nasa-gesdisc/es-publications-researchareas huggingface dataset:
Green infrastructure and climate change impacts on the flows and water quality of urban catchments: Salmons Brook and Pymmes Brook in north-east London (2022)

Poor water quality is a widespread issue in urban rivers and streams in London. Localised pollution can have impacts on local communities, from health issues to environmental degradation and restricted recreational use of water. The Salmons and Pymmes Brooks, located in the London Borough of Enfield, flow into the River Lee, and in this paper, the impacts of misconnected sewers, urban runoff and atmospheric pollution have been evaluated. The first step towards finding a sustainable and effective solution to these issues is to identify sources and paths of pollutants and to understand their cycle through catchments and rivers. The INCA water quality model has been applied to the Salmons and Pymmes urban catchments in north-east London, with the aim of providing local communities and community action groups such as Thames21 with a tool they can use to assess the water quality issue. INCA is a process-based, dynamic flow and quality model, and so it can account for daily changes in temperature, flow, water velocity and residence time that all affect reaction kinetics and hence chemical flux. As INCA is process-based, a set of mitigation strategies have been evaluated including constructed wetland across the catchment to assess pollution control. The constructed wetlands can make a significant difference reducing sediment transport and improving nutrient control for nitrogen and phosphorus. The results of this paper show that a substantial reduction in nitrate, ammonium and phosphorus concentrations can be achieved if a proper catchment-scale wetland implementation strategy is put in place. Furthermore, the paper shows how the nutrient reduction efficiency of the wetlands should not be affected by climate change.

Research areas: Water Quality, Habitat Conversion/Fragmentation, Ecosystems
A multivariate empirical orthogonal function method to construct nitrate maps in the Southern Ocean (2018)

Abstract The ability to construct nitrate maps in the Southern Ocean (SO) from sparse observations is important for marine biogeochemistry research, as it offers a geographical estimate of biological productivity. The goal of this study is to infer the skill of constructed SO nitrate maps using varying data sampling strategies. The mapping method uses multivariate empirical orthogonal functions (MEOFs) constructed from nitrate, salinity, and potential temperature (N-S-T) fields from a biogeochemical general circulation model simulation Synthetic N-S-T datasets are created by sampling modeled N-S-T fields in specific regions, determined either by random selection or by selecting regions over a certain threshold of nitrate temporal variances. The first 500 MEOF modes, determined by their capability to reconstruct the original N-S-T fields, are projected onto these synthetic N-S-T data to construct time-varying nitrate maps. Normalized root-mean-square errors (NRMSEs) are calculated between the constructed nitrate maps and the original modeled fields for different sampling strategies. The sampling strategy according to nitrate variances is shown to yield maps with lower NRMSEs than mapping adopting random sampling. A k-means cluster method that considers the N-S-T combined variances to identify key regions to insert data is most effective in reducing the mapping errors. These findings are further quantified by a series of mapping error analyses that also address the significance of data sampling density. The results provide a sampling framework to prioritize the deployment of biogeochemical Argo floats for constructing nitrate maps.

Research areas: Water Quality, Atmospheric/Ocean Indicators
Remote sensing of suspended sediment concentration and hydrologic connectivity in a complex wetland environment (2013)

Maintaining the ecological diversity and hydrologic connectivity of freshwater delta systems depends on regular recharge of floodplains with river water, which can be difficult to observe on the ground. Rivers that form deltas often carry large amounts of suspended sediment, but floodplain lakes and wetlands usually have little sediment in suspension. Remote observation of high sediment water in lakes and wetlands therefore often indicates connectivity with the river network. In this study, we use daily 250-m MODIS imagery in band 1 (620670nm) and band 2 (841876nm) to monitor suspended sediment transport and, by proxy, hydrologic recharge in the PeaceAthabasca Delta, Canada. To identify an appropriate suspended sediment concentration (SSC)-reflectance model, we compare 31 published empirical equations using a field dataset containing 147 observations of SSC and in situ spectral reflectance. Results suggest potential for spatial transferability of such models, but success is contingent on the equation meeting certain criteria: 1) use of a near infrared band in combination with at least one visible band, 2) development based on SSCs similar to those in the observed region, and 3) a nonlinear form. Using a highly predictive SSC-reflectance model (Spearman's =0.95), we develop a twelve-year time series of SSC in the westernmost end of Lake Athabasca, observe the timing and sources of major sediment flux events, and identify a threshold river discharge of ~1700m3/s above which SSC in Lake Athabasca is clearly associated with flow in the Athabasca River. We also track the influx of Athabasca River water to floodplain lakes, and in three of the lakes identify distinct discharge thresholds (1040m3/s, 1150m3/s, and 1850m3/s) which result in lake recharge. For each of these lakes, we find a statistically significant decline in the threshold exceedence frequency since 1970, suggesting less frequent recharge during the summer.

