Physiographic Properties Research Articles

On the Ability of LIDAR Snow Depth Measurements to Determine or Evaluate the HRU Discretization in a Land Surface Model

To find the adequate spatial model discretization scheme, which balances the models capabilities and the demand for representing key features in reality, is a challenging task. It becomes even more challenging in high alpine catchments, where the variability of topography and meteorology over short distances strongly influences the distribution of snow cover, the dominant component in the alpine water cycle. For the high alpine Research Catchment Zugspitze (RCZ) a new method for objective delineation of hydrological response units (HRUs) using a time series of high resolution LIDAR derived snow depth maps and the physiographic properties of the RCZ is introduced. Via principle component analysis (PCA) of these maps, a dominant snow depth pattern, that turned out to be largely defined during the (winter) accumulation period was identified. This dominant pattern serves as a reference for HRU delineations on the basis of cluster analyses of the catchment’s physiographic properties. The method guarantees for an appropriate, objective, spatial discretization scheme, which allows for a reliable and meaningful reproduction of snow cover variability with the Cold Regions Hydrological Model—at the same time avoiding significant increase of computational demands. Different HRU schemes were evaluated with measured snow depth and the comparison of their model results identified significant differences in model output and best performance of the scheme which best represents measured snow depth distribution.

Evaluation of Filtering Methods for Hydrograph Separation in Small Agricultural Watersheds in Québec, Canada

HighlightsAgricultural hydrology is complex due to the management of surface and subsurface flow to increase productivity.This study provides an interpretation of hydrological functioning, using a geochemical tracer (electrical conductivity) as a reference method, for hydrograph separation and evaluation of filtering methods.Filtering method efficiency must be interpreted according to season, year, watershed relief, and management practices.Routine application of basic filtering concepts is not sufficient to address the heterogeneity of hydrological processes in agricultural watersheds.Abstract. Streamflow hydrographs summarize the behavior of watersheds. Their separation into quick and slow components requires hydrological knowledge of the specific drainage area. To better understand the hydrological response of 14 small agricultural watersheds in Québec, Canada, covering different physiographic attributes ranging from lowlands to hilly and steep landscapes, streamflow electrical conductivity was used as a geochemical tracer. These agricultural watersheds have undergone significant management practices, including artificial drainage. The objective of this research was to evaluate the performance of existing automated filter methods for hydrograph separation (BFLOW, UKIH, PART, FIXED, SLIDE, LOCMIN, and Eckhardt). The geochemical method was used as a reference for comparison with the filter methods. Comparison of the slow flow estimates from non-calibrated filters, using a MANOVA model, showed that the filter performance increased under conditions with high contributions of quick runoff to the stream, such as during snowmelt (spring season), during heavy precipitation, and in subwatersheds with landscape conditions more prone to quick runoff. However, filter performance decreased as hydrological processes predisposed more flow to slower pathways, typically in summer and fall, as well as in lowland landscapes generally associated with high rates of tile drainage rather than in hilly and steep relief. Underlying the filter assumptions is the classic concept of a rainfall event with quick runoff as the main source of the drainage area response. Thus, slow flow is associated with a low threshold response. Eckhardt filter simulations were in good agreement with the geochemical method after calibration, based on model statistical measures (R, NSE, and PBIAS). However, larger errors were associated with higher flow values. The slow flow overestimations were more pronounced during periods of extreme events, i.e., spring runoff and heavy precipitation. The linear concept of the Eckhardt filter yields no information on slow flow response behavior that could be useful in capturing its temporal variability. Because the routing of water has been managed to improve agricultural productivity, these hydrological modifications resulted in a more complex slow flow response. The performance of filtering methods is thus affected. Therefore, simplifications of filter assumptions are less likely to provide more effective estimates of slow flow. Furthermore, given the heterogeneity of hydrological processes due to seasonal climatic characteristics, the routine application of basic filter concepts is not sufficient to address the variable nature of the hydrological response. The variability scale of geochemical separation, from regional (agro-climatic) to local (adjacent watersheds), proved that it is always relevant to have adequate separation. However, the validation of filters without a tracer is limited and almost unsuitable for these agricultural watersheds. Keywords: Agricultural watershed, Artificial drainage, Electrical conductivity, Filtering method, Geochemical method, Hydrograph separation, MANOVA, Quick flow, Slow flow, Tile drainage.

