Hydrologic Soil Group Research Articles

Runoff volume prediction in the megadrigadda reservoir catchment due to past land use/land cover trends-a case study

One major source of water on the Earth is Surface water resources such as Rivers, Rain water sewers, Streams etc. With the rapid change in the mode of usage of land for various purposes like residential, agricultural, industrial, water storage basins, the volume of Surface runoff due to Rain & melting of Snow changes. Estimating such quantities of runoff is essential for proper managing of Water resources over the Earth surface. Runoff estimation of each Mini Water has been done by SCS-CN Curve number method. The required data for this method include Land Use/Land Cover trends of past years, Hydrological Soil Groups, Rainfall trends and AMC Type. Based on the analysis a considerable change in the Groundwater Recharge in the study area is found due to the variations in the Built-up & vegetative cover features ultimately resulting in increasing Surface Runoff there by excess inflow may enter into the Megadrigadda reservoir resulting in Flash floods during monsoons. In the coming years there are chances of the Dam being breached thereby affecting the Visakhapatnam Airport area in its Downstream.

Site Selection Based on Analytic Hierarchy Process in the Planning Process for Solid Waste Sanitary Landfills: The Case of Denizli City, Turkey

Waste management has grown into a significant matter for cities in line with the population growth and increased urbanization. Waste must be properly disposed to avoid causing a problem for environmental and human health. A variety of methods are used to dispose waste. Sanitary landfill, which is among these methods, is one of the common methods used for its safety and affordability. In the implementation of this method, a suitable site selection is a major factor that affects the whole process ranging from the construction to the operation of a sanitary landfill. It is aimed to determine the most suitable solid waste sanitary landfills (SWSL) for the city of Denizli in consideration of site selection criteria regarding solid waste landfills. The relevant legislation, academic studies and the current situation of the study area were taken into consideration to determine site selection criteria for SWSL. In this context, residential areas, primary traffic roads, protected areas, slope, aspect, water surfaces, rock structure, fault line, hydrologic soil groups, land use capability classification and land cover were determined as a site selection criteria. In the study, Geographic Information Systems (GIS) was used in spatial analysis, and analytic hierarchy process (AHP), one of the multi-criteria decision making methods, was used in weighting the site selection criteria. According to the suitability map which is generated as a result of the study, 19.536,40 hectares (1.76%) of 1.109.742,16 hectares of the area was determined to be the "most suitable" for sanitary landfill while 260.520,26 hectares (23.48%) of it was determined to be "suitable". An ideal area was determined for the construction of a sanitary landfill on the areas determined as the “most suitable" in consideration of the requirements of the city of Denizli based on the projections for the year 2040.

Assimilation of remote sensing based surface soil moisture to develop a spatially varying vertical soil moisture profile database for entire Indian mainland

The Climate Change Initiative (CCI) program of the European Space Agency (ESA) (ESA-CCI) provides a global surface Soil Moisture (SM) product by merging the information from various Active and Passive sensors on board for the period of 1971–2014. This study aims to assimilate this surface SM product into a recently developed model, namely Statistical Soil Moisture Profile (SSMP) model, to investigate the efficacy of this combination in developing a vertical soil moisture profile database over a climatologically vast area, such as Indian mainland. The SSMP model is a spatially varying statistical framework that couples the memory and forcing of SM from the overlying layers and utilizes the information of Hydrologic Soil Groups (HSGs) that makes it spatially transferable. The model estimates SM at four depths i.e. 10, 20, 51 and 102 cm using the surface SM information (~0–5 cm). The developed database is named as ‘ESA-CCI Driven Vertical Soil Moisture Profile (root zone) Database (EDVSMPD)’ and the simulated values are validated with observed SM data at many monitoring stations across India, maintained by India Meteorological Department (IMD). As an exemplary demonstration of the utility of the data, basin scale reconstruction of the historical agricultural droughts and its spatial distribution, using the developed EDVSMPD product, is illustrated for a medium sized drought-stricken river basin, namely Wardha, in the central part of India. The resulting SM product for a considerable length of period (more than 30 years) will be immensely useful for many hydro-climatological studies.

