Martinus S. Krol

Identification and classification of uncertainties in the application of environmental models

In the support of environmental management, models are frequently used. The outcomes of these models however, rarely show a perfect resemblance to the real-world system behavior. This is due to uncertainties, introduced during the process of abstracting information about the system to include it in the model. To provide decision makers with realistic information about these model outcomes, uncertainty analysis is indispensable. Because of the multiplicity of frameworks available for uncertainty analysis, the outcomes of such analyses are rarely comparable. In this paper a method for structured identification and classification of uncertainties in the application of environmental models is presented. We adapted an existing uncertainty framework to enhance the objectivity in the uncertainty identification process. Two case studies demonstrate how it can help to obtain an overview of unique uncertainties encountered in a model. The presented method improves the comparability of uncertainty analyses in different model studies and leads to a coherent overview of uncertainties affecting model outcomes.

Regional integrated modelling of climate change impacts on natural resources and resource usage in semi-arid Northeast Brazil

Semi-arid regions are characterised by a high vulnerability of natural resources to climate change, pronounced climatic variability and often by water scarcity and related social stress. The analysis of the dynamics of natural conditions and the assessment of possible strategies to cope with drought-related problems require an integration of diverse knowledge including climatology, hydrology, and socio-economics. The integrated model introduced here dynamically describes the relationships between climate forcing, water availability, agriculture and selected societal processes. The model has been designed to simulate the complex human-environment system in semi-arid Northeast Brazil quantitatively and is applied to study the sensitivity of regional natural resources and socio-economy to climate change. The validity of the model is considered. n nClimate change is concluded to have an enormous potential impact on the region. River flow, water storage and irrigated production are specifically affected, assuming a continuous regional development and unfavourable but plausible changes in climate. Under plausible favourable changes in climate, these variables remain stressed. The impact of the integrated model and its applications on present policy making and possible future roles are briefly discussed.

Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region

Abstractn Abstract Water resources in dryland areas are often provided by numerous surface reservoirs. As a basis for securing future water supply, the dynamics of reservoir systems need to be simulated for large river basins, accounting for environmental change and an increasing water demand. For the State of Ceará in semiarid Northeast Brazil, with several thousands of reservoirs, a simple deterministic water balance model is presented. Within a cascade-type approach, the reservoirs are grouped into six classes according to storage capacity, rules for flow routing between reservoirs of different size are defined, and water withdrawal and return flow due to human water use is accounted for. While large uncertainties in model applications exist, particularly in terms of reservoir operation rules, model validation against observed reservoir storage volumes shows that the approach is a reasonable simplification to assess surface water availability in large river basins. The results demonstrate the large impact of reservoir storage on downstream flow and stress the need for a coupled simulation of runoff generation, network redistribution and water use.

Potential of using remote sensing techniques for global assessment of Water Footprint of crops.

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use.

The water footprint of Tunisia from an economic perspective

This paper quantifies and analyses the water footprint of Tunisia at national and sub-national level, assessing green, blue and grey water footprints for the period 1996–2005. It also assesses economic water and land productivities related to crop production for irrigated and rain-fed agriculture, and water scarcity. The water footprint of crop production gave the largest contribution (87%) to the total national water footprint. At national level, tomatoes and potatoes were the main crops with relatively high economic water productivity, while olives and barley were the main crops with relatively low productivity. In terms of economic land productivity, oranges had the highest productivity and barley the lowest. South Tunisia had the lowest economic water and land productivities. Economic land productivity was found to explain more of the current production patterns than economic water productivity, which may imply opportunities for water saving. The total blue water footprint of crop production represented 31% of the total renewable blue water resources, which means that Tunisia as a whole experienced significant water scarcity. The blue water footprint on groundwater represented 62% of the total renewable groundwater resources, which means that the country faced severe water scarcity related to groundwater.

