Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Parajuli, Prem B.; Risal, Avay

doi:10.3390/cli9110165

Cited by 14 publications

(7 citation statements)

References 33 publications

(37 reference statements)

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“…However, similar studies reported comparable increases in the catchment scale (TN up to 34%, TP up to 50% (Čerkasova et al, 2019). Local predictions are also high, but this has also appeared in the literature (Li et al, 2018;Parajuli & Risal, 2021;Schürz et al, 2019).…”

Section: Water Resources Researchsupporting

confidence: 54%

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios

Bojanowski,

Orlińska‐Woźniak,

Wilk

et al. 2024

Water Resources Research

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Currently, climate change is considered as an important factor affecting nutrient loads introduced through riverine systems into the Baltic Sea. Although the prospect of a large increase in pollution has long seemed very real, it still does not translate into planning of effective remedial actions. One of the factors limiting the development of such activities is the scale of simulations, focusing generally on catchment outlet profiles. To fill this gap and enable a step forward in understanding responses toward future predictions in a higher resolution scale (subcatchment), we assessed nutrient load contribution using calculation profiles localized along a main watercourse and its tributaries. To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. Having at our disposal a catchment model with a good performance we could follow not only total load changes in particular subcatchments, but also track localization of the pollution sources and their direct impact on load estimations. Our results showed an increase of the loads, especially from the agricultural land use type, up to 34% for TN and 85% for TP, in the most extreme scenario. Moreover, forest areas have been noted as highly reactive to climate change, and through their localisation are able to distinctly alter nutrient outflow. Finally, the contribution of urban areas should be further investigated since the dynamics of nitrogen and phosphorus release from impervious surfaces is noticeably different here than from the other diffuse sources.

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Section: Water Resources Researchsupporting

confidence: 54%

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios

Bojanowski,

Orlińska‐Woźniak,

Wilk

et al. 2024

Water Resources Research

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“…In addition to the anthropogenic causes, natural variables such as climate change have also had an impact on the streamflow variability [13][14][15][16]. Climate change has far-reaching ramifications in a way that it modifies precipitation timing, magnitude, and distribution, as well as evapotranspiration rates and general hydrological patterns.…”

Section: Introductionmentioning

confidence: 99%

Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment

Geetha Raveendran Nair,

Shamsudeen,

Mohan

et al. 2023

Sustainability

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Accurate prediction of future streamflow in flood-prone regions is crucial for effective flood management and disaster mitigation. This study presents an innovative approach for streamflow projections in deep learning (DL) environment by integrating the quantitative Land-Use Land-Cover (LULC) overlaid with flow accumulation values and the various Global Climate Model (GCM) simulated data. Firstly, the Long Short Term Memory (LSTM) model was developed for the streamflow prediction of Greater Pamba River Basin (GPRB) in Kerala, India for 1985 to 2015 period, considering the climatic inputs. Then, the flow accumulation-weighted LULC integration was considered in modelling, which substantially improves the accuracy of streamflow predictions including the extremes of all the three stations, as the model accounts for the geographical variety of land cover types towards the streamflow at the sub-basin outlets. Subsequently, Reliability Ensemble Averaging (REA) technique was used to create an ensemble of three candidate GCM products to illustrate the spectrum of uncertainty associated with climate projections. Future LULC changes are accounted in regional scale based on the sub-basin approach by means of Cellular-Automata Markov Model and used for integrating with the climatic indices. The basin-scale streamflow projection is done under three climate scenarios of SSP126, SSP245 and SSP585 respectively for lowest, moderate and highest emission conditions. This work is a novel approach of integrating quantified LULC with flow accumulation and other climatic inputs in a DL environment against the conventional techniques of hydrological modelling. The DL model can adapt and account for shifting hydrological responses induced by changes in climatic and LULC inputs. The integration of flow accumulation with changes in LULC was successful in capturing the flow dynamics in long-term. It also identifies regions that are more likely to experience increased flooding in the near future under changing climate scenarios and supports decision-making for sustainable water management of the Greater Pamba Basin which was the worst affected region in Kerala during the mega floods of 2018.

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“…Climate change is a matter of concern for hydrologists, climatologists, environmentalists, and agronomists as it is anticiapted to have and increasingly serious impact on water resources, infrastructure, agriculture, biodiversity and ecosystem functioning, and human health [5][6][7][8][9]. Although climate change is experienced globall, the degree of its impact varies considerably from region to region [10,11].…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Change on Water Resources and Crop Production in Western Nepal: Implications and Adaptation Strategies

Risal

Urfels²,

Srinivasan

et al. 2022

Hydrology

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Irrigation-led farming system intensification and efficient use of ground and surface water resources are currently being championed as a crucial ingredient for achieving food security and reducing poverty in Nepal. The potential scope and sustainability of irrigation interventions under current and future climates however remains poorly understood. Potential adaptation options in Western Nepal were analyzed using bias-corrected Regional Climate Model (RCM) data and the Soil and Water Assessment Tool (SWAT) model. The RCM climate change scenario suggested that average annual rainfall will increase by about 4% with occurrence of increased number and intensity of rainfall events in the winter. RCM outputs also suggested that average annual maximum temperature could decrease by 1.4 °C, and average annual minimum temperature may increase by 0.3 °C from 2021 to 2050. Similarly, average monthly streamflow volume could increase by about 65% from March–April, although it could decrease by about 10% in June. Our results highlight the tight hydrological coupling of surface and groundwater. Farmers making use of surface water for irrigation in upstream subbasins may inadvertently cause a decrease in average water availability in downstream subbasins at approximately 14%, which may result in increased need to abstract groundwater to compensate for deficits. Well-designed irrigated crop rotations that fully utilize both surface and groundwater conversely may increase groundwater levels by an average of 45 mm from 2022 to 2050, suggesting that in particular subbasins the cultivation of two crops a year may not cause long-term groundwater depletion. Modeled crop yield for the winter and spring seasons were however lower under future climate change scenarios, even with sufficient irrigation application. Lower yields were associated with shortened growing periods and high temperature stress. Irrigation intensification appears to be feasible if both surface and groundwater resources are appropriately targeted and rationally used. Conjunctive irrigation planning is required for equitable and year-round irrigation supply as neither the streamflow nor groundwater can provide full and year-round irrigation for intensified cropping systems without causing the degradation of natural resources.

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Evaluation of Climate Change on Streamflow, Sediment, and Nutrient Load at Watershed Scale

Cited by 14 publications

References 33 publications

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios

Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios

Basin-Scale Streamflow Projections for Greater Pamba River Basin, India Integrating GCM Ensemble Modelling and Flow Accumulation-Weighted LULC Overlay in Deep Learning Environment

Impact of Climate Change on Water Resources and Crop Production in Western Nepal: Implications and Adaptation Strategies

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