How Does Agricultural Water Resources Management Adapt to Climate Change? A Summary Approach

This editorial paper takes the form of a concise report and delves into a critical and intricate issue essential for the sustainability of agriculture. It centers on the intricate relationship between agri-cultural water resource management and agronomical practices, as well as their ability to adapt to the impacts of climate change while ensuring both the quantity and quality of crop yields. Specifically, this paper serves as a synopsis of how the far-reaching consequences of climate change for water resources impact agricultural production. It also highlights primary adaptation strategies for managing agricultural water resources, as drawn from the existing literature. Such strategies are designed to counteract the potentially adverse impacts of climate change on the rural sector. Fur-thermore, this brief report offers a valuable overview of the 17 selected papers featured in this Special Issue (SI) on Water, published by MDPI. These papers serve as exemplars of cutting-edge approaches to adaptability in water resource management and resilient crop production systems, as these fields attempt to thrive in an ever-changing environmental landscape

Developing an Open-Source IoT Platform for Optimal Irrigation Scheduling and Decision-Making: Implementation at Olive Grove Parcels

Climate change has reduced the availability of good quality water for agriculture, while favoring the proliferation of harmful insects, especially in Mediterranean areas. Deploying IoT-based systems can help optimize water-use efficiency in agriculture and address problems caused by extreme weather events. This work presents an IoT-based monitoring system for obtaining soil moisture, soil electrical conductivity, soil temperature and meteorological data useful in irrigation management and pest control. The proposed system was implemented and evaluated for olive parcels located both at coastal and inland areas of the eastern part of Crete; these areas face severe issues with water availability and saltwater intrusion (coastal region). The system includes the monitoring of soil moisture and atmospheric sensors, with the aim of providing information to farmers for decision-making and at the future implementation of an automated irrigation system, optimizing the use of water resources. Data acquisition was performed through smart sensors connected to a microcontroller. Data were received at a portal and made available on the cloud, being monitored in real-time through an open-source IoT platform. An e-mail alert was sent to the farmers when soil moisture was lower than a threshold value specific to the soil type or when climatic conditions favored the development of the olive fruit fly. One of the main advantages of the proposed decision-making system is a low-cost IoT solution, as it is based on open-source software and the hardware on edge devices consists of widespread economic modules. The reliability of the IoT-based monitoring system has been tested and could be used as a support service tool offering an efficient irrigation and pest control service

A Review of HYDRUS 2D/3D Applications for Simulations of Water Dynamics, Root Uptake and Solute Transport in Tree Crops under Drip Irrigation

Orchards with tree crops are of critical importance to the global economy and to the environment due to their ability to be productive for many years without the need for replanting. They are also better adapted to extreme climatic conditions compared to other crops. However, new challenges are emerging as climate change threatens both tree production and water supply. Drip irrigation (surface and subsurface) is an irrigation method that has the potential to save water and nutrients by placing water directly into the root zone and minimizing evaporation. Many irrigation designs and strategies have been tested to best perform drip irrigation for any given soil, crop and/or climate conditions. The researchers’ need to find the optimal combination of irrigation management and design in the most economical and effortless way led to the use of comprehensive numerical models such as HYDRUS 2D/3D. HYDRUS 2D/3D is a widely used mathematical model for studying vadose zone flow and transport processes. A review of HYDRUS 2D/3D applications for simulations of water dynamics, root uptake and solute transport under drip irrigation in the four most common categories of tree crops (citrus, olive, avocado and deciduous fruit/nuts) is presented in this study. The review promotes a better understanding of the effect of different drip irrigation designs and treatments, as well as the reliability provided by HYDRUS 2D/3D in the evaluation of the above. This manuscript also indicates gaps and future challenges regarding the use of the model in simulations of drip irrigation in tree crops

Growth, photosynthesis and pollen performance in saline water treated olive plants under high temperature

