Bridging rigorous assessment of water availability from field to catchment scale with a parsimonious agro-hydrological model

While simple crop and hydrological models are limited with respect to the number and accuracy of the processes they incorporate, complex models have high demand for data. Due to the limitations of both categories of models, there is a need for new agro-hydrological models that simulate both crop productivity and water availability in agricultural catchments, with low data and calibration requirements. This study aimed at developing a widely applicable parsimonious agro-hydrological model, AquaCrop-Hydro, which couples the AquaCrop crop water productivity model with a conceptual hydrological model. AquaCrop-Hydro, simulating crop productivity, the daily soil water balance and discharge at the catchment outlet, performed well for an agricultural catchment in Belgium. The model can be used to investigate the effect of agricultural management and environmental changes from field to catchment scale in support of sustainable water management in agricultural areas.     

中国能量与水平衡遥感监测系统

以土壤、大气和植被系统（SPAC）能量流动与物质转换机理为指导，建立了“中国能量与水平衡遥感监测系统”（CEWBMS）；利用气象卫星GMS－5和风云2号数据，反演出多种地表能量与水平衡关键参数，并形成标准数据产品进行发布；构建了水文、干旱、生态和农作物估产等应用模型，对系统及系统输出产品的实际应用做了示范。     

A holistic generic integrated approach for irrigation,crop and field management: the SALTMED model

A successful water management scheme for irrigated crops requires an integrated approach that accounts for water, crop, soil and field management. Most existing models are designed for a specific irrigation system, specific process such as water and solute movement, infiltration, leaching or water uptake by plant roots or a combination of them. There is a shortage in models of a generic nature, models that can be used for a variety of irrigation systems, soil types, soil stratifications, crops and trees, water management strategies (blending or cyclic), leaching requirements and water quality. SALTMED model has been developed for such generic applications. The model employs established water and solute transport, evapotranspiration and crop water uptake equations. In this paper, the model has been run with five examples of applications for one growing season using data from the literature. The model successfully illustrated the effect of the irrigation system, the soil type, the salinity level of irrigation water on soil moisture and salinity distribution, leaching requirements, and crop yield in all cases. Due to the scarcity of data sets that are suitable for model testing over the complete growing season, where different processes are acting simultaneously, a follow up paper will show the results of the model tests using data being collected from two sites in Egypt and in Syria as a part of ongoing SALTMED project.     

基于Web Service的在线水文模型服务研究

通过分析目前水文模型本地服务模式的不足,针对当前国内外Web Service技术在水文信息系统中的应用现状,设计并实现了一个基于Web Service技术的在线水文模型服务系统,示范了基于Web Service技术的网络数据获取、水文模型运行模拟等过程,说明基于Web Service技术的在线水文模型服务较好地实现了水文模型网络共享,支持异地模型访问。建议在线水文模型服务结构从网络数据库/数据中心获取数据,一定程度上解决了传统模式从本机上传海量数据等问题。这种在线水文模型服务模式节约了模型运行成本、降低了用户要求,在具体水文水资源管理事务中具有较好的应用和拓展前景。     

基于大数据、云平台和微服务的水文综合平台建设

随着社会对水文服务需求的不断提高,为解决水文信息化发展的同时出现的水文应用繁多,资源不共享,标准不统一等问题,江西省建设基于大数据、云平台和微服务的水文综合平台.解析水文综合平台实现水文业务数据的一数一源和业务协同集成的脉络,分别阐述大数据平台、云平台和微服务架构技术结合在数据层和平台层的支撑作用;同时在分析应用支撑、...     

Searching for simplified farmers' crop choice models for integrated watershed management in Thailand: A data mining approach

This study used the C4.5 data mining algorithm to model farmers' crop choice in two watersheds in Thailand. Previous attempts in the Integrated Water Resource Assessment and Management Project to model farmers' crop choice produced large sets of decision rules. In order to produce simplified models of farmers' crop choice, data mining operations were applied for each soil series in the study areas. The resulting decision trees were much smaller in size. Land type, water availability, tenure, capital, labor availability as well as non-farm and livestock income were found to be important considerations in farmers' decision models. Profitability was also found important although it was represented in approximate ranges. Unlike the general wisdom on farmers' crop choice, these decision trees came with threshold values and sequential order of the important variables. The decision trees were validated using the remaining unused set of data, and their accuracy in predicting farmers' decisions was around 84%. Because of their simple structure, the decision trees produced in this study could be useful to analysts of water resource management as they can be integrated with biophysical models for sustainable watershed management.     

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.     

Data assimilation framework: Linking an open data assimilation library (OpenDA) to a widely adopted model interface (OpenMI)

Data assimilation optimally merges model forecasts with observations taking into account both model and observational uncertainty. This paper presents a new data assimilation framework that enables the many Open Model Interface (OpenMI) 2.0 .NET compliant hydrological models already available, access to a robust data assimilation library. OpenMI is an open standard that allows models to exchange data during runtime, thus transforming a complex numerical model to a ‘plug and play’ like component. OpenDA is an open interface standard for a set of tools, filters, and numerical techniques to quickly implement data assimilation. The OpenDA–OpenMI framework is presented and tested on a synthetic case that highlights the potential of this new framework. MIKE SHE, a distributed and integrated hydrological model is used to assimilate hydraulic head in a catchment in Denmark. The simulated head over the entire domain were significantly improved by using an ensemble based Kalman filter.     

Development of a knowledge library for automated watershed modeling

In this work, we develop a library of components for building semi-distributed watershed models. The library incorporates basic modeling knowledge that allows us to adequately model different water fluxes and nutrient loadings on a watershed scale. It is written in a formalism compliant with the equation discovery tool ProBMoT, which can automatically construct watershed models from the components in the library, given a conceptual model specification and measured data. We apply the proposed modeling methodology to the Ribeira da Foupana catchment to extract a set of viable hydrological models. By specifying the conceptual model and using the knowledge library, two different hydrological models are generated. Both models are automatically calibrated against measurements and the model with the lower root mean squared error (RMSE) value is selected as an appropriate hydrological model for the selected study area.     

SWAT-DayCent coupler: An integration tool for simultaneous hydro-biogeochemical modeling using SWAT and DayCent

Process-based numerical models in environmental science can help understand and quantify terrestrial material cycles in nature. However, the existing models usually focus on the cycles of one or more elements (e.g., water, carbon, or nitrogen). For example, hydrological models such as Soil and Water Assessment Tool (SWAT) focus on the water cycle and nutrient loadings at watershed scale, whereas biogeochemical models such as DayCent (i.e., daily CENTURY) emphasize carbon/nitrogen storage and fluxes of ecosystems at landscape scale. Therefore, using either one of the two categories of models is not enough for understanding/solving the current complex environmental issues that involve multiple aspects. Although use of both models (SWAT and DayCent) could be an expedient way toward treating the problem, creating separate model projects for a single area could be challenging and time consuming, and integration/analyses of model results have some limitations due to the non-uniformity of input spatial data between models. To overcome this issue, we developed an integrated model implementation coupler that aims to drive SWAT and DayCent—the two representative models in hydrology and biogeochemistry, respectively—just using a user's SWAT project without the need of any extra efforts such as developing a framework or preparing input data for DayCent modeling. This software is easy to use and would be promising for conducting comprehensive environmental impact assessment involving hydrological and biogeochemical cycles at watershed scale.     

A watershed data management and visualization system using code-first approach

With rapid growth of population and economic development in northwest China, water resource over-exploitation has led to severe deterioration of watershed ecosystems. In this study, we developed a hydrological information platform (called Watershed Datacenter System) for sharing, managing, analyzing and visualizing a diverse range of hydrologic data collected at watershed scale. This platform can help investigators and geotechnical experts to conduct watershed researches with the intensive data convenience. This Watershed Datacenter system (WDC) is developed with Entity Framework 6 (EF6) approach which based on Model-View-Controller (MVC) architecture pattern and several other useful technologies, such as ArcGIS API and Responsive web design. Observation Database Model (ODM), hydrological model as a service, Web services and time-series analysis tools are seamlessly integrated into our WDC with the help of open source HIS (Hydrologic Information System) from the CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.). The results demonstrate that the WDC offers quite a few advantageous features for managing and analyzing of the data for watershed research.     

Integrating hydrological modelling,data assimilation and cloud computing for real-time management of water resources

Online data acquisition, data assimilation and integrated hydrological modelling have become more and more important in hydrological science. In this study, we explore cloud computing for integrating field data acquisition and stochastic, physically-based hydrological modelling in a data assimilation and optimisation framework as a service to water resources management. For this purpose, we developed an ensemble Kalman filter-based data assimilation system for the fully-coupled, physically-based hydrological model HydroGeoSphere, which is able to run in a cloud computing environment. A synthetic data assimilation experiment based on the widely used tilted V-catchment problem showed that the computational overhead for the application of the data assimilation platform in a cloud computing environment is minimal, which makes it well-suited for practical water management problems. Advantages of the cloud-based implementation comprise the independence from computational infrastructure and the straightforward integration of cloud-based observation databases with the modelling and data assimilation platform.     

Development and preliminary evaluation of an integrated field scale model for perennial bioenergy grass ecosystems in lowland areas

Computer models are useful tools for evaluating environmental and economic sustainability of proposed dedicated cellulosic grass ecosystems for biofuel production. This study developed an integrated, field scale, and process-based ecosystem model (DRAINMOD-GRASS) for simulating hydrological processes, soil carbon and nitrogen cycling, and plant growth in cropping systems for producing bioenergy grasses in lowland areas. We tested the model using measurements from three replicated switchgrass (Panicum virgatum) plots located in eastern North Carolina, USA. Results showed that the model accurately predicted 5-year (2009–2013) biomass yield. Predicted daily water table depth closely matched field measurements with Nash-Sutcliffe coefficient of 0.86. The model also accurately predicted temporal dynamics of daily soil moisture and temperature with Nash-Sutcliffe coefficients of 0.7 and 0.9, respectively. Predicted seasonal changes in net N mineralization and nitrification rates were comparable to field measurements in 2011 and 2012.     

Coupling agent-based models of subsistence farming with individual-based forest models and dynamic models of water distribution

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate and the feedback between rainfall, crop growth, land clearance and their coupling to the hydrological cycle. Temporal fluctuations in rainfall alter the spatial distribution of water availability, which in turn is mediated by soil-type, slope and landcover. This pattern ultimately determines the locations within the landscape that can support agriculture and controls sustainability of farming practices. The representation of such a system requires us to couple together the dynamics of human and ecological systems and landscape change, each of which constitutes a significant modelling challenge on its own. Here we present a proto-type coupled modelling system to simulate land-use change by bringing together three simple process models: (a) an agent-based model of subsistence farming; (b) an individual-based model of forest dynamics; and (c) a spatially explicit hydrological model which predicts distributed soil moisture and basin scale water fluxes. Using this modelling system we investigate how demographic changes influence deforestation and assess its impact on forest ecology, stream hydrology and changes in water availability.     

A continuous coupled hydrological and water resources management model

Human exploitation of water resources is widespread and its impact on hydrological fluxes is expected to increase in the future. Water use interacts in a complex manner with the hydrological system causing severe alterations of the hydrological fluxes with multifaceted feedbacks. Implementing this coupling within hydrological models is essential when dealing with the impact of human activities on water resources at all relevant scales. We contribute to the effort in developing models coupling natural and human systems with a distributed continuous model, named GEOTRANSF. The model allows to quantify, within the same framework, alterations in the natural regime and constraints and limitations to water resources availability. After presenting GEOTRANSF, an example of application to a medium-size Alpine catchment with streamflow modified by hydropower and distributed uses is discussed, followed by the analysis of the effect of suitable water uses scenarios in the same catchment.     

