Climate extremes bring both challenges and opportunities for increasing resilience in agriculture and communities. Drought impact assessments are useful to identify systemwide vulnerabilities and downstream effects from water shortages to agriculture, and aid governments, irrigation user organizations and farmers in both short-term response and planning. The recent climate extremes in California, USA over the past 2012-2022 decade provide a useful case study as one of the largest irrigated agricultural systems which are applicable to other semi-arid areas in the world. We present a framework to gather water supply availability for irrigation in California’s large and complex water supply system, estimate idle land, potential cropping patterns response and economic costs to irrigated agriculture, downstream food processing sectors and regional economies. Recent groundwater regulation forcing sustainable pumping rates at a local level bring additional challenges to cope with water scarcity. We employ regional water balances which consider diverse water supply portfolios for agriculture, remote sensing, and economic models which estimate profit-maximizing crop response and economic costs of water shortages to agriculture and related sectors. We also discuss data challenges in quantifying ultimate impacts of low precipitation, surface water reserves and groundwater restrictions, in a highly engineered and diversified water supply system.  Estimated impacts on agriculture and regionwide income and employment from the 2012-2016 and the more recent 2019-2022 drought in California are discussed along with insights for short-term response, and longer-term water management, planning and policy.

How to cite: Medellin-Azuara, J., Escriva-Bou, A., Rodriguez-Flores, J., Cole, S., Abatzoglou, J., Viers, J., and Sumner, D.: On assesssing water supply availability, land idling and economic impacts of agricultural droughts: Cases studies from recent California climate extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17022, https://doi.org/10.5194/egusphere-egu23-17022, 2023.

An effective, efficient, and sustainable allocation of resources has gained prominence on a global scale in recent years, taking into account far more than in the past the environmental needs of the ecosystems linked to them. Proper resource management and planning, as well as the detection of specific sustainable indicators, are required to respond to increasing demand while keeping in mind that its increase corresponds to a gradual reduction in the availability and usability of resources, which is also a result of climate change. This becomes even more important when the resource under consideration is water, which is essential for human survival and well-being as, after all, agricultural production. In comparison to other European countries, Italy has an abundance of meteoric inflows, albeit unevenly distributed across its entire territory. Because of this, the Italian country is particularly vulnerable to water crises, which are becoming more common, particularly in South Italy. The management of water resources, which is already complex, becomes even more so when dealing with scarcity situations, an area in which it is critical, to begin with the cognitive assumption of hydrological balance. Remote Sensing (RS) approaches are essential for investigating and assessing water bodies, meteoric inflows, and water balance parameters, allowing for effective surface water management support. RS is widely used for the aforementioned purposes due to the increasing availability of novel medium-high-resolution remote sensing big data, as well as Copernicus services and data related to water management (https://climate.copernicus.eu/water-management). Thus, the goal of this study is to take a "snapshot" of the current state of natural water resource availability in the Apulian region by extracting and estimating the main hydrological balance components introduced by the BIGBANG model (Braca et al., 2021) by exploiting Copernicus services and freely available medium-high resolution satellite data. Following the collection of all necessary input data, such as high-resolution Digital Elevation Model (DEM), Corine Land Cover maps, remote sensing-based soil sealing maps, mean monthly air temperature and rainfall, Google Earth Engine (GEE) environment, a free cloud platform recently released by Google to manage big geospatial data, were used to handle and estimate the main hydrological balance components. The proposed approach, based on the integration of Copernicus services and the BIGBANG model, appears as a useful and operational tool for supporting sustainable and adaptive resource management activities, particularly in water crisis situations. In fact, it allows extracting trustworthiness water balance components quickly.

How to cite: Capolupo, A., Barletta, C., and Tarantino, E.: Copernicus services and data to support a sustainable and adaptive water resource management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2449, https://doi.org/10.5194/egusphere-egu23-2449, 2023.

With the ongoing economic development and population growth, the shortage of water resources has become a severe problem which involves conflicts and tradeoffs among society, economy, environment, and ecology. Although previous researches proposed multi-objective optimization models, human-water coupled models, and hydro-economic models to deal with these conflicts and tradeoffs, they still did not address water demands’ integration and lacked future vision of water resource allocation. This paper proposed a Water Resource Allocation Model based on coupled Socio-economic-Environment-Ecology-Resources System (WRAM-SEERS) which considered integrally optimization objectives of socio-economic, environmental, and ecological subsystems under the constraints of water and land resources. The proposed model has the following advantages: (a) It could reflect all the closely related elements of the evolution of human society including urban and ecological space planning, cultivated structure and scale, population structure and size, industrial structure and scale, and so on, (b) It could generate the Pareto frontier surface, which maximized the socio-economic interest while minimizing the adverse externalities reacting in environment and ecology, and (c) It could forecast the future development range of each subsystem under hydrologic uncertainties. We applied WRAM-SEERS to allocate water resources of Yinchuan City in China in 2021-2035 and explained issues related the future perspective of Yinchuan: (a) “what is the lower and upper limits of subsystems’ development targets”, (b) “how to set targets consistent with sustainable development”, and (c) “how to achieve the settled targets”. The above explanations provided a scientific basis and decision-making reference for improving the water safety guarantee ability of Yinchuan's economic and social development and promoting a green, sustainable and high-quality development.