Copula Theory as a Generalized Framework for Flow‐Duration Curve Based Streamflow Estimates in Ungaged and Partially Gaged Catchments

AbstractFlow‐duration curve (FDC) based streamflow estimation methods involve estimating an FDC at an ungaged or partially gaged location and using the time series of nonexceedance probabilities estimated from donor streamgage sites to generate estimates of streamflow. We develop a mathematical framework to illustrate the connection between copulas and prior FDC‐based approaches. The performance of copula methods is compared to several other streamflow estimation methods using a decade of daily streamflow data from 74 sites located within two river basins in the southeast United States with different climate characteristics and physiographic properties. We show that copula approaches: (1) outperform other methods in the limiting case of perfect information with regard to the rank‐based correlation structure and FDCs across the gaging network; (2) provide a hedge against poor performance when donor information becomes sparser and less informative; (3) outperform other methods when used for partially gaged sites with several years of available data; and (4) remain a competitive albeit nondominating method for ungaged sites and partially gaged sites with limited data when realistic error is introduced in the estimation of FDCs and correlations across the gaging network.

Identification of homogeneous regions in terms of flood seasonality using a complex network approach

Catchment classification aids in the identification of homogeneous regions in which catchments have similar flood timing and corresponding climatic drivers. As a new classification scheme from complex network theory, the community detection method is introduced to classify 242 catchments in the United States based on flood seasonality. The robustness of this method is tested by calculating the Adjusted Rank Index between the classification results from different random subsets of the 242 catchments and different flood sampling methods. In addition, three network metrics (network density, centrality, and k-core nucleus) are used to further unravel the hydrological connections within each community of catchments. Catchments with similar flood seasonality cluster into six large communities, while catchments in sparsely gauged areas or with unique physiographic properties are isolated from large communities. High values of the Adjusted Rank Index show the robustness of the community detection method for catchment classification. The results indicate that the complex network is valid for use in classifying catchments based on flood seasonality. Moreover, for each community, the network metrics are potential descriptors of: (a) the degree of homogeneity, (b) the representativeness of any catchment, and (c) the spatial scale of synchronized floods. Therefore, the complex network is able to characterize the interconnections between catchments within the community.

A statistical approach for the estimation of water quality characteristics of ungauged streams/watersheds under stationary conditions

Water quality and quantity data are essential for water resources management, but historical records are not always available at sites where information is required, especially for water quality (WQ) data because of the high costs of implementing and operating water quality monitoring networks. This leads to the impossibility/impracticality of monitoring all streams/watersheds in a region under monitoring. A novel statistical approach is proposed for the estimation of WQ characteristics (25th, 50th, and 75th percentiles) at ungauged streams/watersheds. The proposed approach is based on developing a WQ causes-effects functional relationship, which has not been done before. The WQ causes are represented by the watershed physiographic (natural and anthropogenic) attributes and the effects are represented by the WQ characteristics. For a target ungauged stream/watershed: (i) a canonical correlation analysis-based-neighborhood approach was applied to identify homogeneous gauged watersheds; and (ii) nonlinear regression models were then calibrated using data available at the selected gauged watersheds to develop the causes-effects functional relationship between the physiographic attributes as predictors, and WQ characteristics as dependent variables. Once the regression models were validated, the physiographic characteristics of the target ungauged stream/watershed were used to estimate its WQ characteristics. The jack-knife validation method was applied to evaluate the proposed statistical approach using 50 gauged streams from the Nile-Delta of Egypt. Results showed accurate and precise estimation of the Electric Conductivity and Sodium percentiles. For Iron, relatively less precision was obtained due to the absence of attributes that can describe the Iron concentrations.

