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2 results for “Norrström”
H2020 773782-COASTAL MAL03 Scenarios for the Norrström-Baltic region
<p>The scenarios are developed based on projected climate and socio-economic changes, following the representative concentration pathways (RCPs) and the shared socioeconomic pathways (SSPs) for the region.</p> <p>The Norrström-Baltic SD model analyzes possible future shifts in the annual average conditions of sectoral and natural water system interactions. Such shifts are evaluated based on recent annual averages reflecting the condition of system components. Parameters taken into account are, amongst others, sectoral water availability, water fluxes between sectors and the corresponding nutrient (nitrogen and phosphorus) exchanges, coastal runoff and nitrogen and phosphorous loads ending up in the Baltic Sea. </p> <p>An overview of the model input variables and the parameters that are identified as system external uncertainties that may affect the behavior of the model:</p> <p>- Precipitation: climate change</p> <p>- Agricultural land: Development policies and market forces, food security and trade regulations, population growth and corresponding food demand/diet changes</p> <p>- Built-up land: Development policies and market forces, population growth, regional urbanization level, tourism expansion level</p> <p>- Forest land: Mitigation policies on climate change (i.e. afforestation and/or reforestation to maintain/enhance carbon capture and storage capacity), socio-economic developments leading to sectoral land competition (i.e. deforestation)</p> <p>- Open lands and wetlands: Policies and market forces supporting social and economic development in the region</p> <p>A total of 5 scenarios were developed for the Norrström/Baltic Sea case. One of them represents the ‘Base case’ conditions, while the rest are rooted in the combination of a certain SSP with a climate scenario linked to a certain RCP. The following overview shows the combinations used during the scenario building process:<br> - Scenario 1: SSP1 + RCP 4.5<br> - Scenario 2: SSP2 + RCP 4.5<br> - Scenario 3: SSP4 + RCP 4.5<br> - Scenario 4: SSP5 + RCP 4.5<br> - Base Case scenario: Continuation into the future of the past-recent long-term average conditions in relation to hydro-climate and land use variables in the SD model.</p> <p>All the scenarios developed for the Norrström-Baltic region are linked to a climate scenario corresponding with RCP4.5, because projected patterns and changes for climate variables under this climate scenario were found to be more consistent with the observed changes in the region than other RCPs. The period 2010-2100 is compared with the normal mean for the period 1961-1990. Each year is compared separately with the long-term annual average precipitation.</p> <p>The xsls file is organized as follows. It comprises three sheets:</p> <ul> <li>Precipitation RCP with annual data of changes in annual precipitation (in percentage), precipitation (in million of m3/year and in mm/year);</li> <li>Land cover RCPs and SSPs with scenario data on land cover, annual change in land cover (in percentage), annual land cover areas for the Norrström water management district area, land dover area average for teh Norrström water management district area and average change in land cover compared to the long-term average (in percentage);</li> <li>Input data model with the four input variables (precipitation change rate in hydro-climate scenarios, urban growth rate in socioeconomic scenarios, forest land change rate in socioeconomic scenarios and agricultural land change rate in socioeconomic scenarios) and their change for each scenario (expressed in percentage).</li> </ul>
H2020 773782-COASTAL MAL03 Management set for the Norrström-Baltic region
<p>The sets of measures relate to different Business Road Map (BRM) alternatives prioritized by stakeholders in the Norrström-Baltic (MAL3) case:</p> <ul> <li><strong>Current management</strong>: Base case with no change in nutrient concentrations for nitrogen (N) and phosphorous (P) (same results as for the base case scenario in D19).</li> <li><strong>Agricultural set of measures</strong>: Considers the example of 25% reduction in nutrient concentrations leaching from currently active agriculture with associated reduction in agricultural nutrient contributions to subsurface water (SSW) and surface water (SW) nutrient concentrations. Such reductions may result, e.g., from improved/optimized agricultural fertilization practices and drainage facilities, and restoration/construction of wetlands that can capture local nutrient leakage. This set of measures relates to the stakeholder-prioritized BRM alternative “Integrated risk assessment of nutrient losses from agricultural soils to surface waters”.</li> <li><strong>WWTP set of measures</strong>: Considers the example of 25% reduction of nutrient concentrations in discharges from currently active municipal and industrial wastewater treatment plants (WWTPs) and unconnected wastewater facilities with associated reduction in their contributions to SW nutrient concentrations. Such reductions may result, e.g., from improved nutrient removal in WWTPs and recovery in smart water and sanitation systems, related to technological advancements and, more widely, e.g., creation of a nutrient market that makes such capture and reuse worthwhile. This set of measures relates to the stakeholder-prioritized BRM alternatives “Nutrient recovery in wastewater treatment plants” and “Smart water and sanitation systems”.</li> <li><strong>Legacy set of measures</strong>: Considers the example of 25% reduction in total SSW and SW nutrient concentrations. Such reductions may result from catchment-wide mitigation (removal/capture and possible reuse) of nutrients released from diffuse wide-spread legacy sources that still remain in soil, groundwater and sediments from different types of earlier nutrient inputs (past agricultural leakage, municipal and industrial wastewater discharges). Such mitigation may be achieved, e.g., by restoration/construction of wetlands and construction of reactive barriers that are well-placed and distributed to effectively capture considerable parts of the overall legacy nutrient releases throughout each hydrological catchment. This set of measures also relates to possible changes in socio-economic drivers, such as creation of a nutrient market that can make capture and reuse of nutrients worthwhile, along with improved knowledge transfer between sectors and some shift in the municipal water (quality) management monopoly that current applies in Sweden. With regard to the stakeholder-prioritized BRM alternatives, it relates to: (i) “Improved knowledge transfer between sectors” that may drive better system understanding with more efficient nutrient mitigation measures taken and well/optimally placed in each hydrological catchment for targeting and mitigating diffuse legacy sources; and (ii) “Change of municipal monopoly” that may enhance collaboration and communication between different municipalities within the same hydrological catchment toward more overarching efficiency and circular principles on whole catchment-scale.</li> </ul> <p>The .xslx data are organized as follows.</p> <p>One sheet per set of measure: </p> <ul> <li>Base case (current management)</li> <li>Agricultural set of measures</li> <li>Wastewater treatment plants set of measures</li> <li>Legacy set of measures</li> </ul> <p>For each sheet, the following data are included. </p> <p>Columns:</p> <ul> <li><strong>A: Variable name</strong></li> <li><strong>B: Input variables</strong> - full name and units of the variable</li> <li><strong>C: Initial</strong></li> <li><strong>D: current climate and socio-economy</strong></li> <li><strong>E: scenarios</strong>: RCP4.5+SSP1, RCP4.5+SSP2, RCP4.5+SSP4, RCP4.5+SSP5</li> </ul> <p>For each column, the values are organized with the following variables (rows 2-16): “Concentration of N in SSW”, “Concentration of N in SW”, "Concentration of N in WWTP-input", "Concentration of N in WWTP-output", “Concentration of P in SSW”, “Concentration of P in SW”, "Concentration of P in WWTP-input", "Concentration of P in WWTP-output", "Concentration of P-SW to agriculture", "Concentration of N-SW to agriculture", "Concentration of P-agriculture to SW", "Concentration of N-agriculture to SW", "Concentration of N-agriculture to SSW", "Concentration of P-agriculture to SSW"</p> <ul> </ul> <p> </p>
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