The semi-Arid integrated model (SIM), a regional integrated model assessing water availability, vulnerability, of ecossytems and society in NE-Brazil

Northeastern Brazil, an example of vulnerable semi-arid regions on the earth, is characterised by water scarcity and vulnerability of natural resources, pronounced climatic variability and social stress situations. Integrated studies involving hydrology, ecology, meteorology, climatology, pedology, agronomy, and social and economic sciences are required not only for analysing consequences of the adverse natural conditions but also to assess possible strategies to make semi-arid regions less vulnerable to the present and changing climate. nIntegrated modelling of the relationships between water availability, quality of life and migration, including aspects of global change processes, in the Semi-arid Integrated Model (SIM) serves to understand the dynamics of the system. An overview of the concept, structure and application results of the integrated model are given. n nA sensitivity study on climate change illustrates potentially significant adverse effects on the region. Moreover, it shows that a regional integrated model is a suitable tool for complex and interdisciplinary studies. The present version of SIM still is in a development phase, especially in its representation of socio-economic processes.

Water Scarcity Under Scenarios for Global Climate Change and Regional Development in Semiarid Northeastern Brazil

Abstract The state of Ceará, located in semiarid northeastern Brazil, suffers under irregularly recurring droughts that go along with water scarcity. Structural policies to control and reduce water scarcity, as water supply and demand management, should be seen as long-term planning, and thus must consider climate change and regional development. To this end, the present research proposes a model-based global change scenario. Water stress is assessed for 184 municipalities in Ceará between 2001 and 2025. For this purpose, four global change scenarios are developed, considering both global climate change and the effects of development policies. Climatic, hydrological, and water use models are applied and a proposed index computed for identification of long-term water stress. Application of the methodology in the focus area shows that, if no effective intervention measures are taken, up to almost 60 percent of the municipalities of the state may suffer under long-term water scarcity by 2025. On average, municipalities in the state of Ceará have a water shortage probability for the next 25 years ranging from 9 percent to 20 percent annually, depending on the scenario. The 10 percent most stressed municipalities have a probability of over 80 percent annually of facing water scarcity in the scenario period (25 years). Results also show that a decentralized development policy can compensate for the possible severe effects of climatic trends on future water availability over the scenario period.

Balance between calibration objectives in a conceptual hydrological model

Abstract Three different measures to determine the optimum balance between calibration objectives are compared: the combined rank method, parameter identifiability and model validation. Four objectives (water balance, hydrograph shape, high flows, low flows) are included in each measure. The contributions of these objectives to the specific measure are varied to find the optimum balance between the objectives for each measure. The methods are applied to nine middle-sized catchments, using a typical conceptual hydrological model. The results indicate that differences in the optimum balance between the combined rank method and parameter identifiability on the one hand, and model validation on the other, are considerable. The theoretical optimum balance would be a situation without trade-off between single objectives. For some catchments and measures, this situation is closely approximated. On average, the performance of combined rank method is somewhat better than that of parameter identifiability (respectively 3.6% and 5.0% below the theoretical optimum), where the performance of model validation is considerably lower (22.4% below the theoretical optimum). These results are supported by additional validation tests which gave robust results for the combined rank measure and the parameter identifiability measure, and less robust results for the model validation measure. Citation Booij, M. J. & Krol, M. S. (2010) Balance between calibration objectives in a conceptual hydrological model. Hydrol. Sci. J. 55(6), 1017–1032.

Hydrology and hydraulics expertise in participatory processes for climate change adaptation in the Dutch Meuse

Many scientists feel that scientific outcomes are not sufficiently taken into account in policy-making. The research reported in this paper shows what happens with scientific information during such a process. In 2001 the Dutch Ministry of Transport, Public Works and Water Management commissioned their regional office in Limburg to assess how flood management objectives could be achieved in future in the Dutch Meuse valley, assuming climate change will increase peak discharges. To ensure political support, regional discussion rounds were to help assess the measures previously identified. This paper discusses the ways in which hydrological and hydraulic expertise was input, understood and used in this assessment process. Project participants as a group had no trouble contesting assumptions and outcomes. Nevertheless, water expertise was generally accepted as providing facts, once basic choices such as starting situation had been discussed and agreed. The technical constraints determined that politically unacceptable measures would have to be selected to achieve the legally binding flood management objective. As a result, no additional space will be set aside for future flood management beyond the already reserved floodplain. In this case, political arguments clearly prevail over policy objectives, with hydraulic expertise providing decisive arbitration between the two.

Analysis of long-term terrestrial water storage variations in Yangtze River basin

In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA’s PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets.