Climate change impacts on streamflow and subbasin-scale hydrology in the Upper Colorado River Basin

Integrating machine learning for enhanced wildfire severity prediction: A study in the Upper Colorado River basin

Wildfires pose significant threats worldwide, requiring accurate prediction for mitigation. This study uses machine learning techniques to forecast wildfire severity in the Upper Colorado River basin. Datasets from 1984 to 2019 and key indicators like weather conditions and land use were employed. Random Forest outperformed Artificial Neural Network, achieving 72 % accuracy. Influential predictors include air temperature, vapor pressure deficit, NDVI, and fuel moisture. Solar radiation, SPEI, precipitation, and evapotranspiration also contribute significantly. Validation against actual severities from 2016 to 2019 showed mean prediction errors of 11.2 %, affirming the model's reliability. These results highlight the efficacy of machine learning in understanding wildfire severity, especially in vulnerable regions.

Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach

The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20:367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

High Dissolved Carbon Concentration in Arid Rocky Mountain Streams

Warming in mountains is known to intensify aridity and threaten water availability globally. Its impacts on water quality, however, have remained poorly understood. Here we collate long-term (multi-year to decadal mean), baseline stream concentrations and fluxes of dissolved organic and inorganic carbon, two essential indicators of water quality and soil carbon response to warming, across more than 100 streams in the United States Rocky Mountains. Results show a universal pattern of higher mean concentrations in more arid mountain streams with lower mean discharge, a long-term climate measure. A watershed reactor model revealed less lateral export of dissolved carbon (via less water flow) out of the watersheds in more arid sites, leading to more accumulation and higher concentrations. Lower concentrations typically occur in cold, steep, and compact mountains with higher snow fraction and lower vegetation cover, which generally have higher discharge and carbon fluxes. Inferring from a space-for-time perspective, the results indicate that as warming intensifies, lateral fluxes of dissolved carbon will decrease but concentrations will increase in these mountain streams. This indicates deteriorating water quality and potentially elevated CO₂ emission directly from the land (instead of streams) in the Rockies and other mountain areas in the future climate.

Investigation of Wabe River water fitness for agricultural and industrial purposes

The Wabe River is bordered by 74.84% agricultural area, and farmers rely solely on rainfall. The present research made an attempt to investigate the suitability of the Wabe river water for Agricultural and Industrial purpose. The suitability of river water for agricultural use was evaluated using the sodium adsorption ratio (SAR), potential salinity (PS), magnesium ratio (MR), Kelly index (KI), permeability index (PI), residual sodium carbonate (RSC), sodium percentage (%Na), and heavy metal pollution index (HPI). Additionally, the Ryznar Stability Index (RSI), Aggressive Index (AI), and Langelier Saturation Index (LSI) were used to evaluate the river water's suitability for industrial uses. Furthermore, plot the Gibb's diagrams to identify the sources of pollution and Piper diagrams to determine the hydrochemical composition of Wabe water. According to the HPI, pollution levels in the wet and dry seasons ranged from 53.34 (low) to 317.58 (medium) and 32.24 to 102.42 (low), respectively. The results showed that the Wabe River has very acceptable water quality characteristics and that the trace elements identified did not surpass thresholds that made them dangerous for agricultural usage. The findings showed that domestic wastewater and leachate contamination at sampling point W4 is the cause of the water quality deterioration in the downstream zone. The Ryznar Stability Index (RSI), Aggressive index, and Langelier saturation index readings were less than 9 at all sampling locations during both seasons, suggesting that the river water was corrosive, highly aggressive and unusable for industrial use without treatment.

A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019

This article presents a hydrological reconstruction of the Upper Colorado River Basin with an hourly temporal resolution, and 1-km spatial resolution from October 1982 to September 2019. The validated dataset includes a suite of hydrologic variables including streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) simulated by an integrated hydrological model, ParFlow-CLM. The dataset was validated over the period with a combination of point observations and remotely sensed products. These datasets provide a long-term, natural-flow, simulation for one of the most over-allocated basins in the world.

Assessment of Streamflow from EURO-CORDEX Regional Climate Simulations in Semi-Arid Catchments Using the SWAT Model

This research studies the effect of climate change on the hydrological behavior of two semi-arid basins. For this purpose, the Soil and Water Assessment Tool (SWAT) model was used with the simulation of two future climate change scenarios, one Representative Concentration Pathway moderate (RCP 4.5) and the other extreme (RCP 8.5). Three future periods were considered: close (2019–2040), medium (2041–2070), and distant (2071–2100). In addition, several climatic projections of the EURO-CORDEX model were selected, to which different bias correction methods were applied before incorporation into the SWAT model. The statistical indices for the monthly flow simulations showed a very good fit in the calibration and validation phases in the Upper Mula stream (NS = 0.79–0.87; PBIAS = −4.00–0.70%; RSR = 0.44–0.46) and the ephemeral Algeciras stream (NS = 0.78–0.82; PBIAS = −8.10–−8.20%; RSR = 0.4–0.42). Subsequently, the impact of climate change in both basins was evaluated by comparing future flows with those of the historical period. In the RCP 4.5 and RCP 8.5 scenarios, by the end of the 2071–2100 period, the flows of the Upper Mula stream and the ephemeral Algeciras stream will have decreased by between 46.3% and 52.4% and between 46.6% and 55.8%, respectively.

Assessment of Surface Water Availability under Climate Change Using Coupled SWAT-WEAP in Hongshui River Basin, China

Climate change adversely affects the hydrological cycle at the basin level. This study integrated two models, the Soil and Water Assessment Tool (SWAT) for future climate prediction, and Water Evaluation and Planning (WEAP) for the simulation of water quantity in the Hongshui River Basin (HRB), to evaluate the impacts of climate change, which plays a significant role in the lives of inhabitants downstream of the basin. Downscaled monthly rainfalls and temperatures under four Representative Concentration Pathways (RCPs) emission scenarios from five global circulation models (GCMs) were used to generate streamflow using the SWAT model. Streamflow data (1991–2001) were used to calibrate and validate, with the period of 1991–1997 used for calibration and that of 1998–2001 used for validation. Six scenarios were established to evaluate the response of the basin under socio-economic scenarios. The simulated results show that precipitation and streamflow would likely undergo a slight increase. The available water resources would be sufficient to meet the existing needs until 2050. The results indicated that no water shortages exist under socio-economic, low, and medium climate change emission scenarios, however the basin will experience a water shortage under the high climate change emission scenario (RCP-8.5). The study proposed that, to ensure the sustainability of water resources, better long-term management policies are required to be implemented in the basin and to meet future downstream water needs.

Analyzing the Suitability of Remotely Sensed ET for Calibrating a Watershed Model of a Mediterranean Montane Forest

The ability to spatially characterize runoff generation and forest health depends partly on the accuracy and resolution of evapotranspiration (ET) simulated by numerical models. A possible strategy to increase the accuracy and resolution of numerically modeled ET is the use of remotely sensed ET products as an observational basis for parameter estimation (model calibration) of those numerical models. However, the extent to which that calibration strategy leads to a realistic representation of ET, relative to ground conditions, is not well understood. We examined this by comparing the spatiotemporal accuracy of ET from a remote sensing product, MODIS MOD16A2, to that from a watershed model (SWAT) calibrated to flow measured at an outlet streamgage. We examined this in the upper Kings River watershed (3999 km2) of California’s Sierra Nevada, a snow-influenced watershed in a Mediterranean climate. We assessed ET accuracies against observations from three eddy-covariance flux towers at elevations of 1160–2700 m. The accuracy of ET from the stream-calibrated watershed model surpassed that of MODIS in terms of Nash-Sutcliffe efficiency (+0.36 versus −0.43) and error in elevational trend (+7.7% versus +81%). These results indicate that for this particular experiment, an outlet streamgage would provide a more effective observational basis than remotely sensed ET product for watershed-model parameter estimation. Based on analysis of ET-weather relationships, the relatively large errors we found in MODIS ET may be related to weather-based corrections to water limitation not representative of the hydrology of this snow-influenced, Mediterranean-climate area.

