Sub-basin Scale Research Articles

Supply and demand dynamics of hydrologic ecosystem services in the rapidly urbanizing Taihu Lake Basin of China

Although it is challenging to integrate supply and demand to comprehensively understand urbanization effects on ecosystem services, this knowledge is essential, especially in rapidly urbanizing areas. A spatially explicit approach was developed here to synthesize supply and demand dynamics of the two most important hydrologic services in the rapidly urbanizing Taihu Lake Basin (TLB) of eastern China. The supply of water purification (WPS) and flood mitigation (FMS) were measured as nitrogen removal and runoff retention, respectively. Whereas the demand for water purification (WPD) was quantified as the difference between total and permitted nitrogen loading based on relevant water quality standards, the demand for flood mitigation (FMD) was estimated as the vulnerability to potential flood damage, including economic losses and causalities. We found a spatial mismatch where high WPS and FMS occurred in mountainous areas while high WPD and FMD concentrated in urban and agricultural areas across the basin. WPS and WPD decreased by 10% and 20%, respectively during 2000–2015, due mainly to loss of croplands to urban expansion. This was also the main cause of decreased FMS by 7% but increased FMD by 67%, which underscored the importance of conserving croplands in rapidly urbanizing regions of the TLB. Overall, land use composition had strong associations with WPD (r2 ≥ 0.57) and FMS (r2 ≥ 0.38) at the sub-basin scale, while the configuration of multiple land uses, such as urban sprawl, cropland fragmentation, and riparian buffers were crucial in influencing WPS. In comparison, FMD was most sensitive to urban expansion (r2 = 0.74), economic development (r2 = 0.81), and population growth (r2 = 0.93). These findings provide new insights into sustainable land management for coordinating supply of and demand for hydrologic services in the TLB and other urbanizing watersheds of the world.

Spatio-Temporal Analysis of Water Supply Services in the Li River Basin

The water supply services of the Li River are essential for the ecological environment and local social development. Based on the InVEST model, we quantitatively analyzed the spatial and temporal distribution patterns of water supply services in the Li River Basin from 2000 to 2018 at multiple scales, including the raster, sub-basin, and regional scales, clarified the differences in water yield among different land use types, and explored the different stages of changes in the characteristics of water services. The results revealed four key aspects of this system. (1) The water supply service of Li River Basin showed a spatial distribution pattern of high in the north and low in the south, and the water yield gradually decreased from north to south. (2) Among the various land use types in Li River Basin, the average water supply capacity decreased in the following order: artificial surface, unused land, grassland, forest, cropland and wetland. (3) The average amounts of water services in the 18 sub-basins varied widely, with four sub-basins belonging to the high-value area for water supply services, eight in the middle-value area, and six in the low-value area. (4) From 2000 to 2010, the regions with large fluctuations in water supply services include the midstream region, Lipu River region, and the northern region of Gongcheng River; while from 2010 to 2018, the areas with large fluctuations were in the midstream region and Gongcheng River region. The results of this research increase our understanding of the water supply services in the Li River Basin and provide a critical scientific basis for the reverse compensation of a regional ecological compensation mechanism.

Topographical and morphological variability explicates the regional heterogeneity in glacier surface ice velocity across Karakoram-Himalaya

Understanding the implications of variations in glacier surface ice velocity (SIV) has become an essential component of glacier research and monitoring. This study investigates the variability in SIV with respect to geography, morphology, and topography in Karakoram-Himalaya. SIVs are extracted for 1439 glaciers in the Karakoram-Himalaya region for the period 2016–2019 using Landsat-8 datasets and a feature tracking method. Glaciers are categorized based on their area, ice thickness, and ice volume in order to investigate the SIV variability with geographical, morphological, and topographical parameters. We highlight regional heterogeneities in glacier SIV across the Karakoram-Himalaya. We conclude that in addition to glacier morphology, the altitudinal heterogeneity of glaciers in the Karakoram-Himalaya best explains regional disparities in glacier SIV. For all glacier areas smaller than 20 km2, a significant negative correlation (less than −0.4) is observed between glacier minimum elevation and SIV. Heterogeneity in the role of elevation on SIV is also observed at the sub-basin scale, with a correlation of −0.47, −0.33, and −0.18 in the Hanza, Chenab, and Kosi sub-basins, respectively. An unsystematic variability of SIV for large glaciers (area >20 km2), located mostly in the Karakoram and Western Himalayan regions, suggests that the elevation and sub-glacial hydrology may have a significant impact on their dynamics.

