An integrated study of earth resources in the state of California using remote sensing techniques

The author has identified the following significant results. The effects on estimates of monthly volume runoff were determined separately for each of the following parameters: precipitation, evapotranspiration, lower zone and upper zone tension water capacity, imperviousness of the watershed, and percent of the watershed occupied by riparian vegetation, streams, and lakes. The most sensitive and critical parameters were found to be precipitation during the entire year and springtime evapotranspiration

An integrated study of earth resources in the state of California using remote sensing techniques

There are no author-identified significant results in this report

Can the introduction of the topographic indices in LPJ-GUESS improve the spatial representation of environmental variables?

Ecosystem modelling is an always evolving science trying to catch the complexity of the nature and its principles to model environmental responses in a realistic way. Over and over, models try to introduce more variables and interactions to achieve better representations of phenomena of interest like the responses of the ecosystem to a fast changing world (climate change, land use change). LPJ-GUESS is a flexible dynamic ecosystem model widely used to model the structure and dynamics of terrestrial ecosystems. It is based on plant physiology, biochemical cycles and feedbacks on independent gridcells, there is no consideration of lateral transfer of water between cells. On the other hand, soil moisture is essential for vegetation growth and its distribution is known to be driven by the topography of the landscape, which drives the lateral transfer of water. Based on this, it was considered important to assess the modelled spatial representation of environmental variables (soil moisture, LAI) from LPJ-GUESS and to evaluate a possible method to include the effect of topography over the hydrology in LPJ-GUESS model. For this, Alergaarde catchment (smooth relief) was chosen and by the use of correlation analysis and visual interpretation the following issues were studied, 1) Importance of topography on the spatial distribution of environmental variables based on topographic indices (Ln (Drainage area), tan ( angle slope) and topographic wetness index, TWI); 2) LPJ-GUESS ability to catch the environmental variables spatial distribution and 3) Implementation of a coupled LPJ-GUESS - topographic indices model to account for the topography influence on hydrology and assessment of its performance on modelling the spatial patterns of environmental variables. Results of the first two topics showed how LPJ-GUESS could not catch the spatial variations of satellite based LAI, and that even the gentle topography of the catchment was an important issue on explaining the heterogeneity of vegetation related variables. Nevertheless, there are many factors, like climate conditions, which affect the strength of this relationship, as reflected on low correlation coefficients (never over 0.25), the variable correlation coefficients along the year and the identification of areas more related to the topographic indexes than others. Additionally, TWI was selected, based on its higher correlations with respect to the other topographic indices, to be one used to represent the topography influence in the catchment. The integrated model, LPJ-Topographic index (LPJ-TI), use the TWI to make a cell wise characterization and create weights affecting the water inputs to the soil layer as a way to account for hydrological processes driven by topography. LPJ-TI showed localized and time dependent improvement of the spatial representation of the satellite based LAI. These results confirm the need to include the topographic influence on the hydrological module of LPJ-GUESS and present a possible low computational method to start working on.Ecosystem modelling is an always evolving science trying to catch the complexity of the nature and its principles to model the ecosystem in a realistic way. Over and over, models are being modified or complemented to make better predictions and achieve better representations of phenomena of interest like the responses of the ecosystem to a fast changing world (climate change, land use change). LPJ-GUESS is a flexible dynamic ecosystem model widely used to model vegetation, water and carbon cycles in terrestrial ecosystems. In order to model an ecosystem in LPJ-GUESS the area of interest is gridded in cells, where every cell is modelled independently; that is there is no communication between the cells so important interactions such as water movement do not occur; dynamic particularly important at watershed levels. Topography is an important driver on determining the flow of water on a catchment, thus influences de distribution of water over the area, process being evident on differential soil moisture, vegetation, vegetation growth, decomposition, etc. Topographic characteristic can be summarized on topographic indices, which aim to represent the key hydrological processes driven by topography in a simplified but realistic way. Some of the most used topographic indices related to the distribution of water over the landscape are: slope, drainage area and, a combination of former ones, the topographic wetness index. Based on the former information, the current thesis considered important to assess the modelled LPJ-GUESS distribution of the environmental variables values over the area and to evaluate a method to include the effect of topography over the hydrology in the model. For this; Alergaarde catchment, a catchment with little relief located on central Jutland Denmark, was chosen, and by the use of correlation analysis and visual interpretation of the observed and simulated spatial patterns of environmental variables (soil moisture and vegetation development represented as Leaf area index - LAI) the following issues were studied: 1) Importance of topography on the spatial distribution of environmental variables based on topographic indices (Ln (Drainage area), tan ( angle slope) and topographic wetness index, TWI); 2) LPJ-GUESS ability to catch the environmental variables spatial distribution and 3) Implementation of a coupled LPJ-GUESS - topographic indices model ( LPJ-Topographic index, LPJ-TI) to account for the topography influence on hydrology and assessment of its performance on modelling the spatial patterns of environmental variables. The coupled model, LPJ-TI, bases on making a cell wise characterization of the catchment based on giving weights to the range of values of the topographic index and using them to affect the water going into the soil layer as a way to account for hydrological processes driven by topography. Results and conclusions The results of the first two topics showed how LPJ-GUESS could not catch the spatial variations of LAI, and that even the gentle topography of the catchment was an important issue on explaining the heterogeneity of vegetation related variables. Nevertheless, it was also noticed that there are many factors (ex. weather conditions, land management activities) affecting the strength of the relationship between topography and plant development (i.e. LAI), as reflected by the low correlation coefficients (never above 0.25), stronger and lower correlation depending on the month in consideration, and the identification of areas more related to the topographic indexes than others within the same time frame. Additionally on the first topic, TWI was proven to be a good index for demonstrating the association of topography with LAI and was therefore selected to be used on the model LPJ-TI. Regarding the last issue, LPJ-TI showed localized and time dependent improvement of the spatial representation of LAI. These results confirm the need to include the topographic influence on the hydrological module of LPJ-GUESS and present a possible low computational method to start working on