Identifying climate change impacts on surface water supply in the southern Central Valley, California

Mountain regions in arid and semi-arid climates, such as California, are considered particularly sensitive to climate change because global warming is expected to alter snowpack storage and related surface water supply. It is therefore important to accurately capture snowmelt processes in watershed models for climate change impact assessment. In this study we use the Soil and Water Assessment Tool (SWAT) to estimate projected changes in snowpack and streamflow in four alpine tributaries to the agriculturally important but less studied southern Central Valley, California. Watershed responses are evaluated for four CMIP5 climate models (HadGEM_ES, CNRM-CM5, CanESM2 and MIROC5) and two emission scenarios (RCP 4.5 and RCP 8.5) for 2020-2099. SWAT models are calibrated following a dual-objective, lumped calibration approach with an automatic calibration against observed streamflow (stage 1) and a manual calibration against reconstructed Parallel Energy Balance (ParBal) snow water equivalent (SWE) data (stage 2). Results indicate that under a warming climate, peak streamflow is expected to increase 0.5-4 times in magnitude in the coming decades and to arrive 2-4 months earlier in the year because of earlier snowmelt. In the foreseeable future, snow cover will reduce gradually in the lower elevations and diminish at higher rates at higher elevation towards the end of the 21st century. Surface water supply is predicted to increase in the southern Central Valley under the evaluated scenarios but increased temporal variability (wetter wet seasons and drier dry seasons) will create new challenges for managing supply. The study further highlights that the use of remote sensing based, reconstructed SWE data could fill the current gap of limited in-situ SWE observations to improve the snow calibration of SWAT to better predict climate change impacts in semi-arid, snow-dominated watersheds.

Multiscaling NDVI Series Analysis of Rainfed Cereal in Central Spain

Vegetation indices time series analysis is increasingly improved for characterizing agricultural land processes. However, this is challenging because of the multeity of factors affecting vegetation growth. In semiarid regions the rainfall, the soil properties and climate are strongly correlated with crop growth. These relationships are commonly analyzed using the normalized difference vegetation index (NDVI). NDVI series from two sites, belonging to different agroclimatic zones, were examined, decomposing them into the overall average pattern, residuals, and anomalies series. All of them were studied by applying the concept of the generalized Hurst exponent. This is derived from the generalized structure function, which characterizes the series’ scaling properties. The cycle pattern of NDVI series from both zones presented differences that could be explained by the differences in the climatic precipitation pattern and soil characteristics. The significant differences found in the soil reflectance bands confirm the differences in both sites. The scaling properties of NDVI original series were confirmed with Hurst exponents higher than 0.5 showing a persistent structure. The opposite was found when analyzing the residual and the anomaly series with a stronger anti-persistent character. These findings reveal the influences of soil–climate interactions in the dynamic of NDVI series of rainfed cereals in the semiarid.

Using Integrated Hydrological Models to Assess the Impacts of Climate Change on Discharges and Extreme Flood Events in the Upper Yangtze River Basin

Amongst the impacts of climate change, those arising from extreme hydrological events are expected to cause the greatest impacts. To assess the changes in temperature and precipitation and their impacts on the discharge in the upper Yangtze Basin from pre-industrial to the end of 21st century, four hydrological models were integrated with four global climate models. Results indicated that mean discharge was simulated to increase slightly for all hydrological models forced by all global climate models during 1771–1800 and 1871–1900 relative to the 1971–2000 reference period, whereas the change directions in mean discharge were not consistent among the four global climate models during 2070–2099, with increases from HadGEM2-ES and MIROC5, and decreases from GFDL-ESM2M and IPSL-CM5A-LR. Additionally, our results indicated that decreases in precipitation may always result in the decrease in mean discharge, but increases in precipitation did not always lead to increases in discharge due to high temperature rise. The changes in extreme flood events with different return intervals were also explored. These extreme events were projected to become more intense and frequent in the future, which could have potential devastating impacts on the society and ecosystem in this region.