Concept of Soil Moisture Ratio for Determining the Spatial Distribution of Soil Moisture Using Physiographic Parameters of a Basin and Artificial Neural Networks (ANNs)

The results of investigations on shaping the soil moisture ratio in the mountain basin of the Mątny stream located in the Gorce region, Poland, are presented. A soil moisture ratio was defined as a ratio of soil moisture in a given point in a basin to the one located in a base point located on a watershed. Investigations were carried out, using a TDR device, for 379 measuring points located in an irregular network, in the 0–25 cm soil layer. Values of the soil moisture ratio fluctuated between 0.75 and 1.85. Based on measurements, an artificial neural network (ANN) model of the MLP type was constructed, with nine neurons in the input layer, four neurons in the hidden layer and one neuron in the output layer. Input parameters influencing the soil moisture ratio were chosen based on physiographic parameters: altitude, flow direction, height a.s.l., clay content, land use, exposition, slope shape, soil hydrologic group and place on a slope. The ANN model was generated in the module data mining in the program Statistica 12. Physiographic parameters were generated using a database, digital elevation model and the program ArcGIS. The value of the network learning parameter obtained, 0.722, was satisfactory. Comparison of experimental data with values obtained using the ANN model showed a good fit; the determination coefficient was 0.581. The ANN model showed a minimal tendency to overestimate values. Global network sensitivity analysis showed that the highest influence on the wetness coefficient were provided by the parameters place on slope, exposition, and land use, while the parameters with the lowest influence were slope, clay fraction and hydrological group. The chosen physiographic parameters explained the values of the relative wetness ratio a satisfactory degree.

Curve Number Estimation for Ungauged Watershed in Semi-Arid Region

The Benanain Watershed is located in East Nusa Tenggara with an area of 3,181 km2 and is divided into 29 sub-watersheds. The East Nusa Tenggara itself is an eastern region of Indonesia with a unique climate condition called semi-arid. The high rainfall intensity occurring in short duration results in large surface runoff and erosion. Floods and erosion in semi-arid areas due to sensitive soils to drought and heavy rainfall extremely. This paper presents the application of the Soil Conservation Services-Curve Number (SCS-CN) real-flood flows through a digital map of soil type, land use, topography, and the heterogeneity of physical condition, especially for ungauged watersheds. The method used is an approach empirical to estimate runoff from the relationship between rainfall, land use, and soil hydrology groups. This watershed has a large area that must analyze every sub-watershed. The land-use of the Benanain watershed is secondary dryland forest by 44.26% and the hydrological soil group on the B group classification with medium to high absorption potential by 46.502% from the total area. The curve number value of the Benanain Watershed ranges from 56.54 to 73.90, where the mean CN value of 65.32. The rainfall (mm) for the 29 sub-watersheds in the Benanain Watershed has decreased by about 74.65% when being surface runoff or only 25.35% of water becomes surface runoff. The relationship between rainfall depth and CN is classified as standard response and trend line (flat slope) equilibrium occurs when rainfall depth value of 56.71 mm and CN is close to 66.30. The high variability of intense rainfall between the rainy season and the dry season had a significant influence on the curve number value in a large watershed area. Further analysis will be more accurate if it is supported by long rainfall data and observation runoff data as a control. Doi: 10.28991/cej-2021-03091711 Full Text: PDF

Flash-flood susceptibility mapping based on XGBoost, random forest and boosted regression trees

Historical exploration of flash flood events and producing flash-flood susceptibility maps are crucial steps for decision makers in disaster management. In this article, classification and regression tree (CART) methodology and its ensemble models of random forest (RF), boosted regression trees (BRT) and extreme gradient boosting (XGBoost) were implemented to create a flash-flood susceptibility map of the Bâsca Chiojdului River Basin, one of the areas in Romania that is constantly exposed to flash floods. The torrential areas including 962 flash flood events were delineated from orthophotomaps and field observations. Furthermore, a set of conditioning forces to explain the flash floods was constructed which included aspect, land use and land cover (LULC), hydrological soil groups lithology, slope, topographic wetness index (TWI), topographic position index (TPI), profile curvature, convergence index and stream power index (SPI). All models indicated the slope as the most important factor triggering the flash flood occurrence. The highest area under the curve (AUC) was achieved by the RF model (AUC = 0.956), followed by the BRT model (AUC = 0.899), XGBoost model (AUC = 0.892) and CART model (AUC = 0.868), respectively. The results showed that the central part of the Bâsca Chiojdului river basin, which covers approximately 30% of the study area, is more susceptible to flash flooding.

