A spatial stochastic algorithm to reconstruct artificial drainage networks from incomplete network delineations

Contact: [email protected], [email protected], [email protected] spatial stochastic algorithm that aims to reconstruct an entire artificial drainage network of a cultivated landscape from disconnected reaches of the network is proposed here. This algorithm uses random network initialisation and a simulated annealing algorithm, both of which are based on random pruning or branching processes, to converge the multi-objective properties of the networks; the reconstructed networks are directed tree graphs, conform to a given cumulative length and maximise the proportion of reconnected reaches. This algorithm runs within a directed plot boundaries lattice, with the direction governed by elevation. The proposed algorithm was applied to a 2.6-km2 catchment of a Languedocian vineyard in the south of France. The 24-km-long reconstructed networks maximised the reconnection of the reaches obtained either from a hydrographic database or remote sensing data processing. The distribution of the reconstructed networks compared to the actual networks was determined using specific topographical and topological metrics on the networks. The results show that adding data on disconnected reaches to constrain reconstruction, while increasing the accuracy of the reconstructed network topology, also adds biases to the geometry and topography of the reconstructed network. This network reconstruction method allows the mapping of uncertainties in the representation while integrating most of the available knowledge about the networks, including local data and global characteristics. It also permits the assessment of the benefits of the remote sensing partial detection process in drainage network mapping

Simulating the effects of spatial configurations of agricultural ditch drainage networks on surface runoff from agricultural catchments

The study of runoff is a crucial issue because it is closely related to flooding, water quality and erosion. In cultivated catchments, agricultural ditch drainage networks are known to influence runoff. As anthropogenic elements, agricultural ditch drainage networks can therefore be altered to better manage surface runoff in cultivated catchments. However, the relationship between the spatial configuration, i.e., the density and the topology, of agricultural ditch drainage networks and surface runoff in cultivated catchments is not understood. We studied this relationship by using a random network simulator that was coupled to a distributed hydrological model. The simulations explored a large variety of spatial configurations corresponding to a thousand stochastic agricultural ditch drainage networks on a 6.4 km2 Mediterranean cultivated catchment. Next, several distributed hydrological functions were used to compute water flow-paths and runoff for each simulation. The results showed that (i) denser networks increased the drained volume and the peak discharge and decreased hillslopes runoff, (ii) greater network density did not affect the surface runoff any further above a given network density, (iii) the correlation between network density and runoff was weaker for small subcatchments (< 2 km2) where the variability in the drained area that resulted from changes in agricultural ditch drainage networks increased the variability of runoff and (iv) the actual agricultural ditch drainage network appeared to be well optimized for managing runoff as compared with the simulated networks. Finally, our results highlighted the role of agricultural ditch drainage networks in intercepting and decreasing overland flow on hillslopes and increasing runoff in drainage networks

