Ecohydrological Model Research Articles

Bedrock morphology influences rock barrens turtle nesting habitat energy dynamics.

Energy absorption and flow through a nest is an important aspect of embryonic development in many reptile species including turtles. To date, few studies have explicitly attempted to quantify the energy flow through turtle nests, opting instead for the simplified approach offered by temperature index models. However, the quantification of the energy can provide an explicit abiotic link that can link biological models to biometeorological and ecohydrological processes and models. We investigated the energy flow through turtle nests occupying different bedrock morphologies within a Canadian Shield Rock Barren landscape, in Ontario, Canada. The taxons studied were Spotted Turtle (Clemmys guttata), Midland Painted Turtle (Chrysemys picta marginata), and Blanding's Turtle (Emydoidea blandingii). Nest temperature and soil moisture were measured in 2018 and 2019 using sensors placed in the soil adjacent to 12 turtle nest cavities. Three main rock morphologies were identified for each nest location, Crevice, Ledge, and Flat types, that are in order of decreasing bedrock percentage contact with the nest site. Ground heat flux and change in heat storage were determined using the calorimetric method for each nest, while the direction of energy flux between the atmosphere and the underlying rock was also determined. The Crevice nest morphology experienced the lowest ground heat flux on average (1.56 × 10-1 W m-2) and lowest cumulative heat storage (230 MJ) compared to the Flat (440 MJ) and Ledge (331 MJ) nests. However, over the diurnal cycle, large heat gains by Flat nests were mostly balanced out by nighttime heat losses. While Crevice nests saw the lowest daily heat storage gains, they experienced much lower heat losses over the evening period compared to the other nest types. Furthermore, we found that 59% of the energy is directed from the underlying bedrock into the Crevice nest, highlighting the importance of the bedrock in controlling thermal dynamics in the turtle nesting habitat. The lower variability in energy parameters for Crevice nest types can be attributed to higher amounts of nest-to-bedrock contact, compared to the flat nest types. Our results indicate that Crevice morphology may be ideal for turtles nesting at their northern limits because minimal heat loss during the evening can result in a more stable thermal incubation environment. Future conservation and habitat restoration efforts should consider the importance of bedrock morphology and prioritize the protection of Crevice nest sites. Furthermore, this work highlights important opportunities for potential interdisciplinary work between ecologists, climatologists, biologists, and hydrologists, specifically the integration of ecohydrological and biological models. This work also underscores the potential uncertainty of climate change impacts on turtle egg hatching success and nest sex ratios.

Hydrological regimes and evaporative flux partitioning at the climatic ends of high mountain Asia

Abstract High elevation headwater catchments are complex hydrological systems that seasonally buffer water and release it in the form of snow and ice melt, modulating downstream runoff regimes and water availability. In High Mountain Asia (HMA), where a wide range of climates from semi-arid to monsoonal exist, the importance of the cryospheric contributions to the water budget varies with the amount and seasonal distribution of precipitation. Losses due to evapotranspiration and sublimation are to date largely unquantified components of the water budget in such catchments, although they can be comparable in magnitude to glacier melt contributions to streamflow. Here, we simulate the hydrology of three high elevation headwater catchments in distinct climates in HMA over 10 years using an ecohydrological model geared towards high-mountain areas including snow and glaciers, forced with reanalysis data. Our results show that evapotranspiration and sublimation together are most important at the semi-arid site, Kyzylsu, on the northernmost slopes of the Pamir mountain range. Here, the evaporative loss amounts to 28% of the water throughput, which we define as the total water added to, or removed from the water balance within a year. In comparison, evaporative losses are 19% at the Central Himalayan site Langtang and 13% at the wettest site, 24 K, on the Southeastern Tibetan Plateau. At the three sites, respectively, sublimation removes 15%, 13% and 6% of snowfall, while evapotranspiration removes the equivalent of 76%, 28% and 19% of rainfall. In absolute terms, and across a comparable elevation range, the highest ET flux is 413 mm yr−1 at 24 K, while the highest sublimation flux is 91 mm yr−1 at Kyzylsu. During warm and dry years, glacier melt was found to only partially compensate for the annual supply deficit.

