Search

Optimum management of irrigated crops in regions with shallow saline groundwater requires a careful balance between application of irrigation water and upward movement of salinity from the groundwater. Few field-validated surrogate models are available to aid in the management of irrigation water under shallow groundwater conditions. The objective of this research is to develop a model that can aid in the management using a minimum of input data that are field validated. In this paper a 2-year field experiment was carried out in the Hetao irrigation district in Inner Mongolia, China, and a physically based integrated surrogate model for arid irrigated areas with shallow groundwater was developed and validated with the collected field data. The integrated model that links crop growth with available water and salinity in the vadose zone is called Evaluation of the Performance of Irrigated Crops and Soils (EPICS). EPICS recognizes that field capacity is reached when the matric potential is equal to the height above the groundwater table and thus not by a limiting hydraulic conductivity. In the field experiment, soil moisture contents and soil salt conductivity at five depths in the top 100 cm, groundwater depth, crop height, and leaf area index were measured in 2017 and 2018. The field results were used for calibration and validation of EPICS. Simulated and observed data fitted generally well during both calibration and validation. The EPICS model that can predict crop growth, soil water, groundwater depth, and soil salinity can aid in optimizing water management in irrigation districts with shallow aquifers.

Rapid population growth is increasing pressure on the world water resources. Agriculture will require crops to be grown with less water. This is especially the case for the closed Yellow River basin, necessitating a better understanding of the fate of irrigation water in the soil. In this paper, we report on a field experiment and develop a physically based model for the shallow groundwater in the Hetao irrigation district in Inner Mongolia, in the arid middle reaches of the Yellow River. Unlike other approaches, this model recognizes that field capacity is reached when the matric potential is equal to the height above the groundwater table and not by a limiting soil conductivity. The field experiment was carried out in 2016 and 2017. Daily moisture contents at five depths in the top 90 cm and groundwater table depths were measured in two fields with a corn crop. The data collected were used for model calibration and validation. The calibration and validation results show that the model-simulated soil moisture and groundwater depth fitted well. The model can be used in areas with shallow groundwater to optimize irrigation water use and minimize tailwater losses.

Uncertainty in hydrological modeling is of significant concern due to its effects on prediction and subsequent application in watershed management. Similar to other distributed hydrological models, model uncertainty is an issue in applying the Soil and Water Assessment Tool (SWAT). Previous research has shown how SWAT predictions are affected by uncertainty in parameter estimation and input data resolution. Nevertheless, little information is available on how parameter uncertainty and output uncertainty are affected by input data of varying complexity. In this study, SWAT-Hillslope (SWAT-HS), a modified version of SWAT capable of predicting saturation-excess runoff, was applied to assess the effects of input data with varying degrees of complexity on parameter uncertainty and output uncertainty. Four digital elevation model (DEM) resolutions (1, 3, 10 and 30 m) were tested for their ability to predict streamflow and saturated areas. In a second analysis, three soil maps and three land use maps were used to build nine SWAT-HS setups from simple to complex (fewer to more soil types/land use classes), which were then compared to study the effect of input data complexity on model prediction/output uncertainty. The case study was the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region, New York, USA. Results show that DEM resolution did not impact parameter uncertainty or affect the simulation of streamflow at the watershed outlet but significantly affected the spatial pattern of saturated areas, with 10m being the most appropriate grid size to use for our application. The comparison of nine model setups revealed that input data complexity did not affect parameter uncertainty. Model setups using intermediate soil/land use specifications were slightly better than the ones using simple information, while the most complex setup did not show any improvement from the intermediate ones. We conclude that improving input resolution and complexity may not necessarily improve model performance or reduce parameter and output uncertainty, but using multiple temporal and spatial observations can aid in finding the appropriate parameter sets and in reducing prediction/output uncertainty.

