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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.;

The main aim of this paper is to analyze the characteristics of the drinking water quality in Kabul city and identify its suitability for drinking. During the work, a total of 60 water samples were collected from four drinking water sources (qanat, open well, tap water, and a hand pump) located at different points and were tested for physical, chemical, and biological parameters. Physical and chemical analyses were performed according to the standard methods, while a bacterial analysis was performed by using the Wagtech Potatest single incubator test kit and membrane filter method. The results obtained were compared with the standards of the World Health Organization (WHO) and Afghanistan’s National Standards Administration (ANSA). The study showed that physical parameters were within acceptable limits for qanat, open well, and tap waters. However, color, taste, odor, and turbidity values exceeded the recommended limits for hand pump wells. All analyzed chemical parameters were within permissible limits recommended by WHO/ANSA. The bacteriological analysis showed total coliform and fecal coliform contamination, particularly in warm weather conditions. The bacteriological contamination reveals the mixing of the sewage water with drinking water due to expired corroded pipes and discharge of wastewater to the groundwater. Several governance recommendations are proposed for improving water quality. They include strengthening coordination between government and public, considering options to install a new water distribution and sewage collection networks, enforcing standards for adequately preventing contamination from septic tanks, and increasing public awareness on low-cost measures such as boiling the drinking water before intake.

In an effort to improve tools for effective flood risk assessment, we applied machine learning algorithms to predict flood-prone areas in Amol city (Iran), a site with recent floods (2017–2018). An ensemble approach was then implemented to predict hazard probabilities using the best machine learning algorithms (boosted regression tree, multivariate adaptive regression spline, generalized linear model, and generalized additive model) based on a receiver operator characteristic-area under the curve (ROC-AUC) assessment. The algorithms were all trained and tested on 92 randomly selected points, information from a flood inundation survey, and geospatial predictor variables (precipitation, land use, elevation, slope percent, curve number, distance to river, distance to channel, and depth to groundwater). The ensemble model had 0.925 and 0.892 accuracy for training and testing data, respectively. We then created a vulnerability map from data on building density, building age, population density, and socio-economic conditions and assessed risk as a product of hazard and vulnerability. The results indicated that distance to channel, land use, and runoff generation were the most important factors associated with flood hazard, while population density and building density were the most important factors determining vulnerability. Areas of highest and lowest flood risks were identified, leading to recommendations on where to implement flood risk reduction measures to guide flood governance in Amol city.

With the development of shipping in the Caspian Sea, the need for high-quality data on wave characteristics has increased. In the present work, the analysis of maximum wave height at coastal stations in Kazakhstan was carried out using wave and wind data and numerical modeling with the SWAN model. The influence of stationary wind and its direction on the wave height was determined. The results show that the changes in the parameters of the wind wave depend on the wind speed and direction. At wind speeds below 10 m/s, the predicted wave height can reach 3 m in the Middle Caspian basin. In the Northern Caspian basin, where the depths are shallow, the waves do not exceed 2 m. The study output produced the first wind zoning map for the Kazakh part of the Caspian Sea.

With the development of shipping in the Caspian Sea, the need for high-quality data on wave characteristics has increased. In the present work, the analysis of maximum wave height at coastal stations in Kazakhstan was carried out using wave and wind data and numerical modeling with the SWAN model. The influence of stationary wind and its direction on the wave height was determined. The results show that the changes in the parameters of the wind wave depend on the wind speed and direction. At wind speeds below 10 m/s, the predicted wave height can reach 3 m in the Middle Caspian basin. In the Northern Caspian basin, where the depths are shallow, the waves do not exceed 2 m. The study output produced the first wind zoning map for the Kazakh part of the CaspianSea.

Abstract The anthropogenic impacts of development and frequent droughts have limited Iran's water availability. This has major implications for Iran's agricultural sector which is responsible for about 90% of water consumption at the national scale. This study investigates if declining water availability impacted agriculture in Iran. Using the Mann‐Kendall and Sen's slope estimator methods, we explored the changes in Iran's agricultural production and area during the 1981–2013 period. Despite decreasing water availability during this period, irrigated agricultural production and area continuously increased. This unsustainable agricultural development, which would have been impossible without the overabstraction of surface and ground water resources, has major long‐term water, food, environmental, and human security implications for Iran.