Comparison of SWAT-based Ecohydrological Modeling in the Rawa Pening Catchment Area, Indonesia

The Soil and Water Assessment Tool (SWAT) is an ecohydrological model widely applied to assess water quality and watershed management. This tool also has the advantage of building watershed models even with limited monitoring data availability. The essential data required by this tool includes digital elevation models (DEM), land use maps, climate data, and soil data. Nonetheless, the availability of spatial data is still often a challenge in developing hydrological models, especially in developing countries such as Indonesia. This research will compare the accuracy of freely available data in Indonesia in facilitating the development of hydrological models from SWAT in the Rawa Pening catchment area. This research is crucial since Rawa Pening Lake is a priority lake for revitalization, so the research results will help provide suggestions regarding presenting data in SWAT modeling. This research compares SWAT models built from different land use and DEM (Digital Elevation Models) data. The land use data being compared is the result of processing from the Google Earth Engine (GEE) platform using machine learning with land use data from government agencies, namely the Ministry of Environment and Forestry, while the DEM data being compared is SRTM and DEMNAS data. The validation results using R, R2, RMSE, and NSE show that, in general, the model built from land use from GEE is the best compared to the other models. In modeling SWAT in Indonesia, we recommend using good-quality land-use data. Utilizing supervised classification through Random Forest (RF) algorithms within GEE can facilitate the acquisition of this data. To reduce computation time, the DEM can be SRTM with a small sacrifice of accuracy.

Exploring potential trade-offs in outdoor water use reductions and urban tree ecosystem services during an extreme drought in Southern California

In Southern California cities, urban trees play a vital role in alleviating heat waves through shade provision and evaporative cooling. Trees in arid to semi-arid regions may rely on irrigation, which is often the first municipal water use to be restricted during drought, causing further drought stress. Finding a balance between efficient water use and maintaining tree health will be crucial for long-term urban forestry and water resources management, as climate change will increase drought and extreme heat events. This study aimed to quantify how urban tree water and carbon fluxes are affected by irrigation reductions, and how that relationship changes with tree species and temperature. We used an ecohydrologic model that mechanistically simulates water, carbon, and energy cycling, parameterized for 5 common tree species in a semi-arid urban area. We simulated a range of irrigation reductions based on average outdoor water use data from the city for a recent extreme drought as well as with warmer temperatures. We then analyzed the response of model outcomes of plant carbon fluxes, leaf area index (LAI), and water use. Results show that reducing irrigation up to 25%, a comparable amount as the California state mandate in 2014, has minimal effects on tree primary productivity and water use efficiency. We found that transpiration was linearly related to irrigation input, which could lead to a short-term loss of evaporative cooling with irrigation reductions during drought. However, primary productivity and LAI had a nonlinear response to irrigation, indicating shade provision could be maintained throughout drought with partial irrigation reductions. Results varied across tree species, with some species showing greater sensitivity of productivity to both irrigation reductions and potentially warmer droughts. These results have implications for water resources management before and during drought, and for urban tree climate adaptation to future drought.

Modeling pesticides and ecotoxicological risk assessment in an intermittent river using SWAT

The present work aimed to predict the fate of two pesticides, copper (Cu) and glyphosate in a Mediterranean basin with an intermittent river and to assess the ecotoxicological risk related to their presence in water bodies coupling field measurements of streamflow and pesticide concentrations, and an eco-hydrological model. The Soil and Water Assessment Tool (SWAT) model was calibrated and, subsequently used to assess predicted environmental concentrations of pesticides in surface waters. The ecotoxicological risk related to the presence of Cu and glyphosate in surface water was assessed at the reach scale by using the Toxicity to Exposure Ratio approach (TER). Measurements of glyphosate concentrations (< 0.5 μg l−1) exceeded the maximum European threshold of environmental quality standards for pesticides (EQS) of 0.1 μg l−1. High concentrations of glyphosate were predicted in the wet season and in September, when glyphosate is mostly used in vineyards and olive grove productions. Acute risk (TER < 100) associated with the presence of glyphosate was detected for several reaches. High concentrations of Cu (< 6.5 μg l−1), mainly used as a fungicide in vineyards, were predicted in several river reaches. The results of the ecotoxicological risk assessment revealed that November and January were the critical months during which most of the river reaches showed a chronic risk associated with the presence of Cu.

