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Observed streamflow of headwater catchments of the Tarim River (Central Asia) increased by about 30% over the period 1957-2004. This study aims at assessing to which extent these streamflow trends can be attributed to changes in air temperature or precipitation. The analysis includes a data-based approach using multiple linear regression and a simulation-based approach using a hydrological model. The hydrological model considers changes in both glacier area and surface elevation. It was calibrated using a multiobjective optimization algorithm with calibration criteria based on glacier mass balance and daily and interannual variations of discharge. The individual contributions to the overall streamflow trends from changes in glacier geometry, temperature, and precipitation were assessed using simulation experiments with a constant glacier geometry and with detrended temperature and precipitation time series. The results showed that the observed changes in streamflow were consistent with the changes in temperature and precipitation. In the Sari-Djaz catchment, increasing temperatures and related increase of glacier melt were identified as the dominant driver, while in the Kakshaal catchment, both increasing temperatures and increasing precipitation played a major role. Comparing the two approaches, an advantage of the simulation-based approach is the fact that it is based on process-based relationships implemented in the hydrological model instead of statistical links in the regression model. However, data-based approaches are less affected by model parameter and structural uncertainties and typically fast to apply. A complementary application of both approaches is recommended.
Throughfall, that is, the fraction of rainfall that passes through the forest canopy, is strongly influenced by rainfall and forest stand characteristics which are in turn both subject to seasonal dynamics. Disentangling the complex interplay of these controls is challenging, and only possible with long-term monitoring and a large number of throughfall events measured in parallel at different forest stands. We therefore based our analysis on 346 rainfall events across six different forest stands at the long-term terrestrial environmental observatory TERENO Northeast Germany. These forest stands included pure stands of beech, pine and young pine, and mixed stands of oak-beech, pine-beech and pine-oak-beech. Throughfall was overall relatively low, with 54-68% of incident rainfall in summer. Based on the large number of events it was possible to not only investigate mean or cumulative throughfall but also its statistical distribution. The distributions of throughfall fractions show distinct differences between the three types of forest stands (deciduous, mixed and pine). The distributions of the deciduous stands have a pronounced peak at low throughfall fractions and a secondary peak at high fractions in summer, as well as a pronounced peak at higher throughfall fractions in winter. Interestingly, the mixed stands behave like deciduous stands in summer and like pine stands in winter: their summer distributions are similar to the deciduous stands but the winter peak at high throughfall fractions is much less pronounced. The seasonal comparison further revealed that the wooden components and the leaves behaved differently in their throughfall response to incident rainfall, especially at higher rainfall intensities. These results are of interest for estimating forest water budgets and in the context of hydrological and land surface modelling where poor simulation of throughfall would adversely impact estimates of evaporative recycling and water availability for vegetation and runoff.
Field-scale subsurface flow processes are difficult to observe and monitor. We investigated the value of gravity time series to identify subsurface flow processes by carrying out a sprinkling experiment in the direct vicinity of a superconducting gravimeter. We demonstrate how different water mass distributions in the subsoil affect the gravity signal and show the benefit of using the shape of the gravity response curve to identify different subsurface flow processes. For this purpose, a simple hydro-gravimetric model was set up to test different scenarios in an optimization approach, including the processes macropore flow, preferential flow, wetting front advancement (WFA), bypass flow and perched water table rise. Besides the gravity observations, electrical resistivity and soil moisture data were used for evaluation. For the study site, the process combination of preferential flow and WFA led to the best correspondence to the observations in a multi-criteria assessment. We argue that the approach of combining field-scale sprinkling experiments in combination with gravity monitoring can be transferred to other sites for process identification, and discuss related uncertainties including limitations of the simple model used here. The study stresses the value of advancing terrestrial gravimetry as an integrative and non-invasive monitoring technique for assessing hydrological states and dynamics.
The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.org/10.588/GFZ.5.4.2018.001 (Mikolaj et al., 2018).
Many semi-arid regions are characterised by water scarcity and vulnerability of natural resources, pronounced climatic variability and social stress. Integrated studies including climatotogy, hydrology, and socio-econornic studies are required both for analysing the dynamic natural conditions and to assess possible strategies to make semi-arid regions Less vulnerable to the present and changing climate. The model introduced here dynamically describes the retationships between climate forcing, water availability, agriculture and selected societal processes. The model has been tailored to simulate the rather complex situation in the semi-and north-eastern Brazil in a quantitative manner including the sensitivity to external forcing, such as climate change. The selected results presented show the general functioning of the integrated model, with a primary focus on climate change impacts. It becomes evident that due to Large differences in regional climate scenarios, it is still impossible to give quantitative values for the most probable development, e.g., to assign probabilities to the simulated results. However, it becomes clear that water is a very crucial factor, and that an efficient and ecologically sound water management is a key question for the further development of that semi-arid region. The simulation results show that, independent of the differences in climate change scenarios, rain-fed farming is more vulnerable to drought impacts compared to irrigated farming. However, the capacity of irrigation and other water infrastructure systems to enhance resilience in respect to climatic fluctuations is significantly constrained given a significant negative precipitation trend. (c) 2005 Elsevier B.V. All rights reserved.