In cold (i.e. boreal, subarctic, snowy) climate zones, dynamic groundwater storage is greatly affected by the timing and amount of snowmelt. With global warming, cold climates in the northern hemisphere will transition to temperate. As temperatures rise, the dominant type of precipitation will change from snow to rain in winter. Further, the growing season is prolonged. This has a direct impact on the aquifer recharge pattern. However, little is known about the effect of changing annual recharge regimes on groundwater storage.The present work deduces the impact of shifting climate zones on groundwater storage by evaluating the effect of climate seasonality on intra-annual hydraulic head fluctuations. The work compares intra-annual hydraulic head fluctuations in a temperate-cold climate transition zone (Fennoscandia) from two different periods (1980–1989, 2001–2010). This is done by associating rising vs. declining hydraulic heads with hydrometeorology.Due to the northwards migration of the temperate climate zone, there is a shift in seasonality between the two periods. This has a negative impact on groundwater levels, which are significantly lower in 2001–2010, particularly near the climate transition zone. The results demonstrate that increasing temperatures in cold climate regions may change the seasonality of groundwater recharge, by altering the main recharge period from being snowmelt-dominated (spring) to rain-dominated (winter). Additionally, this is connected to the duration of the growing season, which impedes groundwater recharge. The coupled effect of this on groundwater in the study area has led to a significant decrease in groundwater storage.

Climate change's effect on sea surface temperature (SST) at the regional scale vary due to driving forces that include potential changes in ocean circulation and internal climate variability, ice cover, thermal stability, and ocean mixing layer depth. For a better understanding of future effects, it is important to analyze historical changes in SST at regional scales and test prediction techniques. In this study, the variation in SST across the Persian Gulf and Gulf of Oman (PG&GO) during the past four decades was analyzed and predicted to the end of 21st century using a proper orthogonal decomposition (POD) model. As input, daily optimum interpolation SST anomaly (DOISSTA) data, available from the National Oceanic and Atmospheric Administration of the United States, were used. Descriptive analyses and POD results demonstrated a gradually increasing trend in DOISSTA in the PG&GO over the past four decades. The spatial distribution of DOISSTA indicated: (1) that shallow parts of the Persian Gulf have experienced minimum and maximum values of DOISSTA and (2) high variability in DOISSTA in shallow parts of the Persian Gulf, including some parts of southern and northwestern coasts. Prediction of future SST using the POD model revealed the highest warming during summer in the entire PG&GO by 2100 and the lowest warming during fall and winter in the Persian Gulf and Gulf of Oman, respectively. The model indicated that monthly SST in the Persian Gulf may increase by up to 4.3 °C in August by the turn of the century. Similarly, mean annual changes in SST across the PG&GO may increase by about 2.2 °C by 2100.

Fifteen temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) were applied to evaluate spatiotemporal variability and trends in annual intensity, frequency, and duration of extreme temperature statistics in Finland during 1961–2011. Statistically significant relationships between these high-resolution (10 km) temperature indices and seven influential Northern Hemisphere teleconnection patterns (NHTPs) for the interannual climate variability were also identified. During the study period (1961–2011), warming trends in extreme temperatures were generally manifested by statistically significant increases in cold temperature extremes rather than in the warm temperature extremes. As expected, warm days and nights became more frequent, while fewer cold days and nights occurred. The frequency of frost and icing days also decreased. Finland experienced more (less) frequent warm (cold) temperature extremes over the past few decades. Significant lengthening in warm spells was observed in Finland during 1961–2011, while no clear changes are found in cold spells. Interannual variations in the temperature indices were significantly associated with a number of NHTPs. In general, warm temperature extremes show significant correlations with the East Atlantic and the Scandinavia patterns and cold temperature extremes with the Arctic Oscillation and the North Atlantic Oscillation patterns.

Long-term variations and trends in a wide range of statistics for daily precipitation characteristics in terms of intensity, frequency and duration in Finland were analysed using precipitation records during 1908–2008 from 3 meteorological stations in the south (Kaisaniemi), centre (Kajaani) and north (Sodankylä). Although precipitation days in northern part were more frequent than in central and southern parts, daily precipitation intensity in the south was generally higher than those in the centre and north of the country. Annual sum of very light precipitation (0 mm