Impact of Forest Management on Wood Production under Climate Change in the Bonis Catchment

The concept of integrated forest management offers a framework for understanding how forest ecosystem services interact with efforts to conserve natural resources. Forests face various disturbances stemming from human activities, management approaches, and shifts in climate patterns. This study aims to explore how forested watersheds respond to diverse silvicultural practices amidst changing climate conditions. The research is centered in the Bonis catchment, situated in the mountainous region of Sila Greca (latitude 39°25′15″ N, longitude 16°12′38″ W) within Southern Italy’s Calabria region. Nearly 93% of the catchment area is cloaked in a forest dominated by approximately 50-year-old Pinus laricio Poiret stands. To model the catchment’s response to various climate and management scenarios, the FEST-FOREST eco-hydrological model, which is distributed and based on physical principles, has been employed. This model accounts for the dynamic interactions between vegetation and the watershed’s hydrological processes. The monitoring of the basin has been ongoing since 1986, with runoff measurements collected at the catchment outlet using dedicated gauging structures. These data have been utilized to calibrate and validate the model, ensuring its accuracy in simulating future scenarios. These simulation results offer stakeholders some qualitative and scientifically based recommendations for the sustainable management of the catchment. In fact, thinning intensity affects hydrological processes, with a 50% stand density reduction identified as a threshold for significant impact on processes like rainfall partitioning and evapotranspiration. Under heavy thinning scenarios, runoff can change by over 60%, and the impact decreases with larger thinning intervals. Furthermore, different climate scenarios influence stem yield levels, with higher production under RCP 4.5 and RCP 8.5 compared to the base climate scenario. In particular, the RCP 8.5 scenario produces the highest yield due to better forest growth under different climate scenarios. This implies the idea that in regions with a Mediterranean climate and coniferous forests, amidst climate change, meticulous forest management involving precisely calibrated thinning schedules and intensities, tailored to unique biotic and abiotic factors, could potentially enhance carbon sequestration while positively influencing runoff rates.

SWAT + input data preparation in a scripted workflow: SWATprepR

Input data collection, quality assurance and preparation are central but time_consuming steps in environmental modeling. Errors due to manual processing of model input data can result in an incorrect representation of an environmental system and may consequently lead to implausible model simulations. Correct input data preparation and thorough quality check at an early stage of the model setup procedure are essential to build confidence in model simulation results. Typically, in environmental model applications, many steps in the input data preparation phase have to be repeated with the inflow of new, additional or corrected data. In this study, we selected the widely used SWAT + ecohydrological model as an illustrative example to investigate challenges related to input data preparation. To assist in these tasks, we developed an R package named SWATprepR, which provides functions for typical and repeating SWAT + model input data preparation tasks. The package supports the preparation of weather input files, atmospheric deposition, soil parameters, crop rotations, and observed (control or calibration) data, to name a few, presently with focus on European applications. The SWATprepR functions are integrated in R script workflows and can help SWAT + modelers to avoid repetitive tasks, secure reproducibility and transparently document the data processing steps. Application of the package is illustrated with a test case of a SWAT + model for a small catchment in central Poland.

