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Groundwater in shallow aquifers is commonly used for community water supply in cold climates. Shallow groundwaters are inherently susceptible to contamination from land-use and surface water intrusion threatening drinking water usage. We used a large-scale snapshot data set of stable water isotopes from shallow glaciofluvial aquifers used for drinking water supply in Northern Finland to assess surface water intrusion risks and recharge conditions. This data set was supplemented by long-term stable water isotope precipitation data, Geographic Information System proximity analysis and multivariate statistics. The isotope analysis suggest that a warm season contributes about 60% to the total annual precipitation in the region. This is reflected in the aquifers isotopic composition as it represents an approximately equal mixture of warm and cold season precipitation. Groundwater isotope data normalized to precipitation inputs by line-conditioned excess (lc-excess) was used to flag the water supply wells impacted by surface water intrusions. The proximity analysis showed some of the wells may be affected by intrusions from gravel pit ponds, lakes and peatland drainage. On the larger scale, the wells in coastal areas were more likely to have evaporated water (intrusion) compared to inland regions of Northern Finland due to lower water availability and the presence of man-made structures. This application of stable water isotopes with lc-excess is a useful approach not only for recharge studies but also within water management for supply well surface water contamination risk assessment.

Forested buffer zones with varying width have been suggested as the most promising approach for protecting boreal riparian biodiversity, reducing erosion, and minimizing nutrient leaching from managed forestry areas. Yet, less optimal fixed-width approach is still largely used, likely because of its simple design and implementation. We examined the efficiency of varying-width buffer zones based on depth-to-water (DTW) index in protecting stream riparian plant communities. We further compared the economic costs of DTW-based buffer to commonly used 5, 10 and 15 m fixed-width buffers. We also included an additional buffer based on a combination of DTW and erosion risk (Revised Universal Soil Loss Equation, RUSLE) into these comparisons to see the extent and cost of a buffer that should maximize the protection of the linked aquatic environment. Plant species richness increased with increasing soil moisture and species preferring moist conditions, nutrient-rich soils and high pH were clearly more abundant adjacent to stream in areas with high predicted soil moisture than in dry areas. Differences in species richness were paralleled by differences in community composition and higher beta diversity of plant communities in wet than in dry riparian areas. There were also several indicator species typical for moist and nutrient-rich soils for wet riparian areas. Riparian buffer zones based on DTW were on average larger than 15 m wide fixed-width buffers. However, the cost for DTW-based buffer was lower than for fixed-width buffer zones when the cost was normalized by area. Simulated selective cutting decreased the costs, but cutting possibilities were variable among streams and depended on the characteristics of forest stands. Our results thus suggest a high potential of DTW in predicting wet areas and variable-width buffer zones based on these areas in the protection of riparian biodiversity and stream ecosystems.

Ecohydrological studies in tropical peatland have mostly focused on a small number of non-native commercial species. However, studies of native species are urgently needed as they are considered to be a possible solution in the restoration of millions of hectares of degraded tropical peatlands. We investigated peatland species on Padang Island, Indonesia, to assess their responses to changing environmental factors, particularly the high fluctuation of the water table due to intensive peatland draining. We monitored the sap-flux velocity and radial growth of six trees (four native and one non-native peatland species) in high temporal resolution using sap-flux meters and dendrometers up to seven months. Monitoring also included hydrological and micrometeorological parameters. We found that sap-flux velocity in the monitored species was mainly controlled by air vapor pressure deficits, photosynthetic active radiation, and to some extent, by wind speed and water-table depth. We also observed a species-specific correlation between daily sap-flux velocity and daily radial growth. Non-native Acacia crassicarpa had up to twice the radial growth of native species. This growth of non-native species was significantly higher at a shallow water-table depth, while native species did not show the same relationship. The interaction between water-table depth, sap-flux velocity, and radial growth in daily timescale was not straightforward, presumably because of the complex carbon-allocation mechanism in trees.

Climate change in combination with land use alterations may lead to significant changes in soil erosion and sediment fluxes in streams. Optical turbidity sensors can monitor with high frequency and can be used as a proxy for suspended sediment concentration (SSC) provided there is an acceptable calibration curve for turbidity measured by sensors and SSC from water samples. This study used such calibration data from 31 streams in 11 different research projects or monitoring programmes in six Northern European countries. The aim was to find patterns in the turbidity-SSC correlations based on stream characteristics such as mean and maximum turbidity and SSC, catchment area, land use, hydrology, soil type, topography, and the number and representativeness of the data that are used for the calibration. There were large variations, but the best correlations between turbidity and SSC were found in streams with a mean and maximum SSC of >30–200 mg/l, and a mean and maximum turbidity above 60–200 NTU/FNU, respectively. Streams draining agricultural areas with fine-grained soils had better correlations than forested streams draining more coarse-grained soils. However, the study also revealed considerable differences in methodological approaches, including analytical methods to determine SSC, water sampling strategies, quality control procedures, and the use of sensors based on different measuring principles. Relatively few national monitoring programmes in the six countries involved in the study included optical turbidity sensors, which may partly explain this lack of methodological harmonisation. Given the risk of future changes in soil erosion and sediment fluxes, increased harmonisation is highly recommended, so that turbidity data from optical sensors can be better evaluated and intercalibrated across streams in comparable geographical regions.

This doctoral thesis aims to review methods which use high-resolution remote sensing (RS) to evaluate the changes in degraded and restored northern peatlands and to test and develop these topo-hydrological methods. A significant share of peatlands worldwide is degraded and encountered subsidence due to land use and drainage. Recently, activities have been directed increasingly to mitigating environmental impacts and to restoration. Understanding the state and characteristics of degradation, as well as monitoring restoration success, is important in the sustainable management of peatlands. Conventionally, the state of peatlands has been monitored using laborious field surveys that are poorly suited for monitoring larger areas. Monitoring the internal heterogeneity of the site or larger regional, national or international areas requires more applicable methods. This thesis reviews the available remote sensing methods to observe the land cover, water flow routes, and surface soil moisture on peatlands. In addition, the magnitude and impacts of topographical changes on peatland hydrology were demonstrated at eight sites. The analysis showed the subsidence of cultivated peatlands, which have caused a spread of annual river floods by 101–194% over the last 24–51 years. On forestry-drained peatlands, topographic flow accumulation and wetness indices showed that restoration increased the site wetness by 2.9–6.9% and decreased its deviation by 13–15% 1–10 months after the restoration. The methods used emphasized the determinative role of topography in the hydrological conditions of peatlands. RS is well applicable in peatland monitoring, providing advanced large-coverage and/or high-detail monitoring data. Each method, however, includes specific technical challenges and development needs, and field measurements will also be needed in the future to support the remote sensing data and analysis. The production of the data might be laborious and require adjunct resource, Tiivistelmä Tämän väitöskirjan tarkoituksena on koota tarkan resolution kaukokartoitusmenetelmiä soiden kuivatuksesta ja ennallistamisesta aiheutuneiden muutosten arvioimiseen sekä testata ja kehittää valittuja topo-hydrologisia menetelmiä. Merkittävä osuus maailman soista on häiriintynyt, ja maa on painunut maankäytön ja kuivatuksen seurauksena. Toimintaa on alettu suunnata yhä enemmän ympäristövaikutusten lieventämiseen ja ennallistamiseen. Soiden muuttuneen hydrologian ymmärtäminen ja toisaalta toteutettujen toimenpiteiden onnistumisen arviointi ovat soiden tavoitteidenmukaisen ja kestävän käytön edellytys. Perinteisesti soita on seurattu työläillä kenttämenetelmillä. Suon sisäisen vaihtelun kattaviin sekä alueellisiin, kansallisiin ja kansainvälisiin seurantoihin tarvitaan soveltuvampia menetelmiä. Tässä väitöskirjassa kootaan kaukokartoitusmenetelmiä maanpinnan peitteen sekä veden kulkureittien ja suon pintakosteuden tarkastelemiseen. Lisäksi maanpinnan korkeusaseman muutosten vaikutuksia suon hydrologialle demonstroitiin kahdeksalla tutkimuskohteella. Turvepelloilla testattiin menetelmää, joka osoitti turvemaiden painumisen aiheuttaneen viereisen joen vuotuisen tulvan peittämän alueen laajentuneen 101–194 % kuluneiden 24–51 vuoden aikana. Metsätaloutta varten ojitetuilla soilla puolestaan todettiin topografisten virtauskertymien ja märkyysindeksien avulla ennallistamisen lisänneen tutkimusalueiden keskimääräistä märkyyttä 2.9–6.9 % sekä pienentäneen sen vaihteluväliä 13–15 % 1–10 kk aikana ennallistamisen jälkeen. Testatut menetelmät tähdensivät topografian merkitystä hydrologisten olosuhteiden määräytymisessä. Kaukokartoitus soveltuu hyvin soiden tilan seurantaan ja sillä saadaan tuotettua kattavia tarkan resoluution aineistoja. Kuhunkin menetelmään kuitenkin liittyy omat tekniset haasteensa ja kehitystarpeensa, ja kenttämittauksia tarvitaan myös jatkossa kaukokartoitusaineistojen ja -analyysien tukena. Aineistojen tuottaminen voi olla työlästä ja vaatia lisä

