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Sci Rep
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Scientific Reports
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Nature Publishing Group UK London

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72699
10.1038/s41598-024-72699-z
Article
Sediment load assessments under climate change scenarios and a lack of integration between climatologists and environmental modelers
http://orcid.org/0000-0002-5483-193X
Szalińska Ewa eszalinska@agh.edu.pl

1
Orlińska-Woźniak Paulina 2
Wilk Paweł 2
Jakusik Ewa 2
Skalák Petr 3
Wypych Agnieszka 4
Arnold Jeff 5
1 grid.9922.0 0000 0000 9174 1488 AGH University of Krakow, A. Mickiewicza Av. 30, 30-059 Kraków, Poland
2 grid.425033.3 0000 0001 2160 9614 Institute of Meteorology and Water, Management - National Research Institute, Podleśna 61, 01-673 Warsaw, Poland
3 https://ror.org/01v5hek98 grid.426587.a Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, 603 00 Brno, Czech Republic
4 https://ror.org/03bqmcz70 grid.5522.0 0000 0001 2337 4740 Department of Climatology, Jagiellonian University in Krakow, Gronostajowa 7, 30-387 Kraków, Poland
5 grid.512846.c 0000 0004 0616 2502 United States Department of Agriculture, Agricultural Research Service, Temple, TX 76502 USA
17 9 2024
17 9 2024
2024
14 2172730 1 2024
10 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Increasing precipitation accelerates soil erosion and boosts sediment loads, especially in mountain catchments. Therefore, there is significant pressure to deliver plausible assessments of these phenomena on a local scale under future climate change scenarios. Such assessments are primarily drawn from a combination of climate change projections and environmental model simulations, usually performed by climatologists and environmental modelers independently. Our example shows that without communication from both groups the final results are ambiguous. Here, we estimate sediment loads delivered from a Carpathian catchment to a reservoir to illustrate how the choice of meteorological data, reference period, and model ensemble can affect final results. Differences in future loads could reach up to even 6000 tons of sediment per year. We suggest there must be a better integration between climatologists and environmental modelers, focusing on introducing multi-model ensembles targeting specific impacts to facilitate an informed choice on climate information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-72699-z.

Keywords

Climate change scenarios
Sediment loads
Climate and environmental modeling
Subject terms

Climate sciences
Environmental sciences
http://dx.doi.org/10.13039/501100007751 Akademia Górniczo-Hutnicza im. Stanislawa Staszica IDUB No. 501.696.7996/L-34 Szalińska Ewa issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Climate change impacts soil erosion and sediment loads due to increasing precipitation in many catchments around the world1. Since accelerated erosion and sedimentation have severe impacts on the environment and society, there is growing pressure to deliver plausible assessments of these changes in a catchment scale under future climate change scenarios. Many areas are already struggling with an increase in soil loss due to intensification of rainfall2–8, reduction of impounding reservoirs’ capacity9–13, harbour operations and infrastructure performance14–18, and many other pressing problems. Moreover, the forecasted changes in precipitation suggest that the intensity of these phenomena may increase significantly5,19–23; therefore, implementation of appropriate management and mitigation strategies is urgently needed.

In recent years, numerous studies have been conducted to assess future changes in many catchment parameters responsible for water resources, stream flow, land use changes and, finally, erosion and related sediment loads24–26. Majority of them were based on combining climate change projections and environmental model simulations. To obtain the best information about future climate changes, a number of climate models of different parametrization needs to be used. Projections of future climate evolution on global or continental scales are nowadays delivered by large ensembles of Global Climate Models (GCMs). For insight on the climate change impacts on the local or regional scale various downscaling techniques need to be applied to the GCM data. Running a Regional Climate Model (RCM) on a limited area is a well-established and recommended approach. Naturally, adding to the picture a growing number of GCMs and RCM outputs, we end up with a multiplicity of possibilities with a wide range of predicted values. Moreover, despite the ongoing improvements in atmospheric processes representation, both GCM and RCM data are still burdened with unpreventable modeling and postprocessing errors27. To reduce the uncertainty of the climate modeling approach, the use of multi-model ensembles built from the largest possible number of projections is strongly recommended1. To improve a process of model ensemble selection some interactive tools are being created28 however, due to the widespread constraints of common nature, i.e. time, money, and computational power, these ensembles are often significantly reduced, which creates distorted future climate conditions, especially when not insightfully proceeded29,30. On the other hand, the actual assessment of climate change impact on catchment processes is performed by environmental modelers, who when confronted with the complexity of the original climate change data sources, usually turn for projections to the different climate change sources. Such projections frequently result from the ongoing different custom projects31 and are taken subsequently as a ready-to-use product to create variant scenarios in catchment models.

Here we present a set of sediment load assessments for a catchment in the Carpathian Mountains representing the specificity of Central European climate, where the variability of weather and climate conditions is significant, dependent on prevalence and intensity of maritime or continental factors. To pinpoint the three possible pitfalls in undiscriminating choice of climate change projections, and their impact on assessment of the sediment loads, we have discussed three basic problems faced by environmental modelers: (i) the issue of climate change data source based on comparison of future loads on forecasts prepared for a single meteorological station (point approach), and for grid points over the catchment area (areal approach); (ii) impact of reference periods (10- vs. 30 year long) applied in both approaches; (iii) finally, rainfall performance in particular models constituting the model ensemble to depict a possible range of simulated sediment loads during dry and wet conditions.

Methods

Catchment model

Sediment loads have been simulated for the upper Raba River localized in the Western Carpathians (Poland), with the source located at 780 m a.s.l., and flowing into a dammed reservoir (265 m a.s.l.). Its catchment (768 km2) is characterized by fast reaction to precipitation changes and vulnerability to water erosion32. A detailed description of the study area is provided (Supplementary S1 and Fig. S1).

