Surface Water Fluxes Research Articles

A new strategy to simultaneously improve the permeability and antifouling properties of EVAL membranes via surface segregation of macrocyclic supra-amphiphiles

Herein, we propose a new strategy to improve the flux and antifouling properties of ethylene vinyl alcohol (EVAL) membranes by blending with macrocyclic supra-amphiphiles (cyclodextrin; CD). The amphiphilic ‘molecular cage’ geometry of CD, consisting of a hydrophobic cavity segment and hydrophilic rim segment, induces spontaneous surface segregation of CD to form a CD-enriched layer on the membrane surface. The membrane matrix structure was observed by SEM-EDX, wherein elemental composition indicated a gradient distribution of elemental O content from the top to the bottom layer of the cross-section. The layer segregation was governed by the synergistic interactions with hydrophobic and hydrophilic segments of amphiphilic CD polymer during the phase inversion process. When clickable azide-β-CD was fixed into the clickable alkyne-EVAL matrix as a comparative experiment, no surface segregation was observed. The aggregation of hydrophilic CD on the membrane surface increased the surface roughness, hydrophilicity, and water flux (200 L/m2h) of the membrane. Furthermore, the macrocyclic supra-amphiphile-blended membrane showed better antifouling performance than raw EVAL membrane, with a lower water flux decline (21%) and higher water flux recovery (89%). The proposed 3D strategy based on macrocyclic supra-amphiphiles shed lights on the formation of hydrophilic membrane surface with potential applications in membrane technology.

Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework

The High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) programme provides a modeling system to maximize the use of satellite-based products and ensure internally consistent estimation of surface water and energy fluxes. Leaf area index (LAI) and land surface albedo are two key parameters for estimation of latent and sensible heat fluxes with HOLAPS. Thus, to facilitate the generation of long-term high accuracy latent and sensible heat fluxes, high quality global long-term LAI and land surface albedo datasets are essential. The Quality Assurance for Essential Climate Variables (QA4ECV) project released quality-assured long-term LAI and albedo datasets with traceable and reliable uncertainty information provided in the dataset. Taking MODIS-BNU-LAI and MODIS albedo as reference, different global long-term LAI and albedo datasets including GlobAlbedo, QA4ECV and GLOBMAP were investigated for estimation of latent/sensible heat fluxes with HOLAPS in this study. The results show that all albedo datasets show similar accuracy for estimation of latent and sensible heat fluxes when validated against FLUXNET observations. The QA4ECV LAI leads to worse latent heat flux estimation due to its use of effective LAI rather than green leaf LAI. Sensitivity analysis also shows that the HOLAPS estimated latent heat flux (LE) is more sensitive to uncertainty in LAI than land surface albedo. Overall, the combined use of QA4ECV albedo and GLOBMAP LAI is suggested for estimation of latent/sensible heat fluxes with HOLAPS. The root mean square differences (RMSD) between estimations and FLUXNET measurements are 54 (30) W/m2 for hourly (monthly) latent heat flux, and 80.5 (24.5) W/m2 for sensible heat flux, which are comparable to estimates with MODIS and other reported studies.

Regional spatial variability of root-zone soil moisture in arid regions and the driving factors — a case study of Xinjiang, China

Soil moisture is a key element of the hydrological cycle, and it significantly impacts the surface water and energy fluxes. However, a knowledge gap exists on the spatial variability of root-zone soil moisture at the regional scale in arid and hyperarid regions. Thus, soil moisture measurements at 142 sites were taken in Xinjiang (northwest China), and the relationships between soil moisture and 19 environmental factors were analyzed. The results showed that both absolute gravitational soil water content (SWC) and relative extractable water (REW) increased with increasing soil depth in the 0–100 cm soil profile. It generally decreased in the order of cropland > forestland > grassland > shrubland > bare land. Semivariograms suggested that SWC had moderate spatial dependence over a large range of 473–558 km, and REW was more randomly distributed at the regional scale in Xinjiang. Redundancy analysis suggested that environmental factors could explain 47.5%–50.9% of the variability of soil moisture, which was more strongly driven by land surface factors (p < 0.01) than by climatic factors (p > 0.05). Soil properties and other local variables explained, respectively, 40.7% and 32.3% of the variability of soil moisture in the 0–100 cm soil profile. Soil properties independently accounted for 12.8% and 28.1% of the variability in soil moisture in the 0–50 and 50–100 cm soil layers, respectively. Soil texture, field capacity, wilting point, organic carbon, bulk density, land use, and normalized difference vegetation index were the dominant factors influencing soil moisture variations.