How to cite: Shi, Y., Wang, Z., Chen, J., and Chen, J.: A Water Resource Allocation Model Based on Coupled Socio-economic-Environment-Ecology-Resources System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4674, https://doi.org/10.5194/egusphere-egu23-4674, 2023.

Indicators on the sustainability of productive human sectors help boosting societal awareness and provide remarkable information for political decision-making and resources management. Prominent examples of relevant environmental indicators currently available are those that form the footprint family. In agriculture, the water footprint approach provides indicators that integrate direct and indirect freshwater usage. While a considerable number of studies developed so far used tabulated values for crop parametrization, the less explored application of dense remote sensing time series provides huge benefits.

This paper aims to present the spatiotemporal estimation of the green and blue Remote Sensing-based Agriculture Water Footprint (RS-AWAF) at the Pinios River Basin (11,000 km²) in Greece (year 2017), combining two globally accepted and operational methodologies: the Soil Water Balance published by the Food and Agriculture Organization in its irrigation and drainage paper 56 for water accounting purposes, and the standardized methodology for Agricultural Water Footprint estimation of growing a crop or tree published by the Water Footprint Network. Initially, the RS-AWAF applies dense temporal series of the Normalized Difference Vegetation Index produced by Sentinel-2 data at 10m spatial resolution to monitor the crops provided by local authorities through the Land Parcel Information System and derive the biophysical parameters along its development, such as the basal crop coefficient and the fraction of soil surface covered by vegetation. Those are then integrated into a validated and operational Remote Sensing-based Soil Water Balance that day after day and within a pixel spatial scale, estimates among other components of the balance, the adjusted crop evapotranspiration (ET_cadj) and the net irrigation requirements (NIR). In a second step, both previous components are combined to estimate the blue crop water use (CWU_blue), related to the NIR, and the green crop water use (CWU_green), related to the fraction of the ET_cadj that comes from other freshwater sources different than irrigation, the precipitation. Finally, crop yield values collected from official statistics per crop or crop group are used to estimate the blue water footprint (WF_blue) and the green water footprint (WF_green).

Once the green and blue RS-AWAF is estimated, a collection of thematic maps over the Pinios River Basin is ready for use by local stakeholders at their desired working scale. In that sense, monthly and annual thematic maps of ET_cadj, NIR, CWU_green and CWU_blue are available, as well as annual thematic maps of WF_blue and WF_green. In parallel, tabulated values are created from these parameters using zonal statistics through GIS at the spatial scale appropriate to the final user (i.e. water user associations).

These results are part of the EU Horizon 2020 project REXUS (Managing Resilient Nexus Systems Through Participatory Systems Dynamics Modelling), in which stakeholders from water user associations to river basin water managers are evaluating the information. At this stage, our final goal is to provide spatiotemporal distributed accounting of agricultural freshwater resources over large areas that enhance regional knowledge and increases efficiency in water management and subsequently contributing to energy-saving, since the major agricultural water volume is abstracted from deep groundwater wells.

How to cite: Garrido-Rubio, J., González-Piqueras, J., Calera, A., Babakos, K., Pisinaras, V., Panagopoulos, A., and Osann, A.: Spatial and temporal estimation of the green and blue Remote Sensing-based Agriculture Water Accounting and Footprint at the Pinios River Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14825, https://doi.org/10.5194/egusphere-egu23-14825, 2023.

Water distribution networks (WDNs) need restructuring/sectorization into District Metered Areas (DMAs) depicting smaller communities for ease in ensuring equitable water distribution and pressure management. DMA demarcation also helps in systems operation and management, apart from leak and contaminant localization. Many different strategies for DMA demarcation are in use, as none is established to be universally superior. Hence, there is ambiguity in the choice of a strategy for DMA demarcation. A WDN can be viewed as a complex network due to strong interconnections among its components and imposed limitations (being a 2D network). Against this backdrop, the recent decade witnessed the use of community detection approaches from complex network theory (CNT) for DMA demarcation. Community detection is a very basic yet pivotal task in the field of CNT. Modularity maximization is the most widely used approach for community detection. The modularity index defines the quality of the subgraphs or communities delineated from a network. In the case of a WDN, some nodes may be shared by more than one DMA, in which case the conventional and existing variants of the modularity index cannot be used for assessing the quality of the delineated DMAs. A more comprehensive community (DMA) detection procedure must incorporate such nodes with multiple associations among communities. Facilitating this, the present study proposes a comprehensive approach for DMA demarcation in large and complex WDNs considering a weighted modularity index. Edge weights are assigned to incorporate the hydraulic behaviour of a network and the association of nodes among various communities. The efficacy of the proposed approach vis-à-vis existing methods is demonstrated through a case study on a benchmark WDN. Effective demarcation of DMAs helps in their prioritization (based on the existing network level measures) to devise mitigation strategies for improving their performance.