Gully expansion in the Ethiopian Highlands dissects vital agricultural lands with the eroded materials adversely impacting downstream resources, for example as they accumulate in reservoirs. While gully expansion and rehabilitation have been more extensively researched in the semiarid region of Ethiopia, few studies have been conducted in the (sub)humid region. For that reason, we assessed the severity of gully erosion by measuring the expansion of 13 selected permanent gullies in the subhumid Debre Mawi watershed, 30 km south of Lake Tana, Ethiopia. In addition, the rate of expansion of the entire drainage network in the watershed was determined using 0.5 m resolution aerial imagery from flights in 2005 and 2013. About 0.6 Mt (or 127 t ha−1 yr−1) of soil was lost during this period due to actively expanding gullies. The net gully area in the entire watershed increased more than 4-fold from 4.5 ha in 2005 to 20.4 ha in 2013 (> 3 % of the watershed area), indicating the growing severity of gully erosion and hence land degradation in the watershed. Soil losses were caused by upslope migrating gully heads through a combination of gully head collapse and removal of the failed material by runoff. Collapse of gully banks and retreat of headcuts was most severe in locations where elevated groundwater tables saturated gully heads and banks, destabilizing the soils by decreasing the shear strength. Elevated groundwater tables were therefore the most important cause of gully expansion. Additional factors that strongly relate to bank collapse were the height of the gully head and the size of the drainage area. Soil physical properties (e.g., texture and bulk density) only had minor effects. Conservation practices that address factors controlling erosion are the most effective in protecting gully expansion. These consist of lowering water table and regrading the gully head and sidewalls to reduce the occurrence of gravity-induced mass failures. Planting suitable vegetation on the regraded gully slopes will in addition decrease the risk of bank failure by reducing pore-water pressures and reinforcing the soil. Finally, best management practices that decrease runoff from the catchment will reduce the amount of gully-related sediment loss.

Information on sediment concentration in rivers is important for design of reservoirs and for environmental applications. Because of the scarcity of continuous sediment data, methods have been developed to predict sediment loads based on few discontinuous measurements. Traditionally, loads are being predicted using rating curves that relate sediment load to discharge. The relationship assumes inherently a unique relationship between concentration and discharge and therefore although performing satisfactorily in predicting loads, it may be less suitable for predicting concentration. This is especially true in the Blue Nile Basin of Ethiopia where concentrations decrease for a given discharge with the progression of the rainy monsoon phase. The objective of this paper is to improve the sediment concentration predictions throughout the monsoon period for the Ethiopian highlands with a modified rating type equation. To capture the observed sediment concentration pattern, we assume that the sediment concentration was at the transport limit early in the rainy season and then decreases linearly with effective rainfall towards source-limited concentration. The modified concentration rating curve was calibrated for the four main rivers in the Lake Tana basin where sediment concentrations affect fish production and tourism. Then the scalability of the rating type equation was checked in three 100 ha watersheds for which historic data were available. The results show that for predicting sediment concentrations, the (modified) concentration rating curve was more accurate than the (standard) load rating curve as expected. In addition loads were predicted more accurately for three of the four rivers. We expect that after more extensive testing over a wider geographical area, the proposed concentration rating curve will offer improved predictions of sediment concentrations in monsoonal climates.

Placement and hence performance of many soil and water conservation structures in tropical highlands has proven to be challenging due to uncertainty of the actual location of runoff-generating areas in the landscape. This is the case especially in the (sub-)humid areas of the Ethiopian highlands, resulting in limited success of such conservation measures. To improve understanding of the effect of land use on spatial and temporal runoff patterns in the Ethiopian highlands, we monitored runoff volumes from 24 runoff plots constructed in the 113 ha Anjeni watershed, where historical data of rainfall and stream discharge were available. In addition, we assessed the effectiveness of charcoal amendment of the soil and crop rooting depth in reducing runoff, and we compared the effect of lupine (a deep-rooted crop) to that of barley. We also measured daily rainfall, surface runoff, and root zone moisture contents during the monsoon seasons of 2012 and 2013 (with all plots being tilled in 2012, but only barley plots tilled in 2013). In addition, we analyzed long-term surface runoff from four plots, and outlet discharge data from the research site (1989–1993) were analyzed and compared with our observations. Results showed that the degrees of soil degradation and soil disturbance (tillage) were significant factors affecting plot-scale runoff responses. As expected, runoff was greater from more degraded soils. Overall, under the commonly applied lupine cropping practice, runoff was higher than under the commonly applied barley cropping practice. In particular, considerable difference was observed during smaller rainfall events (approximately

