Article
Meteorology & Atmospheric Sciences
Marisol Osman, Caio A. S. Coelho, Carolina S. Vera
Summary: Models from the North American Multi Model Ensemble project were calibrated and combined using Ensemble Regression method to produce reliable precipitation probabilistic forecasts over South America. Different approaches based on EREG were applied to combine forecasts, with results showing that the consolidated forecasts were more skillful than the simple multi-model ensemble, especially in regions impacted by the El Nino Southern Oscillation.
Article
Water Resources
Thatkiat Meema, Yasuto Tachikawa, Yutaka Ichikawa, Kazuaki Yorozu
Summary: This study assesses the sensitivity of Nam Ngum 1 reservoir operation to water resource uncertainty driven by climate change and upstream cascade dam development. Results show that these factors will impact the inflow and energy production of the reservoir. The study suggests that hydropower operation should be adapted to the effects of climate change.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2021)
Article
Engineering, Civil
Jinkai Luan, Yongqiang Zhang, Ning Ma, Jing Tian, Xiaojie Li, Dengfeng Liu
Summary: The study found that human activities play a leading role in streamflow changes in most selected catchments. There are significant differences in the contribution of human activities across different methods, and in catchments with two change periods, there is a trend of increasing contribution of human activities.
JOURNAL OF HYDROLOGY
(2021)
Article
Green & Sustainable Science & Technology
Changzheng Chen, Rong Gan, Dongmei Feng, Feng Yang, Qiting Zuo
Summary: Assessing the impacts of climate change on hydrologic systems is crucial for water resources management and ecological protection. This study develops a workflow that integrates different calculation methods and models to evaluate the uncertainties in future runoff projections. The results show potential increases in monthly and annual runoff, with evapotranspiration calculation methods and climate models being the main sources of uncertainty.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Civil
Chengxin Luo, Wei Ding, Chi Zhang, Xuan Yang
Summary: To effectively mitigate droughts, multiple hydrological forecasts are needed. This study proposes a novel Model Predictive Control (MPC) that integrates streamflow forecast, regime state forecast, and annual streamflow volume state forecast. By incorporating these forecasts, significant performance gains can be achieved in drought mitigation. However, forecast value is influenced by forecast uncertainty and other factors.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Nabil Al Aamery, James F. Fox, Tyler Mahoney
Summary: This study focused on forecasting sediment transport using global climate model ensembles and identified hydrologic modeling parameterization as the primary source of variance impacting forecasted sediment transport, surpassing the uncertainty from the selected global climate model realizations. Climate change impacts on sediment transport were mainly attributed to meteorological variables like precipitation and temperature, with underestimation observed when considering only these factors. Variance introduced by different global climate model ensembles had limited impact on forecasted streamflow and sediment yield, indicating the importance of researcher effort in designing ensemble models for robust results.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
David McInerney, Mark Thyer, Dmitri Kavetski, Richard Laugesen, Fitsum Woldemeskel, Narendra Tuteja, George Kuczera
Summary: Sub-seasonal streamflow forecasts are crucial for water resource management, especially in predicting high and low flows. The study reveals that stratifying forecasts into high/low flow ranges can highlight significant under/over-estimations of forecast uncertainty. By introducing a flow-dependent component, the MuTHRE-FD model significantly improves the reliability of sub-seasonal forecasts for both high and low flows.
WATER RESOURCES RESEARCH
(2021)
Article
Engineering, Civil
Sangchul Lee, Junyu Qi, Gregory W. McCarty, In-Young Yeo, Xuesong Zhang, Glenn E. Moglen, Ling Du
Summary: This study assessed the impacts of uncertainties from hydrologic model parameters and climate change data on streamflow and NFW water storage predictions for the Coastal Plain of the Chesapeake Bay watershed. The variability of GCM projections was identified as the most significant contributor to the total uncertainties, emphasizing the importance of considering model and climate change uncertainties for reliable projections of NFW hydrologic behaviors.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Environmental
Chen Cao, Baowei Yan, Jing Guo, Huining Jiang, Zhengkun Li, Yu Liu
Summary: The study demonstrated that the SWAT hydrological model is suitable for the Yalong River basin, and the BMA method can capture historical streamflow more accurately than individual GCM projections, providing a scientific reference for future water resources planning and utilization in the region.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Environmental Sciences
Pedram Darbandsari, Paulin Coulibaly
Summary: This study evaluates the impact of different hydrologic models on the performance of the hydrologic uncertainty processor (HUP) and proposes a multimodel Bayesian postprocessor (HUP-BMA). Results demonstrate the superiority of HUP-BMA in quantifying hydrologic uncertainty and forecasting compared to traditional HUP and BMA methods.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
George Z. Ndhlovu, Yali E. Woyessa
Summary: The Zambezi River basin is vulnerable to climate change effects due to its highly variable climate. This study evaluates the impact of climate change on streamflow in the Kabombo basin using global climate models. Model predictions suggest an increase in streamflow under the RCP 8.5 scenario, indicating the need for adaptation and mitigation strategies, while a slight decrease in streamflow is predicted under the RCP 4.5 scenario, suggesting a potential need to review current water management strategies.