Research areas: Water Quality, Land Surface/Agriculture Indicators
Spatial dynamics of biophysical trade-offs and synergies among ecosystem services in the Himalayas (2023)

The production of ecosystem services (ES) is highly dependent on the current state of spatial distribution, pattern of occurrence, and interaction among them, which is barely studied in the Hindu-Kush Himalayas (HKH). Taking a case of a multifunctional landscape in the central HKH region, we aimed to assess the biophysical production possibilities of major ES, their relationships and co-occurrence, and dynamic interactions at different spatial scales. We quantified and mapped six major ES (crop production, timber production, carbon sequestration, soil conservation, water yield, and habitat quality) at two spatial scales: landscape level (functional unit) and watershed level (management unit). Further, we analysed the relationship and interactions among all the possible pairs of the considered ES. All six ES were found to have a positive correlation, except crop production which showed a significant negative correlation with soil conservation. Moreover, we delineated 186 watersheds in the landscape and clustered them based on their biophysical potentials for the supply of ES. Gap statistics from K-means clustering identified three main clusters of watersheds (i.e., agriculture-dominated, poor-performing uplands, and multifunctional). The supply of ES from downstream watersheds was substantially higher than that of the upstream watersheds. We then discussed the interrelationships among ES at various spatial scales and suggested policy instruments for ecosystem management. The relationship among ES shows dynamic forms of spatial distribution, which need to be sustainably managed for minimizing trade-offs and maximizing synergies through the consideration of an integrated watershed management approach, improved agronomy practices, and global climate actions.

Research areas: Ecosystems, Habitat Conversion/Fragmentation
Multi-year, spatially extensive, watershed-scale synoptic stream chemistry and water quality conditions for six permafrost-underlain Arctic watersheds (2022)

Abstract. Repeated sampling of spatially distributed river chemistry can be used to assess the location, scale, and persistence of carbon and nutrient contributions to watershed exports. Here, we provide a comprehensive set of water chemistry measurements and ecohydrological metrics describing the biogeochemical conditions of permafrost-affected Arctic watersheds. These data were collected in watershed-wide synoptic campaigns in six stream networks across northern Alaska. Three watersheds are associated with the Arctic Long-Term Ecological Research site at Toolik Field Station (TFS), which were sampled seasonally each June and August from 2016 to 2018. Three watersheds were associated with the National Park Service (NPS) of Alaska and the U.S. Geological Survey (USGS) and were sampled annually from 2015 to 2019. Extensive water chemistry characterization included carbon species, dissolved nutrients, and major ions. The objective of the sampling designs and data acquisition was to characterize terrestrialaquatic linkages and processing of material in stream networks. The data allow estimation of novel ecohydrological metrics that describe the dominant location, scale, and overall persistence of ecosystem processes in continuous permafrost. These metrics are (1) subcatchment leverage, (2) variance collapse, and (3) spatial persistence. Raw data are available at the National Park Service Integrated Resource Management Applications portal (O'Donnell et al., 2021, https://doi.org/10.5066/P9SBK2DZ) and within the Environmental Data Initiative (Abbott, 2021, https://doi.org/10.6073/pasta/258a44fb9055163dd4dd4371b9dce945).

