Peter Fiener

Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment.

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance.

Hydrological modeling with SWAT in a monsoon-driven environment: Experience from The Western Ghats, India

Monsoon regions are characterized by a pronounced seasonality of rainfall. Model-based analysis of water resources in such an environment has to take account of the specific natural conditions and the associated water management. Especially, plant phenology, which is predominately water driven, and water management, which aims at reducing water shortage, are of primary importance. The aim of this study is to utilize the Soil and Water Assessment Tool (SWAT) in a monsoon-driven region in the Indian Western Ghats by using mainly generally available input data and to evaluate the model performance under these conditions. The test site analyzed in this study is the meso-scale catchment of the Mula and Mutha Rivers (2036 km 2 ) upstream of the city of Pune, India. Most input data were derived from remote sensing products or from international archives. Forest growth in SWAT was modified to account for the seasonal limitation of water availability. Moreover, a dam management scheme was derived by combining general dam management rules with reservoir storage capacity and estimated monthly outflow rates from river discharge. With these model adaptations, SWAT produced reasonable results when compared to mean daily discharge measured in three of four subcatchments during the rainy season (Nash-Sutcliffe efficiencies 0.58, 0.63, and 0.68). The weakest performance was found at the gauge downstream of four dams, where the simple dam management scheme failed to match the combined management effects of the four dams on river discharge (Nash-Sutcliffe efficiency 0.10). Water yield was underestimated by the model, especially in the smallest (headwater) subcatchment (99 km 2 ). Due to the absence of rain gauges in these headwater areas, the extrapolation errors of rainfall estimates based on measurements at lower elevations are expected to be large. Moreover, there is some indication that evapotranspiration might be underestimated. Nevertheless, it can be concluded that using generally available data in SWAT model studies of monsoon-driven catchments provides reasonable results, if key characteristics of monsoon regions are accounted for and processes are parameterized accordingly.

Invasive floating macrophytes reduce greenhouse gas emissions from a small tropical lake

Floating macrophytes, including water hyacinth (Eichhornia crassipes), are dominant invasive organisms in tropical aquatic systems, and they may play an important role in modifying the gas exchange between water and the atmosphere. However, these systems are underrepresented in global datasets of greenhouse gas (GHG) emissions. This study investigated the carbon (C) turnover and GHG emissions from a small (0.6 km2) water-harvesting lake in South India and analysed the effect of floating macrophytes on these emissions. We measured carbon dioxide (CO2) and methane (CH4) emissions with gas chambers in the field as well as water C mineralization rates and physicochemical variables in both the open water and in water within stands of water hyacinths. The CO2 and CH4 emissions from areas covered by water hyacinths were reduced by 57% compared with that of open water. However, the C mineralization rates were not significantly different in the water between the two areas. We conclude that the increased invasion of water hyacinths and other floating macrophytes has the potential to change GHG emissions, a process that might be relevant in regional C budgets.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Effects of hydrodynamically rough grassed waterways on dissolved reactive phosphorus loads coming from agricultural watersheds.

A modified type of grassed waterway (GWW) with large hydrodynamic roughness has proven ability to reduce sediment load and surface runoff under conditions where best management practices on the delivering fields reduce sediment inputs that could otherwise damage the grass cover. It is unknown how such a GWW affects the loading of surface runoff with dissolved reactive phosphorus (DRP). The effect on DRP was tested in a landscape-scale study where DRP concentrations and loads in surface runoff were measured in two watersheds in which GWWs were newly installed and increased in effectiveness over time. Both watersheds were compared with paired watersheds without GWW installation; all watersheds were continuously monitored over 5 yr (1993-1997). Additionally, DRP concentrations were measured in open field and throughfall precipitation under growing grass and crops in field experiments, and DRP concentrations in surface runoff from straw covered surfaces were determined with laboratory rainfall simulation experiments. Dissolved reactive P in throughfall for the different cover types was highly variable, and the highest concentrations (up to 2.8 mg L(-1)) occurred especially during flowering of the respective crop and after frost events. Dissolved reactive P concentrations in runoff from straw-covered surfaces were slightly higher compared with those from bare soil. On average, there was a small difference in DRP concentrations between throughfall under growing crops and grass and in runoff from bare or straw covered soil surfaces. Hence, the introduction of a relatively small grassed area has little effect on the DRP concentration in surface runoff from the total watershed. This finding was supported by the watershed data, where watersheds with and without GWW showed similar DRP concentrations. No change in DRP concentrations occurred over the 5-yr period. Such GWWs will thus reduce the DRP load analogously to the reduction in total surface runoff.

Comment on "Rainfall erosivity in Europe" by Panagos et al. (Sci. Total Environ., 511, 801-814, 2015)

Recently a rainfall erosivity map has been published. We show that the values of this map contain considerable bias because (i) the temporal resolution of the rain data was insufficient, which likely underestimates rain erosivity by about 20%, (ii) no attempt had been included to account for the different time periods that were used for different countries, which can modify rain erosivity by more than 50%, (iii) and likely precipitation data had been used instead of rain data and thus rain erosivity is overestimated in areas with significant snowfall. Furthermore, the seasonal distribution of rain erosivity is not provided, which does not allow using the erosivity map for erosion prediction in many cases. Although a rain erosivity map for Europe would be highly desirable, we recommend using the national erosivity maps until these problems have been solved. Such maps are available for many European countries.

