“…Water Balance: Water balance estimation in a river catchment predicts the detailed surface water and groundwater interactions. A detailed water balance explains the main water loss components and will help in developing watershed management practices and better informed policy decisions [49,50]. In this study, the calibrated coupled MIKE SHE and MIKE 11 model has predicted the water balance with an error of less than 2%.…”
Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.
“…Water Balance: Water balance estimation in a river catchment predicts the detailed surface water and groundwater interactions. A detailed water balance explains the main water loss components and will help in developing watershed management practices and better informed policy decisions [49,50]. In this study, the calibrated coupled MIKE SHE and MIKE 11 model has predicted the water balance with an error of less than 2%.…”
Achievements of good chemical and ecological status of groundwater (GW) and surface water (SW) bodies are currently challenged mainly due to poor identification and quantification of pollution sources. A high spatio-temporal hydrological and water quality monitoring of SW and GW bodies is the basis for a reliable assessment of water quality in a catchment. However, high spatio-temporal hydrological and water quality monitoring is expensive, laborious, and hard to accomplish. This study uses spatio-temporally low resolved monitored water quality and river discharge data in combination with integrated hydrological modelling to estimate the governing pollution pathways and identify potential transformation processes. A key task at the regarded lowland river Augraben is (i) to understand the SW and GW interactions by estimating representative GW zones (GWZ) based on simulated GW flow directions and GW quality monitoring stations, (ii) to quantify GW flows to the Augraben River and its tributaries, and (iii) to simulate SW discharges at ungauged locations. Based on simulated GW flows and SW discharges, NO3-N, NO2-N, NH4-N, and P loads are calculated from each defined SW tributary outlet (SWTO) and respective GWZ by using low-frequency monitored SW and GW quality data. The magnitudes of NO3-N transformations and plant uptake rates are accessed by estimating a NO3-N balance at the catchment outlet. Based on sensitivity analysis results, Manning’s roughness, saturated hydraulic conductivity, and boundary conditions are mainly used for calibration. The water balance results show that 60–65% of total precipitation is lost via evapotranspiration (ET). A total of 85–95% of SW discharge in Augraben River and its tributaries is fed by GW via base flow. SW NO3-N loads are mainly dependent on GW flows and GW quality. Estimated SW NO3-N loads at SWTO_Ivenack and SWTO_Lindenberg show that these tributaries are heavily polluted and contribute mainly to the total SW NO3-N loads at Augraben River catchment outlet (SWO_Gehmkow). SWTO_Hasseldorf contributes least to the total SW NO3-N loads. SW quality of Augraben River catchment lies, on average, in the category of heavily polluted river with a maximum NO3-N load of 650 kg/d in 2017. Estimated GW loads in GWZ_Ivenack have contributed approximately 96% of the total GW loads and require maximum water quality improvement efforts to reduce high NO3-N levels. By focusing on the impacts of NO3-N reduction measures and best agricultural practices, further studies can enhance the better agricultural and water quality management in the study area.
“…In general, intrusion from lake or gravel pit water will be easier to identify than from rivers. Lakes in seasonal climates undergo progressive evaporative enrichment over the warm season (Gibson et al., 2016), imprinting a negative d‐exces s (Cui et al., 2017; Yapiyev et al., 2020) and lc ‐ excess signal in lake water. Water in streams and rivers, on the other hand, is typically sourced from groundwater and precipitation, unless there is immediate influence from large lakes (Ala‐aho et al., 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Another, more commonly used metric to identify evaporation impact is d‐excess (Jasechko, 2019; Kong et al., 2013; Yapiyev et al., 2020). The difficulty of the application of d‐excess to estimate the impacts of evaporation on surface and underground water is that it can be confounded by precipitation inputs.…”
Section: Discussionmentioning
confidence: 99%
“…Stable isotope composition of precipitation for a region may be different from GMWL and can be represented as a local meteoric water line (LMWL) with a specific slope and intercept (Putman et al., 2019). Stable isotope composition of water derived from lakes (or other surface water bodies) in a particular region plotted in δ 18 O versus δ 2 H space define the local evaporation line (LEL) (Yapiyev et al., 2020).…”
Section: Methodsmentioning
confidence: 99%
“…The intrinsic ability of stable water isotopologues to separate (fractionate) during phase (liquid‐vapor‐solid) change is described by robust physical models (Gat, 1998; Wassenaar & Aggarwal, 2018), making them the ideal natural environmental tracers (Kendall & McDonnell, 2012). There are many studies which have used isotopes for different applications in water resource research, such as isotopic mass balance of lakes (Gibson et al., 2016; Isokangas et al., 2015; Vystavna et al., 2021), hydrograph separation (Klaus & McDonnell, 2013), end‐member analysis (Barthold et al., 2011), ecohydrology to partition evapotranspiration into transpiration and evaporation (Dubbert et al., 2013), groundwater recharge and seasonality (Jasechko et al., 2014), and groundwater‐surface water interactions (Isokangas et al., 2019; Marttila et al., 2021; Yapiyev et al., 2020). The relative accessibility and ease of isotope analysis allowed by the progress made in cavity‐ring downs spectrometry (Wassenaar et al., 2018) has made it possible to use the isotopes as a tool for a wider range of applications.…”
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.
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