Yağışların tarım alanlarında sebep olduğu göllenmelerin Sentinel-1 uydu görüntüleri ile analizi

In this study, the rainfall that was effective between 24.12.2019 - 08.01.2020 in Adana was analyzed together with the daily total precipitation data from 18 Automatic Meteorological Observation Stations located within and around the study area. The study area consists of the central districts of Adana province; Seyhan, Çukurova, Sarıçam and Yüreğir and the district of Karataş. The pondings in the districts mentioned due to these precipitations were analyzed using Sentinel-1 satellite images. Three different images were used as a satellite image in the study; before the precipitation (09.12.2019), during the precipitation (02.01.2020) and at the end of the precipitation (08.01.2020). In addition, the change of soil moisture in the region with precipitation was also examined. Soil Moisture Active Passive (SMAP) was used as a soil moisture data source. In the study; the effects of altitude, slope, soil structure, soil moisture and precipitation on pondings were investigated. Precipitation increased soil moisture up to 2 times, and therefore it is thought that it helped pondings due to the decrease of leakage capacity of the soil. According to the analyses, in regions where ponding is intense; it has been mostly determined that the hydrological soil group is “D” and the slope is below 1%.

Reassessment of the hydrologic soil group for runoff modelling

The hydrologic soil group (HSG) is required for the determination of curve numbers (CN), which are used in a large number of hydrological models to calculate surface runoff during rain events of ungauged catchments. Despite the paramount importance of HSG, it is still based on an assumption made in 1955. We assessed HSG using 249 rainfall simulation experiments carried out in two sets of experiments examining seedbed conditions. One set analyzed the variation within a small (60 ha) catchment while the other examined 32 benchmark soils selected to cover the full range of arable soils on sloping land in temperate humid areas. The assumption made in 1955 that sandy and stony soils have a low HSG (A), while clayey soils of low permeability have a high HSG (D), cannot be supported. Instead, HSG appeared to be governed by surface sealing because CN increased with increasing silt content in the bulk soil and decreasing soil organic matter content in the fine earth fraction. An equation for calculating CN and, in turn, a HSG from these two parameters is provided. This equation also avoids classification-induced errors. The relation holds true for a wide range of rain properties (e.g., rain amount between 0.2 mm and 103 mm; event intensities between 2 mm h−1 and 80 mm h−1), slope gradients (2 %–24 %) and various soil properties (e. g., stone contents up to 40 %, clay contents up to 61 %, sand contents up to 87 %). The CN and, in turn, HSG remained constant throughout the events from the start of runoff until the end of the event, which was up to 49 h later in 32 cases. Autocorrelation within the catchment was strong and the full variation was found within 600 m. Even small catchments are, hence, heterogeneous and their runoff cannot be assigned to a single HSG or a single CN. Rejecting the assumption developed in 1955, which had not been verified since then, has important implications for hydrological modelling but also for the development, implementation and assessment of water conserving land use.

Integrated Hydrologic Study of the Arid and Semi-arid Regions using RST and GIS in the Riyadh Metropolitan Area, Saudi Arabia

Abstract Water is extremely critical for human survival. It is therefore important to efficiently manage integrated water resources, which includes basins, watersheds, and wadies. In this study, the freely available data was used, which included a digital elevation model, soil and geological maps, satellite imageries, and daily precipitation records. Furthermore, remote sensing techniques and geographic information system were also integrated in this study. The linear and areal aspects, along with the longitudinal profile were also included, and the hydrologic soil groups (HSGs), land use/land cover (LULC), and curve number (CN) were identified for the main basin of the Riyadh capital. The morphometric analysis indicated that the total area of the main basin was 8500 km2, with 40 watersheds and the highest stream order as eighth. The drainage density of the main basin was 1.57 km/km2. Impermeable surface constituted most of the basin area, as group D was the most prevalently found HSG, constituting 71% of the total basin area. Additionally, the main basin had a highly steep slope, with varying elevations. Furthermore, four types of LULC were identified in the basin namely urban-based, barren land, cultivated land, and ways. The CN for every cell of the main basin ranged from 64 to 98, and the basin weighted CN was found to be 92. The potential direct runoff ranged from 10 to 59 mm. More than 70% of the total area was found to be vulnerable to high and very high runoffs (> 35 mm). These values confirmed the occurrence of flood events, particularly in urban areas and cultivated lands.

