Near Surface Hydrometeorology for Sustainable Water Management

Due to strong interactions between the land and atmosphere and the resulting feedbacks as altered by the anthropogenic changes, it is critical to quantify the surface fluxes and boundary layer properties that has direct implications on the regional evolution of hydrometeorology. This study evaluates the impact of irrigation using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model in the Snake River Basin in Idaho. Our simulation extends for the period in the growing season and compares the control and irrigation runs to assess the irrigation induced cooling on the surface energy balance. Understanding this near surface cooling is directly useful for sustainable water management under changing climate conditions in the future. We present simulated latent and sensible heat fluxes as well as air temperature, relative humidity and the depth of the planetary boundary layer (PBL) over the region

Hydrologic Modeling of Boreal Forest Ecosystems

This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM)

Preliminary Water Assessment Reports of The Test Basins of The Watch Project

This report presents the initial plans of the case studies how they link to rest of the Watch project and on which water resources they will focus. This report will function as the basis for further discussions on how to improve the integration of the case studies within the project and to develop a more general protocol for each of the case studies. Currently 5 catchments are used within the Watch project, they differ in climatic and hydro-geological features and expected climate changes: the Glomma River basin (Eastern Norway), the upper Guadiana basin (Central Spanish Plateau), the Nitra River basin (central Slovakia), the Upper-Elbe basin (part of the Elbe River) and the island of Crete. Also the water resources issues vary over these cases. Agricultural (and domestic) water use is under pressure in the Mediterranean catchments probably aggravating with the expected increase in drought frequency under future climate. The Norwegian catchment provides hydropower services under threat of precipitation increase rather than decrease. The central European catchments are threatened mainly by increased variability, i.e. increased frequencies of extremes in a densely populated environment, and river flow may need additional buffers (reservoirs) to reduce floodrisk and store water for dry period

Effects of climate model radiation, humidity and wind estimates on hydrological simulations

Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C

Climate impact research: Beyond patchwork

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 °C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so

Climate impact research: Beyond patchwork

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 degrees C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so