To recreate this catchment in a digital space, the SWAT (Soil and Water Assessment Tool) model has been used (version 2012.10_2.19)33,34. The scope and source of the model input, sensitivity analysis (Table S2) and calibration data have been presented in Supplementary Table S1 and Fig. S2). Calibration, verification, and validation of the Raba River model was performed using the SWAT-CUP software and the SUFI-2 algorithm (Supplementary S2.1). Calibration and verification procedures have been performed for the upper and lower parts of the Raba separately, in the Myślenice and Proszówki profiles, respectively (Fig. 1). Validation procedure has been performed for the right-bank Raba River tributary (Stradomka River). All these points serve also as qualitative and quantitative monitoring locations under the Polish State Environmental Monitoring system. The calibrated, verified, and validated model has been called the baseline scenario in this study (Supplementary Tables S3, S4).Fig. 1 Localisation of the: (a) study area; (b) sources of the meteorological data for the point and areal approaches, and calibration/validation points/calculation profile; and (c) monthly distribution of average precipitation and suspended sediment loads for the baseline scenario. This figure was created using ArcGIS 10.2.1 for Desktop available at https://www.esri.com/en-us/home. License granted to Institute of Meteorology and Water Management.

The total load of suspended sediment delivered from the upper Raba River into the dammed reservoir (values for the model simulation cross-section, Myślenice) has been estimated in this scenario for approx. 6,000 t y−1 (tons per year) (Fig. 1). The monthly loads displayed a vast variability from 64 t m−1 to 1,444t m−1 (December and June, respectively) with maximum corresponding with a precipitation increase in late spring—early summer (May–July) when average monthly precipitation exceeds 70 mm.

Climate change projections

Climate change projections have been incorporated into the upper Raba River SWAT model as variant scenarios with the use of the delta change method. This commonly applied method is based on so-called monthly change rates, obtained from the climate change models with respect to the original historical climate data (reference period)35,36.

In the current study two sets of projections, using precipitation and temperature data, have been used. The first set included scenarios for the single synoptic station (WMO 12566, 19°47′ 42″ E, 50°04′ 40″ N) (point approach, P), and has been applied in the previous modeling studies for this area34,37. The second set has been prepared for the purpose of this study and includes E-OBS gridded data on a spatial resolution of 0.1° regular longitude-latitude grid for the area of the upper Raba River catchment (areal approach, A). In both approaches, described in detail (Supplementary S2.2), 14 different future climate GCM-RCM model pairs were chosen as the best reflecting the annual cycle of both precipitation and air temperature (Supplementary Table S6). In the current study two historical periods were taken into account: 10 year (2006–2015) and 30-year (1981–2010). The 10-year reference period has been originally used in the Development of Urban Adaptation Plans (UAP) for cities with more than 100,000 inhabitants in Poland which included climate change scenarios for Poland based on single meteorological stations38,39. In our study this period has been used to compare with the commonly recommended 30-year long reference period. Moreover, the climate projections were calculated for two time horizons: near (2026–2035) and far future (2046–2055), and for two Representative Concentration Pathways: RCP 4.5 and RCP 8.5 to follow the original scenarios developed to facilitate climate change adaptation in Poland40.

Previous studies indicated that precipitation and its projected changes have a decisive impact on the initiation and transport of soil particles both in the land and river bed phase [e.g. ref41–43]. Therefore, although both precipitation and temperature change projections were implemented in the suspended sediment load simulations, only the results of precipitation scenarios were analyzed. Moreover, to elucidate the impact of rainfall amount on load analyses, two outermost sub-ensembles, dry and wet, have been distinguished based on the already selected GCM-RCM model pairs (Supplementary Table S6). Finally, 20 variant scenarios have been analyzed in the current study (Fig. 2). Predicted precipitation changes for all variant scenarios have been presented in Supplementary S2.3, Figs. S3–S5).Fig. 2 Diagram of modeling variant scenarios applied. Scenario abbreviations include: Point/areal approach: P/A; Reference period length (10- and 30-year periods): 10/30; Model type (ensemble, wet subset, dry subset): e/w/d; RCP (RCP 4.5 and 8.5): 45/85; Future (near: 2026–35 / far: 2046–55): 1/2 (i.e. A10e451 scenario—areal approach, 10-year reference period, ensemble, RCP 4.5, near future).

Results and discussion

Pitfall no. 1: choice of the precipitation data source

Despite the variety of climate projection sources, there is still the limited availability of climate RCM simulations in some areas with their inconsistent accuracy28, which compel environmental modelers to use locally available data for their projections. We have tested projections built on the data from a single station (point approach) which was dictated simply by the availability of projections with monthly resolution, prepared and published nationwide40. Although the selected station was localized outside of the modeled catchment, the distance to the model simulation cross-section and elevation difference were in between the World Meteorological Organization’s (WMO) guidelines44. However, taking into consideration that representativeness of such data quickly decreases in mountainous areas, constituting the upstream part of the studied catchment, the areal approach has been also taken into consideration for comparative purposes. In this approach the diverse topography of the studied catchment, causing large differences in the distribution of rainfall45,46 was reflected more accurately.