Mapping Coastal Flood Susceptible Areas Using Shannon’s Entropy Model: The Case of Muscat Governorate, Oman

Floods are among the most common natural hazards around the world. Mapping and evaluating potential flood hazards are essential for flood risk management and mitigation strategies, particularly in coastal areas. Several factors play significant roles in flooding and recognizing the role of these flood-related factors may enhance flood disaster prediction and mitigation strategies. This study focuses on using Shannon’s entropy model to predict the role of seven factors in causing floods in the Governorate of Muscat, Sultanate of Oman, and mapping coastal flood-prone areas. The seven selected factors (including ground elevation, slope degree, hydrologic soil group (HSG), land use, distance from the coast, distance from the wadi, and distance from the road) were initially prepared and categorized into classes based on their contribution to flood occurrence. In the next step, the entropy model was used to determine the weight and contribution of each factor in overall susceptibility. Finally, results from the previous two steps were combined using ArcGIS software to produce the final coastal flood susceptibility index map that was categorized into five susceptibility zones. The result indicated that land use and HSG are the most causative factors of flooding in the area, and about 133.5 km2 of the extracted area is threatened by coastal floods. The outcomes of this study can provide decision-makers with essential information for identifying flood risks and enhancing adaptation and mitigation strategies. For future work, it is recommended to evaluate the reliability of the obtained result by comparing it with a real flooding event, such as flooding during cyclones Gonu and Phet.

Determinación del Número de Curva (CN) de la cuenca del Río Portoviejo.

El número de curva (CN) es un método para calcular la precipitación efectiva producida por una tormenta en una determinada área. El presente trabajo de investigación tiene como objetivo determinar el Número de Curva (CN) de la cuenca hidrográfica del río Portoviejo para evaluar y conocer su potencial de escurrimiento. Para la obtención de los parámetros morfométricos de la cuenca y los grupos hidrológicos del suelo (HSG) se utilizó el software ArcGIS y la herramienta HEC-GeoHMS. Los resultados indicaron que los números de curva predominantes para condiciones normales de humedad (AMC II) son de 76, 85 y 82. El grupo hidrológico del suelo con mayor presencia en la cuenca es el tipo D, luego seguido el tipo B y C.

Exponent determination in a poorly gauged basin system in Nigeria based on flow characteristics investigation and regionalization method

In this study, a method for estimating the exponent “n” values of the catchment-area equations of four sub-basins within the poorly gauged Benin-Owena River Basin Development Authority (BORBDA) in Nigeria is presented to enable the estimation of flows at ungauged sites within the basin and the determination of small hydropower (SHP) potential at different locations in each sub-basin and the entire basin. Optimal prediction of streamflow characteristics in poorly gauged basin requires developing a methodology for extrapolation of data from gauged to ungauged sites within the basin. Four sub-catchments of BORBDA, a poorly gauged basin in Nigeria, were investigated using Remote Sensing (RS), Geographic Information System (GIS), statistical techniques, and Natural Resources Conservation Service-Curve Number (NRCS-CN) hydrological model. Discharge values at gauged sites (Qg) were obtained from recorded discharge values collected for 12 months at an established gauging station in each sub-basin. RS and GIS techniques were used to develop classification maps and obtain crucial data like curve number (CN), elevation, Hydrologic Soil Group (HSG), rainfall intensity, slope, area of gauged and ungauged required for evaluating spatial discharge (ungauged) utilizing NRCS-CN model. From the established model for each sub-basin, exponent “n” in the relationship between discharge and catchment area was obtained to be 0.23, 0.41, 0.71, and 0.74. Using the lumped modeling approach, which considers a watershed as a single unit for computation, where watershed parameters and variables were to be averaged produced “n” = 0.52 for BORBDA area, which is within the range of 0.5–0.85 suggested by previous researchers. Obtained BORBDA exponent “n” was validated for use in the entire basin through soil homogeneity test by generating BORBDA soil map which confirms the four sub-basins investigated share similar HSG A, B, and D with BORBDA. The exponent “n” value is useful for predicting flows in ungauged parts of the basin. The exponent “n” value obtained for the basin is helpful in the assessment of discharge and determination of SHP potential at different locations within the poorly gauged BORBDA basin, and the dissemination of the research findings will find practical use and guide to practicing hydrologists in Nigeria and locations around the world with similar challenges of poorly gauged basins particularly Africa and other developing countries.