During the past three decades, sea water level (SWL) in the Caspian Sea has declined by about 2 m and sea area has decreased by about 15 000 km ^2 . This has affected coastal communities, the environment and economically important gulfs of the sea (e.g. Dead Kultuk). To assess the effects of coastline change and evaluate zones vulnerable to desiccation, we simulated SWL using total inflow from feeder rivers and precipitation and evaporation over the sea. We determined potential vulnerable areas of the sea over the past 80 years by comparing the minimum and maximum annual water body maps (for 1977 and 1995). We then determined the linear regression between SWL rise and covered potential vulnerable area (CVA), using annual Normalised Difference Water Index (NDWI) maps and SWL data from 1977 to 2018. Combining SWL-CVA regression and SWL simulation model enabled us to determine desiccated areas in different regions of the Caspian Sea due to changes in precipitation, evaporation and total inflow. The results showed that 25 000 km ^2 of the sea is potentially vulnerable to SWL fluctuations in terms of desiccation, with 70% of this vulnerable area located in Kazakhstan. Potential vulnerable area per kilometre coastline was found to be 6 km ^2 in Kazakhstan, 4 km ^2 in Russia and whole of Caspian Sea, 1.5 km ^2 in Iran, 1 km ^2 in Azerbaijan and 0.5 km ^2 in Turkmenistan. The results also indicated that SWL in the Caspian Sea is sensitive to evaporation and that e.g. a 37.5 mm decrease in mean annual net precipitation would lead to a 1875 km ^2 decrease in the sea area, while a 1 km ^3 decrease in mean annual inflow would lead to a 1400 km ^2 decrease in the sea area. Thus the developed framework enabled the spatial consequences of changes in water balance parameters on sea area to be quantified. It can be used to assess future changes in SWL and sea area due to anthropogenic activities and climate change.

The competition over extracting the energy resources of the Caspian Sea together with the major anthropogenic changes in the coastal zones have resulted in increased pollution and environmental degradation of the sea. We provide the first evaluation of the spatiotemporal variation of chlorophyll- a (Chl- a ) across the Caspian Sea. Using remotely sensed data from 2003 to 2017, we found that the Caspian Sea has suffered from a growing increase in Chl- a , especially in warmer months. The shallow parts of the sea, near Russia and Kazakhstan, especially where the Volga and Terek rivers discharge large nutrient loads (nitrogen- and phosphorus-rich compounds) into the sea, have experienced the highest variations in Chl- a . The Carlson’s trophic state index showed that during the study period, on average, about 12%, 26%, and 62% of the Caspian Sea’s area was eutrophic, mesotrophic, and oligotrophic, respectively. The identified trends reflect an increasing rate of environmental degradation in the Caspian Sea, which has been the subject of conflict among its littoral states that since the collapse of the Soviet Union have remained unable to agree on a legal regime for governing the sea and its resources.

Fifteen temperature indices recommended by the ETCCDI (Expert Team on Climate Change Detection and Indices) were applied to evaluate spatiotemporal variability and trends in annual intensity, frequency, and duration of extreme temperature statistics in Finland during 1961–2011. Statistically significant relationships between these high-resolution (10 km) temperature indices and seven influential Northern Hemisphere teleconnection patterns (NHTPs) for the interannual climate variability were also identified. During the study period (1961–2011), warming trends in extreme temperatures were generally manifested by statistically significant increases in cold temperature extremes rather than in the warm temperature extremes. As expected, warm days and nights became more frequent, while fewer cold days and nights occurred. The frequency of frost and icing days also decreased. Finland experienced more (less) frequent warm (cold) temperature extremes over the past few decades. Interestingly, significant lengthening in cold spells was observed over the upper part of northern Finland, while no clear changes are found in warm spells. Interannual variations in the temperature indices were significantly associated with a number of NHTPs. In general, warm temperature extremes show significant correlations with the East Atlantic and the Scandinavia patterns and cold temperature extremes with the Arctic Oscillation and the North Atlantic Oscillation patterns.

In Afghanistan, spring and summertime flash floods result in 54.3% of all natural disasters with an average annual economic loss of US$92.17 million between 1990 and 2014. Knowledge of climate and rainfall periodicity are urgently needed for urban and rural land use and infrastructure planning, and their flood protection. In this study, the Thornthwaite equation was used to determine the seasonal characteristics of dry and wet periods. Spectral Analysis of precipitation was carried out to search for periodicities and intraseasonal oscillations of rainfall within the Kabul River Basin. The analysis is based on data obtained from 49 ground-base stations with three parameters (precipitation, relative humidity, and temperature) for an 8-year (2006-2013) and 5-year (2009-2013) record. Five years weather maps made from JRA-55 (55 year Japan Reanalysis data) were used to recognize the moisture trajectory in each season.The results indicated that Kabul River Basin is divided into three parts with distinct climate regions as Central, Northern, and Eastern parts. The Weather maps of relative humidity with wind arrows showed the origins and pathways of air masses leading to heavy rainfall from the Arabian Sea and the Caspian Sea approaching from the west and northwest of Afghanistan in winter and spring season, corresponding to 10-day spectral peaks. In summer and autumn, influences of South Asian summer monsoon were recognized by 6-8 days of oscillation with different density in each station, where it was much significant in the Eastern part.