Watershed analysis of urban stormwater contaminant 6PPD-Quinone hotspots and stream concentrations using a process-based ecohydrological model

Coho salmon (Oncorhynchus kisutch) are highly sensitive to 6PPD-Quinone (6PPD-Q). Details of the hydrological and biogeochemical processes controlling spatial and temporal dynamics of 6PPD-Q fate and transport from points of deposition to receiving waters (e.g., streams, estuaries) are poorly understood. To understand the fate and transport of 6PPD and mechanisms leading to salmon mortality Visualizing Ecosystem Land Management Assessments (VELMA), an ecohydrological model developed by US Environmental Protection Agency (EPA), was enhanced to better understand and inform stormwater management planning by municipal, state, and federal partners seeking to reduce stormwater contaminant loads in urban streams draining to the Puget Sound National Estuary. This work focuses on the 5.5 km2 Longfellow Creek upper watershed (Seattle, Washington, United States), which has long exhibited high rates of acute urban runoff mortality syndrome in coho salmon. We present VELMA model results to elucidate these processes for the Longfellow Creek watershed across multiple scales–from 5-m grid cells to the entire watershed. Our results highlight hydrological and biogeochemical controls on 6PPD-Q flow paths, and hotspots within the watershed and its stormwater infrastructure, that ultimately impact contaminant transport to Longfellow Creek and Puget Sound. Simulated daily average 6PPD-Q and available observed 6PPD-Q peak in-stream grab sample concentrations (ng/L) corresponds within plus or minus 10 ng/L. Most importantly, VELMA’s high-resolution spatial and temporal analysis of 6PPD-Q hotspots provides a tool for prioritizing the locations, amounts, and types of green infrastructure that can most effectively reduce 6PPD-Q stream concentrations to levels protective of coho salmon and other aquatic species.

Simulating the Role of Biogeochemical Hotspots in Driving Nitrogen Export From Dryland Watersheds

AbstractClimate change and nitrogen (N) pollution are altering biogeochemical and ecohydrological processes in dryland watersheds, increasing N export, and threatening water quality. While simulation models are useful for projecting how N export will change in the future, most models ignore biogeochemical “hotspots” that develop in drylands as moist microsites in the soil become hydrologically disconnected from plant roots when soils dry out. These hotspots enable N to accumulate over dry periods and rapidly flush to streams when soils wet up. To better project future N export, we developed a framework for representing hotspots using the ecohydrological model RHESSys. We then conducted a series of virtual experiments to understand how uncertainties in model structure and parameters influence N export to streams. Modeled N export was sensitive to three major factors (a) the abundance of hotspots in a watershed: N export increased linearly and then reached an asymptote with increasing hotspot abundance; this occurred because carbon and N inputs eventually became limiting as hotspots displaced vegetation cover, (b) the soil moisture threshold required for subsurface flow from hotspots to reestablish: peak streamflow N export increased and then decreased with an increasing threshold due to tradeoffs between N accumulation and export that occur with increasingly disconnected hotspots, and (c) the rate at which water diffused out of hotspots as soils dried down: N export was generally higher when the rate was slow because more N could accumulate in hotspots over dry periods, and then be flushed more rapidly to streams at the onset of rain. In a case study, we found that when hotspots were modeled explicitly, peak streamflow nitrate export increased by 29%, enabling us to better capture the timing and magnitude of N losses observed in the field. N export further increased in response to interannual precipitation variability, particularly when multiple dry years were followed by a wet year. This modeling framework can improve projections of N export in watersheds where hotspots play an increasingly important role in water quality.

Mitigating drought mortality by incorporating topography into variable forest thinning strategies

Abstract Drought-induced productivity reductions and tree mortality have been increasing in recent decades in forests around the globe. Developing adaptation strategies hinges on an adequate understanding of the mechanisms governing the drought vulnerability of forest stands. Prescribed reduction in stand density has been used as a management tool to reduce water stress and wildfire risk, but the processes that modulate fine-scale variations in plant water supply and water demand are largely missing in ecosystem models. We used an ecohydrological model that couples plant hydraulics with groundwater hydrology to examine how within-stand variations in tree spatial arrangements and topography might mitigate forest vulnerability to drought at individual-tree and stand scales. Our results demonstrated thinning generally ameliorated plant hydraulic stress and improved carbon and water fluxes of the remaining trees, although the effectiveness varied by climate and topography. Variable thinning that adjusted thinning intensity based on topography-mediated water availability achieved higher stand productivity and lower mortality risk, compared to evenly-spaced thinning at comparable intensities. The results from numerical experiments provided mechanistic evidence that topography mediates the effectiveness of thinning and highlighted the need for an explicit consideration of within-stand heterogeneity in trees and abiotic environments when designing forest thinning to mitigate drought impacts.