© G.C. Koubouris et al., 2015. Olive cultivation in hot arid areas is hindered by the scarcity of irrigation water. The exploitation of saline water has been proposed as a solution to partially cover plant water demands. This paper presents the effects of salinity [0, 60 and 120 mM sodium chloride (NaCl)] on physiological and reproductive functions of cultivars Koroneiki and Amphissis in a closed hydroponic system. Shoot growth was markedly reduced in high salinity dose in Amphissis (−81%) and Koroneiki (−75%). The photosynthetic rate was significantly reduced at 120 mM NaCl for both cultivars, as well as chlorophyll and carotenoids content (43% and 44%, respectively). The Na+ content in all plant parts increased in both salinity doses especially in Amphissis while K concentration decreased for both cultivars. Inflorescences in Amphissis were severely damaged due to salinity. Consequently, pollen sampling and in vitro germination study was only feasible for Koroneiki. Indeed, Koroneiki pollen germination was reduced at 60 mM NaCl (−42%) and at 120 mM NaCl (−88%). Pollen tube length was also reduced by 15% and 28% for the middle and high salinity dose, respectively. The results of the present study indicate that Amphissis is more sensitive in high salinity doses compared to Koroneiki and that reproductive functions are severely affected by salinity

Growth, photosynthesis and pollen performance in saline water treated olive plants under high temperature

© G.C. Koubouris et al., 2015. Olive cultivation in hot arid areas is hindered by the scarcity of irrigation water. The exploitation of saline water has been proposed as a solution to partially cover plant water demands. This paper presents the effects of salinity [0, 60 and 120 mM sodium chloride (NaCl)] on physiological and reproductive functions of cultivars Koroneiki and Amphissis in a closed hydroponic system. Shoot growth was markedly reduced in high salinity dose in Amphissis (−81%) and Koroneiki (−75%). The photosynthetic rate was significantly reduced at 120 mM NaCl for both cultivars, as well as chlorophyll and carotenoids content (43% and 44%, respectively). The Na+ content in all plant parts increased in both salinity doses especially in Amphissis while K concentration decreased for both cultivars. Inflorescences in Amphissis were severely damaged due to salinity. Consequently, pollen sampling and in vitro germination study was only feasible for Koroneiki. Indeed, Koroneiki pollen germination was reduced at 60 mM NaCl (−42%) and at 120 mM NaCl (−88%). Pollen tube length was also reduced by 15% and 28% for the middle and high salinity dose, respectively. The results of the present study indicate that Amphissis is more sensitive in high salinity doses compared to Koroneiki and that reproductive functions are severely affected by salinity

GIS and Remote Sensing Aided Information for Soil Moisture Estimation: A Comparative Study of Interpolation Techniques

Soil moisture represents a vital component of the ecosystem, sustaining life-supporting activities at micro and mega scales. It is a highly required parameter that may vary significantly both spatially and temporally. Due to this fact, its estimation is challenging and often hard to obtain especially over large, heterogeneous surfaces. This study aimed at comparing the performance of four widely used interpolation methods in estimating soil moisture using GPS-aided information and remote sensing. The Distance Weighting (IDW), Spline, Ordinary Kriging models and Kriging with External Drift (KED) interpolation techniques were employed to estimate soil moisture using 82 soil moisture field-measured values. Of those measurements, data from 54 soil moisture locations were used for calibration and the remaining data for validation purposes. The study area selected was Varanasi City, India covering an area of 1535 km2. The soil moisture distribution results demonstrate the lowest RMSE (root mean square error, 8.69%) for KED, in comparison to the other approaches. For KED, the soil organic carbon information was incorporated as a secondary variable. The study results contribute towards efforts to overcome the issue of scarcity of soil moisture information at local and regional scales. It also provides an understandable method to generate and produce reliable spatial continuous datasets of this parameter, demonstrating the added value of geospatial analysis techniques for this purpose

Good Agricultural Practices Related to Water and Soil as a Means of Adaptation of Mediterranean Olive Growing to Extreme Climate-Water Conditions