Planning for drought relief and floods in developing countries is greatly hampered by the lack of a sufficiently dense network of weather stations measuring precipitation. In this paper, we test the utility of three satellite products to augment the ground-based precipitation measurement to provide improved spatial estimates of rainfall. The three products are the Tropical Rainfall Measuring Mission (TRMM) product (3B42), Multi-Sensor Precipitation Estimate–Geostationary (MPEG) and the Climate Forecast System Reanalysis (CFSR). The accuracy of the three products is tested in the Lake Tana basin in Ethiopia, where 38 weather stations were available in 2010 with a full record of daily precipitation amounts. Daily gridded satellite-based rainfall estimates were compared to (1) point-observed ground rainfall and (2) areal rainfall in the major river sub-basins of Lake Tana. The result shows that the MPEG and CFSR satellites provided the most accurate rainfall estimates. On average, for 38 stations, 78 and 86% of the observed rainfall variation is explained by MPEG and CFSR data, respectively, while TRMM explained only 17% of the variation. Similarly, the areal comparison indicated a better performance for both MPEG and CFSR data in capturing the pattern and amount of rainfall. MPEG and CFSR also have a lower root mean square error (RMSE) compared to the TRMM 3B42 satellite rainfall. The bias indicated that TRMM 3B42 was, on average, unbiased, whereas MPEG consistently underestimated the observed rainfall. CFSR often produced large overestimates.

Erosion modeling has been generally scaling up from plot scale but not based on landscape topographic position, which is a main variable in saturation excess runoff. In addition, predicting sediment loss in Africa has been hampered by using models developed in western countries and do not perform as well in the monsoon climate prevailing in most of the continent. The objective of this paper is to develop a simple erosion model that can be used in the Ethiopian Highlands in Africa. We base our sediment prediction on a simple distributed saturated excess hydrology model that predicts surface runoff from severely degraded lands and from bottom lands that become saturated during the rainy season and estimates interflow and baseflow from the remaining portions of the landscape. By developing an equation that relates surface runoff to sediment concentration generated from runoff source areas, assuming that baseflow and interflow are sediment-free, we were able to predict daily sediment concentrations from the Anjeni watershed with a Nash–Sutcliffe efficiency ranging from 0.64 to 0.78 using only two calibrated sediment parameters. Anjeni is a 113 ha watershed in the 17.4 million ha Blue Nile Basin in the Ethiopian Highlands. The discharge of the two watersheds was predicted with Nash–Sutcliffe efficiency values ranging from 0.80 to 0.93. The calibrated values in Anjeni for degraded (14%) and saturated (2%) runoff source area were in agreement with field evidence. The analysis suggests that identifying the runoff source areas and predicting the surface runoff correctly is an important step in predicting the sediment concentration.

Loss of top soil and subsequent filling up of reservoirs in much of the lands with variable relief in developing countries degrades environmental resources necessary for subsistence. In the Ethiopia highlands, sediment mobilization from rain-fed agricultural fields is one of the leading factors causing land degradation. Sediment rating curves, produced from long-term sediment concentration and discharge data, attempt to predict suspended sediment concentration variations, which exhibit a distinct shift with the progression of the rainy season. In this paper, we calculate sediment rating curves and examine this shift in concentration for three watersheds in which rain-fed agriculture is practiced to differing extents. High sediment concentrations with low flows are found at the beginning of the rainy season of the semi-monsoonal climate, while high flows and low sediment concentrations occur at the end of the rainy season. Results show that a reasonably unique set of rating curves were obtained by separating biweekly data into early, mid, and late rainfall periods and by making adjustments for the ratio of plowed cropland. The shift from high to low concentrations suggests that diminishing sediment supply and dilution from greater base flow during the end of the rainfall period play important roles in characterizing changing sediment concentrations during the rainy season.

In this study we evaluated changes in land cover and rainfall in the Upper Gilgel Abbay catchment in the Upper Blue Nile basin and how changes affected stream flow in terms of annual flow, high flows and low flows. Land cover change assessment was through classification analysis of remote sensing based land cover data while assessments on rainfall and stream flow data are by statistical analysis. Results of the supervised land cover classification analysis indicated that 50.9 % and 16.7 % of the catchment area was covered by forest in 1973 and 2001, respectively. This significant decrease in forest cover is mainly due to expansion of agricultural land. By use of a change detection procedure, three periods were identified for which changes in rainfall and stream flow were analyzed. Rainfall was analyzed at monthly base by use of the Mann-Kendall test statistic and results indicated a statistically significant, decreasing trend for most months of the year. However, for the wet season months of June, July and August rainfall has increased. In the period 1973–2005, the annual flow of the catchment decreased by 12.1 %. Low flow and high flow at daily base were analyzed by a low flow and a high flow index that is based on a 95 % and 5 % exceedance probability. Results of the low flow index indicated decreases of 18.1 % and 66.6 % for the periods 1982–2000 and 2001–2005 respectively. Results of high flows indicated an increase of 7.6 % and 46.6 % for the same periods. In this study it is concluded that over the period 1973–2005 stream flow has changed in the Gilgel Abbay catchment by changes in land cover and changes in rainfall.

Gully formation in the Ethiopian Highlands has been identified as a major source of sediment in water bodies, and results in sever land degradation. Loss of soil from gully erosion reduces agricultural productivity and grazing land availability, and is one of the major causes of reservoir siltation in the Nile Basin. This study was conducted in the 523 ha Debre-Mawi watershed south of Bahir Dar, Ethiopia, where gullies are actively forming in the landscape. Historic gully development in a section of the Debre-Mawi watershed was estimated with semi structured farmer interviews, remotely sensed imagery, and measurements of current gully volumes. Gully formation was assessed by instrumenting the gully and surrounding area to measure water table levels and soil physical properties. Gully formation began in the late 1980's following the removal of indigenous vegetation, leading to an increase in surface and subsurface runoff from the hillsides. A comparison of the gully area, estimated from a 0.58 m resolution QuickBird image, with the current gully area mapped with a GPS, indicated that the total eroded area of the gully increased from 0.65 ha in 2005 to 1.0 ha in 2007 and 1.43 ha in 2008. The gully erosion rate, calculated from cross-sectional transect measurements, between 2007 and 2008 was 530 t ha−1 yr−1 in the 17.4 ha area contributing to the gully, equivalent to over 4 cm soil loss over the contributing area. As a comparison, we also measured rill and interrill erosion rates in a nearby section of the watershed, gully erosion rates were approximately 20 times the measured rill and interrill rates. Depths to the water table measured with piezometers showed that in the actively eroding sections of the gully the water table was above the gully bottom and, in stable gully sections the water table was below the gully bottom during the rainy season. The elevated water table appears to facilitate the slumping of gully walls, which causes the gully to widen and to migrate up the hillside.