How to cite: Pandey, J. and Srinivas, V. V.: A New Weighted Modularity-Based Approach for DMA Demarcation in Large and Complex Water Distribution Networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-609, https://doi.org/10.5194/egusphere-egu23-609, 2023.

In California’s Central Valley, the forecast from climate models is that future precipitation events will be less frequent, more extreme, and deliver a higher proportion of the precipitation as rain. The combination of these effects will challenge the state’s ability to capture and store this critical freshwater resource and will also threaten downstream communities with flooding. A water management strategy gaining popularity in California is managed aquifer recharge (MAR), where excess surface water is captured and directed to selected sites to recharge the underlying groundwater systems. AgMAR is a form of MAR where water is spread over agricultural land to recharge the underlying aquifer over short periods during the wet winter months. One concern with this strategy is the decades of intensive agriculture in the Central Valley. The intense usage of fertilizers such as nitrogen threatens to contaminate the groundwater systems on which municipalities and homeowners rely. Research into nitrate mobilization has shown that the stratigraphic characterization of a site is the dominant factor in determining the infiltration rate and mobilization of contaminants. Therefore, in order to develop a model of nitrate mobilization, detailed information is needed about surface stratigraphy. In this study, a towed-transient electromagnetic geophysical method (tTEM) was used to image the subsurface, in combination with sediment type logs, to characterize the subsurface sediments. tTEM data were acquired on a 56-ha commercial almond farm in the early spring of 2022. The tTEM data were inverted to recover a resistivity model of the site, exhibiting a high degree of spatial variability. Regions of high resistivity typically suggest coarser grained material that is more permeable and hydraulically conductive, whereas regions of lower resistivity tend to be composed of finer grained material and are less hydraulically conductive. We created a site-specific resistivity-to-sediment-type transform to extract sediment-type data from the tTEM data using data from the 1D resistivity models along with twenty co-located sediment type logs and water table measurements. Using the maximum likelihood model, we transformed the recovered resistivity model into a sediment-type model. The integration of tTEM data and well-derived information about sediment types to construct a sediment-type model can provide information about connected pathways for recharge and help inform nitrate mobilization models. This study is allowing us to develop a methodology that can be applied elsewhere for the assessment of a site for agMAR when there are concerns about nitrate mobilization. This work is in support of a larger project on groundwater sustainability in agricultural systems in the southwestern United States.

How to cite: Peralta, J., Knight, R., Goebel, M., and Kang, S.: Geophysical site characterization, with the tTEM system, for studies of nitrate mobilization during recharge in the Central Valley of California, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10821, https://doi.org/10.5194/egusphere-egu23-10821, 2023.

Climate change scenarios have projected that more frequent and severe droughts are likely to occur, especially in arid and semi-arid regions such as a gran part of the Mediterranean basin, where the effects of climate change on irrigated agriculture are more accentuated. These regions are generally characterized by an agroecosystem based on perennial crops that are sensitive to water scarcity. Citrus is among perennial crops in the Mediterranean area currently facing climate change effects and water scarcity. In the Mediterranean region, the changes in rainfall patterns and the increase in temperature caused by climate change will lead to higher evapotranspiration and consequently, increased irrigation needs for this crop that already has high water requirements.

Thus, it is mandatory to develop climate change adaptation measures to reduce their impacts on water resources in arid and semi-arid regions with intensive use of water for irrigation to increase capacity and efficiency for irrigation and ease the projected water stress.  One approach to ensure efficient water management is the development of decision-support tools to improve water management efficiency in irrigation. Crop simulation models are a key tool in extrapolating the impacts of climate change on irrigation water management.