Here, both scenario approaches (point and areal) suggested a future increase in yearly sediment loads compared to the baseline scenario (approx. 2,700 t y−1 on average), however, larger increases are expected for areal (up to 4,277 t y−1) than for point scenarios (up to 2,833 t y−1) (Supplementary Table S7). As for monthly load distribution (Fig. 3; Supplementary S2, S3) both approaches indicated that an unusual increase of loads delivered to the reservoir can be expected in April, by over 1700 t m−1, and almost 1900 t m-1 on average for point and areal scenarios, respectively. The uniqueness of April will be influenced by both the forecast increase in rainfall and temperature. Consequently, in the spring season, in the absence of protecting snow cover an increase in erosion in both the land phase (increased precipitation) and the riverbed phase of the catchment (increased flows) can be expected47,48. The second peak of the sediment loads delivery shall be expected in the summer months (June-July), reflecting precipitation variability in this area with distinctly higher rainfall in these months49,50. Although the monthly trend is similar for both approaches, the higher summer loads for areal scenarios should be observed, resulting from higher precipitation changes predicted for the entire catchment area than for the single meteorological station adopted originally. The difference between point and areal approaches could be more significant for mountainous areas with diverse distribution of precipitation better captured by the areal approach. Therefore, especially in mountainous areas, the areal approach should be adopted as better reflecting a catchment’s characteristics and used whenever possible.Fig. 3 Monthly distribution of sediment loads in the calculation profile for the point and area approach, and the 10 year reference period for RCP4.5 and 8.5 scenarios for near and far future (1-2026-35 and 2-2046-55).

Pitfall no. 2: choice of the reference periods

Lack of explanation for Aprils’ (more than 1 April) extreme loads in this catchment, also observed in other areas where climate change projections were adopted from the very same source40,51,52, prompted an interest in the impact of the reference period on the sediment simulations. Typically, 30 years are used as a climatic reference period in line with WMO’s recommendations53. Since such a period is long enough to filter out interannual variations in climate parameters or anomalies, it is yet short enough to show climate trends. However, many studies to date show that these guidelines are followed in quite a limited way in predicting future changes in catchment ecosystems. The limited access to quality controlled and homogenized local meteorological data in some areas frequently forces to shorten the period down to 10–20 years for environmental analysis [e.g. ref54–59].

Here, comparison of sediment loads in the areal approach based on the 30-year long reference period (1981–2010) and the 10 year period, selected to cover the same period as used in the point approach (2006–2015), interestingly did not show significant differences in average yearly loads. In both sets of simulations sediment loads delivered to the reservoir were higher by over 4,000 t y−1 from the baseline scenario values, but differed from each other only by approx. 2% (Supplementary Table S6). However, the monthly distribution of sediment loads turned out to be distinctly different for simulations based on both reference periods (Fig. 4) with no Aprils’ extremum for the longer reference period.Fig. 4 Monthly distribution of sediment loads in the calculation profile for the area approach and the 10 and 30 year reference period for RCP4.5 and 8.5 scenarios for near and far future (1-2026-35 and 2-2046-55).

Only the detailed analysis of monthly delta change rates for both sets of precipitation projections allowed us to finally understand the mechanism of April’s anomaly. The average precipitation for the month of April in the period of 2006–2015 was lower by almost 42% when compared to 1981–2010. Therefore, the delta change rates for this month also notably differed between both periods, reaching 90% and 35% in the near and far future projections, respectively. Which resulted in a significant increase in precipitation for the simulations based on the short term (2006–2015) reference period. Such an impact of low and high delta changes for the catchment SWAT modeled parameters has been observed before60, and here resulted in an approx. 1,185 t m−1 difference of sediment loads introduced into the reservoir in April.

It should also be noted that for precipitation sums, unlike temperature, no statistically significant trends related to climate change are observed in Central Europe45. Which is also noticeable when monthly precipitation is compared decade by decade for the catchment area (Supplementary Fig. S6). Therefore, selection of short reference periods when implementing model variant scenarios without their careful examination, may lead to random over- or underestimation of sediment loads in individual months.

Pitfall no. 3: choice of the model ensemble

The decisive impact of precipitation on sediment loads prompted in turn an interest in rainfall performance in the GCM-RCM model pairs applied in the current study. Generally, the selection of the final model ensemble for this particular area was performed based on the skill to simulate present and near-past climate, or the ability to represent the same connection pattern that drives the climate of the studied region61,62. Climate models with fundamental errors (e.g., unrealistically represented processes) should be disqualified as they cannot be improved by statistical postprocessing27. Although the bias adjustment (BA) procedure is dedicated to amend the raw model output, it has been proved that if applied without considering the underlying processes it may introduce even large artifacts and constitute itself a significant source of uncertainty27,63.

For environmental studies moisture content seems to be crucial, nevertheless, it is only occasionally observed in terms of the models’ moisture variability64–68, and its impact on environmental parameters is rarely studied. Here, we have used a probabilistic method to identify wet and dry models and subsequently to estimate the range of possible extreme values in sediment loads. As expected, variant scenarios based on the extracted wet and dry sub-ensembles translated into highs and lows of the expected future yearly sediment load delivery into the reservoir. Simulations performed with use of both sub-ensembles revealed that the difference in total sediment loads could exceed 3,000 t y-1 (Supplementary Table S6). What is more important, our results also show that use of only dry and wet models significantly changes the pattern of sediment monthly loads (Fig. 5). For dry sub-ensembles the peak of sediment delivery is expected in May–June, while for wet sub-ensembles the high load delivery period is shifted to early spring. Moreover, this peak can last from March to August, which results from projected precipitation changes (Supplementary Fig. S5). Moreover, it should be noted that the extreme sediment loads in the dry sub-ensemble may exceed the wet sub-ensemble projections in a given month. Therefore, a composition of model ensemble, in terms of wet and dry projections, is of particular value for environmental modelers dealing with pollutants transported via particles eroded from the catchment. Here, if only wet models in the ensemble were taken into consideration, the associated peak of sediment loads would be displayed earlier and coincided with the pre-vegetation period of increased fertilization in the analyzed catchment. This would mean an increased risk in reservoir contamination with biogenic compounds, and consequently, a higher risk of eutrophication.Fig. 5 Monthly distribution of sediment loads in the calculation profile for wet and dry area sub-ensembles for RCP4.5 and 8.5 scenarios for near and far future. (1-2026-35 and 2-2046-55).

