Modelling of climate change impact on flow conditions in the lowland anastomosing river

Abstract

The progressive degradation of freshwater ecosystems worldwide requires action to be taken for their conservation. Nowadays, protection strategies need to step beyond the traditional approach of managing protected areas as they have to deal with the protection or recovery of natural flow regimes disrupted by the effects of future climate conditions. Climate change affects the hydrosphere at catchment scale altering hydrological processes which in turn impact hydrodynamics at the river reach scale. Therefore, conservation strategies should consider mathematical models, which allow for an improved understanding of ecosystem functions and their interactions across different spatial and temporal scales. This study focuses on an anastomosing river system in north-eastern Poland, where in recent decades a significant loss of the anabranches has been observed. The objective was to assess the impact of projected climate change on average flow conditions in the anastomosing section of the Narew River. The Soil and Water Assessment Tool (SWAT software) for the Narew catchment was coupled with the HEC-RAS one-dimensional unsteady flow model. The study looked into projected changes for two future time horizons 2021–2050 and 2071–2100 under the Representative Concentration Pathway 4.5 using an ensemble of nine EURO-CORDEX model scenarios. Results show that low flow conditions in the anastomosing section of the Narew National Park will remain relatively stable in 2021–2050 compared to current conditions and will slightly increase in 2071–2100. Duration of low flows, although projected to decrease on an annual basis, will increase for August–October, when the loss on anastomoses was found to be the most intense. Hydraulic modeling indicated extremely low flow velocities in the anastomosing arm (<0.1 m/s) nowadays and under future projections which is preferable for in-stream vegetation development and their gradual sedimentation and closure.

Development of an integrated modelling framework to evaluate impacts of pressures on habitat conditions and riverine biota

“…Table 1 shows the calculated errors and model performance indices for Gauges J1 and J2 (Figure 3), while the comparison of simulated and observed water levels is shown in Figure 6. The results can be considered very good both in terms of low values of errors and a good visual agreement (Marcinkowski & Mirosław‐Świątek, 2020; Papadaki et al, 2017). The highest values of errors (an underestimation by ~0.05 m) occurred in November 2021 at Gauge J1.…”

Trajectoire d’évolution d’un cours d’eau à faible énergie au cours du second Holocène : la Charente entre Angoulême et Saintes

“…chapitre 5) afin d'identifier son impact dans la dynamique de la mosaïque fluviale, le rôle des étiages a quant à lui été très peu abordé dans le cas de ce travail. Pourtant, Marcinkowski et al (2020) ont effectivement démontré l'extrême vulnérabilité de l'anastomose de la rivière Narew face au changement climatique en liaison avec la modification du régime des étiages. L'allongement des périodes d'étiages (août à octobre) est susceptible de favoriser la déconnexion des chenaux secondaires et leur évolution en bras morts suite à leur colmatage progressif ce qui pourrait accélérer la simplification de l'anastomose de la rivière Narew et à terme favoriser son extinction.…”

Methodology for the assessment of poor-data water resources

“…However, there are precedents of successful modeling with shorter periods ranging from 6 to 15 years ( Marcinkowski & Mirosław-Świątek, 2020 ; Wielgat et al, 2021 ; Goshime et al, 2021 ; Mehla, 2022 ). Moreover, literature suggests modeling periods varying from 15 to 20 years ( Khoshkhoo et al, 2015 ; Rasoulzadeh Gharibdousti, Kharel & Stoecker, 2019 ; Dehghanipour et al, 2019 ; Lerat et al, 2020 ; Bazzi, Ebrahimi & Aminnejad, 2021 ; Nazeer et al, 2022 ), highlighting the preference for extended modeling periods ( Schuol et al, 2008 ; Li et al, 2015 ; Adla, Tripathi & Disse, 2019 ; García-Romero et al, 2019 ; Lakshmi & Sudheer, 2021 ) that include validation and warm-up spans as well as modeling for complete or discontinuous periods ( Zhang et al, 2011 ).…”