Climate change impact assessment on the potential rubber cultivating area in the Greater Mekong Subregion

In order to map potential shifts of rubber (Hevea brasiliensis) cultivation as a consequence of the ongoing climate change in the Greater Mekong Subregion (GMS), we applied rule-based classifications to a selection of nine gridded climatic data projections (precipitation and temperature, and global circulation models (GCMs)). These projections were used to form an ensemble model set covering the representative concentration pathways (RCPs) 4.5 and 8.5 of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change at three future time sections: 2030, 2050 and 2070. We used a post classification ensemble formation technique based on a majority outcome of the classification to not only provide an ensemble projection but also to spatially track and weight the disagreements between the classified GCMs. A similar approach was used to form an ensemble model aggregating the involved climatic factors. The level of agreement between the ensemble projections and GCM products was assessed for each climatic factor separately, and also at the aggregate level. Shifting zones with high confidence were clustered based on their land use composition, physiographic attributes and proximity. Following the same ensemble formation technique and by setting a 28 °C threshold for annual mean temperature, we mapped areas prone to exposure to potentially excessive heat levels. Almost the entire shift projected with high certainty was in the form of expansion, associated with temperature components of climate and temporally limited to the 2030 time window where the total area conducive to rubber cultivation in the GMS is projected to exceed 50% by 2030 (from 44.3% at the turn of the century). The largest detected cluster (41% of the total shifting area), which also is the most ecologically degraded, corresponds to Northern Vietnam and Guangxi Autonomous Region of China. The area exposed to potentially excessive heat is projected to undergo a 25-fold increase under RCP4.5 by 2030 from 14568 km2 at the baseline.

Evaluating the Effects of Watershed Size on SWAT Calibration

The Soil and Water Assessment Tool (SWAT) has been calibrated in many watersheds of various sizes and physiographic features. However, it is still unclear whether SWAT calibration parameters will produce satisfactory results if they are implemented in watersheds of different sizes. Evaluating the transferability of SWAT calibration parameters between watersheds of different sizes will provide insight into whether it is acceptable to calibrate SWAT in one watershed and apply the optimized parameters in different size watersheds by assuming both watersheds have similar physiographic properties. This study investigated the influence of watershed size on the SWAT model calibration parameters transferability between four watersheds (CCW = 680 km2, F34 = 183 km2, AXL = 42 km2, and ALG = 20 km2) located in Northeastern Indiana. The results show that calibrating SWAT at one size and applying the optimized parameters at different watershed sizes of similar physiographic features provided satisfactory simulation results. The size watershed at which SWAT was calibrated had little effect on streamflow predictions. Soluble nitrogen loss estimates were improved when calibration was performed at the larger CCW watershed while calibrating SWAT at the smaller AXL and ALG watersheds produced improved statistical indicator values (NSE, R2, and PBIAS) for soluble P and total P when applied to the larger CCW and F34 watersheds.

Assessing baseflow index vulnerability to variation in dry spell length for a range of catchment and climate properties

AbstractBaseflow index (BFI) prediction in ungauged basins has largely been based on the use of catchment physiographic attributes as dominant variables. In a context where changes in climate are increasingly evident, it is also important to study how the slow component of flow is potentially affected by climate. The aim of this study was to illustrate the impact of climate variability on the baseflow process based on analysis of daily rainfall characteristics and hydrological modelling simulation exercises validated with observed data. Ten catchments were analysed that span southern to northern Europe and range from arid Mediterranean to maritime temperate climate conditions. Additionally, more than 2,000 virtual catchments were modelled that cover an extended gradient of physiographic and climate properties. The relative amounts of baseflow were summarized by the BFI. The catchment slow response delay time (Ks) was assumed to be a measure of catchment effects, and the impact of climate properties was investigated with the dry spell length (d). Well‐drained and poorly‐drained groups were identified based on Ks and d, and their response to an increase or decrease in dry spell length was analysed. Overall, for either well‐ or poorly‐drained groups, an extension in dry spell length appeared to have minor effects on the baseflow compared with a decrease in dry spell length. Under the same dry spell variation, the BFI vulnerability appeared higher for catchments characterized by large initial d values in combination with poorly‐drained systems, but attributing an equal weight to the variations in d both in the case of dry and wet initial conditions, it is in the end concluded that the BFI vulnerability appears higher for systems laying in the transition zone between well‐ and poorly‐drained systems.