Coupling of a physically based lake model into the climate forecast system to improve winter climate forecasts for the Great Lakes region

In this study, we coupled the two-layer one-dimensional Freshwater lake (FLake) model into the Climate Forecast System (CFS) version 2 to improve simulations of the effects of the Great Lakes on winter climate forecasts in that region. We first incorporated global lake fraction and depth data into the coupled CFS-FLake through a subgridding system. An interface between the CFS and FLake was then developed to link the two models for energy and water flux exchanges. The lake scheme was triggered only if the lake fraction was more than 10% in one CFS grid cell. We conducted ensemble retrospective forecasts with CFS-FLake for the period of 1997 through 2016 with 9 monthly leads. These forecasts were assessed to obtain a better understanding of the role of the Great Lakes in the climate system for winter, when significant lake-effect precipitation often occurs. Our results indicate that forecasts of lake surface temperature (LST), lake ice coverage (LIC), and precipitation with CFS-FLake were consistently better than those with CFS. The major improvements resulted from changes in land use type for the Great Lakes, from ocean and land in CFS to lakes in CFS-FLake. With the change from ocean to lake, LST mostly decreased with increasing LIC, resulting in lower surface heat and water fluxes to the atmosphere during the winter. However, with the change from land to lake, LST increased, leading to higher heat and water fluxes. In the meantime, precipitation predicted by CFS-FLake was reduced quite significantly over the Great Lakes compared to that by CFS. This reduction was caused by suppressed rising motion due to increased stability in the lower atmosphere as a result of lowered surface heat and water fluxes. The results from this study indicate that local and mesoscale surface and atmospheric processes significantly affect regional climate forecasts, and the coupled CFS-FLake model will have a broader impact on climate and hydrology research and forecasts.

Porewater exchange drives trace metal, dissolved organic carbon and total dissolved nitrogen export from a temperate mangrove wetland

Porewater exchange is usually the least quantified process in delivering dissolved material from wetlands to coastal waters, although it has been recognised as an important pathway for the transport of trace metal, carbon and nutrient to the ocean. Here, surface water fluxes of dissolved manganese (Mn), iron (Fe), dissolved organic/inorganic carbon (DOC/DIC), total dissolved nitrogen (TDN) and phosphorous (TDP) were estimated from a temperate mangrove wetland (Kooragang Island, Newcastle, Australia). Radon (222Rn, a natural groundwater tracer) was used to develop a mass balance model to quantify porewater exchange rates and evaluate the contribution of porewater-derived dissolved material to the overall wetland surface water export. A 25-h time series dataset depicted a clear peak of Mn, Fe, TDN, DOC and radon during ebb tides which related to porewater discharge. Porewater exchange rates were estimated to be 14.0 ± 6.3 cm/d (0.18 ± 0.08 m3/s), mainly driven by tidal pumping, and facilitated by a large number of crab burrows at the site. Results showed that the wetland was a source of Mn, Fe, TDN and DOC to the adjacent river system and a sink for TDP and DIC. Surface water Mn, Fe, TDN and DOC exports were 4.0 ± 0.6, 6.6 ± 1.6, 23.9 ± 3.6 and 197.7 ± 29.7 mmol/m2 wetland/d, respectively. Porewater-derived Mn, Fe, TDN and DOC accounted for ~95, 100, 89 and 54% of the wetland surface water exports demonstrating its significant contribution. Our study indicates that temperate mangrove wetlands can be a major source of dissolved metal, carbon and nutrient delivery to coastal waters and that mangrove porewater exchange significantly contributes to this process.

