Stein Beldring

Water, energy, and food security are threatened by changes in climate. Shifts in rainfall patterns and increases in temperature affect availability of catchment water resources, particularly when hydrological regimes are rainfall-limited, snow-dominant or influenced by glaciers. The sectors dependent on those water resources are therefore more at risk. To evaluate resource availability, sector interdependencies and overall vulnerability of a catchment, a nexus approach can be used. More holistic solutions can then be developed, increasing the catchment’s resilience to changes in future. However, difficulties lie in capturing the dynamics of climate, land, energy, and water systems together. In Norway for instance, this often includes snow, glaciers, and the management of reservoirs for hydropower production, and few nexus methods include these features. To address this, we selected the Community Water Model (CWatM) and made several new developments. CWatM is a widely available, easily adjustable hydrological model on a 1km x 1km daily resolution. It has the facility to include multiple crop types, and domestic, agriculture and industry water demands, therefore highly suitable for nexus assessment. The new developments to CWatM mean that seasonal changes in both reservoir and glacier water storage can now be assessed, so how these have affected, and may affect resilience to changes in climate in future could be evaluated. To test the model developments, we applied the CWatM model to the Otta catchment in Innlandet, Norway. Three large glacial bodies, and four hydropower reservoirs provide water storage to an otherwise rain-limited catchment (~300mm/year). Water resources are required for consistent hydropower production throughout the year, agriculture, and forestry, as well as white water rafting-dependent tourism. These competing demands, alongside the melting of glaciers due to climate change, have the potential to put a large amount of strain on the limited water resources. Results showed that CWatM with the new developments successfully represented the dynamics of stream discharge, glaciers, and reservoir water storage in the Otta catchment. Future work will focus on assessing the vulnerability and resilience of the Otta catchment to climatic extremes given historic and potential future changes in storage with climate change. Wider application of CWatM and the new developments could improve nexus evaluation of other catchments in Norway and worldwide and highlight opportunities for greater resilience to changes in climate.

We present a new runoff map for Norway for the reference period 1991-2020. A new framework combing precipitation runoff-modelling with geostatistical interpolation was used. The precipitation-runoff model WASMOD was used to simulate runoff on a 1x1 km grid covering all Norway and nearby catchments in Sweden and Finland. The parameters of WASMOD were conditioned on land-use and climate classes and calibrated globally using data from 215 streamflow stations. Figure 1a) shows the runoff estimates from WASMOD that are biased when compared to observations (Figure 2a) .To correct the biases in the gridded simulations we used runoff observations from 732 locations of which 198 had data covering the whole period. A geostatistical approach was used to estimate the 30 year mean annual runoff from short records (1-29 years) for 482 catchments. For 45 catchments with substantial glacier coverage or regulation capacity, a manual extension of mean annual runoff was performed. Another 7 stations with between 25 and 30 years of data were included.The biases from WASMOD were corrected by simple linear regression using the raw runoff map as a covariate and the runoff observations as the dependent variable. The regression coefficients were modelled as spatial fields using a geostatistical Bayesian approach where SPDE and INLA ensured fast Bayesian inference. The mean annual runoff after the correction is shown in Figure 1b), and in Figure 1c) the difference between the two previous maps is shown. Figure 2b shows a scatter plot of corrected and observed runoff. The scatter is now much smaller.Figure 1. Mean annual runoff from a) the Wasmod model and b) after the correction. The difference in runoff between a) and b) is shown in c)The new framework was evaluated by cross-validation. On average this new approach outperformed a WASMOD when predicting runoff for ungauged and partially gauged catchments and reduced the RMSE by 42% . Scatter plot of predicted runoff is shown in Figure 2c).Figure 2. Scatterplot of mean annual runoff for a) WASMOD, b) corrected values, and c) predicted runoff , versus observations in 146 catchments in a split sample cross-validation test   

Climate change impact assessment related to floods, infrastructure networks, and water resource management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on a historical observation-based gridded data product, with coarser-scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Climate change impact assessment related to floods, infrastructure networks and water resources management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on historical observation-based gridded data product, with coarser scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km², daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.

Variation in the sea age at maturity of Atlantic salmonSalmo salarwas studied in 158 Norwegian rivers over large spatial (58–71°N; 5–30°E) and temporal (1983–2000) scales. Age at sexual maturity was expressed as the proportion of grilse (fish with one sea winter) in the nominal salmon catch. No general temporal trend was found in the proportion of grilse in the catches. However, grilse proportion declined significantly in 10 rivers and increased significantly in 11 rivers out of the 55 rivers with data for all 18 years. There were no short‐term cycles in grilse proportion within rivers. We found coherence and similarity in the temporal variation in grilse proportion for rivers draining into large fjord systems. Reasons for the temporal variation in grilse proportions must be sought at a river‐specific or regional scale. River‐specific factors (water discharge, river steepness, and presence of lakes) explained a large percentage of the spatial variation in grilse proportion. Grilse proportion increased with decreasing river size (measured as mean annual water discharge) and with increasing proportion of water discharge occurring during summer (i.e., the migration season). Grilse proportion was higher in rivers located nearer to the open ocean, probably indicating an effect of early feeding on growth and maturation. Even after accounting for environmental variation at the local scale, we found large regional differences in grilse proportion. Region captured this variation more efficiently than latitude, but grilse proportion was higher in the northern part of Norway than in the more southerly part. This variability may indicate large‐scale differences in, for example, oceanic migration routes for fish originating from different regions.