Search

This paper aims to evaluate sources of uncertainty in projected hydrological changes under climate change in twelve large-scale river basins worldwide, considering the mean flow and the two runoff quantiles Q (high flow), and Q (low flow). First, changes in annual low flow, annual high flow and mean annual runoff were evaluated using simulation results from a multi-hydrological-model (nine hydrological models, HMs) and a multi-scenario approach (four Representative Concentration Pathways, RCPs, five CMIP5 General Circulation Models, GCMs). Then, three major sources of uncertainty (from GCMs, RCPs and HMs) were analyzed using the ANOVA method, which allows for decomposing variances and indicating the main sources of uncertainty along the GCM-RCP-HM model chain. Robust changes in at least one runoff quantile or the mean flow, meaning a high or moderate agreement of GCMs and HMs, were found for five river basins: the Lena, Tagus, Rhine, Ganges, and Mackenzie. The analysis of uncertainties showed that in general the largest share of uncertainty is related to GCMs, followed by RCPs, and the smallest to HMs. The hydrological models are the lowest contributors of uncertainty for Q and mean flow, but their share is more significant for Q. [ABSTRACT FROM AUTHOR]

Global warming impacts the water cycle not only by changing regional precipitation levels and temporal variability, but also by affecting water flows and soil moisture dynamics. In Brandenburg, increasing average annual temperature and decreasing precipitation in summer have already been observed. For this study, past trends and future effects of climate change on soil moisture dynamics in Brandenburg were investigated, considering regional and specific spatial impacts. Special Areas of Conservation (SACs) were focused on in particular. A decreasing trend in soil water content was shown for the past by analyzing simulation results from 1951 to 2003 using the integrated ecohydrological model SWIM [Krysanova, V., Müller-Wohlfeil, D.-I., Becker, A., 1998. Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol. Model. 106, 261–289]. The trend was statistically significant for some areas, but not for the entire region. Simulated soil water content was particularly low in the extremely dry year 2003. Comparisons of simulated trends in soil moisture dynamics with trends in the average annual Palmer Drought Severity Index for the region showed largely congruent patterns, though the modeled soil moisture trends are characterized by a much higher spatial resolution. Regionally downscaled climate change projections representing the range between wetter and drier realizations were used to evaluate future trends of available soil water. A further decrease of average available soil water ranging from −4% to −15% was projected for all climate realizations up to the middle of the 21st century. An average decrease of more than 25mm was simulated for 34% of the total area in the dry realization. Available soil water contents in SACs were generally higher and trends in soil moisture dynamics were lower mainly due to their favorable edaphic conditions. Stronger absolute and relative changes in the simulated trends for the past and future were shown for SACs within Brandenburg than for the state as a whole, indicating a high level of risk for many wetland areas. Nonetheless, soil water content in SACs is expected to remain higher than average under climate change conditions as well, and SACs therefore have an important buffer function under the projected climate change. They are thus essential for local climate and water regulation and their status as protected areas in Brandenburg should be preserved. [Copyright &y& Elsevier]

This study assesses future flood risk in the Niger River Basin (NRB), for the first time considering the simultaneous effects of both projected climate change and land use changes. For this purpose, an ecohydrological process-based model (SWIM) was set up and validated for past climate and land use dynamics of the entire NRB. Model runs for future flood risks were conducted with an ensemble of 18 climate models, 13 of them dynamically downscaled from the CORDEX Africa project and five statistically downscaled Earth System Models. Two climate and two land use change scenarios were used to cover a broad range of potential developments in the region. Two flood indicators (annual 90th percentile and the 20-year return flood) were used to assess the future flood risk for the Upper, Middle and Lower Niger as well as the Benue. The modeling results generally show increases of flood magnitudes when comparing a scenario period in the near future (2021–2050) with a base period (1976–2005). Land use effects are more uncertain, but trends and relative changes for the different catchments of the NRB seem robust. The dry areas of the Sahelian and Sudanian regions of the basin show a particularly high sensitivity to climatic and land use changes, with an alarming increase of flood magnitudes in parts. A scenario with continuing transformation of natural vegetation into agricultural land and urbanization intensifies the flood risk in all parts of the NRB, while a “regreening” scenario can reduce flood magnitudes to some extent. Yet, land use change effects were smaller when compared to the effects of climate change. In the face of an already existing adaptation deficit to catastrophic flooding in the region, the authors argue for a mix of adaptation and mitigation efforts in order to reduce the flood risk in the NRB. [ABSTRACT FROM AUTHOR]