Integration steps

It is generally accepted that current changes in the climate system and those expected in the future will increasingly have significant impacts on ecosystems. Since adaptation plays a key role in reducing risks and vulnerability from these changes, the need for reliable assessments of their impacts on the environment is drastically growing. The results of climate, and consequently of catchment models, are increasingly becoming the basis for shaping water policy and management for the upcoming decades. It is therefore not surprising that the pressure on climate scientists, whose work plays a key role here, intensifies extremely. Both types of modeling, climatological and environmental, are performed by specialists expertly, but unfortunately not jointly.

As pointed out above, the abundance of parameters impacting the goodness of final choice of the climate model may overwhelm their potential recipients and users. Moreover, this problem combined with an uneven representativeness of individual climate models and limited number of RCM simulations available for some regions may lead to a gross over- or underestimation of modeled environmental parameters. Ultimately, this situation leads to confusion and deepening distrust towards climate change forecasts, and consequently to ignoring or disregarding warnings on future scenarios.

Presented here, three selected pitfalls help to illustrate how the choice of meteorological data, reference period, and model ensemble can affect sediment load estimations. For our study venue (Carpathian catchment delivering suspended sediment to the dammed reservoir) calculated differences in average future loads could reach up to even 6,000 tons of sediment per year (Fig. 6). However, large differences in monthly loads (up to 2,000 tons) are also visible in selected months. In point of fact, all precipitation variability driven parameters and processes in the catchment (e.g. runoff, flow, and flooding) can be subjected to such discrepancies depending on the climate change scenario choice.Fig. 6 Yearly average sediment loads (t y−1) for modeling variant scenarios: black—baseline, colors/acronyms—according to the scheme applied in Fig. 2

It is now time for better integration between climatologists and environmental modelers and to focus attention on joint projects, workshops, conferences, and publications. These activities should concentrate mainly on mid-scale cooperation to elucidate regional climate and environmental peculiarities, and to introduce future climate multi-model specific impact ensembles in order to facilitate an informed choice of available climate information. We propose as well, development of the concept of rigorous science, already existing in climatology, taking into account biases in climate model simulations27, choice of meteorological data, reference period, and not least model ensemble.

Supplementary Information

Supplementary Information.

Acknowledgements

This research was supported by the program “Excellence initiative–research university” for the AGH University of Krakow and IMGW–PIB (sub. FBW–16).

Author contributions

E.S.: Writing—review and editing, Methodology. Supervision; P.O.-W.—Methodology, Software; P.W.—Methodology, Writing original draft. Data validation; E.J.- Data curation; P.S.—Data curation; A.W.—Methodology, Data validation; J.A.—Methodology. All authors reviewed the manuscript.

Funding

The funding was provided by Akademia Górniczo-Hutnicza im. Stanislawa Staszica (IDUB No. 501.696.7996/L-34).

Data availability

The full dataset of sediment loads in all the applied variant climate scenarios is available as Mendeley dataset https://data.mendeley.com/datasets/g58vhcykcj/2 Precipitation and temperature data for the Kraków-Balice synoptic station [WMO 12,566, 19°47′42″E, 50°04′40″N] was obtained from the Development of Urban Adaptation Plans http://44mpa.pl/?lang=en and https://danepubliczne.imgw.pl/data/dane_pomiarowo_obserwacyjne/. For the for the upper Raba River catchment, data was sourced from area E-OBS gridded data on a spatial resolution of 0.1° regular grid available at https://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php]. To provide future climate information CORDEX regional climate model data for the European domain with 0.11° × 0.11° horizontal resolution (https://cds.climate.copernicus.eu) was used.

