Sarann Ly

Irrigation plays a very important role in rice and other crops production in rural Cambodia where over 75% of the people are residing and depend on agriculture as a source of livelihood and family incomes. Cambodia has an ancient tradition of irrigated agriculture dating back to Angkor Era started in9th Century. After several decades of civil wars, the country aims to become one of the major rice exporters and is therefore investing heavily in the expansion and restoration of its irrigation systems. Several of these multi-million-dollar projects are built by different foreign contractors/developers using their preferred design standard in the absence of national technical standards to apply across all development projects. Cambodia’s irrigation and drainage has many similarities with other countries but also has some unique characteristics, which do not permit the automatic transfer of design standards from other countries to be applied in Cambodia. The draft of Cambodian 2019-2033 ...

This study aims at characterizing agricultural soils’ structure depending on the tillage system: conventional tillage or conservational tillage. Tillage reduction is an increasing practice, but the micro-structural effects on soils and on their hydrodynamic parameters are still not well described. Recent research shows non-converging results. Our point is to highlight fundamental differences in structure through characterization of soils porosity’s parameters using X-ray microtomography measurements coupled to image analysis. This attempt is in line with a more integrated experiment of which the aim is to quantify the effects of tillage intensity on lateral flow production, and finally on global water balance. Parameters’ measurements consist in a combined approach, based on two different space-time scales of exploration: fundamental scale, with soil sampling campaign for microtomography analysis, and field scale, with continuous flow measurements (plots’ dimensions: 18*28 m). For t...

Spatial interpolation of precipitation data is of great importance for hydrological modelling. The methods of geostatistics (krigings) become more popular to make spatial interpolation from point measurement to distributed hydrological models. However, most of existing geostatistic algorithms are available only for single-moment data. The first step of Kriging computation is the semi-variogramme modelling which usually uses only one variogramme model for all-day data. The objective of this paper is to review the implementation of an algorithm of spatial interpolation methods for daily rainfall and to compare the results of geostatistic and deterministic approaches. In this study, we will use daily rainfall data from 70 rain gauges in the hilly landscape of Ourthe and Ambleve Basins in Belgium (2751 km2). This area lies between 35 and 690 m in elevation and consists of river networks which are the tributaries of the Meuse River. The proposed algorithm will use the method of Cressie’s...

An integrated hydrological-hydraulic model employing the 2-D local inertial equation as the core is established for effective numerical simulation of surface water flows in a great lake and its floodplain. The model is a cascade of validated hydrological and hydraulic sub-models. The model was applied to simulating the surface water flows of the Tonle Sap Lake and its floodplain in Cambodia using the roughness coefficient value calibrated comparing with a remote-sensing data set. The resulting model reasonably handles backwater flows during the rainy season and simulates the propagations of wet and dry interfaces without numerical instability, owing to a proper setting of time step supported by a novel numerical stability analysis. Sensitivity analysis of the surface water dynamics focusing on the setting of roughness coefficient and the backwater effect was also carried out. Overall, utilizing the 2-D local inertial equation in the assessment of lake water dynamics is a new modelli...

This study aims at characterizing agricultural soils' structure depending on the tillage system: conventional tillage or conservational tillage. Tillage reduction is an increasing practice, but the micro-structural effects on soils and on their hydrodynamic parameters are still not well described. Recent research shows non-converging results. Our point is to highlight fundamental differences in structure through characterization of soils porosity's parameters using X-ray microtomography measurements coupled to image analysis. This attempt is in line with a more integrated experiment of which the aim is to quantify the effects of tillage intensity on lateral flow production, and finally on global water balance. Parameters' measurements consist in a combined approach, based on two different space-time scales of exploration: fundamental scale, with soil sampling campaign for microtomography analysis, and field scale, with continuous flow measurements (plots' dimensions: 18*28 m). For their part, parameters for water balance determination (precipitation, evapotranspiration…) are monitored on the field. All of these measurements have the main objective of hydrological modeling enhancement by taking into account a better lateral flow description. Discussion in this paper will focus on the first results obtained by X-ray microtomography measurements. Our experiment takes place in Gentinnes (Walloon Brabant, Belgium), on a field organized in a split-plot scheme. Since 2004, plots have been cultivated in conventional tillage or in reduced tillage. The latter consists in sowing after stubble ploughing of about 10cm. The crop rotation is sugar beet followed by winter wheat. The soil is mainly composed of silt loam. Soils samples, with a 3 cm diameter and a 5 cm height, were removed from the upper layer (Ap horizon) for both management practices. Samples are scanned by X-ray microtomography using a Skyscan-1172 high-resolution desk-top micro-CT system (Skyscan, Kontich, Belgium). The cone beam source operated at 100 kV, using an aluminium filter. The detector configuration, i.e. 1048×2000 pixels 16-bit X-ray camera, and the distance source-object-camera were adjusted to produce images with a pixel size of 17 µm. This resolution allows us to visualize both meso- and macro- porosity. In this study, half the samples were placed under a 15000 kPa pressure (corresponding pressure for the wilting point) in Richards' apparatus in order to empty the meso- and macro-porosity. To determine a priori the class of porosity for the samples, relations between water retention and pressure head can be plotted using this apparatus. Scanning results consist in 2D images. The 2D images are recombined to form 3D structure. Then the pore network can be analyzed through useful factors like size distribution, shape, connectivity, orientation, tortuosity etc. The oral presentation will report the first analysis results of images obtained from the microtomographic investigation of soil samples. Soil sampling and scanning methods will be detailed. Main porosity parameters will be discussed, soil's structure will be defined, and finally differences according to the agricultural practices will be put in evidence.