A knowledge - based system to assist in the design of soil survey schemes

Soil survey information with quantified accuracy is relevant to decisions on land use and environmental problems. To obtain such information statistical strategies should be used for collecting and analysing data. A survey project based on a statistical sampling strategy requires a soil survey scheme specifying which sites are to be sampled, which data are to be recorded and how they are to be analysed statistically. The efficiency of such a scheme is determined by the accuracy of the survey results and the cost of operation. This accuracy and cost depend mainly on the method of determination and the sampling design in the scheme.This study aimed at formulating the basic design considerations of a knowledge-based system (KBS) to assist in the design of soil survey schemes. This system should incorporate pedological and statistical knowledge. The domain of the system has provisionally been limited to surveys for which a design-based approach, i.e. the use of classical sampling theory, is appropriate.Initially, the domain of the system has been structured in three layers: (i) an entity structure clarifying the position of the system in a soil survey project; (ii) a model describing the design process as a number of interrelated steps, and (iii) a conceptual framework defining the main concepts and their relations.Further analysis made it possible to specify the tasks in which the KBS should assist: definition of the survey request, selection of prior information, design of outlinear schemes, evaluation and optimization of outlinear schemes, generation of a report, and evaluation a posteriori .The system will primarily assist in the statistical decisions in the design process. Since there was no suitable classification of sampling designs available, a hierarchical framework of sampling designs has been constructed, in which sampling designs are grouped into types of designs, and types are grouped into classes of designs. Furthermore the main classes of sampling designs treated in the literature have been ordered in a taxonomy. Decision trees have been developed to guide the selection of an appropriate sampling approach (designbased versus model-based), and, in the case of a design-based approach, to guide the search for an appropriate class of sampling designs.To ensure that the available means for a project, such as budget, personnel, and equipment, are used adequately schemes should be evaluated and optimized beforehand. Models related to the features of sampling designs have been developed for predicting the accuracy and cost of survey schemes, the so-called prior evaluation. Furthermore the use of dynamic programming is proposed to search for the optimal sampling design within an outlinear scheme. The procedure enables objective comparison of schemes taking into account differences in spatial variability or sampling cost among sub-regions.Finally, basic design considerations are presented consisting of an initial requirements definition, a description of the intended use of the KBS, and a specification of the components for an actual KBS. Five components are distinguished: a database, a knowledge base, a model base, a problem-solving model, and a user interface. The system will assist in its own maintenance through continuous storage of knowledge from executed projects. This will facilitate the re-use of information. A KBS which is based on these basic design considerations will assist in controlling the quality of soil survey projects

Change detection and landscape similarity comparison using computer vision methods

Human-induced disturbances of terrestrial and aquatic ecosystems continue at alarming rates. With the advent of both raw sensor and analysis-ready datasets, the need to monitor ecosystem disturbances is now more imperative than ever; yet the task is becoming increasingly complex with increasing sources and varieties of earth observation data. In this research, computer vision methods and tools are interrogated to understand their capability for comparing spatial patterns. A critical survey of literature provides evidence that computer vision methods are relatively robust to scale and highlights issues involved in parameterization of computer vision models for characterizing significant pattern information in a geographic context. Utilizing two widely used pattern indices to compare spatial patterns in simulated and real-world datasets revealed their potential to detect subtle changes in spatial patterns which would not otherwise be feasible using traditional pixel-level techniques. A texture-based CNN model was developed to extract spatially relevant information for landscape similarity comparison; the CNN feature maps proved to be effective in distinguishing agriculture landscapes from other landscape types (e.g., forest and mountainous landscapes). For real-world human disturbance monitoring, a U-Net CNN was developed and compared with a random forest model. Both modeling frameworks exhibit promising potential to map placer mining disturbance; however, random forests proved simple to train and deploy for placer mapping, while the U-Net may be used to augment RF as it is capable of reducing misclassification errors and will benefit from increasing availability of detailed training data

Application of open-access and 3rd party geospatial technology for integrated flood risk management in data sparse regions of developing countries