Declarations

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. IPCC. Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press).
2. Sentian J Herman F Kai SKS Soil erosion risk under climate change scenarios: A case study in rural area with varying land uses IOP Conf. Ser. Earth Environ. Sci. 2022 1103 1 012037 10.1088/1755-1315/1103/1/012037
Sentian, J., Herman, F. & Kai, S. K. S. Soil erosion risk under climate change scenarios: A case study in rural area with varying land uses. IOP Conf. Ser. Earth Environ. Sci. 1103(1), 012037 (2022).
3. Halecki W Kruk E Ryczek M Loss of topsoil and soil erosion by water in agricultural areas: A multi-criteria approach for various land use scenarios in the Western Carpathians using a SWAT model Land Use Policy 2018 73 363 372 10.1016/j.landusepol.2018.01.041
Halecki, W., Kruk, E. & Ryczek, M. Loss of topsoil and soil erosion by water in agricultural areas: A multi-criteria approach for various land use scenarios in the Western Carpathians using a SWAT model. Land Use Policy 73, 363–372 (2018).
4. Ramos MC Effects of rainfall intensity and slope on sediment, nitrogen and phosphorus losses in soils with different use and soil hydrological properties Agric. Water Manag. 2019 226 105789 10.1016/j.agwat.2019.105789
Ramos, M. C. et al. Effects of rainfall intensity and slope on sediment, nitrogen and phosphorus losses in soils with different use and soil hydrological properties. Agric. Water Manag. 226, 105789 (2019).
5. Borrelli P Land use and climate change impacts on global soil erosion by water (2015–2070) Proc. Natl. Acad. Sci. U.S.A. 2020 117 36 21994 22001 10.1073/pnas.2001403117 32839306
Borrelli, P. et al. Land use and climate change impacts on global soil erosion by water (2015–2070). Proc. Natl. Acad. Sci. U.S.A. 117(36), 21994–22001 (2020).32839306
6. Panagos P Projections of soil loss by water erosion in Europe by 2050 Environ. Sci. Policy 2021 124 380 392 10.1016/j.envsci.2021.07.012
Panagos, P. et al. Projections of soil loss by water erosion in Europe by 2050. Environ. Sci. Policy 124, 380–392 (2021).
7. Wang H Xie T Yu X Zhang C Simulation of soil loss under different climatic conditions and agricultural farming economic benefits: The example of Yulin City on Loess Plateau Agr Water Manage. 2021 244 106462 10.1016/j.agwat.2020.106462
Wang, H., Xie, T., Yu, X. & Zhang, C. Simulation of soil loss under different climatic conditions and agricultural farming economic benefits: The example of Yulin City on Loess Plateau. Agric. Water Manag. 244, 106462 (2021).
8. Eekhout JP de Vente J Global impact of climate change on soil erosion and potential for adaptation through soil conservation Earth Sci. Rev. 2022 226 103921 10.1016/j.earscirev.2022.103921
Eekhout, J. P. & de Vente, J. Global impact of climate change on soil erosion and potential for adaptation through soil conservation. Earth Sci. Rev. 226, 103921 (2022).
9. Elba E Urban B Ettmer B Farghaly D Mitigating the impact of climate change by reducing evaporation losses: Sediment removal from the High Aswan Dam reservoir Am. J. Clim. Change 2017 6 02 230 10.4236/ajcc.2017.62012
Elba, E., Urban, B., Ettmer, B. & Farghaly, D. Mitigating the impact of climate change by reducing evaporation losses: Sediment removal from the High Aswan Dam reservoir. Am. J. Clim. Change 6(02), 230 (2017).
10. Xie M Li Y Cai X Hydrological responses to the synergistic climate and land-use changes in the upper Lancang river basin Environ. Res. Lett. 2023 19 1 014045 10.1088/1748-9326/ad1347
Xie, M., Li, Y. & Cai, X. Hydrological responses to the synergistic climate and land-use changes in the upper Lancang river basin. Environ. Res. Lett. 19(1), 014045 (2023).
11. Ali SA Aadhar S Shah HL Mishra V Projected increase in hydropower production in India under climate change Sci. Rep. U.K. 2018 8 1 12450 10.1038/s41598-018-30489-4
Ali, S. A., Aadhar, S., Shah, H. L. & Mishra, V. Projected increase in hydropower production in India under climate change. Sci. Rep. U.K. 8(1), 12450 (2018).
12. Randle TJ Sustaining United States reservoir storage capacity: Need for a new paradigm J. Hydrol. 2021 602 126686 10.1016/j.jhydrol.2021.126686
Randle, T. J. et al. Sustaining United States reservoir storage capacity: Need for a new paradigm. J. Hydrol. 602, 126686 (2021).
13. Patro ER De Michele C Granata G Biagini C Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview J. Environ. Manage. 2022 320 115826 10.1016/j.jenvman.2022.115826 35952562
Patro, E. R., De Michele, C., Granata, G. & Biagini, C. Assessment of current reservoir sedimentation rate and storage capacity loss: An Italian overview. J. Environ. Manag. 320, 115826 (2022).35952562
14. Salas JD Obeysekera J Vogel RM Techniques for assessing water infrastructure for nonstationary extreme events: A review Hydrol. Sci. J. 2018 63 3 325 352 10.1080/02626667.2018.1426858
Salas, J. D., Obeysekera, J. & Vogel, R. M. Techniques for assessing water infrastructure for nonstationary extreme events: A review. Hydrol. Sci. J. 63(3), 325–352 (2018).
15. Ranasinghe R Wu CS Conallin J Duong TM Anthony EJ Disentangling the relative impacts of climate change and human activities on fluvial sediment supply to the coast by the world’s large rivers: Pearl River Basin China Sci. Rep. U.K. 2019 9 1 9236 10.1038/s41598-019-45442-2
Ranasinghe, R., Wu, C. S., Conallin, J., Duong, T. M. & Anthony, E. J. Disentangling the relative impacts of climate change and human activities on fluvial sediment supply to the coast by the world’s large rivers: Pearl River Basin China. Sci. Rep. U.K. 9(1), 9236 (2019).
16. Toimil A Addressing the challenges of climate change risks and adaptation in coastal areas: A review Coast Eng. 2020 156 103611 10.1016/j.coastaleng.2019.103611
Toimil, A. et al. Addressing the challenges of climate change risks and adaptation in coastal areas: A review. Coast Eng. 156, 103611 (2020).
