Search

Climate change and anthropogenic activities have impacts on fish habitat suitability, demanding more accurate modeling of species abundance for effective conservation and management. In this study, we applied Machine Learning techniques to model the habitat-abundance relationship of juvenile Atlantic salmon (Salmo salar) in the Teno catchment in Finland and Norway. To capture the complexity and nonlinearity of the habitat-abundance relationship, we employed Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting (GB), and Support Vector Classification (SVC) and compared their performances. Among the regression models considered, those incorporating input variables such as substrate, shade, and vegetation demonstrate higher performance. Support Vector Regression yields the highest mean cross-validation score (R2 = 0.58), and Gradient Boosting produces the highest test score (R2 = 0.6) among the regression techniques. The mean cross-validation and test scores obtained for the classification models are notably higher compared to the regression models across all scenarios. A comparison between regression and classification results highlights the challenges of accurately modeling the habitat-abundance relationship. This study provides insights into the challenges and potential of machine learning techniques for juvenile Atlantic salmon habitat-abundance modeling in complex riverine habitat environments. The findings emphasize the importance of considering the limitations of machine learning models, particularly in ecological contexts, and the need for further research to address temporal variations and improve the precision of habitat-abundance modeling.

Sustainable water management measures are being developed to address the challenges posed by agriculture runoff and leaching on water resources. These measures are based on experts' opinions from various sectors and disciplines, ensuring that all stakeholders' perspectives are considered. For this, establishing a common understanding of 'sustainability' is essential to avoid misunderstandings, conflicts, and operational challenges. In this research, the Delphi survey technique was utilized to develop a definition of ‘sustainability’ in agricultural water management (SAWM) by considering the interdisciplinary group of experts from different parts of the world and those involved in a Horizon 2020 Research and Innovation Action. Twenty-six experts' perspectives on environmental, economic, and social dimensions of sustainability were assessed, and identified key concepts included climate change, water quality, water availability, stakeholder participation, capacity building, subsidies, and incentives. These concepts were used to define sustainability for multi/interdisciplinary project settings. The definition was validated with consortium members of the project in the regular consortium-wide meetings and used in the respective deliverables dealing with sustainability. The results serve as a foundation for communication between the involved actors and the project's definition of 'sustainability.' One recommendation from this work for broader policy formulation for SAWM in Europe is to prioritize farmer needs and focus on environmental sustainability. HIGHLIGHTS The research in agricultural water sustainability is essential to find pathways that optimize food production, limit water resource pollution, and promote sustainability of water management practices.; The absence of a common definition of sustainability can lead to miscommunication among partners due to varying interpretations resulting in ineffective collaboration, confusion, and a lack of coordination.; The Delphi survey technique is a powerful tool to capture diverse opinions from various experts in a complex discipline like "Sustainability".; Climate change, the environmental pillar of sustainability, and farmers as major stakeholders should be taken into prime focus when dealing with sustainable water management in agriculture.;

Abstract 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.

The research focused on assessing groundwater quality in Jawharkel, Ghanikhel, Chak, Mandukhel, Dawrankhel, Noorkhel, Baba Qala, Sanikhel, Muhkumkhel, and Rasheeddan villages, and specifically intended to measure groundwater physical and chemical parameters in the mountainous areas of the Chak Karstic Sedimentary Basin in Chak District, Wardak Province, located in Afghanistan’s central part. The analyzed parameters included electric conductivity, pH, turbidity, odor, taste, color, hardness, as well as chloride (Cl2), nitrogen (N), fluoride (F), iron (Fe), arsenic (Ar), ammonia (NH3), and sulfide (SO4) content. All the analyzed chemical and physical parameters were found to be within acceptable limits. The results obtained were compared with the WHO drinking water quality standards. The study revealed that the values of physical parameters such as color, taste, odor and turbidity fell within the acceptable (recommended standard) limits; that the examined samples demonstrated no toxic elements and/or components; and that the analyzed chemical parameters were likewise within the permissible limits recommended by WHO and ANSA. Water quality in the target rural area proved to be better compared to the concerns of its residents and households, and that local water posed no threat to residents’ health and survival. The article emphasizes the importance of properly applying water quality indicators previously not adequately explored in the target area.