A Novel Hybrid Spatiotemporal Missing Value Imputation Approach for Rainfall Data: An Application to the Ratnapura Area, Sri Lanka

Meteorological time series, such as rainfall data, show spatiotemporal characteristics and are often faced with the problem of containing missing values. Discarding missing values or modeling data with missing values causes negative impacts on the accuracy of the final predictions. Hence, accurately estimating missing values by considering the spatiotemporal variations in data has become a crucial step in eco-hydrological modeling. The multi-layer perceptron (MLP) is a promising tool for modeling temporal variation, while spatial kriging (SK) is a promising tool for capturing spatial variations. Therefore, in this study, we propose a novel hybrid approach combining the multi-layer perceptron method and spatial kriging to impute missing values in rainfall data. The proposed approach was tested using spatiotemporal data collected from a set of nearby rainfall gauging stations in the Ratnapura area, Sri Lanka. Missing values are present in collected rainfall data consecutively for a considerably longer period. This pattern has scattered among stations discontinuously over five years. The proposed hybrid model captures the temporal variability and spatial variability of the rainfall data through MLP and SK, respectively. It integrates predictions obtained through both MLP and SK with a novel optimal weight allocation method. The performance of the model was compared with individual approaches, MLP, SK, and spatiotemporal kriging. The results indicate that the novel hybrid approach outperforms spatiotemporal kriging and the other two pure approaches.

Navigating uncertainty: Managing herbivore communities enhances Savanna ecosystem resilience under climate change

Abstract Savannas are characterized by water scarcity and degradation, making them highly vulnerable to increased uncertainties in water availability resulting from climate change. This poses a significant threat to ecosystem services and rural livelihoods that depend on them. In addition, the lack of consensus among climate models on precipitation change makes it difficult for land managers to plan for the future. Therefore, Savanna rangeland management needs to develop strategies that can sustain Savanna resilience and avoid tipping points under an uncertain future climate. Our study aims to analyse the impacts of climate change and rangeland management on degradation in Savanna ecosystems of southern Africa, providing insights for the management of semi‐arid Savannas under uncertain conditions worldwide. To achieve this, we simulated the effects of projected changes in temperature and precipitation, as predicted by 10 global climate models, on water resources and vegetation (cover, functional diversity, tipping points (transition from grass‐dominated to shrub‐dominated vegetation)). We simulated three different rangeland management options (herbivore communities dominated by grazers, by browser and by mixed feeders), each with low and high animal densities, using the ecohydrological model EcoHyD. Our results identified intensive grazing as the primary contributor to the increased risk of degradation in response to changing climatic conditions across all climate change scenarios. This degradation encompassed a reduction in available water for plant growth within the context of predicted climate change. It also entails a decline in the overall vegetation cover, the loss of functionally important plant species and the inefficient utilization of available water resources, leading to earlier tipping points. Synthesis and applications. Our findings underscore that, in the face of climate uncertainty, farmers' most effective strategy for securing their livelihoods and ecosystem stability is to integrate browsers and apply management of mixed herbivore communities. This management approach not only significantly delays or averts tipping points but also maintained greater plant functional diversity, fostering a more robust and resilient ecosystem that acts as a vital buffer against adverse climatic conditions.