Intra-annual sediment dynamic assessment in the Wei River Basin, China, using the AIC functional-structural connectivity index

Hydrological and sediment dynamics have changed considerably on the Chinese Loess Plateau during the last six decades due to large scale land use changes and numerous water regulation actions. Understanding the mechanism of sediment transport change and its effects is of great importance to food and environmental security. Numerical approaches are useful to map and assess spatio-temporal patterns in sediment dynamics. This study evaluates monthly and annual sediment connectivity in the Wei River Basin (134,800 km2) at the basin and sub-basin scales using the aggregated index of sediment connectivity (AIC). For the first time, this index is applied on this relatively large regional scale. The two objectives were to (1) evaluate the performance of the AIC at the regional scale, addressing substantial differences among areas, and (2) analyze how each AIC sub-factor co-determines the monthly sediment and connectivity patterns. Results show that AIC has strong or moderate positive correlation with sediment yield from 15 out of 23 stations in the Wei and Jing sub-basin. The Jing sub-basin has the highest sediment connectivity due to degraded vegetation, while the Beiluo sub-basin has the lowest sediment connectivity on average due to better ecological restoration. Within the year, sediment connectivity is highest in April and lowest in January, due to the rainfall regime and intra-annual land cover variations. Among the AIC factors, the rainfall factor has the highest effect on sediment connectivity, implying that functional connectivity (graded by rainfall and soil cover) determines sediment dynamics more than structural connectivity (mainly determined by topography and soil permeability). This study provides one of the first large-scale estimates of spatial and temporal sediment connectivity from hillslopes to river stream and including large reservoirs, which can be further employed to implement regional ecological construction works and environmental catchment management.

Analysis of spatiotemporal variation in dissolved organic carbon concentrations for streams with cropland-dominated watersheds

It remains a challenge to understand how dissolved organic carbon (DOC) is cycled from farmlands to rivers due to the complex interaction between farming practices, the baseflow hydrology of predominantly flat lowlands, and seasonal environmental influences such as snowpack. To address this, field DOC concentrations were measured monthly throughout the year at sub-basin scales across the Chippewa River Watershed, which falls within the Corn Belt of the Midwestern United States. These DOC dynamics in stream water from croplands were benchmarked against the data sampled from hilly forested areas in the Connecticut River Watershed. The Soil Water Assessment Tool (SWAT) simulation was applied to provide potential predictive variables associated with daily baseflow. Our study outlines a framework using the combination of primary field data, hydrological modeling, and knowledge-based reclassification of Land Use/Land Cover (LULC) data to analyze the viability of modeling the spatial and temporal variations of cropland stream DOC concentrations. Calibration of the SWAT model resulted in the overall daily Nash–Sutcliffe model efficiency coefficient (NSE) of 0.67 and the corresponding R2 = 0.89. Our main results show: 1) baseflow DOC concentrations from croplands were substantially higher throughout the year relative to other landcover areas, especially for spring runoff/snowmelt scenarios, 2) an empirical analysis explained ~82 % of the spatial gradient of annual mean observed DOC concentrations, and 3) with the addition of hydrological simulated variables, a linear model explained ~81 % of monthly and 54 % of daily variations of observed DOC concentrations for cropland sub-basins. Our study identified key factors regulating the spatiotemporal DOC concentrations in cropland streamflow; the contribution here promotes to strengthen future analytical models that link watershed characteristics to carbon cycling processes in a large freshwater ecosystem.