Article
Economics
Chunpei Shi, Yu Wei, Xiafei Li, Yuntong Liu
Summary: The objectives of this paper are to investigate the overall predictive power of multiple uncertainties on China's crude oil futures returns, and to explore the predictive power of connectedness indices between crude oil and uncertainties on oil returns. The empirical results show that the combination forecasts and connectedness indices generally outperform the benchmark, providing new stable predictors for forecasting oil returns.
Article
Water Resources
Zain Syed, Prince Mahmood, Sajjad Haider, Shakil Ahmad
Summary: Streamflow forecasting is crucial for water resources management. The complex terrain and uncertain climate data in the Chitral basin pose challenges for streamflow simulation. This study explored three frameworks and assigned scores based on model evaluation and performance. ANN-RGC achieved the highest score. A bias scaling approach was proposed to reduce simulation biases.
JOURNAL OF WATER AND CLIMATE CHANGE
(2023)
Article
Meteorology & Atmospheric Sciences
Xuan Wang, Zhe-Min Tan
Summary: The selection of physical parameterization schemes for tropical cyclone forecasts is a challenging task. This study introduces an uncertainty-informed framework for evaluating and selecting the combination of parameterization schemes based on ensemble forecasts. The performance of scheme combinations is ranked differently based on ensemble mean error compared to deterministic forecast error. Evaluating the forecast distribution as a whole is important to assess forecast performance, and the ensemble Continuous Ranked Probability Score (eCRPS) is used for this purpose. The performance of scheme combinations in the context of model uncertainty is found to be more comprehensive than in the deterministic context.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
Article
Agronomy
Huidong Jin, Ming Li, Garry Hopwood, Zvi Hochman, K. Shuvo Bakar
Summary: Seasonal climate forecasts have great potential for weather-sensitive sectors like agriculture. This study uses statistical downscaling and crop models to improve yield forecasts. The results show that seasonal climate forecasts can significantly enhance yield forecast skills, especially for early-season predictions.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Dol Raj Chalise, Anantha Aiyyer, A. Sankarasubramanian
Summary: The study quantified the contribution of tropical cyclones to seasonal streamflow and precipitation in the US Southeast and Southcentral regions, finding that TCs account for 12% of streamflow and 6% of precipitation during the hurricane season. Florida, North Carolina, and Louisiana have the highest occurrences of TC-generated precipitation and streamflow. Additionally, TCs are associated with 5%-8% of peak-over threshold precipitation events in coastal areas.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Lili Yao, A. Sankarasubramanian, Dingbao Wang
Summary: This study evaluates the impacts of climate and landscape characteristics on long-term baseflow using various indices and functions. The results show that storage capacity has a significant impact on baseflow indices, with different sensitivities in arid and humid regions, while the shape parameter plays a role in different ways in different regions.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Amir Mazrooei, Meredith Reitz, Dingbao Wang, A. Sankarasubramanian
Summary: This study investigates the impacts of urbanization on evapotranspiration (ET) fluxes across different landscapes and timescales. The observed patterns show that the difference in ET between urban and non-urban areas is influenced by local hydroclimate, with arid regions experiencing increased ET and humid regions showing decreased ET. Cities in cold climates tend to evaporate more during winter due to increased energy availability from human activities. Urban areas in arid regions have increased ET due to water withdrawals and irrigation during drought conditions. These findings can help planners in integrating environmental conditions into urban landscape design and management.
Article
Thermodynamics
Hadi Eshraghi, Anderson Rodrigo de Queiroz, A. Sankarasubramanian, Joseph F. DeCarolis
Summary: By analyzing data from 48 U.S. states using a linear regression model from 2005 to 2017, it was found that the majority of states' summer and winter electricity demand variability is primarily driven by climate, indicating the need for new datasets to quantify unexplained variance in electricity demand.
Article
Environmental Sciences
Hemant Kumar, Jeongwoo Hwang, Naresh Devineni, A. Sankarasubramanian
Summary: Large dams heavily regulate natural river flows, degrading the river's health. While there has been extensive research on the impact of individual dams on flow regulation, few studies have investigated the combined impact of dam regulation on an entire river network. This study proposes a new index, the Dynamic Flow Alteration Index (DFAI), to measure the degree of regulation by comparing controlled flows with naturalized flows. The DFAI captures the localized regulation of upstream dams and reveals increasing cumulative impact downstream. It also considers the shifting of peak flow occurrence and dampening of peak flows caused by dam operations.
WATER RESOURCES RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
J. Michael Johnson, Tom Narock, Justin Singh-Mohudpur, Doug Fils, Keith C. Clarke, Siddharth Saksena, Adam Shepherd, Sankar Arumugam, Lilit Yeghiazarian
Summary: A digital map of the built environment has various applications, and the integration and interoperability of different open geospatial products are challenging. This article presents an approach for merging data from major open building datasets and demonstrates how machine learning models can be built on a structured knowledge graph to address unknown data in disaster management.