The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To facilitate in-depth evaluations of the effects of climate and land use changes and to separate the effects of natural and anthropogenic drivers in the region, six sites were chosen for comprehensive monitoring. In addition, at selected sites, geoarchives were used to substantially extend the instrumental records back in time. It is this combination of diverse disciplines working across different time scales that makes the observatory TERENO-NE a unique observation platform. We provide information about the general characteristics of the observatory and its six monitoring sites and present examples of interdisciplinary research activities at some of these sites. We also illustrate how monitoring improves process understanding, how remote sensing techniques are fine-tuned by the most comprehensive ground-truthing site DEMMIN, how soil erosion dynamics have evolved, how greenhouse gas monitoring of rewetted peatlands can reveal unexpected mechanisms, and how proxy data provides a long-term perspective of current ongoing changes.
In spite of the fundamental role of the landscape water balance for the Earth's water and energy cycles, monitoring the water balance and its components beyond the point scale is notoriously difficult due to the multitude of flow and storage processes and their spatial heterogeneity. Here, we present the first field deployment of an iGrav superconducting gravimeter (SG) in a minimized enclosure for long-term integrative monitoring of water storage changes. Results of the field SG on a grassland site under wet-temperate climate conditions were compared to data provided by a nearby SG located in the controlled environment of an observatory building. The field system proves to provide gravity time series that are similarly precise as those of the observatory SG. At the same time, the field SG is more sensitive to hydrological variations than the observatory SG. We demonstrate that the gravity variations observed by the field setup are almost independent of the depth below the terrain surface where water storage changes occur (contrary to SGs in buildings), and thus the field SG system directly observes the total water storage change, i.e., the water balance, in its surroundings in an integrative way. We provide a framework to single out the water balance components actual evapotranspiration and lateral subsurface discharge from the gravity time series on annual to daily timescales. With about 99 and 85% of the gravity signal due to local water storage changes originating within a radius of 4000 and 200m around the instrument, respectively, this setup paves the road towards gravimetry as a continuous hydrological field-monitoring technique at the landscape scale.
Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.
A methodology is presented to assess the impact of reservoir silting oil water availability for semiarid environments, applied to seven representative watersheds in the state of Ceara, Brazil. Water yield is computed using stochastic modelling for several reliability levels and water yield reduction is quantified for the focus areas. The yield-volume elasticity concept, which indicates the relative yield reduction in terms of relative storage capacity of the reservoirs, is presented and applied. Results chow that storage capacity was reduced by 0.2% year(-1) due to silting, that the risk of water shortage almost doubled in less than 50 years for the most critical reservoir, and that reduction of storage capacity had three times more impact oil yield reduction than the increase in evaporation. Average 90% reliable yield-volume elasticity was 0.8, which means that the global water yield (Q(90)) in Ceara is expected to diminish yearly by 388 L s(-1) due to reservoir silting
The rigorous development, application and validation of distributed hydrological models obligates to evaluate data in a spatially distributed way. In particular, spatial model predictions such as the distribution of soil moisture, runoff generating areas or nutrient-contributing areas or erosion rates, are to be assessed against spatially distributed observations. Also model inputs, such as the distribution of modelling units derived by GIS and remote sensing analyses, should be evaluated against groundbased observations of landscape characteristics. So far, however, quantitative methods of spatial field comparison have rarely been used in hydrology. In this paper, we present algorithms that allow to compare observed and simulated spatial hydrological data. The methods can be applied for binary and categorical data on regular grids. They comprise cell-by-cell algorithms, cell-neighbourhood approaches that account for fuzziness of location, and multi-scale algorithms that evaluate the similarity of spatial fields with changing resolution. All methods provide a quantitative measure of the similarity of two maps. The comparison methods are applied in two mountainous catchments in southern Germany (Brugga, 40 km<sup>2) and Austria (Löhnersbach, 16 km<sup>2). As an example of binary hydrological data, the distribution of saturated areas is analyzed in both catchments. For categorical data, vegetation zones that are associated with different runoff generation mechanisms are analyzed in the Löhnersbach. Mapped spatial patterns are compared to simulated patterns from terrain index calculations and from satellite image analysis. It is discussed how particular features of visual similarity between the spatial fields are captured by the quantitative measures, leading to recommendations on suitable algorithms in the context of evaluating distributed hydrological models.