Assessment framework of water conservation based on analytical modeling of ecohydrological processes

The water conservation (WC) function is an important indicator for ecosystem health. However, the commonly-used technical term like water retention (WR) and its computation methods could not well reflect the concept of WC because WR focused on the amount of water retained in vegetation canopy and soil, whereas WC includes WR and water supply as well. This study is to propose a new index for assessing the WC function (WCI) by integrating ecological and hydrological factors including WR, water yield, and vegetation production. We further developed a new framework for calculating spatiotemporal dynamics of WCI using ecohydrological modeling of Soil and Water Assessment Tool (SWAT) and remote sensing data. We then used the framework to assess the spatiotemporal dynamics of WC function in the Weihe River Basin (WHRB), the largest tributary of the Yellow River. Compared to the traditional method, our newly-developed approach is more reasonable because it could reflect water retention amount, temporal stability of water yield, and vegetation quality. Further, the case study can tell it is our new index (with forest being the highest, followed by grassland and cropland), instead of WR (with grassland being the highest and forest being the least), that could reflect the definition of WC and meet our cognition. Spatially, the high WCI (0.4 ∼ 0.6) areas are mainly located in the southern and central-eastern parts of the WHRB, characterized by relatively higher forest coverage (e.g., the Qinling Mountains in the southern part of the study area in southern part and representative ‘Grain-For-Green’ in central-eastern part). In brief, this study enhances understanding of the WC function and also provides a method for assessing the dynamics of WC that can be applicable to other regions.

Plastic trade-off: Impact of export and import of waste plastic on plastic dynamics in Asian region

Environmental contamination by plastics has been receiving considerable attention from scientists, policy makers and the public, and waste plastic trade has become a major social issue in recent years. In this study, the authors applied eco-hydrology model coupled with plastic debris model in Asian regions by including effect of waste plastic trade in order to clarify this research gap. Result showed settling and resuspension of plastic particles have great impact on mobilisation of plastic and its high intra-annual variability, and that the plastic transport becomes drastically higher during the flood periods accounting for most of the annual flux. In particular, the model simulated the size distribution of plastics in the water and riverbed sediment of the global major rivers and showed that the coarser particles are more distributed in the riverbed than those in the water. Further, the authors evaluated impact of waste plastic trade on change in riverine plastic transport by newly including effect of plastic trade on Mismanaged plastic waste (MPW) in the extension of previous studies. They newly modified to calculate municipal plastic waste by including these effects of plastic trade and disposal, and revised MPW assuming that the import of plastics is treated as the same as the export of plastics as the first approximation, which is the innovation of this study. The modified MPW became smaller than the original one in the exporting countries and vice versa in the importing countries. Further, this analysis clarified waste plastic trade has promoted decrease of riverine plastic transport in Japanese rivers, its slight increase in Yangtze, Yellow, and Ganges Rivers, and almost its constant in Mekong, Indus, Irrawaddy, and Brahmaputra Rivers. Recently, there is a growing progress in compiling existing research results and setting policy making in various countries under the umbrella of an intergovernmental negotiating committee (INC) on plastic pollution. The present results help to quantify plastic trade-off about impact of export and import of waste plastic on plastic dynamics in regional scale and to support the achievement of sustainable development goals (SGDs).

Effects of post-abandonment management on surface runoff in a Mediterranean mid-mountain basin

Mid-mountain catchments across the Mediterranean basin undergone a decrease in runoff and sediment yield during the second half of the 20th century mainly due to forest cover increase following rural abandonment together with a transition to drier climatic conditions. During last decades, land use and land cover (LULC) management of these areas has become a target of environmental policy makers and stakeholders to ensure the sustainability of ecosystem services. In some areas, an active management through the reduction of vegetation density or by human afforestation has been applied, while others undergone a natural process of revegetation. In this context, assessing the contribution of different LULC management on runoff is fundamental for addressing water management and soil loss at the catchment and regional scales. Within this background, the aim of this work is to analyse the relative effects of LULC management techniques on hydrological connectivity and water yield in a Mediterranean mid-mountain basin. To pursue this objective, we applied hydrological connectivity (IC index) and ecohydrological (RHESSys) models to different sub-basins of the Leza River catchment (Iberian System, Spain), representative of three different scenarios: (i) natural revegetation; (ii) human afforestation; and (iii) shrub clearing. Results shows how hydrological connectivity tends to decrease when vegetation cover increases (i.e., natural revegetation and human afforestation) while tend to increase when shrub clearing take place. Runoff coefficient followed a similar pattern, decreasing in basins where vegetation increases and decreasing where there was vegetation clearing. Important differences were observed in terms of the distribution of connectivity changes, their location in relation to the outlet and the effects on surface runoff. Studies of this type are necessary to know the response of the Mediterranean basins to different types of management with the aim of adopting sustainable management measures to guarantee surface water resources in a context of Global Change.