Research areas: Water Quality
Recent desiccation of western Great Basin saline lakes: lessons from Lake Abert, Oregon, USA (2016)

Although extremely important to migrating waterfowl and shorebirds, and highly threatened globally, most saline lakes are poorly monitored. Lake Abert in the western Great Basin, USA, is an example of this neglect. Designated a critical habitat under the Western Hemisphere Shorebird Reserve Network, the lake is at near record historic low levels and ultra-high salinities that have resulted in ecosystem collapse. Determination of the direct human effects and broader climate controls on Lake Abert illustrates the broader problem of saline lake desiccation and suggests future solutions for restoration of key habitat values. A 65-year time series of lake area was constructed from Landsat images and transformed to lake volume and salinity. Natural (without upstream withdrawals) conditions were calculated from climate and stream flow data, and compared to measured volume and salinity. Under natural conditions the lake would have higher volume and lower salinities because annual water withdrawals account for one-third of mean lake volume. Without withdrawals, the lake would have maintained annual mean salinities mostly within the optimal range of brine shrimp and alkali fly growth. Even during the last two years of major drought, the lake would have maintained salinities well below measured values. Change in climate alone would not produce the recent low lake volumes and high salinities that have destroyed the brine shrimp and alkali fly populations and depleted shorebird use at Lake Abert. Large scale withdrawal of water for direct human use has drastically increased the imbalance between natural runoff and evaporation during periods of drought in saline lakes worldwide but could be offset by establishing an environmental water budget to lay a foundation for the conservation of saline lake habitats under continued threats from development and climate change.

Research areas: Water Quality, Habitat Conversion/Fragmentation
Twenty years of change: Land and water resources in the Chindwin catchment, Myanmar between 1999 and 2019 (2021)

Since 2011, Myanmar has undergone a more rapid socio-economic development, which may substantially have affected land use and land cover (LULC) and water resources. This study investigates the changes in land and water resources of the Chindwin River catchment (114,686.9 km2) in Myanmar over a twenty-year timespan from 1999 to 2019. The main aim of this study is to assess LULC change and evaluate its effects on the water balance and the people in the region. To this end, interviews were conducted, LULC classifications based on multi-temporal multi-spectral satellite data and in-situ ground truth data were created, and a hydrologic model was built. The hydrologic model shows a reasonable performance for daily discharge simulation at the catchment outlet (percent bias between -2 and 13.2, Kling-Gupta Efficiency between 0.75 and 0.76, Nash-Sutcliffe Efficiency between 0.57 and 0.61, RMSE-observations standard deviation between 0.63 and 0.66). The LULC changes detected include a decrease in forest area of about 2%, an increase in shrubland area indicating increased degradation of the forest, an increase in mining areas of 0.38%, an overall decrease in agricultural area (2.1%), but also the presence of new agricultural land pointing toward relocation of agricultural areas and an indication of an increase in settlement areas (1.5%). With the help of the hydrologic model, the most significant hydrologic impacts detected were a decrease in evapotranspiration and an increase in water yield which is correlated with the decrease of forest at the sub-catchment scale (R2 = 0.72 and 0.46, respectively). Moreover, an increase of mining areas contributed to the increase in water yield (R2 = 0.62). Interviews confirm that the identified LULC changes deforestation and increased mining activities contribute to major issues, e.g., water pollution, sedimentation, and changes in the river course.

Research areas: Habitat Conversion/Fragmentation, Land Surface/Agriculture Indicators, Water Quality
Inorganic carbon speciation and fluxes in the Congo River (2013)

Seasonal variations in inorganic carbon chemistry and associated fluxes from the Congo River were investigated at Brazzaville-Kinshasa. Small seasonal variation in dissolved inorganic carbon (DIC) was found in contrast with discharge-correlated changes in pH, total alkalinity (TA), carbonate species, and dissolved organic carbon (DOC). DIC was almost always greater than TA due to the importance of CO<SUB>2</SUB>*, the sum of dissolved CO<SUB>2</SUB> and carbonic acid, as a result of low pH. Organic acids in DOC contributed 11-61% of TA and had a strong titration effect on water pH and carbonate speciation. The CO<SUB>2</SUB>* and bicarbonate fluxes accounted for ~57% and 43% of the DIC flux, respectively. Congo River surface water released CO<SUB>2</SUB> at a rate of ~109 mol m<SUP>-2</SUP> yr<SUP>-1</SUP>. The basin-wide DIC yield was ~8.84 × 10<SUP>4</SUP> mol km<SUP>-2</SUP> yr<SUP>-1</SUP>. The discharge normalized DIC flux to the ocean amounted to 3.11 × 10<SUP>11</SUP> mol yr<SUP>-1</SUP>. The DOC titration effect on the inorganic carbon system may also be important on a global scale for regulating carbon fluxes in rivers.