Runoff generation in mountain catchments: long-term hydrological monitoring in the Rio Vauz Catchment, Italy

Trying to obtain a more detailed understanding of the hydrological functioning of mountain catchments represents an important challenge in the effort of counteracting possible consequences of climate and land use change on water resources availability. Long-term (> 10 years) hydro-meteorological monitoring in small (typically < 10 km2) experimental catchments constitutes a valuable tool to achieve these goal. One of these sites is the Rio Vauz Catchment (1.9 km2), in the Italian Dolomites, that represents an excellent example of long-term snowmelt-dominated catchment in Dolomitic regions. The strong elevation gradient of the Rio Vauz Catchment and the different physiographic properties of its nested subcatchments make this a unique site for investigating fundamental runoff generation mechanisms in mountain headwaters. In this work, we provide a review of physical processes that have been inferred from 12 years of hydrological monitoring in this catchment. We present the available dataset and summarize the main hydrological mechanisms that explain the internal functioning of the Rio Vauz Catchment, primarily focusing on three characterizing hydrological behaviours, namely thresholds, hysteresis and connectivity. The main control on surface and subsurface runoff threshold response is constituted by a combination of soil moisture antecedent conditions, rainfall amount and topography. Changes in hysteresis patterns (clockwise and anti-clockwise loops) between streamflow and soil moisture, water table depth and electrical conductivity were governed by distinct runoff generation processes and rainfall event characteristics. Hillslope-riparian-stream subsurface connectivity was controlled by antecedent wetness conditions and rainfall amount. The composition in environmental tracers (stable isotopes of water and electrical conductivity) in different water sources and the application of tracer-based mixing models helped to distinguish the geographical sources to runoff and to quantify the role of rainfall and snowmelt in streamflow. Finally, we define a perceptual model of runoff generation processes for dry and wet conditions that can be considered representative for many mountain headwater catchments in the world.

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

AbstractThe Soil Moisture Active Passive (SMAP) mission has delivered valuable sensing of surface soil moisture since 2015. However, it has a short time span and irregular revisit schedules. Utilizing a state‐of‐the‐art time series deep learning neural network, Long Short‐Term Memory (LSTM), we created a system that predicts SMAP level‐3 moisture product with atmospheric forcings, model‐simulated moisture, and static physiographic attributes as inputs. The system removes most of the bias with model simulations and improves predicted moisture climatology, achieving small test root‐mean‐square errors (<0.035) and high‐correlation coefficients >0.87 for over 75% of Continental United States, including the forested southeast. As the first application of LSTM in hydrology, we show the proposed network avoids overfitting and is robust for both temporal and spatial extrapolation tests. LSTM generalizes well across regions with distinct climates and environmental settings. With high fidelity to SMAP, LSTM shows great potential for hindcasting, data assimilation, and weather forecasting.

Streamflow estimation in ungauged catchments using regionalization techniques

Continuous streamflow regionalization in ungauged catchments is contemplated as a challenging task. In a developing country like India where the subject of prediction in ungauged basins (PUB) is not prevalent, thirty-two catchments were specified in order to analyze continuous streamflow estimation. Spatial proximity (Inverse Distance Weighted, Kriging, and global mean), regression and physical similarity were the regionalization approaches implemented in conjunction with SWAT (Soil and Water Assessment Tool) for streamflow estimation in each catchment treated as ungauged in turn. Kriging and IDW were the two methods that produced superior results than other applied techniques in terms of Nash-Sutcliff Efficiency (NSE), RMSE-observations standard deviation ratio (RSR) Percentage bias (PBIAS) and Peak percent threshold statistics (PPTS). Physical similarity and regression approaches, which were based on catchment attributes exhibited better results than global mean approach. Sequential Uncertainty Fitting (SUFI-2) tool analyzed the uncertainty associated with regionalization techniques in terms of 95% prediction uncertainty (95PPU). The comparative assessment proposes that presence of well-gauged catchments in proximity with the ungauged catchment is more beneficial than catchments having resemblance between them in terms of physiographic attributes for continuous streamflow prediction.