In Northern Finland, the most significant land use challenges are related to bioenergy production from peat extraction and forest biomass. Increasing societal demand for bioenergy may increase production rates. However, environmental impacts of peat extraction are of increasing concern, which has led to a decline in production, thereby freeing up these areas for other uses. Using storylines for different societal futures and process-based models (PERSiST and INCA), we simulated the effect of simultaneous land use change and climate change on water quality (phosphorus, nitrogen and suspended sediments concentration). Conversion of peat extraction areas to arable land, together with climate change, may pose a risk for deterioration of ecological status. On the other hand, continuous forestry may have positive impacts on water quality. Suspended sediment concentrations in the river do not exceed water quality requirements for salmonids, but nitrogen concentrations may exceed threshold values especially during high flows. A storyline emphasizing sustainable development in energy production led to the best outcome in terms of water protection.

A negative effect of hydropower on river environment includes rapid changes in flow and habitat conditions. Any sudden flow change could force fish to move towards a refuge area in a short period of time, causing serious disturbances in the life cycle of the fish. A probability-based model was developed to quantify the impact of hydropeaking on habitat suitability for two fish species, brown trout (Salamo trutta) and Grayling (Thymallus thymallus). The model used habitat preference curves, river velocity and depth to develop the suitability maps. The suitability maps reveal that habitat suitability deteriorates as flow increases in the studied part of the river. The probability model showed that, on average, suitability indices are higher for adult grayling than juvenile trout in hydropeaking events in this part of the river. The method developed shows the potential to be used in river management and the evaluation of hydropeaking impacts in river systems affected by hydropower.

The water table and its dynamics are one of the key variables that control peatland greenhouse gas exchange. Here, we tested the applicability of the Optical TRApezoid Model (OPTRAM) to monitor the temporal fluctuations in water table over intact, restored (previously forestry-drained), and drained (under agriculture) northern peatlands in Finland, Estonia, Sweden, Canada, and the USA. More specifically, we studied the potential and limitations of OPTRAM using water table data from 2018 through 2021, across 53 northern peatland sites, i.e., covering the largest geographical extent used in OPTRAM studies so far. For this, we calculated OPTRAM based on Sentinel-2 data with the Google Earth Engine cloud platform. First, we found that the choice of vegetation index utilised in OPTRAM does not significantly affect OPTRAM performance in peatlands. Second, we revealed that the tree cover density is a major factor controlling the sensitivity of OPTRAM to water table dynamics in peatlands. Tree cover density greater than 50% led to a clear decrease in OPTRAM performance. Finally, we demonstrated that the relationship between water table and OPTRAM often disappears when WT deepens (ranging between 0 to −100 cm, depending on the site location). We identified that the water table where OPTRAM ceases to be sensitive to variations is highly site-specific. Overall, our results support the application of OPTRAM to monitor water table dynamics in intact and restored northern peatlands with low tree cover density (below 50%) when the water table varies from shallow to moderately deep. Our study makes significant steps towards the broader implementation of optical remote sensing data for monitoring peatlands subsurface moisture conditions over the northern region.

This article explores the forecasting capabilities of three classic linear and nonlinear autoregressive modeling techniques and proposes a new ensemble evolutionary time series approach to model and forecast daily dynamics in stream dissolved organic carbon (DOC). The model used data from the Oulankajoki River basin, a boreal catchment in Northern Finland. The models that were evolved used both accuracy and parsimony measures including autoregressive (AR), vector autoregressive (VAR), and self-exciting threshold autoregressive (SETAR). The new method, called genetic-based SETAR (GTAR), evolved through the integration of state-of-the-art genetic programming with SETAR. To develop the models, high-resolution DOC concentration and daily streamflow (as the external input for VAR) were measured at the same gauging station throughout the ice free season. The results showed that all the models characterize the DOC dynamics with an acceptable 1-day-ahead forecasting accuracy. Use of the streamflow time series as an exogenous variable did not increase the predictive accuracy of AR models. Moreover, the hybrid GTAR provided the best accuracy for the holdout testing data and proved to be a suitable approach for predicting DOC in boreal conditions.

The Nordic Bioeconomy Pathways (NBPs), conceptualized subsets of Shared Socioeconomic Pathways varying from environmentally friendly to open-market competition scenarios, can lead to plausible stressors in future for using bioresources. This study analysed the impacts of NBPs on hydrology and water quality based on two different land system management attributes: management strategy and a combination of reduced stand management and biomass removal at a catchment-scale projection. To understand the potential impacts of NBPs, the Simojoki catchment in northern Finland was chosen, as the catchment mainly covered peatland forestry. The analysis integrated a stakeholder-driven questionnaire, the Finnish Forest dynamics model, and Soil and Water Assessment Tool to build NBP scenarios, including Greenhouse gas emission pathways, for multiple management attributes to simulate flows, nutrients, and suspended solids (SS). For the catchment management strategy, an annual decrease in nutrients was observed for sustainability and business-as-usual scenarios. Reduced stand management and biomass removal also led to decreased export of nutrients and SS for the same scenarios, whereas, in other NBPs, the export of nutrients and SS increased with decreased evapotranspiration. Although the study was investigated at a local scale, based on the current political and socioeconomic situation, the approach used in this study can be outscaled to assess the use of forest and other bioresources in similar catchments.

Peatlands have been degrading globally, which is increasing pressure on restoration measures and monitoring. New monitoring methods are needed because traditional methods are time-consuming, typically lack a spatial aspect, and are sometimes even impossible to execute in practice. Remote sensing has been implemented to monitor hydrological patterns and restoration impacts, but there is a lack of studies that combine multi-sensor ultra-high-resolution data to assess the spatial patterns of hydrology in peatlands. We combine optical, thermal, and topographic unmanned aerial vehicle data to spatially model the water table level (WTL) in unditched open peatlands in northern Finland suffering from adjacent drainage. We predict the WTL with a linear regression model with a moderate fit and accuracy (R2 = 0.69, RMSE = 3.85 cm) and construct maps to assess the spatial success of restoration. We demonstrate that thermal-optical trapezoid-based wetness models and optical bands are strongly correlated with the WTL, but topography-based wetness indices do not. We suggest that the developed method could be used for quantitative restoration assessment, but before-after restoration imagery is required to verify our findings.