A multi basin analysis of runoff and erosion in the Blue Nile Basin, Ethiopia was conducted to elucidate sources of runoff and sediment. Erosion is arguably the most critical problem in the Blue Nile Basin, as it limits agricultural productivity in Ethiopia, degrades benthos in the Nile, and results in sedimentation of dams in downstream countries. A modified version of the Soil and Water Assessment Tool (SWAT) model was developed to predict runoff and sediment losses from the Ethiopian Blue Nile Basin. The model simulates saturation excess runoff from the landscape using a simple daily water balance coupled to a topographic wetness index in ways that are consistent with observed runoff processes in the basin. The spatial distribution of landscape erosion is thus simulated more correctly. The model was parameterized in a nested design for flow at eight and sediment at three locations in the basin. Subbasins ranged in size from 1.3 to 174 000 km2, and interestingly, the partitioning of runoff and infiltrating flow could be predicted by topographic information. Model predictions showed reasonable accuracy (Nash Sutcliffe Efficiencies ranged from 0.53–0.92) with measured data across all sites except Kessie, where the water budget could not be closed; however, the timing of flow was well captured. Runoff losses increased with rainfall during the monsoonal season and were greatest from areas with shallow soils and large contributing areas. Analysis of model results indicate that upland landscape erosion dominated sediment delivery to the main stem of the Blue Nile in the early part of the growing season when tillage occurs and before the soil was wetted up and plant cover was established. Once plant cover was established in mid August landscape erosion was negligible and sediment export was dominated by channel processes and re-suspension of landscape sediment deposited early in the growing season. These results imply that targeting small areas of the landscape where runoff is produced can be the most effective at controlling erosion and protecting water resources. However, it is not clear what can be done to manage channel erosion, particularly in first order streams in the basin.

Spatial patterns of water chemistry along stream networks can be quantified using synoptic or "snapshot" sampling. The basic idea is to sample stream water at many points over a relatively short period of time. Even for intense sampling campaigns, the number of sample points is limited and interpolation methods, like kriging, are commonly used to produce continuous maps of water chemistry based on the point observations from the synoptic sampling. Interpolated concentrations are influenced heavily by how distance between points along the stream network is defined. In this study, we investigate different ways to define distance and test these based on data from a snapshot sampling campaign in a 37-km2 watershed in the Catskill Mountains region (New York State). Three distance definitions (or metrics) were compared: Euclidean or straight-line distance, in-stream distance, and in-stream distance adjusted according characteristics of the local contributing area, i.e., an adjusted in-stream distance. Using the adjusted distance metric resulted in a lower cross-validation error of the interpolated concentrations, i.e., a better agreement of kriging results with measurements, than the other distance definitions. The adjusted distance metric can also be used in an exploratory manner to test which landscape characteristics are most influential for the spatial patterns of stream water chemistry and, thus, to target future investigations to gain process-based understanding of in-stream chemistry dynamics.

The spatial distribution of saturated areas is an important consideration in numerous applications, such as water resource planning or siting of management practices. However, in humid well vegetated climates where runoff is produced by saturation excess processes on hydrologically active areas (HAA) the delineation of these areas can be difficult and time consuming. A technique that can simply and reliably predict these areas would be a powerful tool for scientists and watershed managers tasked with implementing practices to improve water quality. Remotely sensed data is a source of spatial information and could be used to identify HAAs. This study describes a methodology to determine the spatial variability of saturated areas using a temporal sequence of remotely sensed images. The Normalized Difference Water Index (NDWI) was derived from medium resolution Landsat 7 ETM+ imagery collected over seven months in the Town Brook watershed in the Catskill Mountains of New York State and used to characterize the areas susceptible to saturation. We found that within a single land cover, saturated areas were characterized by the soil surface water content when the vegetation was dormant and leaf water content of the vegetation during the growing season. The resulting HAA map agreed well with both observed and spatially distributed computer simulated saturated areas (accuracies from 49 to 79%). This methodology shows that remote sensing can be used to capture temporal variations in vegetation phenology as well as spatial/temporal variation in surface water content, and appears promising for delineating saturated areas in the landscape.