Floods are one of the most devastating disasters known to man, caused by both natural and anthropogenic factors. The trend of flood events is continuously rising, increasing the exposure of the vulnerable populace in both developed and especially developing regions. Floods occur unexpectedly in some circumstances with little or no warning, and in other cases, aggravate rapidly, thereby leaving little time to plan, respond and recover. As such, hydrological data is needed before, during and after the flooding to ensure effective and integrated flood management. Though hydrological data collection in developed countries has been somewhat well established over long periods, the situation is different in the developing world. Developing regions are plagued with challenges that include inadequate ground monitoring networks attributed to deteriorating infrastructure, organizational deficiencies, lack of technical capacity, location inaccessibility and the huge financial implication of data collection at local and transboundary scales. These limitations, therefore, result in flawed flood management decisions and aggravate exposure of the most vulnerable people. Nigeria, the case study for this thesis, experienced unprecedented flooding in 2012 that led to the displacement of 3,871,53 persons, destruction of infrastructure, disruption of socio-economic activities valued at 16.9 billion US Dollars (1.4% GDP) and sadly the loss of 363 lives. This flood event revealed the weakness in the nation’s flood management system, which has been linked to poor data availability. This flood event motivated this study, which aims to assess these data gaps and explore alternative data sources and approaches, with the hope of improving flood management and decision making upon recurrence. This study adopts an integrated approach that applies open-access geospatial technology to curb data and financial limitations that hinder effective flood management in developing regions, to enhance disaster preparedness, response and recovery where resources are limited. To estimate flood magnitudes and return periods needed for planning purposes, the gaps in hydrological data that contribute to poor estimates and consequently ineffective flood management decisions for the Niger-South River Basin of Nigeria were filled using Radar Altimetry (RA) and Multiple Imputation (MI) approaches. This reduced uncertainty associated with missing data, especially at locations where virtual altimetry stations exist. This study revealed that the size and consistency of the gap within hydrological time series significantly influences the imputation approach to be adopted. Flood estimates derived from data filled using both RA and MI approaches were similar for consecutive gaps (1-3 years) in the time series, while wide (inconsecutive) gaps (> 3 years) caused by gauging station discontinuity and damage benefited the most from the RA infilling approach. The 2012 flood event was also quantified as a 1-in-100year flood, suggesting that if flood management measures had been implemented based on this information, the impact of that event would have been considerably mitigated. Other than gaps within hydrological time series, in other cases hydrological data could be totally unavailable or limited in duration to enable satisfactory estimation of flood magnitudes and return periods, due to finance and logistical limitations in several developing and remote regions. In such cases, Regional Flood Frequency Analysis (RFFA) is recommended, to collate and leverage data from gauging stations in proximity to the area of interest. In this study, RFFA was implemented using the open-access International Centre for Integrated Water Resources Management–Regional Analysis of Frequency Tool (ICI-RAFT), which enables the inclusion of climate variability effect into flood frequency estimation at locations where the assumption of hydrological stationarity is not viable. The Madden-Julian Oscillation was identified as the dominant flood influencing climate mechanism, with its effect increasing with return period. Similar to other studies, climate variability inclusive regional flood estimates were less than those derived from direct techniques at various locations, and higher in others. Also, the maximum historical flood experienced in the region was less than the 1-in-100-year flood event recommended for flood management. The 2012 flood in the Niger-South river basin of Nigeria was recreated in the CAESAR-LISFLOOD hydrodynamic model, combining open-access and third-party Digital Elevation Model (DEM), altimetry, bathymetry, aerial photo and hydrological data. The model was calibrated/validated in three sub-domains against in situ water level, overflight photos, Synthetic Aperture Radar (SAR) (TerraSAR-X, Radarsat2, CosmoSkyMed) and optical (MODIS) satellite images where available, to access model performance for a range of geomorphological and data variability. Improved data availability within constricted river channel areas resulted in better inundation extent and water level reconstruction, with the F-statistic reducing from 0.808 to 0.187 downstream into the vegetation dominating delta where data unavailability is pronounced. Overflight photos helped improve the model to reality capture ratio in the vegetation dominated delta and highlighted the deficiencies in SAR data for delineating flooding in the delta. Furthermore, the 2012 flood was within the confine of a 1-in-100-year flood for the sub-domain with maximum data availability, suggesting that in retrospect the 2012 flood event could have been managed effectively if flood management plans were implemented based on a 1-in-100-year flood. During flooding, fast-paced response is required. However, logistical challenges can hinder access to remote areas to collect the necessary data needed to inform real-time decisions. Thus, this adopts an integrated approach that combines crowd-sourcing and MODIS flood maps for near-real-time monitoring during the peak flood season of 2015. The results highlighted the merits and demerits of both approaches, and demonstrate the need for an integrated approach that leverages the strength of both methods to enhance flood capture at macro and micro scales. Crowd-sourcing also provided an option for demographic and risk perception data collection, which was evaluated against a government risk perception map and revealed the weaknesses in the government flood models caused by sparse/coarse data application and model uncertainty. The C4.5 decision tree algorithm was applied to integrate multiple open-access geospatial data to improve SAR image flood detection efficiency and the outputs were further applied in flood model validation. This approach resulted in F-Statistic improvement from 0.187 to 0.365 and reduced the CAESAR-LISFLOOD model overall bias from 3.432 to 0.699. Coarse data resolution, vegetation density, obsolete/non-existent river bathymetry, wetlands, ponds, uncontrolled dredging and illegal sand mining, were identified as the factors that contribute to flood model and map uncertainties in the delta region, hence the low accuracy depicted, despite the improvements that were achieved. Managing floods requires the coordination of efforts before, during and after flooding to ensure optimal mitigation in the event of an occurrence. In this study, and integrated flood modelling and mapping approach is undertaken, combining multiple open-access data using freely available tools to curb the effects of data and resources deficiency on hydrological, hydrodynamic and inundation mapping processes and outcomes in developing countries. This approach if adopted and implemented on a large-scale would improve flood preparedness, response and recovery in data sparse regions and ensure floods are managed sustainably with limited resources

