Search Results (6)

Coastal forests are highly sensitive to both climate change and land use change, which can strongly affect hydrological processes and long-term water yield. This study quantifies the individual and combined impacts of climate change and land use/land cover (LULC) change on water yield in the Croatan National Forest (CNF), a coastal ecosystem in North Carolina, USA, from 2003 to 2070. To produce high-resolution climate projections, we extended the MIDAS (Machine Learning-Based Integration of Downscaled Projections for Accurate Simulation) approach by applying a full statistical downscaling of temperature and precipitation from CMIP6–SSP5-8.5 scenarios using the Random Forest algorithm. Future LULC scenarios were generated using machine learning and Markov Chain-based modeling to predict spatial changes up to 2070. The downscaled climate and LULC data were integrated into the WaSSI hydrological model to simulate their potential effects on water yield under the following four scenarios: baseline, LULC change only, climate change only, and combined change. The results showed that climate change alone could reduce annual water yield by about 11%, while LULC change alone could increase it by roughly 3% due to lower evapotranspiration from forest-to-urban conversion. Under the combined scenario, water yield decreased by about 6%, indicating that climate change dominated, but LULC change could locally alter or influence its effects. Overall, the findings highlight that climate change could be the primary driver of reduced water yield in coastal forests, while LULC change mainly affects its spatial variability. This integrated framework improves the accuracy of regional hydrological projections and provides useful insights for climate adaptation and sustainable water resource management in coastal forest ecosystems. Full article

Nepal is known for its complex terrain, climate, and vegetation dynamics, resulting in tremendous hydrologic variability and complexity. Accurately quantifying the water balances at the national level in Nepal is extremely challenging and is currently not available. This study constructed long-term (2000–2022) water balances for 358 watersheds across Nepal by integrating watershed hydrometeorological monitoring data, remote sensing products including Leaf Area Index and land use and land cover data, with an existing ecohydrological model, Water Supply Stress Index (WaSSI). The WaSSI model’s performance is assessed at both watershed and national levels using observed water yield (Q) and evapotranspiration (ET) products derived from remote sensing (ETMonitor, PEW, SSEBop) and eddy flux network (i.e., FLUXCOM). We show that the WaSSI model captured the seasonal dynamics of ET and Q, providing new insights about climatic controls on ET and Q across Nepal. At the national scale, the simulated long-term (2000–2020) mean annual Q and ET was about half of the precipitation (1567 mm), but both Q and ET varied tremendously in space and time as influenced by a monsoon climate and mountainous terrain. We found that watersheds in the central Gandaki River basin had the highest Q (up to 1600 mm yr⁻¹) and ET (up to 1000 mm yr⁻¹). This study offers a validated ecohydrological modeling tool for the Himalaya region and a national benchmark dataset of the water balances for Nepal. These products are useful for quantitative assessment of ecosystem services and science-based watershed management at the national scale. Future studies are needed to improve the WaSSI model and remote sensing ET products by conducting ecohydrological research on key hydrologic processes (i.e., forest ET, streamflow generations of small watersheds) across physiographic gradients to better answer emerging questions about the impacts of environmental change in Nepal. Full article

This study conducts a comparison of two ecosystem service models: the Water Supply Stress Index (WaSSI) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST). It focuses on each model’s capability to estimate annual water yield within the Croatan National Forest (CNF). The Croatan Forest, characterized as a coastal ecosystem with high biodiversity and unique water resource management challenges, provides an opportune setting to examine and compare the accuracy and efficiency of these models in predicting water yield. Utilizing field data and remote sensing, we investigated the capabilities of both models to estimate water yield. The results indicate that both models can serve as useful tools for water resource management in coastal ecosystems, yet there are differences in their accuracy and sensitivity to environmental factors. This study is the first to compare the two ecosystem models, the WaSSI and InVEST, within a coastal forest setting for the calculation of water yield. Full article

Climate change, socioeconomic development, and irrigation management are exacerbating water scarcity in many regions worldwide. However, current global-scale modeling approaches used to evaluate the impact of these factors on water resources are limited by coarse resolution and simplified representation of local socioeconomic and agricultural systems, which hinders their use for regional decision making. Here, we upgraded the irrigation water use simulation in the system dynamics and water environmental model (SyDWEM) and integrated it with the water supply stress index (WaSSI) ecosystem services model. This integrated model (SyDWEM-WaSSI) simulated local socioeconomic and agricultural systems to accurately assess future water stress associated with climate change, socioeconomic development, and agricultural management at subbasin levels. We calibrated the integrated model and applied it to assess future water stress levels in Texas from 2015 to 2050. The water stress index (WSI), defined as the ratio of water withdrawal to availability, was used to indicate different water stress levels. Our results showed that the integrated model captured changes in water demand across various sectors and the impact of climate change on water supply. Projected high water stress areas (WSI > 0.4) are expected to increase significantly by 2050, particularly in the Texas High Plains and Rolling Plains regions, where irrigation water use was projected to rise due to the impact of climate change. Metropolitan areas, including Dallas, Houston, Austin, and San Antonio, were also expected to experience increased domestic water demand, further exacerbating water stress in these areas. Our study highlights the need to incorporate socioeconomic planning into water resources management. The integrated model is a valuable tool for decisionmakers and stakeholders to evaluate the impacts of climate change, socioeconomic development, and irrigation management on water resources at the local scale. Full article

Hurricanes are one of the most significant threats to coastal plain forest ecosystems and urban communities of the southeastern U.S., but their implications for watershed hydrology are unclear. Hurricanes have the potential to alter water balances, causing extensive flooding, biogeochemical cycle disruption, and water quality degradation, saltwater intrusion, and increased nutrient sedimentation export in coastal watersheds. This case study focused on Hurricane Michael, a recent catastrophic event that impacted the Gulf coast, the Florida panhandle, southwestern Georgia, and southeastern Alabama. Through empirical (Double Mass Curve) and process-based ecohydrological modeling (WaSSI model) on long-term streamflow data, we explored whether vegetation damage caused by this hurricane resulted in an increase in streamflow two years after the extreme event. We found that monthly streamflow from the Chipola River watershed with an area of 2023 km² did not change (<6%) appreciably during the first two years following the storm, arguably because only a fraction of the gauged watershed lost substantial tree cover. However, spatially explicit hydrological modeling suggested that several sub-watersheds with the highest decreases in the Normalized Difference Vegetation Index (NDVI) significantly increased their monthly streamflow in 2019 by up to 22%. These modeled streamflow anomalies subsided by the second growing season when vegetation recovered. Overall, this study suggests that changes in vegetation cover after Hurricane Michael did not have lasting impacts on the hydrology of this watershed, and the hydrology of coastal watersheds may be more resilient to hurricane disturbances than previously thought. Full article

A water and sanitation sustainability index (WASSI) was developed and estimated in four cities of the province of Salta, in northern Argentina. The index was built with nine descriptors and fifteen indicators that covered all essential aspects of the sustainability of local water and sanitation management systems. Only one of the cities studied obtained a sustainability value above the acceptability threshold adopted (50 of 100 points). Results indicate that the water company needs to address some environmental and social issues to enhance the sustainability of the systems studied. The WASSI was conceptually robust and operationally simple, and could be easily adapted to the case studies. The index can be followed and updated online on a web site specially developed for this project. This website could be useful to promote participatory processes, assist decision makers, and facilitate academic research. According to local stakeholders, a more open sustainability assessment based on sustainability indices and supported by virtual tools would be relevant and highly feasible. It would help decision makers improve the sustainability and transparency of water and sanitation management systems, and promote more sustainable water policies in the region and beyond. Full article