Agro-hydrological modelling of regional irrigation water demand

The irrigation sector accounts for over 70% of the total freshwater consumption in the world. Therefore, e cient management of irrigation water is essential to ensure water, food, energy and environmental securities in a sustainable manner; these securities are grand challenges of the 21st century. The main objective of this research is to evaluate the simulation of irrigation water demand at the catchment scale in order to develop improved tools for conducting quantitative planning and climate change studies. Irrigation water demand is mostly driven by soil moisture. It is a state variable which is used to trigger the irrigation in hydrological models. In this study, a hydrolgical model (Soil and Water Assessment Tool, SWAT) is evaluated for reliably simulating the spatial and temporal patterns of soil moisture at a catchment scale. The SWAT simulated soil moisture was compared with the indirect estimates of soil moisture from Landsat and Time-domain re ectometry (TDR). The results showed that the SWAT simulated soil moisture was comparable with the soil moisture estimated from Landsat and TDR. Secondly, the applicability of the SWAT model was tested for simulating stream ow, evapotranspiration (ET) and irrigation water demand for four di erent agro-climatic zones (Mediterranean, Subtropical monsoon, Humid, and Tropical). Two di erent irrigation scheduling techniques were used to simulate irrigation namely, soil water de cit and plant water demand. It was seen from the results that the SWAT simulated irrigation amounts under soil moisture irrigation scheduling technique were close to the irrigation statistics provided by the state. However, the irrigation amounts simulated under the plant water demand irrigation scheduling technique were underestimated. Additionally, the two reanalysis data were also used to check the data uncertainty in simulating irrigation water demand. SWAT model code was modi ed by incorporating modi ed root density distribution function and dynamic stress factor. The modi ed model was used to simulate irrigation and crop yield. It was tested against the irrigation and crop yield simulated by Soil Water Atmosphere Plant (SWAP) model and eld data (Hamerstorf, Lower Saxony, Germany). It was then validated for di erent catchments (Germany, India and Vietnam). The results showed that the SWAT simulated irrigation water demand in case of plant water demand is comparable with the amount simulated by the model under soil water de cit irrigation scheduling technique. This dissertation not only bridges the gap between the scales of soil moisture determination but also establishes a close connection with the actual observations and modelled soil moisture and irrigation amounts at the eld, regional and global studies in agricultural water management. Additionally, the studies about simulating irrigation water requirement in data-scarce areas must address data uncertainty when using reanalysis data. It was found that rainfall is not always the dominant variable in irrigation simulation. Therefore, it is worth checking and bias correct the other climate variables

Irrigation water strategies for the Buriti Vermelho watershed: towards a higher water productivity.

RESUMO: Com a necessidade de se utilizar a água de forma cada vez mais eficientemente, faz necessário melhorar a produtividade de uso da água em escala de bacia hidrográfica. Este estudo objetivou avaliar a produtividade de uso da água e a possibilidade de aumentar a área irrigada na bacia hidrográfica do Buriti Vermelho, Brasil. o modelo de Solo-Água-Atmosfera-Planta (SWAP) foi utilizado nas simulações. A bacia do Buriti Vermelho possui agricultura de sequeiro (soja e milho), e irrigada (milho, feijão e trigo). A produtividade de uso da água (CWP) foi calculada em função da lâmina total de água aplicada, que inclui a soma da irrigação e da precipitação. Avaliou-se também o período ideal para o plantio da soja, buscando-se o rendimento ótimo e a maior CWP. A CWP variou de 0,32 kg m-3, para a cultura da soja, a 1,90 kg m-3 para o trigo. Para o período estudado houve uma redução da CWP com o aumento da lâmina de irrigação. A irrigação mostrou ter grande influência no rendimento das culturas do feijão, do trigo e do milho. O rendimento ótimo e a máxima produtividade de uso da água para a soja foram observados no mês de novembro. O cenário futuro mostrou que haverá decréscimo na CWP e que será necessário aplicar mais água para se conseguir as mesmas produtividades. ABSTRACT: As water is required to be used more efficiently, the crop water productivity should be improved. The main objective of this paper was to assess both the crop water productivity and the possibility to expand irrigated land in the Buriti Vermelho experimental watershed, Brazil. Soil-Water-Atmosphere-Plant (SWAP) model was used to perform the analysis. Buriti Vermelho contains both rain fed (soybean and corn) and irrigated (corn, common beans and wheat) crops. The crop water productivity was calculated as a function of total applied water, which includes the sum of irrigation and precipitation. An additional study was performed to verify the most ideal rainfed soybean growth period. The crop water productivity varied from 0.32 kg m-3 for soybeans to 1.90 kg m-3 for wheat. The crop water productivity decreased when the irrigation amount increased. Irrigation showed to have a big influence on the crop yield of common beans, wheat and rainfed corn, caused by a combination of low rainfall and low actual evapotranspiration values with higher irrigation requirements. The results showed November as being the most optimal growth period for soybeans. This month showed both the optimal yield as maximum crop water productivity. The future forecasts a decrease in crop water productivity, what means more water will be needed to reach the same amount of crop yield