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Salt management is a critical component of irrigated agriculture in arid regions. Successful crop production cannot be sustained without maintaining an acceptable level of salinity in the root zone. This requires drainage and a location to dispose drainage water, particularly, the salts it contains, which degrade the quality of receiving water bodies. Despite the need to generate drainage water to sustain productivity, many irrigation schemes have been designed and constructed with insufficient attention to drainage, to appropriate re-use or disposal of saline drainage water, and to salt disposal in general. To control the negative effects of drainage water disposal, state and federal agencies in several countries now are placing regulations on the discharge of saline drainage water into rivers. As a result, many farmers have implemented irrigation and crop management practices that reduce drainage volumes. Farmers and technical specialists also are examining water treatment schemes to remove salt or dispose of saline drainage water in evaporation basins or in underlying groundwater. We propose that the responsibility for salt management be combined with the irrigation rights of farmers. This approach will focus farmers' attention on salt management and motivate water delivery agencies and farmers to seek efficient methods for reducing the amount of salt needing disposal and to determine methods of disposing salt in ways that are environmentally acceptable

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.A In order to promote irrigation sustainability through reporting by irrigation water managers around Australia, we have developed an adaptive framework and methodology for improved triple-bottom-line reporting. The Irrigation Sustainability Assessment Framework (ISAF) was developed to provide a comprehensive framework for irrigation sustainability assessment and integrated triple-bottom-line reporting, and is structured to promote voluntary application of this framework across the irrigation industry, with monitoring, assessment and feedback into future planning, in a continual learning process. Used in this manner the framework serves not only as a "reporting tool", but also as a "planning tool" for introducing innovative technology and as a "processes implementation tool" for enhanced adoption of new scientific research findings across the irrigation industry. The ISAF was applied in case studies to selected rural irrigation sector organisations, with modifications to meet their specific interests and future planning