Research areas: Water Quality, Ecosystems
Characterizing 19 thousand Chinese lakes, ponds and reservoirs by morphometric, climate and sediment characteristics (2021)

Chinese lakes, including ponds and reservoirs, are increasingly threatened by algal blooms. Yet, each lake is unique, leading to large inter-lake variation in lake vulnerability to algal blooms. Here, we aim to assess the effects of unique lake characteristics on lake vulnerability to algal blooms. To this end, we built a novel and comprehensive database of lake morphometric, climate and sediment characteristics of 19,536 Chinese lakes, including ponds and reservoirs (>0.1 km2). We assessed lake characteristics for nine stratification classes and show that lakes, including ponds and reservoirs, in eastern China typically have a warm stratification class (Tavg>4 C) and are slightly deeper than those in western China. Model results for representative lakes suggest that the most vulnerable lakes to algal blooms are in eastern China where pollution levels are also highest. Our characterization provides an important baseline to inform policymakers in what regions lakes are potentially most vulnerable to algal blooms.

Research areas: Water Quality, Ecosystems
The possibilities of explicit Striga (Striga asiatica) risk monitoring using phenometric, edaphic, and climatic variables, demonstrated for Malawi and Zambia (2022)

Food insecurity continues to affect more than two-thirds of the population in subSaharan Africa (SSA), particularly those depending on rain-fed agriculture. Striga, a parasitic weed, has caused yield losses of cereal crops, immensely affecting smallholder farmers in SSA. Although earlier studies have established that Striga is a constraint to crop production, there is little information on the spatial extent of spread and infestation severity of the weed in some SSA countries like Malawi and Zambia. This study aimed to use remotely sensed vegetation phenological (n = 11), climatic (n = 3), and soil (n = 4) variables to develop a data-driven ecological niche model to estimate Striga (Striga asiatica) spatial distribution patterns over Malawi and Zambia, respectively. Vegetation phenological variables were calculated from 250-m enhanced vegetation index (EVI) timeline data, spanning 2013 to 2016. A multicollinearity test was performed on all 18 predictor variables using the variance inflation factor (VIF) and Pearsons  correlation approach. From the initial 18 variables, 12 non-correlated predictor variables were selected to predict Striga risk zones over the two focus countries. The variable start of the season (start of the rainy season) showed the highest model relevance, contributing 26.8% and 37.9% to Striga risk models for Malawi and Zambia, respectively. This indicates that the crop planting date influences the occurrence and the level of Striga infestation. The resultant occurrence maps revealed interesting spatial patterns; while a very high Striga occurrence was predicted for central Malawi and eastern Zambia (mono-cultural maize growing areas), lower occurrence rates were found in the northern regions. Our study shows the possibilities of integrating various ecological factors with a better spatial and temporal resolution for operational and explicit monitoring of Striga-affected areas in SSA. The explicit identification of Striga hotspot areas is crucial for effectively informing intervention activities on the ground.