SUNRISE: Drought monitoring in China - a brief review

Drought is one of the most complex and costly natural hazards. It develops slowly and can affect a large area meaning it can be difficult to pinpoint the start and/or the end of an event. Drought is primarily driven by a deficit in precipitation but an additional level of complexity is introduced when these deficits in precipitation propagate to other parts of the hydrological cycle such as soil moisture, river flows and groundwater levels over different time scales

Assessing long-term conservation of groundwater resources in the Ogallala Aquifer Region using hydro-agronomic modeling

2022 Spring.Includes bibliographical references.Groundwater is vital for domestic use, municipalities, agricultural irrigation, industrial processes, etc. Over the past century, excessive groundwater depletion has occurred globally and regionally, notably in arid and semi-arid regions, often due to providing irrigation water for crop cultivation. The High Plains Aquifer (HPA) is the largest freshwater aquifer in the United States and has experienced severe depletion in the past few decades due to excessive pumping for agricultural irrigation. There is a need to determine management strategies that conserve groundwater, thereby allowing irrigation for coming decades, while maintaining current levels of crop yield within the context of a changing climate. Numerical models can be useful tools in this effort. Hydrologic models can be used to assess current and future storage of groundwater and how this storage depends on system inputs and outputs, whereas agronomic models can be used to assess the impact of water availability on crop production. Linking these models to jointly assess groundwater storage and crop production can be helpful in exploring management practices that conserve groundwater and maintain crop yield under future possible climate conditions. The objectives of this dissertation are: i) to develop a linked modeling system between DSSAT, an agronomic model, and MODFLOW, a groundwater flow model to be used for evaluating long-term impacts of climate and management strategies on water use efficiency and farm profitability of agricultural systems while managing groundwater sustainably; ii) to use the DSSAT-MODFLOW modeling system in a global sensitivity analysis framework to determine the system factors (climate, soil, management, aquifer) that control crop yield and groundwater storage in a groundwater-stressed irrigated region, thereby pointing to possibilities of efficient management; and iii) to quantify the effect of groundwater conservation strategies and climate on crop yield and groundwater storage to identify irrigation and planting practices that will maintain adequate crop yield while minimizing groundwater depletion. These three objectives are applied to the hydro-agronomic system of Finney County, Kansas, which lies within the HPA. Major findings include: 1) climate-related parameters significantly affect crop yields, especially for maize and sorghum, and soybean and winter wheat yields are sensitive to a combination of cultivar genetic parameters, soil-related parameters, and climate-related parameters; 2) Climatic parameters account for 44%, 29%, 40%, and 36% variation in yield of maize, soybean, winter wheat, and sorghum; 3) Hydrogeologic parameters (aquifer hydraulic conductivity, aquifer specific yield, and riverbed conductance) have a relatively low influence on crop yields; 4) water table elevation, recharge, and irrigation pumping are considerably sensitive to soil- and climate-related parameters, while ET, river leakage, and groundwater/aquifer discharge are highly influenced by hydrogeological parameters (e.g., riverbed conductance, and specific yield); 5) the best management practice is the combination of implementing drip irrigation and planting quarter plots under both dry and wet future climate conditions. Other irrigation systems (sprinkler) and planting decisions (half-plots) can also be implemented without severe groundwater depletion. If crop yield is to be maintained in this region of the HPA, groundwater depletion can be minimized but not completely prevented. Results highlight the need for implementing new irrigation technologies, and likely changing crop type decisions (e.g., limiting corn cultivation) in coming decades in this region of the HPA. Results from this dissertation can be used in other groundwater-irrigated regions facing depletion of groundwater

Spatial crop-water variations in rainfed wheat systems: From simulation modelling to site-specific management