Detailed information on seasonal snow cover and depth is essential to the understanding of snow processes, to operational forecasting, and as input for hydrological models. Recent advances in uncrewed or unmanned aircraft systems (UASs) and structure from motion (SfM) techniques have enabled low-cost monitoring of spatial snow depth distribution in resolutions of up to a few centimeters. Here, we study the spatiotemporal variability in snow depth and interactions between snow and vegetation in different subarctic landscapes consisting of a mosaic of conifer forest, mixed forest, transitional woodland/shrub, and peatland areas. To determine the spatiotemporal variability in snow depth, we used high-resolution (50 cm) snow depth maps generated from repeated UAS–SfM surveys in the winter of 2018/2019 and a snow-free bare-ground survey after snowmelt. Due to poor subcanopy penetration with the UAS–SfM method, tree masks were utilized to remove canopy areas and the area (36 cm) immediately next to the canopy before analysis. Snow depth maps were compared to the in situ snow course and a single-point continuous ultrasonic snow depth measurement. Based on the results, the difference between the UAS–SfM survey median snow depth and single-point measurement increased for all land cover types during the snow season, from +5 cm at the beginning of the accumulation to −16 cm in coniferous forests and −32 cm in peatland during the melt period. This highlights the poor representation of point measurements in selected locations even on the subcatchment scale. The high-resolution snow depth maps agreed well with the snow course measurement, but the spatial extent and resolution of maps were substantially higher. The snow depth range (5th–95th percentiles) within different land cover types increased from 17 to 42 cm in peatlands and from 33 to 49 cm in the coniferous forest from the beginning of the snow accumulation to the melt period. Both the median snow depth and its ra

Arctic charr is one of the fish species most sensitive to climate change but studies on their freshwater habitat preferences are limited, especially in the fluvial environment. Machine learning methods offer automatic and objective models for ecohydrological processes based on observed data. However, i) the number of ecological records is often much smaller than hydrological observations, and ii) ecological measurements over the long-term are costly. Consequently, ecohydrological datasets are scarce and imbalanced. To address these problems, we propose jittered binary genetic programming (JBGP) to detect the most dominant ecohydrological parameters affecting the occurrence of Arctic charr across tributaries within the large subarctic Teno River catchment, in northernmost Finland and Norway. We quantitatively assessed the accuracy of the proposed model and compared its performance with that of classic genetic programming (GP), decision tree (DT) and state-of-the-art jittered-DT methods. The JBGP achieves the highest total classification accuracy of 90% and a Heidke skill score of 78%, showing its superiority over its counterparts. Our results showed that the dominant factors contributing to the presence of Arctic charr in Teno River tributaries include i) a higher density of macroinvertebrates, ii) a lower percentage of mires in the catchment and iii) a milder stream channel slope.

Hydropower operation optimization in river systems involves market prices, technological constraints affecting the efficiency of turbines, and flow constraints set by an environmental regulator. Comprehensive environmental flow regulation includes the ecological state of a river system and the impact on hydropower value. This article studies the impacts of environmental constraints on hydropower value under varying electricity price volatility scenarios. The effects of maximum flow, minimum flow, and flow ramping constraints are studied analytically and quantitatively. We frame the lost hydropower value as the economic cost of these constraints. We show that the economic costs of the environmental constraints decrease with lower price volatility. We use a marginal cost and marginal benefit framework to illustrate that the optimal flow constraint should be tightened if the price volatility decreases in the electricity market. Our approach illustrates how electricity price volatility influences the analysis of optimal environmental constraints in regulated river systems. Finally, we analyse the effect of different environmental flow release options in fishways on the economic cost of a fishway. If the hydropower operator can optimize the fishway flow allocation, then the loss in hydropower value is lower than under a constant fishway flow.

This paper reviews the current GeoAI and machine learning applications in hydrological and hydraulic modeling, hydrological optimization problems, water quality modeling, and fluvial geomorphic and morphodynamic mapping. GeoAI effectively harnesses the vast amount of spatial and non-spatial data collected with the new automatic technologies. The fast development of GeoAI provides multiple methods and techniques, although it also makes comparisons between different methods challenging. Overall, selecting a particular GeoAI method depends on the application’s objective, data availability, and user expertise. GeoAI has shown advantages in non-linear modeling, computational efficiency, integration of multiple data sources, high accurate prediction capability, and the unraveling of new hydrological patterns and processes. A major drawback in most GeoAI models is the adequate model setting and low physical interpretability, explainability, and model generalization. The most recent research on hydrological GeoAI has focused on integrating the physical-based models’ principles with the GeoAI methods and on the progress towards autonomous prediction and forecasting systems.

Aapa mires are boreal peatland complexes comprised of wet, typically patterned fens in the center and Sphagnum bog vegetation at the margins. Their distribution is controlled by climate and local catchment hydrology. The daily discharge of twelve aapa mires across the boreal zone was explored for 1961–2099, with the CPIsnow model using observational weather data and projections based on climate models (CMIP5) and emission scenarios (RCP4.5 and RCP8.5). Mire hydrology was assessed for climate-zonal differences, seasonal patterns, and longer-term trends. The results indicated past and future changes in hydrology, particularly related to the duration and magnitude of snow cover and the timing of snowmelt. Increasing winter discharge and decreasing spring discharge were detected in recent past in the southern sites, and these trends were indicated to continue in the future throughout the study area. By the end of the 21st century, the typical seasonality of discharge is indicated to weaken throughout the study area and to largely disappear in the south boreal catchments. In the northernmost sites, a mismatch between past trends and future projections of spring discharge was discovered, indicating complexity and uncertainty of snow process modeling. The hydrological changes indicated in this study, together with direct impacts of increasing temperatures, threaten aapa mires, affecting biodiversity and greenhouse gas balance. In changing climate, special attention should be paid to winter conditions and snow, essential for the hydrological cycle in the north but under-explored in mire hydrology studies.

Environmental impacts from intensive draining and land use in tropical peatlands urge the need for ecosystem protection and peatland restoration. However, our understanding of tropical peatlands is too poor to support the implementation of such mitigation initiatives. We carried out environmental monitoring on Padang Island, Indonesia, which suffers from peatland degradation and forest disturbances that is representative of peatlands across Southeast Asia. The main environmental parameters of hydrology (water-table depth (WTD), rainfall), micrometeorology (radiation, air temperature, and relative humidity), and tree physiologies (sap-flux velocity, radial growth) of several native and one non-native species were recorded by ground sensors, while forest disturbances were monitored using remote sensing. We found out that the spatial and temporal variability in WTD was high, which was mainly controlled by rainfall and the presence of drainage. The response of vegetations to the temporal change in WTD varied based on response parameters and species groups, native versus non-native species. Vapor pressure deficit and photosynthetic active radiation had a profound effect toward temporal variation in sap-flux velocity, while the effect of wind speed was only found in some species. Non-linear relationships between sap-flux velocity and WTD were observed, regardless of the species groups. Sap-flux velocity was slightly higher during transitional WTD, -1.0 to -1.4 m below the ground. The radial growth of non-native species tended to drop with a deeper WTD, while growth of native species did not show a similar trend. We also observed a weak-to-moderate inverse linear relationship between daily radial growth and daily sap-flux velocity. Peatland draining and land use were strongly intertwined with forest disturbances. Up to one third of the island had been deforested for non-native monoculture plantation which was associated with intensive drainages, and another one th, Tiivistelmä Trooppisten turvemaiden ojitusten ympäristövaikutukset lisäävät tarvetta ekosysteemien suojelun ja soiden ennallistamisen lisäämistä. Ymmärrys trooppisten turvemaiden prosesseista on kuitenkin vielä liian vähäistä tätä toimintaa tukemaan. Tutkimuksessa suoritettiin ympäristön tilan seurantaa Indonesiassa Padang Islandin tutkimuskohteella, joka kärsii turpeen ja metsän häiriintymisestä, mikä on tyypillistä Kaakkois-Aasian turvemaille. Tutkimuksessa kerättiin maasensoreilla aineistoa keskeisimmistä ympäristön tilasta kertovista parametreista hydrologiassa (vesisyvyys (WTD), sadanta), mikrometeorologiassa (säteily, ilman lämpötila, suhteellinen kosteus) ja puuston fysiologiassa (mahlan virtausnopeus, säteen kasvu), kun taas metsän häiriintyneisyyttä seurattiin kaukokartoituksen avulla. Tutkimuksessa havaittiin korkeaa spatiaalista ja ajallista vaihtelua WTD:ssä riippuen pääasiassa sadannasta ja kuivatustilanteesta. Kasvillisuuden vaste WTD:n ajalliseen muutokseen vaihteli riippuen vasteparametristä ja lajiryhmästä (paikallinen/ei-paikallinen puulaji). Höyrynpaineen alijäämällä ja fotosynteettisesti aktiivisella säteilyllä oli merkittävä vaikutus mahlan virtausnopeuden ajalliseen vaihteluun, kun taas tuulennopeus vaikutti vain joihinkin lajeihin. Mahlan virtausnopeuden ja WTD:n välillä havaittiin epälineaarisia vuorovaikutuksia riippumatta puulajista. Mahlan virtausnopeus oli hiukan suurempi keskitason WTD:llä -1.0–1.4 m. Ei-paikallisten lajien säteen kasvu yleensä väheni suurilla WTD:llä, kun taas paikallisille lajeille ei löydetty samanlaista trendiä. Lisäksi ei-paikallisen puulajin päiväkohtaisen säteen kasvun ja mahlan virtausnopeuden välille löydettiin heikko–kohtalainen negatiivinen lineaarinen riippuvuus. Soiden ojitus ja maankäyttö kietoutuivat voimakkaasti yhteen metsän häiriintyneisyyden kanssa. Jopa kolmasosa saaren metsistä oli hävinnyt ei-paikallisten puulajien monokulttuurisen kasvatuksen myötä, mikä yhdistettiin voimakkaan kuivatukseen. Lisäks

Peatland restoration aims to achieve pristine water pathway conditions to recover dispersed wetness, water quality, biodiversity and carbon sequestration. Restoration monitoring needs new methods for understanding the spatial effects of restoration in peatlands. We introduce an approach using high-resolution data produced with an unmanned aircraft system (UAS) and supported by the available light detection and ranging (LiDAR) data to reveal the hydrological impacts of elevation changes in peatlands due to restoration. The impacts were assessed by analyzing flow accumulation and the SAGA Wetness Index (SWI). UAS campaigns were implemented at two boreal minerotrophic peatland sites in degraded and restored states. Simultaneously, the control campaigns mapped pristine sites to reveal the method sensitivity of external factors. The results revealed that the data accuracy is sufficient for describing the primary elevation changes caused by excavation. The cell-wise root mean square error in elevation was on average 48 mm when two pristine UAS campaigns were compared with each other, and 98 mm when each UAS campaign was compared with the LiDAR data. Furthermore, spatial patterns of more subtle peat swelling and subsidence were found. The restorations were assessed as successful, as dispersing the flows increased the mean wetness by 2.9–6.9%, while the absolute changes at the pristine sites were 0.4–2.4%. The wetness also became more evenly distributed as the standard deviation decreased by 13–15% (a 3.1–3.6% change for pristine). The total length of the main flow routes increased by 25–37% (a 3.1–8.1% change for pristine), representing the increased dispersion and convolution of flow. The validity of the method was supported by the field-determined soil water content (SWC), which showed a statistically significant correlation (R² = 0.26–0.42) for the restoration sites but not for the control sites, possibly due to their upslope catchment areas being too small. De

In northern regions, like Finland, peak river discharge is principally controlled by maximum snowmelt runoff during spring (March–May). Global warming and climate change extensively influence both the quantity and temporal characteristics of peak discharge in northern rivers by altering snowpack accumulation and melt processes. This study analyzed peak spring flood discharge (PSFD) magnitude (PSFDM) and timing (PSFDT) in four natural rivers (Simojoki, Kuivajoki, Kiiminkijoki, and Temmesjoki) across northern Finland, in terms of long-term (1967–2011) variability, trends, and links to large-scale climate teleconnections. The PSFDM significantly (p < 0.05) declined in the Simojoki, Kuivajoki, and Kiiminkijoki rivers over time. Both the Simojoki and Kuivajoki rivers also experienced significant decreasing trends of about −0.33 and −0.3 (days year−1), respectively, in the PSFDT during 1967–2011. In these two rivers, the less and earlier PSFDs were principally attributable to the warmer spring seasons positively correlated with the North Atlantic Oscillation (NAO) in recent decades. Moreover, daily precipitation time series corresponding to the PSFD events showed no considerable effects on PSFDM and PSFDT changes in all the natural rivers studied. This suggests that less and earlier historical PSFDs in natural rivers at higher latitudes in northern Finland were primarily induced by warmer springtime temperatures influencing snowpack dynamics.

New tools are needed to evaluate the impacts of short-term hydropower regulation practices on downstream river systems and to progress towards sustainable river-flow management. As hydropower is increasingly being used to balance the energy load deficit caused by other less flexible sources, sub-daily flow conditions across many regulated river (RR) systems are changing. To address this, we used wavelet analyses to quantify the discharge variability in RRs and categorized the level of variability based on the conditions in natural free-flowing rivers. The presented framework used the definition of fluvial connectivity (Grill et al., 2019) to identify free-flowing rivers used in the study. We tested the developed framework in 12 different RRs in Finland and found higher overall averaged subdaily variations, with up to 20 times larger variability than natural conditions. A large, highly regulated Finnish river system was found to have the highest sub-daily variations in winter, while smaller RRs with lower levels of regulation the highest variations in summer. The proposed framework offers a novel tool for sustainable river management and can be easily applied to various rivers and regions globally. It had flexibility to analyze sub-daily variations in desired seasonal or other ecologically sensitive periods.

The off-site effects of agricultural organic soils include the leaching of N, P, and organic carbon (OC) to watercourses and CO₂, CH₄, and N₂O emissions into the atmosphere. The aim of this study was to quantify how the thickness of organic layers affects these loads. A 19.56-ha experimental field drained by subsurface pipes was established in Ruukki, northwestern Finland. Three plots had a 60–80 cm-thick sedge peat layer and three others had a thickness of 20 cm or less. The drainage pipes lie in mineral soil that, in this field, contains sulfidic material. This study documents the experimental settings and reports on the leaching of substances in the first two years, as well as CO₂, CH₄ and N₂O emissions during eight weeks in one summer. Total N (TN) and OC loads were higher from the thicker peat plots. The mean TN loads during a hydrological year were 15.4 and 9.2 kg ha⁻¹ from the thicker and thinner peat plots, respectively, with organic N representing 36% of TN load. Total P (TP) load averaged 0.27 kg ha⁻¹ yr⁻¹. Dissolved P load represented 63 and 36% of TP in the thicker peat area and only 23 and 13% in the thinner peat area, and was thus increased upon peat thickness. These N and P loads through the subsurface drainage system represented roughly 83% of TN and 64% of TP loads from this field. There were no clear differences in greenhouse gas emissions among the plots during the eight-week monitoring period. Slowly oxidizing sulfide in the subsoil resulted in annual leaching of 147 kg S ha⁻¹, almost ten times that of non-sulfidic soils. Our first results emphasize the effect of the peat thickness on the leaching of substances and warn about considering all organic soils as a single group in environmental assessments.

Genetic programming (GP) is an evolutionary regression method that has received considerable interest to model hydro-environmental phenomena recently. Considering the sparseness of hydro-meteorological stations on northern areas, this study investigates the benefits and downfalls of univariate streamflow modeling at high latitudes using GP and seasonal autoregressive integrated moving average (SARIMA). Furthermore, a new evolutionary time series model, called GP-SARIMA, is introduced to enhance streamflow forecasting accuracy at long-term horizons in a lake-river system. The paper includes testing the new model for one-step-ahead forecasts of daily mean, weekly mean, and monthly mean streamflow in the headwaters of the Oulujoki River, Finland. The results showed that a combination of correlogram and average mutual information (AMI) analysis might yield in the selection of the optimum lags that are needed to be used as the predictors of streamflow models. With Nash-Sutcliffe efficiency values of more than 99%, both GP and SARIMA models exhibited good performance for daily streamflow prediction. However, they were not able to precisely model the intramonthly snow water equivalent in the long-term forecast. The proposed ensemble model, which integrates the best GP and SARIMA models with the most efficient predictor, may eliminate one-fourth of root mean squared errors of standalone models. The GP-SARIMA also showed up to three times improvement in the accuracy of the standalone models based on the Nash-Sutcliff efficiency measure.

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination ( R2 ) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.

The Arctic’s winter water cycle is rapidly changing, with implications for snow moisture sources and transport processes. Stable isotope values (δ¹⁸O, δ²H, d-excess) of the Arctic snowpack have potential to provide proxy records of these processes, yet it is unclear how well the isotope values of individual snowfall events are preserved within snow profiles. Here, we present water isotope data from multiple taiga and tundra snow profiles sampled in Arctic Alaska and Finland, respectively, during winter 2018–2019. We compare the snowpack isotope stratigraphy with meteoric water isotopes (vapor and precipitation) during snowfall days, and combine our measurements with satellite observations and reanalysis data. Our analyses indicate that synoptic-scale atmospheric circulation and regional sea ice coverage are key drivers of the source, amount, and isotopic composition of Arctic snowpacks. We find that the western Arctic tundra snowpack profiles in Alaska preserved the isotope values for the most recent storm; however, post depositional processes modified the remaining isotope profiles. The overall seasonal evolution in the vapor isotope values were better preserved in taiga snow isotope profiles in the eastern Arctic, where there is significantly less wind-driven redistribution than in the open Alaskan tundra. We demonstrate the potential of the seasonal snowpack to provide a useful proxy for Arctic winter-time moisture sources and propose future analyses.

In agricultural catchments, hydrological processes are highly linked to particle and nutrient loss and can lead to a degradation of the ecological status of the water. Global warming and land use changes influence the hydrological regime. This effect is especially strong in cold regions. In this study, we used long-term hydrological monitoring data (22–26 years) from small agricultural catchments in Norway. We applied a Mann–Kendall trend and wavelet coherence analysis to detect annual and seasonal changes and to evaluate the coupling between runoff, climate, and water sources. The trend analysis showed a significant increase in the annual and seasonal mean air temperature. In all sites, hydrological changes were more difficult to detect. Discharge increased in autumn and winter, but this trend did not hold for all catchments. We found a strong coherence between discharge and precipitation, between discharge and snow water equivalent and discharge and soil water storage capacity. We detected different hydrological regimes of rain and snow-dominated catchments. The catchments responded differently to changes due to their location and inherent characteristics. Our results highlight the importance of studying local annual and seasonal changes in hydrological regimes to understand the effect of climate and the importance for site-specific management plans.

Restoration and water table control on peatlands to limit fire risk are national priorities in Indonesia. The present study was initiated at Padang Island, Sumatra, to increase understanding on peatland hydrology in the tropic. At the pilot site, water table and precipitation were monitored at different stations. The results show variation in water table depths (WTDs) over time and space due to spatial and temporal variability in rain intensity and drainage networks. In part of the island, large-scale drainage for plantations led to deep WTD (−1.8 m) and high WTD recession rates (up to 3.5 cm/day). Around villages, farm-scale drainages had a smaller impact with a lower recession rate (up to 1.8 cm/day) and shallow WTD, typically below −0.4 m, the threshold for sustainable peatland management in Indonesia. The recession rates levelled off at 1.0 cm/day near the drained forest/plantation and at 0.5 cm/day near the farm. Deeper layers had much lower specific yield (Sy), 0.1 at −1.5 m depth, compared with top peat soils with Sy up to 0.3. Proximity to drainages extended discharge flow to deeper layers. The results highlighted the severity of peatland drainage impact on most coastal zones of Padang Island, which have intensive drainage networks.

Snow conditions in the boreal region are changing, mainly due to climate change. Snowmelt impacts catchment water storage conditions and streamflow through spring and early summer, and thus drastic changes in hydrological conditions are expected, especially in headwaters. The measurement of snow cover variability in the catchment scale is a challenge using current techniques, and the connections between catchment characteristics, climate conditions, and hydrology are still not completely understood. This thesis aims to develop and test new robust and cost-efficient observation methods to quantify and analyze snow cover variability and improve understanding of the factors controlling snow hydrology in the boreal landscape. This work applies two approaches for measuring snow cover: in-situ, using low-cost temperature loggers; and remote sensing, using unmanned aerial systems with Structure-from-Motion (UAS-SfM). The high temporal-resolution data from temperature loggers, with the algorithm developed, provided relatively reliable and accurate data on spatiotemporal variations in snow cover ablation and melt rates in different boreal landcover types. The UAS-SfM method captured the snow depth variability in the boreal landscape throughout the snow season with a very high spatial resolution with a larger coverage area, enabling the identification of multiple snow processes and interactions between snow and vegetation. To analyze the factors controlling snow hydrology, data from a spatially well-represented Finnish small-basing research network was used to calculate low flows and catchment storage indices using the recession analysis method. The findings suggest that the changes in summer low flow related to snow conditions will be pronounced in certain snow-to-precipitation ratio thresholds in a warming climate, highlighting the strong connection between ecologically important summer low flows and snow conditions. The developed measurement methods can be used in, Tiivistelmä Pohjoiset lumiolosuhteet ovat muuttumassa erityisesti ilmastonmuutoksen takia. Lumen sulanta vaikuttaa valuma-alueiden vesivarastoihin ja virtaamiin keväällä ja alkukesästä, ja hydrologisten olosuhteiden odotetaan muuttuvan rajusti erityisesti latvavesistössä. Lumipeitteen vaihtelun mittaaminen valuma-alueilla on nykyisillä menetelmillä haastavaa ja tiedot valuma-aluetekijöiden, ilmasto-olosuhteiden ja hydrologisten olosuhteiden välisistä yhteyksistä ovat puutteellisia. Tässä työssä kehitetään ja testataan uusia kustannustehokkaita havaintomenetelmiä lumipeitteen vaihtelun mittaamiseen ja analysointiin sekä pyritään parantamaan ymmärrystä lumihydrologiaa ohjaavista tekijöistä pohjoisilla alueilla. Lumipeitteen mittausta lähestytään maastohavainnoin käyttämällä kustannustehokkaita lämpötila-antureita ja kaukokartoituksen avulla käyttäen miehittämättömiä lennokkeja yhdessä Structure-from-Motion (UAS-SfM) fotogrammetrian kanssa. Lämpötila-antureilla mitatun korkean resoluution datan ja kehitetyn algoritmin avulla saatiin suhteellisen tarkkaa tietoa lumen prosessien vaihteluista pohjoisilla maastotyypeillä. UAS-SfM menetelmällä lumen syvyyden alueellinen vaihtelu määritettiin erittäin suurella resoluutiolla kattaen suuremman alueen, joka mahdollisti useiden lumen prosessien sekä lumen ja kasvillisuuden vuorovaikutusten tunnistamisen. Lumihydrologiaa ohjaavien tekijöiden selvittämiseen käytettiin alueellisesti hyvin jakautuneiden Suomen pienvaluma-alueiden dataa, josta laskettiin alivirtaamat, ja vesivarastoindeksejä käyttäen resessioanalyysiä. Tulokset viittasivat lämpenevässä ilmastossa muuttuvien lumiolosuhteiden vaikuttavan kesän alivirtaamiin erityisen voimakkaasti alueilla, joissa lumen osuus vuosittaisesta kokonaissadannasta on tietyllä kynnyksellä, korostaen ekologisesti tärkeiden kesän alivirtaamien ja lumiolosuhteiden voimakasta yhteyttä. Työssä testattuja ja kehitettyjä mittausmenetelmiä voidaan käyttää lumipeitteen vaihtelun määrittämiseen etäisil

Lake water level fluctuation is a function of hydro-meteorological components, namely input, and output to the system. The combination of these components from in-situ and remote sensing sources has been used in this study to define multiple scenarios, which are the major explanatory pathways to assess lake water levels. The goal is to analyze each scenario through the application of the water balance equation to simulate lake water levels. The largest lake in Iran, Lake Urmia, has been selected in this study as it needs a great deal of attention in terms of water management issues. We ran a monthly water balance simulation of nineteen scenarios for Lake Urmia from 2003 to 2007 by applying different combinations of data, including observed and remotely sensed water level, flow, evaporation, and rainfall. We used readily available water level data from Hydrosat, Hydroweb, and DAHITI platforms; evapotranspiration from MODIS and rainfall from TRMM. The analysis suggests that the consideration of field data in the algorithm as the initial water level can reproduce the fluctuation of Lake Urmia water level in the best way. The scenario that combines in-situ meteorological components is the closest match to the observed water level of Lake Urmia. Almost all scenarios showed good dynamics with the field water level, but we found that nine out of nineteen scenarios did not vary significantly in terms of dynamics. The results also reveal that, even without any field data, the proposed scenario, which consists entirely of remote sensing components, is capable of estimating water level fluctuation in a lake. The analysis also explains the necessity of using proper data sources to act on water regulations and managerial decisions to understand the temporal phenomenon not only for Lake Urmia but also for other lakes in semi-arid regions.