Spatial interpolation of precipitation data is of great importance for hydrological modelling. The methods of geostatistics (krigings) become more popular to make spatial interpolation from point measurement to distributed hydrological models. However, most of existing geostatistic algorithms are available only for single-moment data. The first step of Kriging computation is the semi-variogramme modelling which usually uses only one variogramme model for all-day data. The objective of this paper is to review the implementation of an algorithm of spatial interpolation methods for daily rainfall and to compare the results of geostatistic and deterministic approaches. In this study, we will use daily rainfall data from 70 rain gauges in the hilly landscape of Ourthe and Ambleve Basins in Belgium (2751 km²). This area lies between 35 and 690 m in elevation and consists of river networks which are the tributaries of the Meuse River. The proposed algorithm will use the method of Cressie's Approximate Weighted Least Squares to fit among sevens semi-variogramme models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) to daily sample semi-variogrammes. These seven models are computed on a daily basis. Firstly, one model is chosen by considering the minimum of least squares coefficient. Secondly, if the chosen model gives negative interpolated values, other models will be chosen again until the result become positive. Cross validation will be used to compare the interpolation performance of geostatistic to deterministic methods usually known as Thiessen polygon and Inverse Distance Weighting (IDW). KEYWORDS: spatial interpolation, geostatistic, Kriging, semi-variogramme IDW, Thiessen, daily rainfall, Ourthe, Ambleve

Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using rain gauges or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall, which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrolog...

ABSTRACT Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (krigings) are widely used in spatial interpolation from point measurement to continuous surfaces. However, the majority of existing geostatistical algorithms are available only for single-moment data. The first step in kriging computation is the semi-variogram modelling which usually uses only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. In this study, we used daily rainfall data from 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, Cressie's Approximate Weighted Least Squares method was used to fit seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) to daily sample semi-variogram on a daily basis. Seven selected raingages were used to compare the interpolation performance of these algorithms applied to many degenerated-raingage cases. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably interpolation with the Thiessen polygon that is commonly used in various hydrological models. Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) presented the highest Root Mean Square Error (RMSE) between the geostatistical and IDW methods. Ordinary Kriging (ORK) and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases.

ABSTRACT Precipitation traditionally observed using raingages or weather stations, is one of the main parameters that have direct impact on runoff production. Precipitation data require a preliminary spatial interpolation prior to hydrological modeling. The accuracy of modelling result depends on the accuracy of the interpolated spatial rainfall which differs according to different interpolation methods. The accuracy of the interpolated spatial rainfall is usually determined by cross-validation method. The objective of this study is to assess the different interpolation methods of daily rainfall at the watershed scale through hydrological modelling and to explore the best methods that provide a good long term simulation. Four versions of geostatistics: Ordinary Kriging (ORK), Universal Kriging (UNK), Kriging with External Dridft (KED) and Ordinary Cokriging (OCK) and two types of deterministic methods: Thiessen polygon (THI) and Inverse Distance Weighting (IDW) are used to produce 30-year daily rainfall inputs for a distributed physically-based hydrological model (EPIC-GRID). This work is conducted in the Ourthe and Ambleve nested catchments, located in the Ardennes hilly landscape in the Walloon region, Belgium. The total catchment area is 2908 km2, lies between 67 and 693 m in elevation. The multivariate geostatistics (KED and OCK) are also used by incorporating elevation as external data to improve the rainfall prediction. This work also aims at analysing the effect of different raingage densities and position used for interpolation, on the stream flow modelled to get insight in terms of the capability and limitation of the geostatistical methods. The number of raingage varies from 70, 60, 50, 40, 30, 20, 8 to 4 stations located in and surrounding the catchment area. In the latter case, we try to use different positions: around the catchment and only a part of the catchment. The result shows that the simple method like THI fails to capture the rainfall and to produce good flow simulation when using 4 raingages. The KED and UNK are comparable to other methods for a raingage case in which stations are located around the catchment area, especially in the high elevation catchment but the worst methods for other raingage position cases where the rainfall stations are located only at a part and mostly outside of the catchment area. However, three methods (IDW, ORK and OCK) can overcome this problem since they are more robust and can provide good performance of simulation in all raingage densities. When using 70, 60, 50, 40, 30, 20, 8 raingages in the catchment area (2908 km2), no substantial differences in model performance are observed.

ABSTRACT Spatial interpolation of precipitation data is of great importance for hydrological modelling. The methods of geostatistics (krigings) become more popular to make spatial interpolation from point measurement to distributed hydrological models. However, most of existing geostatistic algorithms are available only for single-moment data. The first step of Kriging computation is the semi-variogramme modelling which usually uses only one variogramme model for all-day data. The objective of this paper is to review the implementation of an algorithm of spatial interpolation methods for daily rainfall and to compare the results of geostatistic and deterministic approaches. In this study, we will use daily rainfall data from 70 rain gauges in the hilly landscape of Ourthe and Ambleve Basins in Belgium (2751 km²). This area lies between 35 and 690 m in elevation and consists of river networks which are the tributaries of the Meuse River. The proposed algorithm will use the method of Cressie's Approximate Weighted Least Squares to fit among sevens semi-variogramme models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) to daily sample semi-variogrammes. These seven models are computed on a daily basis. Firstly, one model is chosen by considering the minimum of least squares coefficient. Secondly, if the chosen model gives negative interpolated values, other models will be chosen again until the result become positive. Cross validation will be used to compare the interpolation performance of geostatistic to deterministic methods usually known as Thiessen polygon and Inverse Distance Weighting (IDW). KEYWORDS: spatial interpolation, geostatistic, Kriging, semi-variogramme IDW, Thiessen, daily rainfall, Ourthe, Ambleve