Shallow water tables near-streams often lead to saturated, overland flow generating areas in catchments in humid climates. While these saturated areas are assumed to be principal biogeochemical hot-spots and important for issues such as non-point pollution sources, the spatial and temporal behavior of shallow water tables, and associated saturated areas, is not completely understood. This study demonstrates how geostatistical methods can be used to characterize the spatial and temporal variation of the shallow water table for the near-stream region. Event-based and seasonal changes in the spatial structure of the shallow water table, which influences the spatial pattern of surface saturation and related runoff generation, can be identified and used in conjunction to characterize the hydrology of an area. This is accomplished through semivariogram analysis and indicator kriging to produce maps combining soft data (i.e., proxy information to the variable of interest) representing general shallow water table patterns with hard data (i.e., actual measurements) that represent variation in the spatial structure of the shallow water table per rainfall event. The area used was a hillslope in the Catskill Mountains region of New York State. The shallow water table was monitored for a 120 m×180 m near-stream region at 44 sampling locations on 15-min intervals. Outflow of the area was measured at the same time interval. These data were analyzed at a short time interval (15 min) and at a long time interval (months) to characterize the changes in the hydrologic behavior of the hillslope. Indicator semivariograms based on binary-transformed ground water table data (i.e., 1 if exceeding the time-variable median depth to water table and 0 if not) were created for both short and long time intervals. For the short time interval, the indicator semivariograms showed a high degree of spatial structure in the shallow water table for the spring, with increased range during many rain events. During the summer, when evaporation exceeds precipitation, the ranges of the indicator semivariograms decreased during rainfall events due to isolated responses in the water table. For the longer, monthly time interval, semivariograms exhibited higher sills and shorter ranges during spring and lower sills and longer ranges during the summer. For this long time interval, there was a good correlation between probability of exceeding the time-variable median water table and the soil topographical wetness index during the spring. Indicator kriging incorporating both the short and long time interval structure of the shallow water table (hard and soft data, respectively) provided more realistic maps that agreed better with actual observations than the hard data alone. This technique to represent both event-based and seasonal trends incorporates the hillslope-scale hydrological processes to capture significant patterns in the shallow water table. Geostatistical analysis of the spatial and temporal evolution of the shallow water table gives information about the formation of saturated areas important in the understanding hydrological processes working at this and other hillslopes.

Successful implementation of best management practices for reducing non-point source (NPS) pollution requires knowledge of the location of saturated areas that produce runoff. A physically-based, fully-distributed, GIS-integrated model, the Soil Moisture Distribution and Routing (SMDR) model was developed to simulate the hydrologic behavior of small rural upland watersheds with shallow soils and steep to moderate slopes. The model assumes that gravity is the only driving force of water and that most overland flow occurs as saturation excess. The model uses available soil and climatic data, and requires little calibration. The SMDR model was used to simulate runoff production on a 164-ha farm watershed in Delaware County, New York, in the headwaters of New York City water supply. Apart from land use, distributed input parameters were derived from readily available data. Simulated hydrographs compared reasonably with observed flows at the watershed outlet over a eight year simulation period, and peak timing and intensities were well reproduced. Using off-site weather input data produced occasional missed event peaks. Simulated soil moisture distribution agreed well with observed hydrological features and followed the same spatial trend as observed soil moisture contents sampled on four transects. Model accuracy improved when input variables were calibrated within the range of SSURGO-available parameters. The model will be a useful planning tool for reducing NPS pollution from farms in landscapes similar to the Northeastern US.

Reducing non-point source phosphorus (P) loss to drinking water reservoirs is a main concern for New York City watershed planners, and modeling of P transport can assist in the evaluation of agricultural effects on nutrient dynamics. A spatially distributed model of total dissolved phosphorus (TDP) loading was developed using raster maps covering a 164-ha dairy farm watershed. Transport of TDP was calculated separately for baseflow and for surface runoff from manure-covered and non-manure-covered areas. Soil test P, simulated rainfall application, and land use were used to predict concentrations of TDP in overland flow from non-manure covered areas. Concentrations in runoff for manure-covered areas were computed from predicted cumulative flow and elapsed time since manure application, using field-specific manure spreading data. Baseflow TDP was calibrated from observed concentrations using a temperature-dependent coefficient. An additional component estimated loading associated with manure deposition on impervious areas, such as barnyards and roadways. Daily baseflow and runoff volumes were predicted for each 10-m cell using the Soil Moisture Distribution and Routing Model (SMDR). For each cell, daily TDP loads were calculated as the product of predicted runoff and estimated TDP concentrations. Predicted loads agreed well with loads observed at the watershed outlet when hydrology was modeled accurately (R2 79% winter, 87% summer). Lack of fit in early spring was attributed to difficulty in predicting snowmelt. Overall, runoff from non-manured areas appeared to be the dominant TDP loading source factor.