Links among warming, carbon and microbial dynamics mediated by soil mineral weathering

Quantifying soil carbon dynamics is of utmost relevance in the context of global change because soils play an important role in land–atmosphere gas exchange. Our current understanding of both present and future carbon dynamics is limited because we fail to accurately represent soil processes across temporal and spatial scales, partly because of the paucity of data on the relative importance and hierarchical relationships between microbial, geochemical and climatic controls. Here, using observations from a 3,000-kyr-old soil chronosequence preserved in alluvial terrace deposits of the Merced River, California, we show how soil carbon dynamics are driven by the relationship between short-term biotic responses and long-term mineral weathering. We link temperature sensitivity of heterotrophic respiration to biogeochemical soil properties through their relationship with microbial activity and community composition. We found that soil mineralogy, and in particular changes in mineral reactivity and resulting nutrient availability, impacts the response of heterotrophic soil respiration to warming by altering carbon inputs, carbon stabilization, microbial community composition and extracellular enzyme activity. We demonstrate that biogeochemical alteration of the soil matrix (and not short-term warming) controls the composition of microbial communities and strategies to metabolize nutrients. More specifically, weathering first increases and then reduces nutrient availability and retention, as well as the potential of soils to stabilize carbon.Soil weathering, rather than short-term warming, controls microbial community composition, nutrient availability and soil carbon content, according to observations from a 3-Myr-old soil chronosequence preserved in river terraces in California.

Human-induced and natural carbon storage in floodplains of the Central Valley of California.

Active floodplains can putatively store large amounts of organic carbon (SOC) in subsoils originating from catchment erosion processes with subsequent floodplain deposition. Our study focussed on the assessment of SOC pools associated with alluvial floodplain soils that are affected by human-induced changes in floodplain deposition and in situ SOC mineralisation due to land use change and drainage. We evaluated depth-dependent SOC contents based on 23 soil cores down to 3 m and 10 drillings down to 7 m in a floodplain area of the lower Cosumnes River. An estimate of 266 Mg C ha-1 or about 59% of the entire SOC stored within the 7 m profiles was found in the upper 2 m. Most profiles (n = 25) contained discrete buried A horizons at depths of approximately 0.8 m. These profiles had up to 130% higher SOC stocks. The mean δ13C of all deep soil profiles clearly indicated that arable land use has already altered the stable isotopic signature in the first meter of the profile. Radiocarbon dating showed that the 14C age in the buried horizon was younger than in overlaying soils indicating a substantial sedimentation phase for the overlaying soils. An additional analysis of total mercury contents in the soil profiles indicated that this sedimentation was associated with upstream hydraulic gold mining after the 1850s. In summary, deep alluvial soils in floodplains store large amounts of SOC not yet accounted for in global carbon models. Historic data give evidence that large amounts of sediment were transported into the floodplains of most rivers of the Central Valley and deposited over organically rich topsoil, which promoted the stabilization of SOC, and needs to be considered to improve our understanding of the human-induced interference with C cycling.

Resistance in Steep Open Channels due to Randomly Distributed Macroroughness Elements at Large Froude Numbers

AbstractEnergy loss in a steep open channel due to randomly spaced spherically shaped macroroughness elements such as boulders was investigated using a three-dimensional fluid dynamics solver. Firs...

Topsoil Organic Carbon Content

Soil organic carbon (SOC) is a key soil component. SOC stores large amounts of carbon and it also affects water fluxes as well as the availability of nutrients. Soil water fluxes are impacted by SOC directly due to its effect upon soil hydraulic parameters. Also many indirect effects of SOC upon water fluxes have to be recognised, such as the impact upon plant growth and nitrogen turnover. SOC maps for all modelled soil layers in the DANUBIA simulation system for the Upper Danube watershed are therefore a necessary prerequisite to model plant growth, soil nitrogen turnover and soil water fluxes. For the majority of the Upper Danube watershed, these maps were easily derived from the 1:1,000,000 soil map (BUK 1000, BGR, Bodenubersichtskarte 1:1 Million. Bundesanstalt fur Geowissenschaften und Rohstoffe, Berlin, 1995). The BUK 1000 distinguishes 33 different soil types within the Upper Danube catchment. Soil properties including SOC content are associated to soil-type-specific pedogenetic horizons. The SOC content and the C/N ratios for each of the soil layers were derived as a weighted mean of the SOC contents given for the BUK 1000 soil layers. The BUK 1000 does not cover areas outside of Germany. For these mainly alpine regions, the SOC contents were estimated using a three-step rule-based approach by (a) establishing a statistical relationship between soil-type unit and elevation, (b) estimating the SOC based on the assigned soil type and (c) selecting the predominate soil type for grid cells with multiple soil types (majority principle).