Study region: Once, the Tigris River (with its twin, the Euphrates) was the remarkable river in the west of Asia, making Mesopotamia a cradle of civilization thousands of years ago. Upstream anthropogenic activity has choked the Tigris River, the connecting lifeline across Iraq, and, due to droughts and desertification, caused the country to be plagued by poverty. Study focus: Here, we give a perspective on flow regime alteration in the main corridor of the Tigris River at five crucial points (Cizre, Mosul, Baiji, Baghdad, and Kut) before and after the planned water resources development in Turkey. Turkey’s Tigris River regulation goal is to generate about 7247 GWh of energy and irrigate over 640,000 ha of farmlands. New hydrological insights for the region: We reconstructed the natural flow along the Tigris River. In addition, to evaluate hydrological droughts, we proposed a modified streamflow drought index (MSDI) and compared it with the original streamflow drought index (SDI). The results show that the worst hydrological conditions could be found below the Samarra barrage in Iraq before the Tigris River regulation in Turkey. This negative hydrological condition will be extended to the whole corridor of the Tigris River in Iraq after the implementation of Turkey's goal. As a result, for example, Cizre and Mosul will experience extreme conditions in 37.5–87.5% of the years; this means a considerable reduction in the Mosul reservoire’s inflow (135–326 m3/sec). Consequently, some parts of Mosul's hydropower and reservoir capacity will be useless, and hydrological drought upstream of the Samarra barrage will be dominated.

The European Union (EU) Water Framework Directive is of paramount importance for water management. According to the legal text, coordination with other directives like the Floods Directive is imperative and motivated by potential synergy effects. In this paper, the degree to which such coordination is achieved is evaluated for five Nordic and Baltic countries. The evaluation is based on legal documents, management plans, as well as on organizational structure in the five countries. The results show that the coordination between the Water Framework Directive and the Floods Directive (or flood management for Norway's case), have been successful for Estonia and Lithuania, whereas Norway, Finland, and especially Sweden need to improve more. HIGHLIGHTS In this paper, the coordination of work with two EU directives in Nordic and Baltic countries is studied.; The potential for synergy effects is reached with varying success in the studied countries.; National legislation and organization of work affect the rate of success with coordination.; Our results confirm conclusions made by the European Commission.;

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. HIGHLIGHTS High spatial and temporal variability of water table was observed in Padang Island.; The variability was partially driven by variation in land use and farm drainages.; Recession rate near pulp plantations remained high (0.01 m/day) at −1.5 m depth.;

Understanding the impact of Climate Variability (CV) on crop yield is crucial for developing sustainable agriculture practices, especially in regions vulnerable to climate change. This study aims to identify the causes of the observed decline in potato yield in Northern Finland by analyzing Remote Sensing data and statistical analysis on climatic variables from 2001 to 2020. First, the exception years with critical production (2004, 2006, 2008, 2012, 2015) were selected based on the anomaly in the annual potato yield. Then a variety of extreme indices based on precipitation and Land Surface Temperature occurrence and intensity during the growing season were calculated to find how much impact they have on potato yield. Principal Component Analysis was used to select the most significant ones among the extreme indices. Finally, through a multiple regression analysis, we found that extreme precipitation events and cumulative temperature explain around 48 % potato yield variations in which extreme precipitation (with 38 %) had much more impact than cumulative temperature (with 10 %). We concluded that one degree increase in cumulative temperature increases potato yield by 19.64 kg/ha and in contrast, heavy precipitation plays a negative role, i.e., one day increase in extreme precipitation events, decreases potato yield by 2085 kg/ha.

In recent years, the effects of human activities and climate change on river flow patterns have become a major concern worldwide. This is particularly true in the southern Caspian Sea (SCS) region of Iran, where increasing water-intensive socio-economic development and climate change have significantly altered river flow regimes. To better understand these changes, this study employs two nonparametric methods, the modified Mann-Kendall method (MK3) and Innovative Trend Analysis (ITA), to examine spatial and temporal changes in hydrometeorological variables in the SCS. The study also evaluates the impact of human activities and climate change on river flow alteration using elasticity-based methods and the Budyko hypothesis in 40 rivers on the closest gauges to the Caspian Sea. The results indicate an alarming trend of increasing temperature, potential evapotranspiration, and decreasing river flows in the SCS region. In particular, human activities were found to be responsible for around 91.7 % of the change on average, resulting in a significant decline in inflow to the Caspian Sea by about 3216 MCM annually. This declining trend in inflow could potentially exacerbate the eutrophication conditions in the Sea and negatively impact its ecosystem and economics. Therefore, appropriate measures need to be taken to address these environmental and socio-economic issues in the southern Caspian Sea region.