Assessment of Future Land Use/Land Cover Scenarios on the Hydrology of a Coastal Basin in South-Central Chile

Land use and land cover (LULC) change is one of the clearest representations of the global environmental change phenomenon at various spatial and temporal scales. Chile is worldwide recognized to have areas dedicated to non-native forest plantations that specifically in coastal range show high environmental and economic deterioration, questioning the sustainability of the forestry industry. Currently, there are no studies in Chile that reveal the real effects of the LULC change on the water balance at basin or sub-basin scales associated with future scenarios, which might contribute to territorial decision-making and reveal the real magnitude of the effects of these dynamics. In this study, in order to study LULC dynamics in a coastal basin in South-Central Chile, we assessed and analyzed the effects of future LULC change scenarios on the hydrological processes by generating future synthetic land cover maps from Landsat (Landsat 5 TM and Landsat 8 OLI) image datasets. The hydrological model Soil Water Assessment Tool (SWAT) was calibrated and validated, using hydroclimatic time series, to simulate discharges and other hydrological components over those future LULC scenarios. The LULC future scenarios were projected using combined Markov chain analysis (CA–Markov) and cellular automata algorithms for the near (2025), middle (2035) and far (2045) future. The results revealed that the effects on the different components of the water balance of the basin are not as significant except in the soil water transfer in percolation (increase 72.4%) and groundwater flow (increase 72.5%). This trend was especially observed in sub-basins with non-native forest plantations that dominated land cover in the year 2035, in which an increase of 43.6% in percolation and groundwater flows resulted in increased aquifer recharge and water storage, mainly offset by a decrease of 27% in the evapotranspiration. This work demonstrates the importance of evaluating the impacts of the dynamics of LULC on the hydrological response of a coastal basin, and also on how the land use governance and policy are closely linked to that of water resources.

Using a Bayesian joint probability approach to improve the skill of medium-range forecasts of the Indian summer monsoon rainfall

Study regionGanga, Mahanadi, Godavari, Narmada, and Tapti River basins of India. Study focusThe manuscript focuses on improving skills of the Indian summer-monsoon precipitation forecasts obtained from National Center for Medium-Range Weather Forecasting (NCMRWF) at both sub-basin and gridded scale. A well-established Bayesian Joint Probability (BJP) based statistical post-processing approach, operational in Australia, is used for the first time in India throughout diverse geographical extent. The work evaluates how the post-processor can be used in a summer-monsoon dominated region like India. The study informs whether annual or seasonal precipitation forecasts should be used as the length of data will play crucial role in both the cases. The spread-skill of the ensembles obtained from BJP approach and the NCMRWF is explored. New hydrological insights for the regionIntroduction of the BJP-based post-processing approach in India could help the forecast community to implement more robust approach in improving the skills of the forecasts. Our results show that instead of using the data of whole year, only monsoonal precipitation forecasts are adequate to setup the BJP approach. The calibrated forecasts obtained using three years of hindcast and observations data at grids and at the centroid of 177 sub-basins are found to be more skillful. The calibrated forecasts can discriminate between extreme and low precipitation events, and have appropriate ensemble spread to capture precipitation peaks. This study presents a guideline for water managers and forecasters to apply BJP approach to improve the forecasts.

A database of water chemistry in eastern Siberian rivers

Permafrost degradation leads to considerable changes in river ecosystems. The Eastern Siberian River Chemistry (ESRC) database was constructed to create a spatially extensive river chemistry database to assess climate warming-induced changes in freshwater systems in permafrost-dominated eastern Siberia. The database includes 9487 major ion (Na+, K+, Ca2+, Mg2+, Cl−, SO42− and HCO3−) data of chemical results from 1434 water samples collected mainly in six large river basins in eastern Siberia spanning 1940–2019. Data were obtained from public databases, scientific literature in English and Russian, and researchers and were formatted with a consistent table structure. The database is transparent and reproducible. Climate variable (air temperature and precipitation) data, discharge data, trace element concentration data, and isotope data at the basin and subbasin scales are also provided. This database enhances knowledge about the water chemistry of the permafrost region, especially in eastern Siberia, where data are scarce. The database will be useful to those assessing spatiotemporal changes in river water chemistry associated with permafrost degradation or other environmental stressors in a warmer climate.

Impacts of land use/cover change on water balance by using the SWAT model in a typical loess hilly watershed of China

Land use/cover change (LUCC) plays a key role in altering surface hydrology and water balance, finally affecting the security and availability of water resources. However, mechanisms underlying LUCC determination of water-balance processes at the basin scale remain unclear. In this study, the Soil and Water Assessment Tool (SWAT) model and partial least squares regression were used to detect the effects of LUCC on hydrology and water components in the Zuli River Basin (ZRB), a typical watershed of the Yellow River Basin. In general, three recommended coefficients (R² and Ens greater than 0.5, and Pbias less than 20%) indicated that the output results of the SWAT model were reliable and that the model was effective for the ZRB. Then, several key findings were obtained. First, LUCC in the ZRB was characterized by a significant increase in forest (21.61%) and settlement (23.52%) and a slight reduction in cropland (–1.35%), resulting in a 4.93% increase in evapotranspiration and a clear decline in surface runoff and water yield by 15.68% and 2.95% at the whole basin scale, respectively. Second, at the sub-basin scale, surface runoff and water yield increased by 14.26%–36.15% and 5.13%–15.55%, respectively, mainly due to settlement increases. Last, partial least squares regression indicated that urbanization was the most significant contributor to runoff change, and evapotranspiration change was mainly driven by forest expansion. These conclusions are significant for understanding the relationship between LUCC and water balance, which can provide meaningful information for managing water resources and the long-term sustainability of such watersheds.

Correction: Ramillien et al. An Innovative Slepian Approach to Invert GRACE KBRR for Localized Hydrological Information at the Sub-Basin Scale. Remote Sens. 2021, 13, 1824

There was an error in the original article [...]

Multi-Scale Effects of Meteorological Conditions and Anthropogenic Emissions on PM2.5 Concentrations over Major Cities of the Yellow River Basin.

The mechanism behind PM2.5 pollution is complex, and its performance at multi-scales is still unclear. Based on PM2.5 monitoring data collected from 2015 to 2021, we used the GeoDetector model to assess the multi-scale effects of meteorological conditions and anthropogenic emissions, as well as their interactions with PM2.5 concentrations in major cities in the Yellow River Basin (YRB). Our study confirms that PM2.5 concentrations in the YRB from 2015 to 2021 show an inter-annual and inter-season decreasing trend and that PM2.5 concentrations varied more significantly in winter. The inter-month variation of PM2.5 concentrations shows a sinusoidal pattern from 2015 to 2021, with the highest concentrations in January and December and the lowest from June to August. The PM2.5 concentrations for major cities in the middle and downstream regions of the YRB are higher than in the upper areas, with high spatial distribution in the east and low spatial distribution in the west. Anthropogenic emissions and meteorological conditions have similar inter-annual effects, while air pressure and temperature are the two main drivers across the whole basin. At the sub-basin scale, meteorological conditions have stronger inter-annual effects on PM2.5 concentrations, of which temperature is the dominant impact factor. Wind speed has a significant effect on PM2.5 concentrations across the four seasons in the downstream region and has the strongest effect in winter. Primary PM2.5 and ammonia are the two main emission factors. Interactions between the factors significantly enhanced the PM2.5 concentrations. The interaction between ammonia and other emissions plays a dominant role at the whole and sub-basin scales in summer, while the interaction between meteorological factors plays a dominant role at the whole-basin scale in winter. Our study not only provides cases and references for the development of PM2.5 pollution prevention and control policies in YRB but can also shed light on similar regions in China as well as in other regions of the world.

Effects of Design and Climate on Bioretention Effectiveness for Watershed-Scale Hydrologic Benefits

Bioretention areas are a common form of green stormwater infrastructure (GSI). There is significant research on the performance of individual bioretention cells, but the watershed-scale benefits of GSI are still unclear. Furthermore, differences in bioretention design and rainfall patterns make it difficult to compare results between studies. We used the Storm Water Management Model (SWMM) to assess the effects of bioretention size, soil infiltration rate, storm size, and climate on the watershed-scale performance of GSI. We first divided the contiguous US into 10 rainfall regions based on similarities in precipitation amount, intensity, and other storm characteristics. We then modeled the effects of bioretention areas in a single watershed under these different rainfall regimes. Bioretention areas did provide watershed-scale benefits, although performance declined as (1) bioretention areas became smaller, (2) soil infiltration rates decreased, and (3) precipitation depth increased. High-intensity rainfall was the primary cause of outflow from bioretention areas, although back-to-back storm events also caused outflow in some climates. There were some clear discrepancies between subbasin-scale and watershed-scale GSI performance. Generally, runoff volume reduction was greater when measured at the subbasin scale. Peak flow reduction, however, was greater at the watershed-scale, likely because bioretention areas changed the shape of subbasin runoff hydrographs, leading to watershed-scale peak flow reduction that was greater than the sum of the parts. We provide recommendations for design, management, and future research to help advance effective application of GSI for achieving watershed-scale hydrologic benefits.