Peatlands worldwide are being threatened by intensive land use and drainage, which leads to soil subsidence. This has consequences for farming, especially on low-gradient cultivated peat-dominated lowlands with high flood risk. In this study, we combined historical soil elevation data and new lidar data to improve the estimation of subsidence and its consequences for lowland river systems. The results showed 202−349 mm subsidence within the last 24–51 years, with a mean rate of 5.15–9.47 mm y⁻¹ for riparian peatland on the west coast of Finland. The subsidence rate was partly explained by the depth of the organic soil layer (R² = 0.710, p > 0.05). The results also showed that increasing flooding of cultivated fields is mainly due to soil subsidence, not to increased flooding occurrence in river systems. The area flooded annually was found to increase by 101–194 % for the last 24–51 years, due to soil subsidence near rivers. Generalization of the results to catchment scale indicated an increase in the annual flood zone of 45 % in cultivated fields in one of two study catchments (Siikajoki river basin). These results demonstrate the value of using historical data to study soil subsidence and confirm that the risk of flooding increases in cultivated organic lowlands due to intensive drainage and subsidence. New management strategies, such as peatland rewetting, restoration, and paludiculture, should be considered in future land use plans to reduce subsidence and provide new income streams for farmers.

Spatiotemporal information on historical peatland drainage is needed to relate past land use to observed changes in catchment hydrology. Comprehensive knowledge of historical development of peatland management is largely unknown at the catchment scale. Aerial photos and light detection and ranging (LIDAR) data enlarge the possibilities for identifying past peatland drainage patterns. Here, our objectives are (1) to develop techniques for semiautomatically mapping the location of ditch networks in peat-dominated catchments using aerial photos and LIDAR data, and (2) to generate time series of drainage networks. Our approaches provide open-access techniques to systematically map ditches in peat-dominated catchments through time. We focused on the algorithm in such a way that we can identify the ditch networks from raw aerial images and LIDAR data based on the modification of multiple filters and number of threshold values. Such data are needed to relate spatiotemporal drainage patterns to observed changes in many northern rivers. We demonstrate our approach using data from the Simojoki River catchment (3,160 km²) in northern Finland. The catchment is dominated by forests and peatlands that were almost all drained after 1960. For two representative locations in cultivated peatland (downstream) and peatland forest (upstream) areas of the catchment; we found total ditch length density (km/km²), estimated from aerial images and LIDAR data based on our proposed algorithm, to have varied from 2% to 50% compared with the monitored ditch length available from the National Land survey of Finland (NLSF) in 2018. A different pattern of source variation in ditch network density was observed for whole-catchment estimates and for the available drained-peatland database from Natural Resources Institute Finland (LUKE). Despite such differences, no significant differences were found using the nonparametric Mann-Whitney U test with a 0.05 significance level based on the sampl

Increased nutrient and soil losses from agricultural areas into water bodies constitute a global problem. Phosphorus is one of the main nutrients causing eutrophication in surface waters. In arable land, phosphorus losses are closely linked to sediment losses. Therefore, a better understanding of the sediment-runoff processes in agricultural areas is a key to reduce the eutrophication impacts and to implement mitigation measures. The objectives of this study were to identify dominant sediment runoff processes in cultivated grain-dominated catchments in a cold climate. We assessed continuous high-resolution turbidity data, temporal and spatial catchment properties and agricultural management data to describe and get a better understanding of the cause-relationship of sediment transfer in two small agricultural dominated catchments in southern Norway. The concentration-discharge pattern, index of connectivity and agricultural activities were considered with the wider aim to establish a link between field and catchment scale. The results showed that the dominant concentration-discharge pattern was a clockwise concentration-discharge (c-q) hysteresis in both catchments indicating that areas close to or in the stream gave the highest contribution to turbidity. The main driver for turbidity was discharge, though soil water storage capacity, rain intensity and former discharge events also played a role. Intensity of soil tillage and index of connectivity (likelihood of water and particles to be transported to the stream) impacted the c-q hysteresis index. Little vegetation cover and high intensity of soil tillage led to a high hysteresis index, which indicates a quick increase in turbidity following increased discharge. Other links between agricultural management and in stream data were difficult to interpret. The findings of this study provide information about discharge, field operations and vegetational status as drivers for turbidity and about the spatial dist

Maintaining and improving surface water quality requires knowledge of nutrient and sediment loads due to past and future land-use practices, but historical data on land cover and its changes are often lacking. In this study, we tested whether land-use-specific export coefficients can be used together with satellite images (Landsat) and/or regional land-use statistics to estimate riverine nutrient loads and concentrations of total nitrogen (TN), total phosphorus (TP), and suspended solids (SS). The study area, Simojoki (3160 km²) in northern Finland, has been intensively drained for peatland forestry since the 1960s. We used different approaches at multiple sub-catchment scales to simulate TN, TP, and SS export in the Simojoki catchment. The uncertainty in estimates based on specific export coefficients was quantified based on historical land-use changes (derived from Landsat data), and an uncertainty boundary was established for each land-use. The uncertainty boundary captured at least 60% of measured values of TN, TP, and SS loads or concentrations. However, the uncertainty in estimates compared with measured values ranged from 7% to 20% for TN, 0% to 18% for TP, and 13% to 43% for SS for different catchments. Some discrepancy between predicted and measured loads and concentrations was expected, as the method did not account for inter-annual variability in hydrological conditions or river processes. However, combining historical land-use change estimates with simple export coefficients can be a practical approach for evaluating the influence on water quality of historical land-use changes such as peatland drainage for forest establishment.

Degradation of freshwater ecosystems requires efficient tools for assessing the ecological status of freshwater biota and identifying potential cause(s) for their biological degradation. While diatoms and macroinvertebrates are widely used in stream bioassessment, the potential utility of microbial communities has not been fully harnessed. Using data from 113 Finnish streams, we assessed the performance of aquatic leaf-associated fungal decomposers, relative to benthic macroinvertebrates and diatoms, in modelling-based bioassessment. We built multi-taxon niche -type predictive models for fungal assemblages by using genus-based and sequence-based identification levels. We then compared the models’ precision and accuracy in the prediction of reference conditions (number of native taxa) to corresponding models for macroinvertebrates and diatoms. Genus-based fungal model nearly equalled the accuracy and precision of our best model (macroinvertebrates), whereas the sequence-based model was less accurate and tended to overestimate the number of taxa. However, when the models were applied to streams disturbed by anthropogenic stressors (nutrient enrichment, sedimentation and acidification), alone or in combination, the sequence-based fungal assemblages were more sensitive than other taxonomic groups, especially when multiple stressors were present. Microbial leaf decomposition rates were elevated in sediment-stressed streams whereas decomposition attributable to leaf-shredding macroinvertebrates was accelerated by nutrients and decelerated by sedimentation. Comparison of leaf decomposition results to model output suggested that leaf decomposition rates do not detect effectively the presence of multiple simultaneous disturbances. The rapid development of global microbial database may soon enable species-level identification of leaf-associated fungi, facilitating a more precise and accurate modelling of reference conditions in streams using fungal communities. This

