the results with empirical observations.

Research areas: Habitat Conversion/Fragmentation, Water Quality
Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled … (2020)

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajos National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

Research areas: Habitat Conversion/Fragmentation, Ecosystems
Recent forest area increase in Europe: Expanding and regenerating forests differ in their regional patterns, drivers and productivity trends (2021)

In Europe, forest area is increasing. These recently established forests can be classified into regenerating after disturbances or expanding into agricultural areas after abandonment. We used European Space Agency land cover maps and MODIS data to investigate which socioenvironmental drivers influenced recent forest expansion and regeneration in Europe from 1992 to 2015 and to compare their productivity by means of the Enhanced Vegetation Index (EVI). Our results showed that forest area increased in Europe by 1.4% from 1992 to 2015. The 66% of this forest area increase corresponded to forest expansion mostly in Mediterranean and temperate regions, while regeneration (34%) dominated in boreal areas. Forest area and land cover diversity in 1992 were the main drivers of local forest area increase from 1992 to 2015. Forest expansion occurred on the warmer zones far from urban areas in the boreal region while it was the opposite in temperate and Mediterranean areas. On the other hand, forest regeneration showed mostly a positive relation with the distance to urban areas and water availability but no relation with temperature. The EVI values in 2015 were higher in expanding than in regenerating forests except in the warmer and drier bioclimates of Europe. These EVI trends suggest a higher productivity of expanding forests, except in areas where they cannot benefit from biological and physicochemical legacies of abandoned agricultural soils for tree growth, owing to water shortage. In sum, our results highlight that recent forest area increase in Europe is mostly caused by forest expansion into former agricultural areas but this is mostly occurring in less productive (warmer and drought-prone) bioclimates where advantages of agricultural legacies may not occur. Ultimately, this casts doubts whether there may be a limit for the role of forest expansion into agricultural areas for carbon sequestration in the long term.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators
Evaluation of urban land green utilization efficiency with a view of GIS images (2021)

The city is at the center of the growing strategy. There are high-cost issues with the production of energy and the environment. The strategy for environmentally friendly and sustainable development is limited. Therefore, if we assess the productivity of urban land use, it is of far-reaching value to use the idea of green growth as an assessment index. On the basis of input, planned production, and unforeseen output, nine indicators, including urban fixed capital stock, secondary and tertiary value-added, and SO2 emissions, are selected to create a research framework and related assessment indicators for the green use of urban land. Related data on the efficiency of urban land use in 12 districts and counties were collected from 2012 to 2018 to assess the efficiency of green land use in urban areas. The findings show that the productivity of green land use decreased significantly during the study period. Many cities in the province have set up a large number of industries, including those with high emissions and high usage. These industries have relocated inland from the eastern coastal regions, resulting in a decline in the rate of urban land use of green land in many towns. If we want to solve this issue, we need to change the framework of land use to follow empirical and fair methods for the rational use of land, to promote the green use of land, and to increase the level of assessment in order to improve the efficiency of green land use.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators
Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region (2022)

For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 20152018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 20002016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R2 =0.81; Kansas R2 =0.51) and temporal cross-validation (Colorado R2 =0.82; Kansas R2 =0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators
Global migration is driven by the complex interplay between (2021)

Migration manifests an important response and adaptation measure to changes in the environment and socioeconomic conditions. In a time when environmental stressors and risks are unprecedentedly increasing, understanding the interplay between the underlying factors driving migration is of high importance. While the relationships between environmental and socioeconomic drivers have been identified conceptually, the comprehensive global-scale spatial quantification of their interactions is in its infancy. Here, we performed a geospatial analysis of gridded global net migration from 1990 to 2000 using a novel machine learning approach which analyses the interplay between a set of societal and environmental factors simultaneously at the place of origins (areas of net-negative migration) and destinations (areas of net-positive migration). We diagnosed the importance of eight environmental and societal factors in explaining migration for each country, globally. Nearly half of global in- and out-migration took place in the areas characterized by low adaptive capacity and high environmental stress. Regardless of the income level, income was the key factor in explaining net-migration in half of the countries. Slow-onset environmental factors, drought and water risk, were found to be the dominant environmental variables globally. Our study highlights that factors representing human capacity need to be incorporated into the quantitative diagnosis of environmental migration more rigorously.

Research areas: Habitat Conversion/Fragmentation
Driving effects of urbanization on city-level carbon dioxide emissions: from multiple perspectives of urbanization (2020)

Cities have emerged as first responders in carbon dioxide emission reduction. However, it is a great dilemma for cities to reach high urbanization level and achieve carbon dioxide emission reduction. Chinese cities are in high speed of urbanization process both in urban-rural population structure change and land-use change. Although there are a large body of research studies exploring urbanization-carbon dioxide emission nexus, some limitations remain. Firstly, most research studies only one-sidedly define urbanization as demographic urbanization, but fail to focus on its land-use change; secondly, present studies more tend to reveal the relationship between urbanization and carbon dioxide emissions, but do not recognize main contributors. Thus, this study aims to explore the urbanization-carbon dioxide emission nexus in South Jiang Province during 20002016. Panel data model and impulse response function based on a vector autoregression (VAR) model are established as the methodology framework. Expressly, urban built-up area, entire built-up area and urban road area are selected to depict land-use change in urbanization process. The results indicate that population and gross regional domestic product (GRDP) are positively correlated with carbon dioxide emissions. The entire built-up area and urban road area are positively correlated with carbon dioxide emissions, while urban built-up area is negatively correlated with carbon dioxide emissions. However, there is little evidence to support the connection between demographic urbanization and carbon dioxide emissions. It is proved that all independent variables impact CO2 emissions in the long run in South Jiangsu Province. Importantly, population and GRDP remain the main contributors of carbon dioxide emissions, compared with urbanization. As such, it is more necessary for South Jiangsu Province to control the upsurge economy and population, especially the migration population. Concentrating compact city development is also critical. These policy implications are also for other Chinese cities.