This research study investigates the impact of air temperature and precipitation on annual potato crop yield in Finland region and a local area in northern Finland. For this, the annual crop yield data of regional and local case study area is processed using Z-score normalization technique. Classification of computed z-score values was carried out into different classes ranging between the most beneficial crop yield year and the most vulnerable crop yield year. Later, the detection of feasible potato cropping season at monthly and daily scale was carried out using different weather parameters. Further, long-term trend analysis using Mann-Kendall's approach at annual, seasonal, and monthly scales was carried out using 60 years of dataset of both case study areas. Then after, the comparative analysis of annual crop yield and the characteristics obtained within climate data using different statistical approaches at annual, seasonal, and monthly scale. Finally, multivariate analysis was carried out to find most influential climate variables obtained using different statistical signatures. The results shows that, over the 100 years of period the annual potato crop yield of regional case study area shows a rising trend with declining area under potato crop. Classification approach found 16 % annual yield scored lowest Z-score while, 18% the highest. Likewise, 20 years of data for the local case study area found that 25 % of the dataset scored the highest Z-score and 15 % of the dataset values scored the lowest. Long-term trend analysis of air temperature shows significant increasing trend annually, seasonally and for monthly during the months between July-September. Whereas, similar procedure with the precipitation data showed increasing trend only at annual scale with the precipitation data analysis. During the comparative analysis between the annual crop yield data based on z-score classification and different statistical results obtained from weather parameters such as variation of precipitation and temperature sum, long-term climate data maximum-minimum totals seasonally as well as monthly during crop growing season; noticeable anomalies were observed in the weather parameters in line with the crop yield years grouped into the lowest and the highest Z-scores. The Multivariate analysis emphasized the impact of air temperature over precipitation on potato crop yield. Present study provides quantitative assessment on usefulness of long-term climate signatures for region specific either event-based or crop-based modelling development efforts to provide efficient decision support for enhancing farm-level crop productivity and sustainability of local and regional agriculture.

This article aims to show that virtual water has historically been an adaptation strategy that enabled some arid regions to develop a prosperous economy without putting pressure on their scarce water resources. Virtual water is referred to as the total amount of water that is consumed to produce goods and services. As an example, in arid central Iran, the deficiency in agricultural revenues was offset by more investment in local industries that enjoyed a perennial capacity to employ more workers. The revenues of local industries weaned the population from irrigated agriculture, since most of their raw materials and also food stuff were imported from other regions, bringing a remarkable amount of virtual water. This virtual water not only sustained the region’s inhabitants, but also set the stage for a powerful polity in the face of a rapid population growth between the 13th and 15th centuries AD. The resultant surplus products entailed a vast and safe network of roads, provided by both entrepreneurs and government. Therefore, it became possible to import more feedstock such as cocoons from water-abundant regions and then export silk textiles with considerable added-value. This article concludes that a similar model of virtual water can remedy the ongoing water crisis in central Iran, where groundwater reserves are overexploited, and many rural and urban centers are teetering on the edge of socio-ecological collapse. History holds an urgent lesson on sustainability for our today’s policy that stubbornly peruses agriculture and other high-water-demand sectors in an arid region whose development has always been dependent on virtual water.

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. Despite the uncertainties related to the heterogenic soil properties and complex groundwater interactions, we conclude the method to have potential for estimating changed flow paths and wetness following peatland restoration.

River flow in cold climates is known to be one of the hydrological systems most affected by climate change, playing a central role in the sustainability of downstream socio-ecological systems. Numerous studies on the temporal and spatial variations of streamflow characteristics have been done, and a comprehensive study on the variation of hydrologic extremes is becoming increasingly important. This study evaluated the long-running changes in the magnitude, time, and inter-annual variability of hydrologic extremes, including high and low flow in 16 major Finnish rivers. We applied four new hydrologic extreme indices for summer–winter low flow ratio, spring-absolute high flow ratio, time-to-peak index, and increasing rate index during the snowmelt period to analyze the spatiotemporal variations of extreme streamflow from 1911 to 2020. The most detected trends in flow regimes have started in the last six decades and become more severe from 1991 to 2020, which is likely to be dominated by anthropogenic global warming. The results also indicated that alteration of low pulses in most rivers was associated with an increase (decrease) in winter (summer) flows, suggesting the annual minimum flow in summer frequently contradicts natural hydrologic regimes in Arctic rivers. Southern Finland has experienced higher variations in extreme hydrology over the last century. A new low flow regime was detected for southern rivers, characterized by frequent annual minimum flow in summer instead of winter. Moreover, the annual maximum flow before/after spring dictated a new high-flow regime characterized by frequent double peak flows in this region.