USCID Fourth international conference on irrigation and drainage

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Integrated regional water management -- Change of irrigation water quantity according to farm mechanization and land consolidation in Korea -- Local stakeholders participation for small scale water resources management in Bangladesh -- Water user participation in Egypt -- The man swimming against the stream knows the strength of it -- Roles and issues of Water Users' Associations for Sustainable Irrigation and Drainage in the Kyrgyz Republic and Uzbekistan in Central Asia -- Chartered Water User Associations of Afghanistan -- Updated procedures for calculating state-wide consumptive use in Idaho -- Measuring and estimating open water evaporation in Elephant Butte Reservoir in New Mexico -- Evapotranspiration of deficit irrigated sorghum and winter wheat -- Evaluation of a two-layer model to estimate actual evapotranspiration for vineyards -- Estimating pecan water use through remote sensing in Lower Rio Grande -- Estimating crop water use from remotely sensed NDVI, crop models, and reference ET -- Alfalfa production using saline drainage water -- Performance evaluation of subsurface drainage system under unsteady state flow conditions in coastal saline soils of Andhrapradesh, India -- Management strategies for the reuse of wastewater in Jordan -- Providing recycled water for crop irrigation and other uses in Gilroy, California -- Oakdale Irrigation District Water Resources Plan -- Use of information technology to support integrated water resources management implementation -- Decision-support systems for efficient irrigation in the Middle Rio Grande -- Salt management -- Ghazi Barotha Project on Indus River in Pakistan -- Field tests of OSIRI -- Water requirements, irrigation evaluation and efficiency in Tenerife's crops (Canary Islands, Spain) -- Using wireless technology to reduce water use in rice production -- Variability of crop coefficients in space and time -- Assessing the implementation of integrated water management approach in closed basins -- New strategies of donors in the irrigation sector of Africa -- Holistic perspective for investments in agricultural drainage in Egypt -- Mapping system and services for canal operation techniques -- An open channel network modernization with automated structures -- Canal control alternatives in the irrigation district 'Sector BXII del Bajo Guadalquivir,' Spain -- Hydrodynamic behavior of a canal network under simultaneous supply and demand based operations -- Simulation on the effect of microtopography spatial variability on basin irrigation performance -- Drip irrigation as a sustainable practice under saline shallow ground water conditions -- Water retention, compaction and bean yield in different soil managements under a center pivot system -- Precision mechanical move irrigation for smallholding farmers -- Wild flood to graded border irrigation for water and energy conservation in the Klamath basin -- A method describing precise water application intensity under a CPIS from a limited number of measurements -- An irrigation sustainability assessment framework for reporting across the environmental-economic-social spectrum -- Planning for future irrigation landscapes -- One size does not fit all -- Water information networks -- Improving water use efficiency -- Irrigation system modernization in the Middle Rio Grande Valley -- Relationship of operation stability and automatic operation control methods of open canal -- Responsive strategies of agricultural water sector in Taiwan -- Effect of network water distribution schedule and different on-farm water management practices on sugarbeet water use efficiency -- Variable Frequency Drive (VFD) considerations for irrigation -- Accuracy of radar water level measurements -- Transition submergence and hysteresis effects in three-foot Cutthroat flumes -- Practical irrigation flow measurement and control -- Linear anionic PAM as a canal water seepage reducing technology -- In-situ non-destructive monitoring of water flow in damaged agricultural pipeline by AE -- Reoptimizing global irrigation systems to restore floodplain ecosystems and human livelihoods -- Water management technologies for sustainable agriculture in Kenya -- Impacts of changing rice irrigation practices on the shallow aquifer of Nasunogahara basin, Japan -- Drought protection from an in-lieu groundwater banking program -- Development of agricultural drought evaluation system in Korea -- Bean yield and root development in different soil managements under a center pivot system -- Can frost damage impact water demand for crop production in the future? -- Real time water delivery management and planning in irrigation and drainage networks -- Growth response of palm trees to the frequency of irrigation by bubblers in Khuzestan, Iran -- Application of Backpropagation Neural Network to estimate evapotranspiration for ChiaNan irrigated area, Taiwan -- Increasing water and fertilizer use efficiency through rain gun sprinkler irrigation in sugar cane agriculture

USCID fourth international conference

Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.The two-layer model of Shuttlerworth and Wallace (SW) was evaluated to estimate actual evapotranspiration (ETa) above a drip-irrigated Merlot vineyard, located in the Talca Valley, Region del Maule, Chile (35° 25' LS; 71° 32' LW ; 136m above the sea level). An automatic weather system was installed in the center of the vineyard to measure climatic variables (air temperature, relative humidity, and wind speed) and energy balance components (solar radiation, net radiation, latent heat flux, sensible heat flux, and soil heat flux) during November and December 2006. Values of ETa estimated by the SW model were tested with latent heat flux measurements obtained from an eddy-covariance system on a 30 minute time interval. Results indicated that SW model was able to predict ETa with a root mean square error (RMSE) of 0.44 mm d-1 and mean absolute error (MAE) of 0.36 mm d-1. Furthermore, SW model predicted latent heat flux with RMSE and MAE of 32 W m-2 and 19W m-1, respectively