Model parameter transfer for streamflow and sediment loss prediction with SWAT in a tropical watershed

Distributed hydrological models are increasingly used to describe the spatiotemporal dynamics of water and sediment fluxes within basins. In data-scarce regions like Ethiopia, oftentimes, discharge or sediment load data are not readily available and therefore researchers have to rely on input data from global models with lower resolution and accuracy. In this study, we evaluated a model parameter transfer from a 100 hectare (ha) large subwatershed (Minchet) to a 4800 ha catchment in the highlands of Ethiopia using the Soil and Water Assessment Tool (SWAT). The Minchet catchment has long-lasting time series on discharge and sediment load dating back to 1984, which were used to calibrate the subcatchment before (a) validating the Minchet subcatchment and (b) through parameter transfer validating the entire Gerda watershed without prior calibration. Uncertainty analysis was carried out with the Sequential Uncertainty Fitting-2 (SUFI-2) with SWAT-Cup and ArcSWAT2012. We used a similarity approach, where the complete set of model parameters is transposed from a donor catchment that is very similar regarding physiographic attributes (in terms of landuse, soils, geology and rainfall patterns). For calibration and validation, the Nash-Sutcliff model efficiency, the Root Mean Square Error-observations Standard Deviation Ratio (RSR) and the Percent Bias (PBIAS) indicator for model performance ratings during calibration and validation periods were applied. Goodness of fit and the degree to which the calibrated model accounted for the uncertainties were assessed with the P-factor and the R-factor of the SUFI-2 algorithm. Results show that calibration and validation for streamflow performed very good for the subcatchment as well as for the entire catchment using model parameter transfer. For sediment loads, calibration performed better than validation and parameter transfer yielded satisfactory results, which suggests that the SWAT model can be used to adequately simulate monthly streamflow and sediment load in the Gerda catchment through model parameter transfer only.

Caracterización edáfica y dasométrica de una plantación de Eucalyptus globulus Labill y propuesta de manejo en la zona estepa espinosa Montano Bajo, Riobamba, Ecuador

Existe escasa información sobre el crecimiento y rendimiento de los árboles de la plantación de Eucalyptus globulus Labill en la hacienda Tunshi-ESPOCH en condiciones variables de fisiografía, propiedades edáficas y manejo; por esta razón se decidió evaluar su masa forestal. Se instalaron parcelas circulares de 12.62 m de radio a una intensidad de 5-6% ha-1. Mediante el muestreo sistemático no alineado para el levantamiento de información dasométrica y la excavación de tres calicatas rodal-1, aplicando el muestreo estratificado para las variables del sitio. La aplicación de estimadores estadísticos, determinó que a una altitud de 2755 msnm el volumen total promedio árbol-1 estimado de 2,32 m3 en comparación con el 0,25 m3 a una altitud de 2929 msnm. Se definieron dos áreas una de conservación y otra de aprovechamiento forestal. Existe asociaciones significativas entre el volumen total unitario de E. globulus frente a la altitud, al contenido de materia orgánica, a la capacidad de intercambio catiónico a nivel superficial y el nivel de boro a nivel subyacente. Generándose una estrategia de manejo para cada área delimitada.

Development of a computationally efficient semi-distributed hydrologic modeling application for soil moisture, lateral flow and runoff simulation

A new automated workflow based computationally efficient hydrologic modeling application is developed for soil moisture and runoff simulation. The spatially distributed conceptual framework underpinning the Soil Moisture And Runoff simulation Toolkit (SMART) resolves water balance in large upland catchments where topography and land cover are significant drivers of rainfall-runoff transformations. SMART's computational efficiency is achieved by delineation of contiguous and topologically connected hydrologic response units and solving the water balance equation on spatially representative Equivalent Cross-Sections (ECSs). ECSs are formulated by aggregating topographic and physiographic properties of the complete or part of the first order Strahler sub-basins, thereby reducing the number of computational elements. Water balance simulations across the ECSs in two sub-basins illustrated little loss of accuracy compared to the distributed cross section delineations and soil moisture observations. A 2-dimensional Richards' equation based hydrologic model in SMART can be augmented with additional functionalities or replaced with other model structures.