Attribution of current trends in streamflow to climate change for 12 Central Asian catchments

This study investigates the attribution of climate change to trends in river discharge during six decades from 1955 until 2014 in 12 selected river catchments across six Central Asian countries located upstream of the main rivers. For this purpose, the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model) was firstly calibrated and validated for all study catchments. Attributing climate change to streamflow simulation trends was forced by factual (reanalysis) and counterfactual climate data (assuming the absence of anthropogenic influence) proposed in the framework of the ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) or ESM without anthropogenic forcing that were firstly tested and then compared. The trend analysis was performed for three variables: mean annual discharge and high flow (Q5) and low flow (Q95) indices. The results show that trends in the annual and seasonal discharge could be attributed to climate change for some of the studied catchments. In the three northern catchments (Derkul, Shagan, and Tobol), there are positive trends, and in two catchments (Sarysu and Kafirnigan), there are negative streamflow trends under the factual climate, which could be attributed to climate change. Also, our analysis shows that the average level of discharge in Murghab has increased during the historical study period due to climate change, despite the overall decreasing trend during this period. In addition, the study reveals a clear signal of shifting spring streamflow peaks in all catchments across the study area.

Potential reduction in carbon fixation capacity under climate change in a Pinus koraiensis forest

There has been an increasing recognition of the crucial role of forests, responsible for sequestering atmospheric CO2, as a moral imperative for mitigating the pace of climate change. The complexity of evaluating climate change impacts on forest carbon and water dynamics lies in the diverse acclimations of forests to changing environments. In this study, we assessed two of the most common acclimation traits, namely leaf area index and the maximum rate of carboxylation (Vcmax), to explore the potential acclimation pathways of Pinus koraiensis under climate change. We used a mechanistic and process-based ecohydrological model applied to a P. koraiensis forest in Mt. Taehwa, South Korea. We conducted numerical investigations into the impacts of (i) Shared Socioeconomic Pathways 2–4.5 (SSP2-4.5) and 5–8.5 (SSP5-8.5), (ii) elevated atmospheric CO2 and temperature, and (iii) acclimations of leaf area index and Vcmax on the carbon and water dynamics of P. koraiensis. We found that there was a reduction in net primary productivity (NPP) under the SSP2-4.5 scenario, but not under SSP5-8.5, compared to the baseline, due to an imbalance between increases in atmospheric CO2 and temperature. A decrease in leaf area index and an increase in Vcmax of P. koraiensis were expected if acclimations were made to reduce its leaf temperature. Under such acclimation pathways, it would be expected that the well-known CO2 fertilizer effects on NPP would be attenuated.

Importance of measured transpiration fluxes for modelled ecohydrological partitioning in a tropical agroforestry system