Effects of land‐cover changes on the partitioning of surface energy and water fluxes in Amazonia using high‐resolution satellite imagery

AbstractSpatial variability of surface energy and water fluxes at local scales is strongly controlled by soil and micrometeorological conditions. Thus, the accurate estimation of these fluxes from space at high spatial resolution has the potential to improve prediction of the impact of land‐use changes on the local environment. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) data were used to examine the partitioning of surface energy and water fluxes over different land‐cover types in one wet year (2004) and one drought year (2005) in eastern Rondonia state, Brazil. The spatial variation of albedo, net radiation (Rn), soil (G) and sensible (H) heat fluxes, evapotranspiration (ET), and evaporative fraction (EF) were primarily related to the lower presence of forest (primary [PF] or secondary [SF]) in the western side of the Ji‐Parana River in comparison with the eastern side, located within the Jaru Biological Reserve protected area. Water limitation in this part of Amazonia tends to affect anthropic (pasture [PA] and agriculture [AG]) ecosystems more than the natural land covers (PF and SF). We found statistically significant differences on the surface fluxes prior to and ~1 year after the deforestation. Rn over forested areas is ~10% greater in comparison with PA and AG. Deforestation and consequent transition to PA or AG increased the total energy (~200–400%) used to heat the soil subsurface and raise air temperatures. These differences in energy partitioning contributed to approximately three times higher ET over forested areas in comparison with nonforested areas. The conversion of PF to AG is likely to have a higher impact in the local climate in this part of Amazonia when compared with the change to PA and SF, respectively. These results illustrate the importance of conserving secondary forest areas in Amazonia.

Changes in concentrations of fine and coarse particles under the CO2-induced global warming

Using an aerosol-climate coupled model, we have investigated the climate response to increases in atmospheric carbon dioxide (CO2) levels and the resulting changes in the column concentrations of anthropogenic and natural particulate matters. Special attention has been paid on the fine particulate matters (PM2.5, particulate matters with aerodynamic diameters ≤2.5 μm) and coarse particles of non-PM2.5 (NPM, particulate matters with aerodynamic diameters >2.5 μm). Rising CO2 levels led to significant effects on surface air temperature, large scale circulation, surface water flux, precipitation, etc., which considerably affect the column concentrations of anthropogenic and natural particulate matters, for both fine and coarse modes. Changes in burden of fine particles are major contributions to that of total anthropogenic particulate matters by CO2-induced global warming. The anthropogenic PM2.5 burden was found to decrease in the regions with latitudes >30°N, whereas in the rest areas increase. The geographical distributions of changes in the column concentrations of fine and coarse natural particles were found in the same order of magnitude in most regions, and the particle size distribution shifted to the coarse mode. The physical mechanisms are analyzed to explain the changes in aerosol local column concentrations due to CO2-induced climate change.

Diagnosing Bias in Modeled Soil Moisture/Runoff Coefficient Correlation Using the SMAP Level 4 Soil Moisture Product

AbstractThe physical parameterization of key processes in land surface models (LSMs) remains uncertain, and new techniques are required to evaluate LSMs accuracy over large spatial scales. Given the role of soil moisture in the partitioning of surface water fluxes (between infiltration, runoff, and evapotranspiration), surface soil moisture (SSM) estimates represent an important observational benchmark for such evaluations. Here, we apply SSM estimates from the NASA Soil Moisture Active Passive Level‐4 product (SMAP_L4) to diagnose bias in the correlation between SSM and surface runoff for multiple Noah‐Multiple Physics (Noah‐MP) LSM parameterization cases. Results demonstrate that Noah‐MP surface runoff parameterizations often underestimate the correlation between prestorm SSM and the event‐scale runoff coefficient (RC; defined as the ratio between event‐scale streamflow and precipitation volumes). This bias can be quantified against an observational benchmark calculated using streamflow observations and SMAP_L4 SSM and applied to explain a substantial fraction of the observed basin‐to‐basin (and case‐to‐case) variability in the skill of event‐scale RC estimates from Noah‐MP. Most notably, a low bias in LSM‐predicted SSM/RC correlation squanders RC information contained in prestorm SSM and reduces LSM RC estimation skill. Based on this concept, a novel case selection strategy for ungauged basins is introduced and demonstrated to successfully identify poorly performing Noah‐MP parameterization cases.