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

Assessing non-point source pollution in an apple-dominant basin and associated best fertilizer management based on SWAT modeling

Investigating the impact of apple-dominated areas on nitrogen (N) and phosphorus (P) losses at a basin scale was essential for the sustainable development of apple industry in China. This study conducted a survey on fertilizer application and built a Soil and Water Assessment Tool (SWAT) model to quantitatively analyze the N and P losses in the Qixia apple-dominated area. Additionally, the decreases in N and P losses through adjusting the fertilizer application modes were evaluated. Results showed that average N and P losses in the Wulong River Basin (WRB) were 44.4 and 0.365 kg ha−1 in 2011–2017, respectively, and apple orchards accounted for 73.3% and 51.4% of the total N and P losses in the basin. Under nine fertilizer scheduling scenarios, three fertilizer schedule scenarios, automatic fertilizer application (S-AUTO), “one shot” mode (S1), and regulated fertilizer application (S-BSD), had the lowest N and P losses in apple orchards. The decreases in N loss ranged from 20.6% to 26.1% at the subbasin scale and 14.8%–30.7% at the basin outlet when applying the S-AUTO, S1, and S-BSD fertilizer application modes in Qixia apple orchards and all apple orchards in the WRB. The reductions in P loss varied from 22.0% to 46.1% at the subbasin scale and 14.6%–25.6% at the basin outlet. In orchard-dominated basin, N and P losses can be effectively reduced by optimizing the orchard fertilizer scheduling strategies.

Managing landscape patterns at the riparian zone and sub-basin scale is equally important for water quality protection

Widespread attention has been given to understanding the effect of the landscape pattern on river water quality. However, which spatial scale (riparian zone versus sub-basin) has the greater impact on water quality has long been controversial, since the key metrics that affect water quality varied with spatial scale. Thus, quantifying the spatial scale effects of key landscape metrics on water quality is critical to clarifying which scale of landscape pattern is more conducive to water quality conservation. Here, we adopted variation partitioning analysis (VPA) and random forest models to quantify the landscape pattern impact on water quality at northern Erhai Lake during the 2019 rainy season (early, mid, and late), and comprehensively analyze the key landscape metrics on different scales. The results revealed that the riparian zone and sub-basin scale landscape patterns explained similar water quality variations (difference only 0.9%) in the mid (August) and late rainy season (October), but exhibited a large difference (24.1%) during the early rainy season (June). Furthermore, rivers were primarily stressed by nitrogen pollution. Maintaining the Grassland_ED > 27.99 m/ha, Grassland_LPI > 4.19%, Farmland_LSI < 3.2 in the riparian zone, and Construction_ED < 1.69 m/ha, Construction_LSI < 2.46, Farmland_PLADJ < 89.0% at the sub-basin scale could significantly reduce the TN concentration in the stream. Meanwhile, managing of these metrics can effectively prevent rapid increases of TN in rivers. Moreover, due to the low phosphorus concentration in the rivers, none of the landscape metrics significantly explained the variation in TP. This study explored the spatial scale effect of landscape patterns on water quality and revealed the driving factors of nutrient variation. This study will provide a scientific basis for aquatic environmental management in plateau watersheds.