Future Changes in Water Supply and Demand for Las Vegas Valley: A System Dynamic Approach based on CMIP3 and CMIP5 Climate Projections

The study investigated the impact on water supply and demand as an effect of climate change and population growth in the Las Vegas Valley (LVV) as a part of the Thriving Earth Exchange Program. The analyses evaluated future supply and demand scenarios utilizing a system dynamics model based on the climate and hydrological projections from the Coupled Model Intercomparison Project phases 3 and 5 (CMIP3 and CMIP5, respectively) using the simulation period expanding from 1989 to 2049. The main source of water supply in LVV is the water storage in Lake Mead, which is directly related to Lake Mead elevation. In order to assess the future water demand, the elevation of Lake Mead was evaluated under several water availability scenarios. Fifty-nine out of the 97 (27 out of the 48) projections from CMIP5 (CMIP3) indicated that the future mean elevation of Lake Mead is likely to be lower than the historical mean. Demand forecasts showed that the Southern Nevada Water Authority’s conservation goal for 2035 can be significantly met under prevalent conservation practices. Findings from this study can be useful for water managers and resource planners to predict future water budget and to make effective decisions in advance to attain sustainable practices and conservation goals.

A REVIEW OF WATER QUALITY RESPONSES TO AIR TEMPERATURE AND PRECIPITATION CHANGES 1: FLOW, WATER TEMPERATURE, SALTWATER INTRUSION

Anticipated future increases in air temperature and regionally variable changes in precipitation will have direct and cascading effects on U.S. water quality. In this paper, and a companion paper by Coffey et al. (2019), we review technical literature addressing the responses of different water quality attributes to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk to inform management responses and to identify research needs to fill gaps in our understanding. Here we focus on potential changes in streamflow, water temperature, and salt water intrusion (SWI). Projected changes in the volume and timing of streamflow vary regionally, with general increases in northern and eastern regions of the U.S., and decreases in the southern Plains, interior Southwest and parts of the Southeast. Water temperatures have increased throughout the U.S. and are expected to continue to increase in the future, with the greatest changes in locations where high summer air temperatures occur together with low streamflow volumes. In coastal areas, especially the mid-Atlantic and Gulf coasts, SWI to rivers and aquifers could be exacerbated by sea level rise, storm surges, and altered freshwater runoff. Management responses for reducing risks to water quality should consider strategies and practices robust to a range of potential future conditions.

A REVIEW OF WATER QUALITY RESPONSES TO AIR TEMPERATURE AND PRECIPITATION CHANGES 2: NUTRIENTS, ALGAL BLOOMS, SEDIMENT, PATHOGENS

In this paper we review the published, scientific literature addressing the response of nutrients, sediment, pathogens and cyanobacterial blooms to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk, to inform management responses and to identify research needs to fill gaps in our understanding. Results suggest that anticipated future changes present a risk of water quality and ecosystem degradation in many U.S. locations. Understanding responses is, however, complicated by inherent high spatial and temporal variability, interactions with land use and water management, and dependence on uncertain changes in hydrology in response to future climate. Effects on pollutant loading in different watershed settings generally correlate with projected changes in precipitation and runoff. In all regions, increased heavy precipitation events are likely to drive more episodic pollutant loading to water bodies. The risk of algal blooms could increase due to an expanded seasonal window of warm water temperatures and the potential for episodic increases in nutrient loading. Increased air and water temperatures are also likely to affect the survival of waterborne pathogens. Responding to these challenges requires understanding of vulnerabilities, and management strategies to reduce risk.