In sloping fields, rainfed crops experience different degrees of water stress caused by spatial variations in water and, consequently, yields also vary spatially within a field. This offers opportunities for precision agriculture through site-specific management. However, while significant advances have been accomplished in the engineering aspects of precision agriculture, such as increasing spatial resolution of data systems and automation, much less effort has been dedicated to the simulation of within field crop responses to spatial variations. Most studies on rainfed yield gaps ignore intra-plot variability, but if crop models are to be used in assisting site-specific management, they may greatly benefit from spatial water modelling approaches capable of accurately representing and simulating within-field variation of water-related processes. This doctoral thesis represents a novel contribution to the agronomy of rainfed agricultural systems, evaluating the role played by water flows in areas of undulating topography in determining the spatial variations of wheat yield. The thesis has been carried out in chapters that are associated by following an integrative approach. The thesis first reviewed some of the most widely adopted crop and hydrologic models and explored new opportunities for simulating spatial water variations at crop field level through the incorporation of lateral inflow at lower elevation zones of the field. From this standpoint, the spatial variations of yield gaps in rainfed wheat, caused by lateral flows from high to low areas, were assessed in Córdoba, Spain. From an agronomic perspective, water lateral inflows (LIF) due to surface and subsurface runoff contribute to yield variations in rainfed wheat production systems such as the one studied here. The net contribution of these flows to spatial variations of rainfed potential yields showed to be relevant but highly irregular among years. Despite the inter-annual variability, typical of Mediterranean conditions, the occurrence of LIF caused simulated wheat yields to vary +16% from up to downslope areas of the field. Average crop yield ranged from 1.3 to 5.4 Mg grain yield (GY) ha−1. The net yield responses to LIF, in downslope areas were on average 383 kg grain yield (GY) ha−1, and the LIF marginal water productivity reached 24.6 (±13.2) kg GY ha−1 mm−1 in years of maximum responsiveness. Such years of maximum responsiveness were associated with low rainfall during the vegetative stages of the crop in combination with LIF occurring at post-flowering stages. However, under field conditions, these differences were only visible in one of the two experimental years. The economic implications associated with multiple scenarios of variable application rate of nitrogen were explored through a case study and several recommendations were proposed. Both farm size (i.e., annual sown area) and topographic structure impacted the dynamics of investment returns. Under current policy-prices conditions, the adoption of variable application rate would have an economic advantage in farms similar to that of the case study with an annual sown area greater than 567 ha year−1. Nevertheless, current trends on energy prices, transportation costs and impacts on both cereal prices and fertilizers costs enhance the viability of variable application rate adoption for a wider population of farm types. The profitability of adopting VAR improves under such scenarios and, in the absence of additional policy support, the minimum area for adoption of variable application rate decreases to a farm size range of 68-177 ha year−1. The combination of price increases with the introduction of an additional subsidy on crop area could substantially lower the adoption threshold down to 46 ha year−1, turning this technology economically viable for a much wider population of farmers.En campos en pendiente, los cultivos de secano experimentan diferentes grados de estrés hídrico causados por variaciones espaciales de la humedad en el suelo, y los rendimientos varían espacialmente dentro del mismo campo. Esta variabilidad supone una oportunidad para la agricultura de precisión a través del manejo espacialmente variable. Sin embargo, si bien se han logrado avances significativos en los aspectos de la ingeniería de la variación espacial, como el aumento de la resolución espacial de los sistemas de datos y la automatización, se ha avanzado mucho menos en relación a la simulación de las respuestas de los cultivos a las variaciones espaciales de la humedad y los flujos hídricos. La mayoría de los estudios sobre las brechas de rendimiento de secano ignoran la variabilidad dentro de la parcela. Sin embargo, el uso de modelos de simulación de cultivos como medida de apoyo a los sistemas de gestión espacialmente variable, requiere que los enfoques de modelación espacial del agua sean capaces de representar y simular con precisión la variación dentro del campo de los factores relacionados con el agua disponible y la respuesta de los cultivos. Esta tesis doctoral representa una nueva contribución a la agronomía de los sistemas agrícolas de secano, con énfasis en el papel que juegan los flujos de agua en zonas de topografía ondulada en la determinación de las variaciones espaciales del rendimiento del trigo. La tesis se ha desarrollado en capítulos que se complementan siguiendo un enfoque integrador. La presente tesis doctoral revisó algunos de los modelos hidrológicos y de cultivo más ampliamente adoptados y exploró nuevas oportunidades para simular variaciones espaciales del agua a nivel de campo mediante la incorporación del flujo lateral de escorrentía superficial y sub-superficial en las zonas de menor elevación del campo. Desde este punto de vista, se evaluaron las variaciones espaciales de las brechas de rendimiento en trigo de secano, en Córdoba, España, que son causadas por flujos laterales de los puntos altos a los bajos. Desde una perspectiva agronómica, las entradas laterales del agua contribuyen a las variaciones de rendimiento en los sistemas de producción de trigo de secano como el que se ha estudiado en el ámbito de esta tesis. La contribución neta de estos flujos a las variaciones espaciales de los rendimientos potenciales de secano se mostró relevante pero altamente irregular entre diferentes años. A pesar de la variabilidad interanual, típica de las condiciones mediterráneas, la existencia de dichos flujos hizo que los rendimientos de trigo simulados variaran un +16% desde las áreas más elevadas de un campo hacia abajo. El rendimiento medio observado osciló entre 1.3 y 5.4 Mg de rendimiento de grano (GY) ha−1. Las respuestas de rendimiento neto al flujo lateral, cuenca abajo, fueron en promedio 383 kg de rendimiento de grano (GY) ha−1, y la productividad marginal de agua de LIF alcanzó 24.6 (±13.2) kg GY ha−1 mm−1 en años de máxima capacidad de respuesta. Dichos años de máxima capacidad de respuesta se asociaron con bajas precipitaciones durante las etapas vegetativas del cultivo en combinación con flujos laterales en las etapas posteriores a la floración. En condiciones de campo, estas diferencias solo fueron visibles en uno de los dos años experimentales. Las implicaciones económicas asociadas con múltiples escenarios de tasa de aplicación variable de nitrógeno se exploraron a través de un caso de estudio y se propusieron varias recomendaciones. Tanto el tamaño de la finca (el área sembrada anual) como la estructura topográfica afectaron la dinámica de los rendimientos de la inversión. Bajo las condiciones actuales de política agrícola, y de precios, la adopción de la tasa de aplicación variable tendría una ventaja económica en fincas similares a la del caso de estudio con un área sembrada anual superior a 567 ha año−1. Sin embargo, las tendencias actuales en los precios de la energía, los costes de transporte y los impactos tanto en los precios de los cereales como en los costes de los fertilizantes mejoran la viabilidad de la adopción de esta tecnología para una población más amplia de tipos de fincas. La rentabilidad de la adopción de aplicación variable de nitrógeno mejora bajo dichos escenarios y, en ausencia de apoyos adicionales, el área mínima para la adopción de aplicación variable disminuye hasta un rango de 68-177 ha año−1 de área de siembra. La combinación de aumentos de precios con la introducción de un subsidio adicional asociado al área de cultivo podría reducir sustancialmente el umbral de adopción hasta 46 ha año−1, lo que hace que la tecnología sea económicamente viable para una población mucho más amplia de agricultores