17. Şen Z Water structures and climate change impact: a review Water Resour. Manag. 2020 34 13 4197 4216 10.1007/s11269-020-02665-7
Şen, Z. Water structures and climate change impact: a review. Water Resour. Manag. 34(13), 4197–4216 (2020).
18. Izaguirre C Losada IJ Camus P Vigh JL Stenek V Climate change risk to global port operations Nat. Clim. Change 2021 11 1 14 20 10.1038/s41558-020-00937-z
Izaguirre, C., Losada, I. J., Camus, P., Vigh, J. L. & Stenek, V. Climate change risk to global port operations. Nat. Clim. Change 11(1), 14–20 (2021).
19. Giorgi F Raffaele F Coppola E The response of precipitation characteristics to global warming from climate projections Earth Syst. Dynam. 2019 10 1 73 89 10.5194/esd-10-73-2019
Giorgi, F., Raffaele, F. & Coppola, E. The response of precipitation characteristics to global warming from climate projections. Earth Syst. Dynam. 10(1), 73–89 (2019).
20. Li C Larger increases in more extreme local precipitation events as climate warms Geophys. Res. Lett. 2019 46 12 6885 6891 10.1029/2019GL082908
Li, C. et al. Larger increases in more extreme local precipitation events as climate warms. Geophys. Res. Lett. 46(12), 6885–6891 (2019).
21. Szalińska E Orlińska-Woźniak P Wilk P Sediment load variability in response to climate and land use changes in a Carpathian catchment (Raba River, Poland) J. Soil Sediment. 2020 20 2641 2652 10.1007/s11368-020-02600-8
Szalińska, E., Orlińska-Woźniak, P. & Wilk, P. Sediment load variability in response to climate and land use changes in a Carpathian catchment (Raba River, Poland). J. Soil Sediment. 20, 2641–2652 (2020).
22. Li D Exceptional increases in fluvial sediment fluxes in a warmer and wetter High Mountain Asia Science 2021 374 6567 599 603 10.1126/science.abi9649 34709922
Li, D. et al. Exceptional increases in fluvial sediment fluxes in a warmer and wetter High Mountain Asia. Science 374(6567), 599–603 (2021).34709922
23. Syvitski J Earth’s sediment cycle during the Anthropocene Nat. Rev. Earth Environ. 2022 3 3 179 196 10.1038/s43017-021-00253-w
Syvitski, J. et al. Earth’s sediment cycle during the Anthropocene. Nat. Rev. Earth Environ. 3(3), 179–196 (2022).
24. Verma SK Prasad AD Verma MK An assessment of ongoing developments in water resources management incorporating SWAT model: Overview and perspectives Nat. Environ. Pollut. Technol. 2022 21 4 1963 1970 10.46488/NEPT.2022.v21i04.051
Verma, S. K., Prasad, A. D. & Verma, M. K. An assessment of ongoing developments in water resources management incorporating SWAT model: Overview and perspectives. Nat. Environ. Pollut. Technol. 21(4), 1963–1970 (2022).
25. Mahdian M Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: Case study of the Anzali wetland Sci. Rep. 2023 13 1 5399 10.1038/s41598-023-32343-8 37012264
Mahdian, M. et al. Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: Case study of the Anzali wetland. Sci. Rep. 13(1), 5399 (2023).37012264
26. Gebrechorkos SH Bernhofer C Hülsmann S Climate change impact assessment on the hydrology of a large river basin in Ethiopia using a local-scale climate modelling approach Sci. Total Environ. 2020 742 140504 10.1016/j.scitotenv.2020.140504 32623168
Gebrechorkos, S. H., Bernhofer, C. & Hülsmann, S. Climate change impact assessment on the hydrology of a large river basin in Ethiopia using a local-scale climate modelling approach. Sci. Total Environ. 742, 140504 (2020).32623168
27. Maraun D Towards process-informed bias correction of climate change simulations Nat. Clim. Change 2017 7 11 664 773 10.1038/nclimate3418
Maraun, D. et al. Towards process-informed bias correction of climate change simulations. Nat. Clim. Change 7(11), 664–773 (2017).
28. Parding KM An interactive tool for evaluation and selection of climate model ensembles Clim. Serv. 2020 18 100167 10.1016/j.cliser.2020.100167
Parding, K. M. et al. An interactive tool for evaluation and selection of climate model ensembles. Clim. Serv. 18, 100167 (2020).
29. Samaniego L Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins Clim. Change 2017 141 435 449 10.1007/s10584-016-1778-y
Samaniego, L. et al. Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins. Clim. Change 141, 435–449 (2017).
30. McSweeney CF Jones RG How representative is the spread of climate projections from the 5 CMIP5 GCMs used in ISI-MIP? Clim. Serv. 2016 1 24 29 10.1016/j.cliser.2016.02.001
McSweeney, C. F. & Jones, R. G. How representative is the spread of climate projections from the 5 CMIP5 GCMs used in ISI-MIP?. Clim. Serv. 1, 24–29 (2016).
31. Mezghani A CHASE-PL Climate Projection dataset over Poland-bias adjustment of EURO-CORDEX simulations Earth Syst. Sci. Data 2017 9 2 905 925 10.5194/essd-9-905-2017
Mezghani, A. et al. CHASE-PL Climate Projection dataset over Poland-bias adjustment of EURO-CORDEX simulations. Earth Syst. Sci. Data 9(2), 905–925 (2017).
32. Bucała-Hrabia A An integrated approach for investigating geomorphic changes due to flash flooding in two small stream channels (Western Polish Carpathians) J. Hydrol. Reg. 2020 31 100731
Bucała-Hrabia, A. et al. An integrated approach for investigating geomorphic changes due to flash flooding in two small stream channels (Western Polish Carpathians). J. Hydrol. Reg. 31, 100731 (2020).
33. Orlińska-Woźniak P Szalińska E Wilk P Do land use changes balance out sediment yields under climate change predictions on the Sub-Basin scale? Carpathian Basin example Water 2020 12 5 1499 10.3390/w12051499
Orlińska-Woźniak, P., Szalińska, E. & Wilk, P. Do land use changes balance out sediment yields under climate change predictions on the Sub-Basin scale? Carpathian Basin example. Water 12(5), 1499 (2020).
34. Wilk P From the source to the reservoir and beyond—tracking sediment particles with modeling tools under climate change predictions (Carpathian Mts) J. Soil. Sediment. 2022 22 11 2929 2947 10.1007/s11368-022-03287-9