A SWAT Evaluation of the Effects of Climate Change on Renewable Water Resources in Salt Lake Sub-Basin, Iran

Future climate change is projected to have significant impacts on water resources availability in many parts of the world. This research evaluated climate change impacts on runoff, aquifer infiltration, renewable water resources, and drought intensity in Salt Lake sub-basin, Iran, by the Soil and Water assessment tool (SWAT) model and the Standardized Precipitation Index (SPI) under A1B, A2, and B1 climatic scenarios for 2011–2030, 2046–2065, and 2080–2099, using 1986–2016 as the reference period. The model was calibrated and validated by the SWAT-CUP software and SUFI-2 algorithm. Nash–Sutcliffe (NS) coefficients (0.58 and 0.49) and the determination coefficients (R2) (0.65 and 0.50) were obtained for the calibration and validation periods, respectively. In order to study the climatic condition in the study basin, drought intensity was calculated. Then, drought intensity was predicted using the SPI index for the period 2011–2030. The results showed that runoff, infiltration, as well as renewable water resources will decrease under all climatic scenarios. Renewable water resources will be approximately reduced 100 Mm3 by the year 2100. The future projections suggest a regional increase of 2 °C in temperature and a 20% decrease in precipitation in the sub-basin. In particular, drought intensity will be increased in the future. In 2015, this index was −1.31, and in 2016, the SPI index was lower than −2. These projection scenarios should be of interest to water resources managers in tropical regions.

Hydrological Modeling of Climate Change Impacts in a Tropical River Basin: A Case Study of the Cauto River, Cuba

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions.

A pollution fate and transport model application in a semi-arid region: Is some number better than no number?

Fate and transport models are powerful tools that aid authorities in making unbiased decisions for developing sustainable management strategies. Application of pollution fate and transport models in semi-arid regions has been challenging because of unique hydrological characteristics and limited data availability. Significant temporal and spatial variability in rainfall events, complex interactions between soil, vegetation and topography, and limited water quality and hydrological data due to insufficient monitoring network make it a difficult task to develop reliable models in semi-arid regions. The performances of these models govern the final use of the outcomes such as policy implementation, screening, economical analysis, etc. In this study, a deterministic distributed fate and transport model, SWAT, is applied in Lake Mogan Watershed, a semi-arid region dominated by dry agricultural practices, to estimate nutrient loads and to develop the water budget of the watershed. To minimize the discrepancy due to limited availability of historical water quality data extensive efforts were placed in collecting site-specific data for model inputs such as soil properties, agricultural practice information and land use. Moreover, calibration parameter ranges suggested in the literature are utilized during calibration in order to obtain more realistic representation of Lake Mogan Watershed in the model. Model performance is evaluated using comparisons of the measured data with 95%CI for the simulated data and comparison of unit pollution load estimations with those provided in the literature for similar catchments, in addition to commonly used evaluation criteria such as Nash-Sutcliffe simulation efficiency, coefficient of determination and percent bias. These evaluations demonstrated that even though the model prediction power is not high according to the commonly used model performance criteria, the calibrated model may provide useful information in the comparison of the effects of different management practices on diffuse pollution and water quality in Lake Mogan Watershed.

Groundwater-surface water interactions in the hyporheic zone under climate change scenarios

Slight changes in climate, such as the rise of temperature or alterations of precipitation and evaporation, will dramatically influence nearly all freshwater and climate-related hydrological behavior on a global scale. The hyporheic zone (HZ), where groundwater (GW) and surface waters (SW) interact, is characterized by permeable sediments, low flow velocities, and gradients of physical, chemical, and biological characteristics along the exchange flows. Hyporheic metabolism, that is biogeochemical reactions within the HZ as well as various processes that exchange substances and energy with adjoining systems, is correlated with hyporheic organisms, habitats, and the organic matter (OM) supplied from GW and SW, which will inevitably be influenced by climate-related variations. The characteristics of the HZ in acting as a transition zone and in filtering and purifying exchanged water will be lost, resulting in a weakening of the self-purification capacity of natural water bodies. Thus, as human disturbances intensify in the future, GW and SW pollution will become a greater challenge for mankind than ever before. Biogeochemical processes in the HZ may favor the release of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) under climate change scenarios. Future water resource management should consider the integrity of aquatic systems as a whole, including the HZ, rather than independently focusing on SW and GW.

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.