In this context, our study aims at developing an agronomic model for woody crops, especially for citrus, since agronomic models for woody crops are practically absent, in contrast to the wide range of alternatives for annual crops, to define water resource management strategies. The model, named AquaCitrus, is a new functional soil water balance for citrus that simulates on daily time step water fluxes in the soil-plant-atmosphere complex. In short, AquaCitrus is composed of a set of sub-models computing the fluxes of effective precipitation, infiltration, runoff, soil evaporation, drainage, and crop transpiration. The model includes the routine of rainfall interception by the canopy, and computes the soil evaporation and crop transpiration separately. Soil evaporation is calculated using the model of Ritchie and citrus transpiration is calculated by the transpiration coefficient method. AquaCitrus considers the heterogeneity of the soil, given that localized irrigation keeps a small fraction of the soil frequently wet while the remaining area remains dry, unless it rains. Therefore, the model is divided into two compartments that solve the water balance separately for each soil zone.

To assess its predictive power, AquaCitrus was evaluated using a 2-year period of soil moisture data from an experimental field conducted in a citrus orchard in Valencia, Spain.  The results pointed out a good agreement between simulated and measured soil water contents at different soil depths; the model predicts the water balance of the system satisfactorily. We concluded that AquaCitrus is a useful tool to simulate strategies for improving irrigation water use efficiency in citrus crops, highlighting that there is additional room for improving its robustness. 

Acknowledgements:

This research has been supported by the ADAPTAMED project (RTI2018-101483-B-I00), funded by the Ministerio de Economía y Competitividad (MINECO) of Spain including EU FEDER funds; and by the GoNEXUS project (GA. 101003722), funded by the European Union Horizon Programme call H2020-LC-CLA-2018-2019-2020.

How to cite: Boubakri, N., Garcia-Prats, A., and Pulido-Velázquez, M.: AquaCitrus: Soil water balance model for irrigation management in citrus orchards, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13408, https://doi.org/10.5194/egusphere-egu23-13408, 2023.

The search for innovative approaches to agricultural production is fundamental to face the challenge of providing sustainable food production without depleting natural resources for growing population. Therefore, an accurate assessment of the green and blue water needs of cultivated land under different agricultural strategies is essential for systematic water management in agriculture. Among the limits to global food production, water availability, and soil and water salinity play key roles, especially in semi-arid and arid regions. In those areas, a possible solution for a sustainable increase in crop production while preserving natural resources is shifting small vegetable crop productions in a controlled environment, as greenhouses, where temperature, humidity, light, and other factors can be adjusted to meet the plant's needs. Here, we propose a method to estimate the water needed to grow small vegetables under different crop production techniques, from the more traditional approach in the field to innovative soilless cultivation techniques in greenhouses, with a case study in Egypt. To do so, we use the spatially distributed agro-hydrological model WATNEEDS to simulate the plant growth, including the effect of greenhouse production on crop water demand. Moreover, we simulate the possible use of brackish water for irrigation. Results show that by shifting to protected cultivation, the reduction in crop water requirement is 60%,65%, and 30% for tomato, watermelon, and pepper, respectively. This model could be used for irrigation planning and resource management policies. Besides, it can be helpful on multiple scales, from farm to global scale.

How to cite: Chiarelli, D. D., Karimzadeh, S., d'Odorico, P., and Rulli, M. C.: Modeling innovative approaches for agricultural production with a case study for small vegetable production in Egypt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13258, https://doi.org/10.5194/egusphere-egu23-13258, 2023.

Climate change is increasingly affecting agriculture water resources. This adverse situation can be addressed by developing approaches focusing on optimization for agricultural water management.  Groundwater depletion is a serious issue for the sustainability of irrigated agriculture in the southern and central parts of the High Plains Aquifer (HPA), USA. Crops that require more water to grow (e.g., maize) may not receive sufficient irrigation due to decline in pumping capacities, and growers can experience yield loss, jeopardizing the farm profits. Geospatial crop modeling can be seen as a tool to simulate different scenarios of water availability for crops in regions like Texas and Oklahoma Panhandle. Open-source version of AquaCrop (AC-OSPy) was run under a gridded environment on the maize pixels of crop frequency layer developed by National Agricultural Statistics Service. Long-term simulations for past 30-year period (1991-2020) were run using the historical weather data for multiple irrigation application rates. Also, deficit irrigation was tested to assess the impact of skipping irrigation in different crop stages. The simulations were able to capture the variation of weather and soil patterns in the region. Mean irrigation requirement ranged between 78 mm and 314 mm under 50% available water capacity irrigation threshold, and mean yield varied from 8.8 to 14.3 Mg-ha^-1. Deficit irrigation showed a potential of water saving during initial and vegetative stages (up to 113 mm), whereas a significant decline in yields was noted for skipping irrigation during flowering. Overall, the results of the study showed great potential of using geospatial crop modeling approach for regional agricultural water planning and drought mitigation efforts.  

How to cite: Saddique, Q., Ajaz, A., and Jain, S.: Using spatial crop modeling to improve the regional agricultural water planning., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4511, https://doi.org/10.5194/egusphere-egu23-4511, 2023.