Taking into account the climatic conditions of the semiarid region of Brazil, with its intermittent rivers and long periods of water scarcity, a dense network of surface reservoirs (on average one dam every 5 km(2)) of very different sizes has been built. The impact of such a network on water and sediment dynamics constitutes a remarkable challenge for hydrologists. The main objective of this work is to present a novel way of simulating water and sediment fluxes through such high-density reservoir networks, which enables the assessment of water and sediment retention in those structures. The new reservoir modeling approach has been coupled with the fully process-oriented and semidistributed hydrological WASA-SED model, which was tailored for semiarid hydroclimatological characteristics. This integrated modeling system was applied to the 933-km(2) Bengue catchment, located in semiarid northeastern Brazil, which has a network of 114 reservoirs with a wide range of surface areas (from 0.003 to 350 ha). The small reservoirs were grouped into size classes according to their storage capacity and a cascade routing scheme was applied to describe the upstream-downstream position of the classes; the large reservoirs were handled explicitly in the reservoir modeling approach. According to the model results, the proposed approach is capable of representing the water and sediment fluxes though the entire reservoir network with reasonable accuracy. In addition, the model shows that the dynamics of water and sediment within the Bengue catchment are strongly impacted by the presence of multiple reservoirs, which are able to retain approximately 21% of the generated runoff and almost 42% of the sediment yield of the catchment for the simulation period, from 2000 to 2012. (C) 2018 American Society of Civil Engineers.
Modelling the effects of climate change on water availability in the semi-arid of North-East Brazil
(2001)
To support scientifically sound water management in dryland environments a modelling system has been developed for the quantitative assessment of water and sediment fluxes in catchments, transport in the river system, and retention in reservoirs. The spatial scale of interest is the mesoscale because this is the scale most relevant for management of water and land resources.
This modelling system comprises process-oriented hydrological components tailored for dryland characteristics coupled with components comprising hillslope erosion, sediment transport and reservoir deposition processes. The spatial discretization is hierarchically designed according to a multi-scale concept to account for particular relevant process scales. The non-linear and partly intermittent run-off generation and sediment dynamics are dealt with by accounting for connectivity phenomena at the intersections of landscape compartments. The modelling system has been developed by means of data from nested research catchments in NE-Spain and in NE-Brazil.
In the semi-arid NE of Brazil sediment retention along the topography is the main process for sediment retention at all scales, i.e. the sediment delivery is transport limited. This kind of deposition retains roughly 50 to 60 % of eroded sediment, maintaining a similar deposition proportion in all spatial scales investigated. On the other hand, the sediment retained in reservoirs is clearly related to the scale, increasing with catchment area. With increasing area, there are more reservoirs, increasing the possibility of deposition. Furthermore, the area increase also promotes an increase in flow volume, favouring the construction of larger reservoirs, which generally overflow less frequently and retain higher sediment fractions. The second example comprises a highly dynamic Mediterranean catchment in NE-Spain with nested sub-catchments and reveals the full dynamics of hydrological, erosion and deposition features. The run-off modelling performed well with only some overestimation during low-flow periods due to the neglect of water losses along the river. The simulated peaks in sediment flux are reproduced well, while low-flow sediment transport is less well captured, due to the disregard of sediment remobilization in the riverbed during low flow.
This combined observation and modelling study deepened the understanding of hydro-sedimentological systems characterized by flashy run-off generation and by erosion and sediment transport pulses through the different landscape compartments. The connectivity between the different landscape compartments plays a very relevant role, regarding both the total mass of water and sediment transport and the transport time through the catchment.
Projected changes in compound flood hazard from riverine and coastal floods in northwestern Europe
(2020)
Compound flooding in coastal regions, that is, the simultaneous or successive occurrence of high sea levels and high river flows, is expected to increase in a warmer world. To date, however, there is no robust evidence on projected changes in compound flooding for northwestern Europe. We combine projected storm surges and river floods with probabilistic, localized relative sea-level rise (SLR) scenarios to assess the future compound flood hazard over northwestern coastal Europe in the high (RCP8.5) emission scenario. We use high-resolution, dynamically downscaled regional climate models (RCM) to drive a storm surge model and a hydrological model, and analyze the joint occurrence of high coastal water levels and associated river peaks in a multivariate copula-based approach. The RCM-forced multimodel mean reasonably represents the observed spatial pattern of the dependence strength between annual maxima surge and peak river discharge, although substantial discrepancies exist between observed and simulated dependence strength. All models overestimate the dependence strength, possibly due to limitations in model parameterizations. This bias affects compound flood hazard estimates and requires further investigation. While our results suggest decreasing compound flood hazard over the majority of sites by 2050s (2040-2069) compared to the reference period (1985-2005), an increase in projected compound flood hazard is limited to around 34% of the sites. Further, we show the substantial role of SLR, a driver of compound floods, which has frequently been neglected. Our findings highlight the need to be aware of the limitations of the current generation of Earth system models in simulating coastal compound floods.