Experimental investigation of hydrodynamics and heat transfer of sphere cooling using air/water mist two phase flow

To improve the cooling performance for the future generation of gas-cooled equipment, experimental studies on air/water mist heat transfer of single sphere inside a cylindrical channel have been carried out with an aim to investigate the heat transfer enhancement by suspending tiny water mist into air flow. The effect of the different key factors such the inlet Reynolds number, surface heat flux and water flux density on friction flow and heat transfer characteristics are examined. Experiments were performed in five cases using air as well as air/water mist two phase flow as working coolant for range of water flux density (j = 23.39 - 111.68 kg m-2 hr-1). The results obtained from the related experimental work revealed that the presence of water mist leads to a significant increase in heat transfer over the use of air coolant alone. The Nusselt numbers are respectively 1%, 19.7%, 90.2% and 134% higher than those in single phase - cooling for all cases of water flux density respectively. It was also found that the water flux density has little influence on friction factor. When the surface heat flux is fixed, the heat transfer enhancement factor increases with the increasing of water flux density.

High spatial resolution monitoring land surface energy, water and CO2 fluxes from an Unmanned Aerial System

High spatial resolution maps of land surface energy, water and CO2 fluxes, e.g. evapotranspiration (ET) and gross primary productivity (GPP), are important for agricultural monitoring, ecosystem and water resources management. However, it is not clear which is the optimal (e.g. coarsest possible) spatial resolution to capture those fluxes accurately. Unmanned Aerial Systems (UAS) can address this by collecting very high spatial resolution (<1 m, VHR) imagery. The objective of this study is to model ET and GPP dynamics using VHR optical and thermal imagery and quantify the influence of the spatial heterogeneity in the flux simulations and validations. The study was conducted at a deciduous willow bioenergy eddy covariance (EC) flux site in Denmark. Flight campaigns were conducted during the growing seasons of 2016 and 2017 with a hexacopter equipped with RGB, multispectral and thermal infrared cameras. A ‘top-down’ modeling approach consisting of the Priestley–Taylor Jet Propulsion Laboratory model and a light use efficiency model sharing the same canopy biophysical constraints was used to estimate ET and GPP. Model outputs were benchmarked by EC flux observations with the source weighted footprint. Our results indicate that our model can well estimate the instantaneous net radiation, ET, GPP, evaporative fraction, light use efficiency and water use efficiency with root-mean-square deviations (RMSD) of 31.6 W·m−2, 41.2 W·m−2, 3.12 μmol·C·m−2·s−1, 0.08, 0.16 g·C·MJ−1 and 0.35 g·C·kg−1, respectively. Further, it is found that using a footprint model to sample different areas of VHR imagery can be a tool to provide better diurnal estimates to benchmark with EC data. Moreover, these VHR maps (0.3 m) allowed us to quantify metrics of spatial heterogeneity by using semivariogram analysis and by aggregating model inputs into different spatial resolutions. For instance, we find that in this site, the aggregation of simulated GPP using the source weighted mean of the EC footprint was about 30% lower in RMSD than using the arithmetic mean of the footprint. This demonstrates the accuracy of the modeled VHR spatial patterns. Nevertheless, we also find that imagery resolution consistent with the canopy size (around 1.5 m in our study) is sufficient to capture the spatial heterogeneity of the fluxes as transpiration and canopy assimilation of CO2 are processes regulated at the tree crown level. Our results highlight the importance of considering the land surface heterogeneity for flux modeling and the source contribution within the EC footprint for model benchmarking at appropriate spatial resolutions.

Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5

Abstract. Fire plays an important role in terrestrial ecosystems. The burning of biomass affects carbon and water fluxes and vegetation distribution. To understand the effect of interactive processes of fire and ecological succession on surface carbon and water fluxes, this study employed the Community Land Model version 4.5 to conduct a series of experiments that included and excluded fire and dynamic vegetation processes. Results of the experiments that excluded the vegetation dynamics showed a global increase in net ecosystem production (NEP) in post-fire regions, whereas the inclusion of vegetation dynamics revealed a fire-induced decrease in NEP in some regions, which was depicted when the dominant vegetation type was changed from trees to grass. Carbon emissions from fires are enhanced by reduction in NEP when vegetation dynamics are considered; however, this effect is somewhat mitigated by the increase in NEP when vegetation dynamics are not considered. Fire-induced changes in vegetation modify the soil moisture profile because grasslands are more dominant in post-fire regions. This results in less moisture within the top soil layer than that in unburned regions, even though transpiration is reduced overall. These findings are different from those of previous fire model evaluations that ignored vegetation dynamics and thus highlight the importance of interactive processes between fires and vegetation dynamics in evaluating recent model developments.

Throughfall and stemflow heterogeneity under the maize canopy and its effect on soil water distribution at the row scale

Quantitative knowledge of the spatial variability of soil infiltration processes caused by canopy rainfall redistribution has significant hydro-chemical consequences owing to their influence on nutrients leaching and groundwater recharge in agricultural ecosystems. The heterogeneity of throughfall and stemflow under the maize canopy was quantified in this study, and its subsequent effect on soil water distribution at the row scale was further examined. Throughfall at 15 locations within and between maize rows as well as stemflow was observed over three growing seasons of 2015, 2016 and 2017 on the Loess Plateau of China. Soil water content at five depths in the row and interrow positions were continuously monitored. The results showed that throughfall was significantly different among the five sampling sections between maize rows, with the highest throughfall in the center and a decreasing trend towards the maize row. Greater throughfall was observed on the windward side of the maize row than on the leeward side. These spatial patterns persisted for most rainfall events. However, much higher net rainfall (throughfall plus stemflow) was obtained in the row positions when stemflow was further considered. Net rainfall reaching the row positions resulted not only in earlier water infiltration, but also in deeper penetration. The results suggested that the presence of maize canopy altered the soil surface water flux and thus caused heterogeneous infiltration water in the soil, which has implications for guiding the placing of fertilizers/pesticides and soil erosion management in the maize field.

An analytical model for estimation of land surface net water flux from near-surface soil moisture observations

The accurate determination of land surface water fluxes at various spatiotemporal scales remains a challenge in hydrological sciences. It is intuitive that land surface net water flux (i.e., infiltration minus evapotranspiration) directly affects near-surface soil moisture. However, there exists no hydrological model suitable to calculate net water flux based on measured near-surface soil moisture data. This is a consequence of the mathematical structure of existing models that use ‘boundary conditions’ to determine ‘internal conditions’, whereas what is needed is a model amenable to use near-surface soil moisture data (an internal condition) to determine the surface water flux (a boundary condition). To pursue the idea of utilizing remotely-sensed or in situ (i.e., sensor networks) near surface soil moisture data for estimation of net water flux, we derived an analytical model via inversion of Warrick’s 1975 analytical solution to the linearized Richards’ equation for arbitrary time-varying surface flux boundary conditions. The applicability of the new analytical solution was evaluated based on actual water flux observations as well as HYDRUS-1D simulations for four vastly different sites in Arizona, California, Idaho, and Indiana. Our results demonstrate that the proposed model reasonably captures net water flux variations in natural settings, including layered and vegetated soils, especially at larger time scales (e.g., monthly). While the model works for a wide range of climatic conditions, the prediction accuracy is somewhat lower for extreme dry or wet conditions. A major advantage of the new model is that it does not require calibration, which provides an unprecedented opportunity for large scale estimation of land surface net water flux using remotely sensed near-surface soil moisture observations.

Performance and Structure of Thin Film Composite Reverse Osmosis Membranes Prepared by Interfacial Polymerization in the Presence of Acid Acceptor

During interfacial polymerization (IP) reaction between m-phenylenediamine (MPDA) and trimesoyl chloride (TMC), a by-product, i.e. hydrochloric acid can produce. This produced acid diffuses back in aqueous phase and protonates MPDA and reduces its reactivity that results in lowering of polymer yield and performance of membrane. Further, for getting consistency in reverse osmosis membranes formation, different acid acceptors (AAs) can investigate in the IP to form polyamide-made barrier layer formation. The main objective was to scavenge hydrochloric acid produced during IP and to fabricate membrane having high flux and salt rejection ability. AAs (of varying concentrations) tested were triethylamine-camphorsulfonic acid (TEACSA), triphenyl phosphate (TPP), sodium hydroxide (SH) and trisoduim phosphate (TSP) for studying structure and performance of membranes. The membrane samples were then characterized using surface proflometer, scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy, atomic force microscopy (AFM), and contact angle goniometer. Results indicated that the addition of organic AA improves water permeability of the membranes without sacrifcing salt rejection. The optimum membranes were prepared with AA concentrations of 3.4, 0.15, 0.02 and 0.19 wt.% for TEACSA, TPP, SH and TSP respectively. Membranes produced in presence of AA had higher surface area difference, hydrophilicity and water flux. Additionally, compare to inorganic AAs, the use of organic AA produced membrane with thicker polyamide layer and higher cross-link density. These induced changes in the physicochemical features of the prepared membranes also signifed the role of the AA in scavenging the hydrochloric acid to forestall the formation of amine salts during IP for polyamide nanocomposite membrane formation.

Deforestation effects on land surface energy coupling: a data-driven perspective

Deforestation dramatically alters land surface properties and functions through multiple biogeophysical and biogeochemical pathways. However, a quantitative identification of how deforestation affects local energy-water-vegetation coupling is still challenging. In this study we employed information theory and transfer entropy framework to identify the overall feedback pattern of land surface water-energy-vegetation coupling, using high frequency eddy covariance measurements at forested versus deforested sites. We found that deforestation strengthened the directional influence of atmospheric demand on land surface water flux, and more importantly, deforestation broke the coupling between vegetation activities and local precipitation, which led to a less efficient ecosystem to recycle and maintain water within this system.

A Review of Geophysical Methods for Soil Structure Characterization

AbstractThe growing interest in the maintenance of favorable soil structure is largely motivated by its central role in plant growth, soil ecological functioning, and impacts on surface water and energy fluxes. Soil structure pertains to the spatial arrangement of voids and solid constituents, their aggregation, and mechanical state. As a fragile product of soil biological activity that includes invisible ingredients (mechanical and ecological states), soil structure is difficult to define rigorously, and measurements of relevant metrics often rely on core samples or on episodic point measurements. The presence of soil structure has not yet been explicitly incorporated in climate and Earth systems models, partially due to incomplete methodological means to characterize it at relevant scales and to parameterize it in spatially extensive models. We seek to review the potential of harnessing geophysical methods to fill the scale gap in characterization of soil structure directly (via impact of soil pores, transport, and mechanical properties on geophysical signals) or indirectly by measurement of surrogate variables (wetness and rates of drainage). We review basic aspects of soil structure and challenges of characterization across spatial and temporal scales and how geophysical methods could be used for the task. Additionally, we propose the use of geophysical models, inversion techniques, and combination of geophysical methods for extracting soil structure information at previously unexplored spatial and temporal scales.

Subdaily to Seasonal Change of Surface Energy and Water Flux of the Haihe River Basin in China: Noah and Noah-MP Assessment

The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin (HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models (LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.

Tracing groundwater inputs to Bay of Bengal from Sankarabarani River Basin, Pondicherry, India, using continuous radon monitoring

Sankarabarani river basin gains importance due to agriculture, an industrial and recreational activity that delivers large groundwater fluxes to the Bay. Attempt has been made by continuous monitoring of radon isotopes to evaluate submarine groundwater discharge with reference to groundwater and surface and pore water samples with distance perpendicular to the coast. 222Rn in groundwater samples were higher (543.0 Bq m−3) signifying major radon sources due to coastal groundwater discharge. Radon mass balance model attempted by considering fluxes like tides, atmospheric emissions, and sediment diffusion suggests higher groundwater and surface water fluxes (7.2 and 20.15 m day−1) near to the coast and higher fluxes (19.7 and 9.7 m day−1) in pore water away from the coast, suggesting influence of hydraulic gradient and radium retention in sediments. The average fresh submarine groundwater discharge calculated accounts 0.88 m day−1, higher in comparison with world studies.

On the ecohydrology of the Yucatan Peninsula: Evapotranspiration and carbon intake dynamics across an eco‐climatic gradient

AbstractThe hydrology and productivity of the ecosystems of the Yucatan Peninsula (YP) are highly constrained by two factors: (a) the lack of surface drainage networks due to the existence of a highly permeable and connected karstic aquifer roughly the size of the peninsula and (b) a climatic gradient that leads to a transition from seasonally dry deciduous and sub‐deciduous tropical forests, in the north‐western and central parts of the Peninsula, to evergreen forests, in the southern and eastern parts. As a result, surface water fluxes of the YP are restricted to evapotranspiration (ET) that are tightly coupled to ecosystems health and gross primary productivity (GPP). The magnitude and seasonal variation of these fluxes are sensitive to climatic variability and perturbations caused by extreme events such as droughts and tropical storms that are frequent in the YP. In this study, we assess the spatio‐temporal dynamics of ET and GPP above average dry and wet conditions through time series analyses of 15 years of remotely sensed data from both Moderate Resolution Imaging Spectroradiometer and Tropical Rainfall Measuring Mission satellite products. Our results show that ET and GPP follow a regional moisture and temperature gradient that highly controls the distribution of ecosystems within the peninsula. We observe that ET and GPP are in phase with the rainy season in the deciduous forests, but for the evergreen forests, only the GPP is in phase. Additionally, and with the exception of droughts on deciduous ecosystems of the northern part of the YP, the productivity of these ecosystems shows a legacy effect, responding more to a defined trajectory (wetting or drying on the previous years), rather than to punctual extreme climatic events. This has implications on the resilience of these ecosystems to natural perturbations of climate. Comparisons between deciduous and evergreen forest indicate that both types of ecosystems have different plant water use strategies in response to hydrologic variability.

Urbanization and climate change: Insights from eco-hydrological diagnostics

To quantify how urbanization induced long-term changes have altered the evolution of urban climate, a novel eco-hydrological diagnostic is introduced and applied globally, to a developing and a developed country (China and US-America). Urban areas are (i) geographically identified by remote sensing based nighttime light, (ii) physically embedded in state spaces spanned by suitable combinations of surface energy and water fluxes comprising the rainfall-runoff chain, and (iii) dynamically characterized by the time evolution of the surface fluxes at geographically fixed locations, analyzed as trajectories in state space, and interpreted by an attribution model separating anthropogenic from climate induced causes. The results describe the long term climatological settings of urban areas in a net radiation versus dryness diagram, while the attribution of change is diagnosed in a state space spanned by energy and water excess: (i) Cities in China are characterized by a bi-modal distribution separated by the boundary between water and energy-limited (northern and southern) regimes while US-American cities are assembling unimodally on this boundary, and globally the urbanized areas are also aligned along this boundary between water and energy-limited regimes. (ii) Attribution of eco-hydrological changes of urbanized regions to climate and human-induced causes shows also basic differences between the developing and developed country: urbanization in Chinese cities is characterized by a ‘wet-gets-drier’ and ‘dry-gets-wetter’ paradigm of the climate-induced contributions, due to which cities tend towards a unimodal state as it is observed for US-American urban areas. Finally, implications for large scale city planning are discussed in the outlook.