Impacts of land uses on spatio-temporal variations of seasonal water quality in a regulated river basin, Huai River, China

Land use impacts from agriculture, industrialization, and human population should be considered in surface water quality management. In this study, we utilized an integrated statistical analysis approach mainly including a seasonal Mann-Kendall test, clustering analysis, self-organizing map, Boruta algorithm, and positive matrix factorization to the assessment of the interactions between land use types and water quality in a typical catchment in the Huai River Basin, China, over seven years (2012–2019). Spatially, water quality was clustered into three groups: upstream, midstream, and downstream/mainstream areas. The water quality of upstream sites was better than of mid-, down-, and mainstream. Temporally, water quality did not change significantly during the study period. However, the temporal variation in water quality of up-, down-, and mainstream areas was more stable than in the midstream. The interactions between land use types and water quality parameters at the sub-basin scale varied with seasons. Increasing forest/grassland areas could substantially improve the water quality during the wet season, while nutrients such as phosphorus from cropland and developed land was a driver for water quality deterioration in the dry season. Water area was not a significant factor influencing the variations of ammonia nitrogen (NH3-N) and total phosphorus (TP) in the wet or dry season, due to the intensive dams and sluices in study area. The parameters TP, and total nitrogen (TN) were principally linked with agricultural sources in the wet and dry seasons. The parameters NH3-N in the dry season, and chemical oxygen demand (CODCr) in the wet season were mainly associated with point source discharges. Agricultural source, and urban point source discharges were the main causes of water quality deterioration in the study area. Collectively, these results highlighted the impacts of land use types on variations of water quality parameters in the regulated basin.

Variability and Predictability of Basinwide and Sub-Basin Tropical Cyclone Genesis Frequency in the Northwest Pacific

Abstract The variability and predictability of tropical cyclone genesis frequency (TCGF) during 1973–2010 at both basinwide and sub-basin scales in the northwest Pacific are investigated using a 100-member ensemble of 60-km-resolution atmospheric simulations that are forced with observed sea surface temperatures (SSTs). The sub-basin regions include the South China Sea (SCS) and the four quadrants of the open ocean. The ensemble-mean results well reproduce the observed interannual-to-decadal variability of TCGF in the southeast (SE), northeast (NE), and northwest (NW) quadrants, but show limited skill in the SCS and the southwest (SW) quadrant. The skill in the SE and NE quadrants is responsible for the model’s ability to replicate the observed variability in basinwide TCGF. Above-normal TCGF is tied to enhanced relative SST (i.e., local SST minus tropical-mean SST) either locally or to the southeast of the corresponding regions in both the observations and ensemble mean for the SE, NE, and NW quadrants, but only in the ensemble mean for the SCS and the SW quadrant. These results demonstrate the strong SST control of TCGF in the SE, NE, and NW quadrants; both empirical and theoretical analyses suggest that ensembles of ∼10, 20, 35, and 15 members can capture the SST-forced TCGF variability in these three sub-basin regions and the entire basin, respectively. In the SW quadrant and the SCS, TCGF contains excessive noise, particularly in the observations, and thus shows low predictability. The variability and predictability of the large-scale atmospheric environment and synoptic-scale disturbances and their contributions to those of TCGF are also discussed.

Impacts of different types of El Niño events on water quality over the Corn Belt, United States

Abstract. The United States Corn Belt region, which primarily includes two large basins, namely, the Ohio–Tennessee River basin (OTRB) and the Upper Mississippi River basin (UMRB), is responsible for the Gulf of Mexico hypoxic zone. Climate patterns such as El Niño can affect the runoff and thus the water quality over the Corn Belt. In this study, the impacts of eastern Pacific (EP) and central Pacific (CP) El Niño events on water quality over the Corn Belt region were analyzed using the Soil and Water Assessment Tool (SWAT) models. Our results indicated that, at the outlets, annual total nitrogen (TN) and total phosphorus (TP) loads decreased by 13.1 % and 14.0 % at OTRB and 18.5 % and 19.8 % at UMRB, respectively, during the EP El Niño years, whereas during the CP El Niño years, they increased by 3.3 % and 4.6 % at OTRB and 5.7 % and 4.4 % at UMRB, respectively. On the subbasin scales, more subbasins showed negative (positive) anomalies of TN and TP during EP (CP) El Niño. A seasonal study confirmed that water quality anomalies showed the opposite patterns during EP and CP El Niño years. At the outlet of OTRB, seasonal anomalies in nutrients matched the El Niño–Southern Oscillation (ENSO) phases, illustrating the importance of climate variables associated with the two types of El Niño events on water quality in the region. At the UMRB, TN and TP were also influenced by agricultural activities within the region, and their anomalies became greater in the growing seasons during both EP and CP El Niño years. A quantitative analysis of precipitation, temperature, and their effects on nutrients suggested that precipitation played a more important role than temperature did in altering the water quality in the Corn Belt region during both types of El Niño years. We also found specific watersheds (located in Iowa, Illinois, Minnesota, Wisconsin, and Indiana) that faced the greatest increases in TN and TP loads and were affected by both the precipitation and agricultural activities during the CP El Niño years. The information generated from this study may help proper decision-making for water environment protection over the Corn Belt.