Integrated Model Development for the Assessment of Food Security in China Related to Climate Change and Adaptation

This thesis developed a practical methodological framework, which integrated the bio-physical and socio-economic processes within the food system across different scales. The framework provides a useful tool for the assessment of food security and possible adaptation related to climate change. It was applied in China, a country with rapid economic growth and a large population, in order to evaluate multiple dimensions of food security related to climate change and socio-economic development in the future. In the framework, an improved bio-physical crop model was coupled with an improved food economic model by scaling up from the farm level to the national level. The bio-physical crop model was developed from the site-based Decision Support System for Agrotechnology Transfer (DSSAT) model in order to investigate the impacts of climate change on physical production of a crop only related to environmental factors. The food economic model was developed from a partial equilibrium economic model, China's Agricultural Policy Simulation Model (CAPSiM). This was done in order to simulate the response of a socio-economic system to the negative consequences on a food economic system from the bio-physical change in crop production due to climate change. Case studies of China and the Jilin province were investigated by applying the framework. The impacts of climate change on yield and phenology of maize under multiple greenhouse gas emission scenarios were studied at provincial and national levels in three time periods, 2020s, 2050s, 2070s, using the improved bio-physical crop model. In general, maize yield reduction due to climate change ranges from -3% in 2020 to -14% in 2070. The worst yield is -20.5% in 2070 produced under the A1FI scenario. Food security for China until 2050 was projected under multiple climate change and socio-economic scenarios by using the food economic model, and analyzed with respect to food availability, food price and the system resilience to sudden disasters. Modelled climate change impacts on food availability in this study are minimal, producing only a 23 Mt (~8%) gap between supply and demand for maize by 2050. The socio-economic system will compensate for the impacts of climate change on the self-sufficiency of grains by about 8% of total production for the whole country. The impacts on single grain would cause the prices of other grains to rise in future. The effectiveness of potential adaptation measures was assessed quantitatively at both farm and national levels. Uncertainties among different scenarios are discussed for China and the Jilin province

Water Management for Sustainable Food Production

The agricultural community is face with the challenge of increasing food production by more than 70% to meet demand from the global population increase by the mid-21st century. Sustainable food production involves the sustained availability of resources, such as water and energy, to agriculture. The key challenges to sustainable food production are population increase, increasing demands for food, climate change, climate variability, and decreasing per capita land and water resources. To discuss more details on (a) the challenges for sustainable food production and (b) mitigation options available, a Special Issue on “Water Management for Sustainable Food Production” was assembled. This Special Issue focused on issues such as irrigation using brackish water, virtual water trade, allocation of water resources, consequences of excess precipitation on crop yields, strategies to increase water productivity, rainwater harvesting, irrigation water management, deficit irrigation, fertilization, environmental and socio-economic impacts, and irrigation water quality. The articles in the Special Issue cover several water-related issues across the U.S., Asia, Middle East, Africa, and Pakistan concerning sustainable food production. The articles in this Special Issue highlight the substantial impacts on agricultural production, water availability, and water quality in the face of increasing demands for food and energy