Towards sustainable rural landscapes? a multivariate analysis of the structure of traditional tree cropping systems along a human pressure gradient in a mediterranean region

The worldwide increase of human pressure in rural areas has resulted in a progressive fragmentation of agro-forest landscapes. Relatively few studies have identified processes of landscape modification and patch fragmentation reflecting long-term human activity from those caused by recent urbanization stimulated by economic development, population growth and improved accessibility of rural areas. In rural districts dominated by high-quality crop mosaics and exposed to increasing levels of human pressure, urbanization-driven changes in the use of land have determined complex and non-linear processes of landscape fragmentation which deserve further investigation. Multidimensional procedures and data mining are appropriate to explore such transformations, basing on a comprehensive assessment of landscape metrics. The present study investigates changes in land-use and landscape structure (2000–2008) in three districts of Latium (central Italy) featuring different cropping systems, physiographic attributes and level of human pressure. A principal component analysis was run to identify a core set of metrics aimed at (i) evaluating the role of traditional cropping systems in the preservation of traditional agro-forest systems and (ii) inferring the relationship between spatial heterogeneity in rural landscapes and socio-ecological processes of change. Our results indicate that crop intensification has contributed to landscape homogeneity and simplification in all areas studied, in contrast with the effects of urban expansion resulting in a more fragmented and diversified landscape with relict tree crop patches. The findings of this study clarify the contribution of traditional tree crop systems to sustainable structures and functions of rural landscapes by preserving the place-specific eco-mosaic complexity.

Arsenic solid-phase speciation in an alluvial aquifer system adjacent to the Himalayan forehills, Nepal

Alluvial aquifers contaminated by geogenic arsenic often lack direct solid-phase speciation data, hindering efforts to understand landscape-scale spatial heterogeneity and controls on As mobility. Here, we examine solid-phase As and Fe speciation of alluvial aquifer, river and hyporheic-seep sediments along a topographic gradient at the Himalayan foothills/upper-Ganges floodplain margin. We employ a combination of X-ray absorption spectroscopy, selective extracts, electron microscopy and X-ray fluorescence. Source-river sediments were found to contain a mixture of solid-phase As(V) and As(III) species, while vertically heterogeneous bore-hole sediments also contained a solid-phase As-sulfide species. In general, the abundance of reduced As species [As(III)+As-sulfide] increased with depth below ground surface, as well as down the topographic gradient from the foothills to the floodplain. Although Fe(III) oxides diminished with depth, goethite-rich nodules were present above the seasonal water table minima and contained 10–100 fold more As than the corresponding bulk sediments [~50–800mgkg−1; mainly As(V)]. In contrast, organic-rich clay layers below the seasonal water table contained abundant As-sulfide species (~30–80% of solid-phase As), as well as authigenic pyrite enriched in As [up to ~8500mgkg−1]. Results indicate that aquifer sediments contain discrete facies that are strongly enriched in As due to post-depositional diagenetic coupling between As retention and redox-dependent Fe mineralization. In riverine hyporheic-seeps, ferrihydrite traps As(V)/As(III) species (~30–200mgkg−1) in a readily exchangeable form, creating a pool of solid-phase As vulnerable to downstream reworking and subsequent reductive mobilization. A paucity of Fe(III) oxides in aquifer sediments at tube well-screen depth suggests that the abundant As(III)(aq) in floodplain tube wells is more likely attributable to downward transport or desorption of As(III)-species, than to contemporary reductive dissolution of As-bearing Fe oxides in sediments at well-screen depth. In contrast with the lower Gangetic plain, where large-scale floodplain sedimentary features are a key control on solid-phase As and Fe speciation, in these alluvial sediments solid-phase As and Fe speciation appears to be controlled mainly by physiographic properties (elevation; depth; seasonal water table) that influence local redox conditions.