Agricultural, forestry‐impacted and natural catchments are all vectors of nutrient loading in the Nordic countries. Here, we present concentrations and fluxes of total nitrogen (totN) and phosphorus (totP) from 69 Nordic headwater catchments (Denmark: 12, Finland:18, Norway:17, Sweden:22) between 2000 and 2018. Catchments span the range of Nordic climatic and environmental conditions and include natural sites and sites impacted by agricultural and forest management. Concentrations and fluxes of totN and totP were highest in agricultural catchments, intermediate in forestry‐impacted and lowest in natural catchments, and were positively related %agricultural land cover and summer temperature. Summer temperature may be a proxy for terrestrial productivity, while %agricultural land cover might be a proxy for catchment nutrient inputs. A regional trend analysis showed significant declines in N concentrations and export across agricultural (−15 μg totN L⁻¹ year⁻¹) and natural (−0.4 μg NO₃‐N L⁻¹ year⁻¹) catchments, but individual sites displayed few long‐term trends in concentrations (totN: 22%, totP: 25%) or export (totN: 6%, totP: 9%). Forestry‐impacted sites had a significant decline in totP (−0.1 μg P L⁻¹ year⁻¹). A small but significant increase in totP fluxes (+0.4 kg P km⁻² year⁻¹) from agricultural catchments was found, and countries showed contrasting patterns. Trends in annual concentrations and fluxes of totP and totN could not be explained in a straightforward way by changes in runoff or climate. Explanations for the totN decline include national mitigation measures in agriculture international policy to reduced air pollution and, possibly, large‐scale increases in forest growth. Mitigation to reduce phosphorus appears to be more challenging than for nitrogen. If the green shift entails intensification of agricultural and forest production, new challenges for protection of water quality will emerge possible exacerbated by climate change. Further analys

High latitude peatlands act as globally important carbon (C) sinks and are in constant interaction with the atmosphere. Their C storage formed during the Holocene. In the course of time, the aggregate effect of the C fluxes on radiative forcing (RF) typically changes from warming to cooling, but the timing of this shift varies among different peatlands. Here we investigated Holocene peatland development, including vegetation history, vertical peat growth and the lateral expansion of a patterned subarctic fen in northern Finland by means of multiple sampling points. We modelled the Holocene RF by combining knowledge on past vegetation communities based on plant macrofossil stratigraphies and present in situ C flux measurements. The peatland initiated at ca. 9500 calibrated years Before Present (cal yr BP), and its lateral expansion was greatest between ca. 9000 and 7000 cal yr BP. After the early expansion, vertical peat growth proceeded very differently in different parts of the peatland, regulated by internal and external factors. The pronounced surface microtopography, with high strings and wet flarks, started to form only after ca. 1000 cal yr BP. C accumulation within the peatland recorded a high degree of spatial variability throughout its history, including the recent past. We applied two flux scenarios with different interpretation of the initial peatland development phases to estimate the RF induced by C fluxes of the fen. After ca. 4000 cal yr BP, at the latest, the peatland RF has been negative (cooling), mainly driven by C uptake and biomass production, while methane emissions had a lesser role in the total RF. Interestingly, these scenarios suggest that the greatest cooling effect took place around ca. 1000 cal yr BP, after which the surface microtopography established. The study demonstrated that despite the high spatial heterogeneity and idiosyncratic behaviour of the peatland, the RF of the studied fen followed the general development pattern

Increases in iron (Fe) concentration have been reported in boreal regions in recent decades, raising concerns about the fate of ecosystems along water courses. In this study, the SWAT (Soil and Water Assessment Tool) model was applied to the river Mustijoki catchment in southern Finland to determine the current state of Fe transport and to evaluate possible effects of ongoing environmental change in this agriculture-dominated catchment. The model was calibrated using five-year discharge, suspended solids, and Fe data, and validated with a three-year dataset of the same parameters. Further, the model was run with spatially downscaled and bias-corrected climate change scenario data to the year 2100 obtained using five different global climate models. The results were divided into 20-year time steps (2020–2039, 2040–2059, 2060–2079, 2080–2099) and compared against a reference modeling period (1997–2016). With present catchment characteristics of the river Mustijoki, Fe transport was shown to be related to soil erosion and suspended solids transport, driven by hydrological conditions. Arable fields, especially with steeper slopes, were identified as the most likely source of Fe loading. Climate change-induced alterations in riverine Fe transport were simulated as concentrations and as annual mass fluxes. High Fe transport season is already shifting from spring snowmelt events to autumn and winter, and this change is likely to increase in coming decades. Based on modeling results, annual peak concentration in the River Mustijoki was projected to decrease by up to 32% (from 6.2 mg L⁻¹ to 4.2 mg L⁻¹ in scenarios RCP4.5 and RCP8.5) in the coming 20-year period, while lowest winter concentration was projected to increase by 126% (from 1.5 mg L⁻¹ in the reference period (1997–2016) to 3.5 mg L⁻¹ in 2080–2099 in scenario RCP8.5. To compensate for these changes in Fe transport dynamics, water protection and land use management planning must be improved.

Nordic water bodies face multiple stressors due to human activities, generating diffuse loading and climate change. The ‘green shift’ towards a bio-based economy poses new demands and increased pressure on the environment. Bioeconomy-related pressures consist primarily of more intensive land management to maximise production of biomass. These activities can add considerable nutrient and sediment loads to receiving waters, posing a threat to ecosystem services and good ecological status of surface waters. The potential threats of climate change and the ‘green shift’ highlight the need for improved understanding of catchment-scale water and element fluxes. Here, we assess possible bioeconomy-induced pressures on Nordic catchments and associated impacts on water quality. We suggest measures to protect water quality under the ‘green shift’ and propose ‘road maps’ towards sustainable catchment management. We also identify knowledge gaps and highlight the importance of long-term monitoring data and good models to evaluate changes in water quality, improve understanding of bioeconomy-related impacts, support mitigation measures and maintain ecosystem services.

Optimal nutrient pollution monitoring and management in catchments requires an in-depth understanding of spatial and temporal factors controlling nutrient dynamics. Such an understanding can potentially be obtained by analysing stream concentration–discharge (C-Q) relationships for hysteresis behaviours and export regimes. Here, a classification scheme including nine different C-Q types was applied to a total of 87 Nordic streams draining mini-catchments (0.1–65 km²). The classification applied is based on a combination of stream export behaviour (dilution, constant, enrichment) and hysteresis rotational pattern (clock-wise, no rotation, anti-clockwise). The scheme has been applied to an 8-year data series (2010–2017) from small streams in Denmark, Sweden, and Finland on daily discharge and discrete nutrient concentrations, including nitrate (NO₃⁻), total organic N (TON), dissolved reactive phosphorus (DRP), and particulate phosphorus (PP). The dominant nutrient export regimes were enrichment for NO₃⁻ and constant for TON, DRP, and PP. Nutrient hysteresis patterns were primarily clockwise or no hysteresis. Similarities in types of C-Q relationships were investigated using Principal Component Analysis (PCA) considering effects of catchment size, land use, climate, and dominant soil type. The PCA analysis revealed that land use and air temperature were the dominant factors controlling nutrient C-Q types. Therefore, the nutrient export behaviour in streams draining Nordic mini-catchments seems to be dominantly controlled by their land use characteristics and, to a lesser extent, their climate.