Ice occurs in the Caspian Sea and its northern part influencing traffic, ports and the coastal region at large. Especially, heavy winds leading to massive ice jams considerably effect the socioeconomic use of the sea. In recent decades, the Caspian Sea is affected by reduced water inflow from the major rivers and changes in climate, but these changes are not well documented or known. To better understand ice conditions, winter regimes and climate change impact, this article analyzes the cold periods from 1980 to 2016, in the northern part of the Caspian Sea and connects ice conditions to climatic characteristics. Winters are classified using the P.I. Buharits in classification from sever to mild. The authors analysed changes in air temperature as of the main indicator of climate change, and a potential ice regime shift. The results show an annual warming of 1,1 0Cand 1,3 0Cfor the cold period since 1990. Winter severity, which is closely linked to ice thickness has clearly decreased since the cold winters in 1950’s and 1960’s. Milder winters have changed ice conditions in the northernmost part of the Caspian Sea. A detailed analysis of mild and cold winters show a clear difference in ice depth, with thickness about 58 cm and 20 cm, respectively.

The water supply to Kabul city is at serious risk due to groundwater over abstraction and severe contamination by sewage. The water overuse is partly due to poor management and a long period of war, and instability in Afghanistan. In recent years shallow wells have been installed and financed by aid programmes, but this, along with high population increase has also lead to over-use of groundwater resources. The current water supply of about 85% inhabitants depends exclusively on local, individual groundwater sources, obtained predominantly from shallow aquifers, mainly, by hand-pumps. The paper analyses the status and trends of the Kabul groundwater system and assesses new solutions to meet the future water supply demand. The status of groundwater shows that groundwater levels are declining quickly (1 m/year) and several wells are already dry. Moreover, water quality analyses of the Kabul aquifers show a negative trend in groundwater quality in respect to concentration of nitrates, borates and faecal microbes(indicated by the coliform bacteria). This pollution exceeds the maximum permissible values determined by the WHO. To provide new solutions for Kabul city, a master plan for future water resources has been developed and this is further discussed.

Large parts of the northern hemisphere are covered by snow and seasonal frost. Climate warming is affecting spatiotemporal variations of snow and frost, hence influencing snowmelt infiltration, aquifer recharge and river runoff patterns. Measurement difficulties have hampered progress in properly assessing how variations in snow and frost impact snowmelt infiltration. This has led to contradicting findings. Some studies indicate that groundwater recharge response is scale dependent. It is thus important to measure snow and soil frost properties with temporal and spatial scales appropriate to improve infiltration process knowledge. The main aim with this paper is therefore to review ground based methods to measure snow properties (depth, density, water equivalent, wetness, and layering) and soil frost properties (depth, water and ice content, permeability, and distance to groundwater) and to make recommendations for process studies aiming to improve knowledge regarding infiltration in regions with seasonal frost. Ground-based radar (GBR) comes in many different combinations and can, depending on design, be used to assess both spatial and temporal variations in snow and frost so combinations of GBR and tracer techniques can be recommended and new promising methods (auocostics and self potential) are evolving, but the study design must be adapted to the scales, the aims and the resources of the study.

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.

In this study, metal concentrations in the water column and surface sediment of the Sabalan Dam Reservoir (SDR) were determined. Moreover, heavy metal pollution index (HPI), contamination index (CI), heavy metal evaluation index (HEI), enrichment factor (EF), geo-accumulation index (Igeo), sediment quality guidelines (SQGs), consensus-based SQGs (C-BSQGs), and mean probable effect concentration quotients (mPECQs) were evaluated for water and sediments of SDR. It was observed that metal concentrations in river entry sediment were lower, but those in river entry water were higher than corresponding values in the vicinity of the dam structure. The HPI values of water samples taken from 10 m depth in the center of SDR exceeded the critical limit, due to high concentrations of arsenic. However, according to CI, the reservoir water was not contaminated. The HEI values indicated contamination of SDR water with metals at 10 m depth. A comparison of water quality indices revealed that HEI was the most reliable index in water quality assessment, while CI and HPI were not sufficiently accurate. For SQGs, As and Cu concentrations in sediments were high, but mPECQ, Igeo, and EF revealed some degree of sediment pollution in SDR. The calculated EF values suggested minor anthropogenic enrichment of sediment with Fe, Co, V, and Ni; moderate anthropogenic enrichment with As and Mn; and moderate to severe anthropogenic enrichment with Cu. A comparison of SQG values revealed that the threshold effect and probable effect levels were the most reliable metrics in the assessment of sediment toxicity. Statistical analysis indicated similarities between metal concentrations in the center of the reservoir and near to the dam structure, as a result of similar sediment deposition behavior at these points, while higher flow velocity at the river entry point limited deposition of fine particles and associated metals.

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.