Article
Environmental Sciences
C. Awasthi, S. A. Archfield, K. R. Ryberg, J. E. Kiang, A. Sankarasubramanian
Summary: This study proposes a new climate-informed methodology for estimating flood-frequency curves under non-stationary future climate conditions. By developing an asynchronous, semiparametric local-likelihood regression model, the researchers relate flood moments to climate variables and estimate the first two marginal moments of the underlying distribution. The proposed methodology is applied to 40 streamgages in the US and evaluated using historical and projected climate data from Global Circulation Models, showing good agreement in humid basins but higher uncertainty in arid basins.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Albert Ruhi, Jeongwoo Hwang, Naresh Devineni, Sudarshana Mukhopadhyay, Hemant Kumar, Lise Comte, Scott Worland, A. Sankarasubramanian
Summary: Large dams are a leading cause of river ecosystem degradation. This study analyzed the regulated Colorado River Basin to understand how flow alteration propagates in river networks, and found that dam impacts were influenced more by network-level attributes than local dam properties. High-impact dams were often located in sub-watersheds with high levels of native fish biodiversity or species requiring seasonal flows.
Article
Energy & Fuels
Lucas Ford, Anderson de Queiroz, Joseph DeCarolis, A. Sankarasubramanian
Summary: This study develops a modeling framework called COREGS, which optimizes the allocation of water resources and reduces power generation costs through the co-optimization of reservoir and electricity generation systems. The findings suggest that co-optimization leads to more efficient water allocation decisions and better meets the needs of the power system compared to separate optimization.
Article
Environmental Sciences
K. Karimi, J. W. Miller, A. Sankarasubramanian, D. R. Obenour
Summary: Nutrient pollution is a global environmental problem that affects water quality worldwide. A hybrid watershed model was developed to assess the temporal drivers of phosphorus loading and transport, incorporating interannual variability in land use and precipitation. The model was calibrated within a Bayesian hierarchical framework, revealing that urban lands developed before 1980 are the largest contributor of phosphorus, especially under dry conditions. The study also found that summer phosphorus export rates are generally lower than annual rates, while in-stream retention is higher in summer.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Dol Raj Chalise, A. Sankarasubramanian, Julian D. D. Olden, Albert Ruhi
Summary: River scientists conducted a study to understand the effects of dam regulation on river flow regimes. By analyzing data from 175 pairs of regulated and unregulated USGS gages, they found that dams not only affect the magnitude and variability of flow, but also the dominant periodicities of a river's flow regime. The analysis also revealed that the alteration of flow periodicity varies over time, with dam operations, changes in dam capacity, and environmental policies shifting the relative importance of periodicities.
Article
Environmental Sciences
Hemant Kumar, Tingju Zhu, A. Sankarasubramanian
Summary: Understanding the interconnections between food, energy, and water systems is crucial for basins with intensive agricultural water use, especially in the face of changing climate and regional development. We utilized a regional hydroeconomic optimization (RHEO) modeling framework to investigate this nexus and developed a hierarchical regression model to estimate crop production using AquaCropOS, a biophysical model. The incorporation of the hierarchical model within RHEO enabled parallel programming and facilitated the analysis of mixed irrigation strategies. Applying this framework to a groundwater-dominated basin in Georgia, we found that optimal deficit irrigation is economically preferable and reduces water, carbon, and energy footprints, thereby increasing resilience in the food, energy, and water sectors.
WATER RESOURCES RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
C. Awasthi, S. A. Archfield, B. J. Reich, A. Sankarasubramanian
Summary: This study proposes an alternate framework to detect significant changes in design-flood between two periods and evaluates its effectiveness through synthetic experiments. The results show that the commonly used trend test method does not consider changes in all three moments of flood distribution, leading to incorrect detection of changes in design-flood. Significant changes in design-flood quantiles were observed in 31 river basins across the United States, even without a significant trend in flood events. Therefore, considering changes in all moments is recommended for evaluating design-flood changes instead of relying solely on simple trend tests.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Lucas Ford, A. Sankarasubramanian
Summary: The study develops a Piecewise Linear Regression Tree to learn generalized daily operating policies from multiple reservoirs, which improves the accuracy of streamflow estimates in land-surface models. The models can accurately predict release from different reservoirs and provide relationships between reservoir state and expected release, contributing to future model improvements.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Peng-Fei Han, Arumugam Sankarasubramanian, Xu-Sheng Wang, Li Wan, Lili Yao
Summary: The changes in climate and catchment properties have significantly altered the hydrological processes at different scales. This study derived new formulas for the unsteady-state streamflow elasticity in a modified Budyko framework, considering both storage change and catchment properties. The study found that the estimated elasticity coefficients performed well in simulating annual streamflow, and the variability of unsteady-state elasticity was higher than that of steady-state elasticity.
WATER RESOURCES RESEARCH
(2023)