River regimes in Nordic rivers are changing, mainly due to climate change and river regulation. As renewables penetrate the power market, the conventional role of hydropower in energy markets is also changing. These factors are altering river flows in ways that are not fully understood. This thesis addressed these information inadequacies in the ecologically sensitive Nordic region. To assess the relative effect of regulation practices and climate change, a spatio-temporal study of two adjacent rivers in Northern Europe, the Kemijoki (regulated) and Tornionjoki (pristine), with similar climate and catchment conditions, was performed. Degree of hydrologic alteration on Kemijoki was twice than at Tornionjoki, while regulation and climate change seemed to have similar degrees of effect on flow alteration in the Kemijoki (50% each). This was confirmed by analyzing data from Ounasjoki, a pristine tributary of the Kemijoki. Short-term changes in Nordic rivers were quantified using discharge datasets from 150 sites with hourly time-step. The results revealed high levels of hydropeaking in Nordic rivers, with increases especially in recent few years. This indicates that expanding for renewable energy, increasing the need for load balancing in the energy market, may increase hydropeaking in Nordic rivers. A method based on wavelet analysis was developed to characterize variability in hydrologic time series data in different periods. It was found that, in winter, sub-daily variations in some large Regulated Rivers were up to 20 times higher than in Free-Flowing Rivers. For smaller Regulated Rivers with lower levels of regulation, the variation was highest in summer. We have assessed the impact of intra-day power demand variation on Regulated Rivers flow and potential to comply with instant energy demand, by quantifying the impact of reservoir volume and hydropower capacity constraints using two new metrics, power market impact and system efficiency ratio. The metrics, Tiivistelmä Pohjoismaisten jokien virtaamat ovat muutoksessa pääasiassa ilmastonmuutoksen ja jokien säännöstelyn takia. Säännöstelyn voimakkuuteen vaikuttaa vesivoiman alati muuttuva rooli energiamarkkinoilla etenkin uusiutuvien energiamuotojen lisääntyvä osuus jolloin tarvitaan enemmän säätövoimaa. Muuttuvien lyhyen ja pitkän aikavälin säännöstelykäytäntöjen vaikutuksista jokien virtaamaolosuhteisiin tarvitaan lisätietoa etenkin ekologialtaan herkistä pohjoisista joista. Säännöstelykäytäntöjen ja ilmastomuutoksen suhteellisen vaikutuksen arvioimiseksi tehtiin tila-ajallinen tutkimus kahdelle ilmasto- ja valuma-alueolosuhteiltaan samankaltaisella pohjoiseurooppalaiselle joelle, joista Kemijoki edustaa säännösteltyä ja Tornionjoki säännöstelemätöntä jokea. Säännöstellyllä joella havaittiin 100 % korkeampi hydrologinen muutos verrattaessa säännöstelemättömään. Joen säännöstellyllä ja ilmastomuutoksella näyttää olevan samanlainen vaikutus Kemijoen virtaaman muutoksiin (molemmat 50 %). Tulos vahvistettiin analysoimalla tietoja Kemijoen säännöstelemättömän Ounasjoen sivuhaaran aineistolla. Lyhytaikaisia muutoksia pohjoismaisissa joissa määritettiin kvantitatiivisesti käyttämällä 150 joen laajoja tuntikohtaisia virtaamatietoja. Tulosten mukaan lyhytaikaissäännöstely on näiden jokien tapauksessa korkealla tasolla, ja se on lisääntynyt viimeisen vuosikymmenen aikana. Syynä voi olla uusiutuvien energialähteiden lisääntyminen energiamarkkinoilla, sillä markkinoilla tarvitaan enemmän säätöenergiana toimivaa vesivoimaa tasapainottamaan sähköntuotannon vaihteluita. Työssä kehitettiin myös wavelet- aikasarja-analyysiin perustuva menetelmä hydrologisen aikasarjatiedon vaihtelevuuden karakterisoimiseksi eri ajanjaksoina. Tulosten mukaan joidenkin säännösteltyjen jokien päivittäiset virtaamavaihtelut olivat etenkin talvisin jopa 20 kertaa suuremmat kuin säännöstelemättömien jokien. Pienemmissä säännöstellyissä joissa muutokset olivat suurimpia kesäaikana. Päivittäisen energian kysyn

With increasing power production from renewable energy sources, sub-daily variations in energy demand need to be balanced. Today, hydropower is commonly used as balancing power. In this study, we quantified the impact of capacity constraints, in terms of reservoir volume and hydropower capacity, on the potential to comply with instant energy demand. To evaluate the impact, we developed two new metrics, power market impact and system efficiency ratio, which are based on two threshold flow regimes derived from natural flow as lower threshold release and regulated flow (based on hourly energy prices) as upper threshold release. The operation support model comprises 96 different regulation scenarios based on varying combinations of hydropower and reservoir capacities. For each scenario, an hourly water balance was simulated, to obtain the highest complying with upper threshold release based on actual energy demand. We tested the framework on the Kemijoki river with defined thresholds based on the natural flow regime (tributary river Ounasjoki) and the hourly energy price in Finland in 2017, and estimated the impact of regulation on hourly flow regime at the Taivalkoski hydropower station. The annual flow regime impact in 2013, 2014 and 2015 was estimated to be 74%, 84% and 61%, respectively, while the monthly impact varied from 27% to 100%. Our framework for evaluating interactions between the power market and sub-daily regulation practices is a useful novel tool for sustainable river management and can be easily applied to different rivers and regions and evaluated for different timescales.

Ecosystem protection requires a better definition of groundwater (GW) dependence and tools to measure this dependence. In this study, a classification method for the GW dependence of headwater streams was devised based on the fact that GW affects discharge, thermal regime, and water quality. The method was tested in three boreal headwater streams discharging from two esker aquifers. Spatial and temporal variability of GW dependence were studied in the stream continuum at several locations, by combining continuous measurements of temperature, electrical conductivity, and discharge with discrete sampling of environmental tracers (e.g., stable water isotopes, silica, chloride). The stream tracer index method developed was used to classify stream sections into GW-dominated, GW-surface water (SW) transition, and SW-dominated zones. We found that, spatially, GW dependence along the stream varied widely, with calculated stream tracer index values ranging from 33 to 94%. The GW-dominated areas extended at least 745, 1 682, and 4 202 m downstream from the main GW discharge points in the three streams studied. A stream located in a pristine peatland-dominated catchment was more prone to rapid change from GW- to SW-dominated than two streams located in catchments dominated by peatland forestry. These results suggest that to evaluate the GW dependence of streams, it may be sufficient to sample stream sections only once, during summer low-flow conditions. The proposed method can serve as a water management tool, especially for streams of exceptional ecological importance or in places where anthropogenic activities are expected to change local hydrology and ecology.

Catchment storage sustains ecologically important low flows in headwater systems. Understanding the factors controlling storage is essential in analysis of catchment vulnerability to global change. We calculated catchment storage and storage sensitivity of streamflow for 61 boreal headwater catchments in Finland. We also explored the connection between computed storage indices and low flow conditions. The relationships between selected climate, snow, and catchment characteristics and calculated storage properties and low flows were investigated, in order to assess the importance of different factors that render catchments vulnerable to climate and environmental change. We found that the most sensitive areas to climate change were located in the southern boreal coastal zone, with fine‐grained soils and agricultural areas. In contrast, catchments in the middle and northern boreal zone, with till and peatland soils and higher snow water equivalent values, were less sensitive under current conditions. In addition, we found a threshold at a snow to precipitation ratio of 0.35. Above that threshold, summer low flows were generally sensitive to changes in snow conditions, whereas below that threshold catchment characteristics gained importance and the sensitivity was more directly related to changes in temperature and timing of rainfall. These findings suggest that a warming climate will have pronounced impacts on hydrology and catchment sensitivity related to snow quantity and snow cover duration in certain snow to precipitation ratio zones. Moreover, land use activities had an impact on storage properties in agricultural and drained peatland areas, resulting in a negative effect on low flows.

The root zone storage capacity (Sr) of vegetation is an important parameter in the hydrological behaviour of a catchment. Traditionally, Sr is derived from soil and vegetation data. However, more recently a new method has been developed that uses climate data to estimate Sr based on the assumption that vegetation adapts its root zone storage capacity to overcome dry periods. This method also enables one to take into account temporal variability of derived Sr values resulting from changes in climate or land cover. The current study applies this new method in 64 catchments in Finland to investigate the reasons for variability in Sr in boreal regions. Relations were assessed between climate-derived Sr values and climate variables (precipitation-potential evaporation rate, mean annual temperature, max snow water equivalent, snow-off date), detailed vegetation characteristics (leaf cover, tree length, root biomass), and vegetation types. The results show that in particular the phase difference between snow-off date and onset of potential evaporation has a large influence on the derived Sr values. Further to this it is found that (non-)coincidence of snow melt and potential evaporation could cause a division between catchments with a high and a low Sr value. It is concluded that the climate-derived root zone storage capacity leads to plausible Sr values in boreal areas and that, apart from climate variables, catchment vegetation characteristics can also be directly linked to the derived Sr values. As the climate-derived Sr enables incorporating climatic and vegetation conditions in a hydrological parameter, it could be beneficial to assess the effects of changing climate and environmental conditions in boreal regions.