Research areas: Habitat Conversion/Fragmentation, Air Quality
The biomass burning contribution to climate–carbon-cycle feedback (2018)

Abstract. Temperature exerts strong controls on the incidence and severity of fire. All else equal, warming is expected to increase fire-related carbon emissions, and thereby atmospheric CO2. But the magnitude of this feedback is very poorly known. We use a single-box model of the land biosphere to quantify this positive feedback from satellite-based estimates of biomass burning emissions for 20002014 CE and from sedimentary charcoal records for the millennium before the industrial period. We derive an estimate of the centennial-scale feedback strength of 6.5  3.4 ppm CO2 per degree of land temperature increase, based on the satellite data. However, this estimate is poorly constrained, and is largely driven by the well-documented dependence of tropical deforestation and peat fires (primarily anthropogenic) on climate variability patterns linked to the El NinoSouthern Oscillation. Palaeo-data from pre-industrial times provide the opportunity to assess the fire-related climatecarbon-cycle feedback over a longer period, with less pervasive human impacts. Past biomass burning can be quantified based on variations in either the concentration and isotopic composition of methane in ice cores (with assumptions about the isotopic signatures of different methane sources) or the abundances of charcoal preserved in sediments, which reflect landscape-scale changes in burnt biomass. These two data sources are shown here to be coherent with one another. The more numerous data from sedimentary charcoal, expressed as normalized anomalies (fractional deviations from the long-term mean), are then used  together with an estimate of mean biomass burning derived from methane isotope data  to infer a feedback strength of 5.6  3.2 ppm CO2 per degree of land temperature and (for a climate sensitivity of 2.8 K) a gain of 0.09  0.05. This finding indicates that the positive carbon cycle feedback from increased fire provides a substantial contribution to the overall climatecarbon-cycle feedback on centennial timescales. Although the feedback estimates from palaeo- and satellite-era data are in agreement, this is likely fortuitous because of the pervasive influence of human activities on fire regimes during recent decades.

Research areas: Environmental Impacts, Atmospheric/Ocean Indicators
State Failure, Violence, and Trade: Dangerous Trade Routes in Colombia (2021)

We investigate the effect of domestic armed violence brought about by political instability on the geography of distance frictions in freight mobility and the resulting differential access of regions to global markets. The Colombian transportation system has been found to be impeded by deficiencies in landside transport infrastructure and institutions, and by fragmented political environments. The micro-level analysis of U.S.-bounded export shipping records corroborates that export freight shipping from inland regions is re-routed to avoid exposures to domestic armed violence despite greatly extended landside and maritime shipping distances. We exploit the trajectories of freight shipping from Colombian regions and spatial patterns of violent armed conflicts to see how unstable geopolitical environments are detrimental to freight shipping mobility and market openness. The discrete choice model shows that the shipping flow is greatly curbed by the extended re-routing due to domestic armed violence and that inland regions have restricted access to the global market. The perception of risk and re-routing behavior is found heterogeneous across shipments and conditional to shipment characteristics, such as commodity type, freight value and shipper sizes. The results highlight that political stability must be accommodated for improved freight mobility and export-oriented economic development in the global South.

Research areas: Habitat Conversion/Fragmentation
Biomass burning and marine aerosol processing over the southeast Atlantic Ocean: a TEM single-particle analysis (2022)

Abstract. This study characterizes single-particle aerosol composition from filters collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoudAerosolRadiation Interaction and Forcing: Year 2017 (CLARIFY-2017) campaigns. In particular the study describes aged biomass burning aerosol (BBA), its interaction with the marine boundary layer and the influence of biomass burning (BB) air on marine aerosol. The study finds evidence of BBA influenced by marine boundary layer processing as well as sea salt influenced by BB air. Secondary chloride aerosols were observed in clean marine air as well as in BB-influenced air in the free troposphere. Higher-volatility organic aerosol appears to be associated with increased age of biomass burning plumes, and photolysis or oxidation may be a mechanism for the apparent increased volatility. Aqueous processing and interaction with the marine boundary layer air may be a mechanism for the presence of sodium on many aged potassium salts. By number, biomass burning potassium salts and modified sea salts are the most observed particles on filter samples. The most commonly observed BC coatings are inorganic salts. These results suggest that atmospheric processes such as photolysis, oxidation and cloud processing are key drivers in the elemental composition and morphology of aged BBA. Fresh BBA inorganic salt content, as it has an important role in the particles' ability to uptake water, may be a key driver in how aqueous processing and atmospheric aging proceed.

Research areas: Environmental Impacts, Atmospheric/Ocean Indicators