Estimation of Infiltration Models’ Parameters Using Regression Analysis in Irrigation Fields of Northern Ghana

The quantification of soil infiltration is necessary for the estimation of water accessibility in soils for plant growth and development. Field infiltration tests runs were conducted on agricultural soils in three irrigation sites of Northern Ghana. The field data were fitted into Green and Ampt, Kostiakov, Philip, Holtan, Soil Conservation Service and Horton infiltration models for the determination of the unknown model parameters. Regression analysis at 95% confidence level using GraphPad Prism 8. Laboratory and field data on infiltration were used for the model fitting and the unknown parameters were determined using the calibrated models. The k and n parameters of Kostiakov model at Bontanga study site were found to be k = 28.0027 and n = 0.5902, k = 17.0294 and n = 0.4504 for Golinga and k = 23.0356 and n = 0.6339 for Libga. For all the models, the coefficient of determination ranged from 0.7612 to 0.9876 indicating strong relationships. Only Holtan model gave different values at all the three study sites. The parameter GIa and ic of the Holtan model drawn from hydrologic soil group were the same at all the study sites because of the same vegetative cover and surface conditions. The study observed the values of the parameters to have influenced the models’ performance.

Rainfall prediction to evaluate the flood risk using remote sensing and geographical information system

Abstract: In this study, the runoff curve number map for Navrud watershed in north of Iran was determined based on the soil hydrological group, land-use and land-cover using remote sensing and geographical information system. For this objective, land-cover and Land-use situation maps were prepared using NDVI index and Landsat satellite data, respectively. Runoff curve number maps were determined using the overlay prepared maps in GIS and SCS table. For evaluating the accuracy of estimated curve numbers, runoff maximum discharge was calculated using HEC-HMS model and compared to the observed values. Furthermore, the climate change trend and probabilistic distribution functions were considered to predict the flood risk. The effects of climate change were defined by atmospheric general circulation models for A1B, A2 and B1 scenarios. Error analysis between calculated and observed discharge showed that watershed curve number was determined with acceptable accuracy.

Identification of flash-floods-prone river reaches in Beas river basin using GIS-based multi-criteria technique: validation using field and satellite observations

In view of an exponential increase in the negative impacts of flash-floods globally, the present work aims at the identification of flash-floods-prone river reaches in the Beas river basin, Himachal Pradesh, India using a multi-criteria indexing technique. The flood hazard index (FHI) was computed by implementing analytical hierarchy process (AHP) model on 6 hydrologic parameters influencing flood hazard, namely rainfall intensity, curve number (CN) grid, time of travel, slope, Manning's roughness coefficient and drainage density. The CN grid (empirical parameter to estimate direct surface runoff) was used as one of the parameters which depend upon the land use, hydrologic soil group and hydrologic conditions. It is imperative to mention that remote sensing and geographical information system (GIS) techniques played a crucial role in the preparation of these 6 parameter layers. The AHP model calculates the normalized weights for each parameter using pair-wise comparison matrices. The rainfall intensity and curve number were the factors having the highest normalized weight of 34.52 each. Subsequently, the estimated weights of the parameters and hazard level-wise rating scores were used in a GIS environment to generate FHI. The generated FHI raster was masked using floodplain layer within geomorphology map and river buffer to identify flash-floods-affected river reaches. The generated flash-floods map was validated by historical flash-floods ground points, field observations and remote sensing data. The results depicted that the river reaches in the north and east of the Beas basin are susceptible to flash-floods which are mainly governed by heavy rainfall intensity and high runoff characteristics. The river stretches namely Bahang–Manali (Beas), Kullu–Bhuntar (Beas) and Manikaran–Kheer-Ganga (Parvati) have been categorized into very high and high flash-floods zones. Decreasing trend of normalized differential vegetation index (NDVI) was observed for river reaches falling within the very high and high zones indicating the vegetation loss post successive flash-floods events. The river order 2 lies in the very high and high flash-floods zones, indicating the fact that the contribution of tributaries is significant to flood events. Flash-floods map will serve as catastrophic product, which will help policymakers to take suitable measures to reduce the risk of flash-floods.