Research areas: Agriculture, Land Surface/Agriculture Indicators
Modeling inorganic carbon dynamics in the Seine River continuum in France (2020)

Abstract. Inland waters are an active component of the carbon cycle where transformations and transports are associated with carbon dioxide (CO2) outgassing. This study estimated CO2 emissions from the human-impacted Seine River (France) and provided a detailed budget of aquatic carbon transfers for organic and inorganic forms, including the in-stream metabolism along the whole Seine River network. The existing process-based biogeochemical pyNuts-Riverstrahler model was supplemented with a newly developed inorganic carbon module and simulations were performed for the recent time period 20102013. New input constraints for the modeling of riverine inorganic carbon were documented by field measurements and complemented by analysis of existing databases. The resulting dissolved inorganic carbon (DIC) concentrations in the Seine aquifers ranged from 25 to 92 mg C L1, while in wastewater treatment plant (WWTP) effluents our DIC measurements averaged 70 mg C L1. Along the main stem of the Seine River, simulations of DIC, total alkalinity, pH and CO2 concentrations were of the same order of magnitude as the observations, but seasonal variability was not always well reproduced. Our simulations demonstrated the CO2 supersaturation with respect to atmospheric concentrations over the entire Seine River network. The most significant outgassing was in lower-order streams while peaks were simulated downstream of the major WWTP effluent. For the period studied (20102013), the annual average of simulated CO2 emissions from the Seine drainage network were estimated at 36499 Gg C yr1. Results from metabolism analysis in the Seine hydrographic network highlighted the importance of benthic activities in headwaters while planktonic activities occurred mainly downstream in larger rivers. The net ecosystem productivity remained negative throughout the 4 simulated years and over the entire drainage network, highlighting the heterotrophy of the basin. Highlights  CO2 emission from the Seine River was estimated at 36499 Gg C yr1 with the Riverstrahler model. CO2 riverine concentrations are modulated by groundwater discharge and instream metabolism. CO2 emissions account for 31 % of inorganic carbon exports, the rest being exported as DIC.

Research areas: Water Quality, Environmental Impacts
Seasonal and Spatial Controls on the Eutrophication-Induced (2021)

Our understanding of eutrophication induced acidification in estuaries and coastal oceans is complicated by the seasonally and spatially changing interactions between physical and biochemical drivers. By combining the conservative mixing method and a physical biogeochemical model, we present the seasonal and spatial dynamical analysis of eutrophication induced acidification in the Pearl River Estuary in the northern South China Sea. In summer, the widespread eutrophication induced acidification is regulated by two distinct physical drivers, which are the strengthened stratification in the hypoxia zone and the high turbidity in the Lingdingyang Bay. In the hypoxia zone, eutrophication induced acidification is controlled by the combined effect of benthic remineralization and stratification, while it is dominantly regulated by local biochemical processes (nitrification and respiration) of the whole water column in other regions of the estuary. In winter with the enhanced vertical mixing, the eutrophication induced acidification is still active in the Lingdingyang Bay, and its strength has largely decreased compared with summer condition. While for the hypoxia zone, the eutrophication induced acidification peaks in summer and disappears in winter.

Research areas: Water Quality, Ecosystems
Measuring mangrove carbon loss and gain in deltas (2019)

Demand for mangrove forest resources has led to a steady decline in mangrove area over the past century. Land conversions in the form of agriculture, aquaculture and urbanization account for much of the deforestation of mangrove wetlands. However, natural processes at the transition zone between land and ocean can also rapidly change mangrove spread. In this study, we applied a robust field-based carbon inventory and new structural and temporal remote sensing techniques to quantify the magnitude and change of mangrove carbon stocks in major deltas across Africa and Asia. From 2000-2016, approximately 1.6% (12 270 ha) of the total mangrove area within these deltas disappeared, primarily through erosion and conversion to agriculture. However, the rapid expansion of mangroves in some regions during this same period resulted in new forests that were taller and more carbon-dense than the deforested areas. Because of the rapid vertical growth rates and horizontal expansion, new mangrove forests were able to offset the total carbon losses of 5 332 843 Mg C by 44%. Each hectare of new mangrove forest accounted for ∼84% to ∼160% of the aboveground carbon for each hectare of mangrove forest lost, regardless of the net change in mangrove area. Our study highlights the significance of the natural dynamics of erosion and sedimentation on carbon loss and sequestration potential for mangroves over time. Areas of naturally regenerating mangroves will have a much larger carbon sequestration potential if the rate of mangrove deforestation of taller forests is curbed.

Research areas: Land Surface/Agriculture Indicators, Habitat Conversion/Fragmentation