A biophysical and economic model of agriculture and water in the Murray-Darling Basin,Australia

Economic analysis of climate scenarios and alternative water policies is critical for development and implementation of appropriate water policies and programs. Mathematical models have been developed to assess water resources policies due to their ability to explicitly represent the biophysical dynamics of natural systems while integrating these within social and economic constraints. These models have been criticised, however, due to the problems of simplification, overspecialisation, plausibility and lack of empirical validation. This paper introduces a mathematical programming model which uses positive mathematical programming method to calibrate and model agriculture and water use in the Murray-Darling Basin of Australia. This paper reviews the theoretical and technical details of the model development including the key steps taken in collating and scaling the biophysical and economic data, and to address model parameterisation issues. The paper summarises results of an application of the model for assessing climate change impacts in the form of reduced rainfall and water allocations and increased crop water use for agricultural production. The results show the degree of variability in gross values under different climate scenarios compared to the base case scenario, especially in very dry years. The results also show how on-farm adaptation options and water markets can mitigate these losses.     

Implications of complexity and uncertainty for integrated modelling and impact assessment in river basins

The paper focuses on implications of complexity and uncertainty in climate change impact assessment at the river basin and regional scales. The study was performed using the process-based ecohydrological spatially semi distributed model SWIM (Soil and Water Integrated Model). The model integrates hydrological processes, vegetation/crop growth, erosion and nutrient dynamics in river basins. It was developed from the SWAT and MATSALU models for climate and land use change impact assessment. The study area is the German part of the Elbe River basin (about 100,000 km²). It is representative for semi-humid landscapes in Europe, where water availability during the summer season is the limiting factor for plant growth and crop yield. The validation method followed the multi-scale, multi-site and multi-criteria approach and enabled to reproduce (a) water discharge and nutrient load at the river outlet along with (b) local ecohydrological processes like water table dynamics in subbasins, nutrient fluxes and vegetation growth dynamics at multiple scales and sites. The uncertainty of climate impacts was evaluated using comprehensive Monte Carlo simulation experiments.     

A framework for integrated assessment of food production economics in South Asia under climate change

Agriculture is a sector vulnerable to climate change. The potential decline of crop yields from this vulnerability has important policy implications for food security in South Asia. In this study an integrated assessment modelling framework is proposed to link a global economic model with global climate models via an econometric model of crop productivity. It is then used to examine the impact of climate change on food security in individual South Asian countries by exploring the interaction between climate-induced productivity change and changes in food production and food prices. The results of our simulations suggest that unfavourable climate change can reduce food production significantly from the historical trend and create upward pressure on food prices. This, in turn, will have serious adverse impacts on food security in the South Asian region.     

基于机理模型的兰江洪水复盘分析

为提高洪水预报水位精度，结合水文和水动力模型，对钱塘江 2022 年“6·21”洪水计算过程进行复盘，分析洪水成因。收集降雨量、水位、流量等水文监测数据及水利工程调度信息，建立兰江流域半分布式水文和分段水动力模型，完成模型率定和验证。基于模型分析洪水成因，分析降雨时空变化、梯级水利枢纽调度、区间水库拦蓄对洪水过程的影响。结果表明：洪水主要由自北向南移动的强降雨形成，在水利枢纽调度影响下，洪水水位过程线由尖瘦型演变为头肩型，其中干流水利枢纽调度影响低水水位上涨和消落，上游水库调蓄可有效削减洪峰并推后峰现时间。通过洪水成因分析，在机理模型中加入水利工程调度影响，计算的洪水水位过程与实际更加吻合。     

Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model

One of the applications of crop simulation models is to estimate crop yield during the current growing season. Several studies have tried to integrate crop simulation models with remotely sensed data through data‐assimilation methods. This approach has the advantage of allowing reinitialization of model parameters with remotely sensed observations to improve model performance. In this study, the Cropping System Model‐CERES‐Maize was integrated with the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products for estimating corn yield in the state of Indiana, USA. This procedure, inversion of crop simulation model, facilitates several different user input modes and outputs a series of agronomic and biophysical parameters, including crop yield. The estimated corn yield in 2000 compared reasonably well with the US Department of Agriculture National Agricultural Statistics Service statistics for most counties. Using the seasonal LAI in the optimization procedure produced the best results compared with only the green‐up LAIs or the highest LAI values. Planting, emergence and maturation dates, and N fertilizer application rates were also estimated at a regional level. Further studies will include investigating model uncertainties and using other MODIS products, such as the enhanced vegetation index.