An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources

[EN] The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales. Whilst these data effectively characterize water cycle variability at regional to global scales, they are less suitable for sustainable management of local water resources, which needs detailed information to represent the spatial heterogeneity of soil and vegetation. The following questions are critical to effectively exploit information from remotely sensed and in situ Earth observations (EOs): How to downscale the global water cycle products to the local scale using multiple sources and scales of EO data? How to explore and apply the downscaled information at the management level for a better understanding of soil-water-vegetation-energy processes? How can such fine-scale information be used to improve the management of soil and water resources? An integrative information flow (i.e., iAqueduct theoretical framework) is developed to close the gaps between satellite water cycle products and local information necessary for sustainable management of water resources. The integrated iAqueduct framework aims to address the abovementioned scientific questions by combining medium-resolution (10 m-1 km) Copernicus satellite data with high-resolution (cm) unmanned aerial system (UAS) data, in situ observations, analytical- and physical-based models, as well as big-data analytics with machine learning algorithms. This paper provides a general overview of the iAqueduct theoretical framework and introduces some preliminary results.The authors would like to thank the European Commission and Netherlands Organisation for Scientific Research (NWO) for funding, in the frame of the collaborative international consortium (iAqueduct) financed under the 2018 Joint call of the Water Works 2017 ERA-NET Cofund. This ERA-NET is an integral part of the activities developed by the Water JPI (Project number: ENWWW.2018.5); the EC and the Swedish Research Council for Sustainable Development (FORMAS, under grant 2018-02787); Contributions of B. Szabo was supported by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00088/18/4).Su, Z.; Zeng, Y.; Romano, N.; Manfreda, S.; Francés, F.; Ben Dor, E.; Szabó, B.... (2020). An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources. Water. 12(5):1-36. https://doi.org/10.3390/w12051495S13612

Prediction of Biome-Specific Potential Evapotranspiration in Mongolia under a Scarcity of Weather Data

We propose practical guidelines to predict biome-specific potential evapotranspiration (ETp) from the knowledge of grass-reference evapotranspiration (ET0) and a crop coefficient (Kc) in Mongolia. A paucity of land-based weather data hampers use of the Penman–Monteith equation (FAO-56 PM) based on the Food and Agriculture Organization (FAO) guidelines to predict daily ET0. We found that the application of the Hargreaves equation provides ET0 estimates very similar to those from the FAO-56 PM approach. The Kc value is tabulated only for crops in the FAO-56 guidelines but is unavailable for steppe grasslands. Therefore, we proposed a new crop coefficient, Kc adj defined by (a) net solar radiation in the Gobi Desert (Kc adjD) or (b) leaf area index in the steppe region (Kc adjS) in Mongolia. The mean annual ETp obtained using our approach was compared to that obtained by FAO-56 guidelines for forages (not steppe) based on tabulated Kc values in 41 locations in Mongolia. We found the differences are acceptable (RMSE of 0.40 mm d-1) in northern Mongolia under high vegetation cover but rather high (RMSE of 1.69 and 2.65 mm d-1) in central and southern Mongolia. The FAO aridity index (AI) is empirically related to the ETp/ET0 ratio. Approximately 80% and 54% reduction of ET0 was reported in the Gobi Desert and in the steppe locations, respectively. Our proposed Kc adj can be further improved by considering local weather data and plant phenological characteristics

Modernization using the structured system design of the Bhadra Reservoir Project, India: an intervention analysis

Performance evaluationIrrigation programsModernizationParticipatory managementFarmer participationFarmer-agency interactionsFarmers' attitudesRemote sensingRiceIrrigated farmingWater distributionWater supplyProductivity

Densification of spatially-sparse legacy soil data at a national scale: a digital mapping approach