Runoff Prediction in Ungauged Watersheds Using Remote Sensor Datasets

Runoff prediction in ungauged watersheds is regarded as one of the major issues in contemporary hydrology. This study examined the utility of remote sensor datasets for parameter regionalization. A distributed hydrologic model, the Coupled Routing and Excess Storage (CREST) model, was employed to simulate runoff conditions in the mountainous watersheds over South Korea. In gauged watersheds, the relationships between the optimized parameter set of the hydrologic model and the physiographic properties of the gauged watersheds were investigated using multiple linear regressions. The regression parameters for the ungauged watersheds were then validated and assessed. Results demonstrated that the hydrologic model and the proposed regression equations could acceptably simulate the discharge in both gauged and ungauged watersheds. However, they provided somewhat biased discharge for all the ungauged watersheds. In further studies, these biases should be reduced by investigating other watersheds and finding physiographic properties highly related to the model parameters. KeywordRunoff Prediction; Ungauged Watersheds; TRMM; Multi-satellite; Regionalization

Erosion Modelling In A Mediterranean Subcatchment Under Climate Change Scenarios Using Pan-European Soil Erosion Risk Assessment (PESERA)

Abstract. The Mediterranean region is particularly prone to erosion. This is because it is subject to long dry periods followed by heavy bursts of erosive rainfall, falling on steep slopes with fragile soils, resulting in considerable amounts of erosion. In parts of the Mediterranean region, erosion has reached a stage of irreversibility and in some places erosion has practically ceased because there is no more soil left. With a very slow rate of soil formation, any soil loss of more than 1 t ha−1 yr−1 can be considered as irreversible within a time span of 50-100 years. The objectives of this study were i) to estimate the temporal and spatial distribution of soil erosion under climate change scenarios in study area ii) to assess the hydrological runoff processes. In this study, climate data, land use, topographic and physiographic properties were assembled for Egribuk Subcatchment at Seyhan River Basin in Turkey and used in a process-based Geographical Information System (GIS) to determine the hydrological sediment potential and quantify reservoir sedimentation. The estimated amount of sediment transported downstream is potentially large based on hydrological runoff processes using the Pan-European Soil Erosion Risk Assessment (PESERA) model. The detailed model inputs included 128 variables derived mainly from, soil, climate, land use/cover, topography data sets. The outcomes of this research were spatial and temporal distribution of erosion amount in t ha−1 yr−1 or month−1.

Pedological Characterization of Some Typical Soils of Busia County, Western Kenya: Soil Morphology, Physico-chemical Properties, Classification and Fertility Trends

Standard soil survey was carried out in Western Kenya to establish representative research sites on the basis of landforms and other physiographic attributes. Soil profiles were characterized at Emalomba (Nambale District) designated (EMA-P1) and at Bukhalalire (Butula District) named BUMA-P1. Both pedons formed from in-situ weathering of granitic rocks under ustic moisture and iso-hyperthermic temperature regimes. Fourteen soil samples from genetic horizons were analyzed for physico-chemical properties. Both pedons had dark brown sandy clay and sandy clay loam topsoils overlying dominantly clayey subsoils. Both pedons indicate clay eluviation-illuviation as a Original Research Article

Spatial distribution of soil erosion and suspended sediment transport rate for Chou-Shui river basin

In this study, a Physiographic Soil Erosion–Deposition Model (PSED) is applied for better management of a watershed. The PSED model can effectively evaluate the key parameters of watershed management: surface runoff discharge, suspended sediment transport rate, quantity of soil erosion, and spatial distribution of soil erosion and deposition. A basin usually contains multiple watersheds. These watersheds may have complex topography and heterogeneous physiographic properties. The PSED model, containing a physiographic rainfall-runoff model and a basin scale erosion–deposition model, can simulate the physical mechanism of the entire erosion process based on a detailed calculation of bed-load transportation, surface soil entrainment, and the deposition mechanism. With the assistance of Geographic Information Systems (GIS), the PSED model can handle and analyze extremely large hydrologic and physiographic datasets and simulate the physical erosion process without the need for simplification. We verified the PSED model using three typhoon events and 40 rainfall events. The application of PSED to Chou-Shui River basin shows that the PSED model can accurately estimate discharge hydrographs, suspended sediment transport rates, and sediment yield. Additionally, we obtained reasonable quantities of soil erosion as well as the spatial distribution of soil erosion and deposition. The results show that the PSED model is capable of calculating spatially distributed soil erosion and suspended sediment transport rates for a basin with multiple watersheds even if these watersheds have complex topography and heterogeneous physiographic properties.