Wilk, P. et al. From the source to the reservoir and beyond—tracking sediment particles with modeling tools under climate change predictions (Carpathian Mts). J. Soil. Sediment. 22(11), 2929–2947 (2022).
35. LaFond, K. M., Griffis, V. W. & Spellman, P. Forcing hydrologic models with GCM output: Bias correction vs. the” delta change” method. In World Environmental and Water Resources Congress 2146–2155 (2014).
36. Li C Fang H Assessment of climate change impacts on the streamflow for the Mun river in the Mekong Basin Southeast Asia: Using SWAT model Catena 2021 201 105199 10.1016/j.catena.2021.105199
Li, C. & Fang, H. Assessment of climate change impacts on the streamflow for the Mun river in the Mekong Basin Southeast Asia: Using SWAT model. Catena 201, 105199 (2021).
37. Szalińska E Climate change impacts on contaminant loads delivered with sediment yields from different land use types in a Carpathian basin Sci. Total Environ. 2021 755 142898 10.1016/j.scitotenv.2020.142898 33348488
Szalińska, E. et al. Climate change impacts on contaminant loads delivered with sediment yields from different land use types in a Carpathian basin. Sci. Total Environ. 755, 142898 (2021).33348488
38. Dumieński G Lisowska A Tiukało A Chojnacka-Ożga L Lorenc H Climatic hazards of 44 Polish cities based on urban plans for adaptation to climate change Contemporary Problems of Polish Climate, IMGW-PIB 2019 Polish
Dumieński, G., Lisowska, A. & Tiukało, A. Climatic hazards of 44 Polish cities based on urban plans for adaptation to climate change. In Contemporary Problems of Polish Climate, IMGW-PIB (eds Chojnacka-Ożga, L. & Lorenc, H.) (Polish, 2019).
39. MPA. Development of Urban Adaptation Plans for Cities with More than 100,000 Inhabitants in Poland. http://44mpa.pl/project-background/?lang=en (2020).
40. MPA. Development of Urban Adaptation Plans for Cities with More than 100,000 Inhabitants in Poland. http://44mpa.pl/project-background/?lang=en (2023).
41. Vercruysse K Grabowski RC Rickson RJ Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation Earth Sci. Rev. 2017 166 38 52 10.1016/j.earscirev.2016.12.016
Vercruysse, K., Grabowski, R. C. & Rickson, R. J. Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation. Earth Sci. Rev. 166, 38–52 (2017).
42. Gholami V Booij MJ Tehrani EN Hadian MA Spatial soil erosion estimation using an artificial neural network (ANN) and field plot data Catena 2018 163 210 218 10.1016/j.catena.2017.12.027
Gholami, V., Booij, M. J., Tehrani, E. N. & Hadian, M. A. Spatial soil erosion estimation using an artificial neural network (ANN) and field plot data. Catena 163, 210–218 (2018).
43. Shrestha NK Wang J Predicting sediment yield and transport dynamics of a cold climate region watershed in changing climate Sci. Total Environ. 2018 625 1030 1045 10.1016/j.scitotenv.2017.12.347 29996400
Shrestha, N. K. & Wang, J. Predicting sediment yield and transport dynamics of a cold climate region watershed in changing climate. Sci. Total Environ. 625, 1030–1045 (2018).29996400
44. WMO World Meteorological Organization. Guide to Instruments and Methods of Observation (WMO-No. 8). https://library.wmo.int/idurl/4/41650 (2021).
45. Wypych A Ustrnul Z Schmatz DR Long-term variability of air temperature and precipitation conditions in the Polish Carpathians J. Mt. Sci. 2018 15 2 237 253 10.1007/s11629-017-4374-3
Wypych, A., Ustrnul, Z. & Schmatz, D. R. Long-term variability of air temperature and precipitation conditions in the Polish Carpathians. J. Mt. Sci. 15(2), 237–253 (2018).
46. Twardosz R Cebulska M Temporal variability of the highest and the lowest monthly precipitation totals in the Polish Carpathian Mountains (1881–2018) Theor. Appl. Climatol. 2020 140 327 341 10.1007/s00704-019-03079-1
Twardosz, R. & Cebulska, M. Temporal variability of the highest and the lowest monthly precipitation totals in the Polish Carpathian Mountains (1881–2018). Theor. Appl. Climatol. 140, 327–341 (2020).
47. Twardosz R Walanus A Guzik I Warming in Europe: Recent trends in annual and seasonal temperatures Pure. Appl. Geophys. 2021 178 10 4021 4032 10.1007/s00024-021-02860-6
Twardosz, R., Walanus, A. & Guzik, I. Warming in Europe: Recent trends in annual and seasonal temperatures. Pure. Appl. Geophys. 178(10), 4021–4032 (2021).
48. Wilk P From the source to the reservoir and beyond—tracking sediment particles with modeling tools under climate change predictions (Carpathian Mts.) J. Soil Sediment. 2022 22 11 2929 2947 10.1007/s11368-022-03287-9
Wilk, P. et al. From the source to the reservoir and beyond—tracking sediment particles with modeling tools under climate change predictions (Carpathian Mts.). J. Soil Sediment. 22(11), 2929–2947 (2022).
49. Walanus A Cebulska M Twardosz R Long-term variability pattern of monthly and annual atmospheric precipitation in the Polish Carpathian Mountains and their Foreland (1881–2018) Pure Appl. Geophys. 2021 178 2 633 650 10.1007/s00024-021-02663-9
Walanus, A., Cebulska, M. & Twardosz, R. Long-term variability pattern of monthly and annual atmospheric precipitation in the Polish Carpathian Mountains and their Foreland (1881–2018). Pure Appl. Geophys. 178(2), 633–650 (2021).
50. Gil E Kijowska-Strugała M Demczuk P Soil erosion dynamics on a cultivated slope in the Western Polish Carpathians based on over 30 years of plot studies Catena 2021 207 105682 10.1016/j.catena.2021.105682
Gil, E., Kijowska-Strugała, M. & Demczuk, P. Soil erosion dynamics on a cultivated slope in the Western Polish Carpathians based on over 30 years of plot studies. Catena 207, 105682 (2021).
51. Bojanowski, D., Orlińska-Woźniak, P., Wilk, P., Jakusik, E. & Szalińska, E. Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios. 10.22541/essoar.168056816.63940296/v1 (2023).
52. Szalińska, E. et al. Total Nitrogen and Phosphorus Loads in Surface Runoff from Urban Land Use (City of Lublin) Under Climate Change. 10.2139/ssrn.4530209 (2023).