Digital soil mapping (DSM) is a viable approach to providing spatial soil information but its adoption at the national scale, especially in sub-Saharan Africa, is limited by low spread of data. Therefore, the focus of this thesis is on optimizing DSM techniques for densification of sparse legacy soil data using Nigeria as a case study. First, the robustness of Random Forest model (RFM) was tested in predicting soil particle-size fractions as a compositional data using additive log-ratio technique. Results indicated good prediction accuracy with RFM while soils are largely coarse-textured especially in the northern region. Second, soil organic carbon (SOC) and bulk density (BD) were predicted from which SOC density and stock were calculated. These were overlaid with land use/land cover (LULC), agro-ecological zone (AEZ) and soil maps to quantify the carbon sequestration of soils and their variation across different AEZs. Results showed that 6.5 Pg C with an average of 71.60 Mg C ha–1 abound in the top 1 m soil depth. Furthermore, to improve the performance of BD and effective cation exchange capacity (ECEC) pedotransfer functions (PTFs), the inclusion of environmental data was explored using multiple linear regression (MLR) and RFM. Results showed an increase in performance of PTFs with the use of soil and environmental data. Finally, the application of Choquet fuzzy integral (CI) technique in irrigation suitability assessment was assessed. This was achieved through multi-criteria analysis of soil, climatic, landscape and socio-economic indices. Results showed that CI is a better aggregation operator compared to weighted mean technique. A total of 3.34 x 106 ha is suitable for surface irrigation in Nigeria while major limitations are due to topographic and soil attributes. Research findings will provide quantitative basis for framing appropriate policies on sustainable food production and environmental management, especially in resource-poor countries of the world

Simulation and management of on-demand irrigation systems: a combined agrohydrological and remote sensing approach

Rational use of water resources in agriculture requires improvements in the efficiency of irrigation. Many irrigation systems, particularly in Mediterranean regions, have been enhanced by replacing open channel conveyance systems with pressurised pipelines. This allows to provide water on-demand. Increased demand of water for civil and industrial uses and a progressive reduction of available water resources compel a more efficient use of irrigation water. To achieve this goal irrigation managers need to understand and to monitor the processes which determine the operation of an irrigation system.In this thesis a procedure integrating the agrohydrological aspects of irrigation with hydraulic and management aspects has been developed. The procedure named SIMODIS (SImulation and Management of On-Demand Irrigation Systems) is based on the integration of different tools such as agrohydrological and hydraulic simulation models, remote sensing and GIS techniques.An irrigation system is described as a set of elementary (e.g. individual fields) connected by the pressurised conveyance system. The spatial distribution of soil water deficit in each elementary unit is computed daily by combining the soil water model SWAP with occasional satellite-based estimates of crop water requirements. A methodology has been developed to obtain spatially distributed input data for the soil water model SWAP i.e. the soil hydraulic properties and the upper and lower boundary conditions.Multispectral satellite images are used to map the crop coefficients needed for the definition of the SWAP upper boundary condition in each elementary unit of the irrigation district. Two different approaches have been proposed. The first is based on classification techniques, where clustering algorithms are applied to derive the spectral classes corresponding to different crop coefficient values. In the second approach, the crop coefficient is analytically related to the canopy variables determining the potential evapotranspiration i.e. leaf area index, surface albedo and crop height. At-surface directional spectral reflectance are used to estimate these canopy variables from which the value of crop coefficient is calculated.The spatial distribution of farmers' water demand is derived on a daily basis from the soil water deficit according to predefined irrigation scheduling criteria. Before applying this farmers' water demand distribution for the given day, the SIMODIS procedure assess whether water demand is consistent with the available amount of water resources and with the structural and operational constraints imposed by the conveyance and distribution system. For this purpose a steady-state simulation model of pipeline hydraulics is used in SIMODIS. The final distribution of farmers' water demand is then resulting from a three-tiered adaptation of irrigation schedule considering: i) the limitation of flow rate at delivery outlets, ii) the limitation of available water resources, iii) the required minimum hydraulic head at the delivery outlets.The procedure SIMODIS has been applied in the Gromola irrigation district of approximately 3000 ha in southern Italy. Measurements of irrigation volumes were used to identify the parameters driving irrigation scheduling. Irrigation efficiency indicators were calculated from the spatial distribution of actual transpiration rates and of the corresponding irrigation volumes applied. To illustrate the use of SIMODIS in support of irrigation decision making, alternative scenarios of water management were simulated and compared.The development of SIMODIS demonstrated that agrohydrological simulation models and remote sensing can be effectively combined to describe the operation of an irrigation system. These techniques have reached a sufficient degree of reliability to be transferred to practical applications. The estimation of crop coefficients by means of remote sensing techniques is of general usefulness in the definition of the upper boundary condition of distributed hydrological simulation models and it can be applied to evaluate with satisfactory accuracy the crop water requirements at regional scale. In the future new types of satellite sensors will probably allow for a more precise determination of the canopy variables, thus providing novel opportunities in the integration between agrohydrological simulation models and remote sensing techniques.</p