Despite the fact that the olive tree is one of the best-adapted species in Mediterranean hydroclimate conditions, climate extremes impose negative effects on olive fruit set and development and subsequently on crop yield. Considering that the frequency of climate extremes is increasing in the last years due to climate change, Good Agricultural Practices (GAPs) have to be applied in order to mitigate their impact on olive trees. In this context, 18 experimental olive groves (irrigated and rainfed) were established, located on the island of Crete (south Greece). A set of 13 GAPs were applied in different combinations, mainly targeting to reduce water losses and erosion, alleviate heat stress and increase water use efficiency. Each experimental orchard was divided into two parts, the control (business-as-usual) and experimental (GAPs implementation). Four indicators were used for the assessment of GAPs performance, namely, Water Productivity (WP), Economic Water Productivity (EWP), Runoff (RF), and Yield (Y). WP and EWP were found to be up to 2.02 and 2.20 times higher, respectively, in the demonstration part of the orchards compared to the control, while Y was found to be up to 119% higher. RF was higher up to 190% in the control compared to the demonstration part of the experimental orchards. The above results clearly demonstrate that the implementation of the proposed GAPs can significantly support the adaptation of olive crops to extreme conditions

Coupling remote sensing with a water balance model for soybean yield predictions over large areas

Summarization: In this study a new method for predicting soybean yield over large spatial scales, overcoming the difficulties of scalability, is proposed. The method is based on the so-called “simplified triangle” remote sensing technique which is coupled with a crop prediction model of Doorenbos and Kassam 1979 (DK) and the climatological water balance model of Thornthwaite and Mather 1955 (ThM). In the method, surface soil water content (Mo), evapotranspiration (ET), and evaporative fraction (EF) are derived from satellite-derived surface radiant temperature (Ts) and normalized difference vegetation index (NDVI). Use of the proposed method is demonstrated in Brazil’s Paraná state for crop years 2002–03 to 2011–12. The soybean crop yield model of DK is evaluated using remotely estimated EF values obtained by a simplified triangle. Predicted crop yield by the satellite measurements and from archived Tropical Rainfall Measuring Mission data (TRMM) and European Centre for Medium-Range Weather Forecasts (ECMWF) data were in good agreement with the measured crop yield. A “d2” index (modified Willmott) between 0.8 and 0.98 and RMSE between 30.8 (kg/ha) to 57.2 (kg/ha) was reported. Crop yield predicted using EF from the triangle were statistically better than the DK and ThM using values of the equivalent of EF obtained from archived surface data when compared with the measured soybean crop data. The proposed method requires no ancillary meteorological or surface data apart from the two satellite images. This makes the technique easy to apply allowing providing spatiotemporal estimates of crop yield in large areas and at different spatial scales requiring little or no surface data.Παρουσιάστηκε στο: Earth Science Informatic

GIS and remote sensing aided information for soil moisture estimation: a comparative study of interpolation techniques

Summarization: Soil moisture represents a vital component of the ecosystem, sustaining life-supporting activities at micro and mega scales. It is a highly required parameter that may vary significantly both spatially and temporally. Due to this fact, its estimation is challenging and often hard to obtain especially over large, heterogeneous surfaces. This study aimed at comparing the performance of four widely used interpolation methods in estimating soil moisture using GPS-aided information and remote sensing. The DistanceWeighting (IDW), Spline, Ordinary Kriging models and Kriging with External Drift (KED) interpolation techniques were employed to estimate soil moisture using 82 soil moisture field-measured values. Of those measurements, data from 54 soil moisture locations were used for calibration and the remaining data for validation purposes. The study area selected was Varanasi City, India covering an area of 1535 km2. The soil moisture distribution results demonstrate the lowest RMSE (root mean square error, 8.69%) for KED, in comparison to the other approaches. For KED, the soil organic carbon information was incorporated as a secondary variable. The study results contribute towards efforts to overcome the issue of scarcity of soil moisture information at local and regional scales. It also provides an understandable method to generate and produce reliable spatial continuous datasets of this parameter, demonstrating the added value of geospatial analysis techniques for this purpose.Παρουσιάστηκε στο: Resource