53. WMO World Meteorological Organization. WMO Guidelines on the Calculation of Climate Normals. WMO-No. 1203. https://library.wmo.int/records/item/55797-wmo-guidelines-on-the-calculation-of-climate-normals (2017).
54. Ragettli S Immerzeel WW Pellicciotti F Contrasting climate change impact on river flows from high-altitude catchments in the Himalayan and Andes Mountains Proc. Natl. Acad. Sci. U.S.A. 2016 113 33 9222 9227 10.1073/pnas.1606526113 27482082
Ragettli, S., Immerzeel, W. W. & Pellicciotti, F. Contrasting climate change impact on river flows from high-altitude catchments in the Himalayan and Andes Mountains. Proc. Natl. Acad. Sci. U.S.A. 113(33), 9222–9227 (2016).27482082
55. Ba W Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: a case study in the Kaidu River Basin, Xinjiang, China J. Arid Land 2018 10 905 920 10.1007/s40333-018-0068-0
Ba, W. et al. Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: a case study in the Kaidu River Basin, Xinjiang, China. J. Arid Land 10, 905–920 (2018).
56. Andaryani S Trolle D Nikjoo MR Moghadam MR Mokhtari D Forecasting near-future impacts of land use and climate change on the Zilbier river hydrological regime, northwestern Iran Environ. Earth Sci. 2019 78 1 14 10.1007/s12665-019-8193-4
Andaryani, S., Trolle, D., Nikjoo, M. R., Moghadam, M. R. & Mokhtari, D. Forecasting near-future impacts of land use and climate change on the Zilbier river hydrological regime, northwestern Iran. Environ. Earth Sci. 78, 1–14 (2019).
57. Woolway RI Merchant CJ Worldwide alteration of lake mixing regimes in response to climate change Nat. Geosci. 2019 12 4 271 276 10.1038/s41561-019-0322-x
Woolway, R. I. & Merchant, C. J. Worldwide alteration of lake mixing regimes in response to climate change. Nat. Geosci. 12(4), 271–276 (2019).
58. Singh L Saravanan S Impact of climate change on hydrology components using CORDEX South Asia climate model in Wunna, Bharathpuzha, and Mahanadi, India Environ. Monit. Assess. 2020 192 11 678 10.1007/s10661-020-08637-z 33025274
Singh, L. & Saravanan, S. Impact of climate change on hydrology components using CORDEX South Asia climate model in Wunna, Bharathpuzha, and Mahanadi, India. Environ. Monit. Assess. 192(11), 678 (2020).33025274
59. Elbeltagi A The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta Egypt Sci. Total Environ. 2020 743 140770 10.1016/j.scitotenv.2020.140770 32679501
Elbeltagi, A. et al. The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta. Egypt Sci. Total Environ. 743, 140770 (2020).32679501
60. Andaryani S Nourani V Trolle D Dehghani M Asl AM Assessment of land use and climate change effects on land subsidence using a hydrological model and radar technique J. Hydrol. 2019 578 124070 10.1016/j.jhydrol.2019.124070
Andaryani, S., Nourani, V., Trolle, D., Dehghani, M. & Asl, A. M. Assessment of land use and climate change effects on land subsidence using a hydrological model and radar technique. J. Hydrol. 578, 124070 (2019).
61. Lutz AF Selecting representative climate models for climate change impact studies: An advanced envelope-based selection approach Int J. Climatol. 2016 36 12 3988 4005 10.1002/joc.4608
Lutz, A. F. et al. Selecting representative climate models for climate change impact studies: An advanced envelope-based selection approach. Int J. Climatol. 36 (12), 3988–4005 (2016).
62. Khan AJ Koch M Selecting and downscaling a set of climate models for projecting climatic change for impact assessment in the Upper Indus Basin (UIB) Climate 2018 10.3390/cli6040089
Khan, A. J. & Koch, M. Selecting and downscaling a set of climate models for projecting climatic change for impact assessment in the Upper Indus Basin (UIB). Climate. 10.3390/cli6040089 (2018).
63. Casanueva A Testing bias adjustment methods for regional climate change applications under observational uncertainty and resolution mismatch Atmos. Sci. Lett. 2020 21 978 10.1002/asl.978
Casanueva, A. et al. Testing bias adjustment methods for regional climate change applications under observational uncertainty and resolution mismatch. Atmos. Sci. Lett. 21, 978 (2020).
64. Karlsson IB Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change J. Hydrol. 2016 535 301 317 10.1016/j.jhydrol.2016.01.069
Karlsson, I. B. et al. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change. J. Hydrol. 535, 301–317 (2016).
65. Zhao P Lü H Yang H Wang W Fu G Impacts of climate change on hydrological droughts at basin scale: A case study of the Weihe River Basin, China Quat. Int. 2019 513 37 46 10.1016/j.quaint.2019.02.022
Zhao, P., Lü, H., Yang, H., Wang, W. & Fu, G. Impacts of climate change on hydrological droughts at basin scale: A case study of the Weihe River Basin, China. Quat. Int. 513, 37–46 (2019).
66. Näschen K Diekkrüger B Evers M Höllermann B Steinbach S Thonfeld F The impact of land use/land cover change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios Sustainability 2019 11 24 7083 10.3390/su11247083
Näschen, K. et al. The impact of land use/land cover change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios. Sustainability 11(24), 7083 (2019).
67. Henriksen HJ Jakobsen A Pasten-Zapata E Troldborg L Sonnenborg TO Assessing the impacts of climate change on hydrological regimes and fish EQR in two Danish catchments J. Hydrol. Reg. 2021 34 100798
Henriksen, H. J., Jakobsen, A., Pasten-Zapata, E., Troldborg, L. & Sonnenborg, T. O. Assessing the impacts of climate change on hydrological regimes and fish EQR in two Danish catchments. J. Hydrol. Reg. 34, 100798 (2021).
68. Yasin M Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models Environ. Sci. Pollut. Res. 2022 10.1007/s11356-021-17050-z
Yasin, M. et al. Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models. Environ. Sci. Pollut. Res.10.1007/s11356-021-17050-z (2022).