Highlights: [•] Nutrient retention cannot be neglected in eco-hydrological watershed modelling. [•] Nutrients coming from diffuse sources do not need in-stream river processes. [•] Retention in soils and rivers is needed to well capture all nutrient concentrations. [•] Most complex model approach for river processes delivers best seasonal dynamics. [•] High complexity requires high calibration effort but is not necessary in all cases. [Copyright &y& Elsevier]

Summary: The replacement of undisturbed tropical forest with cattle pasture has the potential to greatly modify the hydrology of small watersheds and the fluxes of solutes. We examined the fluxes of water, Cl−, , Na+, K+, Mg2+ and Ca2+ in different flow paths in ∼1ha catchments of undisturbed open tropical rainforest and a 20 year-old pasture established from forest in the southwestern Brazilian Amazon state of Rondônia. Storm flow discharge was 18% of incident rainfall in pasture, but only 1% in forest. Quickflow predominated over baseflow in both catchments and in both wet and dry seasons. In the pasture, groundwater and quickflow were important flow paths for the export of all solutes. In the forest, quickflow was important for export, but all other solutes were exported primarily by groundwater outflow. Both catchments were sinks for and Ca2+, and sources of Na+. The pasture catchment also lost K+ and Mg2+ because of higher overland flow frequency and volume and to cattle excrement. These results show that forest clearing dramatically influences small watershed hydrology by increasing quickflow and water export to streams. They also indicate that tropical forest watersheds are highly conservative for most solutes but that pastures continue to lose important cations even decades after deforestation and pasture establishment. [Copyright &y& Elsevier]

This study aimed to investigate the influence of hydrological model calibration/validation on discharge projections for three large river basins (the Rhine, Upper Mississippi and Upper Yellow). Three hydrological models (HMs), which have been firstly calibrated against the monthly discharge at the outlet of each basin (simple calibration), were re-calibrated against the daily discharge at the outlet and intermediate gauges under contrast climate conditions simultaneously (enhanced calibration). In addition, the models were validated in terms of hydrological indicators of interest (median, low and high flows) as well as actual evapotranspiration in the historical period. The models calibrated using both calibration methods were then driven by the same bias corrected climate projections from five global circulation models (GCMs) under four Representative Concentration Pathway scenarios (RCPs). The hydrological changes of the indicators were represented by the ensemble median, ensemble mean and ensemble weighted means of all combinations of HMs and GCMs under each RCP. The results showed moderate (5–10%) to strong influence (> 10%) of the calibration methods on the ensemble medians/means for the Mississippi, minor to moderate (up to 10%) influence for the Yellow and minor (< 5%) influence for the Rhine. In addition, the enhanced calibration/validation method reduced the shares of uncertainty related to HMs for three indicators in all basins when the strict weighting method was used. It also showed that the successful enhanced calibration had the potential to reduce the uncertainty of hydrological projections, especially when the HM uncertainty was significant after the simple calibration. [ABSTRACT FROM AUTHOR]

We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi, upper Niger, Rhine and Tagus. Relative changes in simulated mean annual runoff (MAR) and four indicators of high and low extreme flows are compared between the two ensembles. The ensemble median values of changes in runoff with three different scenarios of global-mean warming (1, 2 and 3 °C above pre-industrial levels) are generally similar between the two ensembles, although the ensemble spread is often larger for the Glob-HM ensemble. In addition the ensemble spread is normally larger than the difference between the two ensemble medians. Whilst we find compelling evidence for projected runoff changes for the Rhine (decrease), Tagus (decrease) and Lena (increase) with global warming, the sign and magnitude of change for the other catchments is unclear. Our model results highlight that for these three catchments in particular, global climate change mitigation, which limits global-mean temperature rise to below 2 °C above preindustrial levels, could avoid some of the hydrological hazards that could be seen with higher magnitudes of global warming. [ABSTRACT FROM AUTHOR]

Global gridded precipitation is an essential driving input for hydrologic models to simulate runoff dynamics in large river basins. However, the data often fail to adequately represent precipitation variability in mountainous regions due to orographic effects and sparse and highly uncertain gauge data. Water balance simulations in tropical montane regions covered by cloud forests are especially challenging because of the additional water input from cloud water interception. The ISI-MIP2 hydrologic model ensemble encountered these problems for Andean sub-basins of the Upper Amazon Basin, where all models significantly underestimated observed runoff. In this paper, we propose simple yet plausible ways to adjust global precipitation data provided by WFDEI, the WATCH Forcing Data methodology applied to ERA-Interim reanalysis, for tropical montane watersheds. The modifications were based on plausible reasoning and freely available tropics-wide data: (i) a high-resolution climatology of the Tropical Rainfall Measuring Mission (TRMM) and (ii) the percentage of tropical montane cloud forest cover. Using the modified precipitation data, runoff predictions significantly improved for all hydrologic models considered. The precipitation adjustment methods presented here have the potential to enhance other global precipitation products for hydrologic model applications in the Upper Amazon Basin as well as in other tropical montane watersheds. [ABSTRACT FROM AUTHOR]