Agricultural tile drainage lines have been implicated as a source of pesticide contamination of surface waters. Field experiments were conducted and a simple model was developed to examine preferential transport of applied chemicals to agricultural tile lines. The conceptual model consists of two linear reservoirs, one near the soil surface and one near the tile drain. The connection between the two reservoirs is via preferential flow paths with very little interaction with the soil matrix. The model assumes that only part of the field contributes solutes to the tile drain. The model was evaluated with data from the field experiments in which chloride, 2,4-D, and atrazine concentrations were measured on eight tile-drained plots that were irrigated twice. Atrazine was applied two months prior to the experiment, 2,4-D was sprayed just before the first irrigation, and chloride before the second irrigation. All three chemicals were found in the tile effluent shortly after the rainfall began. Generally, the concentration increased with increased flow rates and decreased exponentially after the rainfall ceased. Although the simple model could simulate the observed chloride concentration patterns in the tile outflow for six of the eight plots, strict validation was not possible because of the difficulty with independent measurement of the data needed for a preferential flow model applied to field conditions. The results show that, to simulate pesticide concentration in tile lines, methods that can measure field averaged preferential flow characteristics need to be developed.

Field evidence of finger formation and reformation during Successive rain events over an eight months' observation period from June 1994 until January 1995 is presented. Fingered flow pathways were monitored in a no-tilled, grass-covered water repellent sandy field soil using an automated, stand-alone TDR device. Within a 2 m long and 0.7 m deep transect, 98 three-wire probes were installed horizontally at depths of 4, 12, 20, 30, 40, 55, and 70 cm. The horizontal distance between two adjacent probes was IS cm. Finger formation occurred during distinct rainy periods and was most pronounced under heavy rainfall with initially wet topsoil conditions. The percentage of water infiltrated and transported preferentially through the fingers to the deep subsoil varied between 0 and 80%, depending on the wetting history of the soil and the rainfall characteristics.

When tropical forests are felled, subsequent land uses affect surface runoff, soil erosion, and soil compaction. In some cases, they can markedly change the hydrology of a region with disastrous effects on human life. The objective of this paper is to investigate the effect of rainfall on stream hydrology due to conversion of primary forests to agriculture. Near surface water dynamics were compared for three land uses on the steep hillsides in the Talgua River Watershed in Honduras: degraded grass?covered field; traditional coffee plantation; and primary forest. Infiltration and surface runoff rates were measured using several methods. A clear difference was observed in hydraulic conductivity between the degraded and non?degraded lands. The degraded grass?covered hillslopes developed a surface restrictive layer with a low saturated hydraulic conductivity of 8 to 11?mm/hr, resulting in more frequent overland flow than traditional coffee plantation and primary forest. Soils under the latter two land?use types maintained high infiltration capacities and readily conducted water vertically at rates of 109 and 840?mm/hr, respectively. Dye tests confirmed that the coffee plantation and primary forest both maintained well?connected macropores through which water flowed readily. In contrast, macropores in the degraded soil profile were filled by fine soil particles. Soils in the degraded grass?covered field also showed more compaction than soils in the coffee plantation. Copyright © 2004 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Hortonian runoff was measured in the laboratory from uniform slopes of lengths of 1·5, 3·0, and 6·0 m for steady, high-intensity rainstorms with durations of 1·0 to 7·5 min. A clear reduction in runoff per unit slope length was found as slope lengths were increased. This effect becomes more pronounced with decreasing storm duration. The runoff data were used to validate a simple process-based model that combines the Philip-two-term infiltration equation with the kinematic wave overland flow principle. The predicted and experimental results agreed well. Laboratory findings were extrapolated with the aid of the model to slopes and rainfall durations similar to those found under West African conditions. The calculated reduction of runoff per unit length is similar to reported observations. Thus, this process-based model can largely explain the phenomenon of runoff reduction with increasing slope length. Copyright © 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]