Evaporation (E) and transpiration (Tr) are the key terrestrial water fluxes to the atmosphere and are highly sensitive to land cover change. These ecohydrological fluxes can be measured directly only at small scales, such as individual plants or under laboratory experiments. Modelling is needed to upscale E and Tr estimates to plot, hillslope and catchment scales. However, model-derived ecohydrological water partitioning of E and Tr can be ambiguous, particularly when models are trained using hydrometric data and soil moisture. To test the influence of different types of data (i.e., sap flux-derived Tr, Eddy Covariance-derived actual evapotranspiration (AET) and measured soil water (SW)) on model calibration and subsequent water partitioning, we developed the low-parameter plot scale ecohydrology model EcoHydroPlot applied to a data-rich experimental agroforestry plot in humid tropical Costa Rica. The model was able to simulate SW well when calibrated with any data type, but large differences emerged in the E and Tr flux partitioning. Using only hydrometric data for calibration resulted in parameter configurations that produced greater E over Tr fluxes (Tr/AET < 0.5). The opposite was seen for model calibration using Tr data (median Tr simulations with KGE > 0.6), resulting in Tr/AET ratios close to the observed ∼0.9. Further, using all measurements simultaneously (including AET, SW and Tr) did not improve simulated water partitioning. We only found small differences between sun and shade locations with slightly greater average shaded coffee transpiration at the expense of lower upper SW, higher deeper SW and less groundwater recharge compared to sun exposed coffee. This work can inform measurement priorities for applications with relatively simple conceptual ecohydrology models and emphasizes the importance of transpiration estimates for model calibration beyond tropical environments.

Exploring the Critical Zone Heterogeneity and the Hydrological Diversity Using an Integrated Ecohydrological Model in Three Contrasted Long‐Term Observatories

AbstractAn integrated ecohydrological modeling approach was deployed in three long‐term critical zone (CZ) observatories of the French CZ network (CZ Observatories—Application and Research) to better understand how the CZ heterogeneity modulates the water cycle within territories. Ecohydrological simulations with the physically based model EcH2O‐iso constrained by a wide range of observations crossing several disciplines (meteorology, hydrology, geomorphology, geophysics, soil sciences, and satellite imagery) are able to capture stream water discharges, evapotranspiration fluxes, and piezometric levels in the Naizin, Auradé, and Strengbach watersheds. In Naizin, an agricultural watershed in northwestern France with a schist bedrock underlying deep weathered materials (5–15 m) along gentle slopes, modeling results reveal a deep aquifer with a large total water storage (1,080–1,150 mm), an important fraction of inactive water storage (94%), and relatively long stream water transit times (0.5–2.5 years). In the Auradé watershed, representative of agricultural landscapes of the southwestern France developed on molasse, a relatively shallow regolith (1–8 m) is observed along hilly slopes. Simulations indicate a shallow aquifer with moderate total water storage (590–630 mm), an important fraction of inactive water storage (91%), and shorter stream water transit times (0.1–1.3 years). In the Strengbach watershed, typical of mid‐mountain forested landscapes developed on granite, CZ evolution implies a shallow regolith (1–5 m) along steep slopes. Modeling results infer a shallow aquifer with the smallest total water storage (475–575 mm), the shortest stream water transit times (0.1–0.7 years), but also the highest fraction of active water storage (18%).

Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model.

Modeling large-scale hydrological impacts brought about by site-level green and gray stormwater remediation actions is difficult because urbanized areas are extremely complex dynamic landscapes that include engineered features that, by design, expedite urban runoff to streams, creeks, and other water bodies to reduce urban flooding during storm events. Many urban communities use heavily engineered gray infrastructure to achieve that goal, along with more recent additions of green infrastructure such as rain gardens, bioswales, and riparian corridors. Therefore, successfully characterizing those design details and associated management practices, interactions, and impacts requires a detailed understanding of how fine and course-scale hydrologic processes and routing are altered and managed in urban watersheds. To enhance hydrologic modeling capabilities of urban watersheds, we implemented a number of improvements to an existing ecohydrology model called VELMA-Visualizing Ecosystem Land Management Assessments-including the addition of spatially explicit engineered features that impact urban hydrology (e.g., impervious surfaces, curbed roadways, stormwater routing) and refinement to the computational representations of evapotranspiration by adding impervious surface evaporation. We demonstrate improved capabilities for modeling within complex urbanized watersheds by simulating stream runoff within the Longfellow Creek watershed, City of Seattle, Washington (WA), United States (US) with and without these added urban watershed characteristics. The results demonstrate that the newly improved VELMA model allows for more accurate modeling of hydrology within urban watersheds. Being a fate and transport ecohydrology model, the improved hydrologic flow enhances VELMA's current capacity for modeling nutrient, contaminant, and thermal loadings.