The Soil and Water Integrated Model (SWIM) is a continuous-time semi-distributed ecohydrological model, integrating hydrological processes, vegetation, nutrients and erosion. It was developed for impact assessment at the river basin scale. SWIM is coupled to GIS and has modest data requirements. During the last decade SWIM was extensively tested in mesoscale and large catchments for hydrological processes (discharge, groundwater), nutrients, extreme events (floods and low flows), crop yield and erosion. Several modules were developed further (wetlands and snow dynamics) or introduced (glaciers, reservoirs). After validation, SWIM can be applied for impact assessment. Four exemplary studies are presented here, and several questions important to the impact modelling community are discussed. For which processes and areas can the model be used? Where are the limits in model application? How to apply the model in data-poor situations or in ungauged basins? How to use the model in basins subject to strong anthropogenic pressure? Editor D. Koutsoyiannis; Associate editor C. Perrin [ABSTRACT FROM AUTHOR]

Since several destructive floods have occurred in Germany in the last decades, it is of considerable interest and relevance ( e.g., when undertaking flood defense design) to take a closer look at the climatic factors driving the changes in flood hazard in Germany. Even if there also exist non-climatic factors controlling the flood hazard, the present paper demonstrates that climate change is one main driver responsible for the increasing number of floods. Increasing trends in temperature have been found to be ubiquitous in Germany, with impact on air humidity and changes in (intense) precipitation. Growing trends in flood prone circulation pattern and heavy precipitation are significant in many regions of Germany over a multi-decade interval and this can be translated into the rise of flood hazard and flood risk. [ABSTRACT FROM AUTHOR]

Abstract: Water quality modeling was done in order to evaluate possible impact of climate change on water quality in the Jizera catchment regarding nitrate pollution. The research was performed by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modeling period was from 1981 to 2001. After the calibration of hydrological processes in the catchment, water quality (nitrate) modeling was carried out. The emissions from point sources and agricultural diffuse sources were taken into account. The influence of climate change on water quality in the Jizera catchment was assessed by using the outputs of two approaches to regional climate modeling: dynamical (REMO) and statistical (STAR). The two approaches projected different future discharge and nitrate nitrogen loads in the Jizera catchment. REMO projected increased discharges and nitrate loads in winter consequently with projected increased precipitation. The nitrate loads in summer are influenced mainly by changes in precipitation. The statistical approach STAR projected decreased nitrate loads because of decreased precipitation. More intensive rain causes increased load mainly in summer and increased temperature in winter contributes to increased discharge. [Copyright &y& Elsevier]

Time series of the average annual Palmer drought severity index (PDSI) and standardized precipitation index (SPI) were calculated for 483 meteorological stations in China using monthly data from 1961 to 2005. The time series were analyzed for 10 large regions covering the territory of China and represented by seven river basins and three areas in the southeast, southwest, and northwest. Results show that the frequencies of both dry and wet years for the whole period are lower for southern basins than for the northern ones when estimated by PDSI but very similar for all basins when calculated by SPI. The frequencies of dry and wet years calculated for 5- and 15-yr subperiods by both indices show the upward dry trends for three northeastern basins, Songhuajiang, Liaohe, and Haihe; a downward dry trend for the northwest region; a downward wet trend for the Yellow River basin; and an upward wet trend for the northwest region. Trend detection using PDSI indicates statistically significant negative trends for many stations in the northeastern basins (Songhuajiang, Liaohe, Haihe, and Yellow) and in the middle part of the Yangtze, whereas statistically significant positive trends were found in the mountainous part of the northwest region and for some stations in the upper and lower Yangtze. A moderately high and statistically significant correlation between the percentage of runoff anomaly (PRA) and the annual average PDSI and SPI was found for six large rivers. The results confirm that PDSI and SPI indices can be used to describe the tendency of dryness and wetness severity and for comparison in climate impact assessment. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1°C, 2°C and 3°C" which appeared in the December 9, 2016 issue.