Sara4r: an R graphical user interface (GUI) to estimate watershed surface runoff applying the NRCS – curve number method

Abstract This paper introduces a graphical user interface (GUI) for the R software that allows the rainfall-runoff relationship to be calculated, using the curve number method. This GUI is a raster-tool whose outputs are runoff estimates calculated using land use/land cover and hydrologic soil group maps. The package allows the user to select among three different antecedent moisture conditions and includes modifications about the initial abstraction parameter. We tested this GUI with data derived from two watersheds in Mexico and the outputs were compared with those produced using a well-established GIS tool in a vector environment. The results produced by these two approaches were practically the same. The main advantages of our package are: (1) ‘Sara4r’ is faster than previous vector based tools; (2) it is easy to use, even for people with no previous experience using R; (3) the modular design allows the integration of new routines; and (4) it is free and open source.

Mapping saturated hydraulic conductivity from open-access soil databases

Hydrologic models such as the curve number request soil hydraulic variables, among other parameters, as input. In most countries, this represents a problem due to the lack of soil cartography and the high spatial variability of this type of variable. This situation is changing somewhat with the development of open-data sharing policies and the use of pedotransfer functions. Nevertheless, the constant influx of new data may involve repeating analyses too often, which, depending on the type, may represent a high cost or be time consuming. The present study analyses a method for updating saturated hydraulic conductivity (Ks) maps based on kriging interpolation to achieve a regional curve number hydrologic soil group map in Spain based on open-access soil databases. The results indicate that incorporation of the new soil databases improves the existing regional interpolated Ks map showing a high correlation with the lithological distribution. Generally the Iberian lithological siliceous domain presents higher values (26 mm/h) than the Iberian sedimentary domain (22 mm/h). The kriging result also diminishes the root mean square error in the overall map from 12 to 15 mm/h to 9 mm/h. This result was achieved with two validation methods: cross-validation and subsets. As a derivative data, the resultant Ks map has been used to generate a hydrologic soil group map dividing the study area into curve number soil types: B and C which fits with previous regional hydrological studies. Therefore, this method may help to achieve Ks and derived maps, such as hydrologic soil group maps, in countries where there is a lack of soil cartography, improving the input data in hydrological models.

Identification of Owan Catchment Run-of-River Hydropower Potential Sites in Benin Owena River Basin Nigeria Using GIS And RS Procedures

Hydropower is recognized internationally as a source of clean, affordable, and reliable energy that has contributed in a significant way to the global energy supply mix but unfortunately, this is not the case in Nigeria considering hydropower potential of 15 GW where only approximately 2 GW (13%) has been harnessed. Nigeria Small Hydropower (SHP) level is low, as less than 0.1 GW out of 3.5 GW SHP potential is available in a country of over 200 million people with potentials of 333BCM of surface water annually which can be used to increase energy access especially in the rural area where the percentage in 2018 is 34. In this study, Natural Resources Conservation Service - Curve Number (NRCS-CN) method which calculates surface runoff volume for a particular rainfall event in a watershed was applied in conjunction with Remote Sensing (RS) and Geographic Information System (GIS). Land Use Land Cover (LULC) classes of Owan Sub-basin were delineated from Landsat 8 satellite Image using Image Classification procedure and integrated with the hydrologic soil group (HSG) of the sub-basin in a GIS environment to obtain runoff Curve Numbers (CNs) for this study. The estimated CNs and rainfall data of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN – CDR) of the study area for the year 2018 were used to calculate the peak discharges over 125 mapped out points at 2km interval in Owan river. The gauging station data correlates NRCS-CN with a coefficient of 68 % while the Nigerian Meteorological Services Agency (NIMET) data compared with PERSIANN-CDR yielded a 70 % correlation. Using the basin hydrometric indicators of 2% minimum slope and 10m available head which must exist between two points before a site can be considered for ROR hydropower, 20 points were identified in Owan with power range from 423.015kW to 5,456.646kW at 92% available flow exceedance annually. This study revealed that NRCS-CN method combined with RS and GIS can simulate discharge successfully using watershed hydrometry in the absence of weak hydrological data. Also, owing to a significant degree of agreement between the observed and calculated runoff, the method, and models employed for this study are recommended for field applications in Benin-Owena River Basin, Nigeria at large, and other regions with data scarcity challenges hydrologically. Keywords : run-of-river, hydropower potential, Remote Sensing, Geographic Information System, NRCS-CN model. DOI: 10.7176/CER/12-10-05 Publication date: October 31 st 2020