Understanding robustness in multiscale nutrient abatement: Probabilistic simulation-optimization using Bayesian network emulators

Ecosystem management in the face of uncertain disturbances has triggered increasing practices of resilience thinking. A multiscale probabilistic simulation-optimization framework is developed based on the nested nature of watersheds to inform decision robustness for Best Management Practices (BMPs). We presented a novel approach using hybrid Bayesian Networks (BNs) as interpretable and probabilistic emulators of process-based models. The hybrid BNs established at the scale of Hydrologic Response Units (HRUs) are embedded into simulation-optimization, whereby we analyze the cost-effectiveness-robustness of candidate BMP strategies at the subbasin scale. The optimal strategy is identified in compliance with water quality standards using watershed-scale integer programming. We apply the approaches in a typical intensively cultivated plateau watershed adjacent to Lake Dianchi, one of the three most eutrophic lakes in China. Our findings suggest that the hybrid BNs, incorporating both quantitative and qualitative information, are reliable emulators of the Soil and Water Assessment Tool (SWAT) in capturing critical pathways of diffuse phosphorus. Tradeoffs among cost, effectiveness, and robustness follow the law of diminishing marginal benefits. The optimum BMP strategies vary with policymakers’ preference toward robustness levels. Our findings indicate that robustness should be accounted for as an additional decision attribute besides costs and pollution mitigation. The benefits of the modeling framework are to (i) reduce over 99% computation complexity and support efficient decision-making under multifaceted uncertainties; (ii) improve interpretability and reliability of machine learning emulators; and (iii) inform policymakers of robustness with the probability of water quality restoration success.

Basin-wide estimates of loggerhead turtle abundance in the Mediterranean Sea derived from line transect surveys

Loggerhead turtles are a globally vulnerable species of marine turtle. Broad-scale patterns of distribution and abundance can provide regional managers a tool to effectively conserve and manage this species at basin and sub-basin scales. In this study, combined aerial and shipboard line transect survey data collected between 2003 and 2018 were used to estimate distribution and abundance throughout the Mediterranean Sea. Approximately 230,000 linear kilometers of survey effort, from seven different surveying organizations were incorporated into a generalized additive model to relate loggerhead density on survey segments to environmental conditions. Two spatial density models estimating loggerhead density, abundance, and distribution were generated – one a long-term annual average covering 2003-2018 and another covering the summer of 2018, when a basin-wide aerial survey, the Agreement on the Conservation of Cetaceans of the Black Sea, Mediterranean Sea and Contiguous Atlantic Area Survey Initiative, was performed. Both models were adjusted for availability bias using dive data from loggerhead turtles tagged with time depth recorders. Mean abundance for the long-term average model was estimated as 1,201,845 (CV=0.22). The summer 2018 abundance estimate was 789,244 turtles and covered a smaller area than the long-term average. These estimates represent the first basin-wide estimates of abundance for loggerhead turtles in the Mediterranean not based on demographic models. Both models predicted similar distributions, with higher abundance predicted in the northern Adriatic Sea, central Mediterranean basin, Tyrrhenian Sea, and south of the Balearic Islands. Lower densities were predicted in the eastern Mediterranean Sea and the Aegean Sea. The highest density areas generally did not coincide with previously established adult loggerhead turtle foraging areas, which are typically neritic, indicating the models are predominantly predicting oceanic distributions, where most of the survey effort occurred. Juvenile loggerhead turtles are predominantly oceanic and comprise most of the population, but care must be taken when using these models as they may not accurately predict distribution of neritic foraging areas, where subadult and adult loggerheads can often be found. Despite this limitation, these models represent a major step forward for conservation planning and understanding basin-wide distribution and abundance patterns of this species.