Potential Infiltration Determination in Areas of Influence of the Zona Bananera Aquifer in Northern Colombia

Through the implementation of geographic information systems (GIS) and images of the study area obtained by remote sensors, the curve number method (NC) was implemented in this research, in order to determine potential recharge zones in two micro-basins in the aquifer region called Zona Bananera, located in the department of Magdalena in Northern Colombia. Potential infiltration of the area was estimated and the hydrological response for precipitation events with different return periods was evaluated. The predominant hydrological soil groups were found to be A and B, with 77.4% (84115.2 ha) in the Sevilla River micro-basin and 81.6% (7466.1 ha) in La Aguja micro-basin. The Sevilla River micro-basin showed both the best water regulation and enhancement of the infiltration process, evidenced by the existence of low as well as medium values ​​of curve number and potential surface runoff. The highest values ​​of potential runoff were in the middle and lower part of the micro-basins, where there are extensive areas covered with banana crops; indicating that anthropic intervention is a determining factor in the area’s hydrological response. Under current conditions, the micro-basins show a minimal risk of erosive processes for rainfall with return periods of less than 5 years, due to runoff occurrence of less than 100 mm. Within the study area, it was found that approximately 3380 hectares show favorable conditions to contribute to the recharge of the Zona Bananera aquifer, making it a strategic conservation area.

EMPLOYING MODERN TECHNIQUES IN STUDYING SOIL AND WATER RESOURCES IN SELECTED AREA OF NORTH WESTERN COASTAL REGIONS, EGYPT

The study area is extending from Minqar Alousran at the east to Beer Qaaem at the west, Marsa Matrouh at the north to Jable Khaled at the south. The total studied area is about 345563.52 Fadden. Ninety eight soil profiles were selected representing the geomorphic units. The qualitative approach was used to land evaluation. Hydrological and morphometric characteristics have been obtained. Four main geomorphic units were identified: Coastal Plain, Northern Plateau, Southern Plateau and Lybian Plateau. The soils ranged from very shallow to very deep. The dominant soil texture is between sandy clay loam to sand. These soils are moderately to extremely calcareous. These soils are slightly to strongly alkaline. The studied soils in the geomorphic units are classified as follow: Lithic Haplocalcids, Typic Haplocalcids, Typic Torriorthents, Gypsic Aquisalids, Typic Calcigypsids, Lithic Torriorthents and Oxyaquic Torripsamments. Land evaluation for the studied soils. The study aimed also to predict annual peak flow and runoff water volume, as well as the 20, 10, 5, 3, and 2year return periods. Results referred that El-Hraka basin characterized by an area of 178.31km2, basin length of 33.70 km, perimeter of 132.8 km, and gentle slope of 0.012 m/m. There are four types of land use/land cover in the study basin named: agriculture land, bare land, rocky areas and urban representing 3.45, 92.98, 3.41 and 0.16% of El Hraka basin, respectively. There are two hydrologic soil group of the study basin A and C depending on the soil texture. The Curve Number (CN) depending on the land use / land cover and the hydrologic soil groups. Its average values are 73.67 for El-Hraka basin. The annual runoff water volumes are 10583.29 m3 that recharge the groundwater reservoir. However, the annual infiltration volumes are 8195.01m3. The peak flow of the 20, 10, 5, 3 and 2 year return periods flash flood is 29.24, 17.98, 9.50, 3.78 and 0.75 m3/s respectively. The runoff volume of the 20, 10, 5, 3 and 2 year return-periods is 2.78 million, 1.71 million, 906,578.6, 359,883and 69,989.4 m3 respectively for the study basin.